{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"longbench-v2","formal_name":"LongBench v2","introduction":"長い資料の深い理解と推論を、多肢選択問題で評価するベンチマークです。公式紹介では503問を収録し、単一・複数文書の質問応答やコードリポジトリ理解などを扱います。\n\nLongBench v2 evaluates deep understanding and reasoning over long contexts through multiple-choice questions. Its official description lists 503 questions spanning tasks such as single-document and multi-document QA and code-repository understanding.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://huggingface.co/datasets/zai-org/LongBench-v2","indexing_mode":"noindex"},"task_id":"130e3d2e-8395-531d-96a1-92f50c50acbc","task_key":"train--66f3e58c821e116aacb2fabc","task_revision_id":"1","upstream_id":"66f3e58c821e116aacb2fabc","short_description":"Which of the following statements below are false according to the three…","config":"","split":"train","body":"{\"choice_A\":\"(1)(3)(5)\",\"choice_B\":\"(2)(4)(5)\",\"choice_C\":\"(2)(3)(5)\",\"choice_D\":\"(1)(3)(4)\",\"context\":\"Government policy: meaning, types, manifestations, theories, and policy cycles\\nArticle  in  Insights into Regional Development · June 2023\\nDOI: 10.9770/IRD.2023.5.2(6)\\nCITATIONS\\n6\\nREADS\\n10,345\\n4 authors, including:\\nAdetayo Olaniyi Adeniran\\nFederal University of Technology, Akure\\n98 PUBLICATIONS   580 CITATIONS   \\nSEE PROFILE\\nAdedayo Adeniran\\nUniversity of Ibadan\\n7 PUBLICATIONS   27 CITATIONS   \\nSEE PROFILE\\n \\n \\nINSIGHTS INTO REGIONAL DEVELOPMENT \\nISSN 2669-0195(online) https://jssidoi.org/ird/ \\n \\n \\n \\n2023 Volume 5 Number 2 (June) \\n \\n \\nhttp://doi.org/10.9770/IRD.2023.5.2(6) \\n \\n         \\n       \\n            \\n \\n            Publisher \\n    http://jssidoi.org/esc/home \\n \\n \\n \\n \\n  \\n \\n83 \\n \\nGOVERNMENT POLICY: MEANING, TYPES, MANIFESTATIONS, THEORIES, AND POLICY \\nCYCLES \\n \\nAdetayo Olaniyi Adeniran 1, Joseph Mosunmola Muraina 2, Joseph Olanrewaju Ilugbami 3, \\nAdedayo Ayomide Adeniran 4  \\n \\n1Department of Logistics and Transport Technology, Federal University of Technology Akure, Nigeria \\n2Department of Geography and Planning Science, Ekiti State University, Ekiti, Nigeria \\n3Rufus Giwa Polytechnic-Owo Rector Office, Ondo State, Nigeria \\n4Department of Geography and Planning, University of Ibadan, Nigeria \\n \\nE-mails:adeniranao@futa.edu.ng1; jmosun07@gmail.com2; ilugbamijoseph@gmail.com3; ddone2@gmail.com4 \\n \\nReceived 10 March 2023; accepted 10 June 2023; published 30 June 2023 \\n \\n \\nAbstract. In any democracy, it is strongly advised that effective policies be created since they are crucial to how democracies operate. \\nGovernment policy definitions and categories were widened. Government policy types were discussed concerning the sectoral groups \\ncomprising each given government. This is important because a policy’s or its objective elements frequently suggest different meanings for \\ndifferent stakeholders. Policymaking is a process impacted by socio-political and other factors and is not a governmental function. Thus, \\nthere is a need to comprehend the theoretical underpinnings on which government policymaking and its execution may be evaluated and \\ncharacterized. According to the elite/mass hypothesis, there are two groups in society: those who occupy positions of power and those who \\ndo not. Government policy is more influenced by those with access to knowledge and influence. It is a remarkable characteristic of group \\ntheory which is ideally in line with the legislative because the legislatures are where the voices of the people are expressed. Governmental \\ninstitutions and government policy are closely related, claims institutional theory. The rational choice theory may need to be more accurate \\nsince participants in government policy must have access to all information to make informed judgments. The systems theory offers a more \\nstraightforward method for categorizing and comprehending the contributions and interrelationships made by institutions and policy \\nplayers, including the function played by the external environment in policy formulation. Lastly, since democracy is a system of \\ngovernance built on extensive public engagement, any ideology that supports any type of citizen participation (particularly in a democracy) \\nshould be endorsed by both politicians and public officeholders. \\n \\nKeywords: Government policy; Policy manifestations; Policy execution; Policy underpinnings; Policy context and consequences \\n \\nReference to this paper should be made as follows: Adeniran, A.O., Muraina, J.M., Ilugbami, J.O., Adeniran, A.A. (2023). Government \\npolicy: meaning, types, manifestations, theories, and policy cycles. Insights into Regional Development, 5(2), 83-99. \\nhttp://doi.org/10.9770/IRD.2023.5.2(6) \\n \\nJEL Classifications: J58, J68, J78  \\n \\nAdditional discipline: Government policy \\n \\n \\n \\n \\n \\n \\n \\n\\n\\n \\nINSIGHTS INTO REGIONAL DEVELOPMENT \\nISSN 2669-0195 (online) https://jssidoi.org/ird/ \\n2023 Volume 5 Number 2 (June) \\n \\n \\nhttp://doi.org/10.9770/IRD.2023.5.2(6) \\n \\n84 \\n \\n1. Introduction \\n \\nEach democracy needs sound policies. Additionally, in a democracy, the proper application of those policies is \\ncrucial. According to Delamaza (2015), democracy is a kind of government. Under a democratic political \\nadministration, among the issues facing governance is erecting a foundation that enhances the practice of \\ndemocracy without undermining the freedom to embark on purpose and functions and to ensure that social \\ndemands and conflicts arising from various interest groups and civil societies are tackled is one of their tasks \\n(Dunne, 2021; Forcher-Mayr and Mahlknecht, 2020). \\n \\nGiven that both government policies and how they are carried out may strengthen a democracy, there is a need to \\ndefine government policy more broadly and the ingredients of government policy execution (GPE) (Adeniran, \\n2016; Delamaza and Palma, 2022; Matuku-Mphahlele and Zandamela, 2022). These terminologies are essential \\ndue to the elements involved in the execution of government policy. Hence, the word government policy \\nexecution is a subset of the primary term government policy. Government policy may be described as a cycle or \\nprocess with several steps to be taken before achieving a policy’s goals. Typically, there are four or five stages:  \\na) Stage for issue/ problem identification; \\nb) Stage for setting agenda; \\nc) Stage for policy formulation or policymaking; \\nd) Stage for policy execution; and  \\ne) Stage for policy evaluation. \\n \\nPolicy phases will be significantly influenced by the particular technique employed (Zeb-un et al., 2021). \\nGovernment policy is, first and foremost, a persuasive art, as Deygers and Vanbuel (2022) claimed. It is so named \\nbecause it calls for the selection, enactment of legislation, and consultation of all relevant parties (Kofele-Kale, \\n2006; Nunes et al., 2019). According to Oyadiran and Akintola (2014), one objective of government policy is to \\nguarantee that persons responsible for carrying out significant decisions in society, regardless of their position, are \\nwell-trained. This opinion was also agreed upon by Myrczik et al. (2022), De-Marchi, Lucertini and Tsoukiàs \\n(2014), and Ozturk (2015). \\n \\nAccording to Galli (2015), government policy should be viewed as both a declaration of goals and a negotiated \\noutcome resulting from the execution process. One of government policy’s most distinguishing features is how \\nunstable and changeable it is (Deygers and Vanbuel, 2022). The assertion that proposed or envisioned government \\npolicies lacks any evident beginning or end is maintained in the study of Ashmore et al. (2020), which noted that \\nthey should be understood as analogous to seashells or jelly. It flows almost circularly at times. Myrczik et al. \\n(2022) assert that when the policy is discussed, it implies addressing pertinent issues germane to human existence. \\n \\nFalk and Tally (2016) identified the features of government policy, such as the intended direction that the \\nlegislator would want to guide the public, including the description of how the country’s resources are to be used \\n(Díaz-Llamas et al., 2023). It was also revealed by Oyadiran and Akintola (2014) that several variables might \\ninfluence the overall government policy process. These include the legislators in charge, noting what the \\nConstitution stands for. The issues that need to be resolved should be known to politicians or bureaucrats Koelble \\nand Siddle (2014). \\n \\nAlso, a significant portion of those involved in the government policy process are local (government excluded). \\nConsequently, it is crucial to get in touch with these influential individuals who know the community's situation, \\ntheir challenges, and the issues that need to be fixed. The act of fashioning, enacting, monitoring, reviewing, or \\nrevising government policies is covered by Imenda (2014). Nokele (2022) argues that because it is crucial to the \\nefficacy and reach of government policies, its execution should be the primary emphasis of the whole process. \\n \\n\\n\\n \\nINSIGHTS INTO REGIONAL DEVELOPMENT \\nISSN 2669-0195 (online) https://jssidoi.org/ird/ \\n2023 Volume 5 Number 2 (June) \\n \\n \\nhttp://doi.org/10.9770/IRD.2023.5.2(6) \\n \\n85 \\n \\nMacheridis and Paulsson (2019) noted that government policies are centred on presumptions about what \\ngovernments can do and what the effects of those actions would be since they would otherwise be the product of \\npolitical activity and would, as a result, have political ramifications (Mellaard and van Meijl, 2017). Maggetti and \\nGilardi (2016) assert that it is uncommon to get a thorough explanation of the assumptions underlying \\ngovernment policy as a theory or model, much alone the context in which those assumptions must be employed or \\nunderstood. But, as with every procedure, an idea or model is always presupposed (McCann and Ward, 2013). \\n \\nEvery story has two sides, and the government policy level confirms this truism. Government policy is two-\\ndimensional or contains two storylines; given that politics and administration are a component of it, it has a two-\\ndimensional structure. Creese, Dutton and Esteve-Gonzalez (2021) refer to this reality as the more significant \\nnumber of pertinent legislative and administrative operations. Knill and Tosum’s viewpoints on government \\npolicy may be contrasted to show how interdependent politics and the administrative side are. Government policy \\nand politics should adhere to the same course (Molossi et al., 2023). \\n \\nThe role that legislators play in deciding the resource utilization of a country in the government mentioned above \\npolicy is regarded as the political side of the government policy process (Gray, 2018). On the other hand, the \\nadministrative side of the government policy process focuses on the executive and their actions to realize the \\nstated objectives established by the government (Mellaard and van Meijl, 2017). The administrative side of the \\npublic process is responsible for ensuring that the adopted policy will persist throughout time, according to \\nDeygers and Vanbuel (2022). Policymakers, administrators, and bureaucrats should encourage all significant \\nstakeholders of the necessity of a specific policy and the reasons for that requirement for that execution to take \\nplace (Purtle et al., 2023; Mellaard and van Meijl, 2017). \\n \\n2. Literature Review \\n \\n2.1. Manifestations of Government Policy \\nEveryday life is a manifestation of government policy. Also, it starts in casual conversations when regular people \\ntalk about things like how to improve government policy. As stated in the introduction chapter, creating \\ngovernment policies is a complex, multi-layered process (Mellaard and van Meijl, 2017). For the creation and \\nexecution of government policy, two guiding concepts (or significant areas of study) are essential. Public \\nadministration and political sciences/studies fall under this category. According to Andrews-Speed (2021), \\ngovernment policy encompasses several political science subfields. Implementing government policies, which \\ncome from the political (or policymaking) facets of government and are backed and endorsed by political \\nadministrators, is the priority over public administration’s primary goal (Uddin et al., 2023). \\n \\nWilson’s dualism (quoted by Guidi et al., 2020) contends that politics and administration cannot be divided into \\ndistinct roles when determining government policy from both the structural and functional perspectives. There, \\nthe line thins out to the consistency of a spider’s web thread. According to Simeon (1976), institutions and \\npractices that are exposed in and through economic, social, and political dynamics shape government policy. \\nGovernment policy can also result from issue articulation (acknowledging a policy challenge), finding \\nalternatives, and the political processes (Crabolu, Font and Eker, 2023).  \\n \\nAccording to Bertram (2020) the focus of political studies on government policy has been around for a while. \\nMellaard and van Meijl (2017) contend that the academic study of the government policy process is a part of \\npolitical studies/sciences since politics deals with who gets what, when, and how. Political science may be \\nnecessary to government policy issues while maintaining its dedication to scientific investigation (Mellaard and \\nvan Meijl, 2017; Deygers and Vanbuel, 2022; Fischer et al., 2015). Politicians, pressure organizations, and \\n‘passive beneficiaries of policy’ are only a few stakeholders engaged in the government policy process (Jiang, \\n2018). \\n\\n\\n \\nINSIGHTS INTO REGIONAL DEVELOPMENT \\nISSN 2669-0195 (online) https://jssidoi.org/ird/ \\n2023 Volume 5 Number 2 (June) \\n \\n \\nhttp://doi.org/10.9770/IRD.2023.5.2(6) \\n \\n86 \\n \\n \\n2.2. Underpinnings of Government Policy \\nGovernment policy is often regarded as being first and primarily a course of action (Makhetha, 2015). This course \\nof action must demonstrate logical decision-making, as doing so will lead to responsible behaviour (Daniell, \\n2014). Wu (2022) define government policy as the process or series of actions taken by the government to solve a \\nparticular societal issue that was originally recognized. According to Guidi et al. (2020), the people whose lives \\nwill eventually be impacted by the outcomes of policy action are represented in the specialized policy subsystems \\nwhere government policy is developed, implemented, and evaluated.  \\n \\nAccording to Paulsson and Macheridis (2022), who also concurs with Makhetha (2015) and Wu (2022), \\ngovernment policies are the result of a combination of systematic forces, political processes, institutional \\ninfluences, rivalry among groups, elite preferences, belief in or advocacy of change through small steps, and \\nrational planning (Fischer et al., 2015; Deygers and Vanbuel, 2022). Whatever decisions the government agrees \\non will fall under this (Kharel and Kharel, 2020; Jakonen and Sokka, 2022). Simeon (1976) concluded that \\npolicies are the climax of a complicated negotiation process and the outcome of several modest judgments made \\nby decision-makers. Yet, Simeon (1976) maintains that ideology is at play both in the formulation of policies and \\nduring the policymaking process, suggesting that government policies indeed reflect ideology (or have a symbolic \\nrepertoire; Steven, 2021; Molossi et al., 2023). \\n \\nThe socioeconomic circumstances present in a particular geographic area that the government policy must address \\nimpact how the framework of government policies is developed claims Kharel and Kharel (2020). However, \\nseveral factors, such as institutional frameworks, a country’s party system, or the overall relationship between the \\ngovernment and the populace, can affect the process of formulating government policy (Díaz-Llamas et al., 2023). \\nGovernment policy also incorporates a society's dominant ideas, dogmas, and beliefs (Simeon, 1976). Because of \\nthis, these components offer a framework for the underlying assumptions and arrangements that permit the \\nexamination of policies (Simeon, 1976). \\n \\nRecognizing social issues and how societies choose to handle and solve them are essential elements of \\ngovernment policy, according to Parsons (2002) and Steinert (2016). Government facilitates reducing or removing \\nthese issues that society has identified (Parsons, 2002; Crabolu, Font and Eker, 2023). Guidi et al. (2020) assert \\nthat two features or functions, namely structural terms and/or functional words, can be used to conceptualize \\ngovernment policy. The structural component of government policy includes the interactions that may occur \\nbetween the governments' policy players in the setting of the several specialized areas of the subject (Guidi et al., \\n2020). The many policy types considerably influence how government policy is framed (Crabolu, Font and Eker, \\n2023).  \\n \\n2.3. Types of Government Policy \\nGovernment policies can be created in several styles and/or types to address the need on the policy agenda. Lowi \\nrefers to this classification of policies as a policy categorization (1972). As a specific policy type would be \\nassociated with a variety of politics, categorizing policies is essential for studying politics (Oyadiran and \\nAkintola, 2014; Aritz et al., 2017). Hence, a politically appropriate policy classification has been developed \\n(Oyadiran and Akintola, 2014). The classification of policies must, however, be founded on intellectual and \\ntheoretical considerations that have an influence on actual political situations (Oyadiran and Akintola, 2014). The \\npolicy categorization aims to ensure that it supports the study of politics while avoiding omitting the public \\nadministration component or having a detrimental impact on the political environment as a whole (Oyadiran and \\nAkintola, 2014). \\n \\nThe aim of government policy classifications or taxonomies5, according to Bertram, Maleki and  Karsten (2019), \\nis to comprehend the basic contrasts between policies and the political settings that influence the various types of \\n\\n\\n \\nINSIGHTS INTO REGIONAL DEVELOPMENT \\nISSN 2669-0195 (online) https://jssidoi.org/ird/ \\n2023 Volume 5 Number 2 (June) \\n \\n \\nhttp://doi.org/10.9770/IRD.2023.5.2(6) \\n \\n87 \\n \\npolicies in place. It is simpler to express the typifications that role-players typically utilize to characterize \\ngovernment policies when approaches are categorized, according to Aritz et al. (2017). This suggests that using \\npolicy taxonomies makes it possible to accurately describe government policies (Aritz et al., 2017). Sol (2023) \\nclaims that employing policy taxonomies may assist in determining the scope and presentation of a policy. \\n \\nAccording to Simeon (1976), policy taxonomies offer the chance to consider the amount of coercion and the \\nequilibrium between individual and collective activities leisurely. Simeon (1976) thinks Lowi’s (1972) proposed \\npolicy taxonomies are essential and fundamental for political science students. According to Munzhedzi (2020), \\nthere are four types of government policies, or policy taxonomies: distributive, redistributive, regulatory, and \\ncomponent government policies. Some taxonomies or classifications are considered to be governmental functions. \\nAccording to Nico (2015), these policy categories may be used to pinpoint the specific effects of a policy, which \\nmight promote political discourse about how decisions are made and how to execute policies. \\n \\nAlso, the sectoral categories or clusters should serve as the foundation for policy classifications (Ahmad et al., \\n2021). The terms types and categories of policies were used interchangeably throughout the study. For instance, \\nthere may be a collection of regulatory or protective policies. \\n  \\n2.3.1. Distributive government policy \\nGuidi Guardiancich and Levi-Faur (2020) claim that the primary objective of distributive policies is issue-solving; \\nas a result, they typically function in the most supportive political climate. The strong clientele, knowledge, \\nleadership, and coherence characterize the context in which distributive policies are carried out (Rakšnys and \\nValickas, 2023). It involves acting to address issues facing the general population (Rakšnys and Valickas, 2023). \\nSignificantly, distributive policies may also be described as dealing with how additional resources, expenses, and \\nadvantages from the government are distributed to specific population demography (Díaz-Llamas et al., 2023). \\nBertram, Maleki and Karsten (2019) revealed that distributive strategies address Lasswell’s (1936) maxim of who \\nreceives what, when, and how. \\n \\nAccording to Bertram, Maleki and Karsten (2019), distributive policies use general public funds (instead of user \\nfees) to help a particular segment of a social group without considering resource limitations or financial \\nconstraints (Rakšnys and Valickas, 2023; Díaz-Llamas et al., 2023). As shown in election manifestos, when \\ndifferent political parties seek voters to approve of the resources and services they can deliver to them if they are \\nelected to power (or held in power), the constituencies of elected politicians also benefit from distributive policies \\n(Kraft and Furlong, 2013). \\n \\n2.3.2. Redistributive government policy \\nAllocative government policies, sometimes referred to as redistributive government policies, deal with necessities \\nlike the funding of the welfare system, health care system, and education system (Ahmad et al., 2021). Guidi \\nGuardiancich and Levi-Faur (2020) claim that redistributive policies occur when the government levies taxes on \\none group of people to benefit another. These resources are distributed between the wealthy and the socially \\ndisadvantageous and destitute groups (Díaz-Llamas et al., 2023). A redistributive strategy can be implemented \\ndespite ideological cleavages, following Guidi et al. (2020). \\n \\nConcerning the aforementioned, Guidi Guardiancich and Levi-Faur (2020) assert that direct taxation and the \\ntransfer of resources from one socioeconomic group to another lead to the emergence of a distinctive \\ncharacteristic that distinguishes distributive and redistributive policies from one another. A dispute is this trait \\n(Jutta, 2016). Redistributive policies are exceedingly political, difficult, unfavourable, and polarizing to design \\nand implement, which causes this conflict. They cause disputes that polarize the population along party lines \\n(Rakšnys and Valickas, 2023). Redistributive programs face this challenge since one group gains at the expense \\nof another (Yanow, 2015). The discussion around distributive government policies is heightened because they \\n\\n\\n \\nINSIGHTS INTO REGIONAL DEVELOPMENT \\nISSN 2669-0195 (online) https://jssidoi.org/ird/ \\n2023 Volume 5 Number 2 (June) \\n \\n \\nhttp://doi.org/10.9770/IRD.2023.5.2(6) \\n \\n88 \\n \\nexplicitly allude to an ideology or a class war. According to Donnelly (2015), the disadvantage of redistributive \\npolicy is that the government typically lacks the means to implement such a program. \\n \\n2.3.3. Regulatory government policy \\nRegulatory policies, according to Munzhedzi (2020), typically address the need for policies relating to \\ntransportation, infrastructure, health, and other regulations and standards, or they prohibit people from acting in \\ncertain ways, such as selling illegal goods like dangerous drugs, participating in unfair competition in the market \\n(Rakšnys and Valickas, 2023). According to Anyebe (2018), regulatory policies are laws carried out by \\ngovernment agencies without any interference or money inducement. \\n \\nA regulation policy can be a form of competitive regulation to regulate individual industries and their activities. It \\ncan also be a protective regulation meant to protect the general public. Bertram, Maleki and Karsten (2019) \\ncontend that regulatory approaches are questionable because they let the government meddle in private enterprises \\nand people’s daily lives. Another disadvantage of regulatory government policies, according to Creese, Dutton \\nand Esteve-Gonzalez (2021), is that they significantly impact how much money is spent and how much assistance \\nfrom other social actors is needed. \\n \\n2.4. Constitution government policy \\nOyadiran and Akintola (2014) developed the component policy as a subset of constituent policy. Both the \\ngovernment and/or the nation as a whole are considered to be two constituents of government policy, according to \\nOyadiran and Akintola (2014) and Guidi Guardiancich and Levi-Faur (2020). According to Meier’s additional \\ndefinition from 2007, constituent policies aim to advance the interests of the nation-state and the broader public. \\nConstituency policies are portrayed by Guidi Guardiancich and Levi-Faur (2020) as being exceedingly detailed, \\nmeticulous, and in charge of significant initiatives. Meier’s (2000) notion of component policies may be used to \\ndepict the presidential department where policies are executed, monitored, and coordinated. Constituent policies \\nalso cover governmental operations, including defence and foreign policy (Rakšnys and Valickas, 2023). \\n \\nThe present democratic society can be classified under constituent policies because of their method of operation \\nand provision for election laws (Yanow, 2015). According to Creese, Dutton and Esteve-Gonzalez (2021), there is \\na fact that constituent government policies only have an impact on the executive branch of government. As was \\nsaid above, Oyadiran and Akintola (2014) identified the many kinds of government policies and found just four \\npolicy taxonomies. Not all government policies will fall within Lowi’s (1972) taxonomy of approaches, as \\n(Rakšnys and Valickas, 2023) indicates. These policy taxonomies thus have the disadvantage of excluding \\nalternative policies that might not fit the policy classification. A few new categories of approaches have been \\nincluded in the classification of procedures since Lowi’s (1972) policy taxonomies were first introduced. \\n \\nThe following section briefly discusses one more policy type that is mainly referred to as substantive government \\npolicy. \\n \\n2.5. Substantive government policy \\nGovernment policies are crucial in a wide range of substantive sectors, according to Paulsson and Macheridis \\n(2022). These substantive sectors include, but are not limited to, environmental issues, economic development, \\nsecurity, public service, international relations, primary education, social development and domestic affairs \\n(Fischer et al., 2015). A substantive policy focuses on what the government should do (Simeon, 1976). A \\nsubstantive policy may incorporate specific overarching goals (such as describing the anticipated results of the \\npolicy while it is being produced, for example) (Marie-Kim and Marie-Hélène, 2020). It might also consist of \\nmore concrete objectives the policy must achieve. Yudiatmaja et al. (2022) conclude that successful substantive \\nsolutions can resolve a policy issue. \\n \\n\\n\\n \\nINSIGHTS INTO REGIONAL DEVELOPMENT \\nISSN 2669-0195 (online) https://jssidoi.org/ird/ \\n2023 Volume 5 Number 2 (June) \\n \\n \\nhttp://doi.org/10.9770/IRD.2023.5.2(6) \\n \\n89 \\n \\n2.6. Government policy Execution \\nThe policy as it is carried out is the genuine policy of a government, according to Peters (2001). One of the main \\nreasons why government policy execution is one of the most crucial stages in the whole government \\npolicymaking process is because it refers to the point at which a policy is implemented (Díaz-Llamas et al., 2023; \\nAguerre and Hernan, 2015). According to Peters (2001), one of the main issues with our current political systems \\nis how government policies are carried out. Many behaviours in the administrative and political settings where \\ngovernment policy is being implemented are taken into account throughout the execution process, claims Hurel \\nand Rocha (2018). According to Galli (2015), politics substantially influences every action or step taken during \\nthe cycle of policy execution, with both a macro and micro political context (Galli, 2015). \\n \\nThe macro-political backdrop, which includes factors like legislation, economy, and what is happening or moving \\nworldwide, is what Galli (2015) refers to as the external environment. On the other hand, according to Galli \\n(2015), the micro-political context comprises things like the policy’s mission, the competencies needed, the \\norganizational culture, and the external environment. GPE is rather challenging since several factors must be \\nconsidered, some of which the implementers have influence over and others of which they do not. Falk and Tally \\n(2016) argue that it is incorrect to assume that implementing government policy only entails putting previously \\ndeveloped procedures into action since there is more to it than that. Implementing government policy involves \\nusing important inherent information. \\n \\nCreese, Dutton and Esteve-Gonzalez (2021) assert that GPE bridges policymakers and policy addresses. The \\nimplementers aid this relationship. This GPE phase is essential because it makes it possible to execute the \\nproposed or envisioned policy (Steven, 2021). This suggests that the result of the policy is transformed into its \\nproduction. Aguerre and Hernan (2015) contend that policies and practices must be separated to understand the \\nwhole process of producing policies. As mentioned earlier, the role-players in charge of implementing the policies \\nmust thus not act entirely independently. As a result, they offer guidelines for applying already created and \\nauthorized policies. \\n \\n3. \\nTheoretical Review \\n \\nGovernment policy theories are essential in the social, environmental, technological and engineering literature. \\nThese theories offer unique characteristics of political and human development. Among the theories of \\ngovernment policy are the political systems theory, group theory, institutional theory, rational choice theory, and \\nthe policy process model. \\n \\nMany of the previous and present policies are formulated and implemented because they are influenced by \\nsystemic variables, political processes, institutional influences, game-playing, incrementalism, interest group, \\nrational planning, elite preferences, and interest group interests. These theories will pose further issues regarding \\ngovernment policy and the primary channels from which sound decisions are formed. The following section will \\ncover these theories. \\n \\n3.1. The elite/mass theory \\nThe elite notion holds that a small elite group controls the bulk (Zeb-un et al., 2021). This idea works best in the \\ncountries of Africa. Because the interests and well-being of the elite are prioritized under this theory, elite \\nviewpoints that diverge from those of the general public can affect the development of government policy (Zeb-un \\net al., 2021; Jutta, 2016). The elite thesis is based on the notion that because the general public is allegedly \\nuninformed and indifferent, their opinions shouldn’t have any bearing on how government policy is formulated \\n(Fischer et al., 2015). \\n \\n\\n\\n \\nINSIGHTS INTO REGIONAL DEVELOPMENT \\nISSN 2669-0195 (online) https://jssidoi.org/ird/ \\n2023 Volume 5 Number 2 (June) \\n \\n \\nhttp://doi.org/10.9770/IRD.2023.5.2(6) \\n \\n90 \\n \\nThe elite notion holds that only a caste that is acknowledged throughout society should influence government \\npolicy (Kraft and Furlong, 2013). This elite caste includes members of the governing class, political parties, \\nbusiness executives, wealthy individuals, and educated segments of society (Jutta, 2016). One way that the elite \\nideology is implemented is by whom the most influence over how government policy is decided (Jutta, 2016). Not \\nall elites have an outsized impact on shaping government policy. Each elite aims to have a significant effect on a \\nspecific niche market. For instance, business executives would want to weigh in on decisions regarding tax \\nlegislation and import and export laws. The governing class, however, would like to have a voice in how the \\ngeneral public is governed, how money is allocated, and how resources are utilized.  \\n \\nIt’s also conceivable that these two exclusive groups come into contact with one another and interact as they use \\ntheir influence and power. Zeb-un et al. (2021) assert that public administrators’ perceived importance is \\ninfluenced by the idea that they are members of the ruling class rather than citizens’ servants. This idea may be \\nexplained as a small elite making decisions that cascade down to an uneducated civil society (Fischer et al., 2015). \\nZeb-un et al. (2021) assert that political power influences these decisions and that the bureaucracy is necessary to \\ncarry them out. The idea holds that only a select group of experts possess the authority. \\n \\n3.2. Group theory  \\nPolitics is characterized by the interaction of groups, and the group theory incorporates organized interest groups \\nin the creation of government policy (Jutta, 2016). These actors are shown as tenacious voice-hearing warriors. In \\nlight of this, it is possible, to sum up group theory as a battle between the voices of organized interest groups. \\nGroup theory includes, for example, individuals working in the agriculture sector and companies producing \\nmusic. Organizations should be allowed to make a major contribution and have a say in determining government \\npolicy. In order to dispute the abuse, poor administration, and fraudulent execution of policies, as well as hold \\nthose responsible accountable, people should be able to challenge laws that are thought to be illogical, unsuited, \\nor ineffective for the intended purpose. \\n \\nOrganizations ought to promote justice, transparency, the participation of the citizenry, and awareness in \\npolicymaking. The group theory is crucial and pertinent to government policy as a result. This is done so that \\norganizations may play a big part in setting policy and assisting with enforcing previously approved or ratified \\nlegislation like the Constitution. Groups have an impact on government policy, whether it be a policy regarding \\nenvironmental concerns or the welfare of the populous as a whole. This exemplifies how several interest groups \\nfrom diverse socioeconomic domains may all voice their opinions on the policies they believe the government \\nshould adopt or reject and play a significant role in their creation. According to Zeb-un et al. (2021), group theory \\nhas some implications for political decisions. For instance, the dynamics of the cabinet are changed. \\n \\nThe disadvantage of the group theory is that it rewards more organized groups, has more members, has access to \\nresources, has political allegiances, is well-liked, and has built ties with decision-makers (Galli, 2015). The less \\nfortunate members of society lack all of the aforementioned resources and are at the other extreme of the spectrum \\n(Jutta, 2016). According to Bertram, Maleki and Karsten (2019), group theory is criticized by academics studying \\ngovernment policy for giving organized interest groups too much sway and leaving it up to them to decide policy \\n(Oyadiran and Akintola, 2014). Government employees also seem to be left on the side of the road (Tacon and \\nHanson, 2011). \\n \\nResearchers in government policy believe that the degree of impact that organized interest groups have on \\npolicymaking tends to worsen the complexity and dynamic character of policymaking that is already present \\n(Kraft and Furlong, 2013). It is also important to acknowledge that the elite/mass does have some roots in group \\ntheory (Carroll and Common, 2013). Although all groups (regardless of socioeconomic level or prominence) may \\nbe accommodated under the group theory, those with access to more resources are often the ones whose opinions \\n\\n\\n \\nINSIGHTS INTO REGIONAL DEVELOPMENT \\nISSN 2669-0195 (online) https://jssidoi.org/ird/ \\n2023 Volume 5 Number 2 (June) \\n \\n \\nhttp://doi.org/10.9770/IRD.2023.5.2(6) \\n \\n91 \\n \\nare heard when policies are being developed (Chaudhary, 2018). Their voices tend to be aristocratic. The voices \\nof those groups that lack access to the same resources as the privileged are so muffled. \\n \\nThe term \\\"extra influence\\\" refers to the elite groups’ intrusion into group theory and the creation of government \\npolicy. This is characterized by Guidi Guardiancich and Levi-Faur (2020) as having a solid clientele, knowledge, \\nand leadership. Also, this increases the pressure on public servants and policymakers, which tips the balances in \\ntheir favour when deciding the course of government policy. \\n \\n3.3. Institutional-based theory  \\nThis theory is often known as the \\\"classical theory\\\" since it is interpreted classically to study government policy \\n(Zeb-un et al., 2021). It is not a coincidence that Minkman, van Buuren and Bekkers (2018) state that the \\ninstitutional approach arose as awareness of the importance of enshrining government policy-making in the \\nframework of institutions expanded. This implies that the government’s concerns about welfare should take \\nprecedence over other issues (Zeb-un et al., 2021). Institutional theory is deeply rooted in the formal and legal \\naspects of the governmental system (Díaz-Llamas et al., 2023). The institutional model’s purpose is to evaluate \\nthe structures that regulate how the government is structured, its legal power and the norms of behaviour it \\nadheres to while making decisions (Dunne et al., 2021). The institutional theory focuses primarily on the public’s \\naccess to decision-making, government transparency, and, eventually, the separation of powers between the \\nvarious levels of government (Zeb-un et al., 2021).  \\n \\nThe institutional theory rationally asserts that the structures and codes of conduct that regulate the government \\nand its departments significantly impact the various types of policy processes that take place, as well as how role-\\nplayers in those processes will ultimately affect those processes (Kraft and Furlong, 2013). Political, economic, \\nand sociological institutionalism are the three frameworks that institutional theory embraces (Minkman, van \\nBuuren and Bekkers, 2018). Economic institutionalism stresses applying economic analysis to political \\ninstitutions and government policy, whereas political institutionalism looks beyond the traditional forms of \\ninstitutions to pay more attention to (Díaz-Llamas et al., 2023). The institutional theory is essential in ensuring \\ngovernment policies' legitimacy, applicability, and coerciveness (especially true of regulatory laws, which impose \\nobligations on the general populace) (Díaz-Llamas et al., 2023). \\n \\n3.4. Rational choice theory \\nThis is a contemporary theory used in social sciences. The public choice theory is another name for the theory of \\nrational choice (Cagnin, 2017). It has a strong economic foundation (Jutta, 2016). Generally, it uses complex \\nmathematical modelling, which has only been moderately helpful in evaluating marginal behaviours in \\ncompetitive circumstances and is typically seen throughout an election period (Ashmore et al., 2020). \\n \\nThis theory is thoroughly developed and rigorous, and it could be used to address many government policy-\\nrelated issues (Kraft and Furlong, 2013) and used to conclude. Opponents of this theory claim that the decisions \\nmade based on rational choice are faulty, unrealistic and unworkable. \\n \\nCagnin (2017) identified two distinct features of the rational choice theory. Its main focuses are methodological \\nindividualism and the assumption that people are reasonable. The sensible perspective contends that the ability to \\nmake decisions indicates a person’s capability for logical reasoning. On the other hand, Ashmore et al. (2020) \\nargue that a broad account of human behaviour supports all rational choice theories. According to Ashmore et al. \\n(2020), the basic hypothesis holds that individuals are complicated, flawed mortals who strive for perfection \\ndespite whatever challenges they may encounter. \\n \\n \\n \\n\\n\\n \\nINSIGHTS INTO REGIONAL DEVELOPMENT \\nISSN 2669-0195 (online) https://jssidoi.org/ird/ \\n2023 Volume 5 Number 2 (June) \\n \\n \\nhttp://doi.org/10.9770/IRD.2023.5.2(6) \\n \\n92 \\n \\n3.5. Political systems theory \\nThis theory is the most complete among popular approaches (Kraft and Furlong, 2013). The theory aids \\ngovernment initiatives and institutions in transforming public inputs (such as environmental needs) into policy \\noutputs (such as public opinion and pressure from interest groups) (Cagnin, 2017). The theory was designed to \\nraise public awareness of policy issues and give the populace a platform to express grievances (Cagnin, 2017), \\nallowing for the problems to be presented on the government’s policy agenda (Uminska-Woroniecka, 2022). \\nMoreover, it represents the wider, shared socioeconomic, cultural, and political framework that serves as the \\nfoundation for decisions on politics and policy (Jutta, 2016). According to Bertram, Maleki and Karsten (2019), \\nthe language employed in political and policy studies has expanded as a result of the systems theory. \\n \\n3.5.1. Government policy Cycle  \\nIn accordance with the four government policy functions, the policy process model (Jutta, 2016) recommends an \\nanalytical progression of the occasions that impact the formulation of government policies (Guidi et al., 2020). At \\neach level of the policy process model, the connections between policy players are shown (Jutta, 2016). \\nAccording to Appiah-Agyekum (2020), the policy model explains how decisions were made, makes \\nunderstanding the timeline of events simpler, and supports the pragmatic nature of government policy (Guidi et \\nal., 2020). \\n \\nMoreover, it explains how these results in the understanding that can be applied to any political system and its \\ndecision-making procedures (Jutta, 2016). The best method to begin a discussion of policy theories and a strategy \\nto organize the study of policymaking, according to Cagnin (2017), is to use the policy cycle. According to \\nBertram, Maleki and Karsten (2019), the traditional model is cyclical since formulating policies is continuous and \\nalways in “motion\\\" as a rolling wheel. \\n \\nThe policy cycle's main lesson is that just because an issue has been identified and a decision has been taken, it \\ndoesn’t mean everything has been fixed (Cagnin, 2017). That only denotes the beginning of the policymaking \\nprocess. The model’s stages are linked to each other like links in a chain cycle (Appiah-Agyekum et al., 2022). As \\nBertram, Maleki and Karsten (2019) noted, no policy decision or solution is ever final. The policy process model \\ndoes succeed in capturing the essence of policymaking despite all of its flaws, and as a consequence, it correlates \\nto political reality. \\n \\nAccording to Lerma, Díaz-Baca and Burkart (2022), the conventional model of the policy process consists of four \\nfunctional processes or phases:  \\ni. \\nAgenda setting; \\nii. \\nPolicy development;  \\niii. \\nPolicy execution; and  \\niv. \\nPolicy assessment \\nTwo additional steps that Bertram, Maleki and Karsten (2019) add to the concept of the policy process are:  \\ni. \\nPolicy legitimization; and  \\nii. \\nPolicy modification.  \\nGuidi et al. (2020) postulate the results of policies and the related subsystems that must be implemented. This \\nsuggests that the stages theory serves as an example of how a government policy develops (or comes into \\nexistence). Guidi et al. (2020) assert that knowledge and information are the main forces behind policy \\nconstruction. \\n \\nIn a significant sense, this is the reason why everyone involved in the policy process has to be sufficiently \\ninformed of how government policy is produced, as well as possess the knowledge, skills, and competence \\nnecessary to see the process through to the end (Rakšnys and Valickas, 2023). Moreover, it serves as a tool for \\n\\n\\n \\nINSIGHTS INTO REGIONAL DEVELOPMENT \\nISSN 2669-0195 (online) https://jssidoi.org/ird/ \\n2023 Volume 5 Number 2 (June) \\n \\n \\nhttp://doi.org/10.9770/IRD.2023.5.2(6) \\n \\n93 \\n \\nguiding and educating decision-makers on the procedures involved in carrying out government policy (Cairney \\n2012). \\n \\n3.5.2. Agenda setting \\nAny social issue that the public brings up should be taken seriously (Aguerre and Hernan, 2015). But more \\nimportantly, agenda-setting in democracies is expected to be characterized by a high level of citizenry \\nparticipation (Blackstock et al., 2020). Various media influences can manage, shape, and define the issues on the \\npolicy agenda (Fischer et al., 2015). \\nThe topics included on the policy agenda can be influenced, controlled, shaped, and defined using these platforms \\nor the participation of experts from a particular subject (Crabolu, Font and Eker, 2023). These are the three steps \\nthat makeup agenda setting: \\na) Identification of issues; \\nb) verifying which problem is of significant essence; and  \\nc) Outlining the dynamics of an issue (Cagnin, 2017).  \\nAccording to Díaz-Llamas et al. (2023) and Falk and Tally (2016), only one element determines whether \\npolicymakers should pay attention at this early stage of the policy process. That aspect is the availability of \\ninformation about social issues/issues. According to Steinert (2016), the public media’s assessment and awareness \\nof a societal issue has an effect on agenda shaping. This is due to the possibility that the press might impact public \\nopinion, given the variety of media outlets available (Chetty, 2015). \\n \\n3.5.3. Policy formulation \\nBefore creating a policy, one must create a strategy for responding to the suggestions made during the first phase \\nof the policymaking process. According to Cagnin (2017), creating policies entails defining goals, estimating \\ncosts, and assessing the specific outcomes this policy will produce. As a result, the suggested course of action and \\nthe policymaker's (s) ' intentions are both stated at this point in the policy cycle (Steven, 2021). Rational, logical \\nsolutions are chosen. Following the conclusion of this process, crucial policy instruments are selected (Cagnin, \\n2017). Falk and Tally (2016) assert that all necessary stakeholders, such as interest organizations, elected \\nofficials, legislators, and the public, should participate in policy development. \\n \\n3.5.4. Policy execution \\nOnly the events in the early stages of the policy process result in government policy. At this stage, it may be \\nanticipated that a government policy will undergo changes, such as revision; the government policy may even be \\nrejected at this stage (Kustec and Mcardle, 2012). A significant feature of government policy execution is that it \\nmay take on many shapes and forms depending on the institutional and cultural context (Welsh, 2019). Attention \\nwas called to an essential facet of carrying out government policy, especially given that it operates or is carried \\nout at a time when \\\"government\\\" procedures are seen as having been transformed into \\\"governance\\\". \\n \\nMoreover, Jaishia et al. (2023) classify government policy execution research as a political science and \\nadministration subject. This suggests that overly-simplistic hierarchical models are being abandoned and that a \\nbroad spectrum of stakeholders is starting to participate in policymaking (Iroulo and Boateng, 2023). Also, \\npolitics ends when administration begins. Politics and administration are related. According to Mügge and \\nAlenda-Demoutiez (2019), the institutions of democracy and the rule of law have entrenched a tight hierarchy in \\nthe relationship between these two disciplines. \\n \\n3.5.5. Policy Outcomes and Evaluation \\nAt this stage, a policy is evaluated to determine its success (or failure) (Cagnin, 2017). The effective execution of \\nthe procedure, the judgments taken about the policy, and whether the policy generated the intended results as \\ndescribed in the stage of defining the agenda and formulating the policy are all crucial factors to take into account \\nwhen evaluating policies (Cagnin, 2017; Steven, 2021). Lessons will be drawn from this, recognized, and \\n\\n\\n \\nINSIGHTS INTO REGIONAL DEVELOPMENT \\nISSN 2669-0195 (online) https://jssidoi.org/ird/ \\n2023 Volume 5 Number 2 (June) \\n \\n \\nhttp://doi.org/10.9770/IRD.2023.5.2(6) \\n \\n94 \\n \\ntypically serve as the basis for future policy choices (Appiah-Agyekum et al., 2022; Cagnin, 2017). This is done \\nby carefully reviewing all of the information gleaned from evaluating the policy’s outcomes (Mügge and Alenda-\\nDemoutiez, 2019). \\n \\nMany government policy actors, such as think tanks, government organizations, external consultants, nonprofit \\ngroups, the media, and the general public, can engage in this activity (Fischer et al., 2015). When this process is \\nfinished, the policy can be sent back to the legislator, who can then choose whether to change it (possibly \\nsignalling the start of a new policy cycle) (Steven, 2021). \\n \\nThe policy cycle is advantageous. Welsh (2019) identified the main reasons for this:  \\na) Since it is a logical process that may depict the variety of reality, it is plain and easy to grasp.  \\nb) Each phase disseminates knowledge to a particular section of the setting in which government policy is \\nproduced (Welsh, 2019). This could aid the policymaker in selecting the many variables and tactics \\navailable. \\nc) The policy cycle shows that policymaking is flexible.  \\nd) The process of establishing policies follows a chronological order. \\nThe policy cycle also identifies the point at which the policymaking process should start, which makes it a helpful \\ntool for the decision-maker. \\n \\nConclusions \\n \\nDefinitions and classifications of government policy were expanded in this study. It is essential to keep in mind \\ndifferent types of policies are defined in different ways but must be simple to comprehend. As the objective of a \\npolicy is more likely to shape society, the distributive or substantive policy may be seen by one group of \\nparticipants as a regulatory policy. Still, another group may not see it as such. Therefore, policy classifications aid \\nin outlining the various ways that policy stakeholders frequently describe policies and the development of \\npracticability and reality of the policy that will be implemented. \\n \\nThe elite/mass idea holds that society is divided into two groups: those in positions of authority and those who do \\nnot. Those with access to and influence take a more active role in creating government policy, which is in line \\nwith the elite/mass theory. The exciting aspect of group theory is that it aligns more with the legislative branch of \\ngovernment than the bureaucracy. This could be because the legislature is where the general population's opinions \\nare represented. \\n \\nFor the institutional theory, it was revealed that institutions and policy are closely related. The institutional \\ntheory's foundation is procedural legislation and how it could help or impede political goals in various \\ngovernmental structure sectors. Although the rational choice theory assumes that government policy actors have \\naccess to all the information necessary to make well-informed decisions, this theory can be misleading and \\nunrealistic because it believes that government policy actors will have the knowledge and ability to make rational \\ndecisions. \\n \\nTo categorize and understand the contributions and linkages made by institutions and policy players and the role \\nplayed by the external environment in producing policy, however, the systems theory offers a more \\nunderstandable method. It was contended that as democracy is an administrative system built on broad public \\ninvolvement, politicians and people in public office should support any concept that fosters citizen engagement in \\nany form (especially in democracies). \\n \\nThe participation of the citizenry at all proper steps of the policy cycle is only fair because government policy is \\ncreated with the general public in mind; nonetheless, caution against dismissing any of these models or theories. \\n\\n\\n \\nINSIGHTS INTO REGIONAL DEVELOPMENT \\nISSN 2669-0195 (online) https://jssidoi.org/ird/ \\n2023 Volume 5 Number 2 (June) \\n \\n \\nhttp://doi.org/10.9770/IRD.2023.5.2(6) \\n \\n95 \\n \\nThey provide different viewpoints on politics and government policy and information on how these two function \\nin the institutional and political domains. They directly give rise to theories of politics and government policy, \\nwhich provide light on how issues are discussed during policymaking. \\n \\nIt is essential to remember that government policy and how it is carried out are about ‘outcomes’ for the policies \\nbeing implemented. It entails gathering all the inputs (needs) from the community and rating each demand \\naccording to priority. These inputs from the community or other role-players decide the issues listed on the \\npolicy’s agenda. Second, the bureaucracy must recognize the outside world since external variables, except for the \\ncommunity, significantly impact government policy. Laws, the environment on a global scale, technology, \\ntraditional views, politics, diversity, and complexity are some of these external elements. \\n \\n \\n \\nReferences \\n \\nAdeniran, A. O. (2016). 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Palarch’s Journal of Archaeology of Egypt/Egyptology, 18(10), 1307-1321. \\n \\n \\n \\n \\nFunding: This research was supported by the project, which has received funding from the European Union’s Horizon 2020 \\nresearch and innovation programme European Research Council (ERC) under the European Union’s Horizon 2020 research \\nand innovation programme Marie Sklodowska-Curie Research and Innovation Staff Exchanges ES H2020-MSCA-RISE-\\n2014 CLUSDEVMED (2015-2019) Grant Agreement Number 645730730 \\n \\n \\nAuthor Contributions: Conceptualization: Adetayo Adeniran, Joseph Muraina, writing-original draft preparation: Adetayo \\nAdeniran, Joseph Muraina, Joseph Ilugbami, writing; review and editing: Joseph Ilugbami, Adedayo Adeniran. All authors \\nhave read and agreed to the published version of the manuscript. \\n \\n \\n \\nAdetayo Olaniyi ADENIRAN Department of Logistics and Transport Technology, Federal University of Technology \\nAkure, Nigeria. \\nORCID ID: https://orcid.org/orcid.org/0000-0002-6870-1212  \\n \\nJoseph Mosunmola MURAINA Department of Geography and Planning Science, Ekiti State University, Ekiti, Nigeria. \\nORCID ID: https://orcid.org/orcid.org/0009-0006-5764-3594  \\n \\nJoseph Olanrewaju ILUGBAMI Rufus Giwa Polytechnic-Owo Rector Office, Ondo State, Nigeria. \\nORCID ID: https://orcid.org/orcid.org/0009-0005-8114-5264  \\n \\nAdedayo Ayomide ADENIRAN Department of Geopgraphy and Planning, University of Ibadan, Nigeria. \\nORCID ID: https://orcid.org/orcid.org/0009-0001-0241-6232  \\n \\n \\n \\nMake your research more visible, join the Twitter account of INSIGHTS INTO REGIONAL DEVELOPMENT:  \\n@IntoInsights \\n \\nThis is peer-reviewed scientific journal https://jssidoi.org/ird/page/peer-review-policy \\n________________________________________________________________________________________________________________ \\n________________________________________________________________________________________________________________ \\nCopyright © 2023 by author(s) and VsI Entrepreneurship and Sustainability Center \\nThis work is licensed under the Creative Commons Attribution International License (CC BY). \\nhttp://creativecommons.org/licenses/by/4.0/ \\n \\n \\n \\nView publication stats\\n\\n\\n\\n\\nThis book systematically analyzes how and why China has expectedly lost and then \\nsurprisingly gained ground in the quest to solve the complicated environmental \\nproblem of air pollution over the past two decades.\\nYuan Xu shines a light on how China’s sulfur dioxide emissions rose quickly \\nin tandem with rapid economic growth but then dropped to a level not seen for \\nat least four decades. Despite this favorable mitigation outcome, Xu details how \\nthis stemmed from a litany of policy stumbles within the Chinese context of no \\ndemocracy and a lack of sound rule of law. Throughout this book, the author \\nexamines China’s environmental governance and strategy and how they shape \\nenvironmental policy. The chapters weave together a goal-­\\ncentered governance \\nmodel that China has adopted of centralized goal setting, decentralized goal \\nattainment, decentralized policy making and implementation. Xu concludes that \\nthis model provides compelling evidence that China’s worst environmental years \\nreside in the past.\\nThis book will be of great interest to students and scholars of Chinese \\nenvironmental policy and governance, air pollution, climate change and sustainable \\ndevelopment, as well as practitioners and policy makers working in these fields.\\nYuan Xu is Associate Professor in the Department of Geography and Resource \\nManagement, The Chinese University of Hong Kong.\\nEnvironmental Policy and \\nAir Pollution in China\\n\\n\\nStrategic Designs for Climate Policy Instrumentation\\nGovernance at the Crossroads\\nGjalt Huppes\\nThe Right to Nature\\nSocial Movements, Environmental Justice and Neoliberal Natures\\nEdited by Elia Apostolopoulou and Jose A. Cortes-­\\nVazquez\\nGuanxi and Local Green Development in China\\nThe Role of Entrepreneurs and Local Leaders, 1st Edition\\nChunhong Sheng\\nEnvironmental Policy in India\\nEdited by Natalia Ciecierska-­\\nHolmes, Kirsten Jörgensen, Lana Ollier \\nand D. Raghunandan\\nMainstreaming Solar Energy in Small, Tropical Islands\\nCultural and Policy Implications\\nKiron C. Neale\\nEU Environmental Governance\\nCurrent and Future Challenges\\nEdited by Amandine Orsini and Elena Kavvatha\\nThe European Union and Global Environmental Protection\\nTransforming Influence into Action\\nEdited by Mar Campins Eritja\\nEnvironmental Policy and Air Pollution in China\\nGovernance and Strategy\\nYuan Xu\\nFor more information about this series, please visit: www.routledge.com/\\nRoutledge-­\\nStudies-­\\nin-­\\nEnvironmental-­\\nPolicy/book-­\\nseries/RSEP\\nRoutledge Studies in Environmental Policy\\n\\n\\nEnvironmental Policy and \\nAir Pollution in China\\nGovernance and Strategy\\nYuan Xu\\n\\n\\nFirst published 2021\\nby Routledge\\n2 Park Square, Milton Park, Abingdon, Oxon OX14 4RN\\nand by Routledge\\n52 Vanderbilt Avenue, New York, NY 10017\\nRoutledge is an imprint of the Taylor & Francis Group, an informa business\\n© 2021 Yuan Xu\\nThe right of Yuan Xu to be identified as author of this work has been \\nasserted by him in accordance with sections 77 and 78 of the Copyright, \\nDesigns and Patents Act 1988.\\nThe Open Access version of this book, available at www.taylorfrancis.\\ncom, has been made available under a Creative Commons Attribution-­\\nNon \\nCommercial-­\\nNo Derivatives 4.0 license.\\nTrademark notice: Product or corporate names may be trademarks or \\nregistered trademarks, and are used only for identification and explanation \\nwithout intent to infringe.\\nBritish Library Cataloguing-­\\nin-­\\nPublication Data\\nA catalogue record for this book is available from the British Library\\nLibrary of Congress Cataloging-­\\nin-­\\nPublication Data\\nA catalog record for this book has been requested \\nISBN: 978-­\\n1-­\\n138-­\\n32232-­\\n5 (hbk)\\nISBN: 978-­\\n0-­\\n429-­\\n45215-­\\n4 (ebk)\\nTypeset in Times New Roman\\nby Apex CoVantage, LLC\\n\\n\\nList of figures\\b\\nvi\\nList of tables\\b\\nix\\nPreface\\b\\nx\\nAcknowledgments\\b\\nxii\\n1\\t\\nIntroduction\\b\\n1\\n2\\t\\nPolitical will\\b\\n17\\n3\\t\\nEnvironmental governance\\b\\n25\\n4\\t\\nMobilizing the government\\b\\n42\\n5\\t\\nPolicy making\\b\\n77\\n6\\t\\nPolicy implementation\\b\\n105\\n7\\t\\nEnvironmental technology and industry\\b\\n149\\n8\\t\\nGoal-­\\ncentered governance\\b\\n179\\nIndex\\b\\n193\\nContents\\n\\n\\n\\t\\n1.1\\t\\nEnvironmental Performance Index in the baseline year\\b\\n2\\n\\t\\n1.2\\t\\nChina’s premature deaths due to air and water pollution \\nin the Global Burden of Disease study\\b\\n2\\n\\t\\n1.3\\t\\nDisability-­\\nadjusted life years (DALYs) in China due to air \\nand water pollution in the Global Burden of Disease study\\b\\n3\\n\\t\\n1.4\\t\\nDALYs in days (or disability-­\\nadjusted life days [DALDs]) \\nper person per year in China and India\\b\\n4\\n\\t\\n1.5\\t\\nPolity Democracy Index for China, South Korea, Singapore, \\nIndia and the United States\\b\\n5\\n\\t\\n1.6\\t\\nGDP per capita in PPP (purchasing power parity) in China, \\nSouth Korea, Japan and the United States\\b\\n7\\n\\t\\n1.7\\t\\nGovernance indicators of China, India and the United States\\b\\n8\\n\\t\\n1.8\\t\\nSO2 emissions in China\\b\\n10\\n\\t\\n1.9\\t\\nSO2 emissions by sector in China (from two different data \\nsources for 1970–2012 and 2010–2017, respectively)\\b\\n11\\n\\t\\n1.10\\t The power sector’s shares of coal consumption and SO2 \\nemissions in China and the United States\\b\\n11\\n\\t\\n1.11\\t SO2 emissions in the United States and SO2 intensities \\nin China and the United States\\b\\n12\\n\\t\\n2.1\\t\\nSectoral employment changes and GDP growth rates across \\nChina’s administrations\\b\\n19\\n\\t\\n2.2\\t\\nEmployment and population structures in China\\b\\n19\\n\\t\\n3.1\\t\\nEnvironmental protection personnel at four governmental levels \\nin China\\b\\n29\\n\\t\\n3.2\\t\\nGovernmental revenue and expenditure to GDP ratios by central \\nand local governments in China\\b\\n33\\n\\t\\n3.3\\t\\nBudget balance of central and local governments in China \\nas a proportion of GDP\\b\\n35\\n\\t\\n3.4\\t\\nGovernmental budget balance by provinces as a proportion \\nof governmental expenditures in 2018\\b\\n36\\n\\t\\n3.5\\t\\nThe central and local governments’ shares of expenditures \\nby budgetary items in 2018\\b\\n37\\n\\t\\n3.6\\t\\nCentral, local and overall governmental expenditures \\nby budgetary items in 2018\\b\\n37\\nFigures\\n\\n\\nFigures  vii\\n\\t\\n3.7\\t\\nShares in governmental expenditures\\b\\n38\\n\\t\\n4.1\\t\\nDesignated SO2 emission intensity in distributing SO2 emissions \\nquota to coal-­\\nfired power plants for 2010 in the 11th Five-­\\nYear Plan\\b\\n58\\n\\t\\n4.2\\t\\nDaily SO2 concentrations in Shijiazhuang\\b\\n68\\n\\t\\n4.3\\t\\nDaily PM2.5 concentrations in Shijiazhuang\\b\\n69\\n\\t\\n4.4\\t\\nDaily 8-­\\nhour O3 concentrations (daily maximum concentration \\nover 8 hours) in Shijiazhuang\\b\\n70\\n\\t\\n4.5\\t\\nMonthly average AQI in Shijiazhuang\\b\\n70\\n\\t\\n4.6\\t\\nMonthly average AQI in Beijing\\b\\n71\\n\\t\\n4.7\\t\\nMonthly average AQI in Shenzhen\\b\\n72\\n\\t\\n5.1\\t\\nEconomic growth in China, Japan and the United States\\b\\n85\\n\\t\\n5.2\\t\\nPrimary energy consumption and energy efficiency\\b\\n86\\n\\t\\n5.3\\t\\nPrices of coal (Qinhuangdao spot price), oil and natural gas\\b\\n87\\n\\t\\n5.4\\t\\nThe annual growth of primary energy consumption in China \\nby fuels\\b\\n88\\n\\t\\n5.5\\t\\nChina’s primary energy consumption by fuel and the shares \\nof coal and fossil fuels\\b\\n88\\n\\t\\n5.6\\t\\nPrimary energy consumption and its electrification rate\\b\\n89\\n\\t\\n5.7\\t\\nElectricity generation by fuels in China\\b\\n90\\n\\t\\n5.8\\t\\nThe annual growth of electricity generation in China by fuels \\nand coal’s share\\b\\n91\\n\\t\\n5.9\\t\\nThe decomposition of China’s SO2 emissions\\b\\n91\\n\\t\\n5.10\\t Distribution of sulfur contents in coal power plants in China\\b\\n95\\n\\t\\n5.11\\t Coal-­\\nfired power and SO2 scrubber capacities in China\\b\\n97\\n\\t\\n5.12\\t The annual growth of coal-­\\nfired power and SO2 scrubber \\ncapacities in China\\b\\n98\\n\\t\\n5.13\\t Annually increased SO2 scrubber capacity and unit sizes\\b\\n99\\n\\t\\n5.14\\t The annual growth of SO2 scrubber capacity by regions\\b\\n100\\n\\t\\n5.15\\t SO2 scrubbing technologies by unit sizes\\b\\n101\\n\\t\\n6.1\\t\\nThe operation of SO2 scrubbers in Jiangsu Province, including \\nself-­\\nreported operation rates and later confirmed operation \\nrates\\b\\n106\\n\\t\\n6.2\\t\\nA conceptual model of environmental compliance monitoring\\b\\n121\\n\\t\\n6.3\\t\\nModel simulation of compliance rates in the diagnosing and \\nscreening systems with available compliance monitoring \\nresources and initial compliance rates\\b\\n128\\n\\t\\n6.4\\t\\nModel simulation of equilibrium compliance rates in the \\nscreening and diagnosing systems in relation to available \\ninspection staff\\b\\n128\\n\\t\\n6.5\\t\\nModel simulation of equilibrium compliance rates in the \\nscreening and diagnosing systems in relation to (a) the number \\nof polluters; (b) the ratios between pollution abatement costs \\nand noncompliance penalty; (c) available inspection staff, where \\nthe pollution abatement cost-­\\nto-­\\nnoncompliance penalty ratio has \\na lognormal distribution; and (d) the relative resource intensity \\nof screening and diagnosing technologies.\\b\\n130\\n\\n\\nviii  Figures\\n\\t\\n6.6\\t\\nModel simulation of equilibrium compliance rates in the \\nscreening and diagnosing systems in relation to the probabilities \\nthat (a) the screening technology recognizes compliance \\ncases as being compliant, (b) the diagnosing technology \\nrecognizes compliance cases as being compliant, (c) the \\nscreening technology recognizes noncompliance cases as being \\nnoncompliant and (d) the diagnosing technology recognizes \\nnoncompliance cases as being noncompliant.\\b\\n133\\n\\t\\n7.1\\t\\nThe progressive paths on the deployment and operation of SO2 \\nscrubbers in China and the United States\\b\\n150\\n\\t\\n7.2\\t\\nAnnual average unit capital costs of SO2 scrubbers in China and \\nthe United States\\b\\n151\\n\\t\\n7.3\\t\\nModel projection of the SO2 mitigation path in China’s coal-­\\nfired power plants: (a) deployment and operation of SO2 \\nscrubbers under goal-­\\ncentered governance (the dots refer to \\nactual data); (b) avoided SO2 emissions under goal-­\\ncentered and \\nrule-­\\nbased governance\\b\\n154\\n\\t\\n7.4\\t\\nYearly university graduates in China from four-­\\nyear \\nundergraduate programs by subjects\\b\\n157\\n\\t\\n7.5\\t\\nR&D personnel, expenditure and market value (in 2018 RMB) \\nin China\\b\\n161\\n\\t\\n7.6\\t\\nPatents on environmental technology by filing office in the world\\b\\n162\\n\\t\\n7.7\\t\\nWind energy development in China and the United States\\b\\n168\\n\\t\\n7.8\\t\\nCompanies in the Chinese and U.S. markets installing 100-­\\nMW-­\\nscale or greater SO2 scrubbers\\b\\n171\\n\\t\\n7.9\\t\\nAverage prices of wind turbines in China and the United States\\b\\n172\\n\\t\\n8.1\\t\\nAn illustration of the goal-­\\ncentered governance model\\b\\n183\\n\\n\\n\\t\\n4.1(a)\\t\\nCorrelation coefficients of key factors for 27 provinces\\b\\n53\\n\\t\\n4.1(b)\\t\\nSummary of variables\\b\\n54\\n\\t\\n4.2\\t\\nRegression model results for distributing the national goal \\nto provinces\\b\\n56\\n\\t\\n4.3\\t\\nRegression model results for distributing provincial goals \\nto municipalities\\b\\n59\\n\\t\\n4.4\\t\\nProvincial goal distribution matrix\\b\\n61\\n\\t\\n5.1\\t\\nApplied fractions of sulfur retained in ash\\b\\n93\\n\\t\\n5.2\\t\\nEffluent SO2 emissions and necessary SO2 removal rates\\b\\n97\\n\\t\\n6.1\\t\\nData on SO2 scrubbers in China’s seven coal-­\\nfired power \\nplants\\b\\n114\\n\\t\\n6.2\\t\\nDecision scenarios for the managers of coal-­\\nfired power plants\\b\\n117\\n\\t\\n6.3\\t\\nKey parameters in the model and their empirical values\\b\\n126\\n\\t\\n7.1\\t\\nUp-­\\nfront lump-­\\nsum fees of SO2 scrubber technology licenses\\b\\n158\\nTables\\n\\n\\nChina is puzzling to read.\\nAfter the Cultural Revolution and a short transitional period, China entered \\nthe era of Reform and Open-­\\nup in December 1978. The size of China’s economy \\nhas skyrocketed by more than 30 times. Despite numerous benefits, this rapid \\neconomic growth also brought immense pressure on the environment. China’s \\nenvironmental crises are multifaceted, stretching across air, water, soil, ecosystem \\nand climate change.\\nHope was not readily available. As a public good, environmental protection \\nrequires effective governmental intervention. However, China is not a democracy, \\nand sound rule of law has not been established. The country’s governance quality \\nhas been ranked consistently and significantly lower than that in developed coun­\\ntries that are liberal democracies, where environmental quality first deteriorated \\nwith economic growth and then fundamentally improved. Their experiences sug­\\ngest that China’s environmental crises are expected, while their solutions are hard \\nto reach.\\nThen what happened in China in the past 15 years became surprising as the \\nenvironmental trajectory deviated away from the projections. Sulfur dioxide (SO2) \\nis one air pollutant that is crucial for air quality but very difficult to control. Since \\nreaching their peak in the mid-­\\n2000s, SO2 emissions in China have been declin­\\ning, and the downward pace accelerated in the past few years to reach a level not \\nseen in more than four decades. A large coal-fired power sector appeared to install \\nand operate SO2 scrubbers that mitigate emissions from polluting sources. Simi­\\nlar desirable outcomes are also observed in other environmental and renewable \\nenergy fields. However, China has not changed seriously from the perspectives of \\ndemocracy and the rule of law, although environmental policy has been improv­\\ning and strengthening. The legal system still does not play any major role in envi­\\nronmental protection. Policy making lacks transparency and public consultation, \\nwhile policy blunders are not rare. Policy implementation still has considerable \\nproblems and is often selective. It is not unusual to hear about the abuse of gov­\\nernmental authorities.\\nThis book aims to provide a theoretical understanding to explain how China \\nachieved deep and sustained pollution mitigation without democracy and sound \\nrule of law. Causal relationships are explored between the favorable outcome and \\nPreface\\n\\n\\nPreface  xi\\nthe unfavorable path. The major puzzle is why China frequently witnesses both \\nsides at the same time or whether the conventional insights may have missed \\nsomething important in reading China. China’s strategy is theorized into goal-­\\ncentered governance. China is both highly centralized – in goal setting – and \\nhighly decentralized – in goal attainment, policy making and implementation. \\nUnlike the rule-­\\nbased governance in developed countries as indicated in their \\nwell-­\\nestablished rule of law, China places goals in the first place, while deficien­\\ncies in policy making and implementation are much tolerated as long as goals \\ncan be attained. The mitigation trajectory was not centrally planned but gradu­\\nally evolved through decentralized pathfinding under centralized goals. In other \\nwords, the Chinese puzzle should primarily be explained from the perspective of \\nits governance strategy but not individual policies. A strategic mistake is often a \\nlot more devastating and far-­\\nreaching than any policy stumble, while an effective \\nstrategy can accommodate many policy mistakes without compromising much \\nthe final outcome.\\nThe research and thinking for this book stretched over a dozen years. When \\nI first started studying China’s SO2 mitigation around 2007, the hypothesis was \\nthat the environmental crisis was rooted in policy failures and, more fundamen­\\ntally, the lack of democracy and the rule of law. However, what unfolded later \\nforced me to rethink this causal relationship, especially in the 2010s when the \\nmitigation pace dashed forward. As a former physicist, I hope to find a theoretical \\nexplanation to the Chinese puzzle that is simple, like one equation, and rich. The \\ngoal-­\\ncentered governance in this book reflects such a new attempt.\\n\\n\\nI owe a tremendous amount of debts to many people. This book is dedicated \\nto Robert H. Socolow, the supervisor of my PhD thesis at Princeton Univer­\\nsity’s Woodrow Wilson School of Public and International Affairs. His inspi­\\nration is vital in my research journey. Much of this book is rooted although \\nwidely extended from my PhD study over a decade ago. I am grateful for Rob­\\nert H. Williams, Denise L. Mauzerall, Eric D. Larson, Yiguang Ju, Gregory \\nC. Chow, Edward S. Steinfeld, Richard K. Lester and Kin-­\\nChe Lam, whose \\nsupport and insights were crucial to sustain and enlighten this research. My \\ndeep appreciation also goes to numerous interviewees who kindly shared their \\nknowledge. I thank Matthew Shobbrook of Routledge, whom I worked with \\nto finally complete this book.\\nMy wife, Jing Song, and our two children, Anlan Xu and Antao Song, are per­\\npetual motivation and sources of encouragement for my research. My parents, \\nMeilan Yuan and Yicai Xu, and parents-­\\nin-­\\nlaw, Meiyu Song and Changfa Song, \\nprovide patient and unconditional support. My family made this work possible, \\nespecially under the ongoing COVID-­\\n19 pandemic.\\nFunding support throughout this research in the past dozen years was provided \\nby Princeton University, Massachusetts Institute of Technology, The Chinese \\nUniversity of Hong Kong, and Hong Kong Research Grants Council (General \\nResearch Fund, 14654016).\\nParts of the book were adapted with permissions from the author’s several pub­\\nlished journal articles, including Xu, Y. 2011. The use of a goal for SO2 mitigation \\nplanning and management in China’s 11th five-­\\nyear plan. Journal of Environmen­\\ntal Planning and Management, 54, 769–783 [in Chapter 4; Copyright (2011) Tay­\\nlor & Francis]; Xu, Y. 2011. Improvements in the operation of SO2 scrubbers in \\nChina’s coal power plants. Environmental Science & Technology, 45, 380–385 [in \\nChapter 6; Copyright (2011) American Chemical Society]; Xu, Y. 2011. China’s \\nfunctioning market for sulfur dioxide scrubbing technologies. Environmental Sci­\\nence & Technology, 45, 9161–9167 [in Chapter 7; Copyright (2011) American \\nChemical Society]; Xu, Y. 2013. Comparative advantage strategy for rapid pol­\\nlution mitigation in China. Environmental Science & Technology, 47, 9596–9603 \\n[in Chapter 7; Copyright (2013) American Chemical Society]. Much has been \\nrevised and expanded on. \\nAcknowledgments\\n\\n\\n1  \\u0007\\nChina’s environmental crises\\nChina faces colossal, multifaceted environmental challenges, many at crisis lev­\\nels. Its environmental degradation has been widely documented and analyzed in \\nacademic studies as well as in public media. China is now the largest energy \\nconsumer, supplier and emitter of most major air and water pollutants as well as \\nvarious greenhouse gases. Together with its geographically high population and \\neconomic densities, especially in the eastern half of the country, China was cat­\\negorized at the very bottom of air quality among the 180 countries and regions in \\nthe Environmental Performance Index (Wendling et al., 2018; Figure 1.1). Few \\nreaders would be surprised to know that China’s air quality is among the most \\npolluted in the world (Figure 1.1).\\nAir and water pollution in China have certainly taken a serious toll. China has \\nmade steady progress in the past decades to significantly reduce premature deaths \\ndue to water-­\\nrelated environmental factors and indoor air pollution, but ambi­\\nent particulate matter (PM) pollution has been deteriorating. The Global Burden \\nof Disease study elaborates in great detail the causes and risk factors of deaths \\nacross individual countries (Institute for Health Metrics and Evaluation, 2018). In \\n1990, China accounted for 22.2% of the global population, and in 2017, the share \\ndropped to 18.5% despite an 18.0% increase in absolute population (Figure 1.2). \\nIn premature deaths that are due to environmental risk factors, China’s share in the \\nworld in 1990 was 29.2% for household air pollution from solid fuels and 4.6% \\nfor unsafe water, sanitation and handwashing. In other words, an average Chinese \\nwas 31.5% more likely and 79.3% less likely to die prematurely due to the two \\nrisks than an average person in the world. The shares were significantly reduced \\nto 16.5% and 0.6% in 2017, respectively, to make an average Chinese 10.6% and \\n96.8% less likely to die prematurely. In absolute terms, they were reduced by \\n65.7% and 92.5%, respectively. However, ambient PM pollution caused 404,000 \\npremature deaths in 1990 and 852,000 in 2017, more than double. Its global share \\nclimbed from 23.0% to 29.0% over the period. In 2000, indoor air pollution was \\novertaken by ambient PM pollution in causing more premature deaths. In com­\\nparison to China’s share of the global population, in 1990, an average Chinese \\nfaced only a slightly greater risk, 3.8%, from ambient PM pollution than an aver­\\nage person in the world, but in 2017, the risk premium was enlarged to 56.9%.\\n1\\t\\n\\u0007\\nIntroduction\\n\\n\\n2  Introduction\\nChina\\nUS\\nIndia\\nJapan\\nSouth Korea\\nUK\\n0\\n10\\n20\\n30\\n40\\n50\\n60\\n70\\n80\\n90\\n100\\n0\\n20\\n40\\n60\\n80\\n100\\nAir quality\\nAir pollution\\nFigure 1.1  \\u0007\\nEnvironmental Performance Index in the baseline year\\nSource: Wendling et al. (2018).\\nNote: “Air pollution” at the x-axis refers to sulfur dioxide (SO2) and nitrogen oxide (NOx) emission inten­\\nsities, and its baseline year is 2006. “Air quality” in the y-axis indicates household solid fuels (baseline \\nyear: 2005), fine particulate matter (PM2.5) exposure and PM2.5 exceedance (baseline year: 2008).\\n0.0%\\n5.0%\\n10.0%\\n15.0%\\n20.0%\\n25.0%\\n30.0%\\n0\\n150,000\\n300,000\\n450,000\\n600,000\\n750,000\\n900,000\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\nChina’s share in the world\\n)\\ns\\nn\\no\\ns\\nr\\ne\\np\\n(\\n \\ns\\nh\\nt\\na\\ne\\nd\\n \\ne\\nr\\nu\\nt\\na\\nm\\ne\\nr\\nP\\nYear\\nAmbient particulate matter pollution\\nHousehold air pollution from solid fuels\\nUnsafe water, sanitation and handwashing\\nShare of population\\nFigure 1.2  \\u0007\\nChina’s premature deaths due to air and water pollution in the Global Burden \\nof Disease study\\nSource: Institute for Health Metrics and Evaluation (2018).\\nNote: Solid lines indicate absolute numbers in persons with the left y-axis, while dashed lines refer to \\nChina’s shares in the world with the right y-axis.\\n\\n\\nIntroduction  3\\nAnother measurement of pollution’s health impact is the disability-­\\nadjusted life \\nyears (DALYs) that quantifies the loss of “healthy” life years. It combines the lost \\nlife years due to both premature deaths and illnesses. Various types of environmental \\npollution in different countries may cause premature deaths and illnesses that cor­\\nrespond to different life expectancies, ages and other situations. The ratio between \\nDALYs and premature deaths is much higher for water pollution than for air pollu­\\ntion. For example, in 2017, China lost 19.8 million, 6.46 million and 0.85 million \\nDALYs due to ambient PM pollution, household air pollution from solid fuels, and \\nunsafe water, sanitation and handwashing, respectively. The corresponding ratios \\nbetween DALYs and premature deaths were 23.3, 23.8 and 89.0, respectively, to \\nindicate the more severe health impacts of water pollution for an average case.\\nNevertheless, the indicator of DALYs does not change the conclusion that was \\npresented with the examination of premature deaths (Figure 1.3). Substantial pro­\\ngress was also made on indoor air pollution and water, with their DALYs being \\nreduced by 77.3% and 92.0%, while the deterioration trend for ambient PM pol­\\nlution is distinguished with an increase of DALYs by 47.3%. In terms of China’s \\nshares in the world, ambient PM pollution is still the only risk factor among the \\nthree to surpass that of its population, which accounted for 23.8% of the world’s \\ntotal in 2017. For all DALYs due to the three environmental risk factors, ambient \\nPM pollution’s share rose from 25.6% in 1990 to 73.0% in 2017. Accordingly, \\n0.0%\\n5.0%\\n10.0%\\n15.0%\\n20.0%\\n25.0%\\n30.0%\\n0\\n5\\n10\\n15\\n20\\n25\\n30\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\nChina’s share in the world\\n)\\ns\\nr\\na\\ne\\ny\\n \\n0\\n0\\n0\\n,\\n0\\n0\\n0\\n,\\n1\\n(\\n \\ns\\nY\\nL\\nA\\nD\\nYear\\nAmbient particulate matter pollution\\nHousehold air pollution from solid fuels\\nUnsafe water, sanitation and handwashing\\nShare of population\\nFigure 1.3  \\u0007\\nDisability-adjusted life years (DALYs) in China due to air and water pollution \\nin the Global Burden of Disease study\\nSource: Institute for Health Metrics and Evaluation (2018).\\n\\n\\n4  Introduction\\nenvironmental pollution in China is more and more dominated by ambient air \\npollution and especially PM pollution.\\nOn average, the DALYs due to various environmental risks indicate that an \\naverage Chinese loses a significant number of healthy life days for every year liv­\\ning in these environmental risks. In 1990, household air pollution from solid fuels \\nwas the most severe environmental risk in China to incur the loss of 8.7 disability-­\\nadjusted life days (DALDs) per person, while the damages from ambient PM \\npollution and from unsafe water, sanitation and handwashing were similar at 4.1 \\nand 3.2 DALDs per person, respectively (Figure 1.4). In other words, an average \\nChinese lost 16.0 health life days due to the three air and water pollution risk \\nfactors for living through 1990. In 2017, ambient PM pollution became the most \\nsevere risk factor, being responsible for 5.1 DALDs per person or 1.0 DALDs \\nmore, after the other two experienced dramatic improvement in the past decades. \\nThe total loss was 7.0 DALDs for living through 2017.\\nChina is not a unique country to witness the diverging progress of different risk \\nfactors. India had similar paths for distinguishing the rising importance of ambi­\\nent PM pollution in environmental protection. Ambient PM pollution in India \\nhas remained stable throughout the years to account for 5.7 and 5.6 DALDs per \\nperson in 1990 and 2017, respectively. Although household air pollution from \\nsolid fuels still claimed greater health damages in 2017, its steady declining trend \\n0\\n5\\n10\\n15\\n20\\n25\\n30\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\n)\\nr\\na\\ne\\ny\\n \\nr\\ne\\np\\n \\nn\\no\\ns\\nr\\ne\\np\\n \\nr\\ne\\np\\n \\ns\\ny\\na\\nd\\n(\\n \\ns\\nY\\nL\\nA\\nD\\nYear\\nChina: Ambient particulate matter pollution\\nChina: Household air pollution from solid fuels\\nChina: Unsafe water, sanitation and handwashing\\nIndia: Ambient particulate matter pollution\\nIndia: Household air pollution from solid fuels\\nIndia: Unsafe water, sanitation and handwashing\\nFigure 1.4  \\u0007\\nDALYs in days (or disability-adjusted life days [DALDs]) per person per year \\nin China and India\\nSource: Institute for Health Metrics and Evaluation (2018).\\n\\n\\nIntroduction  5\\nsuggests that ambient PM pollution will soon become the most damaging environ­\\nmental risk among the three in India as well (Figure 1.4).\\n2  \\u0007\\nChina’s expected rise of SO2 emissions and unexpected \\nsuccess in SO2 mitigation\\nChina has been rapidly industrializing in the past four decades. Environmental cri­\\nses can be empirically expected in the contexts of its rapid economic development, \\nrising energy consumption and coal dominance. The expectation also comes from \\ncrucial governance factors that are believed to be favorable for environmental tran­\\nsition but that China is especially weak at. First, democracy is believed to be good \\nfor environmental protection by many scholars (e.g., Payne, 1995). Unfortunately, \\nChina is not a democracy, and thus, society’s demand for cleaner air is often not \\nbelieved to be able to effectively influence policy making as in a democracy. It is \\ngenerally ranked at the bottom of various democracy indexes. According to Polity’s \\nratings that can reflect the common views of democracy evaluation at least in West­\\nern liberal democracies, modern-­\\nday China, under the communist rule, is debatably \\nless democratic than the imperial days in the 19th-­\\ncentury Qing dynasty, when the \\nemperors still held absolute power, with the Polity index being −6 (Marshall et al., \\n2019). China’s economic reform era after the Cultural Revolution only slightly \\n–10\\n–8\\n–6\\n–4\\n–2\\n0\\n2\\n4\\n6\\n8\\n10\\n1980\\n1985\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\nPolity Index (–10 ~10) \\nYear\\nChina\\nSouth Korea\\nSouth Korea\\nIndia\\nUnited States\\nSingapore\\nFigure 1.5  \\u0007\\nPolity Democracy Index for China, South Korea, Singapore, India and the \\nUnited States (−10 being the most autocratic and 10 the most democratic)\\nSource: Marshall et al. (2019).\\n\\n\\n6  Introduction\\nimproved its Polity index from −8 to −7 (Figure 1.5). In comparison, South Korea \\nwas fundamentally transformed from an authoritarian regime to a democratic one \\nafter the reform in the 1980s. Singapore is steadily ranked toward the authoritarian \\nside. India and the United States are standard democracies despite slight fluctuations.\\nDemocratic states are argued to be more responsive to the public’s demands. If the \\npublic in a democracy gives top priority to environmental matters, strong political \\nwill is more likely to be generated (Li and Reuveny, 2006; Payne, 1995; Downey and \\nStrife, 2010). Furthermore, the public in a democracy could be more pro-­\\nenvironment \\nthan are the elites in an autocracy; this could be because of better access to informa­\\ntion, a more developed civil society and a longer time horizon of planning (Li and \\nReuveny, 2006; Payne, 1995). Democracy is generally closely associated with the \\nrule of law, and therefore, there should be better enforcement of environmental regu­\\nlations (Li and Reuveny, 2006). Nevertheless, democracy might also be associated \\nwith weakness in environmental protection. People’s self-­\\ninterest and the interests of \\nbusiness are more difficult to overcome in a democracy (Li and Reuveny, 2006). If \\nthe public gives only a low priority to having a clean environment, then a democracy \\ncould be less likely to heavily focus on environmental protection.\\nEmpirical statistical studies have found no conclusive relationship between \\ndemocracy and the environment. Congleton (1992) and Neumayer (2002) found \\nthat democracy contributes positively to international environmental commit­\\nments. Midlarsky (1998) discovered that democracy leads to more protected \\nareas of land, but that it tends to negatively influence deforestation and carbon \\ndioxide (CO2) emissions per capita. Winslow (2005) found only good effects of \\ndemocracy, whereas Pellegrini and Gerlagh (2006) found that it had insignificant \\nimpacts. The mixed results of the relationship could be at least partly caused by \\nthe difference in environmental indicators. For example, CO2 is more difficult \\nto abate, but it has much less local influence than urban particulate pollution. \\nStudies that used panel data also reported mixed results regarding the relation­\\nship (Torras and Boyce, 1998; Barrett and Graddy, 2000). Different democracy \\nindexes do not differ greatly in their relationship to the environment. A prob­\\nlem in the literature is that a linear relationship is generally assumed between \\ndemocracy and the environment. However, theoretical arguments might suggest \\nthat both democracy and autocracy could have a beneficial effect on environ­\\nmental protection, while regimes in between make the situation worse. Among \\ncontrol variables, the most common one is income. Considering the literature on \\nthe Environmental Kuznets Curve and a plausible relationship between income \\nand the environment (Grossman and Krueger, 1995; Stern and Common, 2001), \\nincome together with its squared and cubed terms are necessary control vari­\\nables. One study that did not include income as an independent variable could \\nsuffer from potential missing-­\\nvariable problems (Winslow, 2005). In addition, \\ntwo studies controlled a governance index, namely, that of corruption (Pellegrini \\nand Gerlagh, 2006; Buitenzorgy and Mol, 2011), but most of them disregarded \\ngovernance. Various studies differ greatly from each other in how they control \\nother variables, including trade openness (Li and Reuveny, 2006), inequality/\\nGini ratio (Torras and Boyce, 1998), energy resource endowment (Congleton, \\n\\n\\nIntroduction  7\\n1992), country size in gross domestic product (GDP; Winslow, 2005), population \\nsize (Neumayer, 2002; Congleton, 1992) and literacy (Torras and Boyce, 1998).\\nCase studies found no conclusive relationship either. A case study in Kenya \\nfound that democracy is benign to the environment; this is because the government \\nresponded mainly to the “environmental and developmental civil society” and \\n“Western supporters” rather than to the “marginalized poor” (Njeru, 2010). On the \\nother hand, democratization in a number of southern African countries, particu­\\nlarly Malawi, South Africa and Mozambique, has resulted in greater destruction \\nof the environment for short-­\\nterm economic and social reasons (Walker, 1999). \\nIn Mexico City, it has been found that democratic elections do not assist in stop­\\nping local deforestation (Hagene, 2010). Through studying China and Southeast \\nAsia, it is even proposed that “ ‘good’ authoritarianism” is essential for solving \\nour urgent environmental problems (Beeson, 2010). A case study in Guatemala \\nfound that the relationship between democracy and the environment is complex \\nand not straightforward (Sundberg, 2003).\\nIn addition, the empirical relationship between economic development and \\nenvironmental quality did not expect that China would be able, or willing, to \\npull down its pollutant emissions and improve air quality. Environmental Kuznets \\nCurve – an empirical bell-­\\nshaped relationship between income level and environ­\\nmental quality – predicts that before a country becomes rich enough to reach a \\ncertain level of income (or GDP per capita), its environmental quality will keep \\n0\\n10,000\\n20,000\\n30,000\\n40,000\\n50,000\\n60,000\\n1980\\n1985\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\n)\\np\\na\\nc\\n/\\n$\\nS\\nU\\n \\n1\\n1\\n0\\n2\\n \\n,\\nP\\nP\\nP\\n(\\n \\na\\nt\\ni\\np\\na\\nc\\n \\nr\\ne\\np\\n \\nP\\nD\\nG\\nYear\\nSouth Korea\\nChina\\nJapan\\nUnited States\\nFigure 1.6  \\u0007\\nGDP per capita in PPP (purchasing power parity) in China, South Korea, Japan \\nand the United States\\nSource: IMF (2019).\\n\\n\\n8  Introduction\\ndeteriorating (Grossman and Krueger, 1995). China’s GDP per capita in purchas­\\ning power parity and constant 2011 dollars in 2018 was US$16,100, and the Inter­\\nnational Monetary Fund projected that it would rise to US$22,200 in 2024, while \\nthe level was US$29,100 in the United States in 1980 (Figure 1.6). In other words, \\nChina is about five decades behind the United States in terms of economic devel­\\nopment status. Different studies report different turning points, and the lowest one \\nfor SO2 emissions is at about US$3,000 (in 1990 US$ and nominal exchange rates) \\n(Stern and Common, 2001). China’s GDP per capita only surpassed US$3,000 per \\ncapita in nominal terms in 2008 (IMF, 2019), which was still much lower than the \\nempirical minimum turning point.\\nFurthermore, environmental governance is critical to provide better environ­\\nmental quality as a public good. As suggested in the World Bank’s six governance \\nindicators, comparatively China is poorly governed (Kaufmann and Kraay, 2019). \\nThe indicators assigned a score between −2.5 (worst) and 2.5 (best) to indicate \\ngovernance performance. On “voice and accountability,” China scored consist­\\nently and significantly lower than democracies, such as the United States and India. \\nTheir average scores from 1996 to 2018 were −1.58, 1.18 and 0.42, respectively \\n–2.50\\n–2.00\\n–1.50\\n–1.00\\n–0.50\\n0.00\\n0.50\\n1.00\\n1.50\\n2.00\\n1996\\n2000\\n2003\\n2005\\n2007\\n2009\\n2011\\n2013\\n2015\\n2017\\nGovernance indicators (–2.5 ~ 2.5)\\nYear\\nVoice_China\\nVoice_India\\nVoice_US\\nLaw_China\\nLaw-India\\nLaw-US\\nFigure 1.7  \\u0007\\nGovernance indicators of China, India and the United States\\nSource: Kaufmann and Kraay (2019).\\nNote: “Voice”: Voice and accountability “reflects perceptions of the extent to which a country’s citi­\\nzens are able to participate in selecting their government, as well as freedom of expression, freedom of \\nassociation, and a free media.” “Law”: Rule of law measures “perceptions of the extent to which agents \\nhave confidence in and abide by the rules of society, and in particular the quality of contract enforce­\\nment, property rights, the police, and the courts, as well as the likelihood of crime and violence.”\\n\\n\\nIntroduction  9\\n(Kaufmann and Kraay, 2019; Figure 1.7). It suggests that Chinese citizens are \\nless able to directly participate in selecting a government and that their voices are \\nless likely to be heard. In terms of “political stability and absence of violence/\\nterrorism,” China scored −0.44, better than India’s −1.13 but worse than United \\nStates’ 0.48. “Government effectiveness” measures the provision of public and \\ncivil services as well as the quality of policy making and implementation. It is the \\ngovernance indicator that China had the best performance. It is also the only one \\nthat China’s score is positive, being 0.09 on average, and consistently improved \\nfrom −0.35 in 1996 to 0.48 in 2018 (Kaufmann and Kraay, 2019). Nevertheless, \\nChina is still much behind the United States that scored 1.58 in 2018. For the “rule \\nof law” indicator, China performs poorly with an average score of −0.46, much \\nlower than the United States’ 1.58 and India’s 0.07 (Figure 1.7). Although slight \\nprogress was made in China from −0.55 in 1996 to −0.20 in 2018, it was always \\nlocated in the negative territory. Little progress was achieved on “corruption” as \\nthe score remained consistently low with an average of −0.41, which was poorer \\nthan the 1.47 in the United States and −0.38 in India (Kaufmann and Kraay, 2019). \\nChina performed steadily poor in “regulatory quality” that focuses on the private \\nsector. The United States scored 1.51 on average for the 1996–2018 period, much \\nbetter than China’s −0.25 or India’s −0.36 (Kaufmann and Kraay, 2019). These \\ngovernance indicators quantitatively measure various aspects of governance in a \\ncountry to enable comparison across countries and years. As a classical example \\nof market failure to demand governmental intervention, environmental protec­\\ntion cannot be effective without effective governance. However, none of the six \\ngovernance indicators suggest that the Chinese government can sustainably, effec­\\ntively and efficiently enact and implement environmental policies and laws.\\nWith all the unfavorable conditions and rising environmental pressures from \\nenergy consumption, little hope existed to make China’s environmental cleanup \\npromising. SO2 is one of the most important air pollutants, and it was also the \\nfirst air pollutant explicitly included in the national Five-­\\nYear Plans for serious \\nmitigation (National People’s Congress, 2006). Its emissions were more than \\ndoubled from 1980 to the 2000s to echo such expectations (Figure 1.8). How­\\never, something has obviously worked as indicated in the more recent trajectory \\nof SO2 emissions (Figure 1.8). Multiple data sources – from Chinese official sta­\\ntistics, independent bottom-­\\nup and top-­\\ndown estimates inside and outside of the \\ncountry to satellite and remote sensing data – all point to the same trend: China’s \\nSO2 emissions have been rapidly decreasing in the past decade (Li et al., 2017; \\nZheng et al., 2018; Lu et al., 2011; Crippa et al., 2018; Fioletov et al., 2019; \\nNational Statistics Bureau and Ministry of Ecology and Environment, 2019). \\nAlthough different emission inventories still show gaps between each other on \\nwhen peak SO2 emissions happened and how high they reached, China should \\nhave completely wiped out all additional SO2 emissions that accompanied its \\nunprecedented economic growth in the past four decades (Figure 1.8). Although \\nChina’s economy has expanded by more than 30-­\\nfold since the Open-­\\nup policy \\nwas initiated in 1978, the country now emits significantly less SO2 (Figure 1.8). \\nIt seems to have taken China less than one decade to remove all the additional \\n\\n\\n10  Introduction\\nSO2 emissions that the country increased with its economic development and \\nenergy consumption.\\nWith the rapid electrification trend of energy consumption and the power sec­\\ntor’s increasing share of coal consumption, the power sector is becoming more \\nand more important in deciding the trajectory of China’s SO2 mitigation. In \\n1980, its share of SO2 emissions was only 22.5%, less than the industrial sec­\\ntor’s 50.0% and the residential sector’s 23.5% (Figure 1.9). The relatively less \\nsignificance was due to the power sector’s low share of coal consumption, 20.2% \\n(Figure 1.10). In the following two decades, the power sector’s share climbed \\ncontinuously to peak in 2002 at 45.7% and surpass that of the industrial and resi­\\ndential sectors (Figure 1.9) together with its 52.2% share of coal consumption \\n(Figure 1.10). However, these two trajectories started to diverge from each other \\nafterward (Figure 1.10). In 2017, the power sector consumed 57.3% of China’s \\ncoal but only accounted for 17.4% of SO2 emissions (Figure 1.9). The industrial \\nand residential sectors’ shares rebounded to reach 56.8% and 22.6%, respectively. \\nAccordingly, the power sector now emits much less SO2 for consuming one unit \\nof coal than the industrial and residential sectors do.\\nAlthough energy transition away from coal is favorable for SO2 mitigation, coal \\nconsumption in China still remains at a high level, with only a slight decrease \\n0\\n5,000\\n10,000\\n15,000\\n20,000\\n25,000\\n30,000\\n35,000\\n1980\\n1985\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\nSO2 emissions (1,000 tons)\\nYear\\nOfficial\\nEDGAR\\nLu et al., 2011\\nZheng et al., 2018\\nFioletov et al., 2019\\nFigure 1.8  \\u0007\\nSO2 emissions in China\\nSource: Data from Fioletov et al. (2019) refer to large power plants, while others are for China as a \\nwhole (Zheng et al., 2018; Lu et al., 2011; Crippa et al., 2018; Fioletov et al., 2019; National Statistics \\nBureau and Ministry of Ecology and Environment, 2019).\\n\\n\\nIntroduction  11\\n0%\\n10%\\n20%\\n30%\\n40%\\n50%\\n60%\\n70%\\n0\\n5\\n10\\n15\\n20\\n25\\n30\\n35\\n1970 1974 1978 1982 1986 1990 1994 1998 2002 2006 2010 2010 2014\\nShares in SO2 emissions\\nSO2 emissions (million tons)\\nPower\\nIndustry\\nResidential\\nOthers\\nPower’s share (right)\\nIndustry’s share (right)\\nResidential’s share (right)\\nYear\\nFigure 1.9  \\u0007\\nSO2 emissions by sector in China (from two different data sources for 1970–\\n2012 and 2010–2017, respectively)\\nSource: Crippa et al. (2018); Zheng et al. (2018).\\n0\\n500\\n1,000\\n1,500\\n2,000\\n2,500\\n3,000\\n3,500\\n0%\\n10%\\n20%\\n30%\\n40%\\n50%\\n60%\\n70%\\n80%\\n90%\\n100%\\n1950\\n1960\\n1970\\n1980\\n1990\\n2000\\n2010\\nCoal consumption (Mtce)\\n \\ne\\nr\\na\\nh\\ns\\n \\ns\\nr’\\no\\nt\\nc\\ne\\ns\\n \\nr\\ne\\nw\\no\\nP\\nYear\\nPower’s share of coal consumption: China\\nPower’s share of coal consumption: U.S.\\nPower’s share of SO2 emissions (EDGAR)\\nPower’s share of SO2 emissions (Zheng et al., 2018)\\nTotal coal consumption: China (right)\\nFigure 1.10  \\u0007\\nThe power sector’s shares of coal consumption and SO2 emissions in China \\nand the United States\\nSource: EIA (2019); Fridley and Lu (2016); National Bureau of Statistics (2019).\\n\\n\\n12  Introduction\\nin recent years (Figure  1.10). Most mitigation of absolute SO2 emissions was \\nbecause much greater SO2 emissions are avoided per unit of coal consumption. \\nThe power sector’s high efficiency in removing SO2 is also reflected in its SO2 \\nemission intensity of coal-­\\nfired electricity. Since the enactment of the Clean Air \\nAct Amendments (1990), the United States has substantially reduced its overall \\nSO2 emissions from 20.9 million tons in 1990 to 2.48 million tons in 2018 (Fig­\\nure 1.11). The power sector has consistently been the largest contributor, and its \\nSO2 emissions dropped from 14.4 million tons to 1.19 million tons over the same \\nperiod, while its share declined from 68.9% to 47.8%. The much higher share than \\nChina’s reflects the power sector’s greater importance in U.S. coal consumption \\n(Figure 1.10).\\nIn reference to the successful progress in the United States, China’s SO2 miti­\\ngation trajectory was even steeper. In 1990, for generating 1 kWh of coal-­\\nfired \\nelectricity, 8.4 g of SO2 were emitted in the United States, while the rate was \\n58.5% higher, or 13.3 g in China. In 2017, as calculated with independent emis­\\nsion inventory data, the SO2 intensity decreased to be 0.96 g in the United States \\nand 0.41 g in China, 56.9% lower (Figure 1.11).\\n0%\\n10%\\n20%\\n30%\\n40%\\n50%\\n60%\\n70%\\n80%\\n0\\n5\\n10\\n15\\n20\\n25\\n1985\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\nPower sector’s share of SO2 emissions\\nSO2\\nO\\nS\\n \\n&\\n \\n)\\ns\\ne\\nn\\nn\\no\\nt\\n \\nn\\no\\ni\\nl\\nl\\ni\\nm\\n(\\n \\n.\\nS\\n.\\nU\\n \\ne\\nh\\nt\\n \\nn\\ni\\n \\ns\\nn\\no\\ni\\ns\\ns\\ni\\nm\\ne\\n2\\nl\\na\\no\\nc\\n \\nf\\no\\n \\ny\\nt\\ni\\ns\\nn\\ne\\nt\\nn\\ni\\n-\\nO\\nS\\n \\ng\\n(\\n \\ny\\nt\\ni\\nc\\ni\\nr\\nt\\nc\\ne\\nl\\ne\\n \\nd\\ne\\nr\\ni\\nf\\n2/kWh)\\nYear\\nPower\\nIndustry\\nOthers\\nIntensity: U.S.\\nIntensity: China (EDGAR)\\nIntensity: China (Zheng et al., 2018)\\nPower’s share (right)\\nFigure 1.11  \\u0007\\nSO2 emissions in the United States and SO2 intensities in China and the United \\nStates\\nSource: Crippa et al. (2018); Zheng et al. (2018); BP (2019); U.S. EPA (2019).\\n\\n\\nIntroduction  13\\n3  \\u0007\\nThe organization of this book\\nDemocracy and rule of law have played prominent and indispensable roles in \\nenvironmental cleanup in developed countries. However, China is not a democ­\\nracy and political freedom is indeed highly constrained, but why environmen­\\ntal protection became the country’s priority to witness a dramatic drop in SO2 \\nemissions? Furthermore, many policies are not implemented well, and the legal \\nsystem plays an essentially negligible role in China’s environmental protection. \\nBut why the government was able to effectively bend down pollutant emissions at \\nsuch an astonishing pace? This book focuses on how China defied the empirical \\nexpectations in SO2 mitigation, especially in the coal-­\\nfired power sector. It aims to \\nprovide an explanation at the strategic level for understanding how environmental \\ngovernance is organized and implemented in China.\\nThis book also aims to imply China’s governance in general. Observers on \\nChina’s governance often have polarized views and each side seems to have \\nample supporting evidence. Regardless of what the focused perspective is, \\nChina is full of puzzles and controversies. The country has made many remark­\\nable achievements in the past 40 years, with much higher income and living \\nstandards, much better infrastructures, much wider social safety nets, much less \\ncontrol of individuals’ private lives and much less poverty. It leads the world \\nin renewable energy development and electric vehicles. However, rules are \\nmuch less respected in China than in developed countries. The parliament – the \\nNational People’s Congress – is often referred to as a “rubber stamp,” although \\nin the Chinese Constitution, it has the utmost authority beyond any governmen­\\ntal entity. The judicial system is not independent. Political liberty is much con­\\nstrained without genuine elections. The Chinese Communist Party has almost \\nunchecked power, and the authoritarian country is ruled from the top, but an \\noften-­\\nheard sentence in China goes that “policies and orders cannot go beyond \\nZhongnanhai” (the compound where the central government is located). How \\nshould we explain China’s governance and reconcile the polarized observations \\nthat are both well documented and evidence-­\\nbased? Are the two sides caus­\\nally connected? How can China achieve those favorable outcomes with such \\nan unfavorable policy pathway? If we repair all recognized deficiencies in the \\ngovernance, are we going to throw away the baby together with the bathwater? \\nMost important, does China follow a different governance model from that in \\ndeveloped countries, and thus, is the explanatory power of many theories and \\nhistorical experiences reduced?\\nThe rest of the book is organized as follows: Chapters 2, 3 and 4 examine how \\nthe Chinese government is organized for environmental protection, especially in the \\ncontexts of neither democracy nor sound rule of law. Chapter 2 explores how the \\npolitical will for environmental protection has been centrally evolving without \\ndemocracy. Chapter 3 discusses China’s environmental governance structure that \\ncombines high degrees of both centralization and decentralization from different \\n\\n\\n14  Introduction\\nperspectives. Primary focuses are on the evolution of the Ministry of Ecology \\nand Environment and the relationships between the central and local govern­\\nments. Chapter 4 studies how prioritized environmental protection is transmitted \\nfrom the central government to local governments for their effective mobilization \\nagainst the background of a weak rule of law. The environmental governance is \\norganized to center on goals, specifically on SO2 emissions and environmental \\nprotection in Five-­\\nYear Plans. This book calls the governance strategy in China \\nas the goal-­\\ncentered governance model that features centralized goal setting and \\ndecentralized goal attainment.\\nChapters 5, 6 and 7 analyze the impacts of China’s goal-­\\ncentered governance \\nmodel. Chapter 5 focuses on decentralized policy making for SO2 mitigation that \\nis guided by centralized, top-­\\ndown goals. This integration of centralization and \\ndecentralization has generated not only profound outcomes, with active policy \\nmaking, innovation and competition, but also many policy deficiencies. China’s \\ngovernance is tolerant of mistakes or even abuses in policy making, as long as \\ngoals can be achieved. Such tolerance then significantly reduces the requirements \\nfor policy making quality, choices of policy instruments and inter-­\\npolicy coordi­\\nnation. Chapter 6 explores how this goal-­\\ncentered governance has exerted impacts \\non decentralized policy implementation. From unfavorable backgrounds of inad­\\nequate capacity, effectiveness and efficiency of environmental policy implemen­\\ntation, local governments make gradual and steady improvements that aim for \\napproaching their assigned goals. Chapter 7 addresses how China overcame sup­\\nply constraints and established its domestic SO2 scrubber industry for meeting the \\nskyrocketing demand. Decentralized market entities were able to actively seek \\nand capture market opportunities under goal-­\\ncentered governance. Goals on envi­\\nronmental protection and economic development could thus achieve better syner­\\ngies than conflicts.\\nChapter  8 concludes this book and discusses the goal-­\\ncentered governance \\nmodel. This theoretical framework can integrate the polarized observations on \\nChina within a systematic and compatible understanding. The rule-­\\nbased govern­\\nance model is the primarily applied strategy in countries with sound rule of law \\nthat emphasizes on making good, often centralized policies as means, but the \\nfinal outcome is less explicit. In contrast, this goal-­\\ncentered governance model \\nemphasizes centralized goals as ends but is more relaxed on the means to result \\nin many policy deficiencies. In the contexts of China’s backgrounds of no democ­\\nracy and weak rule of law, this governance strategy has been proved effective \\nnot only on SO2 mitigation but also very likely on other prioritized governmental \\naffairs. China is also applying the same strategy in governing CO2 mitigation. \\nOther countries may also find this alternative governance model helpful in con­\\ntributing solutions to their major public problems.\\nReferences\\nBarrett, S. & Graddy, K. 2000. Freedom, growth, and the environment. Environment and \\nDevelopment Economics, 5, 433–456.\\n\\n\\nIntroduction  15\\nBeeson, M. 2010. The coming of environmental authoritarianism. Environmental Politics, \\n19, 276–294.\\nBP. 2019. Statistical review of world energy [Online]. Available: https://www.bp.com/\\ncontent/dam/bp/business-­\\nsites/en/global/corporate/pdfs/energy-­\\neconomics/statistical-­\\nreview/bp-­\\nstats-­\\nreview-­\\n2019-­\\nfull-­\\nreport.pdf.\\nBuitenzorgy, M. & Mol, A. P. J. 2011. Does democracy lead to a better environment? \\nDeforestation and the democratic transition peak. Environmental & Resource Economics, \\n48, 59–70.\\nCongleton, R. D. 1992. Political-­\\ninstitutions and pollution-­\\ncontrol. Review of Economics \\nand Statistics, 74, 412–421.\\nCrippa, M., Guizzardi, D., Muntean, M., Schaaf, E., Dentener, F., Van Aardenne, J. A., \\nMonni, S., Doering, U., Olivier, J. G. J., Pagliari, V. & Janssens-­\\nMaenhout, G. 2018. \\nGridded emissions of air pollutants for the period 1970–2012 within Edgar v4.3.2. Earth \\nSystem Science Data, 10, 1987–2013.\\nDowney, L.  & Strife, S. 2010. Inequality, democracy, and the environment. Organiza­\\ntion & Environment, 23, 155–188.\\nEIA. 2019. International energy statistics. Washington, DC: U.S. Energy Information \\nAdministration.\\nFioletov, V., McLinden, C., Krotkov, N., Li, C., Leonard, P., Joiner, J. & Carn, S. 2019. \\nMulti-­\\nsatellite air quality sulfur dioxide (SO2) database long-­\\nterm L4 global V1. God­\\ndard Earth Science Data and Information Services Center (GES DISC) [Online]. Avail­\\nable: https://disc.gsfc.nasa.gov/datasets/MSAQSO2L4_1/summary.\\nFridley, D. & Lu, H. 2016. China energy databook version 9.0. Berkeley, CA: Lawrence \\nBerkeley National Laboratory.\\nGrossman, G. M. & Krueger, A. B. 1995. Economic-­\\ngrowth and the environment. Quar­\\nterly Journal of Economics, 110, 353–377.\\nHagene, T. 2010. Everyday political practices, democracy and the environment in a native \\nvillage in Mexico city. Political Geography, 29, 209–219.\\nIMF. 2019. World economic outlook database October 2019 [Online]. Available: https://\\nwww.imf.org/en/Publications/SPROLLs/world-­\\neconomic-­\\noutlook-­\\ndatabases#sort=\\n%40imfdate%20descending.\\nInstitute for Health Metrics and Evaluation. 2018. Global burden of disease (GBD) 2017 \\nstudy [Online]. Available: https://www.thelancet.com/journals/lancet/article/PIIS0140-\\n­\\n6736(18)32279-­\\n7/fulltext.\\nKaufmann, D.  & Kraay, A. 2019. The worldwide governance indicators 2019 update: \\nAggregate governance indicators 1996–2018 [Online]. Available: https://papers.ssrn.\\ncom/sol3/papers.cfm?abstract_id=1682130.\\nLi, C., McLinden, C., Fioletov, V., Krotkov, N., Carn, S., Joiner, J., Streets, D., He, H., Ren, \\nX. R., Li, Z. Q. & Dickerson, R. R. 2017. India is overtaking China as the world’s largest \\nemitter of anthropogenic sulfur dioxide. Scientific Reports, 7.\\nLi, Q.  & Reuveny, R. 2006. Democracy and environmental degradation. International \\nStudies Quarterly, 50, 935–956.\\nLu, Z., Zhang, Q. & Streets, D. G. 2011. Sulfur dioxide and primary carbonaceous aero­\\nsol emissions in China and India, 1996–2010. Atmospheric Chemistry and Physics, 11, \\n9839–9864.\\nMarshall, M. G., Gurr, T. R. & Jaggers, K. 2019. Polity IV project: Political regime char­\\nacteristics and transitions, 1800–2018. Center for Systemic Peace [Online]. Available: \\nhttp://www.columbia.edu/acis/eds/data_search/1080.html.\\n\\n\\n16  Introduction\\nMidlarsky, M. I. 1998. Democracy and the environment: An empirical assessment. Journal \\nof Peace Research, 35, 341–361.\\nNational Bureau of Statistics. 2019. China statistical yearbook. Beijing, China: China Sta­\\ntistics Press.\\nNational People’s Congress. 2006. The outline of the national 11th five-­\\nyear plan on eco­\\nnomic and social development. Beijing, China: The 4th Conference of the 10th National \\nPeople’s Congress.\\nNational Statistics Bureau & Ministry of Ecology and Environment. 2019. China statisti­\\ncal yearbook on environment 2018. Beijing, China: China Statistics Press.\\nNeumayer, E. 2002. Do democracies exhibit stronger international environmental commit­\\nment? A cross-­\\ncountry analysis. Journal of Peace Research, 39, 139–164.\\nNjeru, J. 2010. ‘Defying’ democratization and environmental protection in Kenya: The \\ncase of Karura forest reserve in Nairobi. Political Geography, 29, 333–342.\\nPayne, R. A. 1995. Freedom and the environment. Journal of Democracy, 6, 41–55.\\nPellegrini, L. & Gerlagh, R. 2006. Corruption, democracy, and environmental policy – an \\nempirical contribution to the debate. The Journal of Environment & Development, 15, \\n332–354.\\nStern, D. I. & Common, M. S. 2001. Is there an environmental Kuznets curve for sulfur? \\nJournal of Environmental Economics and Management, 41, 162–178.\\nSundberg, J. 2003. Conservation and democratization: Constituting citizenship in the Maya \\nbiosphere reserve, Guatemala. Political Geography, 22, 715–740.\\nTorras, M. & Boyce, J. K. 1998. Income, inequality, and pollution: A reassessment of the \\nenvironmental Kuznets curve. Ecological Economics, 25, 147–160.\\nU.S. EPA. 2019. Air pollutant emissions trends data: Criteria pollutants national tier 1 for \\n1970–2018. Washington, DC: U.S. EPA.\\nWalker, P. A. 1999. Democracy and environment: Congruencies and contradictions in \\nSouthern Africa. Political Geography, 18, 257–284.\\nWendling, Z. A., Emerson, J. W., Esty, D. C., Levy, M. A., De Sherbinin, A. et al. 2018. \\n2018 environmental performance index. New Haven, CT: Yale Center for Environmen­\\ntal Law & Policy.\\nWinslow, M. 2005. Is democracy good for the environment? Journal of Environmental \\nPlanning and Management, 48, 771–783.\\nZheng, B., Tong, D., Li, M., Liu, F., Hong, C. P., Geng, G. N., Li, H. Y., Li, X., Peng, L. Q., \\nQi, J., Yan, L., Zhang, Y. X., Zhao, H. Y., Zheng, Y. X., He, K. B. & Zhang, Q. 2018. \\nTrends in China’s anthropogenic emissions since 2010 as the consequence of clean air \\nactions. Atmospheric Chemistry and Physics, 18, 14095–14111.\\n\\n\\n1  \\u0007\\nCentralized political will\\nWhich governmental affairs can become national priorities and their relative rank­\\nings are highly centralized in the Chinese context without democracy. In contrast \\nto the path argued by Payne (1995), in which a democracy develops its political \\nwill regarding the environment, China has taken a different route. The state is far \\nmore dominant in China than it is in a democracy. Even nongovernmental organi­\\nzations (NGOs) in China actively seek alliances with the government (Hsu, 2010). \\nThe lack of free elections also reduces the need for the government to directly \\nrespond to the public’s demands.\\nThe Chinese Communist Party holds tremendous authority in deciding, for \\nexample, how important environmental protection is among all governmental \\naffairs. The party is closely intertwined with the Chinese government, but they \\nare also very different. The party makes key decisions while the government takes \\nalmost all implementation tasks. Although the party has about 90 million mem­\\nbers and is organized into multiple levels, the authority is very much centralized \\nupward and eventually into the Central Committee. The 19th cohort was inau­\\ngurated in October 2017 after the corresponding National Party’s Congress. It \\nhas 204 members, and their tenure will last for five years, until 2022 when the \\nnext National Party’s Congress convenes to form another Central Committee. It \\nfurther forms the Political Bureau, currently with 25 members, and then, most \\ncrucially, the 7-­\\nmember Standing Committee as China’s top leadership. Many of \\nthese members, but not all, also hold positions in the Chinese government. Two \\nare most important. The secretary general, currently Xi Jinping, is at the center \\nand generally assumes the position of president in the Chinese government. The \\nprime minister, currently Li Keqiang, leads the Chinese administration. This hier­\\narchy ensures China’s high degree of centralization in making most important \\ndecisions. The Chinese government and, specifically, environmental administra­\\ntion are mainly focused on environmental policy making and implementation. On \\nthose prioritized governmental affairs that decisions have been made by the top \\nleadership of the Party, the government is in charge of implementation.\\nIn the past seven decades after the establishment of the People’s Republic of \\nChina, each top leadership of the Chinese Communist Party has left a phrase in \\n2\\t\\n\\u0007\\nPolitical will\\n\\n\\n18  Political will\\nthe party’s Constitution, with their ideologies written as the party’s “guiding com­\\npass,” which not only guides their own leadership’s rule but also summarizes a \\nlegacy. The line has become longer over time to include “Mao Zedong Thoughts,” \\n“Deng Xiaoping Theory,” “Three Representativeness” (headed by President Jiang \\nZemin), “Scientific View of Development” (headed by President Hu Jintao) and \\n“Socialistic Thoughts with Chinese Characteristics in the Xi Jinping Era” (Chi­\\nnese Communist Party, 2017).\\nThis chapter mainly focuses on how the political will for environmental pro­\\ntection has evolved since the 15th Central Committee was formed in 1998. The \\nperiod transcended three top leaderships of the party, including President Jiang \\nZemin and Prime Minister Zhu Rongji (1998–2002), President Hu Jintao and \\nPrime Minister Wen Jiabao (2003–2012) and President Xi Jinping and Primer \\nMinister Li Keqiang (2013–2022). Chapter 3 examines the environmental gov­\\nernance of the Chinese government for implementing the political will.\\n2  \\u0007\\nEconomy, jobs and the environment (1998–2002)\\nThe period was under the 15th Central Committee and the leadership of President \\nJiang Zemin and Prime Minister Zhu Rongji. Although China’s environmental \\npollution had already reached high levels, more urgent issues were present to \\nsuppress forceful political will for environmental protection. Difficult economic \\nconditions slowed down energy consumption to witness a decline of sulfur diox­\\nide (SO2) emissions in the 9th Five-­\\nYear Plan (1996–2000; Figure 1.8).\\nChina’s economy was still at the early stage of industrialization, while the \\nAsian financial crisis of 1997 hit China badly. In comparison with the previous \\nyears (1992–1997), the average annual gross domestic product (GDP) growth rate \\ndeclined significantly from 11.8% to 8.3% (Figure 2.1). GDP per capita was still \\nat low levels, US$3,185 (purchasing power parity [PPP] in 2011 US$) in 1998 and \\nUS$4,276 in 2002, or 7.4% and 9.3% of the U.S. levels, respectively (Figure 1.6). \\nJob creation was more important than GDP growth. As will be introduced in \\nChapter 3, the following year, 1998, witnessed China’s several far-­\\nreaching fun­\\ndamental reforms with a key focus on state-­\\nowned enterprises and a better-­\\ndefined \\nboundary between the state and the market. Many of these state-­\\nowned enter­\\nprises were substantially overstaffed and loss-­\\nmaking and operated more like gov­\\nernmental agencies and less like market-­\\noriented entities. The Chinese financial \\nsector and, specifically, the state-­\\nowned banks had extremely high levels of bad \\ndebts. This period witnessed large-­\\nscale privatization and the bankruptcy of small \\nand medium-­\\nsized state-­\\nowned enterprises, mainly in the secondary sector. As a \\nresult, the secondary sector shed 8.7 million jobs from 1998 to 2002 to reflect the \\nmassive reform’s side effects (Figure 2.1). Overall, 3.3 million jobs were annu­\\nally added to the secondary and tertiary sectors. With many more people entering \\nthan leaving the workforce as indicated in the rapidly enlarging age group of \\n15-­\\n to 64-­\\nyear-­\\nolds (Figure 2.2), many of the unemployed should have returned \\nto rural regions as the primary sector added 18.0 million jobs over the five years \\n(Figure 2.1). China’s job and demographic structures were still dominated by the \\n\\n\\nPolitical will  19\\n–16\\n–12\\n–8\\n–4\\n0\\n4\\n8\\n12\\n16\\n–90\\n–60\\n–30\\n0\\n30\\n60\\n90\\n1992–1997\\n1998–2002\\n2003–2007\\n2008–2012\\n2013–2018\\nAnnual increase/decrease of nonprimary jobs \\n(million) & annual GDP growth rate (%)\\n)\\nn\\no\\ni\\nl\\nl\\ni\\nm\\n(\\n \\ns\\nb\\no\\nj\\n \\nf\\no\\n \\ne\\ns\\na\\ne\\nr\\nc\\ne\\nd\\n/\\ne\\ns\\na\\ne\\nr\\nc\\nn\\nI\\n \\nc\\ni\\nd\\no\\ni\\nr\\ne\\nP\\nPrimary\\nSecondary\\nTertiary\\nNonprimary jobs per year (right)\\nGDP growth rate (right)\\nFigure 2.1  \\u0007\\nSectoral employment changes and GDP growth rates across China’s administrations\\nSource: National Bureau of Statistics (2019).\\n600\\n650\\n700\\n750\\n800\\n850\\n900\\n950\\n1,000\\n1,050\\n1,100\\n0%\\n10%\\n20%\\n30%\\n40%\\n50%\\n60%\\n70%\\n80%\\n90%\\n100%\\n1980\\n1985\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\nPopulation in the 15–64 age group (million)\\n \\nn\\no\\ni\\nt\\na\\nl\\nu\\np\\no\\np\\n \\nr\\no\\n \\nt\\nn\\ne\\nm\\ny\\no\\nl\\np\\nm\\ne\\n \\nf\\no\\n \\ns\\ne\\nr\\na\\nh\\nS\\nYear\\nPrimary\\nSecondary\\nTertiary\\nUrban population\\nRural population\\nPopulation (15–64; right)\\nFigure 2.2  \\u0007\\nEmployment and population structures in China\\nSource: National Bureau of Statistics (2019).\\n\\n\\n20  Political will\\nprimary sector and rural regions. The primary sector’s share of total jobs hovered \\nstably between 49.8% and 50.1%, while the share of the rural population declined \\nfrom 68.1% in 1997 to 60.9% in 2002 (Figure 2.2). As a result, most Chinese \\nwere less exposed to seriously polluted urban air pollution because they were not \\nbreathing urban air.\\nGenerally speaking, over the period from 1998 to 2002, environmental pro­\\ntection was ranked high neither in governmental affairs nor by society. In the \\naftermath of the Asian financial crisis, economic downturn and unemployment \\nwere more imminent and highly politicized problems to occupy the top leader­\\nship’s mind. This top leadership’s guiding ideology, “three representativeness,” \\nwas mainly engaged in expanding the party’s base from the conventional working \\nclass to other categories of the society. Environmental protection did not occupy \\nany important role in this ideology, while slower industrial development also \\nreduced the deterioration rate of environmental pollution.\\n3  \\u0007\\nSARS and the prioritization of environmental \\nprotection (2003–2012)\\nOver the ten years (two terms with the 16th and 17th Central Committee) between \\n2003 and 2012, when President Hu Jintao and Prime Minister Wen Jiabao were in \\npower, China added 75.6 million new jobs in the secondary sector and 67.3 million \\nin the tertiary sector, while the primary sector had a decrease of 108.7 million jobs \\n(Figure 2.1). To keep pace with the growing working-­\\nage population, the annual \\nincrease of nonprimary jobs was 14.3 million, much faster than the 3.3 million \\nnew jobs annually between 1998 and 2002 (Figure 2.1). The primary sector still \\naccounted for 50.0% of China’s overall employment in 2002 and remained the \\nlargest among the three sectors in 2007 at 40.8%. China’s entry into the World \\nTrade Organization in 2001 and multiple major economic reforms led to unprec­\\nedented growth in the economy, energy consumption and pollution. The global \\nfinancial crisis of 2008 did exert great and negative impacts on China’s economy \\nto slow it down. Comparing the two Hu-­\\nWen administrations (2003–2007 and \\n2008–2012), the annual economic growth rate came down from 11.7% to 9.4%, \\nand the annual increase of nonprimary jobs was from 15.9 million to 12.7 million.\\nEnvironmental protection started to emerge as a nationally prioritized govern­\\nmental affair. The 11th Five-­\\nYear Plan (2006–2010) was completely formulated \\nand implemented under this top leadership of the party. It not only included the \\n10% mitigation goals of SO2 and chemical oxygen demand but actually achieved \\nthem (National People’s Congress, 2011), defying challenges from the rapid \\ngrowth of economy and energy consumption and reversing the humiliating fail­\\nures in the 10th Five-­\\nYear Plan (Figure 1.8). Deeper mitigation of SO2 emissions \\nfollowed in later years, while the turning point of environmental protection hap­\\npened within this period (Figure 1.8).\\nSociety might not have been ready to put the environment as a high priority \\nwith strong cleanup determination. For example, despite the dire situation of air \\npollution, a survey in 2010 by Gallup, a U.S. research-­\\nbased consulting company, \\n\\n\\nPolitical will  21\\nfound that only 26% of the Chinese were dissatisfied, and 73% were satisfied, \\nwith the air quality (English, 2010). The potentially insufficient support from soci­\\nety for pollution mitigation, if China were a democracy, might not have generated \\nstrong political will.\\nThe much stronger political will for environmental protection reflected more \\nthe intention of the top leadership of the party. As is examined in detail in Chap­\\nter 4, the direct involvement of the top leadership was crucial in enacting the \\nenvironmental goals in the 11th Five-­\\nYear Plan after the failures in the 10th Five-­\\nYear Plan. The 16th Central Committee was formed in November 2002 at the 16th \\nNational Party’s Congress. The Standing Committee of the Political Bureaus was \\nheaded by Secretary General Hu Jintao and included Wen Jiabao. In March 2003, \\nat the 10th National People’s Congress, they assumed the positions of president \\nand prime minister, respectively, in the Chinese central government. In the transi­\\ntional period between these two key conferences, they had only party leadership \\nroles but officially not those later government positions.\\nSARS (severe acute respiratory syndrome), a new infectious disease, emerged \\nalmost exactly over this transitional period in November  2002 and became \\nincreasingly damaging over the winter (WHO, 2003). The timing of the devastat­\\ning pandemic coincided well with the top leadership’s search for a new ideology \\nto distinguish themselves from their predecessors. This public health crisis taught \\na painful lesson to the Chinese leadership that public goods should be prioritized \\ntogether with economic development. The overemphasis of the latter may actu­\\nally backfire to result in slow economic growth as the Chinese economy was sig­\\nnificantly damaged, especially in the second quarter of 2003, by the impacts of \\nthe SARS pandemic (Rawski, 2005; Hai et al., 2004; Xu et al., 2009). After the \\npandemic was over and society returned to normal, a new ideology was gradually \\nformed, titled “Science View of Development,” to emphasize development from \\nmultiple aspects to achieve a “harmonious society.” Environmental protection is \\na natural extension from public health and became one pivotal component in this \\nnew development direction.\\nThe authorities of the top leadership and this new ideology were hardly distin­\\nguishable. From this perspective, whether China could achieve serious mitiga­\\ntion of environmental pollution and reverse the deterioration trend became more \\npoliticized. This significantly increased the political will of the top leadership \\nto start taking environmental protection into the inner core of key governmental \\naffairs. In other words, the political will resulted from a more top-­\\ndown rather \\nthan bottom-­\\nup approach, although the pressure from society grew over the years.\\nKey international events also played a role in shaping China’s environmen­\\ntal protection. One of the most important events over the Hu–Wen administra­\\ntions was the 29th Summer Olympic Games in August 2008. To ensure good air \\nquality over Beijing, China shut down many polluting factories across several \\nneighboring provinces around Beijing. Environmental information was increas­\\ningly available over this period. The Internet played a key role in distributing \\ninformation. The U.S. Embassy in Beijing started monitoring fine particulate \\nmatter (PM2.5) levels in 2008. Environmental NGOs, notably the IPE (Institute of \\n\\n\\n22  Political will\\nPublic & Environmental Affairs) that was established in 2006, started systemati­\\ncally collecting, publicizing and distributing environmental information to the \\npublic.\\n4  \\u0007\\nThe sustainability of environmental political will \\n(2013–present)\\nPresident Xi Jinping and Prime Minister Li Keqiang assumed their top leadership \\nroles of the Chinese Communist Party in November 2012 at the 18th National \\nParty’s Congress and then of the central government in March 2013 at the 12th \\nNational People’s Congress. As usual, the change of leadership did raise questions \\nabout whether environmental protection could be further strengthened or weak­\\nened in relation to new economic conditions and new leaders’ ideas. The Chinese \\neconomy entered a “new normal,” or a stabilized but lower level after 2013. The \\nannual GDP growth rate from 2013 to 2018 was 7.0%, even lower than the level \\nduring the aftermath of the Asian financial crisis. Nevertheless, the economy had \\nalready reached a wealthier status before the new leadership came into power and \\nthe progress since 2013 has also been decent. In 2002, China’s GDP per capita \\nwas US$4,276 (PPP in 2011 US$), and it increased to US$11,049 in 2012 and \\nUS$16,098 in 2018 (IMF, 2019). The ratios between China and the United States \\nwere 9.3%, 21.8% and 28.8%, respectively.\\nWith the working-­\\nage population stabilized at about 1  billion people (Fig­\\nure 2.2), job creation was still at a healthy pace with 10.7 million new nonpri­\\nmary jobs added annually. Over the six years, in total, the tertiary sector added \\n82.5 million new jobs, while the secondary and primary sectors had 18.5 million \\nand 55.2 million fewer jobs (Figure 2.1). In contrast to the economic downturn \\nbetween 1998 and 2002, Chinese labor did not return to rural regions. The tertiary \\nsector accelerated significantly to account for 46.3% of all employment in 2018, \\nup from 36.1% in 2012 (Figure 2.2). The primary sector accounted for 31.4% of \\nall jobs in 2013 and further declined to only 26.1% in 2018 (Figure 2.2). Further­\\nmore, China has been urbanizing fast to have 53.7% of people in urban regions \\nin 2013. In 2018, the urbanization rate further increased to 59.6% (Figure 2.1). In \\nother words, China’s employment and demographic structures have been much \\nmore urbanized, which also brought more people under the impacts of more pol­\\nluted urban air.\\nRapid economic development and escalating living standards have been key \\nfoundations for the Chinese people to maintain support to the Chinese Communist \\nParty’s holding of power. The Chinese middle class has expanded rapidly in the \\npast decades to indicate that this demand was to a great extent satisfied. Given \\nthe higher income and more intimate exposure of an average Chinese to urban air \\npollution, society started to place environmental quality at a significantly higher \\npriority than before. The balance between environmental protection and economic \\ngrowth has thus been shifting gradually toward the former’s end. In the leader­\\nship transitional period in January 2013, North China suffered from severe smog \\nwith PM2.5 concentration levels reaching hazardous levels (Wang et al., 2014). \\n\\n\\nPolitical will  23\\nAlthough Hebei Province had worse air quality, it was Beijing, as China’s capi­\\ntal, that attracted most international and domestic attention. Air pollution mitiga­\\ntion started to be widely recognized as one crucial demand by society. People are \\nincreasingly willing to sacrifice economic opportunities for a better environment. \\nEnvironmental protection and especially urban air quality have been significantly \\npoliticized, now by society, and implicitly linked with the legitimacy of the Chi­\\nnese Communist Party as the ruling political party.\\nIn addition, environmental protection also became a more and more visible \\nbusiness to create jobs and economic outputs. The initial efforts in the Hu–Wen \\nadministrations started to bear fruits. China’s environmental and renewable \\nenergy industries are competitive not only domestically but also internationally \\n(Xu, 2013; Zhu et al., 2019). They have grown into another pollical force to push \\nfor China’s continuous environmental cleanup. For example, China now has the \\nworld’s largest solar, wind and electric vehicle industries. They play increas­\\ningly counterbalancing roles against those who are concerned about the negative \\nimpacts of environmental protection on their businesses.\\nIn the formation of this top leadership’s governing ideology, the party was also \\nkeen to significantly elevate the priority of environmental protection. The 18th \\nNational Party’s Congress in 2012 emphasized ecological civilization, while the \\n19th National Party’s Congress in 2017 listed “harmony of people and nature” as \\none of the 14 basic things to insist on, which primarily features ecological civi­\\nlization and the “two mountains” theory. Previously, in the relationship between \\neconomic development and environmental protection, the statement was that we \\nwant not only “gold and silver mountain” but also “clear water and green moun­\\ntain.” In other words, these two were placed as trade-­\\noffs to each other. The new \\nstatement of “two mountains” became that “clear water and green mountain” are \\n“gold and silver mountain.” The pursuit of environmental quality became equiva­\\nlent to economic development. Environmental protection does offer opportunities \\nto satisfy the demands for both economic development and a better environment, \\nfor example, when new industries emerge for pollution mitigation or resource \\nconservation. Environmental policies have also been playing an active role in \\nencouraging innovation and economic transformation, as elaborated in greater \\ndetail in Chapter 7.\\nOverall, in this period, both the top leadership of the party and society came \\ntogether with a common and prioritized stake in a cleaner environment. Environ­\\nmental protection is increasingly politicized to form an unprecedented political will \\nfor pollution mitigation. The top leadership should meet the growing demand of \\nthe society for not just economic growth but also environmental cleanup. Because \\n“ecological civilization” is a key component in the top leadership’s “Socialis­\\ntic Thoughts with Chinese Characteristics in the Xi Jinping Era,” significant \\nimprovement of environmental quality also became crucial for the establishment \\nof this new governing ideology. New economic opportunities and environmental \\nindustries have been serving as an increasingly visible force to counterbalance \\nthe negative economic impacts of environmental protection. The rapid growth of \\nincome has also transformed society’s preference between economic development \\n\\n\\n24  Political will\\nand environmental quality. They are crucial forces to make the political will sus­\\ntainable, even when top leadership changes again in the future.\\nReferences\\nChinese Communist Party. 2017. The party’s constitution (Revised by the 19th national par­\\nty’s congress) [Online]. Available: https://www.researchgate.net/publication/322421053_\\nThe_19th_Congress_of_the_Communist_Party_of_China_and_Its_Aftermath.\\nEnglish, C. 2010. More than 1 billion worldwide critical of air quality. Washington, DC: \\nGallup.\\nHai, W., Zhao, Z., Wang, J. & Hou, Z. G. 2004. The short-­\\nterm impact of SARS on the \\nChinese economy. Asian Economic Papers, 3, 57–61.\\nHsu, C. 2010. Beyond civil society: An organizational perspective on state – NGO relations \\nin the people’s Republic of China. Journal of Civil Society, 6, 259–277.\\nIMF. 2019. World economic outlook databases October  2019 [Online]. Available: \\nhttps://www.imf.org/en/Publications/SPROLLs/world-­\\neconomic-­\\noutlook-­\\ndatabases#\\nsort=%40imfdate%20descending.\\nNational Bureau of Statistics. 2019. China statistical yearbook. Beijing, China: China Sta­\\ntistics Press.\\nNational People’s Congress. 2011. The outline of the national 12th five-­\\nyear plan on eco­\\nnomic and social development. Beijing, China: The 4th Conference of the 10th National \\nPeople’s Congress.\\nPayne, R. A. 1995. Freedom and the environment. Journal of Democracy, 6, 41–55.\\nRawski, T. G. 2005. SARS and China’s economy. In: Kleinman, A. & Watson, J. L. (eds.) \\nSARS in China: Prelude to pandemic? Stanford: Stanford University Press.\\nWang, Y. S., Yao, L., Wang, L. L., Liu, Z. R., Ji, D. S., Tang, G. Q., Zhang, J. K., Sun, Y., \\nHu, B. & Xin, J. Y. 2014. Mechanism for the formation of the January 2013 heavy haze \\npollution episode over central and eastern China. Science China-­\\nEarth Sciences, 57, \\n14–25.\\nWHO. 2003. Update 95 – SARS: Chronology of a serial killer [Online]. Available: https://\\nwww.who.int/csr/don/2003_07_04/en/.\\nXu, Y. 2013. Comparative advantage strategy for rapid pollution mitigation in China. Envi­\\nronmental Science & Technology, 47, 9596–9603.\\nXu, Y., Williams, R. H. & Socolow, R. H. 2009. China’s rapid deployment of SO2 scrub­\\nbers. Energy & Environmental Science, 2, 459–465.\\nZhu, L., Xu, Y. & Pan, Y. J. 2019. Enabled comparative advantage strategy in China’s solar \\nPV development. Energy Policy, 133.\\n\\n\\n1  \\u0007\\nEvolution of environmental administration\\nEnvironmental protection in China could be traced back to the United Nations \\nConference on the Human Environment in June 1972 in Stockholm, Sweden. In \\nthe turmoil of the Cultural Revolution (1966–1976) and after the United Nations \\nvoted in 1971 that the People’s Republic of China is the sole representative of \\nChina, China sent an official delegation to this conference. In August 1973, the \\nFirst National Conference on Environmental Protection was held to mark that \\nenvironmental protection had formally been recognized as a governmental affair. \\nHowever, in the early stage of the Cultural Revolution, the leaders and organiza­\\ntions of the Chinese Communist Party and the Chinese government at various \\nlevels were generally toppled by Red Guards (hong wei bin) and Rebels (zao fan \\npai). Although the Chinese government was rebuilt at a later stage, the primary \\nfocus was not on economic or social affairs but on class struggle. As a result, \\nChina did not demonstrate a significant conflict between economic development \\nand environmental protection because neither mattered.\\nWhen the Cultural Revolution ended in 1976, after a short transitional period, \\nChina entered the new era of Reform and Open-­\\nup in December 1978. Economic \\ndevelopment quickly gained prominence in governmental affairs, while class \\nstruggle and other political affairs wound down. Soon afterward, the impacts of \\neconomic development on environmental quality started to emerge. As a pub­\\nlic affair that requires governmental intervention, environmental protection was \\nannounced as one Basic National Policy in the Second National Conference on \\nEnvironmental Protection from 31 December 1983 to 7 January 1984. Since then, \\ndedicated governmental entities have been established in the Chinese government \\nto regulate and implement environmental protection. The agency in the Chinese \\ncentral government that oversees environmental protection has evolved over the \\nyears in terms of organization, power and jurisdiction. The authority of environ­\\nmental protection has been increasingly strengthened in the past four decades. \\nIn 1984, the State Environmental Protection Agency was established under the \\nthen Ministry of Construction. In 1988, it was pulled out to be directly led by the \\nState Council, thus with an elevated status and authority at the vice-­\\nministry level. \\nEnvironmental protection then became not just an issue for one single ministry \\n3\\t\\n\\u0007\\nEnvironmental governance\\n\\n\\n26  Environmental governance\\nbut also one key state affair that was widely relevant and one level closer to the \\ncenter of the governmental authority.\\nChina’s key reforms in the past four decades have one crucial central theme for \\nadjusting the relationship between the state and the market. There were essentially \\nno real markets in the Cultural Revolution because markets were deemed as too \\ncapitalistic. Prices did not reflect any balance between demand and supply but \\nwere decided directly by the government. Purchases should be accompanied by \\npermits, not just money. Despite fluctuations, the overall trend in the past dec­\\nades was the reemergence, creation and maturity of various markets, as well as \\nthe refocusing of the state from everything to strategic and public affairs. With \\nthe government giving up its original authority, prices have become much better \\nindicators of supply and demand balances. The production and consumption are \\nincreasingly guided by market signals and little by orders from central planners.\\nIn the 1998 reform of the State Council that featured a better-­\\nclarified demarca­\\ntion between the state and the market, 14 ministries that mainly took direct charge \\nof the economic sectors were abolished, and 4 new ministries were formed. The \\ngovernment then became more focused on public affairs and much less on direct \\nmanagement of businesses. In this reform, the then State Environmental Protec­\\ntion Agency was promoted to the ministerial level and renamed the State Environ­\\nmental Protection Administration (SEPA). Other significant reforms in the same \\nperiod marked the reorganization of large state-­\\nowned enterprises, the privatiza­\\ntion of small ones and the widened space for private businesses.\\nAlthough environmental protection gained increasingly higher statuses in the \\npreviously mentioned reforms, it was still kept away from the core of the Chinese \\ncentral government, in which the State Council is in charge of the country’s routine \\nadministration. According to China’s Constitution, the State Council comprises \\nthe following members: prime minister and deputies, state councilors, ministers, \\ndirectors of commissions and the auditor general. Although the SEPA had been \\nelevated to the ministerial level after the 1998 reform, it was not a ministry, and \\nthus, its director was not a constitutional member of the State Council. He or she \\ncould be present in the meeting only by invitation, with much constrained author­\\nity on other ministries’ affairs even if they may be closely relevant to environmen­\\ntal protection. The 2008 reform became crucial when the SEPA was reorganized \\nas the Ministry of Environmental Protection and thus became a formal comprising \\nministry of the State Council. This reform indicated that environmental protection \\nwas recognized as one of the key governmental affairs. The enhanced authority \\nalso gave the new ministry and its counterparts in local governments more force­\\nful power in enacting and implementing environmental policies.\\nIn 2018, a new round of major reforms further concentrated environmental \\nauthorities that scattered in several ministries into the newly formed Ministry of \\nEcology and Environment (MEE; State Council, 2018). Climate change was nota­\\nbly transferred out of the National Development and Reform Commission to fall \\nunder the MEE’s jurisdiction. The MEE now combines the original functions of \\n(1) Ministry of Environmental Protection, (2) climate change and mitigation under \\nthe National Development and Reform Commissions, (3) groundwater pollution \\n\\n\\nEnvironmental governance  27\\nunder the Ministry of Land and Resources, (4) water environment management \\nunder the Ministry of Water Resources, (5) agricultural pollution under the Minis­\\ntry of Agriculture, (6) ocean environment under the State Oceanic Administration \\nand (7) south–north water diversion project’s environmental protection under its \\noffice. This reform further strengthened the authority of environmental protection. \\nThe significantly wider duties are expected to create better synergies among their \\nregulations and solutions.\\n2  \\u0007\\nChain of command for environmental protection\\nEnvironmental protection administration in China has four major levels, being \\ncentral, provincial, municipality and county. The latter three levels are generally \\ncategorized as local governments, although provincial governments are often not \\ndirectly involved in local administration. Local governments take primary respon­\\nsibilities for implementing environmental policies and achieving environmental \\nprotection. The sequential reforms at the central government were followed by \\ncorresponding reforms in local governments that generally resemble the struc­\\ntures of the central government, despite differences contingent on local contexts.\\nAlthough the MEE and its predecessors had a clear chain of command under \\nthe State Council of the central government, it is not straightforward whether local \\nenvironmental protection bureaus (EPBs) should be led by corresponding local \\ngovernments or environmental protection agencies at a higher governmental level \\nfor achieving more effective environmental administration. On one hand, environ­\\nmental protection is far beyond the authority of the EPBs to involve industrial pol­\\nicy, urban planning and other policies. Environmental enforcement heavily relies \\non other agencies and budget allocation from local governments. Accordingly, it \\nis reasonable to have local governments as the major office-­\\nbearers. On the other \\nhand, local governments may create barriers to environmental protection due to \\nthe possible conflicts between economic growth and environmental protection. If \\nlocal EPBs could be vertically controlled, they may better serve the purpose of \\nenvironmental protection as local economic growth is not the central considera­\\ntion of upper-­\\nlevel EPBs.\\nChina’s administrative reform in the past four decades has one key trend: more \\nand more remaining governmental authorities are being decentralized from the \\ncentral government to local governments, especially regarding the regulation of \\neconomic activities and the provision of social public goods such as health care, \\neducation, housing and urban/rural infrastructure and community services. In \\nthe environmental administrative system, the chain of command for local EPBs \\nreflected such a decentralization trend to recognize that environmental protection \\nis generally a localized governmental affair. In 1999, the Department of Organi­\\nzation of the Chinese Communist Party reformed the institutional arrangements \\nand specified that the leaders of local EPBs should be jointly appointed by pri­\\nmarily local governments and, to a lesser extent, upper-­\\nlevel EPBs (Department \\nof Organization of the Central Committee of the Communist Party of China, \\n1999). The “double administration” arrangement aimed for a balance between the \\n\\n\\n28  Environmental governance\\nvertical – or “tiao” based on the function of environmental administration – and \\nhorizontal – or “kuai” based on the location of environmental protection. The \\n1999 reform was accordingly mainly horizontally oriented with decentralization. \\nEPBs were under local governments with their directors and budgets controlled \\nby their corresponding local governments. They were also advised by EPBs in the \\nimmediate upper-­\\nlevel governments.\\nThe general decentralization trajectory in the past decades also engaged \\nanother argument for recentralization. In the era of Reform and Open-­\\nup, local \\ngovernments often have to face the conflicts between environmental protec­\\ntion and economic development. In evaluating the performance of local leaders, \\neconomic indicators tended to occupy much heavier weights than environmen­\\ntal protection, especially in the early years. Accordingly, for the sake of the \\nlocal economy, the environment has often been sacrificed. Together with the \\nrising status of environmental protection in the central government as described \\nearlier, environmental protection started to climb higher on the priority list. \\nThe MEE as well as its predecessors and local counterparts are less bound by \\nsuch evaluation because economic development is not their direct job duty, but \\nenvironmental protection is their primary responsibility. In 2016, another major \\nand more centralization-­\\noriented reform was initiated with several provinces \\nfor pilot implementation (The General Office of the CPC Central Committee \\nand The General Office of the State Council, 2016). The authority of appoint­\\ning local EPB leaders and their budgets were shifted more toward upper-­\\nlevel \\nEPBs. Environmental monitoring and inspection agencies were more directly \\ncontrolled vertically.\\n3  \\u0007\\nDivision of labor for policy making and implementation\\nEnvironmental agencies in China’s central and local governments have distinct \\nfunctional focuses. The central government is mainly in charge of policy mak­\\ning. It also supervises local governments, primarily provincial governments, \\nfor implementing environmental protection. Provincial governments heavily \\nfocus on policy making within their individual provinces. They also adapt poli­\\ncies from the central government to their own situations and supervise mainly \\nmunicipality governments. The municipality level has a further diminished \\ncapacity in policy making and a much heavier focus on policy implementa­\\ntion, while the tasks of county governments fall almost exclusively on the \\nimplementation of policies from the upper levels within localized contexts. \\nImplementation is primarily the responsibility of municipality and county gov­\\nernments. They can also make decisions that are applied within their specific \\njurisdictions, mainly on how to implement policies with greater efficiency and \\neffectiveness.\\nThe clear division of labor among the four levels of governments is reflected \\nin their composition of environmental protection personnel. Their personnel com­\\npositions are accordingly different among the four categories: administration, \\ninspection, monitoring and others. “Administration” mainly refers to the MEE \\n\\n\\nEnvironmental governance  29\\nin the central government as well as corresponding bureaus at the three levels \\nof local governments. “Inspection” personnel are those who work in Inspection \\nBureaus, while “monitoring” personnel are based in Monitoring Stations. “Oth­\\ners” are the remaining personnel, such as those in the Academy of Environmental \\nSciences and Academy of Environmental Planning at the four levels. They pro­\\nvide research and expertise to support environmental policy and decision making. \\nBetween 2004 and 2015, using available data, the compositions at the four gov­\\nernmental levels were largely stable (Figure 3.1). The only significant exception \\nis the share of “inspection” at the central level, which experienced a dramatic \\nincrease in 2009 (Figure 3.1).\\nThe environmental authority in the central government is not organized for \\nshouldering implementation tasks but primarily for making policies and super­\\nvising local governments (SCOPSR, 2018). At the central level, “others” is the \\nlargest category. It accounted for 64.1% of all 3,023 environmental protection \\npersonnel in 2015, while the share was over 80% before 2009 (Figure 3.1). \\nTheir dominant share indicates that environmental policy making in China \\nrequires and has been receiving significant intellectual support. “Administra­\\ntion” hosted only 362 personnel in 2015, and its share remained stable at about \\n12% over the period between 2004 and 2015 based on available data. After \\nthe 2018 reform and the reorganization, the new MEE was allowed to have \\n478 personnel, the addition for accommodating expanded functions (SCOPSR, \\n0\\n20,000\\n40,000\\n60,000\\n80,000\\n100,000\\n120,000\\n140,000\\n160,000\\n0%\\n10%\\n20%\\n30%\\n40%\\n50%\\n60%\\n70%\\n80%\\n90%\\n100%\\n2004 2009 2014 2004 2009 2014 2004 2009 2014 2004 2009 2014\\nTotal personnel (number)\\nl\\ne\\nn\\nn\\no\\ns\\nr\\ne\\np\\nl\\na\\nt\\no\\nt\\nf\\no\\ne\\nr\\na\\nh\\nS\\nYear\\nAdministration\\nInspection\\nMonitoring\\nOthers\\nTotal personnel (right)\\nCentral\\nProvincial\\nMunicipality\\nCounty\\nFigure 3.1  \\u0007\\nEnvironmental protection personnel at four governmental levels in China (for \\n2004–2015 using available data)\\nSource: Ministry of Environmental Protection (2002–2016).\\n\\n\\n30  Environmental governance\\n2018). Partly as a result of the establishment of six Regional Supervision Cent­\\ners, “inspection” had a major shift with its personnel jumping from 41 in 2008 \\nto 294 in 2009 and further to 542 in 2015. The 2018 reform further formalized \\nand upgraded them into Regional Supervision Bureaus, with a total person­\\nnel capacity of 240 officers (SCOPSR, 2018). “Monitoring” had about 6% of \\nall personnel throughout the years. The inspection and monitoring personnel \\nprovide crucial data support for supervising the environmental protection per­\\nformance of local governments.\\nChina’s provincial environmental authorities are also structured to have a \\nheavy focus on policy making and supervision and less a focus on direct pol­\\nicy implementation. At the provincial level, “others” remains the largest to have \\n46.4% of all provincial environmental protection personnel in 2015 (Figure 3.1). \\nIt is the largest category to reflect the desired functions in policy making. “Moni­\\ntoring” occupied 19.9%, which was a decline from 26.9% in 2004 (Figure 3.1). \\nThe share of “inspection” increased from 6.2% in 2004 to 9.0% in 2015, but the \\nincrease was much less significant in comparison with that at the central level \\n(Figure 3.1). Between monitoring and inspection, the central government now \\nputs more emphasis on inspection while provincial governments have a heavier \\nfocus on monitoring.\\nThe municipality and county levels are structured with much lower capacities \\nfor policy making and primarily for policy implementation. At the municipal­\\nity level, “monitoring” is the largest category, with 34.5% of all its environmen­\\ntal protection personnel in 2015 (Figure  3.1). “Inspection,” “administration” \\nand “others” each took about one fifth of the personnel. Their primary tasks \\nare, accordingly, sharply different from the central and provincial levels, with a \\nheavy focus on actually implementing policies, although they also build decent \\nknowledge support for initiating policy innovations. The county level is almost \\nexclusively for implementation, with “others’ accounting for only 6.4% of envi­\\nronmental protection personnel in 2015. “Inspection” became the largest func­\\ntional group with 37.0% of personnel, while “monitoring” and “administration” \\nhad 28.0% and 28.6%, respectively (Figure 3.1).\\nThe differentiated functions of environmental authorities at the four levels indi­\\ncate that China’s environmental protection requires their close cooperation. From \\nthe MEE in the central government to environmental protection bureaus at the \\ncounty level, policy making is more concentrated at the top while implementation \\nis mainly at the lower levels. However, their cooperation should not be taken for \\ngranted, even though China has a conventional image of top-­\\ndown administra­\\ntion. As examined in later sections, local governments and their leaders have their \\nown self-­\\ninterests. If environmental policy implementation is against such inter­\\nests, the implementation will not be expected to be effective. As expected from \\nChina’s weak rule of law, regardless of how stringent environmental policies are, \\ntheir weak implementation was one of the primary reasons that led to China’s \\nenvironmental crises. Without forceful enforcement efforts of local governments \\nand widespread compliance of polluting sources, environmental cleanup cannot \\nbe realized.\\n\\n\\nEnvironmental governance  31\\n4  \\u0007\\nDecentralized policy making\\nFrom social, economic, industrial and environmental perspectives, China has \\nbeen evolving at an astonishing speed in the past four decades. Laws, policies \\nand regulations should continuously adapt to the rapidly changing situations. As \\nindicated in the World Bank’s governance indicators, the rule of law in China has \\nnot been well established (Kaufmann and Kraay, 2019). Laws and courts have not \\nbeen playing important roles in daily environmental protection. Instead, policies \\nand regulations are much more closely relevant.\\nLaws in China are enacted by the National People’s Congress. They tend to take \\nmany years to formulate, enact or amend. For example, the Law of Environmental \\nProtection is the basic law to regulate China’s environmental protection. It was first \\nenacted in 1989, and then it took 25 years to get amended in 2014. However, China’s \\nenvironmental conditions and pollution had dramatically changed during the 25 years, \\nwhich should have indicated that the older version was seriously outdated. In addition, \\na variety of specific laws are enacted to regulate individual categories of the environ­\\nment. For example, the Law of Atmospheric Pollution Prevention and Control was \\nenacted in 1987, and two amendments have been done since then, in 2000 and 2015 \\n(two other minor corrections were done in 1995 and 2018; National People’s Congress, \\n2018). The Law of Water Pollution Prevention and Control was enacted in 1984. Only \\none amendment has been done in 2008, while two minor corrections were made in \\n1996 and 2017 (National People’s Congress, 2017). Accordingly, many environmental \\npolicies in China do not have clear corresponding items in environmental laws.\\nThe slow motion of laws’ enactment and amendment may make them at a great \\ndistance from the rapidly evolving pollution conditions. This could also partly \\nexplain why many of China’s policies were applied before their legal foundations \\nwere established. For example, the eco-­\\ncompensation policy got its legal backing \\nonly in 2014 in the newly amended Environmental Protection Law, but by then, it \\nhad already been experimented with and applied widely (Wang et al., 2016). Fur­\\nthermore, courts do not play significant roles in environmental enforcement and \\ncompliance. The laws are often written to mainly state principles without enough \\ndetails for direct implementation. The situations reflect China’s situation of weak \\nrule of law. The Chinese central government does not file lawsuits against local \\ngovernments for not implementing laws and its policies.\\nIn addition, China’s environmental laws are often intentionally vague in order to \\nallow more flexibility for the administration, while environmental policies contain \\nmore implementable details. Compared with the U.S. Clean Air Act Amendments \\n(CAAA, 1990), China’s goal and initial plan were much less detailed. The CAAA \\nclearly developed a cap-­\\nand-­\\ntrade system with detailed rules and schedules (The \\nU.S. Congress, 1990). Such details were absent in China’s plans. China’s laws are \\noften drafted by a ministry, not the National People’s Congress. For example, a \\nkey task of the MEE is to draft laws and regulations on environmental protection \\n(SCOPSR, 2018). A vague law can provide a legal foundation but not constrain \\nthe enactment of policies. For example, China’s Law of Atmospheric Pollution \\nPrevention and Control entitles the environmental authority to enact ambient air \\nquality standards and effluent emission standards without further clarification on \\n\\n\\n32  Environmental governance\\nwhen and how (National People’s Congress, 2000). The State Council gets the \\nlegal power to collect effluent emission charges and the freedom to enact any \\nrelevant regulation (National People’s Congress, 2000).\\nOther than the National People’s Congress, the State Council can enact Regula­\\ntions. Various ministries, as well as their internal departments, frequently churn \\nout policies, standards, projects and other incentives/commands that are relevant \\nto environmental protection. (For simplicity, they are referred to as environmen­\\ntal policies in the following discussion.) Local governments and their environ­\\nmental authorities also hold the right to enact their own environmental policies \\nor to adapt those from the central government into their corresponding jurisdic­\\ntions and contexts. As shown in Figure 3.1, local governments, especially at the \\nprovincial and (to a lesser extent) municipality levels, do have decent capacities \\nfor making policies. All these environmental policies could have very different \\nscopes, stringency, instruments, targets and intellectual support. In comparison to \\nlaws, environmental policies are much more flexible. Its enactment takes much \\nless time and faces much lower hurdles. The entire process is also much less cen­\\ntralized with numerous governmental bodies at ministerial and local levels who \\ncan independently enact environmental policies. China’s weak rule of law indi­\\ncates that these policies are rarely challenged in courts or through other channels \\nby affected interest groups, although their legal foundation might be porous and \\nshaky in vague and slowly updated environmental laws. In order to understand \\nChina’s rules for environmental protection, laws are not the most reliable sources.\\nNevertheless, ironically the weak status of rule of law in China further strength­\\nened the decentralization of environmental policy making. Although the National \\nPeople’s Congress is distinctly different from that in a democracy, laws are nev­\\nertheless more stable and more authoritative than policies by the administration. \\nLaws are based on wider participation, and the legislative process is more transpar­\\nent. If strong enough incentives are present, the variety of policy-­\\nmaking entities \\nat different levels will be able to actively innovate new policies, learn the lessons \\nand experiences from other policy making entities, adapt top-­\\ndown policies and \\nadopt policies from other regional contexts. Not all policy making is necessarily \\nbacked by sound research or intellectual support. Nevertheless, the decentralized \\npolicy making makes active bottom-­\\nup policy innovation and diffusion possible.\\n5  \\u0007\\nDecentralized policy implementation\\nFrom the perspectives of human resources and fiscal expenditures, China’s capac­\\nity for environmental policy implementation is heavily tilted toward local govern­\\nments, rather than the central government.\\n5.1  \\u0007\\nDecentralized human resources\\nPolicy implementation demands substantially more resources and personnel than \\npolicy making. Corresponding to the designed focuses between policy making \\nand implementation, most of China’s environmental protection officials are at \\n\\n\\nEnvironmental governance  33\\nthe municipality and county levels. China had 232,388 government employees \\non environmental protection in 2015, a 62.8% increase from 142,766 in 2001 to \\nreflect the elevated priority of environmental protection in all government affairs. \\nThe distributions across the four levels of governments have been quite consist­\\nent over the years, with 1.3%, 6.8%, 21.5% and 63.1% of the total environmen­\\ntal protection personnel in 2015 in central, provincial, municipality and county \\ngovernments, respectively. Corresponding to the four categories, the municipality \\nand county levels accounted for 92.5% personnel for administration, 97.0% for \\ninspection, 94.6% for monitoring and 69.5% for others (Figure 3.1). As a result, \\nthe environmental authorities at the central and even the provincial levels do not \\nhave an adequate human resource capacity to implement environmental policies \\nin millions of polluting sources that are scattered in China’s wide geographic ter­\\nritories (Ministry of Environmental Protection et al., 2010).\\n5.2  \\u0007\\nDecentralized fiscal expenditure and centralized fiscal revenue\\nFiscal revenue and expenditure are other key perspectives for understanding the \\ncentral–local relationship in China. The governmental expenditure-­\\nto-­\\nGDP ratio in \\nChina is not high in comparison to that in developed countries. In 2018, the ratio was \\n24.5%, in which the central government accounted for 3.6% and local governments \\n20.9% (Figure 3.2). The ratio dropped significantly from 26.8% to 11.1% from 1980 \\n0.0%\\n5.0%\\n10.0%\\n15.0%\\n20.0%\\n25.0%\\n30.0%\\n1980\\n1985\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\n \\no\\ni\\nt\\na\\nr\\n \\nP\\nD\\nG\\n \\no\\nt\\n \\ne\\nr\\nu\\nt\\ni\\nd\\nn\\ne\\np\\nx\\ne\\n/\\ne\\nm\\no\\nc\\nn\\ni\\n \\nl\\na\\nt\\nn\\ne\\nm\\nn\\nr\\ne\\nv\\no\\nG\\nYear\\nIncome: Central\\nExpenditure: Central\\nIncome: Total\\nIncome: Local\\nExpenditure: Total\\nExpenditure: Local\\nFigure 3.2  \\u0007\\nGovernmental revenue and expenditure to GDP ratios by central and local gov­\\nernments in China\\nSource: National Bureau of Statistics (2019).\\n\\n\\n34  Environmental governance\\nto the mid-­\\n1990s but has since gradually recovered (Figure 3.2). The ratio between \\ngovernmental revenue and GDP had a similar trend, initially falling from 25.3% in \\n1990 to 10.2% in 1995 and then rising back to 20.4% in 2018 (Figure 3.2). The gaps \\nbetween revenue and expenditure indicate fiscal surplus or deficit.\\nIn the current fiscal arrangement, the central government has far more revenue \\nthan it spends while the local governments in general have to rely on fiscal trans­\\nfers from the central government for meeting their expenditures. In 2018, the cen­\\ntral government received 46.6% of total general fiscal revenue but accounted for \\nonly 14.8% of total fiscal expenditures. Local governments, in contrast, received \\nnearly half of the revenue but had to shoulder 85.2% of the expenditures.\\nThe fiscal relationship between the central and local governments have expe­\\nrienced dramatic changes in the past four decades. In 1980, local governments \\ndirectly received an overall revenue of 87.5 billion RMB (current price), but their \\nspending was 56.2 billion RMB (National Bureau of Statistics, 2019). In contrast, \\nthe central government had a revenue of 28.4 billion RMB but spent 66.7 billion \\nRMB. It was the central government, not local governments, that spent most of \\nthe government budget, ranging from 52.5% to 55.0% between 1980 and 1984 \\n(Figure 3.2). Accordingly, the central government ran a huge deficit, and local \\ngovernments, a huge surplus. The fiscal transfer was then from local govern­\\nments to the central government. It reflected that China’s governance remained \\nvery much centralized in the immediate years after the Cultural Revolution. The \\ncentral government was directly engaged in providing a significant proportion \\nof government services and subsidies. Correspondingly, fiscal expenditures were \\nrequired to support such a provision.\\nThe situation was dramatically changed in 1985. When the governmental \\nexpenditure-­\\nto-­\\nGDP ratio started to drop significantly together with market-­\\noriented economic reforms, the central government saw a much steeper decline \\n(Figure 3.2). The budgets for both the central and local governments became indi­\\nvidually more balanced (Figure 3.3). The expenditures of the central and local \\ngovernments were only 3.3% above and 2.1% lower than their revenues in 1985. \\nLocal governments since then have consistently accounted for more than 60% of \\ntotal governmental expenditures, dwarfing the share of the central government. \\nAlthough local governments’ fiscal conditions remain generally balanced in the \\nfollowing years, the central government again started to see a widening gap. In \\n1993, its expenditures exceeded revenue by 37.0% while its shares in total gov­\\nernment revenue and expenditures had dropped to 22.0% and 28.3%, respectively. \\nThe budget deficit of the central government fiscally constrained it from exerting \\nauthority on rich provinces and tackling widening regional disparities across the \\ncountry.\\nIn China’s central–local fiscal relationship, 1994 was a crucial watershed when \\na fundamental tax reform entered into effect in January (State Council, 1993). The \\ncentral government’s share of total governmental revenue skyrocketed to 55.7% \\nin 1994 while its share of expenditures remained at 30.3%. For the first time, the \\ncentral government ran a budget surplus, with revenue exceeding expenditures by \\n65.7%. In contrast, local governments’ fiscal revenue could cover only 57.2% of \\n\\n\\nEnvironmental governance  35\\ntheir expenditures. Then a large fiscal transfer became necessary from the central \\ngovernment to local governments. With further decentralization of governmental \\naffairs and service provision, this newly formed central–local fiscal relationship \\nhas been kept increasingly entrenched in the past two decades. In 2018, local gov­\\nernments accounted for 85.2% of expenditures but only 53.4% of revenue. The \\ngap has significantly widened.\\nThe current central–local relationship that features significant fiscal transfer \\nfrom the central government to local governments reflects their differentiated \\nroles in policy making and implementation as discussed earlier. The central \\ngovernment is primarily in charge of policy making while the implementa­\\ntion is largely in the hands of local governments. The former requires much \\nless expenditure than the latter. All provinces have their expenditures exceed­\\ning revenues, but poor provinces tend to rely on the central government’s \\nfiscal transfer much more than rich ones (Figure  3.4). For example, Tibet’s \\ngovernmental revenue covered only 11.7% of its expenditures in 2018, while \\nthe revenue–expenditure gap for Shanghai was only 14.9%. Accordingly, the \\ncentral government could use fiscal transfer as an incentive for local govern­\\nments to implement policies or achieve goals that are enacted from the top. \\nIt is one of the key incentives that the central government can rely on for the \\ncooperation of local governments.\\n–10.0%\\n–8.0%\\n–6.0%\\n–4.0%\\n–2.0%\\n0.0%\\n2.0%\\n4.0%\\n6.0%\\n8.0%\\n1980\\n1985\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\nBudget balance (% of GDP)\\nYear\\nTotal\\nCentral\\nLocal\\nFigure 3.3  \\u0007\\nBudget balance of central and local governments in China as a proportion of \\nGDP\\nSource: National Bureau of Statistics (2019).\\n\\n\\n36  Environmental governance\\nWith increasing decentralization in the economic reform, more and more budg­\\netary items were shifted with local governments as primary entities of governmen­\\ntal expenditures. Reflecting the division of governmental affairs, the central and \\nlocal governments now have distinct responsibilities on a variety of expenditure \\nitems. Foreign affairs and national defense are two budgetary items that the cen­\\ntral government takes almost exclusive responsibility to account for 99.5% and \\n98.1%, respectively, of total governmental expenditures. Of the central govern­\\nment’s expenditure in 2018, 33.8% was devoted to national defense. Grain storage \\nis for the country’s food security, and thus, the central government remained more \\nimportant, being responsible for 66.8% of all governmental expenditures in 2018 \\n(Figure 3.5). Science and technology is another classical category of public good \\nthat the market underinvests in to require public expenditures, in which the central \\ngovernment took a share of 37.5% in 2018 (Figure 3.5). Health care and urban \\nand rural communities are almost exclusively the responsibility of local govern­\\nments. Environmental protection was responsible for 2.9% of total governmental \\nexpenditures in 2018 (Figure 3.6), while local governments accounted for 93.2% \\n(Figure 3.5). It occupied 3.1% of local governments’ expenditures and 1.3% of the \\ncentral government’s (Figure 3.6).\\nThe expenditure structures between the central and local governments have \\nremained generally unchanged for environmental protection in the past decade. \\nHowever, this largely decentralized budgetary item has also witnessed signs of \\nBeijing\\nTianjin\\nHebei\\nShanxi\\nInner Mongolia\\nLiaoning\\nJilin\\nHeilongjiang\\nShanghai\\nJiangsu\\nZhejiang\\nAnhui\\nFujian\\nJiangxi\\nShandong\\nHenan\\nHubei\\nHunan\\nGuangdong\\nGuangxi\\nHainan\\nChongqing\\nSichuan\\nGuizhou\\nYunnan\\nTibet\\nShaanxi\\nGansu\\nQinghai\\nNingxia\\nXinjiang\\n–100.0%\\n–90.0%\\n–80.0%\\n–70.0%\\n–60.0%\\n–50.0%\\n–40.0%\\n–30.0%\\n–20.0%\\n–10.0%\\n0.0%\\n0\\n20,000\\n40,000\\n60,000\\n80,000\\n100,000\\n120,000\\n140,000\\n160,000\\n)\\ns\\ne\\nr\\nu\\nt\\ni\\nd\\nn\\ne\\np\\nx\\ne\\n \\nl\\na\\ni\\nc\\nn\\ni\\nv\\no\\nr\\np\\n \\nf\\no\\n \\n%\\n(\\n \\ne\\nc\\nn\\na\\nl\\na\\nb\\n \\nt\\ne\\ng\\nd\\nu\\nB\\nGDP per capita (RMB/person)\\nFigure 3.4  \\u0007\\nGovernmental budget balance by provinces as a proportion of governmental \\nexpenditures in 2018\\nSource: National Bureau of Statistics (2019).\\n\\n\\nEnvironmental governance  37\\n0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0% 90.0% 100.0%\\n Total\\n Interregional aid\\n Urban & rural communities\\n Health care\\n Agriculture, forestry & water\\n Social security & employment\\n Commercial services\\n Education\\n Environmental protection\\n Housing\\n Resource exploration & information\\n Culture, sports & communication\\n General public service\\n Transportation\\n Public security\\n Land, ocean & meteorology\\n Others\\n Science & technology\\n Debt interest\\n Financial\\n Debt issuance\\n Grain storage\\n National defense\\n Foreign affairs\\nShare of governmental expenditures\\nLocal’s share\\nCentral’s share\\nFigure 3.5  \\u0007\\nThe central and local governments’ shares of expenditures by budgetary items \\nin 2018\\nSource: National Bureau of Statistics (2019).\\n0%\\n5%\\n10%\\n15%\\n20%\\n25%\\n30%\\n35%\\n Interregional aid\\n Urban & rural communities\\n Health care\\n Agriculture, forestry & water\\n Social security & employment\\n Commercial services\\n Education\\n Environmental protection\\n Housing\\nResource exploration & information\\n Culture, sports & communication\\n General public service\\n Transportation\\n Public security\\n Land, ocean & meteorology\\n Others\\n Science & technology\\n Debt interest\\n Financial\\n Debt issuance\\n Grain storage\\n National defense\\n Foreign affairs\\nShare of governmental expenditures\\nLocal\\nCentral\\nTotal\\nFigure 3.6  \\u0007\\nCentral, local and overall governmental expenditures by budgetary items in 2018\\nSource: National Bureau of Statistics (2019).\\n\\n\\n38  Environmental governance\\nslight recentralization. Recent reforms as described earlier reflected and enabled \\nthe central government to be keener in improving environmental quality and more \\ndirectly involved in supervising local governments. Environmental protection has \\nbeen listed as a separate budgetary item in the data from the China Statistical \\nYearbook since the 2008 edition (for 2007 data). Its share in total governmental \\nexpenditures has inched up from 2.0% in 2007 to 2.7% in 2010 and then fluctu­\\nated narrowly to reach 2.9% in 2018. The share in local governments’ budgets has \\nalso been quite stable, within a narrow range between 2.5% and 3.2% over the \\nperiod. However, the central government had a significant shift, allocating a much \\ngreater share of its budget for environmental protection. It ranged between 0.2% \\nand 0.5% from 2007 to 2013 but then jumped to 1.5% in 2014 and has remained \\nat the level since then (Figure 3.7). Correspondingly, the central government’s \\nshare in total environmental protection expenditures was lifted from 2.9% in 2013 \\nto 9.0% in 2014, while the local governments’ share dropped although their envi­\\nronmental protection expenditures were increased every year in absolute terms.\\nThe significant uplifting in 2014 indicates that environmental protection has \\nbeen increasingly prioritized in China’s public affairs (Figure 3.7). The additional \\nbudget mainly corresponded to the strengthened functions of top-­\\ndown supervi­\\nsion, monitoring and inspection of local governments’ performance. Because the \\nshares in governmental expenditure for China as a whole and for local governments \\n0.0%\\n1.0%\\n2.0%\\n3.0%\\n4.0%\\n5.0%\\n6.0%\\n7.0%\\n8.0%\\n9.0%\\n10.0%\\n2007\\n2008\\n2009\\n2010\\n2011\\n2012\\n2013\\n2014\\n2015\\n2016\\n2017\\n2018\\ns\\ne\\nr\\nu\\nt\\ni\\nd\\nn\\ne\\np\\nx\\ne\\n \\nl\\na\\nt\\nn\\ne\\nm\\nn\\nr\\ne\\nv\\no\\ng\\n \\nn\\ni\\n \\ns\\ne\\nr\\na\\nh\\nS\\nYear\\nCentral’s share in environmental\\nprotection expenditures\\nEnvironmental protection’s share in total\\nexpenditures\\nEnvironmental protection’s share in\\ncentral’s total expenditures\\nEnvironmental protection’s share in\\nlocal’s total expenditures\\nFigure 3.7  \\u0007\\nShares in governmental expenditures\\nSource: National Bureau of Statistics (2019).\\nNote: The National Statistical Yearbook listed environmental protection as a separate budgetary item \\nfor the first time in 2007.\\n\\n\\nEnvironmental governance  39\\ndid not change significantly over the period and especially in 2014, environmen­\\ntal administrative capacities were not expected to be upgraded disproportionally \\nagainst other governmental affairs. The emphasis on environmental protection \\nthus targeted the relationship between the central and local governments to more \\neffectively mobilize implementation capacities and to assign a heavier weighting \\nto environmental protection relative to local economic development.\\n6  \\u0007\\nCentralized and decentralized personnel management\\nAccording to the Chinese Constitution, local leaders are elected by corresponding \\nlocal People’s Congress. Then they are supposed to mainly please their local elec­\\ntorate. Because China’s weak rule of law does not ensure the local implementa­\\ntion of environmental laws and policies from the National People’s Congress and \\nthe central government, the central government should only be able to exert very \\nconstrained authority over the selection of local government leaders and what \\ngovernmental affairs they decide to pursue in their local contexts. Even if local \\nleaders refused to implement policies from the top, only local People’s Congress \\ncan remove them. However, this very decentralized arrangement presents a sharp \\ncontrast with reality. Far-­\\nreaching reforms in the past four decades have featured \\neconomic reforms on the relationship between the state and the market and admin­\\nistrative reforms on the relationship between the central and local governments, \\nbut the relationship between the Chinese Communist Party and the Chinese gov­\\nernment has witnessed fewer changes. In the 1980s, their separation was debated \\nand explored in tentative reforms, but the progress has been much slower.\\nThe party plays a crucial role in shaping the central–local leadership relation­\\nship in reality. The party and the Chinese government have overlapped organiza­\\ntions in the governmental bureaucracy, while the party is even more prevalent \\nto be present in enterprises and other nongovernmental organizations. Although \\nlocal leaders should be elected by local People’s Congress, the party, and espe­\\ncially its Department of Organization, controls the nominations. For the four gov­\\nernmental levels, each level has the authority to appoint leaders at one lower level. \\nFor example, the party’s Department of Organization at the central level controls \\nthe nomination of provincial-­\\nlevel leaders (including those in central ministries). \\nEach provincial Department of Organization nominates municipality-­\\nlevel lead­\\ners within the province. The appointment decisions are in the hands of their cor­\\nresponding party committees. As a result, personnel decisions are one crucial \\nchannel for the central government to influence local governments. Numerous \\nstudies have confirmed that China does put governance performance in the deci­\\nsions to promote or remove officials, especially local government leaders (Li and \\nZhou, 2005; Zhou, 2007). Without the party’s role, China’s governance would be \\nsubstantially different from the current institutional arrangement.\\nFurthermore, a reform did bring a major change in this personnel relationship \\nwith significant decentralization. In 1984, the Central Committee of the party \\nreformed its personnel management system (Gao and Zou, 2007). Before then, the \\nDepartment of Organization at each level managed two levels down. For example, \\n\\n\\n40  Environmental governance\\nthe Central Department of Organization was in charge of nominating and manag­\\ning leaders at the provincial and municipality levels. After the reform, the leaders \\nat the municipality level are left to the sole responsibility of the Provincial Depart­\\nment of Organization, while the Central Department of Organization only takes \\ncare of the provincial-­\\nlevel leaders. As a result, the provincial leaders will have \\nmuch stronger control of their staff and other local government leaders below \\nthem. Such reform substantially reinforces local leaders’ authorities within their \\njurisdictions. The arrangement coincides with the decentralization of governmen­\\ntal affairs and expenditures but still maintains a powerful channel through the \\nparty for the central government to control local leaders.\\nReferences\\nDepartment of Organization of the Central Committee of the Communist Party of China. \\n1999. On reforming the institutions of managing environmental officials. Beijing, China: \\nCentral Committee of the Communist Party of China.\\nGao, X. & Zou, Q. 2007. Research on intra-­\\nparty democracy – evaluation from history and \\nreality. Shandong, China: Qingdao Press.\\nThe General Office of the CPC Central Committee & The General Office of the State \\nCouncil. 2016. Guiding advice on the pilot vertical reform in sub-­\\nprovincial monitoring, \\ninspection and enforcement agencies. Beijing, China: CPC Central Committee, State \\nCouncil.\\nKaufmann, D.  & Kraay, A. 2019. The worldwide governance indicators 2019 update: \\nAggregate governance indicators 1996–2018 [Online]. Available: https://info.world­\\nbank.org/governance/wgi/.\\nLi, H. B. & Zhou, L. A. 2005. Political turnover and economic performance: The incentive \\nrole of personnel control in China. Journal of Public Economics, 89, 1743–1762.\\nMinistry of Environmental Protection. 2002–2016. Annual statistical report on the envi­\\nronment in China. Beijing, China: Ministry of Environmental Protection.\\nMinistry of Environmental Protection, National Statistics Bureau  & Ministry of Agri­\\nculture. 2010. Public report on the first national census of polluting sources. Beijing, \\nChina: Ministry of Environmental Protection, National Statistics Bureau.\\nNational Bureau of Statistics. 2019. China statistical yearbook. Beijing, China: China Sta­\\ntistics Press.\\nNational People’s Congress. 2000. Law of atmospheric pollution prevention and control \\nof people’s republic of China. Beijing, China: The 4th Conference of the 10th National \\nPeople’s Congress.\\nNational People’s Congress. 2017. Law of water pollution prevention and control. Beijing, \\nChina: The 4th Conference of the 10th National People’s Congress.\\nNational People’s Congress. 2018. Law of atmospheric pollution prevention and control \\nof people’s republic of China. Beijing, China: The 4th Conference of the 10th National \\nPeople’s Congress.\\nSCOPSR. 2018. The function, internal organization and personnel of the ministry of ecol­\\nogy and environment. Beijing, China: SCOPSR.\\nState Council. 1993. Decision on implementing the tax sharing mechanism in fiscal man­\\nagement. Beijing, China: State Council.\\nState Council. 2018. Reform plan on the state council. Beijing, China: State Council.\\n\\n\\nEnvironmental governance  41\\nThe U.S. Congress. 1990. Clean air act amendments 1990. Washington, DC: The U.S. \\nCongress.\\nWang, H., Dong, Z., Xu, Y. & Ge, C. 2016. Eco-­\\ncompensation for watershed services in \\nChina. Water International, 41, 271–289.\\nZhou, L. 2007. Governing China’s local officials: An analysis of promotion tournament \\nmodel. Economic Research Journal, 7, 36–50.\\n\\n\\n1  \\u0007\\nGoals in China’s Five-­\\nYear Plans\\nChina’s top leadership has gradually gained strong enough political will for \\nenvironmental protection over the past decades (Chapter  2). However, the \\ndecentralization of policy making and, to a greater extent, policy implementa­\\ntion requires the cooperation between the central and local governments to \\nrealize the environmental political will with concrete improvement of environ­\\nmental quality and pollution mitigation (Chapter 3). This chapter is devoted \\nto understanding how the entire Chinese government, from central to local \\ngovernments, is mobilized through environmental goals, especially in Five-­\\nYear Plans.\\nGoals have been widely used in governance. For example, UNFCCC (United \\nNations Framework Convention on Climate Change) defines its goal as “stabili­\\nzation of greenhouse gas concentrations in the atmosphere at a level that would \\nprevent dangerous anthropogenic interference with the climate system” (United \\nNations, 1992). President Barack Obama set up a goal to withdraw all U.S. troops \\nfrom Iraq by the end of 2011 (DeYoung, February 28, 2009). Many studies are \\nabout environmental goals, including those on negotiating goals, distributing \\ngoals (Chakravarty et al., 2009), policies to achieve goals (such as on emission tax \\nand cap-­\\nand-­\\ntrade) and technological achievability of goals (Pacala and Socolow, \\n2004).\\nA theoretical foundation of using goals as a governance tool can be traced to \\nstudies in social psychology: through experiments on individuals, the impact of \\nvarious goals on task performance is examined. Locke et al. (1981) reviewed \\nthe literature and concluded that “specific and challenging goals lead to higher \\nperformance than easy goals, ‘do your best’ goals, or no goals.” Furthermore,\\ngoal setting is most likely to improve task performance when . . . the subjects \\nhave sufficient ability, . . . feedback is provided to show progress in rela­\\ntion to the goal, rewards such as money are given for goal attainment, the \\nexperimenter or manager is supportive, and assigned goals are accepted by \\nthe individual.\\n(Locke et al., 1981)\\n4\\t\\n\\u0007\\nMobilizing the government1\\n\\n\\nMobilizing the government  43\\nIn the experiments, goals are distributed to individuals and individuals try to accom­\\nplish the goals. The situation is not much different from an environmental goal \\nin a big country like China. The Chinese central government plays a similar role \\nas experimenters: it decides a goal and distributes it to local governments. Three \\ncomponents could be distinguished: (1) goal setting, (2) goal distribution and (3) \\ngoal attainment. Goal setting refers to what type of goals should be set up and how \\nstringent they are. Because a global or national goal often requires the cooperation \\nof different political or administrative entities, goal distribution is necessary. For \\nexample, a global goal of carbon dioxide (CO2) mitigation should be distributed to \\nindividual countries, and a Chinese national goal should be distributed to provinces. \\nFurthermore, these goals need to be accepted before serious efforts are made. The \\nthird component of a goal process focuses on evaluating goal attainment. Strong-­\\nenough incentives should be put into place to mobilize goal implementers.\\nThe seven-­\\ndecade history of the People’s Republic of China can be divided \\ninto two periods: a centrally planned economy in the first three decades and a later \\nera of market-­\\noriented economic reforms. Since the 1950s, originally adopted \\nfrom the Soviet Union, Five-­\\nYear Plans have become pivotal to guide China’s \\neconomic development. Although China’s economy was strictly state-­\\ncontrolled \\nbefore the economic reforms began in 1978, only the first of the earliest five Five-­\\nYear Plans was actually completed (Liu et al., 2006). The other four were not able \\nto be performed due to frequent political movements, with the Cultural Revolu­\\ntion as the most notable one (Liu et al., 2006).\\nFive-­\\nYear Plans gained momentum only in the second period when China tried \\nto establish a market-­\\noriented economy. Starting from the 6th Five-­\\nYear Plan \\n(1981–1985), China has gradually formed a set of rules to design these plans \\n(State Council, 2005b). The 11th Five-­\\nYear Plan (2006–2010) was the first to \\nchange its name from “jihua” (more forceful plans) to “guihua” (more directional \\nplans). Goals are the most important indicators in the Plans. From the 11th Five-­\\nYear Plan, goals are distinguished into foreseeable ones (such as the growth rates \\nof gross domestic product [GDP] and population) and legally binding ones (such \\nas pollutant mitigation; National People’s Congress, 2006). In addition, China’s \\nFive-­\\nYear Plans are not just one document but a system composed of many layers. \\nFor example, for the nation as a whole, there was a National 11th Five-­\\nYear Plan \\nthat included a 10% reduction goal of sulfur dioxide (SO2) emissions. Another \\n11th Five-­\\nYear Plan on Environmental Protection provided further details. At one \\nmore layer lower, the 11th Five-­\\nYear Plan on Acid Rain and SO2 Pollution Control \\nspecifically addressed the mitigation of SO2 emissions. There were also 11th Five-­\\nYear Plans at all governmental levels.\\nGoals are playing more and more prominent roles in China’s environmental \\nprotection, especially in Five-­\\nYear Plans, to mobilize local governments and the \\nChinese bureaucracy. If expressed in percentage terms, the baseline year is the \\nfinal year of the previous Five-­\\nYear Plan. For example, China’s energy intensity \\ngoal in the 11th Five-­\\nYear Plan (2006–2010) was a 20% reduction (National Peo­\\nple’s Congress, 2006); it indicates that China planned to reduce energy intensity, \\nor energy consumption per unit of GDP, by 20% in 2010 from the 2005 level.\\n\\n\\n44  Mobilizing the government\\nIn regulating SO2 emissions that mainly come from the burning of coal, China \\nrelies on absolute emission goals, which were a 3.8% increase, a 10% reduction, a \\n10% reduction, an 8% reduction and a 15% reduction, respectively, for the 9th, 10th, \\n11th, 12th and 13th Five-­\\nYear Plans (National People’s Congress, 2001, 2006, 2011; \\nNEPA et al., 1996; National People’s Congress, 2016). The actual growth rates of \\nSO2 emissions were a 15.8% reduction, a 27.8% increase, a 14.3% reduction and a \\n14.9% reduction, respective for the 9th, 10th, 11th and 12th Five-­\\nYear Plans, indi­\\ncating goal attainment in all but the 10th Five-­\\nYear Plan (National Statistics Bureau \\nand Ministry of Ecology and Environment, 2019). This chapter specifically analyzes \\nthe 10% reduction goal of SO2 emissions in the 11th Five-­\\nYear Plan as it reversed \\nthe humiliating failure in the 10th Five-­\\nYear Plan. The national quantitative goal \\nwas centrally set up to involve the Chinese top leadership and the then State Envi­\\nronmental Protection Administration (SEPA, presently the Ministry of Ecology and \\nEnvironment). The mitigation tasks were distributed to provincial and other local \\ngovernments with their individual goals. Mechanisms were put into place to moni­\\ntor the goal compliance statuses of local governments and take enforcement actions \\nfor their cooperation. Goals have also been rapidly evolving to reflect the status and \\nintended emphasis of SO2 mitigation and air pollution control.\\n2  \\u0007\\nCentralized goal setting\\n2.1  Setting up the national goal\\nChina’s goal process involves three overlapping cycles: Five-­\\nYear Plans, National \\nParty’s Congresses and National People’s Congresses. The 11th Five-­\\nYear Plan for­\\nmally started in 2006 and concluded in 2010. The 16th National Party’s Congress \\nlasted from October 2002 to October 2007. The 10th National People’s Congress \\nlagged half a year behind, from March 2003 to March 2008. The 11th Five-­\\nYear Plan \\ndid not begin until the middle of the two Congresses. Under China’s present political \\nreality, the two Congresses have a reasonable sequence. The National Party’s Con­\\ngress selects party leaders. After a further distribution of power, these leaders assume \\nvarious governmental jobs in the following National People’s Congress. The first \\ngatherings of these two Congresses are mainly about determining the leadership of \\nthe party and the country. Then China’s leaders reshuffle every five years. As a result, \\nthe three cycles are actually two: the Five-­\\nYear Plans and the change of leadership.\\nThe cycles have existed in the present form for about four decades, espe­\\ncially since 1992. The most stable cycle is the Five-­\\nYear Plan. All Five-­\\nYear \\nPlans are targeted for five years, even in the most irrational period of the Cul­\\ntural Revolution. Since the 3rd Five-­\\nYear Plan (1966–1970), the period has been \\nconsecutive. The National Party’s Congress formed its own five-­\\nyear cycle in \\n1977, and the National People’s Congress, in 1978. But the leadership change did \\nnot match the Congresses’ cycles until 14 years later. Jiang Zemin was formally \\nelected as the secretary general of the party in 1992 and the president of China in \\n1993. Since then, China’s top leaders also have established their five-­\\nyear cycles, \\nformally synchronized with the Congresses.\\n\\n\\nMobilizing the government  45\\nThe cycles of Five-­\\nYear Plans do not match China’s change of leadership. The \\nanchor year of a Five-­\\nYear Plan is the previous year before the plan starts. But \\nbecause the plan has to be formed before all information in the anchor year is \\nknown and China’s SO2 emissions are very volatile, relative goals are much bet­\\nter than absolute goals to address the huge uncertainty. China’s failure to attain \\nthe 10% reduction goal of SO2 emissions in the 10th Five-­\\nYear Plan (2001–2005) \\nmay partly reflect the mismatch among cycles. A new administration took full \\ncharge in March 2003 when the 10th Five-­\\nYear Plan had been going on for over \\ntwo years. Almost immediately afterward, China’s SO2 emissions went out of con­\\ntrol. During 2001–2002, SO2 emissions went down by 3.4%, but in the remaining \\nthree years (2003–2005), the emissions surged by 32.3% (SEPA, 2001–2009). \\nOn the other hand, the sharp contrast was not obvious from the perspective of \\neconomic growth. In annual terms, China’s economy expanded at an annual rate \\nof 8.7% in the first two years and 10.2% later (National Bureau of Statistics of \\nChina, 1999). Although the surge could be simply a coincidence with the change \\nof leadership, if 2003 through 2005 had been under the same administration as in \\n2001–2002, the result might be different due to a better unification of planning \\nand implementation.\\nThe Outline of the National 11th Five-­\\nYear Plan on Economic and Social \\nDevelopment (hereafter referred to as the Outline) was the title of an official \\ndocument ratified by the National People’s Congress, the nominally highest \\nauthority in China, in March  2006 (National People’s Congress, 2006). The \\n10% reduction goal of SO2 emissions was clearly included to be legally bind­\\ning. The process to reach the Outline can be divided into three periods: (1) mid-­\\n2003 to December 2004, concluded with the formation of The Basic Thoughts \\nof the National 11th Five-­\\nYear Plan (hereafter referred to as the Basic Thoughts; \\nNational Development and Reform Commissions, or NDRC, was responsible); \\n(2) February 2005 to October 2005, ended with the ratification of The Sugges­\\ntions on Designing the National 11th Five-­\\nYear Plan (hereafter referred to as \\nthe Suggestions; the Central Committee of the Chinese Communist Party was \\nin charge); (3) October 2005 to March 2006, indicated by the enactment of the \\nOutline (State Council took the hold).\\nThe Basic Thoughts contemplated the strategic direction of the Outline. This \\nidea-­\\nframing period was initiated in mid-­\\n2003 and completed by the end of 2004 \\n(Xinhua News Agency, 2006; NDRC, 2003). For environmental protection, the \\njob of the 11th Five-­\\nYear Plan was to “decelerate the trend of ecological and envi­\\nronmental deterioration and strengthen the ability of sustainable development” \\n(NDRC, 2005). The wording clearly differs from, for example, “improving envi­\\nronmental quality.” It may be reflected later in the Basic Thoughts on Environ­\\nmental Protection with a flat SO2 emission goal proposed (SEPA, 2006d; Chinese \\nAcademy for Environmental Planning [CAEP], 2004).\\nThe then named SEPA was responsible for writing the 11th Five-­\\nYear Plan for \\nEnvironmental Protection. The SEPA understood the specific difficulty of control­\\nling SO2 emissions. For example, in 2002, Wang Xinfang, a deputy administrator \\nof the SEPA, admitted that it was hard to achieve the 10% reduction goal of SO2 \\n\\n\\n46  Mobilizing the government\\nemissions in the 10th Five-­\\nYear Plan (2001–2005; Wang, 2002). The final result in \\n2005 confirmed his concern: goals on other pollutants were either met or slightly \\nmissed, but SO2 emissions were 27.8% higher than the level in 2000 and 42% higher \\nthan the original goal (Zou et al., 2006). The SEPA distributed The Basic Thoughts \\non Environmental Protection on December 23, 2004, and proposed a flat goal for \\nthe 11th Five-­\\nYear Plan (SEPA, 2006d; CAEP, 2004). The midterm assessment on \\nthe 10th Five-­\\nYear Plan that was completed in 2004 could have played a guiding \\nrole in the proposal: the available data showed an 8.2% increase of SO2 emissions \\nin 2003 compared with those in 2000 (SEPA, 2001–2009). The midterm assessment \\nbelieved that the 10% reduction goal had fallen out of reach but still expected that \\nSO2 emissions in 2005 could remain the same as the level in 2000 (Zou et al., 2004).\\nWith the tentative Basic Thoughts, the top leadership in the Central Committee of \\nthe Chinese Communist Party got directly involved. The period was formally initi­\\nated with the establishment of a high-­\\nprofile drafting team on February 16, 2005, \\nheaded directly by Premier Wen Jiabao (Xinhua News Agency, 2005). A prominent \\nfeature is the multiple meetings presided by President Hu Jintao in the Political \\nBureau or its Standing Committee and by Premier Wen Jiabao in the drafting team \\n(Xinhua News Agency, 2005). The Suggestions was finally passed and endorsed \\non October 11, 2005, by the Central Committee of the Chinese Communist Party \\n(Xinhua News Agency, 2005). Sharply different from the Basic Thoughts, the Sug­\\ngestions clearly declared to “reduce total emissions of pollutants,” which essentially \\nindicated a goal of improving environmental quality (Xinhua News Agency, 2005).\\nAfter the Suggestions tightened the goal for environmental protection in Octo­\\nber 2005, the third period started with the establishment of a drafting team that \\ncomprised various ministries in the central government (Xinhua News Agency, \\n2006). An expert committee was summoned to comment on the drafts of the Out­\\nline (Ma, 2005). The public was also consulted for advice (Ma, 2005). Presi­\\ndent Hu Jintao and Premier Wen Jiabao organized several meetings to discuss the \\ndrafts (Xinhua News Agency, 2006). In November 2005, the SEPA drafted a plan \\non acid rain and SO2 emission control (SEPA, 2005). Although SO2 emissions in \\n2004 had been 13% higher than the 2000 level, the 10% reduction goal for the \\n11th Five-­\\nYear Plan first appeared (SEPA, 2005, 2001–2009). On December 3, \\n2005, State Council enacted Decisions on Realizing Scientific View of Develop­\\nment and Strengthening Environmental Protection (State Council, 2005a), which \\nlinked the new ideology of Scientific View of Development with environmental \\nprotection. It confirmed the importance of environmental protection in the estab­\\nlishment of the new ideology. When the 4th Conference of the 10th National Peo­\\nple’s Congress was in session, the Outline was submitted on March 5, 2006, and \\napproved on March 14, 2006 (Xinhua News Agency, 2006).\\n2.2  \\u0007\\nMethods of goal setting\\nA Five-­\\nYear Plan anchors at the previous year of its planning period. For exam­\\nple, a goal in the 11th Five-­\\nYear Plan (2006–2010) is to compare 2010 with \\n2005. In practice, the anchor year’s data cannot be fully utilized in setting up \\n\\n\\nMobilizing the government  47\\nthe goals. China generally published environmental data for the previous year in \\naround June (SEPA, 2001–2009). Although the public may get the information \\nlater than the Chinese government, several months could elapse for the collection \\nand compilation of data. Accordingly, the anchor year’s information cannot be \\nfully employed in planning but has to be the foundation for the next Five-­\\nYear \\nPlan. China’s annual change of SO2 emissions varied greatly: the 2004 emissions \\nwere 4.5% up from the 2003 level, but the figure surprisingly jumped 13.1% \\nin 2005 (SEPA, 2001–2009). At the same time, however, the economic growth \\nrates were quite stable with 10.1% in 2004 and 11.4% in 2005 (National Bureau \\nof Statistics, 2019). Because of the substantial volatility, the absence of data in \\nthe most relevant and important anchor year could cause significant trouble in \\ncalibrating goals.\\nTwo components were important in setting up China’s SO2 emission goals in \\nFive-­\\nYear Plans: long-­\\nterm goals and appropriate mitigation paces. China relied \\non a concept called “environmental capacity” to decide long-­\\nterm SO2 emission \\ngoals (Yang et al., 1998, 1999). “Environmental capacity” refers to the upper-­\\nlimit \\nemissions of a pollutant without degrading a kind of environmental quality below \\na minimum level. The environmental capacity for SO2 emissions is a function of \\nthree variables: (1) the amount and distribution of SO2 emissions, or emission \\ninventories; (2) the transport and sinks of SO2; and (3) an acceptable level of some \\nenvironmental quality. The second variable is largely determined by atmospheric \\ncirculation and chemistry. The third variable was used as an external choice. If \\nsociety would like to live in a better environment, the limit of ambient SO2 con­\\ncentration could be lowered and SO2 emissions have to be further reduced.\\nTo set up an SO2 goal in a Five-­\\nYear Plan, China first decided on a long-­\\nterm \\ngoal and then found an appropriate mitigation pace to attain the goal. The long-­\\nterm goals were determined with models of atmospheric transport and chemistry. \\nThe implicit long-­\\nterm goal for the 10th Five-­\\nYear Plan (2001–2005) was 12 mil­\\nlion tons and was scheduled to get attained in 2020 (Wang, 2002). For the 11th \\nFive-­\\nYear Plan (2006–2010), the long-­\\nterm goal became 18 million tons and the \\ngoal attainment year would also be 2020 (SEPA, 2005). Although both goals were \\nsupported by scientific research with different constraint conditions, the signifi­\\ncant upward revision of the long-­\\nterm goal probably arose as a result of the sharp \\nincrease in coal use that led to an unanticipated rise of SO2 emissions in the 10th \\nFive-­\\nYear Plan.\\nThe long-­\\nterm goals have certain scientific foundations. China’s Law of Envi­\\nronmental Protection clearly holds local governments responsible for local envi­\\nronmental quality (National People’s Congress, 1989). Because ambient air quality \\nstandards are also “mandatory standards” in the Law of Standardization (State \\nCouncil, 1990), local government leaders should be mobilized to enforce SO2 miti­\\ngation policies if the law were well respected. In 1996, the then State Environmen­\\ntal Protection Agency enacted ambient air quality standards (NEPA and SBTS, \\n1996). Most of China’s land area with economic and human activities should \\nhave ambient SO2 concentration in annual mean below 0.060 mg/m3. One key \\nstudy showed that only to achieve this average concentration within grid boxes of \\n\\n\\n\\n48  Mobilizing the government\\n0.2° × 0.2°, China has to control its SO2 emissions at 12 million tons (Yang et al., \\n1999). Another study for the 11th Five-­\\nYear Plan selected critical acid deposition \\nwithin grid boxes of 1° × 1° (Zou et al., 2006). Although the number was based \\non several heavy assumptions (most important, the geographical distribution of \\nSO2 emission sources), it signaled the stringency of the ambient SO2 concentra­\\ntion standard. For example, China’s goal in the 11th Five-­\\nYear Plan was to reduce \\nSO2 emissions from 25.5 million tons in 2005 by 10% in 2010, still far above the \\n12-­\\nmillion-­\\nton level (National People’s Congress, 2006).\\nThe distribution of SO2 emissions matters greatly for any national SO2 miti­\\ngation goal that is based on SO2 concentration. For example, with SO2 concen­\\ntration of 0.060 mg/m3 as the constraint condition, Shanghai could emit up to \\n0.63 million tons of SO2 (Yang et al., 1999), but its actual emissions in 2007 were \\n0.50 million tons (Ministry of Environmental Protection, 2008). Then if a pollut­\\ning source was located in Shanghai, it would have no necessity to mitigate. But if \\nthe same source were moved to Jiangsu, a neighboring province with its emission \\nlimit below actual emissions (Ministry of Environmental Protection, 2008; Yang \\net al., 1999), it would be subject to serious abatement. The 1998 study revealed a \\ngoal based on SO2 ambient concentration: if not counting the excess environmen­\\ntal capacity in Tibet compared with its emissions (0.50 million tons vs. 1.5 thou­\\nsand tons), China’s national goal was to reduce SO2 emissions to about 12 million \\ntons (Yang et al., 1999). China planned to attain the goal in 2020 (Wang, 2002). \\nThe goal for the 10th Five-­\\nYear Plan was then established as a 10% reduction, or \\n18 million tons (SEPA, 2001).\\nAfter the big failure in the 10th Five-­\\nYear Plan on SO2 mitigation, China still \\nheld 2020 as the attainment year of a long-­\\nterm goal. However, the original goal \\nwould be too difficult. In 2005, China emitted 25.5 million tons of SO2 (SEPA, \\n2001–2009). To achieve the goal of 12 million tons in 2020, a 53% reduction in \\n15 years would be required. Even if from the 2004 level when a new goal for the \\n11th Five-­\\nYear Plan was formed, the reduction rate should still be 47% (SEPA, \\n2001–2009). By replacing the constraints of SO2 concentration with critical acid \\ndeposition, a new environmental capacity was worked out to be 17.3 million tons \\n(Zou et al., 2006). Then 18 million tons were chosen to be the new long-­\\nterm \\ngoal (SEPA, 2005). These two long-­\\nterm goals assumed a similar pace of about 2 \\nto 2.5 million tons reduction per five years. Because of the relatively stable pace \\nand a common attainment year of the long-­\\nterm goals, China’s long-­\\nterm goals \\nseemed to be reversely decided from current emission levels. Interestingly, both \\nlong-­\\nterm goals were supported by scientific research. The history could indicate \\nthat the results of the scientific research were selected beforehand by nonscientific \\nfactors.\\nIn deciding goals for Five-­\\nYear Plans, the emission trends in previous years \\nwere also considered (Wang et al., 2004). Because the 9th Five-­\\nYear Plan achieved \\na 15.8% reduction (NEPA et al., 1996; SEPA, 2001–2009), even a similar trend \\nwas thought to be too stringent (Wang et al., 2004). Probably the 10% reduction \\ngoal was established because it stood between the 15.8% reduction and the origi­\\nnal goal of a 3.8% increase in the 9th Five-­\\nYear Plan. A middle ground, closer to \\n\\n\\nMobilizing the government  49\\nthe stringent end, was taken. On the other hand, the same historical trend would \\nbe too relaxed for the 11th Five-­\\nYear Plan. SO2 emissions went up by 27.8% in \\nthe 10th Five-­\\nYear Plan (SEPA, 2001–2009). Certainly this was not an acceptable \\ntrend, but it might be an important factor that drove the initial flat goal for the \\n11th Five-­\\nYear Plan (CAEP, 2004). The same principle could have been followed: \\n0% change was closer to the stringent end between a 27.8% increase and a 10% \\nreduction. As a result, the goal attainment in the previous Five-­\\nYear Plan should \\nhave played an important role in framing a goal for the next.\\nThe United States’ goal of SO2 emissions in Clean Air Act Amendments \\n(CAAA; 1990) was also expressed in relative terms. Relative to the emission \\nlevel in the anchor year of 1980, SO2 emissions were planned for reduction by \\n10 million tons (The U.S. Congress, 1990). Although an intensive 10-­\\nyear study \\nwas performed in the 1980s (National Acid Precipitation Assessment Program), \\nit failed to answer relevant questions for policy making and was not closely con­\\nnected to the goal-­\\nsetting process (Roberts, 1991; Pouyat and McGlinch, 1998). \\nFor a fixed long-­\\nterm goal, different anchor years only correspond to different rel­\\native reductions or different expressions of the figures. Furthermore, 1980 was not \\na baseline year for allowance allocation. Rather, 1985 was a much more impor­\\ntant year with real implications in grandfathering emission permits. However, if \\nthe 10-­\\nmillion-­\\nton reduction was fixed, the choice of 1980 did have important \\nimplications. In 1980, the U.S. emitted 23.5 million tons of SO2 and the figures in \\n1985 and 1990 were, respectively, 21.1 and 20.9 million tons (U.S. Environmental \\nProtection Agency, 2007). Essentially, the choice of 1985 and 1990 would have \\nno difference. But anchoring in 1980 could effectively relax the long-­\\nterm goal by \\nabout 2.4 to 2.6 million tons. The goal was planned for attainment in 2010. The \\nanchor year 1980 was ten years ahead of the legislation and 15 years before the \\nprogram formally started in 1995. Although whether a goal was expressed in rela­\\ntive or absolute terms matters greatly in China, it was generally not quite relevant \\nfor the United States’ goal setting. The United States had much less volatility in \\nannual SO2 emissions. The burden to achieve the goal – the difference between \\nbusiness-­\\nas-­\\nusual emissions and the goal – was accordingly much less uncertain \\nthan China’s. The major benefit of relative terms was to reduce the uncertainty of \\nsurprising emission growth or reduction. However, less uncertainty in the United \\nStates and the longer goal cycle did not distinguish this benefit. Furthermore, the \\nAcid Rain Program’s goal cycle was much longer than China’s Five-­\\nYear Plans. \\nBecause of the well-­\\nestablished rule of law, the law ensured that the SO2 mitiga­\\ntion efforts would continue regardless of who was the president or which political \\nparty he or she belonged to.\\n3  \\u0007\\nTop-­\\ndown goal distribution\\nGoal implementation refers to a process for goal implementers to receive, accept \\nand work for goal attainment. It is quite different from policy implementation. \\nGoal implementation deals with the relationship among different governments or \\ntheir agencies, while policy implementation focuses on the relationship between \\n\\n\\n50  Mobilizing the government\\nthe government and polluters, including industrial plants and individuals. Goal \\nsetters and goal implementers are usually separate in the Chinese government. \\nSince goal setters are not directly in charge of achieving the goal, they have \\nto find a way to get goal implementers to accept the goal and to work hard for \\nit. In order for effective goal implementation, subgoals should be created from \\nthe national goal to demand an appropriate distribution scheme. The UNFCCC \\ndefines a principle of sharing the duty of reducing greenhouse gas emissions \\namong countries according to “common but differentiated responsibilities and \\nrespective capabilities” (United Nations, 1992). Which applicable principles \\nshould be followed has attracted negotiation debates and academic studies \\n(Chakravarty et al., 2009; Li, 2010).\\nA national goal and its distribution to local governments often fall into separate \\ndecision-­\\nmaking processes in the Chinese setting. Taking the SO2 goal in the 11th \\nFive-­\\nYear Plan (2006–2010) as an example, the national 10% reduction goal was \\nlargely decided by the top leadership of the party, but provincial goals came from \\na bargaining process between the central government – mainly the then SEPA – \\nand provincial governments.\\n3.1  \\u0007\\nGoal distribution from the central to provincial governments\\nChinese local governments are divided into several levels, mainly provinces, \\nmunicipalities and counties. To implement SO2 emission goals, the central gov­\\nernment distributed subgoals to provincial and local governments and issued \\nincentives to mobilize their leaders. A good national goal is hard to implement \\nwithout a fair distribution of the burden. After a national goal is framed, provinces \\nwill negotiate with the central government for their shares of the burden. The \\ndetails of the negotiation and their applied principles are not publicly available but \\ncould be reversely examined from the outcome.\\nChina qualitatively disclosed principles to distribute the national goal to \\n31 provinces. Key influential factors included environmental quality, environmen­\\ntal capacity, current emission level, economic development status, SO2 mitigation \\ncapability, requirements of various pollution control plans and regional category \\n(west, middle, east; State Council, 2006). An explicit formula was less likely to \\nexist that connected these factors with a province’s goal. However, published pro­\\nvincial information could at least lead to an evaluation of potentially quantitative \\nrelationships. Econometric analysis was applied here with a linear assumption.\\nThe dependent variable was provincial SO2 emission goals in percentage \\nterms: SO2 emission target in 2010 / SO2 emissions in 2005 – 100%. The dis­\\ntributed national goal, 11.9% reduction, was actually a little more stringent than \\na 10% reduction (State Council, 2006). All provinces combined could only emit \\n22.47 million tons, not 22.94 million tons for the nation. The difference (0.47 mil­\\nlion tons) was reserved for experimenting with SO2 emission cap-­\\nand-­\\ntrade (State \\nCouncil, 2006).\\nIndependent variables included all those factors indicated by the Chinese govern­\\nment (State Council, 2006). Because 2005 was the anchor year of the 11th Five-­\\nYear \\n\\n\\nMobilizing the government  51\\nPlan, independent variables all referred to this year unless otherwise specified. Envi­\\nronmental quality was represented by both the annually average SO2 concentra­\\ntion in provincial capitals and nonpower sectors’ emission density (expressed in \\ntons/km2). The capitals’ SO2 concentration data were published in China Statistical \\nYearbooks (National Bureau of Statistics, 2006). In addition, China divided SO2 \\nemissions into two big categories: power and nonpower. Associated with shorter \\nchimneys, non-­\\npower-­\\nsector emissions were believed to be more closely associ­\\nated with local air quality (SEPA, 2006a). Their emission densities in provinces \\nwere employed to represent another perspective of environmental quality (National \\nBureau of Statistics of China, 1999; Zou et al., 2006). Environmental capacity is a \\nterm indicating allowed maximum emissions to maintain a certain environmental \\nquality. The data used in this section came from a study that calculated long-­\\nterm \\nSO2 goals for the 11th Five-­\\nYear Plan (Zou et al., 2006). Critical acid deposition \\nwas the targeted environmental quality. The corresponding upper-­\\nlimit national \\nemissions were 17.3 million tons, and each province had its own figure (Zou et al., \\n2006). Current emission levels were represented by provincial SO2 emissions in \\n2005. Provincial goals were formally distributed in August 2006 (State Council, \\n2006). Because data for 2005 had been published in June 2006 (SEPA, 2001–2009), \\nthey should be available for negotiating the goal distribution. Provincial GDP per \\ncapita stood for economic development status (National Bureau of Statistics, 2006).\\nNo definition had been clearly displayed by the Chinese authorities on SO2 \\nmitigation capability. Two variables were used. First, higher provincial SO2 \\nremoval rates in 2005 could indicate fewer opportunities for the future. From \\nanother aspect, they also represented previous efforts in SO2 mitigation. Second, \\nSO2 scrubbers (or flue-gas desulfurization facilities, FGD) had been designated as \\na key measure to reduce SO2 emissions in the 11th Five-­\\nYear Plan (State Council, \\n2007a). The power sector’s shares of total emissions would then serve as another \\nindicator of mitigation capability (National Bureau of Statistics of China, 1999; \\nZou et al., 2006). Higher shares may lead to a more effective reduction of total \\nSO2 emissions through SO2 scrubbers.\\nChina’s policies and emission control plans targeting individual emission \\nsources could decide provincial goals in a bottom-­\\nup way. Nevertheless, it may \\nnot coincide with the top-­\\ndown results. For example, effluent emission standards \\nand SO2 scrubber planning, respectively, were expected to lead to national power \\nsector’s emissions of 8.9 and 9.7 million tons in 2010, while the finally assigned \\ngoal was 9.5 million tons in the 11th Five-­\\nYear Plan (Zou et al., 2006). To evalu­\\nate their impact on goal distribution, two independent variables were generated \\nfor each province: (1) (Emission standard-­\\ndesignated levels in the power sector \\nin 2010 + Nonpower emission goals in 2010) / Provincial emissions in 2005 – \\n100% (State Council, 2006; Zou et al., 2006; National Bureau of Statistics of \\nChina, 1999) and (2) (Scrubber planning-­\\nprojected emissions in power sector + \\nNonpower emission goals in 2010) / Provincial emissions in 2005 – 100% (State \\nCouncil, 2006; Zou et al., 2006; National Bureau of Statistics of China, 1999).\\nAccording to geographical locations and economic advancement, China \\ndivides its provinces into three regional groups: west, center and east. To alleviate \\n\\n\\n52  Mobilizing the government\\nregional disparity in economic growth and income, China treats the three cat­\\negories differently. For example, “Great West Development” aimed to develop \\nwestern provinces, particularly through building infrastructure. Dummy variables \\nwere generated to indicate a province’s location. In addition, because China’s \\nprevalent wind generally transports air pollutants from the west to the east, SO2 \\nemissions in western provinces could cause more damage than those in eastern \\nprovinces. The dummy variables then evaluated the overall impacts of these two \\nopposite concerns.\\nBesides these variables, several others that were not mentioned in the official \\ndistribution plan were also tested, including SO2 emissions per capita, goal attain­\\nment in the 10th Five-­\\nYear Plan and electricity export. One argument for China \\nnot to accept a legally binding goal on carbon mitigation in the Kyoto Protocol \\nwas its low carbon emissions per capita. Whether China applied this principle in \\ndomestic practice was examined through provincial SO2 emissions per capita in \\n2005 (National Bureau of Statistics of China, 1999).\\nChina failed substantially to achieve its 10% reduction goal of SO2 emis­\\nsions in the 10th Five-­\\nYear Plan (2001–2005): the actual emissions in 2005 \\nwere 42% higher than the original goal (SEPA, 2001–2009, 2001). But some \\nprovinces did better than others. Whether better performance in the past was \\nrecognized is tested through a ratio: Provincial emissions in 2005 / Provincial \\nemission targets in the 10th Five-­\\nYear Plan for 2005 (State Council, 2006; \\nNational Bureau of Statistics of China, 1999). In addition, for the 27 prov­\\ninces used in models (discussed later), this variable was highly correlated with \\nthe provincial growth rates of SO2 emissions in the 10th Five-­\\nYear Plan and \\nthe correlation coefficient is 0.98. Accordingly, the model results on this goal \\nattainment variable could be almost identically applied to a variable on the \\ngrowth rates.\\nPollutant emissions and product consumption are not necessarily in the same \\nlocation. Electricity is a clear and important case. SO2 comes out of coal-­\\nfired \\npower plants, but electricity could be lighting bulbs in another province. This \\neffect was examined through provincial electricity trade: Provincial electricity \\ngeneration / Provincial electricity consumption – 100% (National Bureau of Sta­\\ntistics, 1997–2008).\\nAlthough mainland China has 31 provinces, only 27 were used for the statisti­\\ncal models. Four provinces were kept out. Hainan and Tibet had too-­\\ninsignificant \\nSO2 emissions in 2005, respectively, 22,000 and 2,000 tons. Qinghai had the least \\nemissions among provinces except the two previously mentioned, and its data on \\navoided industrial emissions were not available in China Statistical Yearbooks. \\nShanghai had its nonpower SO2 emission density in 2005 much higher than \\nother provinces (32.7 tons/km2; the next highest was 7.9 tons/km2), a far outlier \\n(National Bureau of Statistics of China, 1999; Zou et al., 2006).\\nThe correlation coefficients between the variables are given in Table 4.1. Pro­\\nvincial goals were highly correlated negatively with nonpower emission density, \\ntotal SO2 emissions and GDP per capita – indicating that higher levels of these \\nvariables were closely associated with more stringent provincial goals  – and \\n\\n\\nMobilizing the government 53\\nElectricity\\nexport\\nin 2005\\n1.00\\nGoal\\nattainment\\nFive−\\nin the\\n10th \\nYear Plan\\n1.00\\n0.31\\n \\n \\n2\\nemission\\n \\nSO\\nper\\ncapita\\nin 2005\\n1.00\\n0.17\\n0.35\\nest\\n1.00\\n0.25\\n0.06\\nW\\n−0.17\\nMiddle\\n1.00\\n−0.46\\n−0.03\\n0.42\\n0.52\\n \\nEmission\\n \\nd\\n \\nstandar\\ndecided\\ngoals\\n1.00\\n−0.08\\n−0.54\\n−0.44\\n−0.07\\n−0.44\\nScrubber\\nplanning\\n \\ndecided\\ngoals\\n1.00\\n0.02\\n0.16\\n0.21\\n−0.03\\n0.32\\n0.10\\n \\ns\\n’\\nPower\\nemission\\ne\\n0.30\\nshar\\nin 2005\\n1.00\\n−0.23\\n0.10\\n0.21\\n−0.29\\n0.18\\n0.28\\nTibet, and Shanghai.\\n2\\nemoval\\nRate\\nin 2005\\n1.00\\n−0.22\\n−0.03\\n0.10\\n0.05\\nSO\\nr\\n−0.08\\n−0.40\\n−0.14\\n−0.05\\nCorrelation coefficients of key factors for 27 provinces\\nGDP\\nper capita\\nin 2005\\n1.00\\n−0.13\\n0.25\\n−0.33\\n0.75\\n−0.28\\n−0.46\\n−0.14\\n−0.22\\n−0.54\\notal\\nin 2005\\n1.00\\n−0.16\\n−0.16\\n0.05\\n−0.39\\n−0.41\\n0.01\\n−0.17\\n0.00\\n0.21\\nT\\nemissions\\n0.24\\n \\nLong−\\nterm\\n1.00\\n0.15\\n0.14\\ngoal\\n−0.30\\n−0.08\\n−0.35\\n0.31\\n−0.19\\n−0.18\\n−0.01\\n−0.05\\n−0.02\\nNonpower\\n \\nemission\\ndensity\\nin 2005\\n1.00\\n−0.04\\n0.22\\n0.59\\n−0.01\\n0.00\\n−0.36\\n0.29\\n−0.32\\n−0.26\\n0.03\\n−0.60\\n−0.47\\ns\\nCapital’\\n conc.\\n2\\n1.00\\n0.17\\n0.05\\n0.16\\nSO\\nIn 2005\\n−0.04\\n−0.12\\n−0.34\\n1\\n0.1\\n−0.17\\n−0.23\\n0.39\\n0.24\\n−0.30\\n−0.05\\nReduction\\n1.00\\n0.00\\ngoal\\n−0.74\\n−0.06\\n−0.53\\n−0.48\\n0.18\\n−0.10\\n0.63\\n−0.06\\n0.35\\n0.24\\n0.01\\n0.44\\n0.40\\nReduction goal\\n \\n \\nable 4.1(a)\\ns SO2\\nconcentration\\ns mainland has 31 provincial regions. Four are not included here: Qinghai, Hainan, \\n \\n \\n \\nemission\\n \\nCapital’\\nNonpower\\ndensity\\nLong−term goal\\n \\nT\\nGDP/capita\\n \\nTotal emissions\\nRemoval rate\\n \\ns\\n’\\nemission\\n \\nPower\\nshare\\nScrubber\\nplanning\\nEmission\\nstandard\\nMiddle\\nest\\nEmission/capita\\nElectricity\\nexport\\nW\\nGoal attainment\\nNote: China’\\n\\n\\n54  Mobilizing the government\\n0.0\\n0.12\\n7.9\\n3.7\\n200.2\\n4.5\\n0.6\\n0.7\\n0.1\\n0.0\\n1\\n1\\n61.0\\n1.3\\n0.6\\nMax\\n−20.4\\n0.02\\n0.2\\n−0.3\\n19.0\\n0.5\\n0.1\\n0.3\\n−0.3\\n−0.2\\n0\\n0\\n9.3\\n0.0\\n−0.6\\nMin\\n.\\nDev\\nStd. \\n5.7\\n0.020\\n2.09\\n1.02\\n48.39\\n0.91\\n0.16\\n1\\n1\\n0.1\\n0.1\\n0.09\\n0.48\\n0.47\\n13.26\\n0.34\\n0.24\\n0.057\\n−10.1\\n2.97\\n0.81\\n91.97\\n1.55\\n0.28\\n0.52\\n−0.09\\n−0.13\\n0.33\\n0.30\\n22.95\\n0.51\\n0.03\\nMean\\nNo. of \\nobservations\\n27\\n27\\n27\\n27\\n27\\n27\\n27\\n27\\n27\\n27\\n27\\n27\\n27\\n27\\n27\\near Plan\\near Plan\\near Plan\\near Plan\\near Plan\\nPeriod\\n11th Five-Y\\n2005\\n2005\\n1th Five-Y\\n1\\n2005\\n2005\\n2005\\n2005\\n1th Five-Y\\n1\\n11th Five-Y\\n2005\\n10th Five-Y\\n2005\\nUnit\\n%\\nton/km2\\nSummary of variables\\nmg/m3\\n%\\n10,000 tons\\n10,000 RMB/person\\n%\\n%\\n%\\n%\\ndummy\\ndummy\\nkg/person\\n%\\n%\\n conc.\\n \\ns emission share\\nTable 4.1(b)\\nariables\\nV\\nReduction goal\\n2\\ns SO\\nCapital’\\nNonpower emission density\\nlong-term goal\\n’\\nTotal emissions\\nGDP/capita\\nRemoval rate\\nPower\\nScrubber planning\\nEmission standard\\nMiddle\\nest\\nW\\nEmission/capita\\ngoal attainment\\nElectricity export\\n\\n\\nMobilizing the government  55\\npositively with SO2 emissions from scrubber planning, goal attainment in the 10th \\nFive-­\\nYear Plan and electricity export.\\nAlthough nonlinear terms could show consistent significance in models, such \\nas the squared term of nonpower SO2 emissions density, its actual application in \\nthe negotiation for provincial goals was difficult. China very likely did not use a \\nwritten formula to decide provincial goals. The nonlinear relationship was thus \\ntoo complicated for arguments, especially those with a turning point. In addition, \\nonce included, several far points could greatly change the overall relationship \\nin models. For example, if Shanghai appeared in the models, its big nonpower \\nSO2 emission density would make the corresponding coefficient much different. \\nThese provinces might experience special negotiation. As a result, only linear \\nterms were used in the models to examine China’s principles in goal distribution.\\nAnother decision about the regression models was whether a constant vari­\\nable should be included. If all provinces had to presume a basic reduction goal \\nand adjust it according to specific situations, the constant variable would show \\nsignificance and the explained variance, R2, should be higher compared with a \\nno-­\\nconstant model. Model runs indicated otherwise (Table 4.2). In response, no \\nconstant variable appeared in the remaining models.\\nThe model results showed that two variables were the most important in dis­\\ntributing the national goal to provinces. First, richer provinces tended to receive \\nmore stringent reduction goals. Provincial GDP per capita in 2005 and provincial \\ngoals in the 11th Five-­\\nYear Plan had a correlation coefficient of −0.48 (Table 4.1). \\nBut statistical models did not consistently show the significance of GDP per capita \\n(Table 4.2). However, if either nonpower emissions density in 2005 or provincial \\ngoals from scrubber planning were excluded, GDP per capita would become sig­\\nnificant. For every 10,000 RMB/person increase, the province should reduce its \\nSO2 emissions by further 1.3% (from the 2005 level). In explaining the model \\nresults, a problem was that two factors had a high correlation, and both showed \\nsignificance on some occasions. However, it should not have mattered much in the \\nnegotiation. As long as no clear formula decided goals, a province could always \\nargue with one factor to generate a more favorable goal. For example, Shanghai \\nhad a much higher nonpower SO2 emission density in 2005 than other provinces, \\nbut its GDP per capita in 2005 was ahead, with a significantly narrower margin \\n(52,000 RMB/person compared with the next highest 45,000; National Bureau of \\nStatistics of China, 1999; Zou et al., 2006). Comparatively, Shanghai could ask \\nfor a less stringent goal from GDP-­\\nper-­\\ncapita point of view. Second, provinces \\nwith large emissions had tougher goals. China’s big provinces experienced greater \\npressure to reduce their emissions more for achieving the national goal. Coeffi­\\ncients of provincial emissions in 2005 were consistently significant (Table 4.2). \\nEvery 100,000 tons more SO2 emissions corresponded to about 0.47% further \\nreduction. Third, nonpower emissions density displayed consistent significance. \\nFor emitting one more ton per square kilometer, a province should further reduce \\ntotal SO2 emission by about 1.3%.\\nNotably, several other variables did not show much influence. First, provinces \\nwith worse environmental quality might not have received more stringent goals. \\n\\n\\n56  Mobilizing the government\\n***\\nModel 9\\n***\\n−0.058\\n**\\n**\\n \\n \\n \\n−2.79\\n \\n \\n10.09\\n12.71\\n \\n \\n \\n3.62\\n6.33\\n \\n0.94\\nModel 8\\n***\\n**\\n \\n−0.033\\n**\\n−1.29\\n \\n−0.97\\n \\n \\n15.39\\n3.33\\n \\n \\n \\n \\n \\n \\n0.94\\n***\\nModel 7\\n***\\n \\n−1.34\\n*\\n \\n−0.047\\n−1.27\\n \\n \\n \\n \\n \\n \\n \\n \\n \\n \\n0.93\\n***\\nModel 6\\n*\\n \\n−0.83\\n−0.066\\n*\\n−1.73\\n \\n \\n \\n \\n \\n \\n \\n \\n1.98\\n4.48\\n \\n0.93\\nModel 5\\n**\\n*\\n \\n−0.042\\n*\\n \\n−1.00\\n−1.47\\n \\n \\n12.98\\n12.55\\n \\n \\n0.05\\n0.73\\n4.43\\n \\n0.94\\nRegression model results for distributing the national goal to provinces\\n***\\nModel 4\\n−0.80\\n−0.43\\n−0.064\\n*\\n−1.87\\n \\n \\n \\n \\n \\n \\n \\n0.01\\n2.16\\n3.96\\n \\n0.93\\nModel 3\\n***\\n*\\n**\\n47.28\\n−1.22\\n−0.99\\n−0.038\\n−2.25\\n2.40\\n1.43\\n15.35\\n9.83\\n0.36\\n−0.99\\n \\n \\n \\n \\n0.94\\nModel 2\\n*\\n−1.14*\\n40.03\\n−0.86\\n−0.041\\n−1.95\\n*\\n4.48\\n−2.42\\n14.10\\n15.38\\n−0.13\\n−0.90\\n0.07\\n0.58\\n3.69\\n \\n0.95\\nModel 1\\n*\\n*\\n39.51\\n−1.14\\n−0.88\\n−0.041\\n−1.98\\n4.36\\n−2.63\\n14.08\\n15.47\\n−0.18\\n−0.95\\n0.07\\n0.57\\n3.74\\n0.31\\n0.76\\ndensity\\n2\\n \\n per capita\\nT\\nIndependent variables\\n concentration\\n2\\ns SO\\ns emission share\\nR\\nable 4.2\\nCapital’\\nNonpower emission \\nLong-term goal\\nRemoval rate\\nPower\\nEmission standard\\nMiddle\\nest\\nTotal emissions\\n’\\nGDP\\nScrubber planning\\nW\\nEmission/capita\\nGoal attainment\\nElectricity export\\nConstant\\nAdjusted \\n* Significant at 10%. ** Significant at 5%. *** Significant at 1%.\\n\\n\\nMobilizing the government  57\\nProvincial capital cities’ SO2 concentration did not significantly affect provincial \\ngoals (Table 4.2). But in most provinces, capital cities only occupy a fraction \\nof the total land area and thus could not represent the general picture. Another \\nproblem with this variable was its coefficient’s sign. Intuitively, the sign should \\nbe negative – dirtier air needs more reduction of pollutant emissions. The actual \\ncoefficient, although not significant, was consistently positive (Models 1–3 in \\nTable 4.2). To avoid its impact, the variable was excluded from other models. \\nSecond, provinces with higher emissions per capita did not face deeper reduc­\\ntions. Emissions per capita did not have any significant relationship with pro­\\nvincial reduction goals. Third, earlier efforts on SO2 emission control were not \\nawarded later with relaxed goals. Neither of the two relevant variables – SO2 \\nremoval rates in 2005 and goal attainment in the 10th Five-­\\nYear Plan – showed \\nany consistent significance. Earlier efforts did not make the future easier in SO2 \\nemission control, while no failure in the past would get punished through adding \\nfuture burden. Because of the very high correlation between the goal attainment \\nvariable and provincial growth rates of SO2 emissions in the 10th Five-­\\nYear Plan, \\nthe model results also indicated that faster emission growth did not have a sig­\\nnificant impact on provincial goals. For China’s political reality, this result was \\nreasonable. Provincial and other local leaders often rotate every five years. If one \\nadministration was irresponsible, its failure did not get the next administration \\npunished. Similarly, a performing administration should not reduce pressure on \\nfuture leaders. Fourth, more electricity net export consistently led to less strin­\\ngent goals, but the relationship was not statistically significant. It seemed that \\nChina did not take serious consideration of the disintegration between emissions \\nand consumption in distributing environmental goals. Fifth, no influence was \\nfound solely due to the location of a province. Regional characteristics should \\nhave been absorbed into other variables. For example, long-­\\nterm goals already \\nconsidered prevalent wind and more damage from western SO2 emissions. West­\\nern and central provinces were poorer than eastern ones, which was reflected in \\nGDP per capita.\\nThree principles were distinguished for distributing the national SO2 emission \\ngoal in the 11th Five-­\\nYear Plan: those provinces with heavier pollution, bigger \\ntotal emissions and richer GDP per capita should reduce more. The second prin­\\nciple was the most consistently applied. An explicit formula of deciding a provin­\\ncial goal could be written as\\nProvincial Goal (−0 to −100) = −1.34 × Nonpower emission density \\n(tons/km2) – 0.047 × Total emissions (10,000 tons) − 1.27 × GDP \\nper capita (10,000 RMB/person).\\nThe 27 provinces had an arithmetic average goal in the 11th Five-­\\nYear \\nPlan of −10.1%. The formula would lead to −10.2%: GDP per capita, −2.0%; \\nnonpower SO2 emissions density, −4.0%; and total emissions, −4.3%. The \\nexplanatory power was high, with adjusted R2 generally over 0.93 (Model 7 in \\nTable 4.2).\\n\\n\\n58  Mobilizing the government\\n3.2  \\u0007\\nGoal distribution from provincial to municipality governments\\nThe SEPA issued guidance for distributing SO2 emission goals from one govern­\\nment level to its subordinate level (SEPA, 2006a). The total emissions are dis­\\ntinguished into the power sector (capacity no less than 6 MW) and nonpower \\nsectors (SEPA, 2006a). The SO2 emission quota was generally assigned to each \\nfossil-­\\nfuel power plant according to provincially homogeneous emission inten­\\nsity (grams SO2/kWh, varying with plant ages; SEPA, 2006a). As shown in Fig­\\nure 4.1, the designated emission intensity was more stringent in new coal power \\nplants and those in eastern or richer provinces. From provinces to municipalities, \\npolluting sources in nonpower sectors received their upper limits on the basis \\nof achieving local air quality – particularly SO2 emissions concentration with a \\nthreshold of 0.060 mg/m3 (SEPA, 2006a). The guidance did not clarify everything \\nfor assigning goals. It left decisions to provincial governments, especially in non­\\npower sectors. More important, the excess emission quota of a region was allowed \\nto transfer or trade across regions (SEPA, 2006a).\\n0.0\\n1.0\\n2.0\\n3.0\\n4.0\\n5.0\\n6.0\\n7.0\\n8.0\\nEast-1\\nEast-2\\nCentral\\nSouthwest\\nNorthwest\\nO\\nS\\n \\nd\\ne\\nt\\na\\nn\\ng\\ni\\ns\\ne\\nD\\n2\\nO\\nS\\n \\ns\\nm\\na\\nr\\ng\\n(\\n \\ny\\nt\\ni\\ns\\nn\\ne\\nt\\nn\\ni\\n \\nn\\no\\ni\\ns\\ns\\ni\\nm\\ne\\n2/kWh)\\nPeriod I\\nPeriod II\\nPeriod III\\nFigure 4.1  \\u0007\\nDesignated SO2 emission intensity in distributing SO2 emissions quota to coal-\\nfired power plants for 2010 in the 11th Five-Year Plan\\nSource: SEPA (2006a).\\nNote: Coal-fired power plants falling in Period I refer to those that went online or passed the Environ­\\nmental Impact Assessment reports before December 31, 1996. Period II spans from January 1, 1997, \\nto December 31, 2003. And Period III is from January 1, 2004, to the present. “East-1” includes the \\nprovinces of Liaoning, Hebei, Shandong, Zhejiang, Fujian and Hainan. “East-2” covers Beijing, Tian­\\njin, Shanghai and Jiangsu Provinces. “Central” refers to Heilongjiang, Jilin, Shanxi, Henan, Hubei, \\nHunan, Anhui and Jiangxi Provinces. “Southwest” provinces are Chongqing, Sichuan, Guizhou, Yunnan, \\nGuangxi and Tibet. “Northwest” has Inner Mongolia, Shaanxi, Gansu, Ningxia, Qinghai and Xinjiang.\\n\\n\\nMobilizing the government  59\\nIn distributing provincial goals, official documents often did not even qualita­\\ntively declare what factors took effect. Furthermore, municipality data were not \\nas publicly available as provincial data. Two aspects receive special attention in \\nexamining the provincial scheme of goal distribution: (1) whether the same prin­\\nciples in the national goal distribution held and (2) whether the SEPA’s guidance \\nwas followed. This section looks at four provinces: Hebei, Guangdong, Jiangsu \\nand Shanxi. Statistical model results are given in Table 4.3. Those models without \\nsignificance are not shown. According to how the four provinces obey the national \\nprinciple – rich and big provinces reduce more – a matrix is generated in Table 4.4.\\nProvinces have high autonomy in further allocating their goals among munici­\\npalities. The four provinces are distinguished with different patterns to dem­\\nonstrate such decentralized authority. In Hebei Province, all municipalities got \\nroughly same reduction goals. The provincial goal of Hebei Province was a 15% \\nreduction from 1.50 million tons in 2005 (State Council, 2006). It had 11 munici­\\npalities, and their SO2 emissions in 2005 ranged from 45,000 to 311,000 tons \\n(Hebei Provincial Government, 2007). GDP per capita also varied, from 9,900 to \\n27,900 RMB/person (Hebei Provincial Statistics Bureau, 2006). The 2005 data on \\nthe power sector’s share in SO2 emissions are not publicly available. Information \\nfrom the goals for 2010 is applied instead: the share of the power sector would \\nrange from 13.4% to 53.4% in the plan (Hebei Provincial Government, 2007). \\nHowever, municipality goals only varied from a 14.1% to a 15.8% reduction, \\ncentering on the provincial goal (Hebei Provincial Government, 2007). Statistical \\nmodels indicated a consistently significant constant (Table 4.3). But neither GDP \\nper capita nor SO2 emissions showed any impact on municipality goals. If the \\ngoal distribution guidance from the central government worked, a municipality \\nwith more SO2 emissions from the power sector should receive somewhat more \\nstringent goals. But no negotiation seemed to have shaped the municipality goals. \\nThe provincial government, very likely its top leaders, decided that the provincial \\ngoal was applied to all with minor adjustments.\\nIn Guangdong Province, higher income and more SO2 emissions led to more \\nstringent goals. In the 11th Five-­\\nYear Plan, Guangdong Province received a \\nTable 4.3 Regression model results for distributing provincial goals to municipalities\\nHebei\\nGuangdong\\nJiangsu\\nShanxi\\nObservations\\n11\\n15\\n13\\n11\\nNonpower emission density in 2005\\n−1.5**\\nGDP/capita in 2005\\n−7.2***\\n6.2***\\nSO2 emissions in 2005\\n−3.3***\\n−1.4**\\n−0.98***\\nPower sector’s emission share in 2005\\n−58.1***\\n_Constant\\n−15.1***\\n33.9***\\n21.4**\\nAdjusted R2\\n0.90\\n0.76\\n0.86\\n0.87\\nNote: Six municipalities in Guangdong province with 2005 SO2 emissions no more than 11,000 tons \\nare not included in the model.\\n* Significant at 10%. ** Significant at 5%. *** Significant at 1%.\\n\\n\\n60  Mobilizing the government\\nprovincial goal of a 15% reduction from 1.29 million tons in 2005 (State Coun­\\ncil, 2006). Among its 21 municipalities, 5 emitted less than 10,000 tons in 2005, \\nand another 13, no more than 60,000 tons (Guangdong Environmental Protection \\nBureau, 2006). The biggest three emitted 475,000 tons, taking 51% of the pro­\\nvincial emissions that belonged to municipalities (929,000 tons; the remaining \\n365,000 tons were directly claimed to the provincial level; Guangdong Environ­\\nmental Protection Bureau, 2006). Collectively, these three should reduce their \\nSO2 emissions by 46% (Guangdong Environmental Protection Bureau, 2006). \\nThe other 18 municipalities were even allowed to increase their emissions by 23% \\n(Guangdong Environmental Protection Bureau, 2006). Regression models could \\nbetter distinguish influential factors. To avoid the heavy impacts of outlying data \\npoints, six municipalities were excluded, with total SO2 emissions in 2005 being \\nno more than 11,000 tons and their goals in 2010 allowed for over 170% growth. \\nModels for the rest of the 15 municipalities show significance of GDP per capita \\nand SO2 emissions (Table 4.3). Nonpower SO2 emissions density was not tested \\nbecause of data unavailability. Different from the situation for provincial goals, \\nthe constant variable here is significant. For every 10,000 RMB/person increase \\nof GDP per capita and 10,000 tons more of SO2 emissions in 2005, a municipal­\\nity goal would be, respectively, 7.2% and 3.3% more stringent (from the 2005 \\nlevel). Although the coefficients were different from those for provincial goals, \\nthe qualitative principles remained the same: rich and big municipalities should \\nreduce more.\\nIn Jiangsu Province, municipalities with higher emissions should reduce more, \\nbut richer ones were allowed to reduce less. Jiangsu Province’s goal was an 18% \\nreduction from 1.23 million tons in 2005 (State Council, 2006). The 13 munici­\\npalities emitted from 28,000 to 243,000 tons of SO2, a much narrower but still \\nlarger range than in Guangdong Province (Jiangsu Provincial Government, 2008). \\nSO2 emission goals varied between 2.6% to 53.6% reduction (Jiangsu Provincial \\nGovernment, 2008). Regression models included four independent variables, all \\nfor 2005 at municipality level: nonpower SO2 emissions density, GDP per capita, \\nSO2 emissions and the power sector’s share in total emissions (Table 4.3). The \\nconstant variable showed significance, and its appearance in models made the \\nadjusted R2 bigger. Corresponding to the increase of, respectively, 10,000 tons of \\nSO2 emissions, 1% of the power sector’s share and 1 ton/km2 of nonpower SO2 \\nemissions density, a municipality goal would become 1.4%, 0.6% and 1.5% more \\nstringent (from the 2005 level). The signs of these coefficients were all reasonable \\nand consistent with the situation of distributing the national goal to provinces, \\nbut GDP per capita displayed the opposite effect: for a municipality with 10,000 \\nRMB/person richer, its SO2 emissions were allowed to grow by 6.2%. For a prov­\\nince, this strategy of “rich municipalities reduce less” might maximize its GDP \\nas well as tax income through entitling more opportunities to more promising \\nmunicipalities.\\nIn Shanxi Province, municipalities with higher emissions should reduce more, \\nbut income level did not have significant impacts. Shanxi Province’s goal was a \\n14% reduction in the 11th Five-­\\nYear Plan from 1.52 million tons in 2005 (State \\n\\n\\nMobilizing the government  61\\nCouncil, 2006). Its 11 municipalities emitted from 92,000 to 185,000 tons of SO2 \\nin 2005, a much narrower range compared with the earlier three provinces or the \\nnational situation (Shanxi Provincial Government, 2006). Their GDP per capita \\nin 2005 was between 5,500 and 26,000 RMB/person (Shanxi Bureau of Statistics, \\n2006). The municipality goals were scattered from a 8.5% to a 17.8% reduction \\n(Shanxi Provincial Government, 2006). Only total SO2 emissions showed a sig­\\nnificant influence in the statistical models (Table 4.3). For emitting every 10,000 \\ntons more of SO2, a municipality goal would be about 1% more stringent (from \\nthe 2005 level). The GDP per capita’s coefficient was negative, although not sta­\\ntistically significant. The principle – big provinces should reduce more – held \\nhere. That rich provinces should reduce more was not well applied but could have \\nbeen considered.\\nIn conclusion, provinces differed from each other in adopting principles from \\ndistributing the national goal (Table 4.4), which closely reflected that China’s \\ngovernance and, especially, environmental governance had been greatly decen­\\ntralized (see Chapter 3). The most consistent principle across provinces was that \\nbigger emitters should reduce more. The guidance from the SEPA did not have to \\nbe exactly followed.\\n4  \\u0007\\nDecentralized goal attainment\\nTo keep the goal process running, goal attainment assessment is an inalienable \\nstep. It examines the effectiveness of the goal process and provides feedback. The \\nkey questions are what can be called goal attainment and how to evaluate it. For \\none Five-­\\nYear Plan, goal attainment evaluation does not wait until its conclusion. \\nIn the 11th Five-­\\nYear Plan, China publicized provincial SO2 emissions every half \\na year (State Council, 2007c). At the end of 2008, a halfway assessment was \\nscheduled (State Council, 2007c).\\n4.1  \\u0007\\nCriteria for goal attainment\\nIn the 11th Five-­\\nYear Plan, China established “three systems” to facilitate SO2 \\nmitigation, which covered statistics, monitoring and evaluation (State Coun­\\ncil, 2007b). This capacity building was planned and carried out by the SEPA \\nand endorsed by the State Council (State Council, 2007b). Because of China’s \\nTable 4.4 Provincial goal distribution matrix\\nRich guys reduce\\nLess\\nNeutral\\nMore\\nBig guys reduce\\nLess\\nNeutral\\nHebei\\nMore\\nJiangsu\\nShanxi\\nGuangdong\\n\\n\\n62  Mobilizing the government\\ndecentralization, that the central government mainly governs through provin­\\ncial governments, the national system only targeted the provincial level (State \\nCouncil, 2007b). The subordinate governments within provinces were evaluated \\nwith the rules passed along by provincial governments. For example, Zhejiang \\nProvince later enacted a more detailed, although not systematically different, \\nregulation targeting municipality and county governments (Zhejiang Provincial \\nGovernment, 2008).\\nProvincial goal attainment was evaluated with three criteria in the 11th Five-­\\nYear Plan (State Council, 2007b). The first criterion was on the quantitative goal \\nitself and environmental quality. It was often a binary judgment: if they were \\nattained, that was a mission accomplished. Excessive reduction would not be fur­\\nther awarded after the goal had been attained, while more emissions would not be \\npunished if the goal was already broken. The second criterion was on the establish­\\nment and operation of three institutions: environmental goal setting of major pol­\\nlutants, monitoring and goal attainment evaluation (State Council, 2007b). They \\nwere mainly judged by the enactment and distribution of official documents. The \\nthird one was on mitigation measures, including the completion and operation of \\npollutant removal facilities, the closure of inefficient factories, policy enactment \\nand plan implementation (State Council, 2007b). If any of the three criteria failed \\nto pass evaluation, the overall goal attainment would be judged a failure (State \\nCouncil, 2007b). Accordingly, one feature was that the attainment of the goal \\n\\nitself, despite its central importance, did not ensure overall success. The first crite­\\nrion focused on the results and the other two on the process. The regulation of the \\nChinese central government on the process provided feedback for local govern­\\nments for adjusting policies and monitoring their implementation.\\nThe 9th Five-­\\nYear Plan barely had any defined scheme to evaluate SO2 goal \\nattainment (NEPA et  al., 1996). The official document available in the public \\ndomain only pointed out that the SO2 control would be annually examined and \\nevaluated and the result would be publicized periodically (NEPA et al., 1996). \\nThe SO2 goal and its attainment process were better defined in the 10th Five-­\\nYear Plan, but no evaluation scheme was clearly defined either (SEPA, 2001). \\nThe National 10th Five-­\\nYear Plan for Environmental Protection only expressed \\nseveral principles, including holding local government leaders responsible and \\nlinking environmental goal attainment with the leaders’ performance evaluation \\n(SEPA, 2001). The evolution path displayed China’s progress in establishing a \\nworking evaluation scheme of SO2 emission goals. Although still not perfect, the \\nmuch clearer scheme in the 11th Five-­\\nYear Plan could have significantly contrib­\\nuted to the SO2 mitigation goal attainment.\\nRecognizing the importance of credible data collection for achieving SO2 emis­\\nsion goals in the 11th Five-­\\nYear Plan, China experienced an intensive capacity-­\\nbuilding process. In December  2006, the updated Management Methods of \\nEnvironmental Statistics entered into force (SEPA, 2006c). The regulation speci­\\nfied the organization and personnel for environmental statistics, rules on environ­\\nmental survey and management and publication of environmental data (SEPA, \\n2006c). For goal attainment in the 11th Five-­\\nYear Plan, China strengthened its \\n\\n\\nMobilizing the government  63\\nstatistical system focusing on data credibility. SO2 emissions were divided into \\nthree categories: power, nonpower industries and domestic (State Council, \\n2007b). The first two categories (industrial sectors) were further distinguished \\ninto two – key and non-­\\nkey surveyed sources – based on the sizes of emission \\nsources, and key surveyed sources covered 65% of total industrial SO2 emissions \\n(State Council, 2007b). Three parallel methods were applied under various situ­\\nations: direct monitoring, estimation according to sulfur budget and estimation \\naccording to emission factors (State Council, 2007b). The first method, if appli­\\ncable, had the highest priority (State Council, 2007b). SO2 emissions from non-­\\nkey surveyed sources were estimated following a similar trend as key surveyed \\nsources (State Council, 2007b). Data about coal consumption and sulfur contents \\nworked out SO2 emissions from domestic sectors (State Council, 2007b). In addi­\\ntion, if cheating were caught in an SO2 removal facility more than twice a year, \\nno SO2 removal would be recognized in the statistics data from the facility (State \\nCouncil, 2007b). Furthermore, another two significantly more detailed policies \\nwere enacted for building emission inventories (SEPA, 2007a, 2007d). Not only \\nwere detailed accounting methods clearly written, but also the data report was \\nregulated in specifics (SEPA, 2007a, 2007d).\\n4.2  \\u0007\\nIncentives for goal attainment\\nThe central government has decentralized its power greatly since the economic \\nreform started in 1978. As discussed in Chapter 3, three measures could exist \\nto incentivize the cooperation of local governments by targeting local leaders, \\nadministrative constraints and fiscal transfer. Corresponding to the personnel \\nrelationship that is mainly established across the various levels of the Chinese \\nCommunist Party, the top national leadership of the party can greatly decide the \\npromotion and removal of provincial-­\\nlevel leaders. The attainment of key goals, \\nincluding those on environmental protection and SO2 mitigation, had become an \\nimportant aspect in the evaluation of provincial leaders’ job performance. Con­\\ncerning SO2 mitigation goal implementation since the 11th Five-­\\nYear Plan, local \\ngovernment leaders but not local environmental protection bureau (EPB) leaders \\nwere targeted. The clear evidence was that provincial deputy governors, not EPB \\ndirectors, were required to sign pollutant emission control contracts with the cen­\\ntral government (SEPA, 2006b). The failure in the 10th Five-­\\nYear Plan on surging \\ncoal consumption demonstrated that pollution control had been far beyond the \\nresponsibility of EPBs alone.\\nOfficially five characteristics distinguish a leader in the Chinese Communist \\nParty for promotion or removal: virtue, ability, diligence, achievements and \\nabsence of corruption (The Central Committee of the Chinese Communist Party, \\n2002). Furthermore, after the formation of “Scientific View of Development,” \\nresource consumption, environmental protection and sustainable development \\nwere clearly pointed out to comprise “achievements” (Department of Organi­\\nzation of the Chinese Communist Party, 2006). Contracts on pollutant emission \\ncontrol and energy conservation clarified even more the responsibilities of local \\n\\n\\n64  Mobilizing the government\\ngovernment leaders (SEPA, 2006b). Two institutions were applied for the attain­\\nment of the SO2 emission goal in the 11th Five-­\\nYear Plan: accountability and \\nveto (State Council, 2007a). “Accountability” demanded local government lead­\\ners be held accountable for their governance that fell within their jurisdictions. For \\nexample, the administrator of the SEPA, Xie Zhenghua, was forced to resign in \\n2005 for a serious pollution event in the Songhua River. “Veto” meant that local \\ngovernment leaders would fail evaluation on their entire job performance if the \\nSO2 emission goal were not attained. Promotion became inappropriate for these \\nleaders. If goal failure did not degrade the leaders’ ranks, they may still face a risk \\nof being removed from original positions to some less significant ones. On the \\nother hand, successful goal attainment was an important achievement and could \\nhelp the leaders’ promotion. A recently developed method for targeting local lead­\\ners has been gradually promoted by the Ministry of Environmental Protection \\n(MEP) and later by the Ministry of Ecology and Environment. Top leaders of \\nthose provinces and municipalities that show serious environmental problems or \\nfail environmental goals are forced to have “interview appointments” with the \\nministry (Ministry of Ecology and Environment, 2020a). Although those local \\nleaders may not face immediate consequences of punishment, they will receive \\ncrucial warnings that darken their future promotion opportunities, especially if no \\nquick fix is achieved afterward.\\nAnother mechanism that was applied in the 11th Five-­\\nYear Plan was to tem­\\nporarily constrain local administrative authorities as punishment: if a goal was \\nnot attained, no new construction projects would receive the ratification of their \\nenvironmental impact assessment (EIA) reports for a given period. Over the 11th \\nFive-­\\nYear Plan period, large construction projects still demanded ratification from \\nthe central government. In terms of environmental protection, every project with \\npotential environmental damage should compose an EIA report and submit for \\nratification to various levels of governments (National People’s Congress, 2002). \\nThe SEPA, and later the MEP, at the central level was responsible for large pro­\\njects, such as new coal-­\\nfired power plants over 200 MW (SEPA, 2002). No project \\n\\nwithout the MEP’s ratification could legally start construction. In early 2007, the \\nSEPA temporarily suspended ratifying EIA reports of four municipalities and \\nfour power corporations (SEPA, 2007c). The suspension took effect for three \\nmonths to force their cooperation (SEPA, 2007b). Afterward, the policy was for­\\nmally established to target goal failure (SEPA, 2008). A failure to achieve the SO2 \\nemission goal could result in regional suspension for one month, three months or \\nhalf a year. If no satisfying progress were made, the suspension could even last \\nlonger until full cooperation. The “suspension” policy may seriously influence \\nthe regional economy. Since GDP is the most important criterion in evaluating \\nlocal leaders, this mechanism could effectively force cooperation. Capital invest­\\nment was a crucial part of China’s GDP. For example, in 2007, China’s over­\\nall GDP was 24.7 trillion RMB, and capital investment comprised 13.7 trillion \\nRMB, about 56% (National Statistics Bureau, 2008). A one-­\\nmonth suspension \\ncould delay construction and significantly affect capital investment and, conse­\\nquently, the local economy. GDP growth itself occupied the most important status \\n\\n\\nMobilizing the government  65\\nin evaluating local government leaders. In addition, a booming GDP could pro­\\nvide growing tax income not only to make officials more powerful but also to \\nenable more budgets for poverty alleviation, health care, education and other key \\ngovernmental affairs. Many of these issues are closely connected with the evalu­\\nation of leaders.\\nFiscal transfer has not been explicitly linked with environmental goal attain­\\nment. However, the very significant fiscal transfer from the central to local gov­\\nernments (as discussed in Chapter 3), if institutionally associated with pollutant \\nemission control, is potentially powerful to mobilize local governments for envi­\\nronmental protection.\\nWith China’s further decentralization of governmental authorities, the first \\nmechanism to directly target local governments is expected to be even more \\nimportant. In the past four decades, the central government has been continuously \\nloosening direct management of local governmental affairs. As a key feature of \\nthe economic reform, China has greatly reduced the requirements of adminis­\\ntrative ratification and decentralized much remaining authority to local govern­\\nments (State Council, 2013b, 2014). Fossil-­\\nfuel-­\\nfired power plants were no longer \\nrequired for the MEP’s ratification after 2015 and the authority entirely went to \\nprovincial governments (MEP, 2015; Ministry of Ecology and Environment, \\n2019).\\n5  \\u0007\\nGoal evolution\\nCorresponding to different strategies for controlling air pollution–induced health \\ndamages, three major types of goals can be adopted. First, emission mitigation \\ngoals of key pollutants, prominently SO2, aim to directly target the sources of \\nenvironmental pollution. The second type focuses on controlling air pollutant \\nconcentrations. Ambient air quality standards are widely adopted across coun­\\ntries to specify concentration thresholds of key air pollutants individually, such \\nas SO2, fine particulate matter (PM2.5) and ozone (O3). As discussed earlier, the \\ncontrol of ambient SO2 concentration was a key scientific foundation to decide \\nChina’s long-­\\nterm SO2 mitigation goal at 12 million tons (Yang et al., 1999). The \\nthird type targets environmental quality directly through the Air Quality Index \\n(AQI) that provides a synthesized measurement of key air pollutant concentra­\\ntions. The AQI also guides people’s activities corresponding to air quality condi­\\ntions. Although the three strategies have a similar ultimate goal for protecting \\npublic health, they have different implications for implementation. Local govern­\\nments can only directly mitigate local emissions while local pollutant concentra­\\ntion is determined by emissions within and outside of their jurisdiction as well as \\nweather conditions, land use and other factors. Then their motivation could differ \\nsignificantly under the different types of goals to affect their performance of pol­\\nlution mitigation.\\nOver the past two decades, China has been switching back and forth between \\nmajor governance strategies on environmental protection with different types of \\ngoals. \\nAs clearly stated in China’s environmental protection law, local governments \\n\\n\\n66  Mobilizing the government\\nare responsible for environmental quality within their jurisdictions (National Peo­\\nple’s Congress, 1989). However, environmental protection was not ranked high \\namong all governmental tasks in the 1990s. Local leaders generally prioritized \\neconomic growth for promotion opportunities. The 10th Five-­\\nYear Plan (2001–\\n2005) was a transitional period toward the Total Emission Control regime to set \\nup environmental goals for reducing major pollutant emissions by 10% (National \\nPeople’s Congress, 2001). However, due to the lack of environmental cleanup \\nincentives and the acceleration of economic growth, SO2 emissions went up by \\n27.8%, and only 2 out of 31 provinces achieved their allocated goals. Demand \\nfor serious, effective and efficient compliance monitoring had not been strong. \\nThe 11th Five-­\\nYear Plan (2006–2010) was a milestone in China’s environmental \\nprotection history. The Total Emission Control regime was strengthened, while \\nserious and implementable incentives were put into place for local governments \\nto achieve their individual mitigation goals (Xu, 2011). A bottom-­\\nup compliance \\nmonitoring system on emissions was initiated and established (SEPA, 2007d). \\nAlthough SO2 emissions did decline in the 11th Five-­\\nYear Plan, data manipulation \\nalso strained the compliance monitoring system as indicated in the gaps between \\nofficial and independent emission inventories (Lu et al., 2011).\\nConcerning SO2 emissions, two sets of regulations were most important and \\ndirect, being effluent emission standards and ambient air quality standards. Pre­\\nviously, cities were given goals of “blue sky” days. “Blue sky” was defined as \\nthat air quality reached the Grade 2 standard. One crucial change in the 2012 \\nversion ambient air quality standards was the addition of PM2.5 (MEP, 2012; \\nNational Environmental Protection Administration and State Bureau of Techni­\\ncal Supervision, 1996). PM2.5 concentration is more closely related to air quality \\nthat affects public health, while the emissions of SO2 and other pollutants are \\nonly indirect measures. In other words, PM2.5 goals are more related to ends of \\nair pollution control, while SO2 emissions goals are more about means. PM2.5 \\ncomprises many more pollutants, including sulfate particles that are originated \\nfrom SO2 emissions.\\nTogether with the 2012 update of the ambient air quality standards, China \\nenacted the Ambient Air Quality Index (Ministry of Environmental Protection, \\n2012). It synthesizes key air pollutant concentrations into one index to indicate \\nair quality. The cutoff AQIs between “excellent,” “good” and “polluted” air are 50 \\nand 100, respectively. Each air pollutant can calculate its individual AQI (IAQI) \\nand the composite AQI is the largest IAQI, or the IAQI of the primary air pol­\\nlutant. An AQI of 50 or lower corresponds to the Grade 1 ambient air quality \\nstandards, while 100 or lower corresponds to Grade 2. They provide the technical \\nfoundation for China to adopt regulatory strategies that are based on air qual­\\nity rather than pollutant emissions. Both regulations gave nearly four years of \\ngrace periods and formally entered into force in January 2016. The 12th Five-­\\nYear \\nPlan (2011–2015) initially continued with the Total Emission Control scheme to \\ninclude more pollutants (National People’s Congress, 2011). However, a major air \\npollution episode in January 2013 that badly hit North China, most notably Bei­\\njing, pushed the Chinese government to rethink its strategy (State Council, 2013a) \\n\\n\\nMobilizing the government  67\\nand accelerated the shift toward the air quality approach and the application of the \\ntwo related standards.\\nAir quality goals and emission mitigation goals of SO2, as well as other major \\nair pollutants, both aim for public health benefits. In order to achieve air quality \\ngoals that focus on ambient air pollution, efforts should still primarily fall on \\nthe mitigation of pollutant emissions together with their geographic and temporal \\ndistributions. Due to the atmospheric transport of air pollution, the attainment of \\nPM2.5 goals depends not only on a region’s own mitigation efforts but also that of \\nneighboring regions. The interregional reliance tends to be greater for geographi­\\ncally smaller jurisdictions. Accordingly, free riding may be a potential problem \\nto compromise the willingness to engage in hard mitigation efforts. Nevertheless, \\ndata credibility is a key element in enforcing environmental policies as well as \\nthe top-­\\ndown goals. Emission mitigation data, however, tend to be much more \\nconveniently manipulated than air quality data. The number of polluting sources \\nin China could easily overwhelm its compliance monitoring resources, especially \\nin sparsely populated and less developed regions. In the 11th Five-­\\nYear Plan, the \\nMEP assembled teams to inspect provinces and their polluting firms. However, \\nthe data had been of unsatisfying quality, and what was reported by local govern­\\nments and polluting firms was often seriously discounted. Data on SO2 emissions \\nare more prone to manipulation because the bottom-­\\nup monitoring and reporting \\nhave to go through many stakeholders who have incentives to underreport emis­\\nsions and overreport mitigation. Occasional verification from the central govern­\\nment often finds big gaps in data and must “squeeze moisture” from the reported \\nmitigation amounts. In contrast, ambient air quality data are much more difficult \\nto manipulate and any dishonest behavior is much easier to discover. The central \\ngovernment also runs its own air quality monitoring network via ground stations \\nand remote sensing, such as satellites. Accordingly, China reversed the strategy \\nto have air quality improvement targets (State Council, 2013a). Air quality moni­\\ntoring stations are much fewer than polluting sources to substantially reduce the \\nresource burden of compliance monitoring. Thus, the probability of compliance, \\ntogether with the better data quality, should be much higher.\\nThe prospective penalty and reward for goal attainment do not differ substan­\\ntially from the 11th Five-­\\nYear Plan to the 12th and 13th. However, the 12th and \\n13th Five-­\\nYear Plans achieved much faster SO2 mitigation, even considering the \\nslower economic growth rates. It could indicate that the free-­\\nriding problems \\nwere less important than data credibility. Furthermore, SO2 emissions are just \\none among many pollutants, while PM2.5 could better serve as a comprehen­\\nsive air quality indicator. Provincial and local governments could have greater \\nflexibility in weighing various technological and policy mitigation alternatives. \\nIt could also potentially encourage more local policy innovations and probably \\nachieve better cost-­\\neffectiveness through balancing the marginal abatement costs \\nof pollutants.\\nFurthermore, although emission reduction goals have been consistently \\nachieved since the 11th Five-­\\nYear Plan, air quality was not perceived to have \\nimproved. One possible cause could be the problems in reporting emission data, \\n\\n\\n68  Mobilizing the government\\n0\\n50\\n100\\n150\\n200\\n250\\n300\\n1/1/2014\\n1/1/2015\\n1/1/2016\\n1/1/2017\\n1/1/2018\\n1/1/2019\\n1/1/2020\\n(\\n \\nn\\no\\ni\\nt\\na\\nr\\nt\\nn\\ne\\nc\\nn\\no\\nc\\n \\ne\\ng\\na\\nr\\ne\\nv\\na\\n \\ny\\nl\\ni\\na\\nD\\nμg/m3)\\nDate\\nFigure 4.2  \\u0007\\nDaily SO2 concentrations in Shijiazhuang (1 January 2014–29 February 2020)\\nSource: Ministry of Ecology and Environment (2020b).\\nNote: The upper and lower dotted horizontal lines indicate the Grade 2 and 1 standard, respectively, in \\nChina’s ambient air quality standards in 1996 and 2012.\\nas discussed earlier. Another more important reason for the wide gap between \\nthe successful attainment of SO2 mitigation goals and the perceived terrible air \\nquality was that SO2 has been increasingly less important in ambient air quality. \\nFor example, Hebei Province often has one of the highest anthropogenic PM2.5 \\nconcentrations in China and the world. In its capital city, Shijiazhuang, air qual­\\nity is taken as one example to illustrate the importance of new PM2.5 standards \\nand goals. Significant improvements have been made on reducing SO2 emissions \\nand concentrations. In the first three months of 2014, SO2 concentrations in Shi­\\njiazhuang exceeded the Grade 1 standard (50 μg/m3) in 90% of all days, while a \\nstrong seasonal cycle indicated that the winter or the heating season as the worst \\nseason (Figure 4.2). From February 2019 to February 2020, in contrast, the stand­\\nard was not exceeded for even a single day (Figure 4.2). It illustrates China’s hard \\nand effective efforts in controlling SO2 emissions and bringing down SO2 concen­\\ntrations. Essentially the original long-­\\nterm goal for SO2 mitigation, 0.060 mg/m3 \\nor 60 μg/m3 (SEPA, 2006a), had been generally achieved. However, from the \\nperspective of PM2.5, Shijiazhuang’s performance has been much less impressive. \\nIts concentration has regularly exceeded the much more relaxed Grade 2 standard \\n(Figure 4.3).\\n\\n\\nMobilizing the government  69\\n0\\n50\\n100\\n150\\n200\\n250\\n300\\n350\\n400\\n450\\n500\\n550\\n600\\n650\\n1/1/2014\\n1/1/2015\\n1/1/2016\\n1/1/2017\\n1/1/2018\\n1/1/2019\\n1/1/2020\\n(\\n \\nn\\no\\ni\\nt\\na\\nr\\nt\\nn\\ne\\nc\\nn\\no\\nc\\n \\ne\\ng\\na\\nr\\ne\\nv\\na\\n \\ny\\nl\\ni\\na\\nD\\nμg/m3)\\nDate\\nFigure 4.3  \\u0007\\nDaily PM2.5 concentrations in Shijiazhuang (1 January 2014–29 February 2020)\\nSource: Ministry of Ecology and Environment (2020b).\\nNote: The upper and lower dotted horizontal lines indicate Grade 2 and 1 standard, respectively, in \\nChina’s 2012 ambient air quality standards.\\nPM2.5 is not a single pollutant but a set of various pollutants that fall into the \\nsize range. SO2 is a gaseous pollutant and could be converted into sulfate particles \\nin the atmosphere to become one important component of PM2.5. Heating seasons \\nin northern China tend to result in more coal consumption and pollutant emis­\\nsions, while inversion (when warm air is above cold air) is more frequent in the \\nwinter when the ground is cold, suppressing convection, and thus facilitates the \\naccumulation of pollutant concentrations. Although SO2 is one key precursor spe­\\ncies of PM2.5, other air pollutants are also crucial components in forming PM2.5.\\nFurthermore, ozone pollution has significantly deteriorated over the period. \\nO3 and PM2.5 concentrations tend to have opposite seasonal cycles. Chemical \\nreactions to form O3 in the atmosphere involve nitrogen oxides (NOx), volatile \\norganic compounds (VOC) and sunlight, while summer months tend to provide \\nmore favorable conditions. PM2.5 and SO2 concentrations peak in winter months, \\nand O3–8h concentration (daily maximum concentration over 8 hours) is the high­\\nest in summer months (Figure 4.4). As a result, mitigation goals of SO2 emissions \\nand SO2 concentrations will be at a greater distance from perceived air quality that \\nmainly corresponds to PM2.5 and O3 concentrations.\\nSO2 has never been the primary pollutant to decide Shijiazhuang’s monthly \\nAQI since 2014 (Figure 4.5). PM2.5 dominated the AQI before 2016, while in and \\n\\n\\n70  Mobilizing the government\\n0\\n50\\n100\\n150\\n200\\n250\\n300\\n350\\n1/1/2014\\n1/1/2015\\n1/1/2016\\n1/1/2017\\n1/1/2018\\n1/1/2019\\n1/1/2020\\nDaily 8-\\n(\\n \\nn\\no\\ni\\nt\\na\\nr\\nt\\nn\\ne\\nc\\nn\\no\\nc\\n \\ne\\ng\\na\\nr\\ne\\nv\\na\\n \\nr\\nh\\nμg/m3)\\nDate\\nFigure 4.4  \\u0007\\nDaily 8-hour O3 concentrations (daily maximum concentration over 8 hours) in \\nShijiazhuang (1 January 2014–29 February 2020)\\nSource: Ministry of Ecology and Environment (2020b).\\nNote: The upper and lower dotted horizontal lines indicate Grade 2 and 1 standard, respectively, in \\nChina’s 2012 ambient air quality standards.\\n0\\n50\\n100\\n150\\n200\\n250\\n300\\n350\\nJan-14\\nJan-15\\nJan-16\\nJan-17\\nJan-18\\nJan-19\\nJan-20\\n)\\nI\\nQ\\nA\\nI\\n(\\n \\nx\\ne\\nd\\nn\\nI\\n \\ny\\nt\\ni\\nl\\na\\nu\\nQ\\n \\nr\\ni\\nA\\n \\nl\\na\\nu\\nd\\ni\\nv\\ni\\nd\\nn\\nI\\nMonth -Year\\nPM2.5\\nSO2\\nO3-8h\\nFigure 4.5  \\u0007\\nMonthly average AQI in Shijiazhuang (January 2014–February 2020; calcu­\\nlated from daily data)\\nSource: Ministry of Ecology and Environment (2020b).\\n\\n\\nMobilizing the government  71\\nafter 2017 with reduced PM2.5 concentration and rising O3–8h concentration, O3 \\nbecame the primary pollution in summer months and PM2.5 remained dominant in \\nthe winter (Figure 4.5). The trend is similar in other Chinese cities. For example, \\nBeijing witnessed the rise of O3 in determining summer AQI a few years earlier \\nthan Shijiazhuang did (Figure 4.6). In southern China, where winter is mild/warm \\nwith adequate sunshine, the importance of O3 entirely overshadows that of PM2.5 \\nin the AQI. For example, in Shenzhen, AQI in most months is now decided by \\nO3–8h but not PM2.5 (Figure 4.7).\\nFrom 2014 to 2020, PM2.5 concentrations and corresponding air quality indexes \\nhave been reduced throughout major cities in China, but O3–8h generally had a \\nrising trend. One reason for their diverging trends in the past years could be traced \\nto the presence of PM2.5 goals but not O3 goals. In the 13th Five-­\\nYear Plan, China \\nfurther enacted air quality goals together with 15% reduction goals on SO2 and \\nNOx emissions (National People’s Congress, 2016). The proportion of days that \\nthe AQI is below 100 in municipalities should reach 80%, while for those cities \\nwith PM2.5 concentrations not reaching the Grade 2 standard (or 75 μg/m3), they \\nshould reduce the level by 18% over the five years (National People’s Congress, \\n2016).\\nThe AQI is a more comprehensive measure of air pollution to consider both \\nPM2.5 and O3. In China’s further goal evolution especially into the 14th Five-­\\nYear \\n0\\n50\\n100\\n150\\n200\\n250\\nJan-14\\nJan-15\\nJan-16\\nJan-17\\nJan-18\\nJan-19\\nJan-20\\n)\\nI\\nQ\\nA\\nI\\n(\\n \\nx\\ne\\nd\\nn\\nI\\n \\ny\\nt\\ni\\nl\\na\\nu\\nQ\\n \\nr\\ni\\nA\\n \\nl\\na\\nu\\nd\\ni\\nv\\ni\\nd\\nn\\nI\\nMonth -Year\\nPM2.5\\nSO2\\nO3-8h\\nFigure 4.6  \\u0007\\nMonthly average AQI in Beijing (January  2014–February  2020; calculated \\nfrom daily data)\\nSource: Ministry of Ecology and Environment (2020b).\\n\\n\\n72  Mobilizing the government\\nPlan (2021–2025), it could play a more prominent role in mobilizing local govern­\\nments for air pollution control.\\nNote\\n\\t\\n1\\t This chapter is based on the author’s own material used in Xu, Y. 2011. The use of a goal \\nfor SO2 mitigation planning and management in China’s 11th five-­\\nyear plan. Journal \\nof Environmental Planning and Management, 54, 769–783; much of which has been \\nrevised and expanded on.\\nReferences\\nThe Central Committee of the Chinese Communist Party. 2002. Regulations on selecting \\nand appointing leaders of the party and governments. Beijing, China: The Central Com­\\nmittee of the Chinese Communist Party.\\nChakravarty, S., Chikkatur, A., De Coninck, H., Pacala, S., Socolow, R. & Tavoni, M. \\n2009. Sharing global CO2 emission reductions among one billion high emitters. Pro­\\nceedings of the National Academy of Sciences of the United States of America, 106, \\n11884–11888.\\nChinese Academy for Environmental Planning (CAEP). 2004. Basic thoughts on national \\n11th five-­\\nyear plan on environmental protection. 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New \\nYork: United Nations.\\nThe U.S. Congress. 1990. Clean air act amendments 1990. Washington, DC: The U.S. \\nCongress.\\nU.S. Environmental Protection Agency. 2007. National emissions inventory (NEI) air pol­\\nlutant emissions trends data. Washington, DC: U.S. Environmental Protection Agency.\\nWang, J., Wu, X., Cao, D. & Meng, F. 2004. Proposed scenarios for total emission control \\nof SO2 during the 10th five-­\\nyear plan period in China. Research of Environmental Sci­\\nences, 17, 4.\\nWang, X. 2002. Exponent on ‘national 10th five-­\\nyear plan on environmental protection’. \\nBeijing, China: Science Press.\\n\\n\\n76  Mobilizing the government\\nXinhua News Agency. 2005. The birth of ‘the suggestions to 11th five-­\\nyear plan’ [Online]. \\nBeijing, China [Online]. Available: http://news.xinhuanet.com/politics/2005-­\\n10/26/con­\\ntent_3685219.htm.\\nXinhua News Agency. 2006. The drafting of 11th five-­\\nyear plan outline. Beijing, China \\n[Online]. Available: http://news.xinhuanet.com/politics/2006-­\\n03/16/content_4308918.\\nhtm.\\nXu, Y. 2011. The use of a goal for SO2 mitigation planning and management in China’s \\n11th five-­\\nyear plan. Journal of Environmental Planning and Management, 54, 769–783.\\nYang, X., Gao, Q., Jiang, Z., Ren, Z., Chen, F., Chai, F. & Xue, Z. 1998. Research on the \\ntransportation and precipitation regular pattern of sulfur pollutants in China. Research of \\nEnvironmental Sciences, 11, 27–34.\\nYang, X., Gao, Q., Qu, J. & Jiang, Z. 1999. The exploration and initial assessment of total \\namount control method for SO2 emission in China. Research of Environmental Sciences, \\n12, 17–20.\\nZhejiang Provincial Government. 2008. Notice on distributing Zhejiang provincial imple­\\nmentation plans and methods of statistics, monitoring and assessment on energy con­\\nservation and pollutant emission reduction. Hangzhou, China: Zhejiang Provincial \\nGovernment.\\nZou, S., Wang, J. & Hong, Y. 2006. Research report on national environmental protection \\nplan in the 11th five-­\\nyear plan. Beijing, China: China Environmental Science Press.\\nZou, S., Zhang, Z., Yan, G. & Tian, R. 2004. Preliminary assessment on medium-­\\nterm \\nexecution of the national tenth five-­\\nyear plan outline, important eco-­\\nenvironmental con­\\nservation and environmental protection plan. In: Wang, J., Zou, S. & Hong, Y. (eds.) \\nEnvironmental policy research series. Beijing, China: China Environmental Science \\nPress.\\n\\n\\n1  \\u0007\\nChina’s challenges in policy making\\nPolicies and goals are important in any country’s governance, but their relative \\nroles could have two primary patterns under different governance models. Rules \\nare set up through policies (and laws), while polluters and other stakeholders \\ndecide on their own actions according to the rules. In the rule-­\\nbased governance, \\npolicies are in the first place, while goals are more implicit to take the second \\nplace. Another strategy explicitly makes goals in the first place, while policies \\nare secondary and could be more flexible. With the rule of law not yet well estab­\\nlished, China would face great challenges in policy supply under the rule-­\\nbased \\ngovernance, especially given its rapidly evolving economy and society.\\n1.1  \\u0007\\nUncertain linkages between actions and outcomes\\nChina is rapidly industrializing and the economy grows at a fast pace. It encoun­\\nters great uncertainties on whether planned actions could achieve intended goals. \\nSulfur dioxide (SO2) emissions as well as other environmental problems tend to \\nhave a wide scope of influential economic, energy and environmental factors, as \\nwell as scattered emission sources in numerous important sectors. Many key fac­\\ntors for SO2 mitigation are beyond the jurisdiction of environmental protection, \\nspecifically the Ministry of Ecology and Environment (and previously the Minis­\\ntry of Environmental Protection). Implementation is largely under the responsibil­\\nity of local governments, while the central government is not designed and well \\nequipped for primary policy implementation. In addition, China’s complexities \\ncan cast substantial uncertainties on whether preplanned actions can achieve their \\ngoals. China identified enough efforts to achieve the 10% reduction goals of SO2 \\nemissions in both the 10th and the 11th Five-­\\nYear Plans, but their outcomes dif­\\nfered from each other dramatically. In the Outline of the National 10th Five-­\\nYear \\nPlan that was ratified by the National People’s Congress, the 10% reduction goals \\nof “major pollutants” were clearly written (National People’s Congress, 2001). \\n“Major Pollutants” were later defined to include SO2, dust, COD (chemical oxy­\\ngen demand), ammonia-­\\nnitrogen and industrial solid waste (SEPA, 2001). Exter­\\nnal measures, particularly energy conservation, did not show up in the national \\n5\\t\\n\\u0007\\nPolicy making\\n\\n\\n78  Policy making\\nOutline (National People’s Congress, 2001). However, in the special plan for \\nenergy development, China did propose a goal to reduce energy intensity by about \\n15% to 17% and coal’s share in total energy consumption by 3.88% in the five \\nyears (NDRC, 2001). China’s annual economic growth rate, another key factor, \\nwas estimated to be 7% (National People’s Congress, 2001). Between 2001 and \\n2005, the reversely calculated sulfur contents in coal from China’s official data \\nwent down from 1.22% to 1.05% (Xu et al., 2009), and a lot more SO2 scrub­\\nbers were installed (Figure 5.11). For the 10th Five-­\\nYear Plan, the SO2 mitigation \\nshortfall was mostly due to the unexpected surge in coal consumption as a result \\nof accelerated economic growth, 87.6% over the five years that overwhelmed the \\nefforts of the State Environmental Protection Agency (SEPA; BP, 2019).\\nIn the 11th Five-­\\nYear Plan, the planning structure differed only slightly. With \\nthe same 10% reduction goal, the Outline of the National 11th Five-­\\nYear Plan nar­\\nrowed the definition of “major pollutants” to cover only SO2 and COD for primary \\nattention (National People’s Congress, 2006). Other pollutants were addressed in \\nthe special plan for environmental protection (State Council, 2007b). A goal on \\nenergy conservation, a 20% reduction of energy intensity, got promoted to the \\nnational Outline. Coal’s share in total energy consumption remained in the special \\nplan for energy development, with a 3% drop in the five years (NDRC, 2007). \\nChina’s economy was estimated, or conservatively planned, to grow 7.5% per \\nyear (National People’s Congress, 2006). These figures were quite close to those \\nin the 10th Five-­\\nYear Plan. Simply from the planning perspective, these two 10% \\nreduction goals of SO2 emissions should both be attained. However, their results \\ndiverged significantly away from each other, which illustrated the difficulty to \\nforesee the effects of policies and actions on goals.\\n1.2  \\u0007\\nChallenges in policy making to induce actions\\nIn the U.S.’s efforts to control SO2 emissions, the Clean Air Act Amendments \\n(1990) established the Acid Rain Program that was distinguished as the most \\nimportant law on the issue (The U.S. Congress, 1990). However, no individual \\nenvironmental policy in China could claim an equal share of importance in its SO2 \\nmitigation cause. In comparison to goal-­\\ncentered governance, policy supply under \\nrule-­\\nbased governance features fewer policies (or laws), and some are of crucial \\nimportance in achieving the intended goals of environmental protection. Each \\npolicy has a more extended enactment procedure and implementation horizon, \\nwhich makes policy-­\\nmaking process lengthy and careful. The failure/success of \\na key policy thus takes on much heavier weight in environmental protection out­\\ncomes. Nevertheless, in developed countries where the rule of law is well estab­\\nlished, the linkages between policies and polluters’ actions are more predictable, \\nwhile these actions further contribute to intended outcomes. However, because \\nChina has not established a sound rule of law, confidence is much lower that a \\npolicy can be implemented well to induce the intended actions.\\nMany environmental policy instruments have been designed and applied across \\ncountries. The first major category involves command and control policies, such \\n\\n\\nPolicy making  79\\nas mandatorily shutting down polluting sources, setting pollutant emission and \\nenergy efficiency standards and mandating the application of the best available \\ntechnologies. Another major category is based on economic incentives and mar­\\nkets. Typical policy instruments include effluent emission discharge fees, taxes, \\ntradable permits and subsidies. Information disclosure, such as labeling and cer­\\ntificates, aims to enable consumers to voluntarily make informed consumption \\nchoices for minimizing environmental impacts.\\nDespite some unique features, China’s policy toolbox for SO2 mitigation was \\nnot fundamentally different from that in developed countries with rule-­\\nbased gov­\\nernance. In China, an engineering approach that was based on SO2 scrubbers in \\ncoal-­\\nfired power plants involved many command and control policies for their \\ndeployment and normal operation to meet effluent emission standards (Minis­\\ntry of Environmental Protection and General Administration of Quality Super­\\nvision Inspection and Quarantine, 2011; the SEPA and General Administration \\n\\nof Quality Supervision Inspection and Quarantine, 2003). China has also been \\nexperimenting with market-­\\nincentive policies, such as cap-­\\nand-­\\ntrade, an effluent \\nemission fee or an emission tax (Yan et al., 2009; Dong et al., 2011; Ge et al., 2011; \\nZhang et al., 2016). Technological licensing from developed countries, through a \\nfunctioning technology market, was a cornerstone in China’s SO2 mitigation to \\nbuild a domestic industry for rapid deployment and cost reduction (Xu, 2011).\\nAfter assessing the effectiveness and efficiency of individual environmen­\\ntal policy instruments, policies are enacted for tackling a given environmental \\nproblem (Barron and Ng, 1996; Goulder and Parry, 2008). A few criteria could \\nbe important in making an optimal policy, including cost-­\\neffectiveness; capabil­\\nity to address uncertainty, synergy or conflict with current policy instruments; \\ncompliance monitoring and inspection capacity and requirements; and compli­\\nance of polluters. The latter two are especially relevant to developing countries \\nlike China, where the rule of law has not been well established and environmen­\\ntal noncompliance might be prevalent. In developed countries, there has been \\nan increasing trend in the application of market-­\\nbased instruments (Portney and \\nStavins, 2000; Tietenberg, 1990). Cost-­\\neffectiveness is the most important argu­\\nment for their adoption considering particularly the reduced abatement costs \\n(Goulder and Parry, 2008). For example, in the U.S. Acid Rain Program in the \\nClean Air Act Amendments (1990), total SO2 emissions from coal power plants \\nwere capped and emission permits were allowed to trade in a market (The U.S. \\nCongress, 1990). The policy substantially reduced the abatement costs compared \\nwith command-­\\nand-­\\ncontrol instruments (Benkovic and Kruger, 2001).\\nEnvironmental policy instruments differ from each other in their capability of \\naddressing uncertainties. For example, environmental taxes establish certain lev­\\nels of emission prices but leave the quantities of emissions uncertain. In contrast, \\ntradable permits with a fixed cap are more certain about the quantity within the \\ndefined boundary of emission sources but not about the price. Other instruments \\nall have various impacts on uncertainties (Goulder and Parry, 2008). The intro­\\nduction of a new environmental policy instrument should consider how it interacts \\nwith existing policies to create synergies or conflicts. If a new emission trading \\n\\n\\n80  Policy making\\npolicy is imposed into an area that is already dominated by command and control \\npolicies, it may not be able to achieve its intended cost-­\\neffectiveness (Zhang et al., \\n2013). China’s experiments of SO2 emission trading schemes encountered major \\nproblems, including frequent governmental intervention and inter-­\\npolicy conflicts \\ntogether with the quality of policy design (Zhang et al., 2016).\\nCompared with developed countries, developing countries and specifically \\nChina have more difficulties in making optimal policies. Research tends to be \\nthinner especially in the past to understand how individual policy instruments \\nperform in their contexts. Significant constraints on environmental policy imple­\\nmentation may exist due to the lack of adequate financial resources, personnel \\nand necessary expertise (Blackman, 2010). More details on China’s policy imple­\\nmentation problems are discussed in Chapter 6. The effectiveness of individual \\npolicies could be very uncertain with unpredictable implementation, which makes \\npolicy design challenging.\\n2  \\u0007\\nGoal-­\\ncentered policy supply\\nChina’s policy supply follows a very different pattern from that in rule-­\\nbased gov­\\nernance. Goals play the central role in environmental governance, while policies \\nas means to achieve goals are primarily instrumental and failures of individual \\npolicies are more accommodated. Important centralized goals as those few in \\nNational Five-­\\nYear Plans drive decentralized policies, laws and regulations from \\nministries, local governments, the People’s Congress and other stakeholders. For \\nthose environmental fields without goals or with goals but at lower priorities, \\npolicy supply tends to be less adequate and strong.\\n2.1  \\u0007\\nEnabling goal-­\\ncentered policy supply\\nGoal-­\\ncentered governance in China is enabled by centralized national goals, \\ndecentralized goal attainment, decentralized policy making and implementation \\nand mobilized central and local governments. In the past four decades, China’s \\nenvironmental governance has been heavily decentralized, as discussed in Chap­\\nter  3. The four levels of governments  – central, provincial, municipality and \\ncounty – have diverging divisions of governmental authorities and functions. As \\nmatched by their personnel categories and fiscal expenditures, the central gov­\\nernment heavily focuses on policy making, while the county-­\\nlevel governments \\nare almost entirely on policy implementation. Provincial-­\\n and municipality-­\\nlevel \\ngovernments have significant authorities and functions on both. Local govern­\\nments hold significant decentralized authorities in initiating local policy innova­\\ntion, learning and adopting policies from other regions and implementing various \\npolicies. Without the cooperation and mobilization of local governments, the cen­\\ntral government can hardly achieve serious SO2 mitigation or any environmental \\ncleanup.\\nHowever, much authority remains substantially centralized, especially setting \\nup national goals for environmental protection. Various considerations for or \\n\\n\\nPolicy making  81\\nagainst strong environmental protection are centrally weighed to form strong or \\nweak political will by the top leadership of the Chinese Communist Party, as dis­\\ncussed in Chapter 2. It is then reflected in Five-­\\nYear Plans. When the top leader­\\nship determines to prioritize environmental protection among other governmental \\naffairs, pollution mitigation goals started to enter as the key goals into National \\nFive-­\\nYear Plans. These national goals are then decomposed into provincial goals \\nfor their implementation, as examined in Chapter 4. The goal allocation further \\npenetrates into municipality and county levels, one level at a time. The types and \\nstringency of goals closely follow the centralized political will for environmental \\nprotection. In addition, ministries and their internal departments in the central \\ngovernment are also directed by those goals to make policies and supervise pro­\\nvincial and other local governments for goal attainment. If a crucial environmen­\\ntal goal in the Five-­\\nYear Plan is missed, the Ministry of Ecology and Environment \\nas the primary responsibility bearer will also be held accountable.\\nCredible mechanisms are established for central and local governments to make \\nefforts for their goals. Most important, provincial leaders and ministers in the cen­\\ntral government have their promotion opportunities controlled centrally through \\nthe Chinese Communist Party, while the fates of municipality-­\\nlevel leaders are \\ndetermined at the provincial level. The clear linkages between their career devel­\\nopment and goal-­\\ncentered job performance are crucial incentives to motivate their \\ngenuine efforts but not just lip service.\\nUnder goal-­\\ncentered governance, it is the succession of goals but not individual \\npolicies that define environmental milestones. The top leadership of the party and \\nthe central government cares more about whether a certain goal has been achieved \\nrather than a certain policy has been effective, efficient or fully implemented. \\nIn addition, the fact that China has not established a sound rule of law is also \\nan important facilitating factor for enabling a goal-­\\ncentered policy supply. Local \\nleaders in charge, such as provincial governors, municipality mayors and county \\nleaders as well as their corresponding party secretaries, will be less likely to lose \\ntheir jobs or promotion opportunities for having policy failures, but the probabil­\\nity will increase significantly if a crucial goal does not get achieved. If one policy \\ndoes not work, new ones will be quickly enacted to inch toward goal attainment.\\n2.2  \\u0007\\nPolicy evolution by implementation selection\\nPolicy supply under goal-­\\ncentered governance has two key components: environ­\\nmental goals to shape policy demand and low policy-­\\nmaking barriers and strong \\nincentives to enable policy supply. More ambitious environmental goals will cre­\\nate stronger demand for pollution mitigation actions and thus a larger number \\nof and more stringent policies. Goal-­\\ncentered governance significantly reduces \\nbarriers for making policies. The much lower policy-­\\nmaking barriers result in \\nintensive policy-­\\nmaking activities, competition among policies and much faster \\npolicy cycles. With a significant number of policies, each makes a small step \\ntoward an intended goal, although some are more important than others. The fail­\\nure/success of any policy does not determine, but only to a limited extent affects, \\n\\n\\n82  Policy making\\nthe final environmental outcome. Besides laws, a large number and wide variety \\nof policies can be found in China on environmental protection that are enacted by \\nvarious authorities, including the Central Committee of the Chinese Communist \\nParty, the State Council, ministries and their composing departments (www.mee.\\ngov.cn/zcwj/) and local governments.\\nSeveral causes contribute to the low policy-­\\nmaking barriers. The significantly \\ndecentralized policy making effectively reduces the barriers from the perspective \\nof policy suppliers as they have a wide variety of sectoral and geographic jurisdic­\\ntions and authorities. One consequence of this goal-­\\ncentered policy supply is that \\nit encourages policy innovation. Local governments have significant flexibility in \\ndeciding how to achieve top-­\\ndown goals. Decentralized policy makers can weigh \\nthe significance, costs and benefits of various policies and their suitability to local \\ncontexts with dramatic regional disparities. Policies are constantly churned out \\nfrom these decentralized policy makers at various levels to try their effectiveness \\nin approaching goals. The effective mobilization of local governments not only \\nfacilitates policy enforcement, but it also creates incentives for even more active \\nlocal environmental policy making if goal attainment so requires.\\nFurthermore, several key questions should be considered over the making of \\nindividual policies, while goal-­\\ncentered governance has much lower require­\\nments on policy designs to effectively decrease the policy-­\\nmaking barriers. \\nFirst, how to ensure the quality of individual policies? Policies may be directly \\nadopted from other countries and regions, revised to suit local contexts or inno­\\nvated from scratch. China’s colossal size and complexity indicate that many \\nenvironmental policies can hardly be applied to fit all situations across the entire \\ncountry. China’s contexts are also sharply different from those in developed \\ncountries, where many environmental policies were first introduced and imple­\\nmented. The decentralization of policy makers also indicates that the training \\nand knowledge of those who write the policy texts may vary across local gov­\\nernments and ministries/departments. The much more greatly decentralized pol­\\nicy implementation and its unsatisfactory track record add further difficulties in \\nunderstanding how policies could be designed better for more effective imple­\\nmentation. Accordingly, direct policy adoption is rarely effective, while policy \\nlocalization and innovation are great challenges and require relevant knowledge \\nand understanding. In addition, China’s complexity also hinders timely-­\\nenough \\nassessment of the crucial causes of any policy failure and success. Under goal-­\\ncentered governance, the requirements on the quality of making individual poli­\\ncies are much lower because no policy or law occupies the central stage to solve \\na targeted environmental problem. The lower requirement for policy quality \\nenables much swifter design and enactment processes. In other words, read­\\ners of China’s environmental policies should not be primarily entangled in the \\nenactment and effectiveness of individual policies, because they are of much \\nless importance than goals. For example, essentially no SO2 emission trading \\nschedules have produced desirable outcomes that dominate SO2 mitigation, but \\nthe failure had little impact on China’s trajectory of controlling SO2 emissions \\n(Zhang et al., 2016).\\n\\n\\nPolicy making  83\\nSecond, how to choose the most effective and efficient policy instrument among \\nmany alternatives? The choice of policy instruments is a crucial question for pol­\\nicy making, especially when a single or very few policies dominate the solutions \\nto an environmental problem. Under goal-­\\ncentered governance, this question is \\nmuch less significant because policies are much less mutually exclusive. The con­\\nsiderably decentralized policy making also significantly reduces the possibility of \\nany policy monopoly or oligopoly. The enactment of one policy instrument does \\nnot prevent the application of others. Accordingly, China does not need to choose \\na primary policy instrument for dealing with one environmental problem. For \\nexample, China’s environmental protection tax law formally entered into force \\nin January 2018, covering a wide variety of environmental pollutants, including \\nSO2 (National People’s Congress, 2016). Many other crucial environmental poli­\\ncies are simultaneously in effect, such as the effluent emission standards that were \\nexamined earlier (MEP and AQSIQ, 2011).\\nThird, how are policies coordinated? While policies are individually made by \\ndifferent ministries and their internal departments, as well as various levels of \\ngovernments, they can exert significant impacts on each other to create synergies \\nand/or conflicts. Economic and energy policies are far beyond the jurisdiction \\nof environmental protection. With local governments rather than their environ­\\nmental protection bureaus in charge, coordination across these different types of \\npolicies became more feasible. In an optimized situation, policies should be well \\ncoordinated to maximize synergies and minimize conflicts. However, such coor­\\ndination in China is inadequate in the context of decentralized policy making \\nand especially policy implementation. Little evidence indicates that China rolls \\nout the numerous policies for achieving the SO2 mitigation goals in a system­\\natic and coordinated way. Instead, the policy making is messy, with decentralized \\npolicy makers who have their individual authority in designing or shaping policies \\nwithin their respective jurisdictions. Under goal-­\\ncentered governance, however, \\nsuch prior coordination of policy making is of lesser importance. After policies \\nare made and put into implementation, they evolve rapidly. In China’s context of \\nweak rule of law and as examined earlier, individual policies have higher prob­\\nabilities of unsatisfactory implementation. Similar to the natural selection process \\nas proposed by Charles Darwin in understanding biological evolution (Darwin, \\n1859), policies in China also experience a dynamic evolution process and those fit \\nones are selected through implementation. Policies that have too many conflicts \\nwith others will be difficult to get effectively implemented. If one policy fails \\nto achieve its intended consequences, new policies can be quickly introduced. \\nSuccessful policies in one province can be rapidly adopted by other provinces or \\nelevated to the national level.\\nAlthough much progress has been made in policy research in the past decade, \\nsuch capacity was especially deficient in the early stages of SO2 mitigation. China \\nshould still enhance its capability in policy making to improve the quality of indi­\\nvidual policies, choose more wisely environmental policy instruments especially \\nfor those of relatively greater importance and scopes and better coordinate across \\npolicies. Nevertheless, the goal-­\\ncentered policy supply substantially lowered the \\n\\n\\n84 Policy making\\nrequirements for achieving desirable environmental protection outcomes such as \\nserious mitigation of SO2 emissions. The preceding crucial questions in policy \\nmaking are of much less concern from their perspectives on influencing policy \\noutcomes.\\n3  \\nPolicy scope for achieving SO2 mitigation goals\\nChina faces a wide scope in policy making for SO2 mitigation. SO2 emissions \\nare affected by many economic, energy and environmental development factors \\nand corresponding policies. Although the coal-fired \\n \\npower sector is increasingly \\nimportant in coal consumption, still nearly two fifths of coal is consumed in other \\nsectors (Figure 1.10). For achieving increasingly stringent SO2 mitigation and \\nenvironmental goals, the decentralized policy makers should evaluate the contri-\\nbutions of individual policies in policy supply.\\n3.1   \\nKey factors for SO2 emissions\\nSO2 emissions can be decomposed with the following formula into various key \\nfactors:\\nEnergy\\nCoal\\nSO2 emissions\\nSO2 emissions = GDP ×\\n×\\n×\\nGDP\\nEnergy\\nCoal\\nCoal\\n  \\nEquation 5.1\\n= GDP ×\\n×\\nEI\\n×\\n×\\nh\\nh\\ns\\ns\\n(\\n)\\n1\\n2\\n−\\n×\\nr\\nR\\n×\\n−\\n(\\n)\\n1\\nh\\nEnergy\\n“GDP” (gross domestic product) indicates the scale effect. Rapid economic \\ngrowth in China leads to more SO2 emissions. Energy consumption is a key foun-\\nEnergy \\ndation for any modern economy, and thus, energy intensity \\n\\n\\n is another \\n\\n\\n\\nGDP \\n\\ncrucial effect. It measures how much energy is consumed for producing a given \\nunit of GDP. Energy conservation and efficiency will reduce energy intensity and \\nthus be beneficial for SO2 mitigation. The economic structure also matters greatly. \\nA greater proportion of service sectors in an economy could potentially reduce \\nthe overall energy intensity because in comparison to industrial sectors, they tend \\nto consume much less energy for producing the same amount of economic out-\\nputs (Feng et al., 2009). China had a goal to reduce energy intensity by 20% in \\nthe 11th Five- \\nYear Plan (National People’s Congress, 2006). The Chinese central \\ngovernment also declared its intention in the 12th Five- \\nYear Plan to “change the \\neconomic growth pattern,” with a focus on energy conservation and environmen-\\ntal protection (National People’s Congress, 2011). These two effects are related to \\neconomic development and energy conservation, on which economic and energy \\npolicies exert important influences.\\nBecause coal consumption dominates the sources of SO2 emissions, the share \\nof coal in the energy mix is thus critical in deciding the sulfur intensity of energy. \\n\\n\\nPolicy making  85\\nCoal\\nEnergy is referred to as the energy transition effect. Its reduction is another meas­\\nure for bringing down SO2 emissions, which largely falls into the category of \\nenergy development and the scope of energy policy.\\nSO emissions\\nCoal\\n2  \\n refers to the mitigation effect, which is primarily decided by \\nenvironmental policies. In combustion, a certain proportion of sulfur (ηsr ) will \\nbe retained in ash and thus not emitted. This rate is mainly decided by the coal \\ntype and combustion technology, but not by policy intervention. Sulfur content in \\ncoal (ηs) is an important indicator of coal quality. The control of sulfur contents is \\noften targeted in early environmental regulations for reducing SO2 emissions. SO2 \\nscrubbers and other SO2 removal measures can avoid a certain share of SO2 (ηR) \\nfrom being emitted after generation.\\nChina’s economy has been growing at an astonishing pace in the past four dec­\\nades. Real GDP in 2018 was 31.7 times of that in 1980 with a growth rate of 9.5% \\nannually, while real GDP per capita rose to be 22.4 times or 8.5% annually (Fig­\\nure 5.1). As measured in nominal GDP of current U.S. dollars, China overtook \\nJapan to become the second-­\\nlargest economy in the world in 2010 and further rose \\nto be equivalent to 65.0% of the United States in 2018 (Figure 5.1). China’s much \\nlarger population indicates that the country’s GDP per capita still trails the global \\naverage and is a small fraction of that in Japan and the United States. Although \\nthe GDP growth rate has been significantly slower in the 2010s than in the 2000s, \\n0\\n5,000\\n10,000\\n15,000\\n20,000\\n25,000\\n0\\n10,000\\n20,000\\n30,000\\n40,000\\n50,000\\n60,000\\n70,000\\n80,000\\n90,000\\n1980\\n1985\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\nNominal GDP (Billion US dollars)\\n)\\nB\\nM\\nR\\n \\n5\\n1\\n0\\n2\\n(\\n \\na\\nt\\ni\\np\\na\\nc\\n \\nr\\ne\\np\\n \\nP\\nD\\nG\\n \\n&\\n \\nP\\nD\\nG\\nYear\\nReal GDP (Billion RMB, China; left)\\nReal GDP per capita (RMB per capita, China; left)\\nNominal GDP (Billion US dollars, China; right)\\nNominal GDP (Billion US dollars, Japan; right)\\nNominal GDP (Billion US dollars, US; right)\\nFigure 5.1  \\u0007\\nEconomic growth in China, Japan and the United States\\nSource: IMF (2019).\\n\\n\\n86  Policy making\\nthe convergence of average living standards in China toward that of developed \\ncountries is expected to further intensify economic activities within its geographi­\\ncal territory and thus to add great environmental pressures.\\nEnergy consumption is not only one key foundation for economic develop­\\nment, but it also brings unwanted consequences of environmental pollution. The \\ncombustion of fossil fuels, especially coal, is the primary source of air pollutant \\nemissions that cause ambient particulate matter (PM) pollution. Although China \\nhas been improving its energy efficiency for producing one unit of GDP espe­\\ncially in the past decade, its primary energy consumption climbed up quickly. \\nWhen consuming one ton of oil equivalent of primary energy, China in 2018 \\nproduced US$4,084 of nominal GDP, while the rates for Japan and the United \\nStates were US$10,948 and US$8,945, respectively (IMF, 2019; BP, 2019). Due \\nto the significantly lower energy efficiency, China overtook the United States \\nto become the largest energy consumer in the world in 2009, but its economy \\nthen was two thirds smaller. A major shift took place in around 2003, and since \\nthen, China’s energy consumption has been growing at a much faster pace than \\nbefore (Figure 5.2). Not only China’s economic growth accelerated after 2003, \\nbut also the energy efficiency reversed its earlier improvement trend to decrease \\nbetween 2002 and 2005 (Figure 5.2). In 2018, China consumed 224% more pri­\\nmary energy than in 2000 to become 42% higher than the United States’ level \\n(Figure 5.2).\\n0.0\\n5.0\\n10.0\\n15.0\\n20.0\\n25.0\\n30.0\\n0\\n500\\n1,000\\n1,500\\n2,000\\n2,500\\n3,000\\n3,500\\n1980\\n1985\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\nEnergy efficiency (1,000 (2015) RMB/toe)\\n)\\ne\\no\\nt\\nM\\n(\\n \\nn\\no\\ni\\nt\\np\\nm\\nu\\ns\\nn\\no\\nc\\n \\ny\\ng\\nr\\ne\\nn\\ne\\n \\ny\\nr\\na\\nm\\ni\\nr\\nP\\nYear\\nChina\\nIndia\\nUnited States\\nEnergy efficiency in China (right)\\nFigure 5.2  \\u0007\\nPrimary energy consumption and energy efficiency\\nSource: BP (2019).\\n\\n\\nPolicy making  87\\nChina’s low level of GDP per capita might partly explain why its energy mix \\nheavily focuses on coal. As shown in Figure 5.3, coal is the cheapest and most \\naffordable among the three major fossil fuels. When China’s economy grew very \\nfast, especially in the 2000s, to rapidly push up energy consumption, coal became \\nthe primary choice for meeting the additional energy demand (Figure 5.4), and \\nthus, its share in the energy mix even reversed its earlier declining trend to become \\nhigher in the early 2000s (Figure 5.5).\\nIn the past decade, energy transition has also been playing an increasingly vis­\\nible role that led to the mitigation of SO2 emissions. China’s energy mix is heav­\\nily tilted toward coal, the most pollution-­\\nintensive fuel. With more coal burning \\nsqueezed into China’s territory, the pressure on the environment is mounting. \\nThroughout the 1980s and 1990s, the share of coal was continuously above 70% \\n(Figure 5.5). The slow declining trend in the 1990s was reversed in early 2000s to \\nwitness the share climbing up again from 69.5% in 2001 to 73.7% in 2007, further \\nintensifying environmental pollution in China. The following decade witnessed \\nan unprecedented decrease and coal’s share had dropped to 58.2% in 2018. Never­\\ntheless, China still accounted for 50.5% of global coal consumption in 2018 (BP, \\n2019). Although oil and natural gas have increasing shares in China’s primary \\nenergy consumption, the overall share of fossil fuels experienced an accelerated \\ndecline from 94.1% in 2007 to 85.3% in 2018. Nonfossil fuels are much more \\n0\\n2\\n4\\n6\\n8\\n10\\n12\\n14\\n16\\n18\\n20\\n1980\\n1985\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\n)\\nJ\\nG\\n/\\n$\\n \\nt\\nn\\ne\\nr\\nr\\nu\\nc\\n(\\n \\ne\\nc\\ni\\nr\\np\\n \\ny\\ng\\nr\\ne\\nn\\nE\\nYear\\nOil\\nGas\\nCoal\\nFigure 5.3  \\u0007\\nPrices of coal (Qinhuangdao spot price), oil and natural gas\\nSource: Japan LNG CIF; BP (2019).\\n\\n\\n88  Policy making\\n–50\\n0\\n50\\n100\\n150\\n200\\n250\\n1980\\n1985\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\n)\\ne\\no\\nt\\nM\\n(\\n \\nn\\no\\ni\\nt\\np\\nm\\nu\\ns\\nn\\no\\nc\\n \\ny\\ng\\nr\\ne\\nn\\ne\\n \\nf\\no\\n \\nh\\nt\\nw\\no\\nr\\ng\\n \\nl\\na\\nu\\nn\\nn\\nA\\nYear\\nCoal\\nOil\\nGas\\nNuclear\\nHydro\\nRenewables\\nFigure 5.4  \\u0007\\nThe annual growth of primary energy consumption in China by fuels\\nSource: BP (2019).\\n55%\\n60%\\n65%\\n70%\\n75%\\n80%\\n85%\\n90%\\n95%\\n100%\\n0\\n500\\n1,000\\n1,500\\n2,000\\n2,500\\n3,000\\n3,500\\n1980\\n1985\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\nShare in the energy mix\\n)\\ne\\no\\nt\\nM\\n(\\n \\nn\\no\\ni\\nt\\np\\nm\\nu\\ns\\nn\\no\\nc\\n \\ny\\ng\\nr\\ne\\nn\\ne\\n \\ny\\nr\\na\\nm\\ni\\nr\\nP\\nYear\\nCoal\\nOil\\nGas\\nNuclear\\nHydro\\nRenewables\\nCoal’s share\\nFossil fuels’ share\\nFigure 5.5  \\u0007\\nChina’s primary energy consumption by fuel and the shares of coal and fossil fuels\\nSource: BP (2019).\\n\\n\\nPolicy making  89\\nimportant in the energy mix, from 5.9% in 2007 to 14.7% in 2018 (Figure 5.5). \\nNuclear, hydropower and nonhydro renewables witnessed their shares increased \\nfrom 0.7%, 5.1% and 0.2% in 2007 to 2.0%, 8.3% and 4.4% in 2018, respectively. \\nNonhydro renewables were the fastest-­\\ngrowing energy type.\\nAs one indicator of energy modernization, China’s primary energy consump­\\ntion is rapidly electrifying to reshape the major sources and sectors of SO2 emis­\\nsions. In 1990, only 20.8% of primary energy consumption went through the \\nintermediate stage of electricity before final consumption, which was only slightly \\nhigher than Africa’s 17.8% (Figure 5.6). With rapid energy modernization, this \\nratio increased to 42.5% in 2015, then similar to the United States’ 40.3% (Fig­\\nure 5.4). Rapid electrification also happened in other rapidly industrializing coun­\\ntries such as India, but the progress in Africa has been much slower (Figure 5.4). \\nWith China’s continuous efforts for electrifying energy consumption – such as the \\npush for electric vehicles (IEA, 2019) – this electrification rate is expected to fur­\\nther escalate, which will distinguish the importance of the power sector in China’s \\nenergy consumption and environmental protection.\\nEnergy transition for electricity generation is even more visible. Coal’s share \\nhas been reduced significantly from the 81.0% peak in 2007 to 66.5% in 2018. \\nOther fossil fuels, including oil and natural gas, accounted for only an insignificant \\nshare at 3.3% in 2018 (Figure 5.7). In contrast, the share of nonhydro renewables, \\nmostly wind and solar energy, has achieved the largest growth from 0.5% in 2007 \\nto 8.9% in 2018 (Figure 5.7). Coal’s share in electricity generation is significantly \\n0%\\n5%\\n10%\\n15%\\n20%\\n25%\\n30%\\n35%\\n40%\\n45%\\n0\\n500\\n1,000\\n1,500\\n2,000\\n2,500\\n3,000\\n1990 2000 2015\\n1990 2000 2015\\n1990 2000 2015\\n1990 2000 2015\\nShare of power generation\\n)\\ne\\no\\nt\\nM\\n(\\nn\\no\\ni\\nt\\np\\nm\\nu\\ns\\nn\\no\\nc\\ny\\ng\\nr\\ne\\nn\\nE\\nPower generation\\nOthers\\nShare of power generation\\nUnited States\\nChina\\nAfrica\\nIndia\\nFigure 5.6  \\u0007\\nPrimary energy consumption and its electrification rate\\nSource: IEA (2017).\\n\\n\\n90  Policy making\\nhigher than that in primary energy consumption, being 66.5% and 58.2% in 2018, \\nrespectively (Figure 5.8). From 2007 to 2018, their drops were 14.4% and 15.4% \\nin percentage points, respectively. Nonfossil fuels – such as nuclear, hydro and \\nnonhydro renewables – are generally for electricity generation, while oil and natu­\\nral gas in China are primarily consumed not in the power sector. Especially in the \\npast decade, the advancement of renewables significantly accelerated to account \\nfor increasingly sizable shares of electricity generation growth (Figure 5.8).\\nThe power sector has been increasing its importance in coal consumption. In \\n1980, only 20.2% of China’s coal consumption was in the power sector, while \\nthis ratio climbed steadily to 52.2% in 2002 before a decade-­\\nlong stabilization \\n(Figure 1.10). During 2015~2017, the increasing trend restarted to reach 57.3% in \\n2017 from 50.3% in 2014 (Figure 1.10). This ratio is expected to further increase, \\nin reference to the situation in the United States, whose power sector accounted \\nfor 18.6% of coal consumption in 1950 and 92.8% in 2017 (Figure 1.10). The \\ntrend indicates that the energy mix in nonpower sectors shifts away from direct \\ncoal consumption faster than that in the power sector, although the former may \\nconsume more electricity that comes from coal-­\\nfired power plants.\\nIn China’s trajectory of SO2 mitigation, these economic, energy and envi­\\nronmental factors made different contributions in different Five-­\\nYear Plans \\n(Figure  5.9). SO2 emissions went down by 15.8% in the 9th Five-­\\nYear Plan \\n50%\\n55%\\n60%\\n65%\\n70%\\n75%\\n80%\\n85%\\n90%\\n0\\n1,000\\n2,000\\n3,000\\n4,000\\n5,000\\n6,000\\n7,000\\n8,000\\n1985\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\nShare in the energy mix\\n)\\nh\\nW\\nT\\n(\\n \\nn\\no\\ni\\nt\\na\\nr\\ne\\nn\\ne\\ng\\n \\ny\\nt\\ni\\nc\\ni\\nr\\nt\\nc\\ne\\nl\\nE\\nYear\\nCoal\\nOil\\nGas\\nNuclear\\nHydro\\nRenewables\\nOthers\\nFossil fuels’ share\\nCoal’s share\\nFigure 5.7  \\u0007\\nElectricity generation by fuels in China\\nSource: BP (2019).\\n\\n\\nPolicy making  91\\n50%\\n55%\\n60%\\n65%\\n70%\\n75%\\n80%\\n85%\\n–50\\n50\\n150\\n250\\n350\\n450\\n550\\n650\\n1985\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\nCoals shares\\n)\\nh\\nW\\nT\\n(\\n \\nn\\no\\ni\\nt\\na\\nr\\ne\\nn\\ne\\ng\\n \\ny\\nt\\ni\\nc\\ni\\nr\\nt\\nc\\ne\\nl\\ne\\n \\nf\\no\\n \\nh\\nt\\nw\\no\\nr\\ng\\n \\nl\\na\\nu\\nn\\nn\\nA\\nYear\\nCoal\\nOil\\nGas\\nNuclear\\nHydro\\nRenewables\\nOthers\\nCoal’s share in electricity generation\\nCoal’s share in primary energy\\nFigure 5.8  \\u0007\\nThe annual growth of electricity generation in China by fuels and coal’s share\\nSource: BP (2019).\\n–60%\\n–50%\\n–40%\\n–30%\\n–20%\\n–10%\\n0%\\n10%\\n20%\\n30%\\n40%\\n50%\\n60%\\nSO2 emissions\\nScale effect\\nEnergy intensity\\neffect\\nEnergy transition\\neffect\\nMitigation effect\\ne\\nv\\ni\\nF\\n \\nr\\ne\\nv\\no\\n \\ne\\ng\\nn\\na\\nh\\nC\\n-\\n \\ns\\nn\\na\\nl\\nP\\n \\nr\\na\\ne\\nY\\n9th FYP (1996–2000)\\n10th FYP (2001–2005)\\n11th FYP (2006–2010)\\n12th FYP (2011–2015)\\n13th FYP (2016–2017)\\nFigure 5.9  \\u0007\\nThe decomposition of China’s SO2 emissions\\nSource: National Statistics Bureau and Ministry of Ecology and Environment (2019); IMF (2019); \\nBP (2019).\\nNote: Method comes from Ang (2005).\\n\\n\\n92 Policy making\\n(1996–2000). Under the influence of the Asian financial crisis of 1997, the scale \\neffect would still lead to an increase of 38.0%, while the effects of energy inten-\\nsity, energy transition and mitigation reduced SO2 emissions by 26.4%, 6.1% and \\n21.3%, respectively, over the five years (Figure 5.9). They indicated the varying \\nimpacts of economic, energy and environmental policies and development. Spe-\\ncifically, as represented in the mitigation effect, environmental policies made an \\nimportant but certainly not decisive contribution. The 10th Five-Y\\n ear Plan had a \\nvery different picture. With accelerated economic growth, the scale effect would \\nboost emissions by 53.0%, while the energy intensity and energy transition effects \\nalso pushed the emissions upward by 12.6% and 5.7%, respectively. Although \\nthe mitigation effect of 43.5% reduction was much greater than that in the 9th \\nFive- \\nYear Plan, the outcome was that SO2 emissions increased by 27.8%. In other \\nwords, the deterioration was not due to less effective environmental policies, but \\nfaster economic expansion reversed trends of energy intensity and transition.\\nReversing the deterioration trend, the 11th Five- \\nYear Plan managed to reduce \\nSO2 emissions by 14.3%. The following 12th Five- \\nYear Plan registered a similar \\nreduction of 14.9%. The four effects also had comparable contributions in these \\ntwo Five- \\nYear Plans: the scale effect 49.6% versus 35.0%, the energy intensity \\neffect −19.6% versus −17.6%, the energy transition effect −4.2% versus −9.1% \\nand the mitigation effect −40.0% versus −23.2% (Figure 5.9). In the first two \\nyears (2016–2017) of the 13th Five- \\nYear Plan with available data, SO2 emissions \\ndropped by whopping 52.9%, and the mitigation effect contributed decisively a \\nreduction of 52.0% (Figure 5.9).\\n3.2   \\nTechnological factors for effluent SO2 emissions  \\nin the power sector\\nElectrification of energy consumption and the power sector’s increasing share in \\ncoal consumption distinguish the importance of coal-fired \\n \\npower plants in control-\\nling China’s SO2 emissions. Given the understanding of coal combustion and SO2 \\n\\nSO  emissions\\n\\nemissions in electricity generation, the SO  emission intensity \\n2\\n\\n2\\n\\n \\n\\n\\nCoal\\n\\n\\n\\ncan be converted to effluent SO2 concentration, mg/Nm3 (Ministry of Environ-\\nmental Protection and General Administration of Quality Supervision Inspection \\nand Quarantine, 2011). The SO2 concentration is measured under normal condi-\\ntions (thus “N”), with excess air coefficient being 1.4. The value 1.4 here indi-\\ncates that 40% more air or, specifically, oxygen will be blown into boilers than \\nwhat is required for complete combustion. Excess air is needed for more complete \\ncombustion within a short residence time of fuels in boilers, but excess air will \\nalso take heat away and lower the thermal efficiency. Accordingly, an optimum \\nvalue exists, not necessarily being 1.4 for every power plant. The fixed value is \\nfor policy purposes and intends to prevent cheating because a convenient option \\nof lowering effluent SO2 concentration is to dilute the flue gas with more air. \\n21%\\nApproximately, excess air coefficient a can be calculated as a ≈\\n, x% \\n21%\\n%\\n−x\\nreferring to the percentage of O2 in flue gas, when a = 1.4 and x%\\n%\\n»\\n≈6 .\\na\\n−\\n21\\n21\\n%\\n%\\n%\\nx\\n\\n\\nPolicy making  93\\nAs revealed in Equation 5.1, there are three key technological factors to decide \\nSO2 emission intensity and effluent SO2 concentration. The first factor is the frac­\\ntions of sulfur retained in ash (ηsr). When coal is burned in boilers, sulfur is con­\\nverted into several forms, being gaseous (SO2, SO3, gaseous sulfates) and solid \\n(in bottom ash and as particulate sulfate; EPA, 1998). SO2 greatly dominates the \\ngaseous forms (EPA, 1998). Higher combustion temperature leads to lower frac­\\ntions of sulfur retained in ash, which disadvantages pulverized coal (PC) combus­\\ntion against fluidized bed combustion (FBC; Sheng et al., 2000). Another factor is \\nthe calcium/sulfur (Ca/S) molar ratio in coal: a higher Ca/S ratio facilitates sulfur \\nretention (Cheng et al., 2004; EPA, 1998). (The Ca/S ratio here is different from \\nthe Ca/S ratio for SO2 scrubbers as discussed later.) For PC combustion, the pres­\\nence of calcium is much less important than FBC due to the thermal instability of \\ncalcium sulfate (CaSO4), the main product responsible for sulfur retention (Sheng \\net al., 2000). The fractions of sulfur retained in the application are summarized \\nin Table 5.1. Compared with China’s assumption of 20% (State Council, 2007a), \\nfractions of sulfur retained are widely believed to be significantly lower, except \\nfor the situations of burning lignite and applying FBC technologies. Even another \\nChinese official document believed the rate to be 10% to 15% and recommended \\n10% for the purpose of designing SO2 scrubbers (NDRC, 2004). China’s SO2 \\nemissions could have been underestimated partly because of the choice of this \\nparameter (Figure 1.8).\\nSecond, lower sulfur contents in coal are crucial for reducing SO2 generation \\nintensity. An official data set is employed to analyze the distribution of sulfur \\ncontents for SO2 scrubbers. In the 11th Five-­\\nYear Plan on Acid Rain and SO2 \\nPollution Control, China published data for 248 coal power plants with a total \\ncapacity of 164 GW that covered all SO2 retrofit projects to be completed between \\n2006 and 2010 (SEPA and NDRC, 2008). Sulfur contents estimated from this data \\nTable 5.1 Applied fractions of sulfur retained in ash\\nCoal type\\nFractions of \\nSource\\nsulfur retained \\nin ash\\nBituminous, PC*\\n5%\\nU.S. Environmental Protection (EPA, 1998)\\nSub-bituminous, PC* 12.5%\\nAgency’s (EPA’s) choice\\nLignite, PC*\\n25%\\nCoal in general\\n≤10%\\nU.S.’s study\\n(Singer, 1981)\\nNonlignite coal\\n5%\\nAssumption from the U.S. EPA (Smith et al., 2001)\\nLignite\\n30%\\nAssumption in the research\\nCoal\\n5%~30%\\nThe study’s assumption\\n(Ohara et al., 2007)\\nCoal\\n5%~10%\\nChina’s study\\n(Zhao et al., 2008)\\nCoal, PC*\\n10%~15%\\nChina’s official recommendation (NDRC, 2004)\\nfor scrubber design\\nCoal\\n20%\\nAssumption in compiling \\n(State Council, 2007a)\\nChina’s statistical data\\nNote: PC* refers to pulverized coal power plants.\\n\\n\\n94  Policy making\\nset are expected to represent their distribution for all coal power plants with SO2 \\nscrubbers. Each plant disclosed information on scale (MW), year, annual SO2 \\nremoval capability (tons per year), location and name. Sulfur contents can then \\nbe estimated under the following assumptions: thermal efficiencies were 370 g \\nof coal equivalent per kilowatt-­\\nhour, or 1,930 kWh per ton coal (the average effi­\\nciency in 2005 [China Electricity Council, 2006–2015]); capacity factors were \\n5,500 hours per year (SEPA, 2006a); 80% of the sulfur was converted to SO2 in \\ncombustion and 20% was retained in ash, as recognized in China’s official sta­\\ntistics (State Council, 2007a); and overall SO2 removal rates were 85% (SEPA, \\n2007). The calculation formula is\\nSulfur content\\n \\nSO  removal capability\\nCoal power capacity\\n2\\n\\u001f\\n\\u001e55\\n1930\\n8\\n85\\n00\\n2\\n0\\n\\u001e \\u001e\\n\\u001e\\n%\\n%\\n“2” in the denominator refers to the fact that when sulfur is converted to SO2, the \\nmass doubles since the molecular weight of SO2 is twice that of sulfur. A caveat \\nis that these numbers are used here to reversely calculate sulfur contents because \\nthey represent China’s original assumption in compiling the data. One legitimate \\nconcern is the accuracy of the assumed 80% conversion. Actually, in the com­\\nbustion of anthracite, bituminous and sub-­\\nbituminous coal, 90% or more of the \\nsulfur is converted to SO2, as discussed earlier. In addition, as discussed in Chap­\\nter 6, China’s actual SO2 removal rates should be significantly lower than 85% \\nespecially before 2007. Actual thermal efficiencies and capacity factors also vary \\nacross years.\\nSulfur contents are closely related to the costs of SO2 mitigation. Generally \\nspeaking, higher sulfur contents correspond to lower costs for every ton of SO2 \\nremoved but higher costs for every kilowatt-­\\nhour of electricity generated. The \\ndistribution of sulfur contents is shown in Figure 5.10 with the national average \\nbeing about 1.0%. Of the coal-­\\nfired power plants, 68% burned coal with less \\nthan 1% sulfur and another 26% between 1% and 2%. The remaining 6% of the \\ntotal capacity was associated with higher than 2%-­\\nsulfur coal. China not only \\ninstalled SO2 scrubbers not only in coal power plants burning high-­\\nsulfur coal \\nbut also in those burning low-­\\nsulfur coal. China’s distribution of sulfur contents \\nhad a single peak at around 0.75% (Figure 5.10), which reflected the fact that \\nmost of China’s coal is mined in one region. For example, two thirds of China’s \\ncoal production in 2007 came from the seven nearby provinces of Shanxi, Inner \\nMongolia, Shaanxi, Shandong, Anhui, Hebei and Henan (National Bureau of \\nStatistics, 1997–2008).\\nThe preceding two factors decide how much SO2 is generated when burning \\na unit quantity of coal. SO2 removal rates are the third factor to reduce the SO2 \\nemission intensity. Before construction begins, a report of environmental impact \\nassessment (EIA) had to be submitted to a governmental authority on environ­\\nmental protection (NPC, 2002). If the plant was believed to bring unacceptable \\nenvironmental damage – for example, seriously worsen ambient air quality – the \\n\\n\\nPolicy making  95\\nEIA report would be rejected. Another policy – “three simultaneities” – required \\npollution control facilities to be designed, constructed and completed at the same \\ntime as the main project (State Council, 1998). For example, if SO2 scrubbers \\nwere considered necessary in the EIA report, this policy would demand their \\ninstallation.\\n3.3  \\u0007\\nTechnical measures for SO2 removal in the power sector\\nIn order to remove SO2 in electricity generation, coal-­\\nfired power plants in China \\nare required to meet effluent emission standards that are made more stringent \\nevery six or seven years to reflect growing environmental concerns. In the stand­\\nards enacted in 1996, new coal-­\\nfired power plants that passed EIA after Janu­\\nary 1997 should achieve 2,100 mg/Nm3 (if burning coal with ≤1% sulfur) or 1,200 \\nmg/Nm3 (if burning coal with >1% sulfur; SEPA and AQSIQ, 1996). For coal-­\\nfired power plants burning bituminous coal with 0.5% sulfur, SO2 concentration \\nin the non-­\\ndesulfurized flue gas will generally exceed 1,000 mg/Nm3. Essentially \\nthe 1996 effluent emission standards meant that coal-­\\nfired power plants burning \\ncoal with >1% sulfur should have SO2 scrubbers while those with ≤1% sulfur \\ndid not need to. In the standards enacted in 2003, for the great majority of coal \\npower plants, their effluent SO2 concentration should be kept below 400 mg/Nm3 \\n0%\\n5%\\n10%\\n15%\\n20%\\n25%\\nShare of SO2\\ny\\nt\\ni\\nc\\na\\np\\na\\nc\\n \\nr\\ne\\nb\\nb\\nu\\nr\\nc\\ns\\nSulfur Content\\nFigure 5.10  \\u0007\\nDistribution of sulfur contents in coal power plants in China (with retrofitted \\nSO2 scrubbers)\\nSource: SEPA and NDRC (2008).\\n\\n\\n96  Policy making\\non 1 January 2010 (SEPA and General Administration of Quality Supervision \\nInspection and Quarantine, 2003). In addition to China’s shutting down old, small \\npower-­\\ngenerating units, the effluent emission standard itself would ensure that a \\ndominant share of China’s coal power capacity in 2010 would have SO2 scrubbers \\ninstalled and operate normally.\\nThe standards were updated in 2011 for being effective on 1 January 2012 (Min­\\nistry of Environmental Protection and General Administration of Quality Supervi­\\nsion Inspection and Quarantine, 2011). New plants should then reduce their effluent \\nSO2 emissions below 100  mg/Nm3 while the standard for existing plants was \\n200 mg/Nm3. In southwestern provinces, including Guangxi, Chongqing, Sichuan \\nand Guizhou, where local coal contains much higher sulfur contents, the standards \\ncould be relaxed to 200 mg/Nm3 and 400 mg/Nm3, respectively. Natural gas–fired \\npower plants tend to be much cleaner, with the standard being 35 mg/Nm3.\\nIn 2014, a new policy, “Upgrading and Retrofitting Action Plan for Energy Con­\\nservation and Pollution Mitigation in the Coal-­\\nFired Power Sector,” was enacted \\njointly by National Development and Reform Commission, Ministry of Environ­\\nmental Protection and National Energy Administration (National Development \\nand Reform Commission et al., 2014). It required newly constructed coal-­\\nfired \\npower plants in eastern provinces to achieve the standard for natural gas–fired \\npower plants, that is, 35 mg/Nm3 for SO2 emissions. Central provinces should \\napproach this standard, while western provinces were encouraged to reach the \\nlevel. This much more stringent standard is referred to in China as the ultra-­\\nlow \\nemissions. In 2015, another policy mandates the ultra-­\\nlow standard to be achieved \\nin most new and existing coal-­\\nfired power plants with only occasional exceptions \\n(Ministry of Environmental Protection et al., 2015).\\nChina’s Law of Standardization and its implementation regulations provide \\nlegal teeth (NPC, 1988; State Council, 1990). Effluent emission standards are \\nclearly stated as “mandatory standards” (State Council, 1990), while products \\nnot meeting “mandatory standards” are forbidden to produce, sell and import \\n(NPC, 1988). In this sense, coal power plants should stop generating electricity \\nif the effluent SO2 emissions exceeded corresponding standards. The electric grid \\nshould not accept the electricity if it were not legally generated.\\nIn order to achieve SO2 removal rates as required by the stringent ultra-­\\nlow efflu­\\nent emission standard, coal-­\\nfired power plants should generally achieve very high \\nSO2 removal rates, being 98.5% if Huolinhe lignite or Datong bituminous coals are \\nburned or 96.9% for Shenfu bituminous coal (Table 5.2). The SO2 emission intensity \\nof electricity generation should also be substantially reduced to about 0.10 to 0.11 \\ng/kWh. The sulfur contents in these three types of coal, from 0.50% to 0.99%, fall \\nwithin the normal range. For high-­\\nsulfur coal, especially in southwestern provinces, \\nthe required SO2 removal rates are much higher, generally beyond 99%. The deep \\nreduction can only be achieved through SO2 scrubbers if coal remains as the fuel.\\nBefore China started the large-­\\nscale deployment of SO2 scrubbers in the early \\n2000s, the world in total had installed about 200 GW (Taylor et al., 2005). The \\nUnited States accumulated around 100 GW in a 25-­\\nyear period between 1975 and \\n2000 (Taylor et al., 2005). Germany and Japan together took 30% of the world’s \\n\\n\\nPolicy making  97\\nmarket, and the remaining 20% were in other countries (Taylor et al., 2005). The \\nscrubber capacity numbers presented in Figure 5.11 were calculated from a pub­\\nlicly available plant-­\\nlevel data set (Ministry of Environmental Protection, 2014). \\nThe dataset includes information on the name and location of coal power plants, \\nthe serial number and power capacity of generators, the dates that generators and \\nTable 5.2 Effluent SO2 emissions and necessary SO2 removal rates\\nHuolinhe \\n \\nDatong \\nShenfu \\nlignite\\nbituminous\\nbituminous\\nLHV (MJ/kg)\\n13.9\\n21.0\\n21.4\\nContents in coal (%)\\nSulfur\\n0.61%\\n0.99%\\n0.50%\\nCarbon\\n34.1%\\n55.7%\\n57.0%\\nHydrogen\\n2.7%\\n3.4%\\n3.4%\\nOxygen\\n10.5%\\n8.3%\\n8.0%\\nNitrogen\\n0.7%\\n0.9%\\n1.1%\\nEffluent SO2 emissions \\nConcentration (mg/Nm3)\\n2,315\\n2,291\\n1,133\\n(without removal)\\nEmissions (g/kWh)\\n6.79\\n7.27\\n3.60\\nFor achieving the \\nRequired SO2 removal \\n98.5%\\n98.5%\\n96.9%\\n35 mg/Nm3 standard\\nrate (%)\\nEmissions (g/kWh)\\n0.10\\n0.11\\n0.11\\nNote: Assuming the sulfur retention rate in ash, 90%; thermal efficiency of electricity generation \\n(42%, or 293 g of coal equivalent/kWh). Coal quality data are from Shi and Yu (2005).\\n0%\\n10%\\n20%\\n30%\\n40%\\n50%\\n60%\\n70%\\n80%\\n90%\\n100%\\n0\\n100\\n200\\n300\\n400\\n500\\n600\\n700\\n800\\n2000\\n2002\\n2004\\n2006\\n2008\\n2010\\n2012\\nShare of coal-fired power capacity \\n)\\nW\\nG\\n(\\n \\ny\\nt\\ni\\nc\\na\\np\\na\\nC\\nYear\\nCoal-fired power capacity\\nSO2 scrubber capacity\\nShare of coal-fired power capacity with SO2 scrubbers (right)\\nFigure 5.11  \\u0007\\nCoal-fired power and SO2 scrubber capacities in China\\nSource: Ministry of Environmental Protection (2014); EIA (2019); China Electricity Council (2010, \\n2006–2015).\\n\\n\\n98  Policy making\\nSO2 scrubbers came online, SO2 scrubber technology type and the name of the \\nSO2 scrubber company in charge. The SEPA (Ministry of Environmental Pro­\\ntection after March 2008) established a standard procedure for registering SO2 \\nscrubbers (SEPA, 2005, 2006b); for example, an SO2 scrubber had to operate \\ncontinuously for 168 hours to test its performance before registration.\\nChina’s share was negligible with only 5.6 GW of SO2 scrubbers at the end of \\n2000, or 2.5% of its coal-­\\nfired power capacity (Figure 5.11). In the 10th Five-­\\nYear \\nPlan (2001–2005), SO2 scrubber capacity rose to 46.7 GW in 2005. The progress \\nwas noticeable and the proportion of coal-­\\nfired power capacity with SO2 scrub­\\nbers increased to 12.5%. However, because total coal-­\\nfired power capacity esca­\\nlated from 218.9 GW in 2000 to 360.6 GW in 2005, essentially China had more \\ncoal-­\\nfired power plants without SO2 scrubbers to witness a steady increase of the \\npower sector’s SO2 emissions. In the 11th Five-­\\nYear Plan (2006–2010), coal-­\\nfired \\npower capacity grew at a much faster pace to reach 654.3 GW in 2010, while SO2 \\nscrubber capacity was lifted even faster to 569.3 GW in 2010. Then only 85.0 \\nGW of coal-­\\nfired power plants, or 13.0%, did not have SO2 scrubbers. This rate \\nhad already been much lower than that in 2000. In the following years, the ratio \\nfurther inched higher to 94.4% in 2013. Essentially, in China, nearly all coal-­\\nfired \\npower plants should have SO2 scrubbers to continue operation.\\nThe 11th Five-­\\nYear Plan witnessed a large-­\\nscale campaign to retrofit existing \\ncoal-­\\nfired power plants (Figure  5.12), besides shutting down many inefficient \\n0%\\n50%\\n100%\\n150%\\n200%\\n250%\\n300%\\n0\\n30\\n60\\n90\\n120\\n150\\n2000\\n2002\\n2004\\n2006\\n2008\\n2010\\n2012\\nRatio\\n)\\nW\\nG\\n(\\n \\nh\\nt\\nw\\no\\nr\\ng\\n \\ny\\nt\\ni\\nc\\na\\np\\na\\nc\\n \\nl\\na\\nu\\nn\\nn\\nA\\nYear\\nCoal-fired power capacity\\nSO2 scrubber capacity\\nRatio between SO2 scrubber and\\ncoal-fired power capacities (right)\\nFigure 5.12  \\u0007\\nThe annual growth of coal-fired power and SO2 scrubber capacities in China\\nSource: Ministry of Environmental Protection (2014); EIA (2019); China Electricity Council (2006–\\n2015, 2010).\\n\\n\\nPolicy making  99\\nsmall units (Xu et al., 2013). The ratios between the annually increased capacities \\nof SO2 scrubbers and coal-­\\nfired power plants were consistently higher than 100% \\nin every year of the 11th Five-­\\nYear Plan. At the retrofitting peak in 2008, SO2 \\nscrubber capacity grew by 127.4 GW while coal-­\\nfired power capacity increased \\nonly by 43.1 GW. After the 12th Five-­\\nYear Plan, a great majority of SO2 scrubbers \\nwere either built together with coal-­\\nfired power plants or further retrofitted for \\nmeeting more stringent effluent emission standards.\\nMost SO2 scrubbers fall into three scale categories: 300 MW, 600 MW and \\n1000 MW (Figure  5.13). They correspond to several predominant, standard­\\nized unit scales that China’s coal-­\\nfired power units have. Among the 754.9 GW \\nof coal-­\\nfired power units with SO2 scrubbers in 2013, 62.1 GW, 215.1 GW and \\n263.9 GW were within the 1,000~1,050-­\\nMW, 600~650-­\\nMW and 300~350-­\\nMW \\nranges, respectively. Two smaller scales have seen their importance fading after \\nChina focused more on larger and more efficient units. Respectively, 42.3 GW and \\n32.7 GW fell within the 200~220-­\\nMW and 135~150-­\\nMW ranges. In total, these \\nfive standardized unit sizes accounted for 618.6 GW or 81.9% of all SO2 scrub­\\nbers. These size and technology standardization provided one crucial advantage \\nin designing and rapidly deploying SO2 scrubbers.\\nThe geographic distribution of SO2 scrubbers reflects that of coal-­\\nfired power \\nplants. Provinces in East China, North China and South China had 249.2 GW, \\n213.0 GW and 104.1 GW (or 33.0%, 28.2% and 13.8%) of SO2 scrubbers, \\n0\\n20\\n40\\n60\\n80\\n100\\n120\\n140\\nBefore\\n2001\\n2003\\n2005\\n2007\\n2009\\n2011\\n2013\\n)\\nW\\nG\\n(\\n \\ny\\nt\\ni\\nc\\na\\np\\na\\nC\\nYear\\n>=1000 MW\\n600 MW ~ 999 MW\\n300 MW ~ 599 MW\\n200 MW ~ 299 MW\\n100 MW ~199 MW\\n< 100 MW\\nFigure 5.13  \\u0007\\nAnnually increased SO2 scrubber capacity and unit sizes\\nSource: Ministry of Environmental Protection (2014).\\n\\n\\n100  Policy making\\nrespectively, in 2013 (Figure  5.14). Northeast, Southwest and Northwest had \\n188.5 GW in total, or 25.0%. Their vast geographic territories indicate that these \\ncoal-­\\nfired power plants are scattered at much greater distances from each other \\nto potentially enhance difficulties for environmental compliance monitoring and \\nenforcement.\\nDifferent SO2 scrubber technologies correspond to a wide range of possible \\nSO2 removal rates. China had 1589 units of SO2 scrubbers at or above 200 \\nMW in 2013. The limestone-­\\ngypsum wet type is the most applied technol­\\nogy especially for large coal-­\\nfired power units, accounting for 93.6% of units \\n>=1000 MW, 96.1% of those between 600 MW and 999 MW, 87.6% of those \\nbetween 300 MW and 599 MW and 81.0% of those between 200 MW and \\n299 MW (Figure 5.15). The share dropped significantly for units smaller than \\n200 MW, being only 30.0% (Figure 5.15). Due to the same consideration of \\neconomy of scale, seawater type also heavily tilted toward large units (Fig­\\nure 5.15). Only 94.5 GW of SO2 scrubbers in 2013 were individually smaller \\nthan 200 MW (12.5% of all SO2 scrubbers), but they had 2,878 units (64.4% \\nof all; Figure 5.15).\\n0%\\n10%\\n20%\\n30%\\n40%\\n50%\\n60%\\n0\\n20\\n40\\n60\\n80\\n100\\n120\\n140\\nBefore\\n2001\\n2003\\n2005\\n2007\\n2009\\n2011\\n2013\\nProportion as retrofit\\n)\\nW\\nG\\n(\\n \\ny\\nt\\ni\\nc\\na\\np\\na\\nC\\nYear\\nEast\\nSouth\\nSouthwest\\nNorthwest\\nNorth\\nNortheast\\nPorportion as retrofit (right)\\nFigure 5.14  \\u0007\\nThe annual growth of SO2 scrubber capacity by regions (as categorized by the \\nsix Regional Supervision Bureaus of the Ministry of Ecology and Environ­\\nment; SO2 scrubbers are called “retrofits” when the online dates of SO2 scrub­\\nbers and coal power units are over one year)\\nSource: Ministry of Environmental Protection (2014).\\n\\n\\nPolicy making  101\\nReference\\nAng, B. W. 2005. 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The list of China’s SO2 scrubbers in coal-­\\nfired \\npower plants. Beijing, China: Ministry of Environmental Protection.\\nMinistry of Environmental Protection & General Administration of Quality Supervision \\nInspection and Quarantine. 2011. Emission standard of air pollutants for thermal power \\nplants. GB 13223-­\\n2011. Beijing, China: Ministry of Environmental Protection.\\nMinistry of Environmental Protection, National Development and Reform Commission & \\nNational Energy Administration. 2015. Comprehensive implementation of the upgrading \\nand retrofitting action plan for energy conservation and pollution mitigation in the coal-­\\nfired power sector. Beijing, China: Ministry of Environmental Protection.\\nNational Bureau of Statistics. 1997–2008. China energy statistical yearbook. Beijing, \\nChina: China Statistics Press.\\nNational Development and Reform Commission, Ministry of Environmental Protection & \\nNational Energy Administration. 2014. Upgrading and retrofitting action plan for energy \\nconservation and pollution mitigation in the coal-­\\nfired power sector (2014–2020). Bei­\\njing, China: Ministry of Environmental Protection.\\nNational People’s Congress. 2001. The outline of national 10th five-­\\nyear plan on economic \\nand social developments. Beijing, China: The 4th Conference of the 9th National Peo­\\nple’s Congress.\\nNational People’s Congress. 2006. The outline of the national 11th five-­\\nyear plan on eco­\\nnomic and social development. Beijing, China: The 4th Conference of the 10th National \\nPeople’s Congress.\\nNational People’s Congress. 2011. The outline of the national 12th five-­\\nyear plan on eco­\\nnomic and social development. Beijing, China: The 4th Conference of the 10th National \\nPeople’s Congress.\\nNational People’s Congress. 2016. Environmental protection tax law of the people’s repub­\\nlic of China. Beijing, China: The 4th Conference of the 10th National People’s Congress.\\nNational Statistics Bureau & Ministry of Ecology and Environment. 2019. China statisti­\\ncal yearbook on environment 2018. Beijing, China: China Statistics Press.\\n\\n\\nPolicy making  103\\nNDRC. 2001. Key special 10th five-­\\nyear plan on energy development. Beijing, China: \\nNDRC.\\nNDRC. 2004. Technical code for designing flue gas desulfurization plants of fossil fuel \\npower plants. DL/T5196-­\\n2004. Beijing, China: NDRC.\\nNDRC. 2007. 11th five-­\\nyear plan on energy development. Beijing, China: NDRC.\\nNPC. 1988. The standardization law of the people’s republic of China. Beijing, China: 7th \\nNational People’s Congress of the People’s Republic of China.\\nNPC. 2002. Environmental impact assessment law of the people’s republic of China. Bei­\\njing, China: 9th National People’s Congress of the People’s Republic of China.\\nOhara, T., Akimoto, H., Kurokawa, J., Horii, N., Yamaji, K., Yan, X. & Hayasaka, T. 2007. \\nAn Asian emission inventory of anthropogenic emission sources for the period 1980–\\n2020. Atmospheric Chemistry and Physics, 7, 4419–4444.\\nPortney, P. R. & Stavins, R. N. 2000. Public policies for environmental protection. Wash­\\nington, DC: Resources for the Future.\\nSEPA. 2001. National 10th five-­\\nyear plan on environmental protection. Beijing, China: \\nState Environmental Protection Administration.\\nSEPA. 2005. Flue gas limestone/lime – gypsum desulfurization project technical specification \\nof thermal power plant. Beijing, China: State Environmental Protection Administration.\\nSEPA. 2006a. Guidelines on calculating SO2 emission quotas. Beijing, China: State Envi­\\nronmental Protection Administration.\\nSEPA. 2006b. Technical guidelines for environmental protection in power plant capital \\nconstruction project for check and accept of completed project. Beijing, China: State \\nEnvironmental Protection Administration.\\nSEPA. 2007. Detailed methods to verify major pollutants emission reduction in the 11th five-­\\nyear period (on trial). Beijing, China: State Environmental Protection Administration.\\nSEPA & AQSIQ. 1996. Emission standard of air pollutants for thermal power plants. GB \\n13223-­\\n1996. Beijing, China: SEPA, AQSIQ.\\nSEPA & NDRC. 2008. National 11th five-­\\nyear plan on acid rain and SO2 pollution control. \\nBeijing, China: State Environmental Protection Administration, NDRC.\\nSheng, C. D., Xu, M. H., Zhang, J. & Xu, Y. Q. 2000. Comparison of sulphur retention by \\ncoal ash in different types of combustors. Fuel Processing Technology, 64, 1–11.\\nShi, D. & Yu, C. 2005. Optimization design, technical control and coal quality evaluation \\nof contemporary coal pre-­\\nprocessing. Beijing, China: China Contemporary Audio and \\nVideo Press.\\nSinger, J. G. 1981. Combustion, fossil power systems: A reference book on fuel burning and \\nsteam generation. Windsor, CT: Combustion Engineering.\\nSmith, S. J., Pitcher, H. & Wigley, T. M. L. 2001. Global and regional anthropogenic sulfur \\ndioxide emissions. Global and Planetary Change, 29, 99–119.\\nState Council. 1990. Regulations for the implementation of the law of standardization. \\nBeijing, China: State Council.\\nState Council. 1998. Administrative rule on environmental protection of construction pro­\\njects. Decree No. 253. Beijing, China: State Council.\\nState Council. 2007a. Notice on distributing implementation plans and methods of statis­\\ntics, monitoring and assessment on energy conservation and pollutant emission reduc­\\ntion. Beijing, China: State Council.\\nState Council. 2007b. Notice on distributing the 11th five-­\\nyear plan on environmental pro­\\ntection. Beijing, China: State Council.\\nState Environmental Protection Administration (SEPA) & General Administration of Qual­\\nity Supervision Inspection and Quarantine. 2003. Emission standard of air pollutants for \\n\\n\\n104  Policy making\\nthermal power plants. GB 13223-­\\n2003. Beijing, China: State Environmental Protection \\nAdministration.\\nTaylor, M. R., Rubin, E. S. & Hounshell, D. A. 2005. Control of SO2 emissions from power \\nplants: A case of induced technological innovation in the U.S. Technological Forecast­\\ning and Social Change, 72, 697–718.\\nTietenberg, T. H. 1990. Economic instruments for environmental regulation. Oxford \\nReview of Economic Policy, 6, 17–33.\\nThe U.S. Congress. 1990. Clean air act amendments 1990. Washington, DC: The U.S. \\nCongress.\\nXu, Y. 2011. China’s functioning market for sulfur dioxide scrubbing technologies. Envi­\\nronmental Science and Technology, 45, 9161–9167.\\nXu, Y., Williams, R. H. & Socolow, R. H. 2009. China’s rapid deployment of SO2 scrub­\\nbers. Energy & Environmental Science, 459–465.\\nXu, Y., Yang, C. J. & Xuan, X. W. 2013. Engineering and optimization approaches to \\nenhance the thermal efficiency of coal electricity generation in China. Energy Policy, \\n60, 356–363.\\nYan, G., Yang, J., Wang, J., Chen, X. & Xu, Y. 2009. Carry out SO2 emission trading \\nprogram to set up long-­\\nterm mechanism for emission reduction. In: Wang, J., Lu, J., \\nJintian, Y. & Li, Y. (eds.) Environmental policy research series. Beijing, China: China \\nEnvironmental Science Press.\\nZhang, B., Fei, H., He, P., Xu, Y., Dong, Z. & Young, O. 2016. The indecisive role of \\nthe market in China’s SO2 and COD emissions trading. Environmental Politics, 25, \\n875–898.\\nZhang, B., Zhang, H., Liu, B. B. & Bi, J. 2013. Policy interactions and underperform­\\ning emission trading markets in China. Environmental Science  & Technology, 47, \\n7077–7084.\\nZhao, Y., Wang, S., Duan, L., Lei, Y., Cao, P. & Hao, J. 2008. Primary air pollutant emis­\\nsions of coal-­\\nfired power plants in China: Current status and future prediction. Atmos­\\npheric Environment, 42, 8442–8452.\\n\\n\\n1  \\u0007\\nGoal-­\\ncentered policy implementation\\nIn a country with effective rule of law, law enactment and policy making are the \\nmost important step for environmental protection, while implementation is more \\nor less expected, although some bumps may still exist. China does not have sound \\nrule of law, and thus, its policy implementation could be even more important than \\npolicy making. In the United States, after the Acid Rain Program in the Clean Air \\nAct Amendments (1990) was enacted, law enforcement was largely the respon­\\nsibility of the administrative branch. The rule of law obliges the administration \\nto enforce the law. However, in China, no such tradition has been established to \\nensure that laws and policies will be genuinely implemented. Furthermore, Chi­\\nna’s policy implementation is heavily decentralized to local governments (Chap­\\nter 3), while the U.S. federal government has a relatively much stronger capacity \\nfor implementing their own policies. A key difference between China and the \\nUnited States is that China should first mobilize its decentralized policy imple­\\nmenters before witnessing significant efforts and sulfur dioxide (SO2) mitigation. \\nChina relies on the goal system to mobilize ministries at the central government \\nand, more important, local governments for policy making and implementation, \\nas discussed in Chapter 4.\\nEnvironmental compliance in China was indeed weak but has been improving \\nsteadily. China has made much progress in the past 15 years to reverse the ear­\\nlier poor implementation of environmental policies (Jin et al., 2016). Coal-­\\nfired \\npower plants in China have nearly universally installed SO2 scrubbers, already \\n94.4% as of 2013 (Figure 5.11). Although most SO2 scrubbers in China today \\ndo operate properly to greatly contribute to the deep reduction of SO2 emissions \\n(Figure 1.8), evidence of their misreporting and cheating was widely present to \\nindicate serious noncompliance problems. A study showed that many factories in \\nChina were primarily concerned about minimizing operation costs and only oper­\\nated their pollutant removal facilities when an inspection was imminent (OECD, \\n2006). Official data reported that SO2 emissions from the power sector in 2007 \\nwere 11.5 million tons (Ministry of Environmental Protection, 2006–2009), but \\nan independent study estimated that 16.4 million tons were emitted in that year \\n(Lu et al., 2010). In addition, official data announced that in 2007, 73.2% of SO2 \\n6\\t\\n\\u0007\\nPolicy implementation1\\n\\n\\n106  Policy implementation\\nwas removed from coal-­\\nfired power plants that had SO2 scrubbers (Ministry of \\nEnvironmental Protection, 2009b). In Jiangsu Province, which had a relatively \\ngood track record on environmental protection, however, the rate was found to \\nbe only about one third in the first few months of 2007 (SERC, 2009). Especially \\nbefore June  2007, cheating was widespread (Figure  6.1). Although almost all \\ncoal-­\\nfired power plants generally reported that their SO2 scrubbers were operating \\nnormally, later confirmed data found the operating time to be much shorter (Fig­\\nure 6.1). For those in operation, their SO2 removal efficiencies were often much \\nlower than required (SERC, 2009). However, after July 2007, a great majority \\nof their SO2 scrubbers were operating for more than 90% of the time and were \\nachieving SO2 removal efficiencies of over 90% (Jiangsu Department of Environ­\\nmental Protection, 2007–2009). Data from the Ministry of Environmental Protec­\\ntion reported that SO2 scrubbers had already been removing 78.7% of SO2 from \\nassociated coal-­\\nfired power plants in 2008 (Ministry of Environmental Protection, \\n2009b), indicating that they were largely operating as they were supposed to do. \\nThis chapter evaluates such transition and examines how the compliance deci­\\nsions were reversed.\\nAfter SO2 scrubbers are installed, the managers of coal-­\\nfired power plants decide \\nwhether to operate them or not. The willingness to install SO2 scrubbers does not \\n0%\\n20%\\n40%\\n60%\\n80%\\n100%\\n1/2006\\n7/2006\\n1/2007\\n7/2007\\n1/2008\\n7/2008\\ne\\nt\\na\\nR\\n \\nn\\no\\ni\\nt\\na\\nr\\ne\\np\\nO\\nMonth-Year\\nLater confirmed rates\\nSelf-reported rates\\nFigure 6.1  \\u0007\\nThe operation of SO2 scrubbers in Jiangsu Province, including self-reported \\noperation rates and later confirmed operation rates\\nSource: The Economic & Trade Commission of Jiangsu Province, 2009; Jiangsu Department of Envi­\\nronmental Protection, 2007–2009; State Electricity Regulation Commission (Nanjing office), 2009.\\n\\n\\nPolicy implementation  107\\nnecessarily mean that the incentives are strong enough for their proper operation. \\nIn addition, China’s SO2 scrubbers vary greatly in sizes, technology types, sul­\\nfur contents, costs of reagents and local environmental governance effectiveness. \\nA significant variance should exist in their operation especially across provinces.\\nStudies have shown that three conditions are favorable to ensure compliance \\nwith environmental legislation: low compliance costs, high penalties for noncom­\\npliance and a high probability of catching noncompliance (Cohen, 1999; Helland, \\n1998; Becker, 1968). The latter two conditions are complementary to each other. \\nIn 2000, Blackman and Harrington judged that in China, “both the probability \\nof getting caught for underreporting and the penalty for doing so are quite low” \\n(Blackman and Harrington, 2000). A 2009 IEA (International Energy Agency) \\nreport claimed that the operation of China’s SO2 scrubbers was problematic due \\nto high operation costs and ineffective environmental regulation (IEA, 2009). As \\nthe crucial factor to decide the probability of catching noncompliance, the impor­\\ntance of an effective compliance monitoring system has been widely recognized \\nfor implementing environmental policies and achieving their intended objectives \\n(Lu et al., 2006; Raufer and Li, 2009). Monitoring and site inspection are essential \\nfor catching offenders but are subject to the constraints of high costs and limited \\nbudgets (Arguedas, 2008). The problem is especially serious in developing coun­\\ntries (McAllister et al., 2010; Blackman and Harrington, 2000). To enforce the \\nSO2 allowance trading scheme in the United States, the strategy was to install \\ncontinuous emissions monitoring systems (CEMSs) with “periodic quality con­\\ntrol tests of monitoring devices to maintain the accuracy of emissions data” (The \\nU.S. Congress, 1990; Stranlund and Chavez, 2000). Large polluters can attract \\nmore attention. A study of the U.S. steel industry found that large polluting plants \\nattracted more scrutiny than their smaller counterparts, regardless of how good \\ntheir compliance record was (Gray and Deily, 1996).\\nSimilar to policy making, policy implementation in China is also goal-­\\ncentered, \\nunder which actions from the central and local governments focus more on whether \\nthey can contribute to goal attainment and less on whether policies are genuinely \\nimplemented. Heavily decentralized policy implementation facilitates their selec­\\ntive and goal-­\\ncentered enforcement efforts. Such selective policy implementa­\\ntion also indicates that many rules in China are not followed or respected even \\nby governments, which results in the weak rule of law. Given the political, eco­\\nnomic, social and technological feasibility of implementation, as well as probable \\ncapacity constraints, those policies that can lead to more pollution mitigation have \\nhigher probabilities of being prioritized in implementation. This will trigger the \\npolicy evolution through implementation selection, as discussed in Chapter 5. For \\nimplementing a given policy in China’s context of originally low environmental \\ncompliance rates, those factors that contribute to their enhancement are strength­\\nened selectively and sequentially, depending on how progress can be made more \\neffectively and efficiently with corresponding efforts. In a certain period, compli­\\nance costs are determined by technological statuses and market conditions, which \\nare largely not decided directly by the environmental administration. In the longer \\nterm, technologies may evolve and costs may go down, as examined in detail in \\n\\n\\n108  Policy implementation\\nChapter 7. The other two factors, penalties for noncompliance and environmental \\ncompliance monitoring, are primarily examined in this chapter.\\nThis goal-­\\ncentered policy implementation echoes the comparative advantage the­\\nory that was originated by David Ricardo to analyze the development of international \\ntrade (Ricardo, 1817). In a two-­\\ncountry, two-­\\nproduct model, even though a country \\nmay have lower productivity or absolute disadvantage in producing both products, it \\nstill could specialize in and export one product based on comparative advantage and \\nimport only the other. Heckscher and Ohlin further developed the model to attribute \\nthe origin of comparative advantage in a country’s factor endowment (Ohlin, 1967). \\nIt later became the foundation of a development theory that argued that a country \\nshould base its development on its comparative advantage (Chenery, 1961). Lin \\net al. employed this theory to explain the rapid economic growth of China and other \\ncountries (Lin et al., 2003). Before the economic reform in 1978, China adopted a \\nleap-­\\nforward strategy to develop capital-­\\nintensive heavy industries against its com­\\nparative advantage, and this resulted in slow and unsustainable economic growth, \\nwhereas after the reform, the comparative advantage of labor was better utilized to \\nachieve rapid economic growth and upgrading (Lin et al., 2003).\\nFrom a status of prevalent noncompliance, goal-­\\ncentered policy implementa­\\ntion suggests making progress according to the contingent comparative advantage \\nof alternative paths for achieving goals. When policy implementers decide which \\npath could better serve the SO2 mitigation goals, the chosen path should follow \\nthe direction whereby the effort’s “productivity” is comparatively higher. In other \\nwords, easier measures are taken first before moving to more difficult measures, \\nalthough many problems exist in the process.\\nThis chapter examines the progress of three key measures. Penalties for non­\\ncompliance were first increased. A 2007 policy provided subsidies to coal-­\\nfired \\npower plants for normally operating their SO2 scrubbers, but nonoperation would \\nincur a penalty of five times. Managers of those coal-­\\nfired power plants, mostly \\nstate-­\\nowned, would lose their jobs if cheating were caught. These penalties were \\nrelatively easier to be made available, while the more difficult environmental \\ncompliance monitoring was strengthened in following two steps to enhance the \\nprobability of catching noncompliance. First, more resources were made available \\nto support the conventional environmental compliance monitoring system that \\nfeatures monitoring, reporting and verification (MRV). CEMSs also played a key \\nrole to signal potential noncompliance. The strategy worked well for coal-­\\nfired \\npower plants that tend to be large, making frequent inspections little constrained \\nby the shortage of inspectors. Collusion was also made more difficult for improv­\\ning data quality. Furthermore, new technologies for environmental compliance \\nmonitoring are rapidly emerging and evolving, including sensors, satellites and \\nsocial media. They tend to be much cheaper in monitoring one polluter but less \\naccurate for legally confirming compliance statuses and issuing penalties, while \\nconventional technologies are much more expensive but, if working smoothly, \\ncan meet the legal accuracy requirements. In the 2010s and, especially, since \\n2015, the Chinese government has been actively developing and integrating these \\nbig data technologies into governance. In environmental protection with millions \\n\\n\\nPolicy implementation 109\\nof polluting sources scattered across China’s vast geographic landscape, environ-\\nmental compliance monitoring is one primary field to apply these new technolo-\\ngies for achieving higher compliance rates without demanding more resources.\\n2  \\nCompliance on the operation of SO2 scrubbers\\n2.1  SO2 scrubber technologies\\nCompliance costs of SO2 scrubbers are mainly for their operation as well as main-\\ntenance. A comprehension of SO2 scrubber technologies is accordingly essential \\nto understand how coal- \\nfired power plants may cheat on compliance and how the \\ngovernment could catch such noncompliance.\\nSO2 scrubbers (or flue gas desulfurization) have various technology types. Wet \\nscrubbers are the most applied technology with SO2 removal efficiencies nor-\\nmally over 90% (Figure 5.15). This section introduces major features associated \\nwith wet scrubbers and briefly compares these with dry scrubbers. After the flue \\ngas comes out of a dust- \\nremoval facility (generally electrostatic precipitator, or \\nESP, in China’s coal- \\nfired power plants), it will be directed to an SO2 scrubber \\nsystem. The first step is often to pass the flue gas through fans or boosters, which \\nfacilitate the flow and adjust the velocity of the flue gas to be in a desirable range \\nfor the best performance of the SO2 scrubber. Then the flue gas enters an absorber \\ntower, where actual SO2 removal happens. Generally speaking, coal-fired \\n \\npower \\ngeneration units of 300 MW or over should have their own absorber towers and \\ntwo units of 200 MW or less could share one (NDRC, 2004). The flue gas enters \\nthe absorber tower at the lower- \\nmiddle part and moves upward. Limestone slurry \\nmixed with products of chemical reactions fills the lower part of the absorber \\ntower and is lifted by several circulation pumps to the upper part. Special nozzles \\nare used to spray the slurry for the maximization of SO2 removal efficiency. The \\nfalling slurry droplets contact the flue gas physically and remove approximately \\n90% to 95% of SO2 through chemical reactions. Simply put, the main and over-\\nall reaction is CaCO3\\n2\\n+\\n+\\nSO\\nH O\\n2\\n3\\n→\\n+\\nCaSO\\nCO2\\n2\\n+ H O. Air is blown into the \\nslurry pool at the lower part of the absorber tower to force the oxidization of SO2-\\n3   \\n1\\nand make gypsum (CaSO 2\\n4\\n2\\nH O): CaSO3\\n2\\n+\\n+\\nO\\n2H O\\n2\\n2\\n4\\n→\\n↓\\nCaSO 2H2O . \\nBefore the flue gas exits from the top of the absorber tower, it passes through \\nequipment that removes mist. Because the processing removes much heat from \\nthe flue gas and the efficient outflow from a chimney (often over 200 m high for \\ncoal- \\nfired power plants) requires the flue gas to be above a certain temperature, a \\ngas–gas heat exchanger may be included to heat the outlet flow gas with the inlet \\nflue gas to raise its temperature.\\nTwo important side systems are respectively for the preparation of limestone \\nslurry and the production of gypsum. Limestone is crushed and mixed with water \\nto make limestone slurry. Fresh limestone slurry enters the absorber tower often \\nthrough circulation pumps. The bottom slurry with gypsum is pumped out and \\nfiltered to separate gypsum. The wastewater is sent to a treatment system.\\n\\n\\n110  Policy implementation\\nSO2 removal efficiency can be controlled by adjusting various factors, includ­\\ning the contact time length between the flue gas and the limestone slurry droplets, \\ncalcium-­\\nto-­\\nsulfur ratio (or Ca/S ratio) and liquid-­\\nto-­\\ngas ratio (or L/G ratio). The \\ncontact time depends on the velocity of the flue gas and the path length before its \\nleaving the point where limestone slurry is injected. The height of the absorber \\ntower is an influential factor determining the path length. Another factor is asso­\\nciated with the different injection heights of circulation pumps. Higher injection \\npoints indicate a longer path for contact and reaction. When the electricity genera­\\ntion unit is not in full load with less flue gas, not all circulation pumps will have to \\nbe operated. Then the choice of different circulation pumps could make some dif­\\nference in the SO2 removal efficiency. However, higher absorber tower and longer \\ncontact path correspond to higher electricity consumption to lift limestone slurry.\\nIn the L/G ratio, the liquid refers to the volume of limestone slurry dropping \\nfrom the upper part of the absorber tower, or circulated liquids. The gas is the \\nvolume of flue gas entering the absorber tower. Higher L/G ratio leads to higher \\nSO2 removal efficiency because the chance is higher for an SO2 molecule to be \\nabsorbed. It is controlled through circulation pumps: if the flue gas volume does \\nnot change, turning on more pumps indicates a higher L/G ratio. Since the number \\nand power of circulation pumps are fixed after an SO2 scrubber comes online, the \\nliquid volume has an upper limit, which restrains the maximum contribution of \\nenhancing L/G ratio to increase SO2 removal efficiency.\\nCa/S ratio is the molar ratio between calcium carbonate (CaCO3) and sulfur \\noxides (SOx, dominantly SO2). In a perfect situation, as predicted in the chemical \\nreaction introduced earlier, the ideal Ca/S ratio is 1 to remove all SO2 and use up \\nall limestone. But in the actual situation, not all limestone will be consumed and \\nnot all SO2 will be removed. SO2 wet scrubbers can achieve high efficiencies in \\nboth aspects. As a result, the actual Ca/S ratio is only a little higher than 1, usually \\naround 1.03 for China’s wet scrubbers (Wu and Qian, 2007). Because the inlet \\nquantity of SO2 changes with the volume of flue gas and the SO2 concentration, \\neven though the Ca/S ratio is maintained stable, the rate of adding limestone to the \\nsystem will still change. On the other hand, the workload of removing SO2 could \\nbecome too heavy when the actual sulfur content exceeds the designed level by \\na significant margin. In this situation, when all circulation pumps are turned on \\nand the L/G ratio has reached its maximum, the only major method to maintain \\na required high SO2 removal efficiency is to enhance the Ca/S ratio. However, a \\nmuch higher Ca/S ratio than the designed level will not only add costs but also \\nwill more likely clog the system and barricade its normal function. The adjustment \\nof the Ca/S ratio is through controlling the pH value of the limestone slurry in the \\nabsorber tower. In daily operation, the pH value should be maintained within a \\nrange. A pH value above the normal range indicates excessive limestone and that \\nthe injection rate of fresh limestone slurry should be reduced.\\nSO2 wet scrubbers consume about 1% of the electricity generated from the cor­\\nresponding power generation units. The rate could be as high as 3.5% when high-­\\nsulfur coal is burned with a heavy workload of SO2 removal. China’s coal-­\\nfired \\npower plants consumed, on average, 6.79% of the electricity they generated in \\n\\n\\nPolicy implementation  111\\n2008 (SERC et al., 2009), in which SO2 scrubbers accounted for a notable share. \\nSignificant electricity-­\\nconsuming components of SO2 scrubbers include the fans, \\ncirculation pumps and limestone slurry preparation system.\\nTwo major economies of scale are associated with SO2 scrubbers in construc­\\ntion. First, the size of an absorber tower is largely determined by the volume of \\nflue gas or the scale of the corresponding power generation unit. A larger volume \\nof flue gas or a larger scale in megawatts leads to lower average costs for each \\nunit of flue gas treated or each megawatt. Because absorber towers are responsi­\\nble for a large part of the capital costs, this economy of scale could significantly \\nreduce the unit capital costs. Since most nonpower SO2 emission sources consume \\nmuch less coal and do not generate large enough volume of flue gas to provide \\nthe economy of scale, the unit costs of SO2 scrubbers are often more expensive.\\nSecond, higher SO2 concentration in the inlet flue gas, or higher sulfur input \\nrate, raises capital costs for each unit of flue gas treated because they require \\nlarger systems of limestone preparation and gypsum handling, as well as probably \\nhigher absorber tower and more circulation pumps. Economy of scale can also \\nbe realized for these systems to treat each unit of SO2. SO2 concentration in the \\ninlet flue gas is mostly determined by two factors: sulfur and thermal contents of \\ncoal. The link with sulfur contents is quite straightforward: if different types of \\ncoal only differ in sulfur contents, higher sulfur contents indicate more SO2 in a \\nroughly equal amount of flue gas. With the same thermal efficiency, the volume of \\nflue gas mainly depends on the thermal input. Then lower thermal contents of coal \\nmean that more coal has to be burned for the required thermal input, and accord­\\ningly, more SO2 will be generated. Accordingly, sulfur content per unit of energy \\nis a better indicator of SO2 concentration in the inlet flue gas of SO2 scrubbers.\\nThe product of SO2 scrubbers is gypsum. Depending partly on the quality, it \\ncan either be sold in the market or go to landfill. A significant market for gypsum \\nis in building materials.\\nThe operation and maintenance (O&M) of SO2 scrubbers are associated with \\ncosts in materials (including mainly limestone, electricity and water), labor and \\nmaintenance. The sale of gypsum could earn some revenue but often only at an \\ninsignificant portion. If the quality of SO2 scrubbers remains about the same, \\nmaintenance costs are positively related to the capital investment of SO2 scrub­\\nbers. As a result, larger scales of SO2 scrubbers are linked with lower maintenance \\ncosts on the bases of megawatt-­\\nhour or ton SO2 removed. Similarly, economy \\nof scale is also relevant to labor costs, but the impact on overall O&M costs is \\nconstrained by the insignificant share of labor costs; for example, my field trip \\nto China’s coal-­\\nfired power plants found that roughly 15 workers were required \\nto run the SO2 scrubber and ESP for a 300-­\\nMW plant in 2008. Their total annual \\ncosts could be about 1 million RMB. The average O&M costs of China’s SO2 \\nscrubbers were about 15 RMB/MWh, indicating that the total O&M costs would \\nbe approximately 23 million RMB if the capacity factor was about 5,000 hours/\\nyear. Then the share of labor costs was less than 5%.\\nMaterials comprise most of operation costs. In normal operation, the Ca/S ratio \\nremains fairly stable, and thus, the limestone consumption is about linearly related \\n\\n\\n112  Policy implementation\\nto sulfur input. Electricity consumption for running SO2 scrubbers can be roughly \\ndivided into three major parts: in fans that are mainly associated with the flue \\ngas volume, in the handling of limestone and gypsum that is affected by sulfur \\ninput and in circulation pumps connected with both. Most water consumption is \\nin the form of evaporation to the flue gas in the absorber tower, and the water is \\nreleased to the atmosphere together with the cleaned flue gas. As a result, water \\nconsumption is mainly correlated with the volume of flue gas and is also affected \\nby economy of scale.\\nBecause of its wide availability and low costs, limestone is the dominant \\nabsorbing reagent in wet scrubbers. However, other alkaline reagents are some­\\ntimes applied, such as seawater and alkaline wastewater. Furthermore, SO2 scrub­\\nbers can be dry. Lime (CaO) is often used as the absorbing reagent. Because of its \\nmuch lower utilization rate, the Ca/S ratio has to be much higher (e.g., 1.3~1.5). \\nGenerally, the SO2 removal efficiency is in the range of about 70% to 80%, lower \\nthan that of wet scrubbers. The capital costs of dry scrubbers are lower, but the \\noperation and maintenance costs are higher (EPA, 2003).\\n2.2  \\u0007\\nNoncompliance behaviors\\nThe managers of coal-­\\nfired power plants have strong incentives to avoid the costs \\nof O&M. Data from Jiangsu Province showed that from 2006 to June 2007, the \\nself-­\\nreported operation rates (the percentage of time that an SO2 scrubber is in \\noperation alongside the corresponding power generation unit) from coal-­\\nfired \\npower plants were significantly higher than the values that were later confirmed, \\nlikely through other relevant data such as limestone consumption, gypsum pro­\\nduction and electricity consumption (respectively, more than 90% and about 60%; \\nFigure 6.1). The discrepancy reflects the likely magnitude of misreporting. This \\nsection discusses several prominent problems that emerged from the author’s \\ninterviews and the literature. These problems prevented the proper operation of \\nSO2 scrubbers and caused very significant uncertainty in estimating SO2 emis­\\nsions from coal-­\\nfired power plants.\\nTypical noncompliance behaviors could include the following: first, SO2 emis­\\nsions may be underreported and the quality of SO2 scrubbers could be poor. Coal-­\\nfired power plants underreported SO2 emissions to pay a lower effluent discharge \\nfee and to be seen as complying with regulations. In 2007, 98% of coal consumed \\nin China’s power plants was raw coal (National Bureau of Statistics, 2008). Coal-­\\nfired power plants were allowed to pick out coal stones from received raw coal \\nto calculate actual coal consumption. In interviews, the author found that coal \\nstones were sometimes overreported. This factor could have led to a 1% to 2% \\nunderestimation of SO2 emissions. Furthermore, China’s coal-­\\nfired power plants \\nusually had to use different coals with sulfur contents that could vary signifi­\\ncantly. The instability of coal supply was confirmed by Steinfeld et al. (2009). It \\nmade the underreporting of sulfur contents harder to detect. Interviews in China’s \\nSO2 scrubber companies found that many early scrubbers (e.g., before 2005) had \\nserious quality problems. In order to reach designed SO2 removal efficiencies, \\n\\n\\nPolicy implementation  113\\nbesides the replacement of malfunctioning equipment, a few SO2 scrubbers even \\nhad to have their very expensive absorber towers retrofitted. The main reason \\nfor the faults in the SO2 scrubbers was that they were designed on the basis of \\nunderreported sulfur contents. In China’s first public and high-­\\nprofile statement \\nto penalize the abnormal operation of SO2 scrubbers, instability and bad quality \\nwere particularly pointed out, and three power plants were found to use coal with \\nmuch higher sulfur than the designed levels (Ministry of Environmental Protec­\\ntion, 2008). At the design stage of SO2 scrubbers, if the managers of coal-­\\nfired \\npower plants had been underreporting sulfur contents in the past, they would con­\\ntinue to do so to conceal their guilt. Some managers did not plan to operate their \\nSO2 scrubbers initially and were not concerned about their quality. They installed \\nthe SO2 scrubbers purely in order to comply with the government’s requirements \\nand to qualify for a subsidy for generating desulfurized electricity. The managers \\nwanted to minimize capital costs through underreporting sulfur contents. When \\ninspections were known in advance, reaching the required SO2 removal efficien­\\ncies was not a problem because coal-­\\nfired power plants often kept some low-­\\nsulfur coal in reserve on-­\\nsite.\\nSecond, illegal bypass ducts may be used to avoid flue gas treatment. Many \\nSO2 scrubbers had bypass ducts to allow the flue gas to exit without going through \\nthe SO2 scrubber systems. The purpose was to enable electricity generation when \\nSO2 scrubbers had minor problems and need to be shut down temporarily. In a \\n2007 policy, coal-­\\nfired power plants were not penalized provided that their SO2 \\nscrubbers were properly operating for at least 90% of the time (NDRC and SEPA, \\n2007b). However, bypass ducts also provided opportunities to avoid the operation \\nof SO2 scrubbers when they functioned normally. Six coal-­\\nfired power plants were \\npenalized for illegally using bypass ducts and leaving some flue gas untreated in \\n2007 and 2008 (Ministry of Environmental Protection, 2008, 2009c).\\nThird, data from CEMSs may also be inaccurate and manipulated. CEMSs \\ncould greatly enhance environmental monitoring capacity. China had 60 SO2 \\nscrubbers at the end of 2004 (Ministry of Environmental Protection, 2010a), while \\na general survey in 2004 found that about 400 CEMSs had been installed in 180 \\ncoal-­\\nfired power plants (Pan et al., 2005). The author’s site visits and Steinfeld \\net al. also found that CEMSs were being widely used (Steinfeld et al., 2009). As \\nfar as cost was concerned, there was little reason for coal-­\\nfired power plants to \\nresist the installation of CEMSs. Two CEMSs in Plant 3 in Table 6.1 cost about \\nUS$132,000, only 0.5% of the capital costs of the plant’s SO2 scrubbers. How­\\never, CEMSs may not report credible and reliable data. One concern was over \\nthe quality of the equipment used. CEMSs cost much more in the United States: \\naccording to a cost model from the U.S. Environmental Protection Agency (EPA), \\nit generally required more than half a million dollars for one set (The U.S. EPA, \\n2007). The 2004 general survey found that only 20% of the CEMSs in China were \\nfunctioning normally (Pan et al., 2005), local environmental protection bureaus \\ngenerally refused to accept data from CEMSs and only one was recognized as a \\ncredible data source for the purposes of levying the SO2 effluent discharge fee \\n(Pan et al., 2005). Later on, CEMSs were officially accepted as data sources after \\n\\n\\n114 Policy implementation\\n \\nge \\nUS$/MWh\\nThe \\nThe \\n2.5\\n0.7\\n6.83 RMB. Upon the request \\n (State Devel-\\n**\\ndisclosed in Plant 4. Comparing with other plants in the eastern provinces, 1.0% is used here for later analysis. ** \\n(State \\nstandard \\nEffluent \\ndischar\\nfee \\n2.0\\n2.8\\n0.3\\n0.7\\n0.4~0.7\\n2008. \\ndata \\nthe \\nfor \\n2\\nofficial \\ngenerally \\nand \\nemium for \\ndesulfurized \\nof US$0.092/kg SO\\nChina’s \\ngeneration; \\nPrice \\npr\\nelectricity\\nUS$/MWh\\n2.2\\n2.2\\n2.2\\n2.2\\n2.2\\n3.7\\nestimation \\n \\n =\\ncompiling \\ngin \\nrecent \\nmar\\nofit \\ngeneration\\nUS$/MWh\\n~ 14.6\\n> 0\\n>> 14.6\\n< 7.3\\nPr\\nof electricity \\nmost \\ntheir \\nreflect \\n31, 2008, is used: US$1\\n \\n& \\ngin \\n \\nmar\\nThe fee rate refers to the level \\nin \\nelectricity \\nassumed \\nas \\nefficiencies of \\n20%, \\nash, \\nthermal \\ninterviews; \\nOperation\\nmaintenance \\n(O&M) costs\\nUS$/MWh\\n~4.1\\n1.8\\n2.2\\n<2.2\\n(1): >3.7;\\n(2): <3.7\\nprofit \\nand \\n scrubbers. \\nin \\n3.7\\nrates \\n2\\nSO\\nretention \\ns \\n’\\ncosts \\nauthor\\nts\\nSulfur content\\nThe \\ndown \\nthe \\nto \\n*\\n2009. \\nshutting \\nechnical Supervision, 2007).\\ns seven coal-fired power plan\\nsulfur \\nare \\n%\\n3.0%\\n4.0%\\n3.5%\\n1.0% \\n0.5%\\n1.0%\\n0.7~1.1%\\nT\\nJuly \\ndollars, the exchange rate on December\\nand \\nassumptions \\naccording \\n95%, \\n \\nJune \\npayment if \\n \\nin \\n \\n2\\nt\\nt\\nt\\nt\\nSO\\nscrubber \\ntype\\nt\\nt\\nWe\\nWe\\nWe\\nWe\\nWe\\nWe\\n(1): dry;\\n(2): wet\\nadditional \\nintermediate \\nscrubbers, \\ninterviews \\n scrubbers in China’\\nwet \\nthe \\nThe \\nof \\nNew or \\nRetrofit\\nRetrofit\\nRetrofit\\nRetrofit\\nRetrofit\\ns \\nofit\\n’\\nreflect \\n2003). \\ns \\nRetr\\nNew\\nNew\\nauthor\\ncalculated to \\nal., \\nthe \\n \\net\\nefficiencie\\nin \\n2\\nremoval \\nRegion\\nSouthwest\\nSouthwest\\nSouthwest\\ncollected \\nis \\n \\n2\\nEast\\nEast\\nEast\\nEast\\nCommission \\nData on SO\\nfee \\nwere \\noriginal currency units were in Chinese RMB. In the conversion to U.S. \\nge \\ndata \\nPlanning \\n2007b); SO\\n \\nThe \\nopment \\nCouncil, \\nTable 6.1\\nPlant 3\\nPlant 5\\nPlant 6\\nPlant 7\\nclear information on sulfur contents was \\nNote: \\nof the interviewees, the names of coal-fired power plants are intentionally not shown.\\ndischar\\nPlant No.\\nNo \\neffluent \\nPlant 1\\nPlant 2\\nPlant 4\\nlevels at the corresponding unit scales (Zhejiang Bureau of Quality and \\n \\n*\\n\\n\\nPolicy implementation  115\\ntheir online connection with provincial environmental protection bureaus. How­\\never, the author’s interviewees still said that they did not fully trust data from \\nCEMSs. The locations of the sensors could affect the readings of CEMSs, and \\ndata reporting could also be manipulated. In 2008, three coal-­\\nfired power plants \\nwere caught illegally setting up ceilings of outlet SO2 concentrations that could be \\nreported (Ministry of Environmental Protection, 2009c).\\nFourth, coal-­\\nfired power plants could either cheat or even collude with environ­\\nmental compliance inspectors. Data from CEMSs were compared quarterly with \\ndirect measurements to verify accuracy (State Council, 2007b). A survey in China \\nfound that multiple inspections per annum tended to deter violation, no matter \\nwhich government level inspectors were from (Lu et al., 2006). However, the \\neffectiveness of site inspections could be constrained. According to the author’s \\ninterviews, many plants were able to raise the removal efficiency of their SO2 \\nscrubbers from zero to the designed level in half an hour and significantly more \\nquickly if from an intermediate level. Some plants therefore kept their scrubbers \\neither turned off or on low power and put them in full operation only when an \\ninspection was imminent, enabling them to keep costs down while also passing \\nthe inspection. Even if abnormal operation were caught, a solution could be to \\ncollude with inspectors through bribes.\\n3  \\u0007\\nReversing noncompliance: penalty\\nThe proper operation of SO2 scrubbers demands strong enough incentives to over­\\ncome the hurdle of the high O&M costs. In the United States, the average O&M \\ncosts in 2008 were US$1.55/MWh (EPA and DOE, 2010). These figures could \\nhardly be extrapolated for China because of the great differences in the capital \\ncosts of SO2 scrubbers, labor costs and other items. My interviews collected rel­\\nevant data from six coal-­\\nfired power plants, as presented in Table 6.1. The O&M \\ncosts varied from US$1.8 to 4.1/MWh, all above the average in the United States. \\nSulfur contents were the most influential factor: Plants 1 and 3 burned coals with \\napproximately 3% to 4% sulfur content, and their O&M costs were roughly twice \\nas high as those in Plants 4, 5, 6 and 7, which burned coals with 1% sulfur content \\nor less. The O&M costs could be used as the average marginal costs of operating \\nSO2 scrubbers. In generating electricity, several coal-­\\nfired power plants that the \\nauthor visited had gross profit margins from not much above zero to significantly \\nover US$14.4/MWh (including the O&M costs of SO2 scrubbers and the price \\npremium for desulfurized electricity).\\nA survey of China’s inspection authorities and polluting firms found that fines \\nfor noncompliance were often not high enough to deter potential offenders (Lu \\net  al., 2006). The initial SO2 effluent discharge fee was about 0.20 RMB/kg \\n(US$0.031/kg) in most provinces and lower than the marginal abatement costs in \\nChina’s large plants (Cao et al., 1999; Dasgupta et al., 1997). Polluting firms may \\nsimply pay to pollute. When facing a penalty, the first reaction of polluting firms \\nwas to negotiate with environmental protection bureaus or ask for the interference \\nof local governments (Lu et al., 2006), which compromised the penalty.\\n\\n\\n116  Policy implementation\\nIn July 2005, China’s SO2 effluent discharge fee was raised from US$0.031/kg \\nin 2003 to US$0.092/kg (State Development Planning Commission et al., 2003). \\nHowever, as converted to US$/MWh in Table 6.1, it was still too low to overcome \\nthe hurdle of the much higher O&M costs. Another increase was scheduled in \\n2007 to reach US$0.18/kg in three years (State Council, 2007a), but the exact \\nschedule varied from province to province. In Jiangsu Province, the higher rate \\nhad been in effect since July 2007 (Jiangsu Department of Environmental Pro­\\ntection, 2008), but in Henan Province, the lower rate was still being applied in \\nthe first quarter of 2010 (Henan Department of Environmental Protection, 2010). \\nWith the higher rate, coal-­\\nfired power plants burning high-­\\nsulfur coals would find \\noperating SO2 scrubbers cheaper than paying the effluent discharge fee (Plants 1 \\nand 3 in Table 6.1). However, for others (Plants 4, 5, 6 and 7) when facing only \\nthis policy, the rational decision was to pay the fee.\\nAnother policy was introduced in 2004. If new coal-­\\nfired power plants came \\nonline together with SO2 scrubbers, the desulfurized electricity could enjoy a \\nprice premium of US$2.2/MWh (NDRC and SEPA, 2007a). In June 2006, the \\npolicy extended to cover all SO2 scrubbers, including retrofitted ones (NDRC and \\nSEPA, 2007a). Some coal-­\\nfired power plants were awarded higher price premi­\\nums, such as Plant 7 in Table 6.1. The price premium and the effluent discharge \\nfee together were a little higher than the O&M costs (Table 6.1), but the small \\ndifference indicated that the proper operation would be a rational decision only \\nwhen most nonoperation cases were caught.\\nThe 11th Five-­\\nYear Plan witnessed sharp increases in noncompliance penalties. \\nIn 2007, a harsh penalty measure was associated with the price premium for the \\nfirst time. If the operation rate of an SO2 scrubber were lower than 80%, a penalty \\nof US$11.0/MWh would be issued for any additional non-­\\ndesulfurized electric­\\nity generation (NDRC and SEPA, 2007b). The required minimum probability of \\ncatching nonoperation became much lower to induce the proper operation of SO2 \\nscrubbers. For Plant 3 in Table 6.1 burning high-­\\nsulfur coal, corresponding to the \\neffluent discharge fee of US$0.092/kg SO2, a risk-­\\nneutral manager would decide \\nto operate SO2 scrubbers properly if the probability of catching nonoperation \\nexceeded 26% (see Table 6.2 for the calculation formula). For Plants 4 and 5 burn­\\ning low-­\\n to medium-­\\nsulfur coals, the minimum probability was about one seventh. \\nFurthermore, additional penalties were introduced on the managers of coal-­\\nfired \\npower plants. In China, almost all coal-­\\nfired power plants were owned by the \\nstate. The nonoperation of SO2 scrubbers could increase profit and benefit the \\nmanagers’ career and salary. However, according to formal regulations (NDRC \\nand SEPA, 2007b) and the author’s interviews, cheating and nonoperation could \\nlead to the removal of the managers. They had to calculate the risk for themselves.\\nThe penalties in 2007 also aimed for minimizing potential moral hazard when \\nSO2 scrubbers occasionally had to stop operating due to accidents, malfunctions \\nor other reasons. While they were out of action, SO2 emissions could be controlled \\neither by minimizing the sulfur content of coal or by shutting down electricity \\ngeneration. China would issue no penalty as long as the operation rate were above \\n90%, a mild penalty of US$2.2/MWh if the rate were between 80% and 90% and \\n\\n\\nPolicy implementation 117\\nTable 6.2 Decision scenarios for the managers of coal-fired power plants\\nScenario SO2 scrubbers SO2 scrubbers Electricity Net revenue of a coal-fired power \\nfunctioning\\noperating\\ngeneration plant\\n(1)\\nYes\\nYes\\nYes\\nProfit margin\\n(2)\\nYes\\nNo\\nYes\\nProfit margin + O&M costs – C% × \\n(Price premium + Discharge fee + \\nPenalty)\\n(3)\\nNo\\nNo\\nYes\\nProfit margin + O&M costs – C% × \\n(Price premium + Discharge fee + \\nPenalty)\\n(4)\\nNo\\nNo\\nNo\\n0\\nNote: C% is the actual probability of catching the nonoperation of SO2 scrubbers. The \\nproper operation of SO2 scrubbers, when they function, requires that the net revenue in sce-\\nnario (1) is greater than that in scenario (2). The corresponding condition can be calculated as \\nO&M costs\\nC% >\\n. When SO2 scrubbers do not function, the discon-\\nDischarge fee\\nP\\n+\\n+\\nrice premium\\nPenalty\\ntinuation of electricity generation becomes a rational decision when the net revenue in scenario \\nProfit margin + O&M costs\\n(4) is greater than that in scenario (3), or C% >\\n. Because \\nDischarge fee\\nP\\n+\\n+\\nrice premium\\nPenalt\\nl y\\nprofit margins are generally positive, it is accordingly easier to push for the proper operation of \\nSO2 scrubbers when they function than to ask coal-fired power plants to discontinue electricity gen-\\neration when they do not. In order to encourage coal-fired power plants to fix malfunctioning SO2 \\nscrubbers as soon as possible, the rational decision when SO2 scrubbers function should generate \\ngreater net revenue than that with malfunctioning SO2 scrubbers. The condition is fulfilled when \\nO&M costs\\nC% >\\n.\\nDischarge fee\\nP\\n+\\n+\\nrice premium\\nPenalty\\na harsh penalty of US$11.0/MWh if the rate were under 80% (NDRC and SEPA, \\n2007b). Because it was expensive to restart electricity generation, the O&M costs \\nof SO2 scrubbers may not be critical in the decision making when SO2 scrubbers \\ncould get fixed soon.\\nWhen problems have to take much time to fix – for example, several weeks – and \\nthe penalty of US$11.0/MWh is applied, the economic incentives should make it \\na rational decision to discontinue electricity generation for many coal-fired \\n \\npower \\nplant managers. Electricity generation without operating SO2 scrubbers earned \\na profit margin and avoided the O&M costs of SO2 scrubbers, but if the non-\\noperation of SO2 scrubbers were caught, coal-fired \\n \\npower plants would need to \\nreturn the price premium and pay the effluent discharge fee as well as the penalty. \\nMany coal- \\nfired power plants might continue generating electricity as long as the \\nprobability of catching the nonoperation of SO2 scrubbers was low enough (see \\nTable 6.2 for the specific calculation). For coal-fired \\n \\npower plants with large profit \\nmargins (such as Plant 5 in Table 6.1), electricity generation should continue even \\nwhen nonoperation could not be hidden at all. However, when the author visited \\nPlant 5, electricity generation in one system had been discontinued for several \\nweeks due to its malfunctioning SO2 scrubber. Personal penalties on the manag-\\ners could have played a role. Furthermore, even if the decision was to continue \\nelectricity generation, a high-enough probability \\n \\nof detection was still necessary \\n\\n\\n118  Policy implementation\\nto encourage coal-­\\nfired power plants to fix malfunctioning SO2 scrubbers as soon \\nas possible (see Table 6.2 for the specific calculation). If the actual probability was \\nnot expected to reach this level, there would be little concern about the quality of \\nSO2 scrubbers, as in the early years.\\nFurthermore, coal-­\\nfired power plants should also comply with regulations on \\nSO2 removal efficiency and effluent emission standards (NDRC and SEPA, 2007b; \\nSEPA and General Administration of Quality Supervision Inspection and Quar­\\nantine, 2003; MEP and AQSIQ, 2011). Technically in practice, a coal-­\\nfired power \\nplant could choose a designated SO2 removal efficiency. For example, higher \\nratios of Ca/S (the molar ratio between CaCO3 and SOx) or L/G (the liquid-­\\nto-­\\ngas \\nratio in volume) would remove more SO2 from the flue gas. Reasonably, if not \\nregulated, a coal-­\\nfired power plant could lower SO2 removal efficiencies to reduce \\ncosts. On the other hand, because of changing sulfur contents and workload, SO2 \\nconcentration and flue gas volume were not stable. Scrubbers’ capability to track \\nthe changes – with the same methods of adjusting SO2 removal efficiencies – was \\nnecessary for their reliable operation.\\nThe Chinese central government mandated minimum SO2 removal efficiencies \\nbeing established (NDRC and SEPA, 2007b) and provincial governments were in \\ncharge of the details. For example, when SO2 removal efficiencies were lower than \\npredetermined levels (generally 90% for wet scrubbers), Henan Province simply \\ncounted the time as nonoperation (Henan Development and Reform Commission \\nand Henan Environmental Protection Bureau, 2007). In normal conditions, the \\nincentives were strong enough to make SO2 scrubbers reach the required levels of \\nSO2 removal efficiencies. Two actual cases from the author’s field trip could demon­\\nstrate the decisions. In the first case, sulfur contents went up significantly but were \\nexpected to be a temporary situation. The designed sulfur content for Plant 6’s SO2 \\nscrubber was 0.84%, but for a period in 2008 when coal supply was constrained, \\nthe actual sulfur content was higher than 2%. Such a dramatic increase in sulfur \\ncontent became a serious burden. To maintain SO2 removal efficiencies over 90%, \\nthe solution was to raise the Ca/S ratio from the designed level of 1.03 to 1.3. In the \\nsecond case, when the increased sulfur contents were expected to be long-­\\nlasting, \\na temporary solution would not be sustainable. One of the eight coal-­\\nfired power \\nplants the author visited had to shut down and modify the original SO2 scrubber to \\nhandle the much higher sulfur input rate. Particularly, the absorber tower became \\nsignificantly taller by adding another section on the top of the original one. The \\npathway was accordingly longer for the flue gas and limestone slurry to contact and \\nreact. Additional circulation pumps could also be added to enhance the L/G ratio.\\nIn order to better implement the incentives, responsible government agen­\\ncies are specified: electric grid corporations were in charge of paying the price \\npremium in time; provincial environmental protection bureaus collected effluent \\ndischarge fees; provincial price agencies were responsible to recover unjustified \\nprice premium according to actual operation rates (NDRC and SEPA, 2007b). \\nSeven coal-­\\nfired power plants in 2008 and five in 2009 were penalized for cheat­\\ning or nonoperation with the US$11.0/MWh penalty applied (Ministry of Envi­\\nronmental Protection, 2009c, 2008).\\n\\n\\nPolicy implementation  119\\nCentral and local governments in China are not the only entities that have their \\ntasks centered around goals. Because almost all coal-­\\nfired power plants in China \\nwere state-­\\nowned, they were also assigned quota or goals for their total SO2 emis­\\nsions (SEPA, 2006). Both goals and policies play crucial roles in their compli­\\nance decisions on the operation of their SO2 scrubbers. In addition to financial \\npenalties, administrative penalties were also applied for noncompliance. In envi­\\nronmental enforcement and compliance, decision makers at local governments, \\npower corporations and coal-­\\nfired power plants also kept in mind their SO2 emis­\\nsion caps or goals. If SO2 removal efficiencies were too low and nonoperation was \\ncaught, the SO2 emission permits could be used up soon. In addition, seriously \\nabnormal operation of SO2 scrubbers was publicly punished (MEP and NDRC, \\n2008; Ministry of Environmental Protection, 2009a), which could affect the \\ncareer of the coal-­\\nfired power plants’ managers. In the words of an interviewee, \\n“it is not worthwhile for the managers of a coal-­\\nfired power plant to risk losing \\nthe positions to save money for the plant. Anyway, the money is not theirs, but \\nthe positions are.”\\n4  \\u0007\\nReversing noncompliance: environmental \\ncompliance monitoring\\nThe effectiveness of environmental compliance monitoring determines the prob­\\nability of catching noncompliance. China’s emission data MRV system is largely \\nbottom up, which could potentially suffer from two major challenges. The first \\nchallenge lies in the system’s high costs. Compliance monitoring resource con­\\nstraints exist in all countries, but the problem is especially daunting in develop­\\ning countries, due to the high costs of compliance monitoring, limited resources, \\nunderstaffed environmental agencies, inadequate training and technological sup­\\nport (Arguedas, 2008; McAllister et al., 2010; Blackman and Harrington, 2000; \\nRussell and Vaughan, 2003; Pan et  al., 2005). How to better utilize available \\nresources is critical to determine the effectiveness of every domestic policy and \\ninternational environmental treaty. Compliance monitoring is the most resource-­\\nconsuming activity in enforcing environmental policies. For example, an emis­\\nsion trading scheme should effectively deter cheating and verify actual emission \\nlevels (Kruger and Egenhofer, 2006), while compliance monitoring was respon­\\nsible for 69% of transaction costs for German companies in the European Union \\nCO2 Emission Trading Scheme (Heindl, 2012). The existence of many small and \\nmedium-­\\nsized polluters could seriously attenuate available resources, even in \\ndeveloped countries where the rule of law is generally well established. Due to \\nthe significant economy of scale, large point sources generally have lower com­\\npliance monitoring costs on a per-­\\nton-­\\nemission basis and are often prioritized \\n(Heindl, 2012; Gray and Deily, 1996). Because of China’s sheer size, the large \\nsystem involves many personnel and occupies substantial resources. In the 12th \\nFive-­\\nYear Plan (2011–2015) alone, the Chinese government planned to invest \\n40 billion RMB (~US$5.9 billion) to enhance related environmental regulation \\ncapacity (MEP, 2013).\\n\\n\\n120  Policy implementation\\nThe second challenge is intentional data manipulation. Environmental moni­\\ntoring and reporting in China generally must pass through, and be inspected by, \\npolluting firms and various levels of local governments and relevant agencies \\nbefore reaching the central government. Most environmental compliance capaci­\\nties, such as personnel and governmental expenditure, are in local governments, \\nwhile the central government is mainly in charge of policy making. Emissions \\nof CO2, SO2 and NOx are generally calculated via bottom-­\\nup energy consump­\\ntion data and emission factors (Liu et al., 2015; Lu et al., 2011; Zhang et al., \\n2007). This approach is often subject to the influence of intentional distortions \\nfor the interest of stakeholders along the path (Tsinghua University, 2010). China \\nhas been exerting increasingly high pressure on local governments and energy-­\\nintensive firms to achieve top-­\\ndown energy and emission control goals from the \\ncentral government (Xu, 2011b). In comparison to the technologically challeng­\\ning, economically expensive and politically difficult tasks of actual mitigation, it \\nwould be much more convenient to twist the reported numbers (Jin et al., 2016).\\nThe objective resource constraint and the intentional data manipulation could \\nseriously compromise data quality and thus the effectiveness of environmen­\\ntal compliance monitoring. Facing immense pressure of environmental crises, \\nthe Chinese government has been actively searching for potential solutions for \\nenhancing environmental data quality.\\n4.1  \\u0007\\nModel construction\\nIn order to understand China’s environmental compliance monitoring in greater \\ndepth, a conceptual, computable model is constructed to simulate the evolution \\nof compliance rates under different compliance monitoring strategies and how \\ninfluential factors in three categories – pollution abatement costs, noncompliance \\npenalty and, most important, compliance monitoring effectiveness – affect com­\\npliance decisions of polluters and thus the compliance rate. Mathematical details \\nof the model are provided in the Appendix to this chapter.\\nThis model stands on the shoulders of two pieces of research literature for cre­\\nating a theoretical framework. The first well-­\\ndeveloped economics literature of \\ncrime and punishment understands crimes as rational choices. Whether a pol­\\nluter chooses compliance or noncompliance is based on comparing related costs \\nand benefits (Polinsky and Shavell, 2000; Becker, 1968; Glaeser, 1999; Xu, \\n2011a; Shimshack, 2014; Levitt, 2004). If a polluter pondered not complying \\nwith an environmental regulation, pollution abatement costs could be saved as its \\nexpected benefits. However, such behavior would incur expected costs, which is a \\nproduct of (1) penalty on noncompliance and (2) the probability of being caught. \\nRisk-­\\nneutral rational polluters would choose environmental noncompliance if the \\nexpected benefits were greater than the expected costs. The compliance or non­\\ncompliance decision is assumed to be deliberate but not at random. The second \\nmature literature, or a series of related literature, such as on policing, pollution \\ncontrol and tax evasion, examines how to enhance the probability of catching non­\\ncompliance. Compliance monitoring could apply various strategies for enhancing \\n\\n\\nPolicy implementation  121\\nthe probability with a given amount of resources, although the effectiveness is \\nmixed. Levitt (2004) found that policing strategies are of only minor signifi­\\ncance, while the number of police may explain a large proportion of the crime rate \\nchange. For tax compliance, endogenous audit selection rules screen taxpayers \\nfor potential auditing, but the impacts on compliance are mixed (Konrad et al., \\n2017; Vossler and Gilpatric, 2018). In epidemiology, strategies are developed to \\npromote public health and enhance the rate of finding sick patients at early stages \\namong a population (Bonita et al., 2006). A population would be first screened, \\nand those with positive results would have to go through another round of more \\ncareful diagnosing for confirming whether they were true or false positive.\\nThese two pieces of literature are integrated together in this study to simulate \\nenvironmental compliance decisions. Two environmental compliance monitoring \\nsystems are proposed and simulated, as illustrated in Figure 6.2. The conventional \\nsystem that is based on monitoring, reporting and verification is simplified to \\nrequire governmental compliance monitoring resources primarily for site inspec­\\ntion. Adopting the terminology in epidemiology, the model refers to these activi­\\nties as diagnosing. If a polluter were caught as being noncompliant, a penalty \\nwould be issued. The new compliance monitoring system inserts an additional \\nstep before diagnosing to actively screen polluters into high-­\\nrisk and low-­\\nrisk \\ngroups, with higher and lower probabilities of being noncompliant, respectively. \\nDiagnosing with higher costs follows with site inspections or other more accurate \\nmeans to confirm noncompliance only in the high-­\\nrisk group. For the convenience \\nPolluters in compliance and noncompliance\\nScreening: cheap but more errors \\nHigh-risk group\\nLow-risk group\\nDiagnosing: expensive but accurate\\nPenalty\\nNo penalty\\nPolluters making compliance decisions\\nCompliance \\nmonitoring \\nresources\\nScreening: c\\nHigh-risk grou\\nDiagnosing: expensive but accurate\\nPenalty\\nCompliance \\nmonitoring\\nresources\\nFigure 6.2  \\u0007\\nA conceptual model of environmental compliance monitoring\\nNote: The dash-line arrows indicate the screening system’s flow, while the diagonal-pattern arrows \\nrefer to the diagnosing system’s flow. Their major difference is the existence/absence of the screen­\\ning step with screening technologies. The gray boxes show compliance monitoring resources that not \\nonly are allocated between screening and diagnosing technologies in the screening system but only to \\ndiagnosing technologies in the diagnosing system.\\n\\n\\n122  Policy implementation\\nof discussion, the conventional system is referred to in this chapter as the diagnos­\\ning system, while the new system contains both screening and diagnosing, and it \\nwill be called the screening system. Numerous studies have applied the economic \\nmodel of crime and punishment for understanding environmental noncompliance \\n(Xu, 2011a; Shimshack, 2014; Guo et  al., 2014). The compliance monitoring \\nstrategy with screening has also been widely applied in multiple fields (Konrad \\net al., 2017; Vossler and Gilpatric, 2018; Bonita et al., 2006).\\n4.2  \\u0007\\nStrengthening the conventional diagnosing system\\nChina has made several prominent improvements in monitoring and site inspec­\\ntion to address the previously mentioned two challenges for enhancing the prob­\\nability of catching the nonoperation of SO2 scrubbers. First, more resources were \\nmade available for environmental compliance monitoring. The numbers of gov­\\nernment employees at all levels increased from 46,984 in 2005 to 52,944 in 2009 \\nand 61,668 in 2015 for environmental monitoring and from 50,040 in 2005 to \\n60,896 in 2009 and 66,379 in 2015 for inspection (Figure 3.1). Although still lim­\\nited, the personnel resources had already been enough to have an intensive focus \\non SO2 scrubbers in coal-­\\nfired power plants. Particularly, only 503 coal-­\\nfired \\npower plants housed 461 GW SO2 scrubbers (1,264 systems) at the end of 2009, \\nand the largest 300 had a total capacity share of 82% (Ministry of Environmental \\nProtection, 2010a). In 2013, 282 coal-­\\nfired power plants that were at or greater \\nthan 1 GW each had 470 GW SO2 scrubbers in total, or 62.3% of all (Ministry of \\nEnvironmental Protection, 2014). Government personnel are sufficient to follow \\nthese large plants closely and conduct inspections frequently.\\nThe number of polluting sources (N) that require compliance monitoring varies \\ndramatically, depending on focused polluter sizes, pollutants and other features. \\nChina conducted the first census of polluting sources with the census date being \\nDecember 31, 2007, and pollution information for 2007, covering 5,925,576 pol­\\nluting sources, including 1,575,504 industrial, 2,899,638 agricultural, 1,445,644 \\ndomestic and 4,790 centralized pollution control facilities (Ministry of Environ­\\nmental Protection et al., 2010). In comparison, China’s annual environmental sta­\\ntistics report focused on about one tenth of the polluting sources, being 161,598 \\nindustrial sources, 131,837 farms and 7,578 districts for animal husbandry and \\n6,910 water treatment plants, 2,315 municipal waste treatment facilities and 866 \\nhazardous waste treatment facilities in 2015 (Ministry of Environmental Protec­\\ntion, 2002–2016). Among these sources, 68,121 polluting sources were under spe­\\ncial supervisory monitoring (Ministry of Environmental Protection, 2002–2016).\\nFurthermore, in order to make the conventional diagnosing system more effi­\\ncient, CEMSs have become critical to monitor the operation of SO2 scrubbers \\nespecially since 2007 (NDRC and SEPA, 2007b). Six plants (all in Table  6.1 \\nexcept Plant 2) allowed me to read the computer screens of their CEMSs. The val­\\nues of SO2 concentrations changed continuously, and different data were generally \\nconsistent. Many CEMSs and SO2 scrubbers had been inspected once or twice \\na month. Because CEMSs transmitted data online and in real time, inspections \\n\\n\\nPolicy implementation  123\\noften followed abnormal data reporting. Coal-­\\nfired power plants were informed \\nin advance of some inspections, but in many other cases, inspections were unan­\\nnounced. Inspectors had the right to enter coal-­\\nfired power plants without being \\ndelayed. In the plants that I visited, inspection vehicles generally needed just a \\nfew minutes to drive from the gates to the sites where the SO2 scrubbers were \\ninstalled. China was actively building up its site inspection capacity. The num­\\nber of government inspectors at all levels increased steadily (Figure 3.1). China \\nfocused on monitoring and inspection in its efforts to build capacity. During the \\nperiod between 2006 and 2008, the two functions accounted for 85% of govern­\\nment personnel growth for environmental protection (Ministry of Environmental \\nProtection, 2006–2009).\\nBecause of the concern about their data accuracy and reliability, as discovered \\nin my interviews, CEMSs were not the only data source to track the operation of \\nSO2 scrubbers. Other relevant data were collected, including operation and main­\\ntenance records, load factors of electricity generation, sulfur contents of coal, the \\nconsumption of limestone and other reagents, electricity consumption, the han­\\ndling of products from SO2 scrubbers, the opening and closure of bypass dampers \\nand records of accidents and responses (NDRC and SEPA, 2007b; SEPA, 2007). \\nSO2 concentration in the inlet flue gas corresponds to the sulfur contents within a \\nfairly predictable range. The load factors of electricity generation decide the flow \\nrate of the flue gas and can check direct measurement with CEMSs. The factors \\ntogether determine the sulfur load to an SO2 scrubber system. For wet scrubbers \\nusing limestone as the reagent, the molar ratio between CaCO3 and SO2 is nor­\\nmally quite stable at approximately 1.02 to 1.05 (Ministry of Environmental Pro­\\ntection, 2010b). Then the sulfur load would decide the consumption of limestone \\nand the production of gypsum. The managers of coal-­\\nfired power plants were \\nasked to keep the receipts of limestone purchases, and cheating on receipts was \\nconsidered financial fraud, with harsh penalties on those responsible. Electricity \\nis another important input to operate SO2 scrubbers. Because all data should be \\nconsistent with each other, it became more difficult to cheat.\\nThe problem of collusion appeared under control. Data from CEMSs were sent \\nto more than one agency, including environmental protection bureaus and elec­\\ntric grid corporations. Authorities at China’s four government levels – central, \\nprovincial, prefectural and county – all inspected SO2 scrubbers. The multiplicity \\nof inspection authorities effectively diminished the opportunities of collusion. In \\naddition, the pressure to achieve the 10% reduction goal of SO2 emissions in the \\n11th Five-­\\nYear Plan reduced incentives to collude.\\n4.3  \\u0007\\nBuilding the screening system with big data\\nThe preceding measures to strengthen the diagnosing system indeed worked, \\nbut for achieving an even deeper reduction of SO2 emissions, China faces much \\nmore daunting problems in dealing with smaller polluting sources that are a few \\norders of magnitude greater in numbers. New opportunities are emerging with \\nnewly emerged environmental compliance monitoring technologies (Kitchin, \\n\\n\\n124  Policy implementation\\n2014), which are evolving rapidly in terms of effectiveness in catching noncom­\\npliance and efficiency in utilizing compliance monitoring resources. For example, \\nCEMSs played a central role in the U.S. Acid Rain Program as well as the Euro­\\npean Union Emission Trading Scheme (The U.S. Congress, 1990; Stranlund and \\nChavez, 2000; European Commission, 2012). Remote-­\\nsensing technologies using \\nsatellites could provide large-­\\nscale spatial coverage of multiple pollutants (Streets \\net al., 2013). The measurement extends to areas beyond the current monitoring \\nnetwork, although the spatial resolution is coarse (Streets et al., 2013). Social \\nmedia and the prevalent use of smartphones have greatly facilitated and strength­\\nened the power of the civil society in monitoring environmental pollution and \\ncompliance (Stevens and Ochab, 2010; Kay et al., 2015). Various types of sensors, \\nin addition to novel carriers such as unmanned aerial vehicles, have been more \\nand more widely adopted to measure pollution levels (Snyder et al., 2013; Wang \\nand Brauer, 2014).\\nChina has been actively seeking opportunities in big data that can be applied for \\nenvironmental protection. In 2015, State Council formally issued the Action Out­\\nline for Promoting Big Data Development to encourage the wide integration of \\nbig data in governance (State Council, 2015). In 2016, the then Ministry of Envi­\\nronmental Protection enacted the Comprehensive Plan on Ecological and Envi­\\nronmental Big Data Construction (Ministry of Environmental Protection, 2016a). \\nIt listed a comprehensive plan on how big data could be collected, integrated, \\ndeveloped and applied for environmental compliance monitoring, enforcement \\nand management.\\nThese new compliance monitoring technologies shed light on new solutions to \\nthe old challenges. First, in addressing the compliance monitoring resource con­\\nstraint, these technologies could potentially provide a relatively low-­\\ncost means \\nto monitor polluting sources. For example, although one satellite observing the \\nEarth’s CO2 and air quality could cost a few hundred million U.S. dollars, such as \\nthe OCO-­\\n2 satellite for CO2 monitoring by the National Aeronautical and Space \\nAdministration with a price tag of US$465 million, its wide spatial and regular \\ncoverage would substantially reduce the average and, especially, marginal costs \\nfor one observation (Wall, July 2, 2014; Osterman et al., 2018). Second, many of \\nthese technologies could circumvent various levels of local governments and pol­\\nluting sources to provide top-­\\ndown, external and objective data without subjective \\ndistortions. They are originated from entirely different external sources, not inter­\\nnal reporting. Satellite or remote-­\\nsensing data could be gathered in a centralized \\nmanner without the direct involvement of local governments or polluting sources \\nthemselves.\\nNevertheless, these new technologies also have a critical weakness. Most of \\nthem generally have not reached the minimum accuracy requirements to legally \\nor administratively punish polluters, while conventional technologies currently \\nin application (although not all) could fulfill the requirements if intentional data \\nmanipulation is effectively deterred. Remote-­\\nsensing data have been successfully \\napplied in China to examine the impacts of environmental policies on pollutant \\nemissions from coal-­\\nfired power plants, but the accuracy has not been adequate \\n\\n\\nPolicy implementation  125\\nto justify their direct application in legally determining the compliance status of \\nindividual polluting firms (Zhang et al., 2009; Li et al., 2010).\\nThe trade-­\\noffs between conventional and new technologies indicate that the \\nlatter cannot completely replace the former at their current stage, but their clear \\nadvantages in costs (and objectiveness) are crucial considerations for China’s \\nongoing reform on the conventional diagnosing system to deeply integrate big \\ndata and other technologies. Section 4.4 mainly focuses on how this reform may \\nachieve better efficiency and effectiveness in environmental compliance monitor­\\ning. Different technologies are recognized to have different features mainly from \\ncost and accuracy perspectives. Their weaknesses and strengths could comple­\\nment each other for building a better system than any individual category of tech­\\nnologies can do alone.\\n4.4  \\u0007\\nComparing diagnosing and screening systems\\nEnvironmental compliance rates are simulated with empirically defined param­\\neters as discussed in the Appendix to this chapter. This subsection discusses the \\nmodel simulation and sensitivity analysis results. If any input parameter is not \\ntargeted in a simulation, it will adopt the empirical value as specified in the current \\nscenario as summarized in Table 6.3.\\nCompliance rates (1−M t) in the screening system depend on their initial levels \\n(1\\n0\\n−M ; Figure 6.3). For example, if initially with 40,000 inspection staff, the \\nscreening system results in two equilibrium compliance rates (1−M *) after sev­\\neral time steps, about 27% (a very low compliance rate) and 100% (full compli­\\nance; Figure 6.3). An equilibrium state is defined as, given the empirical values \\nof parameters, the compliance rate remains stable over time and swings back if \\na small disturbance happens (Table 6.3). When the initial compliance rates are \\nabove a certain level, the final equilibrium compliance rates tend to converge \\nto a high level close to full compliance. However, when the initial compliance \\nrates are below that level, the available resources would not be adequate to catch \\nenough noncompliance cases. Noncompliance will become the dominant choice \\nof rational polluters, or the compliance monitoring system falls into a noncompli­\\nance trap due to its equilibrium status. The following simulations of the screen­\\ning system will primarily report equilibrium compliance rates. In contrast, the \\ndiagnosing system demonstrates no memory. Its compliance rates at each time-­\\nstep (1−M t) have no relationship with the initial or proceeding levels (1\\n0\\n−M  and \\n1\\n1\\n−\\n−\\nM t ). They are decided only by immediately available compliance monitoring \\nresources (Rt; Figure 6.3).\\nThe relative effectiveness of the diagnosing and screening systems in enhanc­\\ning compliance rates depends heavily on resource availability (Rt; Figure 6.4). \\nWhen resources were too scarce (e.g., less than 30,000 inspection staff or half of \\nChina’s available personnel in 2015), neither system would be able to result in \\nhigh-­\\ncompliance statuses, although the diagnosing system could achieve slightly \\nbetter outcomes. When resources were abundant (more than 130,000 inspection \\nstaff or doubling the available personnel in 2015), either system would lead to \\n\\n\\n126 Policy implementation\\nSimulation\\n6.4\\n 6.3\\n \\n 6.5(a)\\n6.5(b)\\nFigure\\nFigure\\nFigure\\n \\nFigure\\nEmpirical ranges in the model \\nunder special supervisory monitoring \\n \\nin 2015 (Ministry of Environmental \\nProtection, 2002–2016) to 5,925,576 \\nC\\n) \\ns from 0% (full compliance\\ns first census of polluting \\nsimulation\\nto 100% (complete noncompliance), \\nwhich covers the full range of possible \\ncompliance rates\\nnumber of inspection staff at the \\nto 185,108 (the total number of \\nenvironmental officials at all levels \\n; \\n varie\\n0\\ncentral and provincial levels in 2015) \\nfor administration, inspection and \\nmonitoring in 2015; Ministry of \\nProtection, 2002–2016)\\nEnvironmental \\nin China’\\nsources with the census date being \\nal., 2010)\\n scrubbers, \\n1a; \\n1.6 (very \\n31, 2007 (Ministry of \\n \\n; in the 2007 \\nP\\n2\\n [Xu, 201\\nP\\nC\\nA, 2007b]) to \\n 60% higher than \\nfor operating SO\\ns shale-gas development, the \\nEnvironmental Protection et\\nNDRC and SEP\\nC\\n \\n with \\nin China’\\n was significantly lower than \\n al., 2014])\\nDecember\\nregulation \\n was five times of \\nlenient P\\nP\\nP\\nthen \\n[Guo et\\nM\\nFrom 1,959 inspection staff (the total \\nFrom 68,121 polluting sources that were \\nFrom 0.1 (very harsh \\n2018)\\ns \\n, is \\nEmpirical values in the current \\n0\\nM\\nscenario\\npoint of the full possible range \\nbetween 0% and 100%.\\n66,379 inspection staff (in 2015; \\nMinistry of Environmental \\nProtection, 2002–2016), within \\nwhich 46,800, or 70.5%, were \\nenvironmental inspectors (in 2017) \\nas in the “double randomness, one \\npublicization” databases (Ministry \\nof Ecology and Environment, \\n809,500 polluters under compliance \\nmonitoring as in the “double \\nrandomness, one publicization” \\ndatabases (Ministry of Ecology and \\nKey parameters in the model and their empirical values\\nInitial noncompliance rate, \\nassumed to be 50% as the middle \\nEnvironment, 2018)\\n is assumed to be 1.5 times \\nP\\n2/3 (\\nof the pollution abatement costs, \\nbeing a middle ground in China’\\nempirical cases as introduced in the \\ncell to the right)\\n \\n; \\n \\nNoncompliance rate (%) at time-step t\\nthe corresponding compliance rate is\\n \\n. Equilibrium noncompliance\\n, is defined as the level when\\nWhen it \\notal available resources for \\ncompliance monitoring at the time-\\n, which could be allocated \\nbetween screening and diagnosing, \\n can be changed \\nexogenously at a time step. \\n.\\n=\\nt\\nR\\nR\\n.\\n0 0\\n. %\\nt\\nR\\n. \\n: the penalty on \\n1\\nP\\n−\\nt\\nd\\n*\\nR\\nt\\nM\\nM\\nrate, \\nt\\nt\\n−\\n=\\nM\\nM\\nt\\n and \\n1 − \\nstep \\nt\\nRs\\nremains a constant: \\n \\nThe number of polluting sources \\nunder compliance monitoring\\n pollution abatement costs (US$/\\nsources; \\nT\\nC:\\nton), which vary across polluting \\nnoncompliance (US$/ton), which \\nis assumed to be fixed for every \\npunished polluting source.\\nR\\nt\\nTable 6.3\\nParameters\\nt\\n or \\nM\\nR\\nN\\nC\\nP\\n\\n\\nPolicy implementation 127\\n(b)\\n(d)\\n& \\n6.5(d)\\n \\n 6.5(c)\\n \\n6.6(a)\\n6.6(c) & \\nFigure\\nFigure\\n \\n \\nFigure\\nFigure\\nThe impacts of a lognormal distribution \\nare also simulated, due to the lack of \\nactual information.\\nDue to inadequate information, the \\nined with a full \\n, is exam\\ns\\nd\\nr\\nr\\nratio, \\npossible range from 1% to 100%. By \\ndefinition, screening technologies \\nmust be cheaper than diagnosing \\ntechnologies. Otherwise, the latter will \\nbe better from both cost and accuracy \\nperspectives to make the former \\nobsolete.\\nDue to inadequate information, a full \\nrange, 0%~100%, is examined.\\nDue to inadequate information, a full \\nrange, 0%~100%, is examined.\\n normal distribution is assumed with \\na standard deviation of 0.33.\\n-year per \\n is assumed to be \\n : 0.074 inspector\\ninspection (see text for empirical \\ns\\nd\\nr\\nr\\n is equivalently 0.0074 \\nestimation); \\n.\\n.\\ns\\n-year per inspection.\\n, the corresponding \\n10%, or r\\n, the corresponding \\ninspector\\n1d\\n and \\nprobabilities for screening and \\nrespectively\\n2d\\nK\\nK\\n and \\n1s\\ndiagnosing technologies, are \\nassumed to be 90% and 99%, \\n2s\\nprobabilities for screening and \\ndiagnosing technologies, are \\nassumed to be 70% and 90%, \\nrespectively\\nA\\nd\\nr\\nK\\nK\\nC\\nP\\n \\nCumulative distribution function of \\ns\\nr\\nvely), which are \\n1\\nRequired resources to screen and \\n polluting source (\\n-\\n1\\nK\\nype \\n : (T\\n1\\nK2\\n-\\none\\n, respecti\\nerror) the probability that \\ndiagnose \\nr\\nassumed to remain unchanged over \\nd\\nand \\ntime\\nThe probability (%) that one \\ntechnology recognizes compliant \\ncases as being compliant; \\nype I \\n: (T\\ncompliant cases are recognized as \\nbeing noncompliant.\\nThe probability (%) that one \\ntechnology recognizes \\nnoncompliant cases as being \\nnoncompliant; \\nII error) the probability that \\nnoncompliant cases are recognized \\nas being compliant\\n•\\n( )\\n1\\n2\\nΦ\\nr\\nK\\nK\\n\\n\\n128  Policy implementation\\n0\\n10,000\\n20,000\\n30,000\\n40,000\\n50,000\\n60,000\\n70,000\\n0%\\n10%\\n20%\\n30%\\n40%\\n50%\\n60%\\n70%\\n80%\\n90%\\n100%\\n0\\n5\\n10\\n15\\n20\\n25\\n30\\n35\\n40\\n45\\n50\\nInspection staff\\ne\\nt\\na\\nr\\n \\ne\\nc\\nn\\na\\ni\\nl\\np\\nm\\no\\nC\\nTime step\\nDiagnosing system\\nScreening system\\nCampaign\\nAvailable inspection\\nstaff (right)\\nShock\\nFigure 6.3  \\u0007\\nModel simulation of compliance rates (1−M t) in the diagnosing and screen­\\ning systems with available compliance monitoring resources (i.e., exogenously \\ndetermined number of inspection staff in the dashed curve, Rt) and initial com­\\npliance rates (1\\n0\\n−M , from 0% to 100%)\\nNote: After compliance rates reach equilibrium levels (1\\n1\\n1\\n0\\n−\\n−\\n−\\nM\\nM\\nM t\\n*\\n), a hypothetical envi­\\nronmental campaign (temporarily with more inspection staff) is exogenously triggered to run for three \\ntime-steps and a hypothetical shock (temporarily with fewer inspection staff) for two time-steps. Their \\nperiods are indicated alongside the dashed curve. All other model parameters adopt the empirical \\nvalues in the current scenario in Table 6.3.\\n0%\\n10%\\n20%\\n30%\\n40%\\n50%\\n60%\\n70%\\n80%\\n90%\\n100%\\n0\\n20,000\\n40,000\\n60,000\\n80,000\\n100,000\\n120,000\\n140,000\\ns\\ne\\nt\\na\\nr\\n \\ne\\nc\\nn\\na\\ni\\nl\\np\\nm\\no\\nc\\n \\nm\\nu\\ni\\nr\\nb\\ni\\nl\\ni\\nu\\nq\\nE\\nInspection staff\\nScreening system\\nDiagnosing system\\nFigure 6.4  \\u0007\\nModel simulation of equilibrium compliance rates (1−M *) in the screening and \\ndiagnosing systems in relation to available inspection staff (R)\\n\\n\\nPolicy implementation 129\\nnearly full compliance and strategies would not matter much. Most situations in \\nthe real world, including China in 2015 with 66,379 inspection staff, should fall \\nin between: resources are constrained but neither unlimited nor depleted. In these \\nsituations, the two systems would diverge away from each other and the screening \\nsystem could use available resources much more efficiently to achieve signifi-\\ncantly higher compliance rates (Figure 6.4).\\nThe number of polluters (N) matters greatly for the relative performance of \\nthe two compliance monitoring systems. With 66,379 environmental inspection \\nstaff in the current scenario, the screening system shows significantly higher \\ncompliance rates than the diagnosing system when the number of polluters is \\nbetween 0.5 million to about 1.2 million (Figure 6.5(a)). Both systems could \\neffectively handle fewer than 0.5 million polluters for their nearly full compli-\\nance, while neither system could be up for the job with more than 1.2 million \\npolluters. As discussed in the Appendix at the end of this chapter, the polluting \\nsources under the central government’s special supervisory monitoring, gener-\\nally large or hazardous polluters, were 68,121 in 2015. The currently available \\ninspection staff would be of little resource constraint to achieve their general \\nenvironmental compliance, as in China’s current situation. The “double ran-\\ndomness, one publicization” scheme covered 809,500 polluters, for which the \\nscreening system with nearly full compliance tends to have a great advantage \\nover the diagnosing system with only about half of polluters under compliance. \\nIf compliance monitoring does not differentiate the 5,925,576 polluting sources \\nin the 2007 census, the overall compliance rate would be very low, being less \\nthan 5%. As in the Chinese practice, compliance monitoring should strategically \\nallocate resources to those bigger and more severe polluters. Otherwise, the \\nsystem would be overwhelmed. From another perspective, the model simulation \\nalso indicates that small polluters have significantly low environmental compli-\\nance rates.\\nAs enlightened in the economic theory of crime and punishment, a penalty \\ncould enhance compliance rates in a similar way as compliance monitoring. When \\nC\\nthe penalty level is ten times of the pollution abatement costs (i.e., \\n being 0.1), \\nP\\nboth the screening and the diagnosing systems could yield nearly full compli-\\nance (Figure 6.5(b)). For example, in ensuring the normal operation of SO2 scrub-\\nbers, the penalty for noncompliance was five times the pollution abatement costs \\nC\\n(i.e., \\n being 0.2; Xu, 2011a). China’s compliance monitoring system was closer \\nP\\nto the diagnosing system, but it still effectively brought coal-fired \\n \\npower plants \\nunder prevalent compliance as projected by the model (Figure 6.5(b); Xu, 2011a). \\nC\\nWhen the penalty level barely catches up with the abatement costs (i.e., \\n  > 1), \\nP\\nneither system would work although the screening system performs even worse \\n(Figure 6.5(b)). This was the case in China’s early days in dealing with water pol-\\nlution in shale-gas development (Guo et\\n \\n al., 2014).\\nA deviation of the statistical distribution of the cost/penalty ratio (Φ( )\\n• ) \\ndoes not seem to cause much difference for the earlier simulation results \\n\\n\\n130 Policy implementation\\nFigure 6.5  \\nModel simulation of equilibrium compliance rates (1-M *) in the screening \\nand diagnosing systems in relation to (a) the number of polluters (N); (b) the \\n \\nC \\nratios between pollution abatement costs and noncompliance penalty \\n\\n\\n; \\n\\n\\nP \\n\\n\\n(c) available inspection staff (R), where the pollution abatement cost-to-non-\\nC \\ncompliance penalty ratio \\n\\n\\n has a lognormal distribution (Φ( )\\n• ); and (d) the \\n\\n\\nP \\n\\n\\nr \\nrelative resource intensity of screening and diagnosing technologies \\ns \\n\\n\\n\\n\\nr\\nd \\n\\n\\n0%\\n20%\\n40%\\n60%\\n80%\\n100%\\n0\\n500,000\\n1,000,000\\n1,500,000\\n2,000,000\\n2,500,000\\ns\\ne\\nt\\na\\nr\\ne\\nc\\nn\\na\\ni\\nl\\np\\nm\\no\\nc\\nm\\nu\\ni\\nr\\nb\\ni\\nl\\ni\\nu\\nq\\nE\\nNumber of polluters\\n0%\\n20%\\n40%\\n60%\\n80%\\n100%\\n0.0\\n0.2\\n0.4\\n0.6\\n0.8\\n1.0\\n1.2\\n1.4\\n1.6\\n \\ns\\ne\\nt\\na\\nr\\n \\ne\\nc\\nn\\na\\ni\\nl\\np\\nm\\no\\nc\\n \\nm\\nu\\ni\\nr\\nb\\ni\\nl\\ni\\nu\\nq\\nE\\nPollution abatement costs to noncompliance penalty ratio\\n(a)\\n(b)\\n\\n\\nPolicy implementation 131\\n0%\\n20%\\n40%\\n60%\\n80%\\n100%\\n0\\n20,000\\n40,000\\n60,000\\n80,000\\n100,000\\n120,000\\n140,000\\n \\ns\\ne\\nt\\na\\nr\\n \\ne\\nc\\nn\\na\\ni\\nl\\np\\nm\\no\\nc\\n \\nm\\nu\\ni\\nr\\nb\\ni\\nl\\ni\\nu\\nq\\nE\\nInspection staff\\n0%\\n20%\\n40%\\n60%\\n80%\\n100%\\n0%\\n10%\\n20%\\n30%\\n40%\\n50%\\n \\ns\\ne\\nt\\na\\nr\\n \\ne\\nc\\nn\\na\\ni\\nl\\np\\nm\\no\\nc\\n \\nm\\nu\\ni\\nr\\nb\\ni\\nl\\ni\\nu\\nq\\nE\\nDiagnosing system\\nScreening system\\nUnit cost ratio: screening vs diagnosing technologies\\n(c)\\n(d)\\nFigure 6.5 (Continued)\\n(Figure 6.5(c)). When the pollution abatement cost-to-\\n \\n \\nnoncompliance penalty \\n\\nratio C \\n is assumed to have a lognormal distribution, the relationship between \\n\\n\\n\\nP \\n\\n\\n\\navailable inspection staff and equilibrium compliance rates is similar to the situ-\\nation earlier (Figure 6.5(c)).\\n\\n\\n132  Policy implementation\\nScreening technologies should be carefully selected. Otherwise, the screening \\nsystem would not yield higher compliance rates than the diagnosing system. The \\nlow costs of a screening technology to monitor one polluting source ( rs ) is crucial \\nfor its better performance (Figure 6.5(d)). It should be no less than 65% cheaper \\nthan a diagnosing technology (r\\nd  ; Figure 6.5(d)). Furthermore, in terms of accu­\\nracy, compliance monitoring technologies for screening and diagnosing have dis­\\ntinctly different requirements on their Type I and II errors. Screening technologies \\nshould make fewer Type I errors in wrongly recognizing compliant cases into the \\nhigh-­\\nrisk group (K1s should be generally above 60%; Figure 6.6(a)), while diag­\\nnosing technologies should make fewer Type II errors in wrongly recognizing \\nnoncompliant cases as being compliant for them to evade penalties (K2d must be \\ngenerally above 60%; Figure 6.6(d)). The requirements on the other two accuracy \\nindicators are much more relaxed. Screening technologies should not put more \\nthan 80% of noncompliant cases into the low-­\\nrisk group (K2s must be generally \\nabove 20%; Figure 6.6(c)). The probability of a diagnosing technology to recog­\\nnize compliant cases as being compliant seems to matter little (K1d; Figure 6.6(b)). \\nAlthough this model assumes only two compliance statuses of a polluter, being \\ncompliant or noncompliant, polluters do differ in terms of the noncompliance \\nseverity. In the terminology of this model, compliance monitoring technologies \\nshould inherently have thresholds on whether to recognize a polluter as being \\ncompliant or not. The preceding accuracy indicators, especially K2s and K2d, also \\nreflect such thresholds. Accordingly, screening technologies only need to catch \\nthose more severe noncompliant cases or with strong noncompliant signals (due \\nto the relaxed requirement of K2s) while diagnosing technologies must convict \\nmost of these severe noncompliant polluters (K2d). These results could serve as \\nthe guideline for assessing and selecting screening and diagnosing technologies.\\nOverall, the screening system in general does show significantly better perfor­\\nmance than the diagnosing system to achieve higher compliance rates. Depend­\\ning on initial compliance rates and available resources, compliance rates in the \\nscreening system may evolve into two equilibrium levels, being at nearly full \\ncompliance and prevalent noncompliance. At the 2015 level of inspection staff in \\nChina, the screening system would be able to yield nearly full compliance for the \\n809,500 polluting sources as covered under the “double randomness, one publi­\\ncization” scheme. However, the diagnosing system that is closer to reality would \\nonly bring about half of those polluters under compliance.\\n4.5  \\u0007\\nResilience of screening and diagnosing systems\\nCampaigns or movements (yundong) are widely used in China’s governance. In \\norder to achieve a highly prioritized goal within a short time, the government may \\nintensively reallocate unusual amounts of human, financial or political resources \\nfor certain tasks. These resources are usually “borrowed” from other agencies or \\nfunctions and thus must be “returned” after campaigns conclude. Examples include \\nanticrime campaigns, especially “strike hard” (Trevaskes, 2010); anticorruption \\ncampaigns (Wedeman, 2005); and environmental campaigns (Jahiel, 1998; van \\n\\n\\nPolicy implementation  133\\nFigure 6.6  \\u0007\\nModel simulation of equilibrium compliance rates (1−M *) in the screening \\nand diagnosing systems in relation to the probabilities that (a) the screening \\ntechnology recognizes compliance cases as being compliant (K1s), (b) the diag­\\nnosing technology recognizes compliance cases as being compliant (K1d), (c) the \\nscreening technology recognizes noncompliance cases as being noncompliant \\n(K2s) and (d) the diagnosing technology recognizes noncompliance cases as \\nbeing noncompliant (K2d)\\n0%\\n20%\\n40%\\n60%\\n80%\\n100%\\n40%\\n50%\\n60%\\n70%\\n80%\\n90%\\n \\ns\\ne\\nt\\na\\nr\\n \\ne\\nc\\nn\\na\\ni\\nl\\np\\nm\\no\\nc\\n \\nm\\nu\\ni\\nr\\nb\\ni\\nl\\ni\\nu\\nq\\nE\\nProbability (K1s) \\n0%\\n20%\\n40%\\n60%\\n80%\\n100%\\n0%\\n20%\\n40%\\n60%\\n80%\\n100%\\ns\\ne\\nt\\na\\nr\\n \\ne\\nc\\nn\\na\\ni\\nl\\np\\nm\\no\\nc\\n \\nm\\nu\\ni\\nr\\nb\\ni\\nl\\ni\\nu\\nq\\nE\\nProbability (K1d)\\n(a)\\n(b)\\n\\n\\n134  Policy implementation\\n0%\\n20%\\n40%\\n60%\\n80%\\n100%\\n10%\\n20%\\n30%\\n40%\\n50%\\n60%\\n70%\\n80%\\n90%\\ns\\ne\\nt\\na\\nr\\n \\ne\\nc\\nn\\na\\ni\\nl\\np\\nm\\no\\nc\\n \\nm\\nu\\ni\\nr\\nb\\ni\\nl\\ni\\nu\\nq\\nE\\nProbability (K 2s)\\n0%\\n20%\\n40%\\n60%\\n80%\\n100%\\n50%\\n60%\\n70%\\n80%\\n90%\\n100%\\ns\\ne\\nt\\na\\nr\\n \\ne\\nc\\nn\\na\\ni\\nl\\np\\nm\\no\\nc\\n \\nm\\nu\\ni\\nr\\nb\\ni\\nl\\ni\\nu\\nq\\nE\\nDiagnosing system\\nScreening system\\nProbability (K2d)\\nFigure 6.6  \\u0007\\n(Continued)\\n(d)\\n(c)\\n\\n\\nPolicy implementation  135\\nRooij, 2006). Opposite to environmental campaigns, compliance monitoring might \\nalso experience shocks as observed in the author’s fieldwork in China, for exam­\\nple, when inspection staff in one region or for one environmental task are tempo­\\nrarily “borrowed” for launching campaigns in another region or for other tasks.\\nCampaigns can achieve rapid progress on the targeted tasks. However, when \\nthe temporarily available resources are retreated, such campaign-­\\nstyle compliance \\nmonitoring and enforcement often fail to reach sustained compliance. One nota­\\nble example of a largely short-­\\nlived environmental enforcement campaign is the \\n“midnight action” for solving the unacceptable water pollution in the Huai River in \\n1997 that shut down about 5,000 small polluting factories (Bai and Shi, 2006; Liu, \\n1998). Improvements were achieved in the short term with significantly reduced \\nwater pollutant emissions and cleaner water quality (Liu, 1998). However, pollu­\\ntion rebounded quickly after the campaign was over (Bai and Shi, 2006).\\nThe compliance monitoring model as constructed in this study provides an under­\\nstanding of the short-­\\nlived impacts of environmental compliance monitoring cam­\\npaigns and shocks in the diagnosing system. The diagnosing system has no memory, \\nand its compliance rate at a given time directly corresponds to the immediately avail­\\nable enforcement resources (Figure 6.3). In contrast, the screening system has a mem­\\nory and this feature suggests that short-­\\nterm environmental campaigns might be more \\nstrategically utilized to establish the screening system for compliance monitoring and \\nachieve high compliance rates. As illustrated in Figure 6.3, although compliance moni­\\ntoring resources are kept at the same level before and after environmental campaigns, \\nthe equilibrium compliance rate will be fundamentally lifted from a low to a high sta­\\ntus. The compliance rate evolution could be explained with the compliance monitoring \\nmodel. Before a campaign starts, the prevalent noncompliance indicates that a great \\nmajority of compliance monitoring resources should be spent in the diagnosing step to \\nconvict polluters. A small proportion of resources will be enough to screen noncompli­\\nant cases for the relatively expensive diagnosing. When the environmental campaign is \\nlaunched, with more and more noncompliant polluters being caught in noncompliance, \\ntheir rational decisions will result in higher compliance rates. Then fewer polluting \\nsources will be screened into the high-­\\nrisk group in the following time-­\\nstep, which \\nrequires less resource for diagnosing. In addition, the simulation also suggests that if \\ntransformed into the screening system, China might reduce the number of environ­\\nmental inspection staff from the current level but still maintain high compliance rates.\\nEnvironmental compliance monitoring shocks have opposite impacts as cam­\\npaigns. A temporary shortage of inspection staff could destabilize high equilibrium \\ncompliance rates back to low levels (Figure 6.3). As explained in the model construc­\\ntion, the compliance rate in the screening system at a time-­\\nstep is only affected by \\nthat in the previous time-­\\nstep. This short memory leads to the screening system’s \\nlimited resilience when facing environmental compliance monitoring shocks.\\nIf compliance rates with a longer past contribute to compliance decisions at a \\ncurrent time-­\\nstep, the screening system of compliance monitoring will become \\nmore resilient. A longer memory shows that environmental campaigns should run \\nlonger for elevating the compliance rate to a higher equilibrium, while temporary \\n\\n\\n136  Policy implementation\\nenvironmental shocks would be less damaging, with the dipped compliance rate \\nquickly rebounding afterward.\\nEnvironmental campaigns with temporary increases in inspection staff or \\nshocks with their temporary reduction could destabilize the equilibrium rates in \\nthe screening system with longer-­\\nterm impacts, while the impacts in the diag­\\nnosing system would be short-­\\nlived as seen in empirical cases. Environmental \\ncampaigns might be especially utilized to pull the system out of a possible non­\\ncompliance trap. 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Policing serious crime in China: From ‘strike hard’ to ‘kill fewer’. \\nLondon and New York: Routledge.\\nTsinghua University. 2010. A study on the management system of environmental pollution \\ndata collection in China. Beijing, China: Tsinghua University Press.\\nThe U.S. Congress. 1990. Clean air act amendments 1990. Washington, DC: The U.S. Congress.\\nThe U.S. EPA. 2007. CEMS cost model. Washington, DC [Online]. Available: www.epa.\\ngov/ttn/emc/cem/cems.xls.\\nVan Rooij, B. 2006. Implementation of Chinese environmental law: Regular enforcement \\nand political campaigns. Development and Change, 37, 57–74.\\nVossler, C. A. & Gilpatric, S. M. 2018. Endogenous audits, uncertainty, and taxpayer assis­\\ntance services: Theory and experiments. Journal of Public Economics, 165, 217–229.\\nWall, M. 2014. NASA launches satellite to monitor carbon dioxide, July 2 [Online]. 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Hangzhou, China: Zhejiang Bureau \\nof Quality and Technical Supervision.\\n\\n\\n­\\nAppendix\\nModeling environmental compliance \\nmonitoring systems\\nKey parameters\\nThis model’s primary output is the compliance rate of polluters under compli-\\nance monitoring: M t is the noncompliance rate at the end of the time-step \\n \\nt, \\nwhile 1-M\\n \\nt is the corresponding compliance rate. For simulating the evolution \\nof compliance rates over time, the model is designed to follow time-steps. In\\n \\n \\neach time-step, \\n \\nenforcement activities are first conducted to comprise compli-\\nance monitoring and penalty on noncompliance. The compliance rate at the end \\nof the previous time-step \\n \\ncould affect the subsequent performance of environ-\\nmental compliance monitoring, that is, the probability of catching noncompli-\\nance. This probability is assumed to be commonly available information for all \\npolluters. Based on the expected penalty and compliance costs, polluters make \\ncompliance decisions to yield an overall compliance rate at the end of the cur-\\nrent time-step.\\nAs listed in Table 6.3, the model has a series of input parameters, whose values \\nare given exogenously. They fall into several major categories: (1) environmental \\ncompliance monitoring system, including initial noncompliance rate (M 0), the \\ntotal available resources for compliance monitoring (Rt) and the number of pol-\\nluting sources (N); (2) the ratio between pollution abatement costs and penalty on \\n\\nnoncompliance C \\n as well as its distribution (\\n\\nΦ\\n\\n( )\\n• ); (3) compliance monitoring \\n\\n\\n\\n\\ntechnologies, including \\nP \\nrequired resources for monitoring one polluting source \\n(r), the probability that one technology recognizes compliant cases as being com-\\npliant (K1) and the probability that one technology recognizes noncompliant cases \\nas being noncompliant (K2). Screening and diagnosing technologies are further \\ndistinguished with subscripts s and d, respectively. The four parameters (K1s, K1d, \\nK2s and K2d) are assumed to be specific for a given compliance monitoring technol-\\nogy and do not change over time and cases. Compliance-monitor\\n \\ning technologies \\nand systems could make two types of errors in identifying noncompliance (Polin-\\nsky and Shavell, 2000; Bonita et al., 2006). We assume H0: a polluter is under \\nenvironmental compliance. A Type I error indicates that a polluting firm is under \\ncompliance, but the environmental compliance monitoring wrongly identifies the \\ncase as noncompliance to mistakenly punish it. A Type II error refers to the situ-\\nation that although a polluter is not complying, the system wrongly recognizes it \\nas being compliant. Accordingly, the illegal polluter walks away without penalty. \\n\\n\\nPolicy implementation 143\\nBoth errors consequently lower the deterrence effect, which might lead to lower \\ncompliance rates.\\nThe diagnosing system\\nIn this diagnosing-only system, the probability \\n \\nof noncompliant polluting sources \\nRt\\nthat are rightfully punished is: \\nd\\n1\\n´\\n´K\\nr\\nN\\n2d, while the probability of compliant \\npolluting sources that are mistakenly punished is \\nd\\nRt\\nd\\n1\\n×\\n×(\\n)\\n1−K\\nr\\nN\\n1d . A polluter \\nRt\\nd\\nRt\\nwill choose compliance when C\\nP\\n+\\n×\\nd\\n1\\n×\\n×(\\n)\\n1−\\n<\\nK\\nP ×\\n×\\nd\\n1\\nd\\n×K\\nr\\nN\\n1\\n2\\nr\\nN\\nd, or \\nC\\nRt\\nd\\nd\\n<\\n×\\nd\\n1 ×\\n+\\n(\\n)\\nK\\nK\\n2\\n1\\nd\\nd −1 . Because all resources are devoted to diagnosing, \\nP\\nr\\nN\\nd\\nR\\nR\\nt =\\nt\\nd. One polluting source could be diagnosed more than once to potentially \\nincur a penalty every time that it is caught noncompliance. Corresponding to \\navailable enforcement resources, the noncompliance rate will be\\nRt\\nM t\\n1\\n=\\n−\\n1\\nΦ(\\n(\\n×\\n× K\\nK\\nr\\nN\\n2\\n1\\nd\\nd\\n+\\n−1)) \\nEquation 6.1\\nd\\nBecause M t is not related to M t-1, the noncompliance rate under the diagnosing \\nsystem will not show dynamic evolution over time when other factors remain \\nunchanged.\\nThe screening system\\nWhen resources are inadequate, some polluting sources may be neither screened \\nnor diagnosed, while the optimal allocation of resources will make sure that \\nall screened-out polluting \\n \\nsources in the high- \\nrisk group are diagnosed and no \\navailable resource is wasted. Due to the existence of Type I and II errors, each \\ngroup contains compliant and noncompliant sources. The high- \\nrisk group in the \\nRt\\ntime-step t will comprise \\ns ×\\n×\\nM\\nK\\nt−1\\n2s noncompliant polluting sources and \\nRt\\nr\\ns\\ns ×\\n−\\n(\\n)\\n1\\n1\\nM\\nK\\nt−1 ×\\n−\\n(\\n)\\n1s  compliant polluting sources. Accordingly, the noncom-\\nr\\npliance rate in the high-\\ns\\nM\\nK\\nt−1\\nrisk group is \\n \\nM t\\n×\\nh =\\n2s\\nt−\\n−\\n1\\nt\\n1\\n.\\nM\\nK\\n×\\n+(\\n)\\n1\\n1\\n−\\n×\\nM\\nK\\n(\\n)\\n−\\nThe low- \\nrisk group will contain all remaining polluting \\n2s\\nsources, including \\n1s\\nthose \\nRt\\nRt\\nscreened out and those not screened, \\nN −\\n×\\ns\\nM\\nK\\nt−\\n−\\n1 ×\\n−\\ns ×\\n−M\\nK\\nt\\n1\\n2s\\n(\\n)\\n1\\n1\\n×\\n−\\n(\\n)\\n1s , \\nr\\ns\\nr\\nRt\\nRt\\nRt\\ns\\nor (\\n)\\nN −\\n+\\ns\\ns ×\\n×\\nM\\nK\\nt−\\n−\\n1\\n(\\n)\\n1\\n1\\n−\\n+\\ns ×\\n−\\n(\\n)\\nM\\nK\\nt\\n1\\n2s\\n×\\n1s. The number of noncom-\\nr\\ns\\nr\\ns\\nr\\ns Rt\\npliant polluting sources is N\\nM\\n×\\n−\\nt−\\n−\\n1\\n1\\ns ×\\n×\\nM\\nK\\nt\\n2s. Then the noncompliance \\nr\\ns\\nRt\\nN\\nM\\n×\\n−\\nt−\\n−\\n1\\n1\\ns ×\\n×\\nM\\nK\\nt\\nr\\n2s\\nrate in the low-risk group is \\n \\nM t =\\ns\\nl\\nRt\\nN\\ns\\nM\\nK\\nt\\n1\\nRt\\n.\\n−\\n×\\n−\\n−\\n×\\n−\\ns\\n2s\\n×\\n−\\n(\\n)\\n1\\nM t\\n1 ×(1−K\\nr\\ns\\nr\\n1s)\\ns\\n­\\n\\n\\n144 Policy implementation\\nAfter diagnosing, the number of noncompliant polluting sources that are \\nRt\\nrightfully punished is \\nd ´\\n´\\nM\\nK\\nt\\nr\\nh\\n2d. The probability of noncompliant pollut-\\nt\\nd\\nRd ×\\n×\\nM\\nK\\nt\\nr\\nh\\n2d\\nd\\nRt\\nM t\\ning sources that are rightfully punished is \\nd\\n1\\n=\\n×\\n×\\n×\\nh\\nK\\nN\\nM\\n×\\nt−\\n−\\n1\\n1\\nr\\nN\\nM t\\n2d. \\nThe number of compliant polluting sources that are mistakenly pun\\nd\\n-\\nished is \\nRt\\nd\\nM\\nK\\nr ´ -\\n(\\n)\\n1\\n1\\nt\\nh ´ -\\n(\\n)\\n1d C : \\\\ wspath\\\\ WS5551\\\\ Math_Preference\\\\ Equat\\ntion\\\\ pref\\\\ Euclid.eqp\\nd\\n, and the corresponding probability is \\nRt\\nd ×\\n−\\n(\\n)\\n1\\n1\\nM\\nK\\nt\\nr\\nh ×\\n−\\n(\\n)\\n1d\\nRt\\n1\\nM t\\nd\\n=\\n×\\nd\\n1−\\n×\\nh ×\\n−\\n(1\\nK ). We assume that the two \\nN\\nM\\n×\\n−\\n(\\n)\\n1\\nt−\\n−\\n1\\n1\\nr\\nN\\n1−M t\\n1d\\nd\\nprobabilities are known to all polluting sources for their following compliance \\ndecisions.\\nRt\\n−\\nThus, the expected compliance cost is C\\nP\\nd\\n1\\n1\\nM t\\n+\\n×\\n×\\n×\\nh ×\\n−\\n(\\n)\\n1\\nK\\nr\\nN\\n1−M t−1\\n1d , \\nd\\nRt\\n1\\nM t\\nwhile the expected penalty on noncompliance is P ×\\n×\\nd\\n×\\n×\\nh\\nK . \\nr\\nN\\nd\\nd\\nM t−1\\n2  \\nFor a decision of compliance, the former should be lower than the latter: \\nRt\\n1\\n1−M t\\nRt\\n1\\nM t\\nt\\nd\\nh\\n1\\nC\\nP\\n+\\n×\\n×\\n×\\n×\\n−\\n(\\n)\\n1\\nK\\nP\\nd\\nh\\nC\\nR\\n1d <\\n×\\n×\\n×\\n×K\\n<\\n×\\n1\\nM t−\\n−\\n1\\nr\\nN\\nt\\n1\\n2d , or \\nd\\n×\\nr\\nN\\nd\\n−\\nd\\nM\\nP\\nr\\nN\\nd\\nK\\nK\\n2\\n2\\ns\\nd\\n×\\n−(\\n)\\n1\\n1\\n−\\n×\\nK\\nK\\n1\\n1\\ns\\nd\\n(\\n)\\n−\\nr\\nN\\nM\\nK\\nt−\\n−\\n1 ×\\n+\\ns\\n1\\n1\\nM\\nK\\nt\\n1\\n.\\n2\\n(\\n)\\n−\\n×( −\\n1s)\\nRt\\nscreened \\nmin  is further defined as a threshold when all polluting sources have just been \\n(R\\nN\\nt\\ns =\\n×r\\ns ), all polluting sources in the high-risk group are \\n \\ndiagnosed \\nRt\\nt\\n(Rt =\\n×\\n(\\n(\\ns\\nM\\nK\\nt−\\n−\\n1\\nRs\\nd\\n×\\n+\\ns\\n1\\n1\\nM\\nK\\nt\\n2\\n×\\n−\\n1)\\n(\\n×\\n−\\n1s\\nd\\n))×r ) and all resources are uti-\\nr\\ns\\nr\\nlized \\ns\\nR\\nR\\nt =\\n+\\nt\\ns\\nRt . Then R\\nN\\nt\\nt−\\n−\\n1\\nt\\n1\\nd\\nmin =\\n×(\\n(\\nr\\nM\\ns +\\n×K\\nM\\n2s +\\n−\\n(\\n)\\n1\\n1\\n×\\n−\\n(\\n)\\nK\\nr\\n1s\\nd\\n)\\n)\\n×\\n.\\nWhen R\\nR\\nt\\nt\\nRt\\n£\\nRt =\\nmin , \\nd\\n. The com-\\n1\\n(\\n+1)\\nr\\nd ×\\n×\\n(\\n(\\nM\\nK\\nt−\\n−\\n1\\n+\\n−\\n1\\n2\\n×\\n−\\nr\\ns\\n1\\n1\\nM\\nK\\nt\\n)\\n(\\n1s))\\ns\\nC\\nRt\\nK\\nK\\n2\\n2\\ns\\nd\\n×\\n−(\\n)\\n1\\n1\\n−\\n×\\nK\\nK\\n(\\n)\\npliance condition is \\n1\\n1\\n−\\n<\\n×\\ns\\nd\\nr\\nM t\\n.\\nP\\nN\\n(\\n(\\ns +\\n×\\n−\\n−\\n1\\nK\\nM\\ns\\n1\\n1\\nt\\n1\\n2 +\\n−\\n(\\n)×\\n−\\n(\\nK1s\\nd\\n))×r )\\nAdditional compliance monitoring resources beyond Rt\\nmin will be devoted \\nto diagnosing those polluting sources in the high- \\nrisk group. These sources \\ncould be diagnosed and punished once or multiple times. In this situation, \\nR\\nR\\nt\\nt\\nd =\\n−R\\nR\\nt\\nt\\ns =\\n−N\\nr\\n× s.\\nThen corresponding to available enforcement resources, the noncompliance \\nrate at the end of time-step \\n \\nt will be\\n\\nt\\n\\nIf R\\nR\\nt\\nt\\n\\n−\\n£\\nt\\n×\\n−\\n, \\nR\\nK\\nK\\n(\\n)\\n1\\n1\\n−\\n×\\nK\\nK\\n(\\n)\\n\\nmin M =\\n−\\n1\\nΦ\\n×\\n2\\n2\\ns\\nd\\n1\\n1\\n\\n\\ns\\nd\\n\\n\\nN\\n(\\n(\\nr\\nM\\n+\\n×\\nt−\\n−\\n1\\nK\\nM\\n+\\n−\\n(\\n)\\n1\\n1\\nt\\n1\\n; Equation 6.2\\n\\ns\\n2s\\n×( −\\n×\\nK\\nr \\n\\n1s\\nd\\n))\\n)\\nK\\nK\\nM\\nK\\ns\\nd\\nt\\ns\\n×\\n−\\n×\\n+\\n−\\n2\\n2\\n1\\n2\\n(\\n(\\nC\\nP\\nRd\\nt\\nd\\n<\\n×\\n×\\n1\\n\\n\\nPolicy implementation 145\\n\\nIf \\nt\\n\\nt\\nt , \\nt\\n\\nR\\nN\\n−\\n×r\\nK\\nK\\n×\\n−(\\n)\\n1\\n1\\n−\\n×\\nK\\nK\\n(\\n)\\n−\\n\\nR\\nR\\n>\\nmin M =\\n−\\n1\\nΦ\\n\\ns ×\\n2\\n2\\ns\\nd\\n1\\n1\\ns\\nd\\n\\n.  \\nEquation 6.3\\n\\n\\n\\n\\nN\\nr\\n×\\nt\\nd\\nM\\nK\\n−\\n−\\n1 ×\\n+\\ns\\n(\\n)\\nM t\\n1\\n2\\n1−\\n×\\n−\\n(\\n)\\n1\\nK1 \\n\\ns\\nRt  will be greater if the noncompliance rate at the end of time-step \\n \\nt-1, M t-1\\nis higher or screening and diagnosing are more resource-\\nmin\\n, \\n \\nintensive with greater \\nr\\ns and r\\nindividual \\nd. Given a certain amount of total emissions under regulation, smaller \\npolluting sources will result in a greater number of polluting sources, \\nN, for compliance monitoring and thus higher demand for resources. Because the \\nnoncompliance rate, M t, changes over time, Rt  will change accordingly.\\nMore accurate compliance monitoring technologies (\\nmin\\nK\\nK\\n1\\n1\\ns\\nd\\n,\\n,K\\nK\\n2\\n2\\ns\\nd\\n,\\n® 1) with \\nlower costs for an average polluting source (r r\\n,\\n® 0) tend to induce higher com-\\npliance rates. Various factors could affect the availability \\ns\\nd\\nof enforcement resources \\nRt\\nper polluting source (\\n). The economy of scale in compliance monitoring could \\nN\\nhave two folds. On one hand, larger polluting sources could lead to an internal \\neconomy of scale because the required enforcement resources are more related to \\nthe number of sources. More enforcement resources, larger polluting sources and \\na smaller amount of total emissions will increase the resource availability indica-\\ntor. Even if with the screening step or effective compliance monitoring strategy, \\nthe probability of catching enough noncompliance cannot be enhanced to a high \\nenough level without sufficient enforcement resources. On the other hand, the \\ngeographical proximity of polluting sources could provide an external economy \\nof scale. The sources could then be equivalently bundled and reduce the compli-\\nance monitoring costs for one polluting source.\\nCorresponding to their required features, screening technologies are less accu-\\nrate but also less expensive than diagnosing technologies. They must have such \\ntrade- \\noffs to fit in the expected complementary roles. If one technology were both \\ncheaper and more accurate than the other, the latter technology would be entirely \\nreplaced by the former.\\nInput parameters in China’s empirical case\\nIn order to empirically illustrate and analyze the model, the input parameters will \\nadopt empirical values from the Chinese context. A current scenario and the range \\nof parameters are defined with the best available empirical data in China’s current \\nsituation. They are briefly summarized in Table 6.3, and this subsection provides \\na more detailed explanation.\\nAvailable resources for compliance monitoring (Rt) are a key input parameter \\nthat this model focuses on. For simplicity, compliance-monitoring \\n \\nresources (Rt) \\nand costs of screening and diagnosing technologies (r\\ns and r\\nd) are counted as the \\nnumber of environmental inspection staff. China has been gradually increasing \\ngovernmental employees for environmental inspection. The resource availabil-\\nity still faces constraints, but it does not fall into the situation of extreme scar-\\ncity. From 2001 to 2015, staff for environmental inspection grew from 37,934 to \\n66,379 (Ministry of Environmental Protection, 2002–2016). More important, with \\n­\\n\\n\\n146 Policy implementation\\nthe full establishment of regional supervisory centers/bureaus in 2008 by the then \\nMinistry of Environmental Protection, the central government has significantly \\nstrengthened its capacity of environmental inspection, accounting for 0.48% (294 \\nemployees) of inspection staff at all four levels in 2009 and 0.82% (542 employ-\\nees) in 2015, up from 0.07% in 2008 (41 employees; Ministry of Environmental \\nProtection, 2002–2016). Six regional Supervision Bureaus were allowed to have, \\nin total, 240 formal employees for taking charge of supervision tasks within their \\njurisdictions (State Commission Office for Public Sector Reform, 2018). Not all \\nstaff employed in the inspection section are environmental inspectors, for exam-\\nple, to play supporting roles such as office work. In 2017, China had 46,800 envi-\\nronmental inspectors in the databases for “double randomness, one publicization” \\n(Ministry of Ecology and Environment, 2018). The closest year with available \\ndata on inspection staff was 2015. Accordingly, about 70.5% of inspection staff\\n \\nwere environmental inspectors. The empirical model simulation adopts this ratio \\nto examine the impacts of resource availability on environmental compliance \\nrates. The current scenario thus has 66,379 inspection staff, or 46,800 environ-\\nmental inspectors. If not specified, they will remain unchanged over time.\\nThe number of polluting sources (N) was been briefly described in Section 4.2. \\nThe current scenario takes the intermediate number, 809,500 polluting sources as \\ntargeted in 2017 under the “double randomness, one publicization” scheme.\\nPollution abatement costs and the associated penalty for noncompliance range \\nacross sectors, technologies and severity of noncompliance. The ratio between \\n\\ncompliance costs and penalty C \\n is a key variable in this compliance monitoring \\n\\n\\n\\nP \\n\\n\\n\\nmodel. In 2007, in order to tackle the long-term \\n \\nproblem of weak environmental \\npolicy enforcement, China not only subsidized those coal-fired \\n \\npower plants to \\nnormally operate their SO2 scrubbers but, more important, also issued a penalty, \\nbeing five times of the subsidy/costs on a per- \\nkilowatt-hour \\n \\nbasis (Xu, 2011a; \\nNDRC and SEPA, 2007b). In dealing with potential noncompliance on water pol-\\nlution and withdrawal, however, China’s penalty was barely able to catch up with \\nthe pollution abatement costs (Guo et al., 2014). In the current scenario, the cost/\\npenalty ratio is assumed to be 2/3. Furthermore, pollution abatement costs are not \\nidentical across polluting firms due to, for example, economy of scale, the sulfur \\ncontent of coal and whether the pollution removal facility is a retrofit or built \\ntogether with the main equipment. In compiling China’s SO2 emission inventory, \\nLu et al. (2011) assumed that the sulfur content had a normal distribution. The \\ncurrent scenario follows, due to the key influence of sulfur contents on SO2 abate-\\n\\nment costs, to assume that the cost/penalty ratio C \\n has a normal distribution \\n\\n\\n) among the polluting sources.\\n\\nP \\n\\n\\n(Φ( )\\n•\\n\\nThe costs of screening and diagnosing technologies are accounted as the \\nrequired number of inspectors in a year per environmental observation, either \\nscreening or diagnosing inspection (inspector-year \\n \\nper observation, being noted \\nas r\\nrandomness, one publicization” \\ns and r\\nd, respectively). China has comprehensively established the “double \\nmethod for governmental, including environ-\\nmental and other, inspections on firms (State Council, 2019). For environmental \\n\\n\\nPolicy implementation  147\\ninspections, the method had been well established in 2017 (Ministry of Ecology \\nand Environment, 2018). Under this method, polluting firms and environmental \\ninspectors will both be randomly selected from databases, while the information \\nwill be publicized to the public. In 2017, 809,500 polluting firms and 46,800 envi­\\nronmental inspectors were included in the databases, while 632,600 environmen­\\ntal inspections were conducted (Ministry of Ecology and Environment, 2018). \\nAccordingly, 27 inspections were conducted by an average inspector in 2017. \\nAccording to the author’s earlier fieldwork in China (Guo et al., 2014; Xu, 2011a), \\none inspection generally involves two inspectors. Thus, the cost of environmental \\ninspection or diagnosing technology (r\\nd) was 0.074 inspector-­\\nyear per inspection. \\nIt is adopted in the current scenario.\\nDifferent screening and diagnosing technologies have different cost structures. \\nFor example, a sophisticated satellite-­\\nbased technology has very high initial \\ncapital costs, but its marginal costs of monitoring one more pixel are negligi­\\nble. For example, OCO-­\\n2 cost US$465 million to set up, but with more than \\n100,000 measurements of column CO2 concentrations each day (Osterman et al., \\n2018), each measurement since its launch in July 2014 cost merely about US$2 \\nto US$3 per measurement, considering neither operation and maintenance costs \\nthat will raise the unit cost nor expected longer lifetime that will reduce the \\nunit cost. According to the author’s fieldwork in China’s coal-­\\nfired power plants, \\ncontinuous emissions monitoring system (CEMS) costs about 500,000 RMB/set \\naround 2010. China has been publishing hourly data from CEMSs in key pollut­\\ning sources. With an expected lifetime of approximately 5 to 10 years, the unit \\ncost would also be about US$1 to US$2 per published data point. Screening often \\nrequires multiple observations. OCO-­\\n2 has a 16-­\\nday ground-­\\ntrack repeat cycle \\nto result in about 23 repeated observations per year for one pixel, or at a cost of \\nroughly US$50 per year. CEMSs in China could provide more than 8,000 hourly \\nobservations per year and have an annual cost of about US$8,000 to US$16,000. \\nAccordingly, the costs of an average screening technology are assumed to be \\nin the range of several hundred U.S. dollars per year for one polluting source. \\nIn contrast, compliance monitoring by environmental inspectors is cheaper to \\nset up but more expensive to operate. For example, China in 2015 at the cen­\\ntral level had 542 employees for environmental inspections (Figure 3.1), with \\na total cost of 63.5 million RMB (~US$10.2 million in 2015 exchange rate, or \\nUS$18,800/person-­\\nyear; Ministry of Environmental Protection, 2016b). Accord­\\ningly, the average cost of one inspection was about 0.074 inspector-­\\nyear/inspec­\\ntion / 70.5% × US$18,800/person-­\\nyear, or US$2,000/inspection. In the current \\nscenario, the unit cost of a screening technology (rs) is then assumed to be one \\norder of magnitude cheaper than that of screening technology, or equivalently \\n0.0074 inspector-­\\nyear per screening round.\\nThe compliance monitoring accuracy of one technology is hard to exactly \\nmeasure, because only data on observed compliance and noncompliance are avail­\\nable but not those on absolute truth. Furthermore, the dichotomy of compliance \\nand noncompliance does not measure the severity of noncompliance, while more \\nsevere cases, due to their stronger signal-­\\nto-­\\nnoise ratios, tend to be easier to catch. \\n\\n\\n148  Policy implementation\\nIn theory, the screening strategy would only work when the noncompliance rate \\nin the high-­\\nrisk group is higher than that in the low-­\\nrisk group. The more different \\ntheir noncompliance rates between these groups gap are, the better the screening \\nstrategy will be. In the current scenario, K1s, K1d, K2s and K2d are assumed to be \\n90%, 99%, 70% and 90%, respectively.\\n\\n\\n7\\t\\n\\u0007\\nEnvironmental technology \\nand industry1\\n1  \\u0007\\nGoal-­\\ncentered SO2 mitigation path\\nBesides other critical measures, pollution mitigation often involves facilities \\nsuch as those installed in coal-­\\nfired power plants to remove sulfur oxide (SO2), \\nnitrogen oxide (NOx), particles, mercury and carbon dioxide (CO2), together with \\nrenewable-­\\nenergy facilities for reducing coal consumption such as wind turbines \\nand solar panels and hybrid and electric vehicles. Two major factors determine \\nhow rapidly a country could utilize these facilities for pollution mitigation. First, \\nthere must be a strong demand for their rapid deployment and normal operation, as \\nexamined in detail in Chapters 5 and 6. Second, if the demand is put in place, \\nenough supply capacity should be established to meet the demand. A develop­\\ning country could take the latecomer’s advantage to utilize the supply capacity \\nin developed countries. However, because of China’s sheer size, the rest of the \\nworld might not be able to accommodate its huge demand. With constrained sup­\\nply capacity but significantly greater demand, the international price of pollution \\ncontrol facilities could rise sharply, and this would discourage their utilization and \\nslow the pollution mitigation process. Rapid pollution mitigation in China relies \\ngreatly on the rapid establishment of a domestic industry.\\nSO2 mitigation achieved rapid progress over the past two decades from low \\nstarting positions. On the supply side, in the late 1990s, China had few domestic \\nfirms and barely any commercialized technologies. The Chinese markets were \\ndominated by foreign firms and foreign technologies. After a decade, a large num­\\nber of firms entered the market to meet the newly emerged huge demand for SO2 \\nscrubbers to even drive down prices substantially.\\nAs an illustration of the differences between goal-­\\ncentered and rule-­\\nbased gov­\\nernance, the progressive paths in China and the United States have been dra­\\nmatically different in reaching the wide deployment of SO2 scrubbers in coal-­\\nfired \\npower plants and their normal operation of high SO2 removal rates (Figure 7.1). \\nFrom the very beginning, the normal operation of SO2 scrubbers in the United \\nStates with rule-­\\nbased governance has been achieved while the progress went \\nmainly through the deployment dimension. In contrast, China deployed SO2 \\nscrubbers with poor operation in the early stage and then proceeded simultane­\\nously in the dimensions of deployment and operation until the technical limits of \\n\\n\\n150  Environmental technology and industry\\nSO2 removal rates were roughly reached. Accordingly, the requirements on the \\nquality of SO2 scrubbers were initially low in the Chinese market and became \\nincreasingly higher only later, while in the U.S. market, quality was important \\nfrom the beginning.\\nIn China, under goal-­\\ncentered governance, at the early stage of deployment with \\nfew SO2 scrubbers and incapable policy implementation, more SO2 mitigation \\nwould be achieved if the focus were on further deployment rather than on opera­\\ntional improvement. With more and more SO2 scrubbers in place, any improve­\\nment in the operation of the growing stock would lead to a greater reduction in \\nSO2 emissions. For achieving their SO2 mitigation goals, the rational choice of \\nthe Chinese central and local governments led to a path in which initial progress \\nwas made mainly in deploying more SO2 scrubbers, and it was only afterward that \\ntheir level of operation caught up.\\nImplementing policies on the deployment and normal operation of SO2 scrub­\\nbers require different amounts of resources for compliance monitoring. On one \\nhand, the compliance monitoring on the physical existence of SO2 scrubbers is \\nstraightforward and the huge sizes – for example, an absorbing tower is generally \\nseveral meters in diameter and tens of meters high – make them easily visible. The \\none-­\\nby-­\\none inspection indicates that the corresponding compliance monitoring \\n0\\n100\\n200\\n300\\n400\\n500\\n600\\n0%\\n20%\\n40%\\n60%\\n80%\\n100%\\n)\\nW\\nM\\n0\\n0\\n0\\n,\\n1\\n(\\nt\\nn\\ne\\nm\\ny\\no\\nl\\np\\ne\\nd\\ne\\nv\\ni\\nt\\na\\nl\\nu\\nm\\nu\\nC\\nSO2 removal rate\\nChina \\n(2006–2008, 2010)\\nUnited States\\n(1973–2010)\\nFigure 7.1  \\u0007\\nThe progressive paths on the deployment and operation of SO2 scrubbers in \\nChina and the United States\\nSource: Lefohn et al. (1999); Xu (2011b); Ministry of Environmental Protection (2011b, 2008–2012); \\nEIA (1986–2006, 2007–2011); Xu (2013).\\n\\n\\nEnvironmental technology and industry  151\\ncosts for each SO2 scrubber do not greatly differ, regardless of how many have \\nbeen deployed. On the other hand, the compliance monitoring on the installation \\nis just a onetime event, but when in operation they demand significantly more \\nresources on a day-­\\nby-­\\nday basis. A well-­\\nfunctioning environmental compliance \\nmonitoring system has significant initial costs of establishment. A  significant \\nproportion of additional costs for monitoring one more SO2 scrubber are largely \\nborne by the polluting firms because they are responsible for installing their own \\nmonitoring equipment. For policy enforcers, the compliance monitoring costs \\nhave a great economy of scale and they increase relatively modestly with wider \\ndeployment of SO2 scrubbers.\\nThe political resistance against the deployment and against the normal opera­\\ntion of SO2 scrubbers also differs. The normal operation and maintenance (O&M) \\ncosts are significantly higher than the annualized capital costs, especially for SO2 \\nscrubbers with compromised quality (Xu, 2011b). Data on the capital costs of SO2 \\nscrubbers were retrieved from two sources to report a dramatic reduction together \\nwith an expanding domestic market of SO2 scrubbers (Figure 7.2). From February \\nto August 2006, China’s Association of Environmental Protection Industries sur­\\nveyed SO2 scrubber projects in operation or under construction at the end of 2005 \\n(Xu et al., 2006). One hundred thirteen projects (223 coal-­\\nfired power units) with \\n0\\n20\\n40\\n60\\n80\\n100\\n120\\n140\\n160\\n180\\n200\\n0\\n20\\n40\\n60\\n80\\n100\\n120\\n140\\n)\\nW\\nk\\n/\\n$\\nS\\nU\\n(\\ns\\nt\\ns\\no\\nc\\nl\\na\\nt\\ni\\np\\na\\nc\\nt\\ni\\nn\\nU\\nAnnual installation of SO2 scrubbers (1,000 MW)\\nUnited States, 2000–2009\\nChina, 2000–2008\\nFigure 7.2  \\u0007\\nAnnual average unit capital costs of SO2 scrubbers in China and the United States\\nSource: Xu et al. (2006); EIA (2012–2013); Ministry of Environmental Protection (2008–2012); Xu \\n(2013).\\nNote: China’s average unit capital costs refer to limestone-gypsum wet scrubbers. Annual average \\nexchange rates were used for currency conversion. Data from 2000 to the peak year of deployment \\nare shown.\\n\\n\\n152  Environmental technology and industry\\na total capacity of 83,850 MW applied limestone-­\\ngypsum wet scrubber technol­\\nogy and had cost information available. Data on projects using other technologies \\nare much less continuous to provide longitudinal insights. They had already been \\nor were expected to be in operation over the period from 2002 to 2008. Their \\nexpected time in operation could partly reflect when the contracts were signed and \\naccordingly the then market situation. Furthermore, the author’s interviews pro­\\nvided an independent source to cross-­\\ncheck the survey data and to shed light on \\ntheir more recent changes. Data for the United States came from the U.S. Energy \\nInformation Administration (EIA; 2012–2013).\\nQuality has a great impact on the capital costs of SO2 scrubbers. For example, \\nSO2 scrubbers in Hong Kong’s two coal-­\\nfired power plants were contracted with \\nfirms from mainland China, and the unit capital costs were three to four times \\nthose of similar projects in mainland China, although still at about half of the \\ncomparable costs in the United States. Hong Kong’s SO2 scrubbers require high-­\\nquality equipment, engineering and construction and enough redundancy, and \\nthey take about twice the amount of time from contract to completion. Beyond \\nhigher labor costs, the higher price in Hong Kong above “The China Price” could \\nbe mainly explained as a quality premium.\\nConsidering the reduction of capital costs in the Chinese market (Figure 7.2), the \\ninvestment for one more SO2 scrubber would decrease to indicate that the politi­\\ncal resistance dwindles when many SO2 scrubbers had been deployed. The O&M \\ncosts for each SO2 scrubber varied less along the deployment dimension because \\nof the necessary consumption of electricity, limestone, and water (Table  6.1). \\nMore SO2 scrubbers led to greater overall O&M costs, and this increased the over­\\nall political resistance. However, installing SO2 scrubbers without normal opera­\\ntion wasted financial resources, and it conflicted with environmental policies. The \\nassociated political pressure for each SO2 scrubber from the civil society, despite \\nits underdeveloped status in China, and from within the government increased \\nwhen more SO2 scrubbers were deployed to make the problem more visible. The \\noverall net political resistance against the normal operation of existing SO2 scrub­\\nbers could increase at the very early stage of deployment and then shrink when \\nmore SO2 scrubbers are in place.\\nGiven China’s then poor record of implementing environmental policies, the \\nevolving quality requirements contributed to goal attainment with a rapid path \\nthat could be theoretically understood. The Chinese government can make a cer­\\ntain amount of effort to work for pollution mitigation with two choices, either to \\ndeploy more pollution control facilities or to enhance the operational performance \\nof the existing stock. The goal is to maximize the impacts of efforts on pollution \\nmitigation at every step. After a certain amount of pollution control facilities have \\nbeen deployed, the net political resistance against the deployment of one more \\nfacility and against the enhancement of operational performance by 1% could be \\nroughly taken as unchanged with the level of deployment. Accordingly, a given \\namount of effort could either raise the deployment rate by α (in the two cases of \\nSO2 scrubbers, the unit is megawatts, MW) or the performance of existing facili­\\nties by β% (in the SO2 scrubber case, the unit is percentage points of SO2 removal \\n\\n\\nEnvironmental technology and industry 153\\nrates). The initially deployed facilities have a total capacity of A, and the initial \\nperformance is B%. Then the initial pollution mitigation effect of the facilities is \\nroughly proportional to A × B%. The performance has a technical upper limit, \\nB*%.\\nThe option of devoting the efforts to the deployment could raise the pollution \\nmitigation effect to (A + α) × B%, and the other option to work on the opera-\\ntion would have an effect of A × (B% + β%). If there is no constraint, a rational \\ndecision maker to maximize the impact of his or her efforts will choose the first \\nA + α\\nβ\\nB%\\n%\\n+\\noption when (A + α) × B% > A × (B% + β%), or when \\n>\\n or \\nA\\nB%\\nα\\nβ%\\nα\\nβ%\\n>\\n. The second option will be taken when \\n<\\n, and the two options \\nA\\nB%\\nA\\nB%\\nα\\nβ%\\nare no different when \\n=\\n. With the progress on the deployment and opera-\\nA\\nB%\\ntion, the choice could change. This is what goal-centered \\n \\ngovernance would indi-\\ncate. If adding one constraint that the choice should prioritize policy enforcement, \\nthe progress should be first made to improve the operation. Only when B% has \\nreached B*%, more facilities are allowed to be deployed. This could illustrate \\nrule-based governance.\\nOne more constraint could be added to describe the situation on the supply side. \\nAs examined below with more details, the goal-centered \\n \\ngovernance strategy low-\\ners technological barriers of market entry to facilitate the rapid establishment of \\na large-enough supply capacity\\n \\n, while the rule-based governance \\n \\nstrategy would \\ncorrespond to higher market- \\nentry barriers and discounted supply capacity in the \\nChinese context. To simplify the model, the supply capacity under rule-based \\n \\ngovernance is η% less than that in goal-centered\\n \\n governance, and thus, the same \\namount of efforts could only raise the deployment rate by α\\nη\\n×\\n−\\n(\\n%\\n1\\n).\\nThe SO2 scrubber case is simulated here to exemplify the usefulness of this \\nvery simple model. Here are the assumptions of the earlier parameters: (1) A0: the \\ninitial capacity of SO2 scrubbers, 7,000 MW, equivalent to the level in 2000 (Min-\\nistry of Environmental Protection, 2008–2012); (2) B0%: the initial SO2 removal \\nrate in coal- \\nfired power plants with SO2 scrubbers, 31.3%, equivalent to the level \\nin Jiangsu Province in 2006 (Xu, 2011b); (3) B*%: 79%, the highest SO2 removal \\nα\\n4,500 MW\\nrate China achieved in 2010 (Figure 6.1); (4) \\n: \\n, or the required \\nβ%\\n1%\\neffort from decision-makers \\n \\nwas the same to deploy 4,500 MW of SO2 scrubbers \\nand to increase the SO2 removal rate of the existing stock by 1%. The number is \\nassumed to fit China’s actual data; (5) η%: 50%, assumed to indicate the impacts of \\nhigher market-entry barriers in the rule-\\n \\nof-\\n \\n \\nlaw strategy. As illustrated in Figure 7.3, \\nthe projection with the goal-centered \\n \\ngovernance strategy fits well into China’s SO2 \\nmitigation path for coal-fired \\n \\npower plants with SO2 scrubbers. If considering no \\nconstraint from the supply side, rule-based \\n \\ngovernance mainly would differ from \\ngoal- \\ncentered governance at the early stage of progress. However, if considering \\nthe potential supply constraints due to higher market-entry barriers, pollution miti\\n \\n-\\ngation under rule-based governance would proceed at a much slower pace.\\n \\n­\\n\\n\\n154  Environmental technology and industry\\nFigure 7.3  \\u0007\\nModel projection of the SO2 mitigation path in China’s coal-fired power plants: \\n(a) deployment and operation of SO2 scrubbers under goal-centered govern­\\nance (the dots refer to actual data); (b) avoided SO2 emissions under goal-\\ncentered and rule-based governance\\nSource: Xu (2013).\\n0\\n100\\n200\\n300\\n400\\n500\\n600\\n0%\\n20%\\n40%\\n60%\\n80%\\n100%\\nSO2\\n)\\nW\\nM\\n \\n0\\n0\\n0\\n,\\n1\\n(\\n \\ny\\nt\\ni\\nc\\na\\np\\na\\nc\\n \\nr\\ne\\nb\\nb\\nu\\nr\\nc\\ns\\nSO2 removal rate\\n2006\\n2007\\n2008\\n2010\\n(a)\\nAvoided SO2 emissions\\nCumulative efforts\\nActual path\\nGoal-centered governance\\nRule-based governance without supply constraint\\nRule-based governance with supply constraint\\n2006\\n2007\\n2008\\n2010\\n(b)\\n\\n\\nEnvironmental technology and industry  155\\n2  \\u0007\\nTechnology licensing under goal-­\\ncentered SO2 \\nmitigation path\\nThe international technology market provided opportunities for China’s domestic \\nfirms to license foreign technologies and to quickly ramp up their technological \\ncapabilities, although at a cost. Functioning markets for transferring technologies \\nto developing countries not only are important for their economic development \\nand upgrading along the value chain but also have critical implications for the \\nenvironment. Due to China’s huge and steadily growing emissions, how fast and \\neffective environmentally friendly technologies were adopted was a key determi­\\nnant for its environmental cleanup. Technology transfer from developed to devel­\\noping countries has long been recognized as a key measure in addressing CO2 \\nmitigation (United Nations, 1992). One important method of technology transfer \\nis through technology licensing. With available markets for technologies, a tech­\\nnology owner could choose between licensing its product or directly investing \\nin the client country, and a firm that needs technology could either license in or \\ninnovate indigenously (Arora et al., 2001a; Teece, 1988; Arora et al., 2001b). In \\ninternational negotiation on transferring low-­\\ncarbon technologies from developed \\nto developing countries, developed countries generally argue for market-­\\nbased \\nsolutions and adequate protection of intellectual property rights (IPR), while \\ndeveloping countries often demand nonmarket solutions at lower than market \\nrates (Ockwell et al., 2010). The differing positions become an obstacle to the \\nagreement of new and effective climate treaties (Ockwell et al., 2010).\\nDespite unfavorable conditions, the global market for technology has been sig­\\nnificant, amounting to about US$35 to US$50 billion in the mid-­\\n1990s (Arora \\net al., 2001b) and roughly US$100 billion in 2002 (Arora and Gambardella, 2010). \\nHowever, only a small portion – less than one third for the United States – of \\ntechnological transactions were between unaffiliated organizations and thus true \\nmarket transactions (Arora and Gambardella, 2010; Saggi, 2002). Most cross-­\\nborder technology licensing happens among developed countries and that from \\ndeveloped to developing countries is much rarer (Arora and Gambardella, 2010). \\nProduct markets in most developing countries are not large enough to attract many \\npotential technology licensors. Developing countries generally lag behind devel­\\noped countries in human and technological capacities that enable them to effec­\\ntively absorb licensed foreign technologies and exploit their full value (Metz et al., \\n2000). Additionally, effective IPR protection could help address the problems of \\nunauthorized use of intellectual property (Gans and Stern, 2010), but developing \\ncountries often do not have well-­\\ndeveloped systems of IPR protection and thus are \\nplaced in relatively disadvantageous positions in creating an attractive market for \\ntechnology (Strokova, 2010). However, large developing countries like China are \\nable to access foreign low-­\\ncarbon technologies, although not those at the cutting \\nedge (Ockwell et al., 2010; Lewis, 2007). China’s rapid development of many \\nindustries had roots partly in the importation of foreign technologies, including, \\nfor example, wind turbines (Lewis, 2007), large hydroelectric turbines (Liang, \\n2001) and high-­\\nspeed railways (Chan and Aldhaban, 2009).\\n\\n\\n156  Environmental technology and industry\\nAn especially prominent case was that of SO2 scrubbers. SO2 scrubber tech­\\nnologies have been commercially deployed since the mid-­\\n1970s, mainly in devel­\\noped countries. Up until 1998 (expressed in terms of generating capacity of power \\nstations thus equipped), the pace of deployment was about 10 GW per year in \\nthe world and 4 GW per year in the United States (Srivastava et al., 2001). Many \\ninternational firms had established their technological and engineering reputations \\nin this field. China began to significantly deploy SO2 scrubbers about three dec­\\nades later than developed countries, with a deployment rate of over 100 GW per \\nyear in the 11th Five-­\\nYear Plan (Chapter 5). Because of their high SO2 removal \\nefficiencies – generally over 90% with wet-­\\ntype technologies – SO2 scrubbers \\nbecame the most vital technology in achieving China’s goal of a 10% reduction \\nin SO2 emissions in the 11th Five-­\\nYear Plan (2006–2010; Xu, 2011b, 2011c). \\nAmong the more than 500 GW of SO2 scrubbers in China at the end of 2010, more \\nthan 90% were installed by Chinese firms using licensed foreign technologies \\n(Ministry of Environmental Protection, 2011a). Major Chinese firms universally \\nlicensed foreign technologies and relied heavily on them. Conversely, fewer than \\n5% were installed by foreign firms or under joint ventures (Ministry of Environ­\\nmental Protection, 2011a). Domestic firms dominated the market, in spite of their \\ninitial lack of proven technologies and experience.\\nThe goal-­\\ncentered SO2 mitigation path created three characteristics of Chi­\\nna’s SO2 scrubber demand in the early stage. The difficult SO2 mitigation goals \\ntogether with China’s colossal size required more than 100 GW SO2 scrubbers \\nannually, which was multiple times as big as the world together had experienced \\nbefore (Figure 5.12). Their initial poor operation significantly relaxed actual qual­\\nity requirements (Figure 7.1). The initial one-­\\nsided emphasis on the deployment \\nof SO2 scrubbers indicated that the huge demand for SO2 scrubbers would be cre­\\nated swiftly from a low level in the 10th Five-­\\nYear Plan, which led to stringent \\ntime constraints for SO2 scrubber firms (Figure 5.12). They played key roles in \\nshaping the strategies of domestic technology licensees and foreign technology \\nlicensors for tapping into the market.\\n2.1  \\u0007\\nThe strategy of domestic technology licensees\\nChina’s domestic firms as technology licensees could fall into the three follow­\\ning categories: state-­\\nowned, university-­\\nestablished and nonstate. “State-­\\nowned” \\nfirms refer to those controlled by state-­\\nowned power corporations, which could \\nhave faced less fierce competition to win SO2 scrubber projects because of their \\nspecial “internal” relationship. Indigenous SO2 scrubber technologies had been \\ndeveloped by a few research institutes and universities to directly transfer their \\nhuman and technological capabilities to state-­\\nowned and university-­\\nestablished \\nfirms. Nonstate firms could behave differently due to their relative lack of such \\ninitial capabilities. In addition, although most of China’s major firms relied heav­\\nily on licensed technologies, some concentrated on applying their own. China \\nhad five large state-­\\nowned power corporations at the national level in the late \\n2010s, four having major SO2 scrubber firms, and two were selected for interview. \\n\\n\\nEnvironmental technology and industry  157\\nIn the available SO2 scrubbers at the end of 2011 with unit scales not smaller \\nthan 100 MW, the two firms had market shares of 11.9% and 3.3%, respectively. \\nAnother smaller firm owned by one of the five power corporations was also vis­\\nited, and its market share was 0.4%. The special relationship with their parent \\ncorporations put them in relatively advantageous positions in market competition. \\nEight firms that had no association with power corporations were interviewed. \\nTheir market shares ranged from 0.7% to 6.0%, being 22.8% in total. In addition, \\ntwo foreign firms and their Chinese representative offices as technology licensors \\nwere also interviewed to provide an external perspective.\\nDomestic firms’ decisions to license in SO2 scrubber technologies were heavily \\ninfluenced by the three demand characteristics under the goal-­\\ncentered SO2 miti­\\ngation path. First, the sheer size of China’s demand for SO2 scrubbers challenged \\nthe supply capacity. One concern was whether China had enough engineers. This \\ncondition was met partly through rapidly training many more university students \\n(Figure 7.4). In 2000, 496,000 undergraduate students graduated from full-­\\ntime \\nfour-­\\nyear undergraduate programs, including 213,000 in engineering. In 2010, the \\nnumbers had grown to 2,591,000 and 813,000, respectively. In 2018, the numbers \\nfurther climbed to 3,868,000 and 1,269,000, respectively. In 2018, about the same \\nnumber of undergraduate students (3,665,000) graduated from other full-­\\ntime pro­\\ngrams with shorter study periods of two or three years. The age group, 20 to 24, \\ncomprised 5.95% of China’s population in 2018, or 16.6 million for each yearly \\n0\\n500\\n1,000\\n1,500\\n2,000\\n2,500\\n3,000\\n3,500\\n4,000\\n1998\\n2000\\n2002\\n2004\\n2006\\n2008\\n2010\\n2012\\n2014\\n2016\\n2018\\n)\\ne\\nl\\np\\no\\ne\\np\\n \\n0\\n0\\n0\\n,\\n1\\n(\\n \\ns\\ne\\nt\\na\\nu\\nd\\na\\nr\\nG\\nYear\\nScience\\nEngineering\\nAgriculture\\nMedicine\\nOthers\\nFigure 7.4  \\u0007\\nYearly university graduates in China from four-year undergraduate programs \\nby subjects\\nSource: Ministry of Education (1999–2019).\\n\\n\\n158  Environmental technology and industry\\nage (National Bureau of Statistics, 1996–2019). Accordingly, in 2018, about half \\nof China’s newly available labor force had a received formal university educa­\\ntion. Other part-­\\ntime or Internet-­\\nbased undergraduate programs trained another \\n4.1 million graduates in that year. These enhanced human resources provide a \\ncrucial foundation for China’s rapid deployment of pollution-­\\nremoval industrial \\nfacilities.\\nThe huge market also helps diminish one concern that licensors might not trans­\\nfer technologies completely after receiving payments (Arora et al., 2001b). In the \\ncase of SO2 scrubber technology, royalties dominated the revenue stream in tech­\\nnology licensing and effectively deterred such a moral hazard. By way of exam­\\nple, an American firm charged one licensee US$652,118 as the up-­\\nfront lump-­\\nsum \\nfee (Table 7.1): interviews discovered that a license’s approximate royalty rate \\nshould be 2% of SO2 scrubber contract values. Between 2004 and 2010, the firm’s \\nincome from royalties was nearly 40 times as much as the up-­\\nfront lump-­\\nsum fee \\n(the licensee completed 34,900-­\\nMW wet SO2 scrubbers in that period; Ministry \\nof Environmental Protection, 2011a), and the national average contract value was \\nabout US$35/kW (Xu et al., 2006)). From another perspective, as demonstrated \\nin the case of a Japanese licensor, a licensee’s loss was limited to approximately \\nthe up-­\\nfront lump-­\\nsum fee when the technology transfer was not satisfactory. In \\naddition, if a licensor gained a bad reputation, this could limit its future business \\nopportunities in the huge and rapidly growing Chinese market.\\nSecond, the quality requirements for SO2 scrubbers were initially low. The \\ndeployment of SO2 scrubbers took off around 2002, but the normal operation was \\nimproved significantly only in about 2007 (Xu, 2011b; Xu et al., 2009). In the five \\ngap years, many managers of installed SO2 scrubbers did not plan to operate them \\nnormally and cared very little about the quality, while quality was closely associated \\nwith the technological advancement of a supply firm. In addition, China’s reform \\nin the power sector in 2002 created multiple independent power corporations to \\nTable 7.1 Up-front \\n \\nlump-sum fees of SO2 scrubber technology licenses (the Chinese \\nlicensees here are all listed on stock markets and the data are from their annual \\nreports)\\nChinese licensee\\nCountry origin Lump-sum fee*\\nYear\\nTechnology type\\nof the foreign \\nlicensor\\nWuhan Kaidi\\nGermany\\nUS$277,304\\n1998\\nDry type\\nFujian Longjing\\nGermany\\nUS$3,989,234\\n2001\\nWet type\\nCirculation fluidized bed\\nWuhan Kaidi\\nUnited States\\nUS$652,118\\n2002\\nWet type\\nZhejiang Feida\\nUnited States\\nUS$1,250,000\\n2002\\nWet type\\nJiulong Electric\\nJapan\\nUS$1,126,563\\n2002\\nWet type\\nJiulong Electric\\nAustria\\nUS$1,423,765\\n2004\\nWet type\\nInsigma Technology\\nFrance\\nUS$1,200,000\\n2004\\nWet type\\n* Exchange rates on December 31, 2010 were used: 1 US$ = 6.62 RMB = 0.75 euro.\\n\\n\\nEnvironmental technology and industry  159\\nencourage competition – this was even though all of these were state-­\\nowned. The \\nrapid construction of new power plants strained their available financial resources \\nto create strong incentives to minimize capital investment for each new project, \\nwhile the poor quality of SO2 scrubbers could substantially reduce capital costs. \\nFurthermore, the low requirement for quality was strengthened by the largely sepa­\\nrate decisions of capital investment and daily operation and by the different incen­\\ntives of respective decision-­\\nmakers. Managers of coal-­\\nfired power plants should \\nhave an incentive to install high-­\\nquality SO2 scrubbers while capital investment \\nwas within the authority of the upper levels of management in power corporations. \\nThe low requirement for quality and technological advancement substantially low­\\nered the technological market-­\\nentry barrier not just for the SO2 scrubber firms but \\nalso along the entire supply chain. In contrast, the quality requirement and techno­\\nlogical market-­\\nentry barrier in the U.S. market were much higher.\\nChina’s regulators also paid attention to the quality requirements, especially with \\nthe knowledge of domestic firms’ initially unsatisfactory technological statuses. \\nTechnologies could come from international transfer or in-­\\nhouse innovation. Vari­\\nous factors could affect the choice of a country or a firm between these two technol­\\nogy strategies. China used to focus almost entirely on in-­\\nhouse innovation under \\nthe rule of Chairman Mao when China segregated itself from the world. The “Not \\nInvented Here” syndrome – that internally developed technologies are preferred – \\nwas found to be a barrier to technology licensing (Arora and Gambardella, 2010), but \\nit does not seem to be deeply rooted in China in the economic reform era. Secondary \\ninnovation based on imported technologies, coupled with original and integrated \\ninnovation, had been established as three cornerstones of China’s indigenous inno­\\nvation strategy (State Council, 2006). With regard to the installation of SO2 scrub­\\nbers, China stipulated in tendering documents that established technologies were \\nrequired. As late as 2005, bidders were clearly asked to specify a foreign technology \\nprovider that had installed SO2 scrubbers of the same or greater scale (Guizhou \\nQiandong Power Station, 2005). Interviews also confirmed the general requirement \\nfor foreign, commercialized technologies in the early years when almost no Chinese \\nfirms had any proven experience. This requirement was relaxed only in later years \\nafter many firms in the market had completed enough projects.\\nThird, time was a serious constraint. In the late 1990s and early 2000s, few \\ndomestic firms were capable of designing SO2 scrubbers. The sudden appearance \\nof a huge market led to the creation of many new firms and the reorientation of \\nexisting ones from other industries. Because few firms had any prior experience \\nand the market was large enough to accommodate many, most – except those \\nowned by coal-­\\nfired power corporations – were placed on a more or less equal \\nfooting. Firms would achieve distinction if they could establish engineering and \\nmanagement teams and develop their technological capability faster than others. \\nAnother time constraint was the short period from the issue of tendering docu­\\nments to completion of the bidding process; this typically lasted only one to four \\nweeks. Additionally, the design process could not take more than a few months \\nif the construction was to begin on schedule. Successful firms had to respond \\nquickly and provide acceptable quality.\\n\\n\\n160  Environmental technology and industry\\nThese time constraints helped push domestic firms toward technology licens­\\ning, due to their weak technological foundations. When demand for SO2 scrub­\\nbers started to surge, domestic technologies were generally not able to satisfy \\nthe time constraints because of their immaturity. Domestic research and devel­\\nopment generated “naked” technologies, to quote the word of one interviewee. \\nDemonstration projects on a commercial scale should be followed by multiple \\nprojects to make the technology mature and ready for wide commercial deploy­\\nment. The commercialization of these “naked” technologies would require at least \\na few years plus significant financial resources and the willingness of coal-­\\nfired \\npower plants to take risks by trying them. The expected short-­\\nterm peak in Chi­\\nna’s scrubber market diminished the potential return on investment in indigenous \\ntechnology. The easy prospect of licensing foreign technologies also reduced the \\nincentive to take risks with indigenous innovations. All the major Chinese firms \\nin the market licensed foreign technologies in order to acquire and substantiate \\ntheir technological capabilities. No clear difference could be found among state-­\\nowned, university-­\\nestablished and nonstate firms. Even the nonstate firm that \\nmainly applied its own technology had to initially license from abroad.\\nAs tacit knowledge cannot be so easily transferred as codified knowledge, kno­\\nwhow played a positive role in establishing a sound market for technology. The \\ncontractual acquisition of know-­\\nhow presents more problems than licensing pat­\\nents (Arora et al., 2001b). However, in a developing country like China with poor \\nIPR protection, the licensing of patents might be unnecessary in the absence of \\nknow-­\\nhow as the knowledge contained in the patents have already entered the \\npublic domain. Chinese firms had generally chosen to legally license, rather than \\nto illegally acquire, SO2 scrubber technologies. Legal licensing secured a com­\\nplete package including systematic training, technical documentation and trade \\nsecrets in a relatively short timescale, without exposing the licensees to legal \\ndisputes. One alternative option was to recruit experts from foreign firms, but \\nthe legal risks were not insignificant and the received technologies may not be \\ncomplete because it would be difficult to recruit an entire team. It would also take \\nmuch longer for the acquiring firms to comprehend a technology by this means \\nthan they would through technology licensing. The associated costs would not be \\nlow either, because foreign experts generally had to be paid considerably more \\nthan standard Chinese salaries. Furthermore, illegal acquisition did not provide a \\ntechnological guarantee from a trusted provider, while this guarantee was stipu­\\nlated by coal-­\\nfired power plants in their tendering documents.\\nChina’s domestic firms could quickly absorb licensed technologies to meet the \\ntime constraints. From as early as the 1970s, China had, through its own research \\nand development on SO2 scrubbers, built up vital capabilities to establish domes­\\ntic firms and assimilate imported technology (Shu, 2003). From the mid-­\\n1970s \\nto the mid-­\\n1980s, China appraised several technologies, although on scales that \\nwere at least one or two orders of magnitude smaller than any commercial pro­\\nject. For example, a 300-­\\nMW unit corresponds to a flue gas flow rate of about \\n1,000,000 Nm3/hour (cubic meter at standard temperature and pressure per hour), \\nwhile the largest Chinese experiment at the time had a flow rate of 70,000 Nm3/hour \\n\\n\\nEnvironmental technology and industry  161\\n0.00%\\n0.25%\\n0.50%\\n0.75%\\n1.00%\\n1.25%\\n1.50%\\n1.75%\\n2.00%\\n2.25%\\n0\\n500\\n1,000\\n1,500\\n2,000\\n2,500\\n3,000\\n3,500\\n4,000\\n4,500\\n1995\\n2000\\n2005\\n2010\\n2015\\nRatio\\nl\\nl\\nu\\nf\\n \\n0\\n0\\n0\\n1\\n(\\n \\nl\\ne\\nn\\nn\\no\\ns\\nr\\ne\\np\\n \\nD\\n&\\nR\\n-\\n \\n)\\ne\\nl\\np\\no\\ne\\np\\n \\nt\\nn\\ne\\nl\\na\\nv\\ni\\nu\\nq\\ne\\n \\ne\\nm\\ni\\nt\\n)\\nB\\nM\\nR\\n \\n8\\n1\\n0\\n2\\n \\nn\\no\\ni\\nl\\nl\\ni\\nb\\n(\\n \\ne\\nr\\nu\\nt\\ni\\nd\\nn\\ne\\np\\nx\\ne\\n \\nd\\nn\\na\\nYear\\nR&D Personnel (Full-time Equivalent)\\nR&D expenditure\\nTechnology market transaction value\\nR&D expenditure vs. GDP (%)\\nTechnology market transaction value vs. GDP (%)\\nFigure 7.5  \\u0007\\nR&D personnel, expenditure and market value (in 2018 RMB) in China\\nSource: National Bureau of Statistics (1996–2019).\\n(Shu, 2003). From the mid-­\\n1980s to 2000, foreign technologies were demonstrated \\non a commercial scale (Gu, 2004; Shu, 2003). In 2000, having resulted in a consid­\\nerable fund of domestic human and technological capability, foreign technologies \\nwere officially recognized as the basis for further development of SO2 scrubber \\ntechnologies in China (National Economic and Trade Commission, 2000). China’s \\nabsorptive capacities were effectively distributed to all major firms including non­\\nstate ones through a free labor market of engineers and managers.\\nRecognizing the constraints of technology licensing such as on expansion \\nbeyond China, in the past two decades, China has put a much heavier empha­\\nsis on research and development (R&D). In 2000, China had 922,000 full-­\\ntime \\nequivalent personnel on R&D and this number rapidly grew by 375% to 4.4 mil­\\nlion in 2018. R&D expenditures were raised from 0.60% of gross domestic \\nproduct (GDP) in 1995 to 2.19% in 2018 (Figure 7.5). A much more vibrant mar­\\nket for technology emerged and the transaction value increased from 0.46% of \\nGDP in 1995 to 1.97% in 2018 (Figure 7.5). Together with the rapid growth of \\nChina’s GDP, the R&D expenditures and technology market transaction values \\nhad become 1084% and 1365% greater in 2018 from the levels in 2000 in real \\nterms (Figure 7.5). This R&D boom strengthened China’s capacity to absorb for­\\neign technologies and innovate domestic intellectual property. In the category of \\nenvironmental technology, China’s residents and nonresidents were granted 103 \\nand 69 patents, respectively, in 2000 in China’s patent filing office, which were \\nabout 10% of those in the United States. They grew to 7,459 and 881 patents, \\n\\n\\n162  Environmental technology and industry\\nrespectively, in 2018, while the figures in the United States were correspondingly \\n1,258 and 1,369 patents (Figure 7.6).\\n2.2  \\u0007\\nThe strategy of foreign technology licensors\\nThe strategy of potential foreign technology licensors was also shaped by the pre­\\nviously mentioned three characteristics of China’s SO2 scrubber demand under a \\ngoal-­\\ncentered SO2 mitigation path. First, the huge demand for SO2 scrubbers created \\nprofitable business opportunities. Their decision of technology licensing involves \\nthe revenue effect (i.e., payments received from licensing) and rent-­\\ndissipation effect \\n(i.e., revenue loss due to a new or strengthened competitor in the product market; \\nArora and Fosfuri, 2003). A stronger revenue effect promotes the decision to license, \\nwhile a stronger rent-­\\ndissipation effect discourages licensing. For major foreign \\nfirms that held intellectual property of SO2 scrubber technologies, the option to do \\nnothing was rarely attractive because of the temptation of the huge emergent Chi­\\nnese market. The revenue effect was indeed significant. Technology licensing only \\nrequired a small office in China to monitor licensees and to “service” the partnership. \\nFor example, each of the two interviewed American firms had an office in Beijing \\nwith about five staff members, whereas their licensees were in charge of contracts \\nworth several hundred million dollars annually. The initial cost in transferring tech­\\nnologies was covered by up-­\\nfront lump-­\\nsum fees paid by licensees (Table 7.1). The \\n0\\n3,000\\n6,000\\n9,000\\n12,000\\n15,000\\n18,000\\n21,000\\n1980\\n1985\\n1990\\n1995\\n2000\\n2005\\n2010\\n2015\\n)\\ny\\ng\\no\\nl\\no\\nn\\nh\\nc\\ne\\nt\\n \\nl\\na\\nt\\nn\\ne\\nm\\nn\\no\\nr\\ni\\nv\\nn\\ne\\n(\\n \\ne\\nc\\ni\\nf\\nf\\no\\n \\ng\\nn\\ni\\nl\\ni\\nf\\n \\ny\\nb\\n \\ns\\nt\\nn\\na\\nr\\ng\\n \\nt\\nn\\ne\\nt\\na\\nP\\nYear\\nChina: Resident\\nChina: Nonresident\\nU.S.: Resident\\nU.S.: Nonresident\\nOthers: Resident\\nOthers: Nonresident\\nFigure 7.6  \\u0007\\nPatents on environmental technology by filing office in the world\\nSource: WIPO (2019).\\n\\n\\nEnvironmental technology and industry  163\\ncommercial success of licensees would result in considerable royalties to the licensor \\nif the contracts were honored. After the know-­\\nhow and trade secrets were transferred, \\nthe intellectual property rights were at risk of misuse or infringement, possibly with \\nthe royalties not being fully paid. Despite this, most foreign firms decided to take this \\nrisk in order to avoid the much greater risk inherent in direct investment.\\nAfter technologies are transferred, one primary concern of technology licensors \\narose on whether licensees paid royalties honestly. Both licensors and licensees \\nreported in interviews that major Chinese firms were paying royalties regularly. Also, \\nseveral expiring licenses had been renewed, indicating a good record of royalty pay­\\nments. As a preventative measure, design software was encrypted and only specially \\nprepared computers could install it with annual reregistration. Several interviewees \\nin the Chinese firms said that, after a few years, they had figured out what was inside \\nthe black box but still chose to pay royalties. It was not very difficult to keep track of \\nlicensees. The huge size of SO2 scrubbers often made local news and the Ministry of \\nEnvironmental Protection annually published details of every SO2 scrubber and its \\ncontractor (Ministry of Environmental Protection, 2011a). Besides, a good partner­\\nship with licensors suited the long-­\\nterm interests of licensees. Technological sophis­\\ntication had increased step by step in the Chinese SO2 scrubber market as reflected \\nin the unit scales: the 300-­\\nMW scale was dominant before 2005, but after 2006, the \\n600-­\\nMW scale became crucial and then the 1,000-­\\nMW scale or greater (Ministry \\nof Environmental Protection, 2014). Every significant increase in scale indicated a \\nnew technical advance. Accordingly, the licensing of scrubber technologies was a \\ncontinuous operation and not a one-­\\noff process. Good partnerships, strengthened \\nby honest royalty payments, could also help licensees expand into new markets \\nthrough future technology licensing. In addition, a partnership may generate busi­\\nness opportunities for both sides. For example, when a large coal-­\\nfired power plant \\nin Hong Kong decided to install SO2 scrubbers, it first approached several interna­\\ntional firms, including one from the United States. But the American firm was fully \\ncommitted in the domestic market and was not willing to take the financial risk of \\nan Engineering, Procurement, and Construction (EPC) project in Hong Kong. Its \\nChinese licensee was introduced and finally won the contract.\\nRoyalty rates may decrease over time to reduce the costs of honoring licensing \\ncontracts. For example, one license divided the ten-­\\nyear contract period into three \\nphases with declining royalty rates. In several other cases, the royalty rate was rene­\\ngotiated when competition in the market became much too fierce to significantly \\nshrink the profit margin. Excessively high royalty rates could damage licensees’ \\ncompetitiveness. The final result might be a reduced income from royalties and \\nan increased risk of no payment being made at all. The renegotiation strengthened \\nthe partnerships between licensors and licensees and thus worked for the inter­\\nests of both sides. In one licensing contract signed in 1998, the level of royalties \\nwas originally associated with the volume of flue gases. Because China’s capital \\ncosts of installing SO2 scrubbers had dropped substantially since then (Figure 7.2), \\nthe royalty rate would increase significantly as a percentage of the contract value. \\nRenegotiation took place to lower the royalty rate. The partnership remained strong \\nwith both the licensor and the licensee maintaining market success.\\n\\n\\n164  Environmental technology and industry\\nLawsuits, particularly those resolved outside China, were also a deterrent to \\npotential infringement, which maintained the strong revenue effect. For example, \\nInsigma Technology is a Chinese firm listed on the Shanghai Stock Exchange, and \\nit releases information regularly. It signed a technology licensing contract with \\na French firm in December 2004 (Table 7.1). However, in April 2006, Insigma \\ndeclared that it would cancel the contract and thereafter stop using the licensed \\ntechnology. Royalties were paid for six projects in 2005 and 2006 with a total \\ncapacity of 7,450 MW (Sina Finance, 2010). The firm later signed a new contract \\nwith an Italian firm in September 2006, which was for one year and was to be \\nautomatically renewed if no objections were received from either side. The fee \\nfor royalties was a fixed sum of €20,000 (US$26,600) for every project regardless \\nof the contract value (Sina Finance, 2010). The French firm later sued Insigma in \\nSingapore (where disputes should be resolved according to the licensing contract). \\nThe court made a decision in February 2010 and Insigma was ordered to pay com­\\npensation of US$2,085,737 for the loss of royalties in 2005 and US$24,566,684 \\nfor the loss afterward (Sina Finance, 2010). The lawsuit may have helped deter \\nother significant licensees from not honoring their licensing contracts.\\nSecond, low-­\\nquality requirements and correspondingly low technological \\nmarket-­\\nentry barriers led to active market entry of new firms to contain the rent-­\\ndissipation effect for technology licensors. If the downstream operations of a firm \\nare small or the downstream market is in fierce competition, the rent-­\\ndissipation \\neffect will be limited and technology licensing becomes more likely (Arora and \\nGambardella, 2010). Indeed, the Chinese downstream SO2 scrubber market was \\nnewly created and in fierce competition (Ministry of Environmental Protection, \\n2011a). In addition, market evolution also demonstrated that the rent-­\\ndissipation \\neffect should be minimal. Foreign firms tended to lag behind domestic ones in \\nunderstanding the market’s real demand, especially in the early period. Among all \\nthe foreign firms, the examined Japanese firm ought to be the best prepared for \\nthe Chinese market. It owned more Chinese patents on flue gas desulfurization \\nthan any other firm (State Intellectual Property Office, 2010) and, between the late \\n1980s to 1990s, had won contracts to install China’s first-­\\never commercial wet \\nSO2 scrubbers (four units of 360-­\\nMW capacity; Gu, 2004). However, up to the \\nend of 2010, its technology was only applied to a further 3,300 MW, with the final \\nproject in 2006 (Mitsubishi Heavy Industries, 2011). Interviews in China revealed \\nthat many foreign firms generally licensed design software together with other \\nknow-­\\nhow in order to enable their Chinese licensees to compete independently, \\nbut this Japanese firm was reluctant to hand over design software and wanted to \\nparticipate more actively. Thus, the technology transfer of know-­\\nhow was not \\ncomplete. The decision could have been influenced by the expectedly significant \\nrent-­\\ndissipation effect due to potentially high rents as a result of its favorable \\nposition in granted patents. However, partly because the relationship made them \\nslower in responding to the market and hampered their competitiveness, its Chi­\\nnese licensees decided instead to do business with other technology licensors. For \\nexample, according to the annual reports from a firm listed on the Shanghai Stock \\nExchange – Jiulong Electric, the holding firm of Yuanda Environmental Protection \\n\\n\\nEnvironmental technology and industry  165\\nEngineering – although US$1.1 million was paid to the Japanese firm as the up-­\\nfront lump-­\\nsum fee, just two years later it decided to sign another licensing con­\\ntract with a European firm and gave up the Japanese technology (Table 7.1). Even \\nwith the tight control of technology licensing, the Japanese firm earned little profit \\nor rent from the Chinese market, an indication of a small rent-­\\ndissipation effect. \\nThe existence of many technology licensors diminished the rent-­\\ndissipation effect \\nbecause no single licensor had significant market power.\\nThird, time constraints discouraged direct participation of foreign technology \\nlicensors in the Chinese market. Two interviewed American firms each had a \\nsmall representative office in Beijing, but their licensing strategies were notably \\ndifferent. They reported that the Chinese government put no restrictions on allow­\\ning foreign firms to bid for SO2 scrubber projects, but many foreign firms did not \\nexpect that they would earn significant profits by establishing subsidiaries or joint \\nventures in China. One major American firm expected the Chinese market to peak \\nfor only a few years before it began shrinking; this expectation proved prescient \\n(Figure 5.12). The initial investment of capital and human resources to establish a \\nsubsidiary in China would therefore only be of temporary benefit. The firm’s past \\nexperience in other countries suggested that direct investment could not be freely \\nwithdrawn, and accordingly, it was not justified in this particular Chinese market. \\nIn addition, the lack of adequate human resources also constrained some foreign \\nfirms from choosing direct investment, particularly due to the revived U.S. market \\nfor SO2 scrubbers (U.S. Energy Information Administration, 2011).\\n2.3  \\u0007\\nWhy technology market can emerge in China?\\nEven in developed countries – as Gans and Stern argue – an effective market for \\ntechnology is difficult to establish because it often fails to satisfy the three criteria \\nof effective market design as specified by Roth that successful marketplaces must \\nbe “thick, uncongested and safe” (Gans and Stern, 2010; Roth, 2008). The Roth \\ncriteria were proposed to fix broken markets or build new ones if they are missing, \\nwhich could be especially useful for environmental protection as market failure \\nis often the cause. First, an efficient market requires many potential buyers and \\nsellers, or market thickness, to enhance the chances of effective matching. How­\\never, many ideas are not independent but reliant on other complementary ideas and \\nassets to achieve their full value, with notable examples in low-­\\ncarbon technolo­\\ngies (Harvey, 2008). This problem makes the licensing of a single idea less desir­\\nable. If the ideas belong to different entities, ineffective coordination could limit \\nthe willingness of potential buyers and sellers to participate in the market. Second, \\nthe market should overcome Roth’s “congestion” criterion, whereby buyers and \\nsellers should be able to negotiate with a number of possible trading partners and \\nhave sufficient time to make effective selections. In a congested market, competi­\\ntion is not sufficient and the price does not reach market equilibrium. Because nec­\\nessary information disclosure for buyers to assess a technology’s value might lead \\nto unwanted diffusion, the information is often kept secret between buyers and sell­\\ners to constrain open market competition, thus failing the “congestion” criterion. \\n\\n\\n166  Environmental technology and industry\\nThird, market transactions should be “safe”; that is, conducted in good faith and \\nwith safeguards that allow the expression of real intention and information and \\nresult in mutual satisfaction. A drawback on this point is that, after licensors have \\ndisclosed information, licensees might be able to exploit it independently, without \\nsigning licensing contracts, creating issues over misuse of intellectual property.\\nThe Chinese market for SO2 scrubber technologies satisfied all three Roth crite­\\nria. Key contributing factors could include China’s large market size, the maturity \\nof available technologies and goal-­\\ncentered governance. First, because the size of \\nthe Chinese market for SO2 scrubbers as a downstream market for the technolo­\\ngies is far greater than any other country, major foreign SO2 scrubber firms, as \\npotential licensors, could hardly overlook the potential business opportunities. \\nThe large market and low technological barriers facilitated by technology licens­\\ning have created many domestic firms as potential licensees. Multiple sellers from \\nthe United States, Europe and Japan actively licensed out their technologies (Xu \\net al., 2009, 2006). In addition, in the Chinese market up to 2010, 16 firms – all \\nChinese – had completed at least 10 GW of SO2 scrubbers, all using licensed-\\n­\\nin foreign technologies (Xu et al., 2006; Ministry of Environmental Protection, \\n2011a). The three types of Chinese firms – state-­\\nowned, university-­\\nestablished \\nand nonstate – did not show significantly different behavior in the market for \\ntechnology. Fierce competition drove down costs and diminished expected profit \\nfrom direct investment, but revenue from technology licensing was significant. \\nThe rent-­\\ndissipation effect was overwhelmed by the revenue effect of technology \\nlicensing, which accordingly became a dominant choice of foreign firms. As a \\nlarge country, China has a strong capacity to absorb new technology due to its \\nprevious R&D, and this capacity was effectively distributed to all three types of \\nfirms through a free labor market. Licensors and licensees held multiple bilateral \\nnegotiations simultaneously to help solve the market congestion problem. Fur­\\nthermore, the safety of technology licensing also benefited from China’s large \\nmarket size. As a result of the large market, there were significant revenues from \\nroyalties that encouraged licensors to transfer complete packages of technolo­\\ngies. The market for SO2 scrubbers at every unit scale was substantial and the \\nunit scales escalated over time to require continuous technological support from \\nlicensors. Such dynamism favored long-­\\nterm partnerships between licensors and \\nlicensees for their mutual benefit and fostered honest royalty payments.\\nSecond, the maturity of SO2 scrubber technologies played a crucial facilitating \\nrole. After several decades of commercial deployment in developed countries, \\nmany firms had acquired complete technology packages. Personal and corporate \\nexpertise, or know-­\\nhow as tacit knowledge, was a vital part of the technology \\npackage. Acquiring knowhow raised costs and contracting problems, but given \\nthe inadequate standard of IPR protection in China, technology licensing became \\nnecessary in order to acquire complete packages of technologies. Many foreign \\nfirms had become independent technology holders, and a potential licensee only \\nneeded to negotiate with one licensor for a complete technology package. When \\ndeciding whether to license out technologies or set up direct subsidiaries in devel­\\noping countries or even just do nothing, firms from developed countries needed \\n\\n\\nEnvironmental technology and industry  167\\nto compare the expected profits of each market option. The dominant business \\nreality in the market was technology licensing. For a potential licensee, the tech­\\nnology could either be developed internally or acquired externally. Favorable con­\\nditions created the demand for foreign technologies in the Chinese market.\\nThe Chinese market also met the second Roth criterion on the lack of con­\\ngestion. The maturity and wide deployment of SO2 scrubbing technologies also \\nenabled a fairly accurate estimation of the technology’s value to facilitate mar­\\nket transactions. Interviews revealed that, although the negotiation of technology \\nlicensing was generally bilateral, without disclosing information to third parties, \\nlicensors and licensees often negotiated with several entities on the other side at \\nthe same time for most suitable licensing contracts. IPR protection is recognized \\nas a key means to ensure market safety and satisfy the third Roth criterion (Gans \\nand Stern, 2010). As examined earlier, know-­\\nhow and credible threat of lawsuits \\nensured the general satisfaction of this criterion. The disclosure of the necessary \\ninformation for value assessment in negotiations caused fewer problems because \\nknowhow could not be easily acquired.\\nThe existence of many potential licensees enabled licensors to design their \\nstrategies to maximize profit. At least three clear strategies emerged among three \\nlicensors. A major American firm licensed to only two Chinese firms and built up \\nlong-­\\nterm partnerships through full technical support. One license was restricted \\nto the licensee’s home province for a certain period and the other covered the \\nwhole of mainland China. The licensees had a near monopoly to use the specific \\ntechnology in their assigned market territories. Another significant American firm \\nhad about eight licensees in China; the strategy was to increase the market share \\nof its technology as well as its royalties, but the licensees were still selected so as \\nto prevent unqualified ones from ruining the technology’s reputation. In addition, \\nas mentioned earlier, a Japanese firm licensed its technology to a few Chinese \\nfirms but, unlike the two American firms, refused to transfer design software. The \\ntwo American firms had their technologies widely applied but the Japanese tech­\\nnology was abandoned without much deployment. From the perspective of the \\nlevel of royalties, the two American strategies were clear winners.\\nAn effective market for cutting-­\\nedge technologies is understandably more \\ndifficult to establish. It is probable that not many organizations have acquired \\nintellectual property as potential licensors. The value of a particular cutting-­\\nedge \\ntechnology is harder to assess and the accumulation of know-­\\nhow may still be in \\nprogress with a consequently high price of the final product which will limit its \\ndeployment. These unfavorable conditions discourage the emergence of potential \\nlicensees. Information disclosure to facilitate licensing will also raise more con­\\ncerns on the part of technology owners. As a result, the Roth criteria of effective \\nmarket design will be harder to meet for cutting-­\\nedge than for mature technologies.\\nThird, goal-­\\ncentered governance resulted in a path of SO2 mitigation to signifi­\\ncantly lower market-­\\nentry barriers for domestic firms. The previous two factors \\nare mainly given, while governance strategy could be more deliberately taken. \\nFor developing countries that have not established a sound rule of law and strong \\ndomestic industries for pollution removal, goal-­\\ncentered governance may induce \\n\\n\\n168  Environmental technology and industry\\na feasible path for improvement. In order to meet time constraints and technologi­\\ncal requirements, major Chinese firms universally licensed in foreign technolo­\\ngies to quickly build technological strength. In the early period, China had not \\nestablished a system to well implement environmental policies and thus many \\nSO2 scrubbers were not operating normally. For meeting governmental regula­\\ntions, coal-­\\nfired power plants chose to install the cheapest SO2 scrubbers but did \\nnot expect to run them. For domestic firms that had no technological advantages, \\nthis initially low but escalating requirements on the quality of SO2 scrubbers pro­\\nvided helpful stepping-­\\nstones to enter the market.\\nThe utilization of wind energy followed a comparable path under goal-­\\ncentered \\ngovernance, which also helped to lower market-­\\nentry barriers for the establish­\\nment of a domestic wind turbine industry. Similar to the SO2 mitigation case, the \\ninitial stage of wind energy development also focused more on the deployment \\nto follow the goal-­\\ndriven demand. In China’s 11th Five-­\\nYear Plan for Renew­\\nable Energy Development, the major goal for wind electricity referred to gen­\\neration capacity whereas actual electricity generation served as a supplementary \\ngoal (NDRC, 2008). One average kilowatt-­\\nhour of wind capacity consistently \\ngenerated much less electricity in a year in China than in the United States, and \\nthis partly indicated poorer operating conditions in China (Figure 7.7). When the \\ndeployment of wind turbines became sufficiently wide, the Chinese government \\nstarted to pay more attention to their operation. Problems in the quality and opera­\\ntion of wind turbines emerged with their deployment to threaten not just wind \\n0\\n20\\n40\\n60\\n80\\n100\\n120\\n140\\n160\\n180\\n200\\n0\\n50\\n100\\n150\\n200\\n250\\n300\\n350\\n400\\n2000\\n2002\\n2004\\n2006\\n2008\\n2010\\n2012\\n2014\\n2016\\n2018\\nWind capacity (1,000 MW)\\n)\\nh\\nW\\nT\\n(\\n \\ny\\nt\\ni\\nc\\ni\\nr\\nt\\nc\\ne\\nl\\ne\\n \\nd\\nn\\ni\\nW\\nYear\\nWind electricity: China (left)\\nWind electricity: United States (left)\\nWind capacity: China (right)\\nWind capacity: United States (right)\\nFigure 7.7  \\u0007\\nWind energy development in China and the United States\\nSource: BP (2019).\\n\\n\\nEnvironmental technology and industry  169\\nelectricity generation but, more important, also the safety of the electric grid and \\nto push for greater focus and higher requirements (SERC, 2011). In 2010, the \\nNational Energy Administration published a plan to enact 247 technical stand­\\nards for wind energy development, including several which were already in force \\n(National Energy Administration, 2010). Lower technological market-­\\nentry bar­\\nriers played a positive role to encourage new firms. In 2006, the Chinese market \\nhad 12 firms that supplied wind turbines, and the number rose to 29 in 2012 (Shi, \\n2007; China Wind Energy Association, 2012). Many component suppliers along \\nthe supply chain also actively entered the market (Chinese Wind Energy Equip­\\nment Association, 2011). Compared to wind turbine manufacturers, market-­\\nentry \\nbarriers were even lower and the technologies were less complex for component \\nsuppliers, and this resulted in fiercer competition and thinner profit margins.\\nFurthermore, unlike SO2 scrubber firms, the Chinese firms in the wind industry \\nlicensed their technologies from a very different category of foreign firms. Foreign \\nlicensors of SO2 scrubber technologies were generally major firms that were closely \\ninvolved in the downstream business of installing SO2 scrubbers (Xu, 2011a). In \\ncontrast, major foreign wind turbine manufacturers were largely reluctant to license \\ntechnologies to Chinese firms, and most foreign licensors were design firms or small \\nmanufacturers that focused more on upstream technological development. This \\nphenomenon is explained in the theory of markets for technology as the rational \\nchoice based on the respective industrial structure (Arora and Gambardella, 2010). \\nThe good-­\\nenough quality, lower price and no geographic constraints of technology \\nlicenses made the Chinese domestic wind industry potentially competitive.\\nThe market for technology might also work for other large developing coun­\\ntries, such as India. They may also have potentially large markets through which \\nto spawn many domestic operators and fierce competition. Many other low-­\\ncarbon \\nand pollution-­\\ncontrol technologies have been commercialized with much know-­\\nhow. A caveat is that these large developing countries may not necessarily always \\nhave large domestic markets for pollution mitigation. These are partly determined \\nby government policies and not just by the overall sizes of their economies. Their \\nabilities to take on board foreign technologies might not be consistently strong. \\nHowever, there is great potential for large developing countries to make use of mar­\\nkets for technology to build their industrial prowess with mature technologies. Goal-­\\ncentered governance may provide more feasible pathways for domestic industries in \\nthese developing countries to take roots and further grow from weak starting points.\\n3  \\u0007\\nEnvironmental industry under goal-­\\ncentered SO2 \\nmitigation path\\n3.1  Market entry and competition\\nConsidering both firms that pollute the environment and others that provide pol­\\nlution removal facilities, the impacts of the goal-­\\ncentered SO2 mitigation path in \\nChina may not be straightforward. On one hand, although empirical studies gen­\\nerated mixed results on the “pollution haven hypothesis” in the Chinese context \\n\\n\\n170  Environmental technology and industry\\n(Levinson and Taylor, 2008; He, 2006; Shen, 2008), its key root cause – poor \\nenvironmental regulation, including weak policies and poor enforcement  – is \\nargued to potentially benefit polluting firms for not acting on, delaying or comply \\nonly partially with pollution control (Harney, 2008). In China, policies on envi­\\nronmental protection and business standards were recognized by polluting firms \\nas less important barriers to market entry (Niu et al., 2012). Relative to the Euro4 \\nfuel quality standards, the poorer Euro2 standards in China could reduce costs by \\n1.1 and 1.9 U.S. cents per gallon for gasoline and diesel, respectively (Liu et al., \\n2008). The cost burden also acts as a political and regulatory hurdle to bring pol­\\nluting firms under full compliance. On the other hand, from the perspective of \\nsupplying pollutant removal facilities, weak regulation could lower market-­\\nentry \\nbarriers to encourage competition, innovation and the establishment of industrial \\ncapacities for pollution control (Stigler, 1971; Dean and Brown, 1995).\\nTwo important barriers on the supply side could slow down the deployment \\nof SO2 scrubbers in China. No existing supply capacity could meet the unprec­\\nedented peak demand of over 100 GW a year (Figure 5.12). The capital costs of \\nabout US$65 to 90/kW (Figure 7.2) were initially too high, being over 10% of \\nthe costs of building new coal-­\\nfired power plants (SERC, 2006). If the large labor \\nforce and industrial base in China could be effectively mobilized for the deploy­\\nment of SO2 scrubbers, the supply capacity would not have a major problem in \\nmeeting the rapidly growing demand. The lack of significant restrictions on for­\\neign direct investment indicates that both foreign and domestic firms could tap \\ninto the labor force.\\nThe huge Chinese market can easily accommodate many SO2 scrubber firms \\nwithout losing economies of scale. Whether the supply potential could be released \\ndepends on whether existing firms could expand their capacity and (more impor­\\ntantly) whether new firms could emerge. Although the U.S. market had only \\nabout ten firms, and with new firms rarely entering, the Chinese market had over \\n60 firms – almost all of which were newly established, most being domestic but \\nsome being foreign – thereby indicating much lower market-­\\nentry barriers (Fig­\\nure 7.8). In the past decade, the annually added capacity of SO2 scrubbers increased \\nsignificantly both in China and the United States, but the evolution of unit capital \\ncosts showed a rapid cost reduction in China and a cost spike in the United States \\n(Figure 7.2). In China, the rapidly rising demand triggered intensive market entry \\nto create fierce competition followed by a cost reduction whereas competition in \\nthe United States was rather limited, and this constrained the expansion of the sup­\\nply capacity. When the demand for SO2 scrubbers grew, the price was pushed up.\\nAs discussed earlier, domestic firms did not have technological advantages, \\nespecially in the early period. Nevertheless, because of the existence of many \\npotential licensors in the technology market, no foreign firm was able to prevent \\nothers from licensing technologies to China. Technologies therefore could not be \\nused as a barrier to exclude Chinese firms from competing. The crowded market \\nenabled fierce competition not just for providing SO2 scrubbers. Competition also \\ntook place between foreign firms for licensing to especially promising Chinese \\nfirms that were expected to win many projects and return significant revenues \\n\\n\\nEnvironmental technology and industry  171\\n0\\n10\\n20\\n30\\n40\\n50\\n60\\n70\\n0\\n2\\n4\\n6\\n8\\n10\\n12\\n14\\n2000 2002 2004 2006 2008 2010\\n2000 2002 2004 2006 2008 2010\\nNumber of FGD companies in the Chinese market\\nt\\ne\\nk\\nr\\na\\nm\\n \\n.\\nS\\n.\\nU\\n \\ne\\nh\\nt\\n \\nn\\ni\\n \\ns\\ne\\ni\\nn\\na\\np\\nm\\no\\nc\\n \\nD\\nG\\nF\\n \\nf\\no\\n \\nr\\ne\\nb\\nm\\nu\\nN\\nYear\\nNew entry\\nExisting\\nUnited States\\nChina\\nFigure 7.8  \\u0007\\nFirms in the Chinese and U.S. markets installing 100-MW-scale or greater SO2 \\nscrubbers\\nSource: Ministry of Environmental Protection (2008–2012); EIA (2007–2011); Xu (2013).\\nNote: “Existing”: firms have been in the market in the past. “New entry”: firms entering the market for \\nthe first time. The U.S. numbers use the left axis, and the Chinese numbers use the right axis.\\nfrom royalties. Those potential licensees were mainly established by coal-­\\nfired \\npower producers. Interviews showed that financial payments were the most criti­\\ncal aspect of negotiating licenses, although other aspects were also important, \\nsuch as the suitability of technologies and the scope of licenses. The willingness \\nto accept lower up-­\\nfront lump-­\\nsum fees and lower royalty rates made a licensor \\nmore competitive. After the significant variance of early contracts, the up-­\\nfront \\nlump-­\\nsum fee stabilized to be about US$1.2 million for wet scrubbers (Table 7.1).\\n3.2  \\u0007\\nInternational competitiveness of China’s SO2 scrubber industry\\nDue to specific features in various environmental fields, goal-­\\ncentered govern­\\nance may present very different impacts on different environmental industries. \\nOne significant difference is on the international competitiveness of China’s SO2 \\nscrubber and wind turbine industries, as could clearly be seen from the reaction \\nof the United States to China’s rising industrial prowess. Over the same period \\nas China’s rapid growth was taking place, the United States also witnessed sig­\\nnificantly wider deployment. From 2004 to 2010, its SO2 scrubber capacity grew \\nfrom 100 GW to 181 MW and its wind capacity from 6.8 GW to 40.3 GW (EIA, \\n\\n\\n172  Environmental technology and industry\\n2012–2013). “The China Price” was a critical reason for trade disputes between \\nChina and the United States. In 2010, the price tag of SO2 scrubbers in China was \\nabout US$20/kW as revealed in the author’s fieldwork, whereas in the United \\nStates, it was US$206/kW (EIA, 2012–2013). For wind turbines, the average \\nprice in 2010 was US$700/kW in China and US$1,460/kW in the United States \\n(Figure 7.9). However, China’s SO2 scrubbers barely made any news in trade dis­\\nputes between the two countries while those of wind turbines were highly visible \\n(Cooper, September 28, 2012). From another perspective, the Chinese SO2 scrub­\\nber industry did not contribute to international SO2 mitigation whereas its wind \\nindustry strengthened the global CO2 mitigation capability.\\nDespite the success in building up the supply capacity and achieving cost \\nreduction, China’s large SO2 scrubber industry did not become competitive in \\nthe international market as indicated by the nearly tenfold price difference in the \\nsegregated Chinese and U.S. markets (Figure 7.2). Many SO2 scrubbers were of \\nlow quality, and this increased the operation and maintenance costs and shortened \\ntheir lifetimes. Although the delayed improvement of the operation of SO2 scrub­\\nbers was critical for lowering the initial quality requirement and technological \\nbarriers to market entry, after 2007 when the normal operation of SO2 scrubbers \\nwas largely expected, the prices stayed low. The gap between 2002 and 2007 \\nwas too long and China was trapped in a low-­\\nquality bottom. The huge quality \\n0\\n200\\n400\\n600\\n800\\n1,000\\n1,200\\n1,400\\n1,600\\n1,800\\n0\\n5\\n10\\n15\\n20\\n)\\nW\\nk\\n/\\n$\\n(\\n \\ne\\nc\\ni\\nr\\np\\n \\ne\\nn\\ni\\nb\\nr\\nu\\nt\\n \\nd\\nn\\ni\\nW\\nAnnual installation of wind turbines (1,000 MW)\\nUnited States (2004–2010)\\nChina (2004–2010)\\nFigure 7.9  \\u0007\\nAverage prices of wind turbines in China and the United States\\nSource: IEA and ERI (2011); Wiser and Bolinger (2012); BP (2019); Xu (2013).\\n\\n\\nEnvironmental technology and industry  173\\npremium presented serious financial challenges to power corporations. In addi­\\ntion, the quality of SO2 scrubbers was quite opaque to investors, and only the SO2 \\nscrubber firms had the best knowledge of the product. In the five gap years, a race \\nto the bottom had pushed the quality and price of SO2 scrubbers to reach a mini­\\nmum and stable level. Because no SO2 scrubber firm had established a reputation \\nfor quality, any significant price increase would put the firm in a disadvantageous \\nposition in competition. Even when China started to allow BOT (Build, Operate, \\nTransfer) contracts for SO2 scrubbers to better integrate the decisions of capi­\\ntal investment and daily operation (NDRC and SEPA, 2007), the trap remained \\na difficult one to escape from. Another important reason for the segregation of \\nthe Chinese and U.S. SO2 scrubber markets lay in the restriction of technology \\nlicensors. Almost every major Chinese SO2 scrubber firm licensed and relied on \\nforeign technologies that felt themselves constrained in the Chinese market (Xu, \\n2011a). Even projects in Hong Kong required special permission from technology \\nlicensors.\\nHowever, the lower market-­\\nentry barrier at the early stage of wind energy \\ndevelopment was still much higher compared to that of SO2 scrubbers. Although \\ncosts were much lower in China than in the United States, a race to the bottom on \\nquality and price did not happen and the price of China’s wind turbines remained \\nstable (Figure 7.9). The operational requirement never dropped to a bottom as in \\nthe SO2 scrubber case. One critical reason lied in their different regulatory foun­\\ndations. Although the enforcement capacity for the deployment and operation of \\nSO2 scrubbers could be built on the existing regulatory system, the weak environ­\\nmental policy enforcement indicated that such a system had not been satisfactorily \\nestablished in China. In comparison, the compliance monitoring system for wind \\nelectricity delivery had been largely established despite wind energy being a new \\nenergy type for electricity supply. Furthermore, because electricity generation has \\ndirect and significant economic benefits to local governments, the political will \\nfor greater demand and better management was much stronger than in the case \\nof SO2 scrubbers. Because the poor operation or quality of wind turbines would \\naffect wind electricity generation and thus the revenue, investors in wind farms \\nvalue quality substantially more than those investing in SO2 scrubbers.\\nDespite the highly visible trade disputes between China and the United States, \\nthe actual trade in wind turbines was minimal. In 2011, the total capacity of \\nexported wind turbines was equivalent to only 1.3% of that installed domesti­\\ncally (China Wind Energy Association, 2012). Although four Chinese wind tur­\\nbine manufacturers had been ranked among the largest ten in the world, unlike the \\nother six as regional or global suppliers, they remained largely domestic (Li et al., \\n2011). Besides other influential factors, one important reason could be the quality \\ngap that made the Chinese wind turbines fail to reach the technological market-­\\nentry barriers in developed countries. However, the Chinese wind industry could \\nhave a promising future. If the price difference between China and the United \\nStates were taken as the upper limit of the quality premium or the depth of the \\nquality trap, the wind industry would be much more likely to escape the trap than \\nthe SO2 scrubber industry.\\n\\n\\n174  Environmental technology and industry\\nAs demonstrated in the two comparative case studies, the depth of the low-­\\nquality trap could be determined by how long the operational improvement of \\npollution control facilities is delayed. The delay should be long enough for the \\ndomestic supply capacity to become established but short enough to prevent a \\nrace to the bottom on quality and price. Another influential factor on the depth \\nof the trap is how strong the initial enforcement capacity is. Because electricity \\ngeneration corresponds to much stronger enforcement capacity than the mitiga­\\ntion of conventional pollutants, China could have a better chance to build inter­\\nnationally competitive industries for renewable energy that generally has to be \\nconverted into electricity. Low market-­\\nentry barriers for quality and technological \\nadvancement are a key factor to make the Chinese market and industrial develop­\\nment vibrant. In the later upgrading, China could focus more on raising the corre­\\nsponding requirements but on keeping other barriers low to minimize the negative \\nimpacts of such enhancement.\\n4  \\u0007\\nInter-­\\ngoal coordination under goal-­\\ncentered governance\\nChina’s Five-­\\nYear Plans feature multiple goals in several fields, including econ­\\nomy, social development, environmental protection and resource conservation. \\nGoals on economic growth rates are always the first one in the goal table in each \\nFive-­\\nYear Plan, while they have been listed as “expecting” since the 11th Five-­\\nYear Plan when goals were first differentiated between “expecting” and “binding” \\n(National People’s Congress, 2001, 2006, 2011, 2016, 1996). Although goals on \\nenvironmental protection have been gaining importance and become “binding,” \\nthe relationship between economic development and environmental protection is \\nstill crucial to profoundly affect the sustainability of the environmental political \\nwill and the achievement of environmental goals. One pivotal concern is how to \\ncoordinate various goals for maximizing their potential synergies and minimiz­\\ning conflicts. SO2 mitigation and economic development have two-­\\nway impacts. \\nFirst, SO2 mitigation is one constraint for economic development. Energy con­\\nsumption and economic growth are fundamental drivers of SO2 emissions, whose \\nmitigation thus reversely becomes a limiting factor. Second, SO2 mitigation also \\nrelies on the emergence and development of a pollution removal industry to fea­\\nsibly provide the technological means of SO2 mitigation, which could create new \\njobs and economic opportunities.\\nOver the past four decades, central economic planning has also gradually \\nshifted toward decentralized market evolution. Various local governments are also \\nactively competing with each other in establishing local industries that can serve \\nthe huge national market. One key feature of the four-­\\ndecade economic reform \\nhas been the gradual peeling of constraints on the market. The state-­\\nowned sec­\\ntor has been generally retreating and those remaining ones are more profit-­\\ndriven \\nthan like governmental agencies. China’s economic reform has created many mar­\\nkets from a negligible basis after the Cultural Revolution and greatly enhanced \\nthe importance of the markets. The boundary between the state and the market has \\nalso become clearer.\\n\\n\\nEnvironmental technology and industry  175\\nChina’s SO2 mitigation path as examined earlier surely has contributed to its \\nSO2 mitigation goals. At the same time, new economic opportunities emerged and \\nwere generally seized, which should also have facilitated the advancement of eco­\\nnomic goals. In comparison with rule-­\\nbased governance, goal-­\\ncentered govern­\\nance has resulted in much lower requirements on inter-­\\ngoal coordination. Local \\ngovernments in China are the primary, decentralized entities to bear the respon­\\nsibilities and incentives for achieving both environmental and economic goals. \\nThey can have greater flexibility in adapting their policies and actions to take the \\nbest advantage of changing situations.\\nThese goals are also crucial indicators of how the Chinese central government \\nbalances between environmental protection and economic development. When \\neconomic goals were emphasized while environmental goals were not, local gov­\\nernments primarily focused on achieving economic goals. These goals are not \\nfully coordinated but generally are independently implemented in a bottom-­\\nup \\nmanner. They do not demand centrally planned coordination either, as shown pre­\\nviously in China’s surprising emergence of the SO2 scrubber industry. They will \\nseek appropriate ways for balancing how they achieve both goals. Decentralized \\npolicies and market evolution may utilize unexpected opportunities and circum­\\nvent unexpected difficulties in a much better way than any intelligent central plan­\\nner can foresee in advance. Goal-­\\ncentered governance thus can better maximize \\nsynergies and minimize conflicts among various goals and government tasks.\\nNote\\n\\t\\n1\\t Adapted with permission from Xu, Y. 2011. China’s functioning market for sulfur diox­\\nide scrubbing technologies. 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Energy & Environmental Science, 459–465.\\n\\n\\n8\\t\\n\\u0007\\nGoal-­\\ncentered governance\\n1  \\u0007\\nAlternative governance models\\nChina is experiencing very serious environmental damage. Nevertheless, the \\ncountry in the past decade has achieved probably the fastest sulfur dioxide (SO2) \\nmitigation pace for a large country. Significant progress has been made to clean up \\nair and water. Its energy system has been gaining momentum to transition away \\nfrom coal and toward renewables. With the economy more than 30 times bigger, \\nSO2 emissions within one decade dropped to a level that was seen only before the \\neconomic reform era began in the late 1970s. Strong political will was formed to \\nincreasingly prioritize environmental protection among governmental affairs. The \\nentire Chinese government across the central, provincial, municipality and county \\nlevels has been much better mobilized and committed. Policies are constantly \\nenacted by various central and local authorities. The conventional poor policy \\nimplementation has been more effectively addressed and rapidly evolving to gain \\ngreater efficiency. In the coal-­\\nfired power sector, China managed to achieve essen­\\ntially universal coverage of SO2 scrubbers. More important, the original nonoper­\\nation of SO2 scrubbers was also reversed to reach high SO2 removal rates. On the \\nother hand, China established the largest SO2 scrubber industry, which provided \\nemployment and economic outputs. However, two decades ago at the early stage \\nof China’s SO2 mitigation, few domestic firms existed with barely any domestic \\ncommercialized technologies. Although China has not been widely recognized \\nby developed countries as a market economy, new firms were actively formed \\nand swarmed into the new market to seek profitable opportunities. China’s inad­\\nequate protection of intellectual property rights did not seem to have prevented \\nwidespread market-­\\nbased technology licensing from firms in developed countries. \\nDespite numerous problems, China can claim great success in SO2 mitigation in \\nthe past two decades. These different components of environmental governance \\nmust work together to witness a favorable outcome. This book assesses the out­\\ncome and, most important, aims to explain the trajectory.\\nConventional wisdom can easily explain China’s environmental crises but has \\nserious difficulties in understanding the cleanup process. Democracy and the \\nrule of law are believed to be crucial contributors to forming strong political will \\nand enabling the means to achieve pollution mitigation. However, China is not a \\n\\n\\n180  Goal-­\\ncentered governance\\ndemocracy and often ranked much behind developed countries in the rule-­\\nof-­\\nlaw \\nindex. Accordingly, we expect that China’s rapid economic growth will result in \\nenvironmental crises and unacceptably high SO2 emissions, but the later, even \\nfaster SO2 mitigation is surprising because it defies the original expectations. \\nChina has not been fundamentally changed from the perspective of democracy \\nand rule of law. The Chinese Communist Party is still the ruling political party in \\nChina. Governmental officials at various levels are still appointed but not demo­\\ncratically elected. Although certain progress has been made, Chinese society is \\nstill far from reaching the similar rule-­\\nbased status as developed countries.\\nIn one common conventional impression, the Chinese government is authori­\\ntarian and highly centralized with forceful central planning. Accordingly, in this \\ntheory, China’s environmental cleanup in the past two decades would be explained \\nfrom the perspective of central planning. The central government might have \\ndesigned the trajectory and its unchallenged authority could then implement such \\na design. This logic goes that the Chinese government does not have the checks \\nand balances as in those democratic, developed countries, which enables China’s \\ncentral planners to design an optimized path with good coordination among vari­\\nous policy makers and implementers. When few domestic firms existed, the Chi­\\nnese government did not require the good operation of SO2 scrubbers to enable \\nlow technological market-­\\nentry barriers, provide and localize necessary supply \\ncapacities and reduce costs of SO2 mitigation. When many firms have been well \\nestablished in the market, effluent emission standards and other regulations were \\nmade more stringent with better implementation for more effective SO2 mitiga­\\ntion. These newly emerged environmental industries provide economic opportu­\\nnities and cushion the negative impacts of stringent environmental protection on \\neconomic growth.\\nHowever, this explanation must assume that China’s central planners were \\nextremely intelligent and well informed, but little evidence shows that such high-­\\nquality central planning has ever existed. As a developing country, China’s data \\ncollection system is less advanced than that in developed countries, especially two \\ndecades ago, to provide adequate data support for central planning. China’s com­\\nplexity and scale also make such high-­\\nlevel central planning intelligence impossi­\\nble to achieve. The extreme centralization under Chairman Mao resulted in social, \\npolitical and economic chaos with disastrous consequences. It is hardly convinc­\\ning that central planning can lead to either rapid SO2 mitigation amid momentous \\neconomic growth or the establishment of a large SO2 scrubber industry.\\nFurthermore, the rule-­\\nbased environmental governance that accounts for the \\ntrajectories in developed countries can also experience difficulties if applied to \\nprovide a primary explanation. As indicated in the World Bank’s governance \\nindicators as well as in general impression, China’s performance has not been \\nremarkable. China is still unable to make rules as important as developed coun­\\ntries prevalently do for environmental governance. In addition, under rule-­\\nbased \\ngovernance, although individual entities make their own decisions based on the \\nrules, the rules are often centrally enacted by legislatures and/or courts as laws \\nand the executive branch as regulations. Even if the rule of law is well established \\n\\n\\nGoal-­\\ncentered governance  181\\nin a society, whether rule-­\\nbased governance can produce good outcomes depends \\non the quality of rulemaking. Rule-­\\nbased governance alone is not a guarantee of a \\ngood outcome. Poorly designed rules and effective implementation may turn out \\nto be undesirable, while policy making in China has not gained a decent reputa­\\ntion on its soundness, and consultation has also been much less thorough than \\nthat in developed countries. For example, before 1997, market speculation was a \\nserious crime in China that was written into the Criminal Law. The intention was \\nto maintain the order of a planned economy.\\nThis book provides a different account of China’s environmental cleanup. \\nChina today has abandoned the Soviet-­\\nstyle central planning that was featured in \\nthe first three decades of the People’s Republic under the leadership of Chairman \\nMao. However, rule-­\\nbased governance has not been well established. New laws \\nand policies take a considerable amount of time to form and settle. For example, \\nthe Civil Code had just been enacted in May 2020 after many decades of grad­\\nual formation. Instead, a new governance strategy has been tried and gradually \\nbecome mature, with various goals taking the central stage. This goal-­\\ncentered \\ngovernance model is a mixture of centralization and decentralization to explain \\nChina’s SO2 mitigation trajectory much better than the central planning approach \\nor rule-­\\nbased governance can.\\n2  \\u0007\\nGoal-­\\ncentered governance\\nReadings of China are polarized, especially when China becomes bigger and \\nmore influential. One side profoundly denounces China and accuses the country \\nof being messy, of not being a democracy, of having a rubber-­\\nstamp legislature \\nand of being authoritarian without adequate respect to the rule of law. The Chinese \\ngovernment has been heavily criticized for breaking many rules that are highly \\nvalued in liberal democracies, such as those related to political liberty. Freedom \\nof speech and civil society are constrained. Rising income inequality and privi­\\nleges of the wealthy and the powerful add social tensions. However, another side \\nsupports the Chinese government as they see many positive outcomes in China’s \\ndevelopment. Together with rapid and sustained economic growth, the social wel­\\nfare system has been expanded dramatically to widen health care coverage even \\nin rural communities, increase retirement pension and alleviate poverty. The Chi­\\nnese people can now enjoy living standards that were unimaginable one genera­\\ntion ago. They can largely choose where to live, work or travel as well as what to \\nbuy and sell. A great majority of the population has received significant returns \\nof the economic development, although the distribution is uneven. Both views on \\nChina seem to have strong evidence to validate their claims. Then how can we \\nunderstand China with these two sharply polarized readings? Are they connected? \\nHow China may further reform to embrace a better future?\\nFor evidence-­\\nbased researchers, the negative views on China could be mainly \\nabout rules and their implementation, while the positive views could be primarily \\nshaped by outcomes. Although not all arguments on either side are sound, both \\nviews can find enough evidence to back them up. SO2 mitigation, or environmental \\n\\n\\n182  Goal-­\\ncentered governance\\nprotection in general, is one government affair that exemplified such situations. \\nThe rapid mitigation was surprising but has been verified from multiple independ­\\nent data sources, including external satellite data. Although active policy making \\nand effective implementation were pivotal for achieving SO2 mitigation goals, \\nmany policies failed or were not implemented well. Initially, a large fleet of SO2 \\nscrubbers were built but not normally operating. In any understanding of China’s \\ngovernance, a theoretical explanation should be able to accommodate both sides \\nbut not ignore the evidence of the other side. Furthermore, how are the two sides \\nconnected? In China’s case, does the favorable outcome have to be accompa­\\nnied by numerous policy blunders? If the rules were required to be well designed \\nand implementable before putting into practice, would that affect the favorable \\noutcomes?\\nThis book explains China’s puzzles into a goal-­\\ncentered governance model. As \\nthis book has examined in individual chapters on China’s SO2 mitigation, goal-­\\ncentered governance has two foci, including goals and policies. Goals direct poli­\\ncies and policies achieve goals. Rule-­\\nbased governance also has such two foci, but \\ngoals become secondary. The decisions in governance are mainly about enacting \\nrules that are expected to be genuinely implemented. Fewer policies (or regula­\\ntions and laws) are enacted and the policy making might be more centralized, but \\nthey tend to be more carefully drafted. The outcome is an implicit product of such \\nrules but not in the form of explicit, binding goals.\\nThe goal-­\\ncentered governance model can be understood from its organization \\nmechanisms, features and applicability.\\n2.1  \\u0007\\nOrganization mechanisms\\nChina has two hands in environmental governance, one visible and the other \\ninvisible. SO2 mitigation and environmental cleanup were achieved when the \\ntwo hands cooperated. As a visible hand, the top leadership sets up prioritized \\ngoals with neither full-­\\nfledged deliberation nor stringent requirements on the path \\nselection. The path results from bottom-­\\nup efforts of decentralized stakeholders \\nas directed by an invisible hand of governance. The invisible hand of the market \\nhas been widely recognized and utilized. Rational market participants maximize \\ntheir self-­\\ninterests or profits, while this decentralized process also leads to the \\nmaximization of a society’s overall economic interest. Goal-­\\ncentered governance \\ncould resemble and enable such an invisible hand to guide the central and local \\ngovernments toward goal attainment. When their self-­\\ninterests are served with \\nvarious incentives for goal attainment, the overall goal will be achieved to sat­\\nisfy society’s overall interest. If more stringent goals are enacted, the incentives \\nshould also be strengthened. In order to finally achieve environmental cleanup, \\nenvironmental goals must be prioritized with increasing stringency over a long \\nperiod. If goals are changed, the invisible hand will direct the system away from \\nthe original goals and toward new ones.\\nAs illustrated in Figure 8.1, goal-­\\ncentered governance comprises three pillars: \\ncentralized goal setting, decentralized goal attainment and decentralized policy \\n\\n\\nGoal-­\\ncentered governance  183\\nmaking and implementation. First, the process for setting up goals of nationwide \\npriority is highly centralized. The top leadership, with the Political Bureau of the \\nChinese Communist Party and its Standing Committee at the core, is in charge \\nof supplying the country with goals as they deem crucial, especially in Five-­\\nYear \\nPlans. The relationship among different goals could be balanced at this stage. \\nSome goals could be prioritized that correspond to higher ratings in the perfor­\\nmance assessment of local leaders. In the case of SO2 mitigation, the Chinese top \\nleadership did generally respond to what society wants, although the process was \\nnot democratic. The goals on SO2 mitigation and environmental protection were \\nrevised more stringent when such demand escalated.\\nSecond, for decentralized goal attainment, national goals are distributed to \\nprovincial governments and then lower-­\\nlevel local governments, as in the case \\nof SO2 mitigation and environmental protection goals. These individualized, \\nquantitative goals guide the efforts of local governments and related ministries. \\nStrong enough incentives are put into place to reward goal attainment and pun­\\nish failures. Because China’s local leaders are appointed but not elected, their \\njobs are explicitly linked to the performance of achieving various goals with \\ndifferent priorities. The Chinese Communist Party’s organization plays a crucial \\nrole in establishing such a crucial personnel relationship between the central and \\nprovincial governments and their further subsidiaries. In addition, the central \\ngovernment receives much greater revenues than it spends, while the situation \\nfor local governments is generally the opposite: to demand a significant fiscal \\ntransfer from the central government. If local governments failed their individual \\ngoals, their leaders would face grim opportunities of promotion and could even \\nbe removed. Those who outperform others are distinguished for better promotion \\nopportunities.\\nThird, policy making and implementation are heavily decentralized. With the \\nresponsibility of achieving goals, local governments have sufficient flexibility, \\nauthority and capacity for policy making and especially implementation, while \\nthe central government is especially weak in policy implementation. Require­\\nments are significantly lowered on the quality of policy making, the optimal \\nchoice of policy instrument and coordination among policies. As a developing \\nPolicy Implementation\\nPolicy Making\\nLocal \\nGovernments\\nPollution Control Firms\\nPolluting Firms\\nLocalized Goals \\n& Incentives\\nSociety & Economy\\nCentral Government\\nNational Goals\\nTop Leadership\\nCentralized goal setting\\nDecentralized goal \\nattainment\\nDecentralized policy \\nmaking & implementation\\nFigure 8.1  \\u0007\\nAn illustration of the goal-centered governance model\\n\\n\\n184  Goal-­\\ncentered governance\\ncountry, China has not acquired enough strengths from these perspectives despite \\ncontinuous improvement. The weak rule of law indicates that the system neither \\nrequires nor ensures their genuine implementation. Policies compete with each \\nother and evolve with implementation selection.\\n2.2  \\u0007\\nFeatures\\nUnder goal-­\\ncentered governance, several key features could emerge.\\nFirst, not all goals are important and prioritized goals are few. The mobilization \\nof the entire Chinese government, from central to local levels, depends on the cred­\\nible incentives for their goal attainment performance. Any additional goal could \\ndilute the effectiveness of existing ones. Accordingly, the number of nationally \\nprioritized goals should be constrained, while provincial governments and central \\nministries may have their second-­\\ntier goals with lower priorities. Governmental \\nefforts are highly concentrated on those goals of high priority, while in areas with \\nlesser or no goals, the performance could be significantly compromised.\\nSecond, policy making is active and each makes an incremental contribution \\nto goal attainment. Local governments and central ministries are mandated to \\nachieve their individualized goals. The incentives are mainly associated with the \\ngoals’ attainment, while any mistakes in policy making and implementation are \\nmuch more leniently accommodated. Furthermore, they also have great authority \\nand flexibility in policy making, adoption, innovation and learning in the decen­\\ntralized arrangement. These favorable conditions encourage active policy making, \\nas witnessed in the case of SO2 mitigation. Because it is local governments but \\nnot their environmental protection bureaus that bear the responsibility of achiev­\\ning goals, they often involve multiple bureaus in making their specialized policies \\nthat may contribute to SO2 mitigation. Ministry of Ecology and Environment, its \\npredecessors and its composing departments, as well as other central ministries, \\nhave also been actively trying new policy tools. Unlike the situation in the United \\nStates that the Acid Rain Program in the Clean Air Act Amendments (1990) and \\nits previous versions may claim a lion’s share of credits, China does not feature \\nany pivotal policy of similar importance for SO2 mitigation, while SO2 mitigation \\ngoals were achieved through numerous policies and each contributed a small and \\naccumulative share.\\nThird, more policy failures exist and policy implementation is selective. These \\nmay be seen as the necessary costs of the goal-­\\ncentered governance model, espe­\\ncially when China is still in the process of strengthening its policy-­\\nmaking quality \\nand policy implementation effectiveness. Policies in China may fail from multi­\\nple perspectives. The design itself may be less mature and flawed. Decentralized \\npolicy making indicates that not all policy makers, especially those in local gov­\\nernments, have adequate intellectual support. Policy implementation may have \\nunexpectedly high obstacles from various interest groups or weak enforcement \\ncapacity. To ensure the faithful implementation of individual policies is only a \\nsecondary priority for local governments. When good implementation of a certain \\npolicy contributes significantly to goals, more efforts will be directed to this issue. \\n\\n\\nGoal-­\\ncentered governance  185\\nFor SO2 mitigation, those policies on installing SO2 scrubbers were first targeted \\nin implementation, while their operation was only made a priority later when the \\nsignificant and growing fleet of SO2 scrubbers increased the impacts of such pol­\\nicy on reducing SO2 emissions. Environmental policy implementation capacity \\nwas strengthened, and new environmental compliance monitoring technologies \\nwere actively adopted with SO2 mitigation goals in primary focus.\\nFourth, requirements on goal coordination are lower. With impacts on SO2 mitiga­\\ntion, industrial, energy and environmental policies are enacted generally indepen­\\ndently from each other for achieving their specific goals. Various policies for one or \\nmultiple goals could have synergies and/or conflicts. In goal-­\\ncentered governance \\nfor SO2 mitigation, policy coordination largely is not centrally organized. Conflicting \\npolicies may not be implemented well to positively contribute to goal attainment, \\nand thus, they would dwindle. Those compatible policies that have synergies will be \\nexpanded from local to national levels or adopted from one region to another. In other \\nwords, such policy coordination is not achieved primarily through intentional intel­\\nligent design but via bottom-­\\nup evolution through implementation selection.\\nFifth, requirements on information availability and measurability are lower \\nwith moral hazards better contained. Policy making and implementation are much \\nmore data-­\\nintensive than the assessment of goal attainment. Significant uncertain­\\nties exist and many potential factors could affect the final outcome, such as in \\nthe case of SO2 mitigation. Because the efforts of local governments are difficult \\nto accurately measure and sometimes hardly observable, local leaders in China \\nmay simply pay frequent lip service, emphasize constraints and external factors \\nother than their own efforts but behave differently in reality. Comparison across \\nregions then faces high hurdles to disable effective competition among local gov­\\nernments. However, under goal-­\\ncentered governance, goals are primarily on those \\nmeasurable outcome indicators, such as SO2 emissions and air quality, which sig­\\nnificantly reduce the required information. Lip service is much less helpful than \\nactual efforts for achieving goals.\\nCorresponding to the questions that are raised in the book, the coexistence of \\nfavorable outcomes and unfavorable policy pathways is only puzzling because \\nthey cannot be properly explained by the rule-­\\nbased or central planning govern­\\nance models, while a decent theoretical understanding can be reached with the \\ngoal-­\\ncentered governance model. If the system has a very low tolerance for prob­\\nlems in policy making and implementation, especially for China as a developing \\ncountry, the favorable outcomes might indeed be seriously compromised. Nev­\\nertheless, the costs of policy deficiencies can be reduced when China gradually \\nacquires the capability and capacity for high-­\\nquality policy making and effective \\npolicy implementation.\\n2.3  \\u0007\\nApplicability\\nSince the Qin dynasty (221–207 BCE) first established centralized rule in China, \\nlocal governments have always been crucial in Chinese governance to distinguish \\nthe importance of the central–local relationship. The vast territory and population, \\n\\n\\n186  Goal-­\\ncentered governance\\nas well as huge regional differences, weaken direct ruling by the emperors or \\nprime ministers who reside in the distant capital. Although China has long been \\nenacting laws and policies in texts, such as those by Shang Yang in a major reform \\nin the 4th century BCE that led to the rise of the Qin Kingdom, the modern sense \\nof the rule of law has never been well established to occupy the central stage of \\ngovernance.\\nCorresponding to the organization mechanisms of goal-­\\ncentered governance, \\nthe system may fail under three situations. First, the achievement of governmental \\ngoals does not lead to outcomes that the society wants. The supply of goals by \\nthe top leadership may have a lag or lead from the demand, but the gap should \\nnot be too wide to let the system fail. This concern is closely related to arguments \\nin China’s context without democracy. When China was much poorer and the \\npublic prioritized economic growth and jobs over environmental protection, envi­\\nronmental goals were ranked much lower than economic goals. When the public \\nstarted to pay more attention to life quality and clean environment, environmental \\ngoals should then be ranked high among governmental affairs. It is not neces­\\nsary that the goals are exactly identical as what the society desires. For example, \\nthe maximization of long-­\\nterm tax revenues may be compatible with improving \\nthe living standard of the public. After the Mongol empire under Genghis Khan \\noccupied North China in early 13th century, one high-­\\nranking official suggested \\neliminating all Han Chinese and using the land for grazing because Han Chinese’s \\nprimary economic activities were not raising animals. His goal was for the land to \\ngenerate more tax revenues. Another key advisor to Genghis Khan, Yelv Chucai, \\nproposed that if the Han Chinese could be left alive to still engage in agriculture \\nand business, they would contribute much more tax. His advice was taken, and the \\noutcome was favorable to both the Mongol court and the people.\\nSecond, the decentralized goal attainment fails. The central government may \\nnot be able to impose their prioritized goals onto local governments. A frequent \\ncomplaint in the Chinese government was that “policies and orders cannot go \\nbeyond Zhongnanhai.” Zhongnanhai, or “Central and Southern Seas,” is a com­\\npound in Beijing where the central government of the People’s Republic of China \\nis located. This sentence generally means that the central government cannot \\nsmoothly impose their policies and orders onto local governments. Even Chair­\\nman Mao complained before the Cultural Revolution that the Beijing municipal \\ngovernment was “penetrable by neither water nor needles.” Local governments \\nand central ministries may malfunction or no effective incentives are available to \\nincentivise or force them to work for their assigned goals. A long-­\\nlasting ques­\\ntion in the Chinese history is the collapse of the Ming dynasty (1368–1644) in \\nearly 17th century. Historians pointed out one crucial reason in Emperor Wanli \\n(r. 1572–1620) when he left many key positions vacant and the government could \\nnot function (Huang, 1981). In the later decades of the Tang dynasty (618–907), \\nlocal leaders had exclusive power over military, civil affairs and fiscal revenue. \\nThey could also pass their titles to heirs who were chosen by themselves. Essen­\\ntially, local governments were semi-­\\nindependent kingdoms, which eventually led \\nto the collapse of the Tang dynasty.\\n\\n\\nGoal-­\\ncentered governance  187\\nThird, policy making and implementation are overcentralized, and local gov­\\nernments have very limited flexibility or capability in choosing their own paths \\nfor achieving goals. One-­\\nsize-­\\nfits-­\\nall rules from Beijing may be at a great distance \\nfrom diverging regional realities to undermine their effectiveness and efficiencies. \\nActive policy making, innovation and learning could be suppressed with overcen­\\ntralization or when mistakes were much less accommodated. When policy-­\\nmaking \\nauthorities, fiscal revenues/expenditures and capable officials are concentrated \\ninto the central government, local governments may be too weak to perform their \\njobs well. Local governments in wealthy regions may experience little difficulty \\nin attracting capable employees or building enough capacity in policy making and \\nimplementation for achieving their goals. However, China has significant regional \\ndisparity in economic development. If left alone, poor regions would not be able \\nto utilize the policy and technological tools effectively and efficiently.\\nGoal-­\\ncentered governance is mainly for new and evolving governmental affairs \\nwithout well-­\\nestablished policies. In comparison to two decades ago, China has \\ndesigned, enacted and implemented many policies for SO2 mitigation and other \\nenvironmental goals. Many will last to make SO2 mitigation a routine governmen­\\ntal affair, such as the effluent emission standards of thermal power plants. These \\ntested policies and correspondingly strengthened implementation systems will \\nform an escalating base for the continuous advancement of environmental protec­\\ntion until reaching fundamental solutions. Then goal-­\\ncentered governance could \\ngradually give way to rule-­\\nbased governance and other governmental affairs may \\nreceive more attention with prioritized goals. In the past two decades, key envi­\\nronmental goals in China’s Five-­\\nYear Plans have been extended from SO2 and \\nchemical oxygen demand (COD) in the 11th Five-­\\nYear Plan (2006–2010), plus \\nammonia-­\\nnitrogen (NH3–N) and nitrogen oxide (NOx) in the 12th Five-­\\nYear Plan \\n(2011–2015), plus water quality grade, the Air Quality Index and fine particulate \\nmatter (PM2.5) concentrations in the 13th Five-­\\nYear Plan (2016–2020; National \\nPeople’s Congress, 2011, 2006, 2016). With the continuous progress, it will not be \\nsurprising to see that SO2 mitigation goal removed and an ozone (O3) goal added \\nin the future, if not in the upcoming 14th Five-­\\nYear Plan (2021–2025).\\nThis goal-­\\ncentered governance has been tested as an effective strategy for China \\nto make rapid advancement from unfavorable situations and to significantly lower \\nkey requirements on policy making as in a rule-­\\nbased governance system. From \\none perspective, it is an effective and efficient path-­\\nfinding strategy for China \\nto reach a more sustainable, rule-­\\nbased future. With new problems continuously \\nemerging, it should and will be the crucial strategy in China’s future governance \\neven when China reaches the stage of a developed country.\\nThe goal-­\\ncentered governance model may be best utilized in countries with \\nthe following characteristics: (1) newly prioritized governmental affairs or others \\nwith rapid evolution to require continuous focus; (2) developing countries where \\npolicies have not been maturely established and policy making has not achieved \\nadequate quality and acquired enough data and intellectual support; (3) being \\nlarge in scale with genuine necessity of multiple governmental levels and where \\nthe central government can impose adequate incentives on local governments to \\n\\n\\n188  Goal-­\\ncentered governance\\nencourage policy innovation, while goal evaluation is largely fair with good data \\nsupport and rewards are issued based mainly on meritocracy; (4) where the system \\nis more tolerant to mistakes in policy making and implementation and pays pri­\\nmary attention to outcomes and only secondarily on paths; and (5) local govern­\\nments are capable of policy innovation and resourceful for policy implementation.\\nCountries in federal systems may not find this governance model applicable \\nbecause incentives very likely are neither adequately available nor strong enough \\nfor the federal government to incentivize state governments. Small countries may \\nnot need this governance strategy as the central government is much closer to the \\nsociety and local governments are not as important as those in large countries. For \\ncountries that have established sound rule of law, goal-­\\ncentered governance may \\nnot occupy center stage either because the system is less tolerant of mistakes in \\npolicy making and implementation, while active policy innovation may indeed \\nencounter more mistakes and failures. Highly centralized countries in policy mak­\\ning and implementation may constrain such bottom-­\\nup efforts as well. This goal-­\\ncentered governance model is not necessarily inapplicable in democracies, but \\nthe application nevertheless may be much constrained if competition across local \\ngovernments may not have enough impetus and incentives.\\nDespite the constraints of its applicability, governments at various levels across \\ncountries with different institutional and developmental contexts may still be able \\nto draw helpful insights from the goal-­\\ncentered governance model and explicitly \\napply goals in organizing their governance. Decentralized policy innovation and \\ncompetition can be encouraged in countries with sound rule of law, despite vari­\\nous constraints of existing rules.\\n2.4  \\u0007\\nComparison with other theories\\nThis study’s development of the goal-­\\ncentered governance model not only ben­\\nefits immensely from earlier theoretical explorations but also demonstrates sig­\\nnificant differences.\\nGoal-­\\nsetting theory in social psychology is one key intellectual source (Latham \\net al., 2008; Latham and Yukl, 1975; Locke and Latham, 1990, 2002; Locke et al., \\n1981). The goal-­\\nsetting theory mainly emphasizes on how goals could enhance \\ntask performance of individuals, while goal-­\\ncentered governance pays primary \\nattention to the performance of local governments, central ministries and other \\ngovernmental agencies. In addition, the latter has a heavy focus on the flexibility \\nof those decentralized stakeholders in utilizing policies for achieving those goals.\\nThe goal-­\\ncentered governance model can be regarded as a specific application \\nof pragmatism with clear directions (Alford and Hughes, 2008), while it places \\ngoals at the center and makes policies instrumental. The criteria of assessing pol­\\nicies are based on whether they contribute, undermine or have no impacts on \\ngoal attainment in actual contexts but not on prior selection. Policy innovation, \\ncompetition, revision, learning and expansion are common, and specific policies \\nwill rarely be unequivocally relied on. This governance model is a theoretical \\nextension of Deng Xiaoping’s cat theory. Deng Xiaoping was officially accredited \\n\\n\\nGoal-­\\ncentered governance  189\\nas the “chief architect of China’s reform and open-­\\nup” by the Chinese Commu­\\nnist Party. However, he did not have a clear long-­\\nterm blueprint on how China’s \\neconomic reform should proceed when China just got out of the devastation of \\nthe Cultural Revolution, but many doctrines remained strong. As summarized in \\nhis famous quote, “regardless of whether the cat is a white cat or a black cat, as \\nlong as it can catch mice, it is a good cat.” He was less interested in the debate \\nabout whether China’s economic reform may contain too much capitalism but \\nmainly focused on whether the country can prosper at a faster pace. This strategy \\nwas sharply different from Chairman Mao’s, under whose leadership China had a \\nstringent restriction on the choice of paths or “cats.” Another famous quote could \\nsummarize his main idea: “we would rather have socialistic grass than capitalistic \\ngrain.” This goal-­\\ncentered governance has clear directions as specified in goals, \\nbut the pathfinding is much less constrained.\\nIt also echoes adaptive and polycentric governance to address complexity and \\nuncertainty that emphasize localized solutions (Dietz et al., 2003; Chaffin et al., \\n2014; Ostrom, 2010). This goal-­\\ncentered governance emphasizes more on how \\nthese solutions could evolve in decentralized and bottom-­\\nup manners with moti­\\nvated local governments under the centralized direction of goals. In comparison \\nto the comparative advantage strategy that advocates good, incremental improve­\\nments but not perfect, once-­\\nand-­\\nfor-­\\nall solutions to environmental problems (Xu, \\n2013), this goal-­\\ncentered governance model is more incorporative to explain in \\nwhat conditions the comparative advantage strategy will be taken, why it can \\nwork and what impacts it may exert on governance. The competition among local \\ngovernments and other goal bearers borrows the idea from the Tiebout model \\n(Tiebout, 1956), but they are also quite different. The incentives for the competi­\\ntion are not bottom up from local citizens but are top down from imposed goals. \\nFor explaining the development of China’s environmental industries, the ecologi­\\ncal modernization theory may provide an alternative understanding that connects \\nenvironmental protection with economic modernization (Hajer, 1995; Zhang \\net al., 2007). The goal-­\\ncentered governance model, in comparison, explains that \\nthe impacts on environmental industries were not intentionally planned, and envi­\\nronmental and economic policies were not deliberately coordinated for new firms \\nin a developing country like China to actively enter the market and grow up.\\nIncrementalism is another crucial intellectual source to build the goal-­\\ncentered \\ngovernance model (Lindblom, 1959; Lindblom, 1979). Neither emphasizes on \\nkey, deliberately designed policies with maximized impacts on achieving objec­\\ntives, but each policy should make incremental but accumulative contributions. \\nHowever, goal-­\\ncentered governance does have explicit goals at the center as ends, \\nwhile policy making is not centralized for finding optimized means. Instead, the \\nincremental improvement was made by decentralized local governments, not by \\ncentralized policy makers. Goal-­\\ncentered governance is compatible with Joseph \\nStigler’s economic theory of regulation (Stigler, 1971). It understands the demand \\nfor regulations with an additional key source from goals, while the supply of \\nregulations is decentralized to witness active policy making, innovation and \\ncompetition.\\n\\n\\n190  Goal-­\\ncentered governance\\n3  \\u0007\\nImplications\\nIn the past two centuries, China has tried, voluntarily or involuntarily, many dif­\\nferent governance models. When one model was proved ineffective, reforms were \\nattempted, and frequently, revolutions were started. Even under the rule of the \\nChinese Communist Party since 1949, China has tried sharply different models. \\nUnder Chairman Mao, the Chinese government was much more centralized. His \\ngoals significantly deviated away from what the society wanted, but no effective \\nchecks could counterbalance and prevent his goals from becoming the nation’s. \\nThe results were disastrous.\\nThrough trial and error and with tremendous costs, China should have found \\nan effective model to govern the vast, complex, developing country with a deep \\ninstitutional history. The goal-­\\ncentered governance model has demonstrated its \\neffectiveness and efficiency in fundamentally reversing the rising trend of SO2 \\nemissions as well as China’s multifaceted environmental crises. Nevertheless, the \\ngovernance model has two potentially highly damaging risks. First, goals may \\nnot be formed to satisfy society’s demands, like what happened under Chairman \\nMao. The current focus on environmental protection could have a chance to be \\ndisrupted, and thus, the entire governance system would be directed in another \\ndirection. Second, overcentralization and low tolerance to policy mistakes may \\nundermine the system’s effectiveness and efficiency. Local governments and \\nother governmental agencies may be weakened on the incentives, authorities and \\ncapacities of policy making and implementation. One indicator would be whether \\npolicy innovation and learning are still active.\\nA famous quote from Voltaire, a French writer, is that “the perfect is the enemy \\nof the good.” The goal-­\\ncentered governance model is far from being perfect. Even \\nwhen it achieves great success, the process is full of stumbles, policy deficien­\\ncies, unsatisfactory policy implementation and even frequent abuse of govern­\\nmental authorities. However, as China has tried, alternative governance models \\nmay hardly provide better outcomes due to difficulties from uncertainties, com­\\nplexities and data inadequacy in China’s contexts, although they may work well \\nin another country’s contexts. Rule-­\\nbased governance demands high requirements \\non policy making quality, optimal choice of policy instruments and inter-­\\npolicy \\ncoordination, but these were not China’s strengths especially in the early stages of \\ndealing with major issues such as SO2 mitigation and environmental cleanup. This \\ngoal-­\\ncentered governance is a “good” model but certainly not a “perfect” one due \\nto its numerous weaknesses. Especially for developing countries with many diffi­\\nculties in policy making and implementation, this proven “good” model provides \\na promising way to organize governance for achieving what the society deems \\nsignificantly desirable, while a “perfect” governance model may be unreachable. \\nThe pursuit of being perfect should not stop a country from becoming better.\\nEnvironmental crises that have accumulated over a few decades cannot be \\nsolved within a few years. Efforts should be sustained even when the govern­\\nment changes after elections or leadership reshuffle. In developed countries, the \\nrule-­\\nbased governance model has been effective to achieve economic prosperity \\n\\n\\nGoal-­\\ncentered governance  191\\nand later sustained reduction of pollution with laws at the center. The gradually \\nformed and tested goal-­\\ncentered governance model offers a feasible method for \\nChina to fundamentally solve environmental degradation problems. The SO2 mit­\\nigation has transcended multiple Five-­\\nYear Plans since the 9th Five-­\\nYear Plan \\n(1996–2000) under three top leaderships. The demand for environmental quality \\nhas grown stronger among the public, and China’s top leadership has also been \\nlargely supplying national goals to match the demand. It is expected that environ­\\nmental goals will remain highly prioritized among governmental affairs in China.\\nClimate change is a much greater environmental problem than any conven­\\ntional air or water pollution. This goal-­\\ncentered governance model has also been \\nused in tackling the mitigation of China’s greenhouse gas emissions since the 12th \\nFive-­\\nYear Plan (2011–2015) when a goal to reduce carbon dioxide (CO2) intensity \\nby 17% over the five years was first written into the national plan (National Peo­\\nple’s Congress, 2011). Goal attainment, policy making and implementation have \\nalso been heavily decentralized. The market has been actively taking advantage \\nof economic opportunities from CO2 mitigation to develop, deploy and innovate \\ntechnologies, such as renewable energy, electric vehicles and energy efficiency. \\nSimilar to SO2 mitigation, CO2 mitigation has centralized goals, but its actual \\nattainment is largely decentralized. It is expected that this goal-­\\ncentered govern­\\nance model will also lead to China’s eventual transition of climate mitigation.\\nReferences\\nAlford, J. & Hughes, O. 2008. Public value pragmatism as the next phase of public man­\\nagement. American Review of Public Administration, 38, 130–148.\\nChaffin, B. C., Gosnell, H. & Cosens, B. A. 2014. A decade of adaptive governance schol­\\narship: Synthesis and future directions. Ecology and Society, 19.\\nDietz, T., Ostrom, E. & Stern, P. C. 2003. The struggle to govern the commons. Science, \\n302, 1907–1912.\\nHajer, M. A. 1995. The politics of environmental discourse: Ecological modernization and \\nthe policy process. Oxford and New York: Clarendon Press, Oxford University Press.\\nHuang, R. 1981. 1587, a year of no significance: The Ming dynasty in decline. New Haven: \\nYale University Press.\\nLatham, G. P., Borgogni, L. & Petitta, L. 2008. Goal setting and performance management \\nin the public sector. International Public Management Journal, 11, 385–403, 113.\\nLatham, G. P. & Yukl, G. A. 1975. Review of research on application of goal setting in \\norganizations. Academy of Management Journal, 18, 824–845.\\nLindblom, C. E. 1959. The science of muddling through. Public Administration Review, \\n19, 79–88.\\nLindblom, C. E. 1979. Still muddling, not yet through. Public Administration Review, 39, \\n517–526.\\nLocke, E. A. & Latham, G. P. 1990. A theory of goal setting & task performance. Engle­\\nwood Cliffs, NJ: Prentice Hall.\\nLocke, E. A. & Latham, G. P. 2002. Building a practically useful theory of goal setting and \\ntask motivation – A 35-­\\nyear odyssey. American Psychologist, 57, 705–717.\\nLocke, E. A., Saari, L. M., Shaw, K. N. & Latham, G. P. 1981. Goal setting and task-­\\nperformance – 1969–1980. Psychological Bulletin, 90, 125–152.\\n\\n\\n192  Goal-­\\ncentered governance\\nNational People’s Congress. 2006. The outline of the national 11th five-­\\nyear plan on eco­\\nnomic and social development. Beijing, China: The 4th Conference of the 10th National \\nPeople’s Congress.\\nNational People’s Congress. 2011. The outline of the national 12th five-­\\nyear plan on eco­\\nnomic and social development. Beijing, China: The 4th Conference of the 10th National \\nPeople’s Congress.\\nNational People’s Congress. 2016. The outline of the 13th five-­\\nyear plan on economic and \\nsocial development. Beijing, China: The 4th Conference of the 10th National People’s \\nCongress.\\nOstrom, E. 2010. Beyond markets and states: Polycentric governance of complex eco­\\nnomic systems. American Economic Review, 100, 641–672.\\nStigler, G. J. 1971. The theory of economic regulation. The Bell Journal of Economics and \\nManagement Science, 2, 3–21.\\nTiebout, C. M. 1956. A pure theory of local expenditures. Journal of Political Economy, \\n64, 416–424.\\nXu, Y. 2013. Comparative advantage strategy for rapid pollution mitigation in China. Envi­\\nronmental Science & Technology, 47, 9596–9603.\\nZhang, L., Mol, A. P. J. & Sonnenfeld, D. A. 2007. The interpretation of ecological mod­\\nernisation in China. Environmental Politics, 16, 659–668.\\n\\n\\nPage numbers in italic indicate a figure and page numbers in bold indicate a table on the \\ncorresponding page.\\nIndex\\n3rd Five-Year Plan (1966–1970) 44\\n6th Five-Year Plan (1981–1985) 43\\n9th Five-Year Plan (1996–2000) 18, 62\\n10th Five-Year Plan (2001–2005) 45 – 48, \\n62, 66, 92, 98\\n11th Five-Year Plan (2006–2010) 20, \\n43 – 49, 57, 62, 64, 66, 67, 78, 92, \\n98 – 99, 116, 168, 187\\n12th Five-Year Plan (2011–2015) 119, \\n187, 191\\n13th Five-Year Plan (2016–2020) 187\\nAcademy of Environmental Planning 29\\nAcademy of Environmental Sciences 29\\naccountability 64\\nacid rain and SO2 pollution control, 11th \\nFive-Year Plan on 43, 46, 93\\nAcid Rain Program, U.S. 49, 78, 79, 105, \\n124, 184\\nAction Outline for Promoting Big Data \\nDevelopment 124\\nadministration 28 – 29, 29, 30, 33\\nAfrica, energy consumption and \\nelectrification rate in 89\\nagricultural pollution, under Ministry of \\nAgriculture 27\\nair and water pollution: in China 1; \\ncontrolling 65; DALYs in China due 3, \\n3; mitigation 23; premature deaths due \\nto 1, 2, 3\\nAir Quality Index (AQI) 65, 66, 71\\nambient particulate matter (PM) pollution: \\ncause of 86; in China 1 – 4, 2, 3; in India \\n4 – 5, 4; PM2.5 goals 66\\nAsian financial crisis of 1997 18\\nAssociation of Environmental Protection \\nIndustries, China’s 151\\nautocracy, democracy and 6\\nBasic Thoughts of the National 11th Five-\\nYear Plan, The 45, 46\\nBeijing, AQI in 71, 71\\nBlackman, A. 107\\n“blue sky” 66\\nBOT (Build, Operate, Transfer) contracts, \\nfor SO2 scrubbers 173\\nbudget balance: of central and local \\ngovernments 34, 35; by provinces 35, 36\\ncalcium/sulfur (Ca/S) molar ratio in coal \\n93, 110\\ncampaigns/movements (yundong) \\n135 – 136\\ncarbon dioxide (CO2); emissions 6; \\nmitigation, goal of 43, 191\\nCentral Department of Organization 40\\ncentral government: budget balance 34, \\n35, 36; in charge of policy making 28, \\n35; environmental authorities at 29, 33; \\ngovernmental revenue and expenditure \\nto GDP ratios by 33 – 35, 33; reforms \\nat 27; shares of expenditures (2018) \\n36 – 38, 37 – 38\\ncentralized: and decentralized personnel \\nmanagement 39 – 40; goal setting 44 – 49, \\n183; political will 17 – 18\\nChina 25, 43; administrative reform 27; \\nair quality 1, 2; average prices of wind \\nturbines in 172 – 173, 172; central–local \\nfiscal relationship (1994) 34 – 35; central \\nplanning 180; challenges in policy \\nmaking 77 – 80; coal consumption in \\n10, 11, 84, 87, 90; coal-fired power and \\nSO2 scrubber capacities in 96 – 99, 97, \\n98; DALYs in 3, 3, 4; deployment and \\noperation of SO2 scrubbers in 149 – 150, \\n150; economic growth in 85 – 87, 85; \\n\\n\\n194  Index\\neconomy 9, 18, 22; electricity \\ngeneration by fuels in 89 – 90, 90; \\nemployees on environmental protection \\n(2015) 33; energy consumption 43, 78, \\n86 – 90, 86, 88, 92, 174; energy intensity \\ngoal 43, 78, 84, 92; environmental \\nagencies in 28; environmental \\ncompliance in 105; environmental \\ncrises 1 – 5, 180; environmental \\npolicies and laws in 29, 31 – 32, 39; \\nenvironmental/renewable energy \\nindustries 23; financial sector 18; firms \\nin 170, 171; GDP in 7 – 8, 7, 18, 19, 22; \\ngoal-centered governance in 80 – 84; \\ngoal-centered policy implementation \\n105 – 109; goals in Five-Year Plans \\n42 – 44; governance indicators of \\n8 – 9, 8; governmental income/\\nexpenditure-to-GDP ratio in 33 – 35, \\n33; international competitiveness of \\nSO2 scrubber industry 171 – 174; job \\nand demographic structures 18 – 20, 19, \\n22; Law of Environmental Protection \\n47; Law of Standardization 47, 96; \\nlaws in 31; leadership change 44 – 45; \\nmarket-incentive policies 79; mobilizing \\ngovernment 42 – 72; NGOs in 17; \\npatents on environmental technology \\n161 – 162, 162; policies in 83; polity \\ndemocracy index for 5 – 6, 5; pollution \\nmitigation in 149; power sector shares \\n10, 11; premature deaths 1, 2; provincial \\nenvironmental authorities 30; R&D \\nexpenditures in 161, 161; shares in \\ngovernmental expenditure for 36 – 39; \\nstrategies on environmental protection \\n65; sulfur contents distribution in coal \\npower plants 93 – 94, 95; unit capital \\ncosts of SO2 scrubbers in 151 – 152, 151; \\nweak rule of law 32, 39, 107; \\nwind energy development in 168 – 169, \\n168; yearly university graduates in \\n157 – 158, 157\\n“China Price, The” 172\\nChinese Communist Party 13, 17, 25, 39, \\n180, 183\\nCivil Code 181\\nClean Air Act Amendments (CAAA, U.S.) \\n12, 31, 49, 78, 79, 105, 184\\nclimate change 26, 191\\ncoal: consumption 10, 11, 84, 87, 90, 149; \\nlower sulfur contents in 93; prices of 87, \\n87; share in electricity generation 89 – 90\\ncoal-fired power: annual growth of 98 – 99, \\n98; decision scenarios for managers of \\nplants 117; plants 95 – 100, 105 – 106, \\n112 – 119, 123; and SO2 scrubber \\ncapacities 96 – 97, 97\\ncompetition, market entry and 169 – 171\\ncompliance: costs 107, 109; monitoring \\n119, 120 – 121; see also environmental \\ncompliance monitoring\\ncompliance on SO2 scrubbers operation: \\nnoncompliance behaviors 112 – 115; SO2 \\nscrubber technologies 109 – 112\\nComprehensive Plan on Ecological \\nand Environmental Big Data \\nConstruction 124\\nCongleton, R. D. 6\\ncontinuous emissions monitoring systems \\n(CEMSs) 107, 108, 113, 115, 122\\ncorruption 6, 9\\nCultural Revolution (1966–1976) 25\\nDarwin, C. 83\\ndecentralization 27 – 28; in economic \\nreform 36; fiscal revenue and \\nexpenditure 33 – 39; goal attainment \\n61 – 65, 183; of governmental affairs 35, \\n40; human resources 32 – 33; personnel \\nmanagement 39 – 40; of policy making \\n31 – 32, 42, 82 – 83, 183 – 184\\nDecisions on Realizing Scientific View \\nof Development and Strengthening \\nEnvironmental Protection (2005) 46\\ndeforestation 6, 7\\ndemocracy: and environment 5 – 7; and \\npolitical will 17; and rule of law 13, \\n179 – 180\\nDeng Xiaoping 188 – 189\\nDepartment of Organization of the Chinese \\nCommunist Party 27, 39\\ndisability-adjusted life years (DALYs) 3; \\nin China, due to air and water pollution \\n3, 3, 4; in India 4, 4; premature deaths \\nand 3\\ndivision of labor, for policy making and \\nimplementation 28 – 30\\ndomestic technology licensees, strategy of \\n156 – 162, 158\\n“double randomness, one publicization” \\nscheme 129, 132\\neco-compensation policy 31\\necological civilization 23\\neconomic development: and energy \\nconservation 84; and environmental \\nprotection 25, 27, 28, 174; and \\nenvironmental quality 7, 51; Five-Year \\nPlans 43; and SO2 mitigation 174\\n\\n\\nIndex  195\\neffluent emissions: and SO2 removal rates \\n97, 118; standards 31 – 32, 51, 66, 79, \\n83, 95 – 96, 180, 187\\nelectricity generation: annual growth of 90, \\n91; energy consumption/transition for \\n10, 89, 89, 92; by fuels in China 89 – 90, \\n90; provincial 52; SO2 scrubbers 95, \\n112, 117; wind 173\\nelectrostatic precipitator (ESP) 109\\nemployment and population structures, in \\nChina 18 – 20, 19, 22\\nenergy consumption: annual growth of 87, \\n88; economic conditions and 18, 20, 78, \\n84, 174; electrification of 10, 89, 89, 92; \\nand energy efficiency 86, 86; by fuel 87, \\n88; reduction of 43\\nenergy intensity goal 43, 78, 84, 92\\nenergy transition effect 85, 92\\nEngineering, Procurement, and \\nConstruction (EPC) project, in Hong \\nKong 163\\nenvironment: and democracy 5 – 7; income \\nand 6\\nenvironmental campaigns 135 – 136\\nenvironmental capacity 47, 51\\nenvironmental compliance monitoring \\n105, 108 – 109, 119 – 136; building \\nscreening system with big data 123 – 125; \\ncomparing diagnosing and screening \\nsystems 125 – 135; conceptual model \\nof 121; model construction 120 – 122; \\nresilience of screening and diagnosing \\nsystems 135 – 136; strengthening \\nconventional diagnosing system 122 – 123\\nenvironmental crises, in China 1 – 5, 180\\nenvironmental enforcement 27, 119\\nenvironmental governance 8; centralized/\\ndecentralized personnel management \\n39 – 40; evolution of environmental \\nadministration 25 – 27; for implementing \\npolitical will 25 – 40; policy making \\nand implementation 28 – 39; see also \\nenvironmental protection\\nenvironmental impact assessment (EIA) \\nreports 64, 94 – 95\\nenvironmental industry under goal-\\ncentered SO2 mitigation path: \\ninternational competitiveness of China’s \\nSO2 scrubber industry 171 – 174; market \\nentry and competition 169 – 171\\nEnvironmental Kuznets Curve 6, 7\\nEnvironmental Performance Index 1, 2\\nenvironmental policies 23\\nenvironmental protection: 11th Five-Year \\nPlan for 43, 45; administration 27; \\nauthority of 25; as Basic National Policy \\n25; as budgetary item 36, 37, 38; chain \\nof command for 27 – 28; in China 25; \\neconomic development and 25, 27, 28, \\n174; economic growth and 22, 23; goals \\non 43, 174; implementing 28; importance \\nin new ideology establishment 46; \\npersonnel at governmental levels 28 – 29, \\n29; political will for 17 – 24; prioritized \\n42 – 72; provincial personnel 30; \\nrecognized as governmental affair 25, \\n26; regulations on 31; SARS and 20 – 22; \\nshare in governmental expenditures \\n36 – 38, 38; south–north water diversion \\nproject 27; strategies on 65; tax law 83; \\nurban air quality and 23\\nEnvironmental Protection Agency (EPA), \\nU.S. 113\\nenvironmental protection bureaus (EPBs) \\n27 – 28\\nEnvironmental Protection Law 31\\nenvironmental quality 7, 47, 51, 65, 191\\nEuropean Union Emission Trading Scheme \\n119, 124\\nexpenditures/revenue, of central and local \\ngovernments 33 – 35, 33\\nfinancial sector 18\\nFirst National Conference on \\nEnvironmental Protection (1973) 25\\nfiscal revenue and expenditure 33 – 39, 33\\nFive-Year Plans, goals in 42 – 44; see also \\nindividual plans\\nflue gas desulfurization see SO2 scrubbers\\nfluidized bed combustion (FBC) 93\\nforeign affairs and national defense 36\\nforeign technology licensors, strategy of \\n162 – 165\\nfossil-fuel-fired power plants 65\\nfossil fuels 87, 89\\nfractions of sulfur retained in ash 93, 93\\nGDP (gross domestic product): capital \\ninvestment and 64; in China, South \\nKorea, Japan and US 7 – 8, 7; \\ngovernmental revenue and 33 – 35, 33; \\ngrowth rates of 18, 19, 22, 43, 85; R&D \\nexpenditures and 161\\nGenghis Khan 186\\nGerlagh, R. 6\\nGlobal Burden of Disease study: China’s \\npremature deaths due to air and water \\npollution in 1, 2; DALYs in China due \\nto air and water pollution 3, 3\\nglobal financial crisis of 2008 20\\n\\n\\n196  Index\\ngoal(s): in China’s Five-Year Plans \\n42 – 44; in environmental protection \\n43; evolution 65 – 72; implementation \\n49 – 50; types of 65\\ngoal attainment 43, 183; criteria for \\n61 – 63; incentives for 63 – 65, 184\\ngoal-centered governance: alternative \\ngovernance models 179 – 181; \\napplicability 185 – 188; characteristics \\n187 – 188; in China 80 – 84; comparison \\nwith other theories 188 – 189; features \\n184 – 185; illustration of model \\n183; implications 190 – 191; inter-\\ngoal coordination under 174 – 175; \\norganization mechanisms 182 – 184\\ngoal-centered policy implementation and \\nsupply 105 – 109; enabling 80 – 81; \\npolicy evolution by implementation \\nselection 81 – 84\\ngoal-centered SO2 mitigation path \\n149 – 154; environmental industry under \\n169 – 174; technology licensing under \\n155 – 169, 158\\ngoal distribution 43; from central to \\nprovincial governments 50 – 57; \\ncorrelation coefficients of key factors \\nfor provinces 52, 53 – 54; provincial goal \\n57, 61; from provincial to municipality \\ngovernments 58 – 61; regression results \\nto provinces/municipalities 56, 59\\ngoal setting 43, 183; methods of 46 – 49; \\nsetting up national goal 44 – 46; in social \\npsychology 188\\ngovernance indicators 8 – 9, 8\\ngovernmental revenue and expenditure to \\nGDP ratios 33 – 35, 33\\ngovernment effectiveness 9\\ngrain storage 36\\nGreat West Development 52\\ngreenhouse gas concentrations, \\nstabilization of 42, 50, 191\\ngroundwater pollution, under Ministry of \\nLand and Resources 26 – 27\\nGuangdong Province, distributing goals to \\nmunicipality 59 – 60, 59\\nGuatemala 7\\ngypsum 111\\nHainan Province 52\\nHarrington, W. 107\\nhealth care 36\\nHebei Province 23, 59, 59, 68\\nHenan Province 116, 118\\nhousehold air pollution from solid fuels \\n1 – 4, 2, 3\\nHu Jintao 18, 20, 21, 46\\nHuman Environment, UN Conference on \\n(1972) 25\\nhuman resources and fiscal expenditures \\n32 – 39\\nIEA (International Energy Agency) report \\n107\\nincome and environment 6\\nincrementalism 189\\nIndia: ambient PM pollution in 4; energy \\nconsumption and electrification rate 89; \\ngovernance indicators of 8 – 9, 8; market \\nfor technology 169; polity democracy \\nindex for 5, 6\\nindoor air pollution 1, 3\\nindustrial and residential sectors 10\\nInsigma Technology 164\\ninspection 29 – 30, 29, 33\\ninter-goal coordination under goal-\\ncentered governance 174 – 175\\ninternational competitiveness of China’s \\nSO2 scrubber industry 171 – 174\\nInternational Monetary Fund 8\\nIPE (Institute of Public & Environmental \\nAffairs) 21 – 22\\nJapan: economic growth in 85, 85; GDP in 7\\nJiangsu Province 48, 59, 60, 106, 112, 116, \\n153\\nJiang Zemin 18, 44\\nJiulong Electric 164 – 165\\njob creation 18 – 20, 22\\nKenya 7\\nKyoto Protocol 52\\nLaw of Atmospheric Pollution Prevention \\nand Control 31\\nLaw of Environmental Protection 31, 47\\nLaw of Standardization 47, 96\\nLaw of Water Pollution Prevention and \\nControl 31\\nLevitt, S. D. 121\\nLi Keqiang 17, 18, 22\\nlimestone 109 – 112\\nliquid-to-gas ratio (L/G ratio) 110\\nlocal governments: achieving top-down \\ngoals 82; budget balance 34, 35, 36; \\nenvironmental agencies in 28, 32; in \\nera of Reform and Open-up 28; goal \\ndistribution 50 – 61; governmental \\nrevenue and expenditure to GDP \\nratios by 33 – 35, 33; implementing \\nenvironmental policies 27; mobilization \\n\\n\\nIndex  197\\nof 43, 82; at provincial/municipality \\nlevels 32; responsibility for \\nenvironmental quality 47, 65 – 66; shares \\nof expenditures (2018) 36 – 38, 37 – 38\\nLocke, E. A. 42\\nmajor pollutants 77 – 78\\nManagement Methods of Environmental \\nStatistics 62\\nmarket: entry and competition 169 – 171; \\n-oriented economic reforms 43; \\nspeculation 181; state and 26, 39, 174\\nMidlarsky, M. I. 6\\nMing dynasty (1368–1644) 186\\nMinistry of Agriculture 27\\nMinistry of Ecology and Environment \\n(MEE) 26 – 27, 28, 31, 44, 64, 77, 81, 184\\nMinistry of Environmental Protection \\n(MEP) 26, 64, 67, 96, 106, 124, 163\\nMinistry of Land and Resources 26 – 27\\nMinistry of Water Resources 27\\nmitigation effect 85, 92\\nmonitoring 29 – 30, 29, 33\\nNational Acid Precipitation Assessment \\nProgram 49\\nNational Aeronautical and Space \\nAdministration 124\\nNational Development and Reform \\nCommission (NDRC) 26, 45, 96\\nNational Energy Administration 96, 169\\nNational Environmental Protection \\nAdministration 47\\nNational Party’s Congress 44\\nNational People’s Congress 13, 31, 32, 44, \\n45, 77\\nNeumayer, E. 6\\nnoncompliance, reversing: environmental \\ncompliance monitoring 119 – 136; \\npenalty 115 – 119\\nnoncompliance behaviors, on SO2 \\nscrubbers operation 112 – 115\\nnonfossil fuels 90\\nnongovernmental organizations (NGOs), \\nin China 17\\nnonhydro renewables 89\\nnon-power-sector emissions 51\\nnonstate firms 156\\n“Not Invented Here” syndrome 159\\nObama, B. 42\\nocean environment, under State Oceanic \\nAdministration 27\\noil and natural gas 87, 89\\nOpen-up policy 9, 25\\norganization mechanisms, of goal-centered \\ngovernance 182 – 184\\nOutline of the National 11th Five-\\nYear Plan on Economic and Social \\nDevelopment, The 45, 46, 77 – 78\\nozone pollution 69, 70, 71\\npatents on environmental technology \\n161 – 162, 162\\nPayne, R. A. 17\\nPellegrini, L. 6\\npenalties for noncompliance 108, 115 – 119\\nPeople’s Republic of China; see China\\npersonnel management, centralized/\\ndecentralized 39 – 40\\npolicing strategies 121\\npolicy making and implementation: \\nchallenges in 77 – 80; compliance on \\noperation of SO2 scrubbers 109 – 115; \\ndecentralized 31 – 39, 183; division \\nof labor for 28 – 30; environmental \\ncompliance monitoring 119 – 136; goal-\\ncentered 105 – 109; lower barriers 81 – 82; \\novercentralized 187; penalty 115 – 119; \\nreversing noncompliance 115 – 136\\npolitical stability and absence of violence/\\nterrorism 9\\npolitical will 6; centralized 17 – 18; \\neconomy/jobs/environment (1998–2002) \\n18 – 20, 19; for environmental protection \\n17 – 24; SARS and prioritization of \\nenvironmental protection (2003–2012) \\n20 – 22; sustainability of (2013–present) \\n22 – 24\\npollution: abatement costs 120; health \\nimpact, measurement of 3; mitigation \\n149; ozone 69, 70, 71; see also air and \\nwater pollution; ambient particulate \\nmatter (PM) pollution\\npower sector: shares of coal consumption \\nand SO2 emissions 10, 11 – 12, 12, 59, \\n60, 90; technological factors for effluent \\nSO2 emissions in 92 – 95, 97\\npremature deaths: DALYs and 3; reduction \\nand causes of 1, 2\\nprovincial governments, on policy making 28\\npublic: in democracy 6; health, goal for \\nprotecting 65\\npulverized coal (PC) combustion 93\\nQin dynasty (221–207 BCE) 185\\nQinghai Province 52\\nRebels (zao fan pai) 25\\nRed Guards (hong wei bin) 25\\n\\n\\n198  Index\\nRegional Supervision Bureaus 30\\nregulation, economic theory of 189\\nrent-dissipation effect 162\\nresearch and development (R&D) \\nexpenditures 161, 161\\nrevenue: and expenditures, of central and \\nlocal governments 33 – 35, 33; effect 162\\nRicardo, D. 108\\nrule-based environmental governance \\n180 – 181\\nSARS and environmental protection \\n(2003–2012) 20 – 22\\nscience and technology 36\\nScientific View of Development 21, 63\\nsectoral employment changes and GDP \\ngrowth rates, across China 18, 19\\nShanghai: revenue–expenditure gap for 35; \\nSO2 emissions 48, 52, 55\\nShang Yang 186\\nShanxi Province, distributing goals to \\nmunicipality 59, 60 – 61\\nShenzhen, AQI in 71, 72\\nShijiazhuang: daily O3 concentrations in \\n69, 70, 71; daily PM2.5 concentrations in \\n68 – 69, 69; daily SO2 concentrations in \\n68, 68; monthly average AQI in \\n69, 70\\nSingapore, polity democracy index for 5, 6\\nSO2 (sulfur dioxide) emissions: in 9th \\nFive-Year Plan 18, 62, 90, 92; in China \\n9 – 10, 10 – 12, 12; controlling 48; daily \\nSO2 concentrations, in Shijiazhuang \\n68, 68; decomposition of 90, 91; \\ndesignated intensity, in coal power \\nplants 58, 58; economic growth and 84; \\nemission mitigation goals of 67 – 69, \\n83; environmental capacity for 47; goal \\nimplementation 50, 58, 63; intensity of \\nelectricity generation 96; key factors \\nfor 84 – 92; mitigation of 10, 12, 20, \\n43, 51, 65, 67 – 68, 72, 77 – 78, 84, \\n181 – 182, 185, 191; policy scope for \\nachieving mitigation goals 84 – 100; \\nin power and nonpower categories 51, \\n63; reduction goal of 43 – 44, 45 – 46, \\n48 – 49, 59 – 60; regulations 44, 66, 118; \\nremoval efficiencies/rates 51, 57, 94, \\n118; by sector 10, 11; setting up goals \\n47; technical measures for 95 – 100; \\ntechnological factors for 92 – 95; \\nunderestimation of 112; in United States \\n12, 12\\nSO2 mitigation path: and economic \\ndevelopment 174; environmental \\nindustry under goal-centered 169 – 174; \\ngoal-centered 149 – 154; model \\nprojection of 154; technology licensing \\nunder goal-centered 155 – 169, 158\\nSO2 scrubbers: BOT contracts for 173; \\ncapacities 95, 97 – 99, 97 – 100, 171; \\ncapital costs of 112, 115, 151 – 152, 151; \\ncategories 99; coal-fired power and 79, \\n97, 97, 98, 99, 106; compliance costs of \\n109; compliance on operation 109 – 115; \\ndata, in China’s coal-fired power plants \\n114; deployment and operation of \\n149 – 151, 150; designing 93; economies \\nof scale and 111 – 112; effluent discharge \\nfee 115 – 116; electricity-consuming \\ncomponents of 111; firms 156; \\ngeographic distribution of 99; goals \\nand policies in compliance decisions \\non operation 119; installation 94 – 96, \\n95, 106 – 107, 151, 159, 171, 185; \\ninternational competitiveness of industry \\n171 – 174; noncompliance behaviors on \\noperation 112 – 115; nonoperation of \\n116 – 117; O&M costs of 111 – 112, 115, \\n151, 152; operation in Jiangsu Province \\n106, 106; planning 51, 55; product of \\n111; reduction of emissions through \\n51, 85, 96, 105; technologies 100, \\n101, 109 – 112, 156; see also reversing \\nnoncompliance\\n“Socialistic Thoughts with Chinese \\nCharacteristics in the Xi Jinping Era” 23\\nsocial psychology 42\\nsocial welfare system 181\\nSouth Korea: GDP in 7; polity democracy \\nindex for 5, 6\\nsouth–north water diversion project’s \\nenvironmental protection 27\\nStanding Committee of the Political \\nBureaus 21\\nstate and market 26, 39, 174\\nState Council, 1998 reform of 26\\nState Environmental Protection \\nAdministration (SEPA) 26, 44, 45 – 46, \\n50, 58, 64, 78, 98\\nState Environmental Protection Agency \\n(1984) 25, 26\\nState Oceanic Administration 27\\nstate-owned enterprises/firms 18, 156\\nSteinfeld, E. S. 112, 113\\nStigler, J. 189\\n\\n\\nIndex  199\\nSuggestions on Designing the National \\n11th Five-Year Plan, The 45, 46\\nsulfur contents 94, 111; coal consumption \\nand 63, 78; control of 85; distribution in \\ncoal power plants 93 – 94, 95; see also \\nSO2 entries\\nsuspension policy 64\\nsustainability of environmental political \\nwill (2013–present) 22 – 24\\nTang dynasty (618–907) 186\\ntax compliance 121\\ntechnology licensing under goal-centered \\nSO2 mitigation path 155 – 169; criteria \\nof effective market design 165 – 167; \\nstrategy of domestic technology \\nlicensees 156 – 162, 158; strategy of \\nforeign technology licensors 162 – 165; \\ntechnology market emerging in China, \\nreasons for 165 – 169\\nthermal contents of coal 111\\n“three representativeness” 20\\nTibet: governmental revenue/expenditures \\n35; SO2 emissions 48, 52\\ntop-down goal distribution 49 – 61\\nTotal Emission Control regime 66\\nunemployment 20\\nUNFCCC (United Nations Framework \\nConvention on Climate Change) 42, 50\\nUnited States: average prices of wind \\nturbines in 172 – 173, 172; CEMSs cost \\nin 113; Clean Air Act Amendments \\n(1990) 12, 31, 49, 78, 79, 105, 184; \\ncoal consumption 12; deployment and \\noperation of SO2 scrubbers in 149 – 150, \\n150; economic growth in 85, 85; energy \\nconsumption and electrification rate 89; \\nEnergy Information Administration 152; \\nEnvironmental Protection Agency (EPA) \\n113; firms in 170, 171; GDP in 7; \\ngovernance indicators of 8 – 9, 8; patents \\non environmental technology 161 – 162, \\n162; polity democracy index for 5, 6; \\npower sector shares of coal consumption \\nand SO2 emissions 10, 11; SO2 emissions/\\nintensities in 12, 12, 49; unit capital costs \\nof SO2 scrubbers in 151 – 152, 151; wind \\nenergy development in 168 – 169, 168\\nuniversity-established firms 156\\nunsafe water/sanitation/handwashing 1, \\n2, 3, 4\\n“Upgrading and Retrofitting Action Plan \\nfor Energy Conservation and Pollution \\nMitigation in the Coal-Fired Power \\nSector” policy 96\\nveto 64\\nWang Xinfang 45 – 46\\nWanli (Emperor) 186\\nwater: consumption 112; environment \\nmanagement 27; pollution, health \\nimpacts of 3; see also air and water \\npollution\\nWen Jiabao 18, 20, 21, 46\\nwind: energy development 168 – 169, 168, \\n173; and solar energy 89; turbines, \\naverage prices of 172 – 173, 172\\nWinslow, M. 6\\nWorld Bank 8, 31, 180\\nWorld Trade Organization in 2001 20\\nXie Zhenghua 64\\nXi Jinping 17, 18, 22\\nYelv Chucai 186\\nZhejiang Province 62\\nZhongnanhai (Central and Southern \\nSeas) 186\\nZhu Rongji 18\",\"difficulty\":\"easy\",\"domain\":\"Multi-Document QA\",\"length\":\"medium\",\"question\":\"Which of the following statements below are false according to the three documents related to environmental policy in China.\\n(1) LCC has the potential to draw substantial foreign direct investment by lowering compliance expenses and fostering technological advancements. Additionally, LCC positively influences FDI inflows in neighboring cities through spillover effects.\\n(2) Since 2011, China has initiated several carbon emissions trading system pilot projects in cities such as Beijing, Tianjing, Shanghai, Chongqing, Hubei, Guangdong, and Shenzhen. By 2017, a national carbon trading market had been formally established.\\n(3) The environment policy theory supports government programs and organizations in converting public needs, like environmental concerns, into actionable policy outputs, such as feedback from the public and advocacy from interest groups. It was created to enhance public awareness of policy matters and provide citizens with a way to voice their concerns, thereby bringing issues to the forefront of the government's policy priorities.\\n(4) At the central level, the category labeled \\\"others\\\" constitutes the largest segment. In 2015, it made up 64.1% of the total 2,023 environmental protection personnel, compared to over 80% before 2009. This predominant proportion illustrates that environmental policymaking in China both demands and receives substantial intellectual support. In contrast, the \\\"administration\\\" category included only 342 personnel in 2015, with its share consistently around 12% from 2004 to 2015, according to the data available.\\n(5) Ambient PM pollution resulted in 404,000 premature deaths in 1990 and increased to 852,000 in 2017, more than doubling during this period. Its global share rose by 5%. In 2000, ambient PM pollution surpassed indoor air pollution as the leading cause of premature deaths.\",\"sub_domain\":\"Governmental\"}","display_format":"text","language":"","answer_status":"published","assets":[],"source_url":"https://huggingface.co/datasets/zai-org/LongBench-v2","history":"initial import","indexing_mode":"noindex","subproblems":[],"grids":[]}