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Article

Policies for Achieving Carbon Reduction in China from 1995 to 2022: A Review and Content Analysis

by
Kai Zhou
1,
Ziyi Qu
1,
Jun Wang
1,*,
Jianli Chen
2 and
Junkai Zhang
1
1
School of Management Engineering, Qingdao University of Technology, Qingdao 266520, China
2
College of Engineering, Tongji University, Shanghai 200092, China
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(3), 1326; https://doi.org/10.3390/su17031326
Submission received: 19 December 2024 / Revised: 18 January 2025 / Accepted: 4 February 2025 / Published: 6 February 2025
(This article belongs to the Special Issue Achieving Carbon Neutrality: Recent Progress of Sustainable Energy Economic, Energy Policy and Energy Transition)
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Abstract

:
The formulation and implementation of carbon reduction policies are pivotal strategies for attaining the Carbon Peaking and Carbon Neutrality objectives in China, yet there has been limited in-depth research at the policy level. This study systematically compiled 179 central government carbon reduction policy documents and 1183 local government carbon reduction policy documents from China. These policies were classified into command-and-control (CC), market-based (MB), and public participation (PP) categories based on their policy tools. Through detailed content analysis, the intensity of each policy within each category was calculated and the distributions of both quantity and intensity were analyzed. Subsequently, a multiple regression analysis was conducted to evaluate the impact of policy intensity on carbon emissions at the provincial level. The findings highlight a more pronounced policy activity and intensity in the eastern regions relative to the central and western regions, reveal the dominance of CC policies in terms of both their prevalence and intensity, and identify a counterintuitive increase in carbon emissions associated with CC policies. This research elucidates the landscape of China’s carbon reduction policies, offering nuanced insights into their distribution, intensity, and effectiveness in lowering carbon emissions, often a major concern of policymakers, researchers, and industry stakeholders.

1. Introduction

Global warming and climate change represent formidable challenges confronting the global community. The intensification of human activities, coupled with the rapid pace of industrialization, has precipitated significant and potentially irreversible impacts on the Earth’s ecosystems and climatic systems [1]. Notably, China’s carbon dioxide emissions have surpassed those of the United States since 2007, eclipsing the combined emissions of the United States, 27 EU countries, and the United Kingdom by 2012 and constituting 28% of the world’s carbon dioxide emissions by 2019 [2]. As a significant contributor to global carbon emissions for that year [3], China has pledged to reach a peak in carbon emissions by 2030 and attain carbon neutrality by 2060 [4]. In pursuit of these carbon peaking and carbon neutrality (CPCN) goals, China has advanced its efforts to curb carbon emissions through the enactment and execution of an array of carbon reduction policies [5]. These initiatives encompass the Action Plan for the Energy Development Strategy of the People’s Republic of China (2021–2035), the Notice on Strengthening Carbon Market Regulation, the CPCN Target Allocation Plan, the Notice on Launching the Carbon Emission Trading System, and the Guiding Opinions on Promoting Clean Energy Consumption [6].
Recent research has predominantly concentrated on the downstream effects of China’s carbon reduction policies, yet there is a notable gap in the direct examination of the policies themselves, resulting in a lack of comprehensive policy analysis [7]. For instance, numerous studies have evaluated the tangible outcomes of carbon reduction initiatives on aspects such as energy composition, industrial evolution, and carbon neutrality objectives [8,9]. This includes shifts in energy utilization patterns, industrial reconfiguration, and carbon emission trends following policy implementation [10,11]. Additionally, researchers have examined the implications of these policies on economic growth and job creation [12], studied the impact of policy uncertainty on carbon emissions [13], and analyzed their influence on enterprise labor demands [14]. Previous research has not adequately addressed the policy’s dynamic evolution or conducted systematic quantitative assessments of the initiatives enacted by both central and local governments [15].
Given the disparate regional economic, technological, and energy consumption landscapes, carbon emission distributions are inherently uneven. For instance, the burgeoning manufacturing sector, notably in the metallurgy of metals and non-metals in areas such as Shandong and Hebei, contributes to elevated carbon emissions [16]. This raises several pertinent questions regarding carbon reduction policy research: What is the status quo of carbon reduction policy research via systematic review? How can the intensity of the carbon reduction policy be quantitatively measured? Is there a significant variance in carbon reduction policy intensity across different regions? Which areas should be prioritized to fulfill the CPCN objectives in the future? Addressing these inquiries is crucial for enhancing understanding and optimization of China’s carbon reduction strategy, offering benchmarks for other developing nations, and furnishing actionable insights for policymakers [6]. Despite the critical role of policy document analysis in refining the carbon reduction trajectory, few researchers have dedicated attention to this approach [17]. In addition, while the majority of studies on policy primarily focus on the design and application of policy instruments, the classification of policy types, and the strategic interactions or game dynamics among central and local government bodies during the implementation process [18], few have explored the classification of carbon reduction policies based on China’s policy driving mechanisms into command-and-control (CC), market-based (MB), and public participation (PP) categories. Even fewer studies have examined the distribution of these policy types, intensity, and impacts on carbon emissions.
In the last few years, the growing focus on carbon reduction policies has spurred both domestic and international researchers to apply various quantitative methodologies for policy evaluation. Prominent among these methods are bibliometrics, text mining, and content analysis. Bibliometric analysis, in particular, can uncover trends and focal points within policy research by scrutinizing policy literature citations. However, this approach faces challenges in delving into the intricate details and underlying concepts of the policy documents [19,20]. In the realm of policy analysis, text mining offers a promising avenue for distilling key topics and keywords from policy documents. However, the inherent complexity of policy contexts and terminology poses significant challenges to semantic interpretation within text mining processes. To enhance result accuracy, meticulous text cleaning and word segmentation are essential prerequisites [21].
Given these considerations, this study adopts content analysis as its primary methodological framework, aiming to construct a three-dimensional quantitative evaluation model of policy texts, encompassing policy intensity, objectives, and strength [22]. Content analysis, recognized for its systematic and objective approach, facilitates the quantification of phenomena, policy narratives, or communicative content [23], thereby enabling the transformation of qualitative policy text into quantifiable data [24]. This method supports the detailed examination of policy texts, revealing insights into policy aims, contextual backgrounds, and specific measures, thus enabling a nuanced understanding of policy texts [25,26,27].
This study meticulously reviews and analyzes China’s carbon reduction policies spanning from 1995 to 2022. Employing content analysis, it systematically quantifies a vast array of carbon reduction policy documents from both central and local Chinese government levels. This approach not only investigates the intensity and efficacy of diverse policy instruments across governmental tiers but also facilitates a comprehensive understanding necessary to address the posed questions. Furthermore, the study incorporates multiple linear regression analysis to examine the impact of various types of carbon reduction policies on provincial carbon emissions in China, utilizing data from the China Emission Accounts and Datasets (CEADs) and integrating policy intensity, lagged effects, and potential confounders to capture the long-term policy impact. Through this systematic review, researchers can swiftly grasp the developmental context and progress of pertinent studies, pinpoint critical issues and research gaps, and subsequently embark on more focused, effective, and systematic subsequent inquiries. The structure of this study is organized as follows: Section 2 reviews existing literature, Section 3 delineates research methods, Section 4 presents research results, Section 5 engages pertinent discussions, and Section 6 discusses research conclusions and future directions.

2. Literature Review

2.1. Carbon Reduction Policy

Research on carbon reduction policies is broadly categorized into two realms: (1) evaluating the effects of carbon reduction policy implementation on carbon emissions, the achievement of carbon neutrality, and related industries; and (2) examining the prevailing state of carbon emissions to offer recommendations for the selection, formulation, and optimization of carbon reduction policies.
Within the first realm, Wang et al. [14] demonstrated that low-carbon pilot policies (LCPPs) led to a 14.6% increase in labor demand within enterprises, employing a difference-in-differences (DID) model for their analysis; Yu et al. [28] highlighted the external impacts and green transformation facilitated by carbon market pilot policies, evidenced by policy spillover effects and the relocation of industrial enterprises; Wang et al. [10] assessed carbon trading policies within China’s ‘Five in One’ construction model, revealing their substantial and lasting influence on achieving carbon neutrality, with cultural and political constructions playing significant mediating roles; Chen et al. [29] affirmed the effectiveness of carbon trading in enhancing the carbon performance of the energy sector, thus promoting carbon neutrality; Lai et al. [30] found that carbon emission trading pilot policies spurred innovation in both regulated and non-regulated industries; Li et al. [31] observed significant carbon reduction and spatial spillover effects in the transportation sector due to carbon emission trading policies; Wang et al. [32] noted an exacerbation of overcapacity issues in enterprises due to the same policies; and, lastly, Hong et al. [33] confirmed that carbon reduction policies significantly encourage green innovation, particularly in heavily polluting industries, showcasing the policies’ broad and varied implications. Downing and White [34] observed that, in comparison to CC policies, MB policies are more effective in fostering corporate innovation and improving efficiency. Similarly, Milliman and Prince [35] argued that direct regulatory controls generally offer minimal incentives for driving technological advancements, whereas market-based mechanisms, such as emissions taxes and permit auctions, provide stronger incentives for innovation. Williams [36] also highlighted that MB policies encourage greater efficiency improvements compared to CC regulations.
Within the second realm, Gallagher et al. [37] scrutinized the policy discrepancies hindering the attainment of carbon peak in China and revealed the necessity for the Chinese government to fully actualize its policies, providing such recommendations as expediting the power industry reform, bolstering China’s carbon emissions trading framework, and developing new carbon pricing strategies for previously unregulated sectors. Zhu et al. [38] delved into the dynamics of carbon emissions within the Yangtze River Delta, assessing carbon reduction pressures and potentials, and proposed a regional collaborative carbon reduction mechanism. Their study introduced a bespoke set of emission reduction policies tailored for the Yangtze River Delta, offering insights for the nationwide application of carbon reduction strategies and fostering national collaboration in carbon mitigation. Zhang et al. [39] developed the GLOBUS model to create a global dataset on building stock turnover, facilitating the measurement of carbon emissions and decarbonization potential across countries while highlighting the role of building renovation in reducing new construction needs and accelerating sector-wide decarbonization. Deng et al. [40] evaluated the real-world energy use and carbon emissions of China’s top-selling plug-in hybrid electric vehicle (PHEV) models, revealing significant regional differences in energy consumption and carbon emissions while providing policy recommendations to accelerate the carbon-neutral transition in the passenger car sector.
Despite the prevalent focus on evaluating the impacts of existing policies on carbon emissions and related sectors, as well as the refinement of these policies, there has been a noticeable gap in research directly addressing the policies’ substantive content. For the successful realization of CPCN objectives, the meticulous crafting of policies and the strategic selection of policy tools is imperative [41]. However, the current body of research is predominantly characterized by conceptual definitions and qualitative analyses, with a notable dearth of policy quantification efforts and quantitative studies related to carbon reduction policies. This gap hinders the accurate assessment of carbon reduction policies’ impact on achieving China’s CPCN goals. In response to these challenges, the present study undertakes a thorough and systematic quantitative examination of China’s carbon reduction policies spanning from 1995 to 2022. By commencing with an analysis of the policies themselves, this research aims to methodically explore the trajectory of policy evolution, elucidate the correlation between policy stringency and carbon emission trends, and introduce effective methods to quantify carbon reduction-related policy texts. This approach allows for a deeper exploration of policy intensity, addressing the scarcity of quantitative analyses in the field and paving the way for a more precise evaluation of policy impacts on carbon emission reduction goals.

2.2. Policy Intensity

Quantitative assessment of policy intensity emerges as a crucial methodology in the realm of policy analysis, enabling the examination of policy instruments through the establishment of measurable objectives, delineated budgets, explicit goals, timelines, and other quantifiable parameters [5]. This metric not only mirrors the governmental commitment to CPCN objectives but also gauges the influence of policies on industrial evolution [42]. To facilitate the study of policy intensity, scholars have introduced a variety of indicators. Peng et al. [22] devised a framework to evaluate the vigor of technological innovation policies across three facets: the intensity of the policy, its objectives, and the measures employed. Schaffrin et al. [43] proposed a climate policy intensity indicator system spanning six dimensions: objectives, scope, integration, budget, implementation, and monitoring. Furthermore, Zhang et al. [5] categorized environmental policies into CC, MB, and PP types to assess environmental policy intensity.
The quantification of policy intensity necessitates a meticulous manual review and annotation of policy documents to identify and evaluate overarching indicators [44]. This study employs content analysis to systematically quantify China’s carbon reduction policies from 1995 to 2022, crafting a three-dimensional evaluation model that encompasses policy intensity, objectives, and strength. The intensity of a policy is quantified by the product of its objectives and strength, offering a comprehensive framework to analyze the efficacy and impact of carbon reduction policies within a quantitative paradigm.

3. Research Methods

Figure 1 depicts the research methods used, divided into three sections: data collection and screening, content analysis and intensity calculation, and policy effect assessment. First, carbon reduction-related central and local policies were searched, collected, and screened from multiple data sources. Following that, policy documents were classified, policy strength and goals were scored, and policy intensity was calculated. Finally, the policy effect was assessed using regression analysis to quantify its impact on carbon emissions.

3.1. Data Collection and Screening

The collection of carbon reduction-related policies involved a thorough search through the PKULAW database (https://pkulaw.com/), Wanfang database (https://c.wanfangdata.com.cn), and the official websites of both central and local Chinese governments. Keywords such as ‘carbon emission’, ‘renewable energy’, and ‘low carbon transition’ were used to retrieve policy texts, and the time range was set between 1995 and 2022, aiming for an extensive and thorough dataset conducive to comprehensive analysis. Each policy text underwent a meticulous manual screening process to ensure the relevance of the retrieved policies and duplicated or less relevant documents were removed in this process, yielding a corpus of 179 central government policies and 1183 local government policies from 30 different provinces related to China’s CPCN targets in total.

3.2. Content Analysis and Intensity Measurement

Policy tool classification is pivotal for environmental policy content analysis as it delineates the spectrum of governmental approaches to managing environmental issues, distinguishing between direct regulatory interventions, economic incentives, and engagement strategies to harness public participation [5,6,45,46]. Based on policy-driving mechanisms, the design and implementation of policy tools, and previous research [5,47,48], this study classifies carbon reduction policies into three categories: CC, MB, and PP. Detailed explanations of each category and their associated policy tools are presented in Table 1. CC policies are characterized by their mandatory nature, relying on administrative tools such as governance mechanisms and regulatory standards [49]. MB policies, on the other hand, use market-driven instruments such as fiscal measures, emission charges, emissions trading, and product promotion catalogs [50]. PP policies focus on involving both public and private sectors in environmental protection, empowering them to actively contribute [5].
Policy intensity is a powerful tool for quantitative policy research, reflecting the government’s attitude and enforcement intensity towards policy implementation, which is highly correlated with the scope and nature of the policy itself. A higher policy intensity implies more vigorous policy enforcement. Policy intensity is calculated by multiplying the indicator scores from Table 2 and Table 3, following a methodical approach to quantify both policy strength and policy goals, building on insights from prior research [5,15]. Policy strength, which reflects the legal force behind policies, is determined by the product of the document type score and the leading body score. Document types are assigned a value from 1 to 5 based on the policy level, with ‘Notice, Announcement, or Letter’ having the lowest value of 1 and ‘Law’ receiving the highest value of 5 due to its strong enforcement power. The leading body is also assigned a value from 1 to 5 according to the agency’s administrative level, with the National People’s Congress and the State Council representing the highest administrative and legislative bodies, thus receiving a score of 5. If the leading body is a district-level or county-level bureau, the policy is assigned the lowest value of 1. In contrast, policy goals, which reflect the intended outcomes, are evaluated based on the clarity and specificity of the targets defined within the policy framework. Policies with ‘detailed quantitative targets’ are assigned a score of 5, while those with ‘qualitative targets’ are assigned a score of 1.
To ensure a rigorous and uniform application of the carbon reduction policy classification criteria and scoring standards, three experts were thoroughly briefed on the methodology, with any ambiguities clarified through discussion. Initially, fifty policy texts were randomly selected for classification and scoring by the researchers. Discrepancies in their assessments were resolved through consensus-building discussions. This process was repeated with another set of fifty environmental policy texts, achieving classification and scoring consistency rates of 86% and 90%, respectively. After addressing any areas of disagreement, the researchers proceeded to classify and score the entire dataset of 179 central and 1183 local policies. The final assessment yielded high consistency rates of 94.4% and 98.9% for central policy classification and scoring, and 98.5% and 99.4% for local policy classification and scoring, respectively. These high levels of agreement, surpassing the 80% threshold, confirm the results pass the reliability test and are, therefore, acceptable [6,54].
Finally, the intensity of each policy is calculated using Equation (1):
PI = PG × (DT × LB)
where PI represents the policy intensity of each policy, PG represents the policy goals score, DT represents the document type score, and LB represents the leading body score of the policy. The cumulative policy intensity (CPI) for policy type i, in year j, for province k is calculated using Equation (2):
C P I j , k i = ∑ s ∈ S j , k i s i ∈ { C C , M B , P P } , j ∈ [ 1995,2022 ] , k ∈ [ 1,30 ]
where S j , k i represents the set of all policy intensity scores for policy type i, in year j, for province k, and s represents an individual policy intensity score within the set S j , k i .

3.3. Policy Effect Assessment

This study leverages the multiple linear regression analysis to empirically assess the influence of carbon reduction policies on provincial carbon emissions in China. The carbon emissions data, derived from the CEADs database [55,56,57,58], provides a comprehensive basis for this analysis and is merged with the previously calculated policy intensity data, yielding a combined dataset that contains 750 instances across 30 different provinces and 25 years. To account for external influences on provincial carbon emissions, the emissions data from the preceding period are incorporated into the regression model as a proxy for potential confounders, such as economic growth, industrial structure, energy consumption, and technological advancements. Recognizing the temporal nuances associated with policy impacts, the model also integrates the lagged effects of carbon reduction policies, acknowledging that the ramifications of these policies often materialize over time rather than immediately upon implementation. Consequently, the study formulates Equation (3) for its regression analysis, meticulously designed to capture the effects of carbon reduction policies on reducing carbon emissions at the provincial level:
C E j k = α + β 1 × C E j − 1 k + β 2 × C C j − l C C k + β 3 × M B j − l M B k + β 4 × P P j − l P P k + ε j k
where C E j k represents the carbon emissions for province k in year j, C C j − l C C k represents the cumulative policy intensity of CC type for province k in year j − l C C , M B j − l M B k represents the cumulative policy intensity of MB type for province k in year j − l M B , and P P j − l C C k represents the cumulative policy intensity of PP type for province k in year j − l P P . The selection of different lag periods l C C , l M B , and l P P for different policy types will be based on both the coefficient significance level and the AIC criteria.

4. Results

4.1. Central and Local Carbon Reduction Policies Trends

China’s carbon reduction policy landscape has undergone significant transformation, evolving from a focus on ‘energy conservation and emission reduction’ to embracing ‘low-carbon’ development, and ultimately advancing into the current ‘carbon peaking and carbon neutrality’ era. This evolution is demarcated into three distinct stages: the initial phase of development and transformation spanning from 1995 to 2007, followed by a period of deepening reform from 2007 to 2016, and culminating in the transition from ‘low-carbon’ to ‘CPCN’ strategies from 2016 to the present. An analysis of the policy issuance trends, as depicted in Figure 2, reveals a marked increase in the number of carbon reduction policies enacted by both central and local governments, with the third stage witnessing the highest policy issuance. While the issuance of central policies exhibits relatively stable fluctuations, local policy issuance displays more pronounced variability. The overall trajectory of local policy issuance mirrors that of central policies, albeit with local policies experiencing greater fluctuation, highlighting the dynamic response of both levels of government to the evolving priorities of China’s carbon reduction agenda.

4.2. Trends in Carbon Reduction Policies Across Provinces

Figure 3 illustrates the distribution of carbon reduction policies over time and across different provinces of China, with the size of the nodes representing the number of policy releases. Initially, prior to 2005, the central government was predominantly responsible for issuing carbon reduction policies. Post-2005, there was a noticeable shift as policy issuance expanded to local jurisdictions, indicating a vertical diffusion from the central to local levels. During the early stages, only four provinces began to explore carbon reduction initiatives. A significant horizontal proliferation of provincial carbon reduction policies was observed between 2007 and 2009, encompassing all three geographical regions of China. From 2010 onwards, there has been a substantial influx of provincial policies. Notably, four eastern provinces—Beijing, Guangdong, Shandong, and Shanghai—have demonstrated a consistent release of carbon reduction policies since their initial introduction, showcasing temporal continuity in policy issuance that is not observed in many other provinces. Furthermore, there is a pronounced regional disparity in policy issuance: the eastern region leads with an average of 53.1 policies per province, followed by the middle region with 33.8 and the western region with 27.3. Guangdong tops the list with the highest number of policies (113), followed by Shanghai (94), Fujian (82), and Shandong (67), indicating that the provinces with the most policies are all located in the eastern region, whereas Xizang has the lowest count with only one carbon reduction policy issued. The disparities in the issuance of carbon reduction policies across Chinese provinces are driven by economic, industrial, political, and structural differences [59]. Economically developed eastern provinces, such as Beijing, Shanghai, and Guangdong, have greater financial and technological resources to implement policies, along with higher environmental stakes due to dense populations and industrial activity. Their diversified industries and proactive governance enable the adoption of advanced low-carbon technologies and participation in pilot programs such as carbon trading schemes. In contrast, the middle and western provinces, reliant on energy-intensive industries and traditional energy sources such as coal, face greater challenges in transitioning to low-carbon models. Urbanization rates further influence policy focus, with urbanized eastern regions prioritizing emissions from transportation and buildings, while resource-dependent regions emphasize cleaner coal technologies. These regional disparities underscore the importance of tailoring carbon reduction strategies to align with each province’s unique economic and structural conditions.

4.3. Distribution of Carbon Reduction Policy Types

Figure 4 delineates the distribution of carbon reduction policies across different types, with subfigures 4 (above) and 4 (below) representing central and local policies, respectively. At the central level, China has deployed a diversified array of carbon reduction policies to meet its targets, exhibiting a notable shift in policy preferences over time. Prior to 2005, the focus was predominantly on CC measures aimed at fostering energy conservation and emission reduction. From 2006 onwards, the repertoire expanded to include MB and PP policies. Although CC policies have been consistently implemented throughout the period from 1995 to 2022, with the exception of 2010, their prevalence fluctuated, decreasing significantly between 2006 and 2018, before witnessing a sharp rise from 2019 to 2022. In terms of issuance volume, CC policies lead with 82 enactments, followed by MB policies with 61 and PP policies with 36.
At the local level, the early stages saw a predominance of CC policies, which continued until 2007. Subsequently, both MB and PP policies gained momentum. The issuance of all three policy types exhibited upward trends from 2007 to 2016, experienced a decline from 2017 to 2020, and saw a resurgence in 2021 and 2022. The distribution of policy types at the local level shows a less pronounced disparity compared to the central level, with CC policies accounting for 469 enactments, MB policies for 358, and PP policies for 356, indicating a more balanced approach to policy deployment across the provinces.

4.4. Policy Intensity of Different Types at the Provincial Level

Figure 5 delineates the cumulative intensity of carbon reduction policies across different provinces, categorized by policy type. It reveals that Henan, Beijing, and Hunan lead in terms of cumulative CC policy, with intensity scores of 393, 370, and 258, respectively. For MB policies, Shanghai, Hubei, and Fujian stand out with cumulative intensity scores of 186, 145, and 144, respectively. In the realm of PP policies, Guangdong, Fujian, and Shanghai exhibit the highest cumulative intensity scores of 115, 81, and 72, respectively. Additionally, when considering the total cumulative intensity of all three types, Beijing, Shanghai, and Henan emerge as the top provinces, with respective intensity scores of 502, 453, and 443.
The analysis further shows that the average cumulative policy intensity significantly varies across the three types, with CC policies averaging 149.1, MB policies averaging 58.7, and PP policies averaging 31.8. This indicates a predominant reliance on CC policy measures. Geographically, the average cumulative policy intensities differ across regions, with the eastern region leading at 304.7, followed by the middle region at 248.6, and the western region at 173.8. This distribution underscores the variances in policy intensity across China’s diverse provincial landscapes.

4.5. Carbon Reduction Policy Effect Assessment

A multiple regression analysis was employed to assess the impacts of three distinct types of carbon reduction policies—CC, MB, and PP—on policy outcomes, particularly focusing on carbon emissions. The analysis, as detailed in Table 4, yields an R-square of 97.8%, suggesting a high level of model fit and indicating that the model effectively captures the variation in carbon emissions outcomes.
The findings reveal a nuanced picture of policy impacts: CC policies are associated with an increase in carbon emissions, evidenced by a coefficient of 0.584 (p-value = 0.010). Historically, these policies have played a crucial role in China’s environmental management, particularly in transitioning from a planned economy, by enforcing energy conservation and pollution control measures. Despite their past successes, the analysis suggests that command and control mechanisms alone may not suffice for reducing carbon emissions in China’s current developmental context. In contrast, MB policies are shown to reduce carbon emissions, with a coefficient of −0.630 (p-value = 0.016), underscoring their effectiveness in leveraging economic incentives to guide behavior towards more environmentally friendly practices. This transition towards MB mechanisms reflects an evolution in policy strategy, emphasizing cost-benefit considerations and investment in sustainable development. Finally, PP policies emerge as the most potent in curbing carbon emissions, with a coefficient of −1.550 (p-value = 0.014). This finding highlights the critical role of societal engagement in achieving CPCN objectives, where legal mandates and market incentives are complemented by encouraging grassroots initiatives and fostering a collective environmental ethos. The significant impact of PP policies underscores the importance of inclusive approaches that mobilize widespread societal action toward carbon neutrality.

5. Discussions

5.1. Command-and-Control Policy

The CC policy has been a predominant strategy in China’s policy landscape, both in the quantity of policies enacted and their average intensity. Figure 4 illustrates that China’s initial endeavors in energy conservation and emission reduction heavily relied on CC policies, aiming to curtail pollutant emissions via obligatory emission standards [60]. However, the journey toward carbon reduction in China is fraught with challenges, including economic and technological uncertainties [61]. Given the current economic climate and technological capabilities, the achievement of dual carbon targets represents a formidable challenge that requires sustained effort over time [29]. Although CC policies have been instrumental in the early stages of promoting energy conservation, their limitations have become more pronounced with ongoing economic advancement, particularly their inflexibility in application [62]. Furthermore, the effectiveness of these policies is often contingent upon local enforcement, which can lead to inconsistent implementation [63].
The analysis presented in Table 4 reveals that CC policies might inadvertently lead to an increase in carbon emissions. Specifically, CC policies, rooted in coercive policy authority, fail to inspire voluntary participation from businesses and the general public. This lack of encouragement significantly diminishes the natural willingness of market participants to engage in carbon reduction efforts [53]. Such policies, by enforcing uniform emission reduction targets across all enterprises within a given province or city without accounting for their diverse characteristics, breach the principle of equal marginal cost-effectiveness. This one-size-fits-all approach limits companies’ ability to optimize profits in their production processes, thereby reducing operational efficiency and discouraging technological innovation [64]. As a result, CC policies are ineffective in achieving sustainable low-carbon development, showing no significant impact on improving efficiency or reducing carbon dioxide emissions, a conclusion further supported by Zhao et al. [65]. While CC policies establish strict environmental regulations, uneven enforcement at the local level may undermine their effectiveness, particularly in regions where economic growth is prioritized over environmental goals [66]. The rigid nature of many CC policies may also limit their adaptability to evolving economic and technological landscapes, reducing their effectiveness in addressing emissions in dynamic environments [67]. Unlike MB policies, CC policies do not inherently encourage the adoption of low-carbon technologies, which could hinder long-term emissions reductions. When used in isolation, CC policies may be less effective, requiring complementary measures such as MB or PP policies to amplify their impact [65].
However, as shown in Figure 4, CC policies still dominate China’s carbon reduction strategy. Consequently, there is an increasing call for the Chinese government to gradually shift away from reliance on CC policies and toward more flexible, non-coercive policy instruments, with greater emphasis on coordinating different policy tools to achieve better environmental outcomes [68,69].

5.2. Marked-Based Policy

MB policies are less prevalent than CC policies, both in their numerical count and in average intensity. This observation aligns with the analysis by Luo and Zhu [70], who, through a quantitative examination of China’s low-carbon policy documents, deduced a similar pattern. Despite their lower frequency, MB policies offer a dynamic and flexible approach to reducing emissions, leveraging economic levers and monetary incentives to encourage polluters towards emission reduction [71]. In contrast, CC strategies have been critiqued for their potential to deter technological innovation and investment [72].
Empirical evidence, as detailed in Table 4, underscores the efficacy of MB initiatives in curbing carbon emissions. The research by Ji et al. [73] on the carbon emission trading pilot policies within the construction sector demonstrates a significant decrement in direct emissions, supporting the positive impact of MB measures outlined in this study. The effectiveness of MB policies varies significantly across provinces due to differences in economic structures, industrial compositions, and governance capacities. Provinces with advanced economies, such as Guangdong, Jiangsu, and Zhejiang, exhibit higher policy intensity and more effective implementation of MB strategies, as shown in Figure 5. For instance, Guangdong’s Emissions Trading Scheme (ETS) has successfully reduced emissions in energy-intensive industries such as steel and cement, supported by strong market infrastructure and regulatory enforcement [68]. In contrast, central and western regions, such as Gansu and Ningxia, face challenges due to limited market maturity, weaker regulatory capacity, and reliance on energy-intensive industries, which undermine the effectiveness of carbon trading and taxation schemes. MB policies are designed to harness market forces to facilitate the reduction of carbon emissions, employing economic incentives to motivate both corporate and individual actions towards climate change mitigation and carbon neutrality. These policies typically encompass tools such as carbon trading systems, taxes, and quotas to motivate emission reductions by monetizing carbon output. Furthermore, they often support investments in clean energy and low-carbon technologies, steering economic growth towards more sustainable pathways. By employing market mechanisms, such policies not only incentivize environmentally friendly practices across industries but also foster economic development, offering a holistic strategy to address climate change challenges [74,75]. However, the implementation of MB policies can lead to increased administrative expenses, including the costs associated with establishing carbon markets and related disclosure and verification frameworks. Such augmented administrative demands may contribute to an ’inflationary’ effect in policy application, potentially explaining the restrained utilization of MB approaches.

5.3. Public Participation Policy

PP policies, in comparison with the other two policy types, are less prevalent in both quantity and intensity. This observation is consistent with findings from Luo and Zhu [70], who analyzed Chinese low-carbon policy texts, highlighting a similar trend. The effectiveness of PP policies varies widely across provinces, shaped by differences in socioeconomic development, public awareness, and civic engagement capacity, as shown in Figure 5. Economically developed and urbanized provinces such as Beijing, Shanghai, and Guangdong demonstrate a stronger impact of PP policies, supported by a more informed public, better access to technology, and greater backing for environmental initiatives. In contrast, central and western provinces face challenges such as lower public awareness, limited access to information, and weaker civil society networks. Additionally, a lack of transparency in carbon data and limited platforms for public participation further constrain the effectiveness of PP policies in these regions. The importance of public support in climate policy efficacy cannot be overstated, as the absence of public involvement in the policymaking process can lead to resistance towards such initiatives [76]. The public’s engagement with dual carbon issues plays a crucial role in addressing governance limitations, potentially offsetting governmental shortcomings [31]. Research indicates that public awareness and concern for environmental issues significantly contribute to environmental improvements across both developed and developing nations [77,78]. Enhanced information technology has further facilitated public engagement in environmental governance.
Table 4 reveals that PP policies exert the most substantial impact on reducing carbon emissions, a finding supported by Zhang et al. [79], who demonstrated that public involvement significantly lowers both regional carbon emissions and intensity. PP serves as a vital adjunct to governmental efforts in environmental management, offering significant benefits to ecological conservation [80,81]. Despite this, mechanisms for engaging the public in dual-carbon environmental governance and encouraging widespread participation in low-carbon initiatives remain underdeveloped in China. Currently, the enforcement of green measures predominantly resides with governmental authorities. Moreover, the public lacks access to authoritative data on carbon intensity and the efficacy of implemented green measures through official channels. The relatively nascent development of non-governmental organizations focused on carbon reduction in China further hinders the optimal utilization of PP as a policy tool [82].

6. Conclusions

This study employs a content analysis method to meticulously evaluate 179 central government and 1183 local government carbon reduction policy documents. Policies were classified into CC, MB, or PP categories, with the intensity of each policy determined based on predefined criteria for policy strength and policy goals. A subsequent multiple regression analysis quantitatively assessed the influence of each policy type’s intensity on provincial carbon emissions. Key findings include: (1) a consistent upward trend in the number of carbon reduction policies at both the central and local levels; (2) a higher activity level in policy issuance and average intensity in eastern regions compared to middle and western regions; (3) a predominance of CC policies in the carbon reduction policy framework in terms of both quantity and average intensity, followed by MB and PP policies; and (4) a counterintuitive effect of CC policies on carbon emissions, in contrast to the effective emission reduction observed with MB and PP policies, particularly the latter, which exhibited the most significant impact.
The theoretical contribution of this paper lies in its exhaustive and systematic exploration of carbon reduction policy categorization from 1995 to 2022 through content analysis. This study surpasses prior analyses by thoroughly reviewing the entire span of relevant policies within China’s carbon reduction strategy, from its inception to the current state. It sheds light on the evolution of policy numbers and their intensities at both central and local levels, enhancing the objectivity and precision of the findings. Additionally, by employing multiple regression analysis to empirically evaluate the effects of carbon reduction policies on carbon emissions, this research provides valuable insights into the differential impacts of policy intensities, pinpointing the policy types that are most conducive to carbon emission reduction.
This paper also provides practical implications by offering actionable insights and recommendations for policymakers by analyzing the intensity and impact of three distinct types of policy tools on carbon emissions. The findings suggest a strategic recalibration of policy tools to align with the diverse economic, energy, and technological landscapes of each province. Policymakers should rebalance CC, MB, and PP policies to optimize carbon reduction efforts, prioritizing flexibility, innovation, and regional adaptability. Over-reliance on CC policies should shift towards MB mechanisms, such as carbon trading and taxation, to drive market innovation and green investments while enhancing PP initiatives through public awareness campaigns and transparent data-sharing platforms. Joint policies often achieve a “1 + 1 > 2” synergy, where integrating MB and PP approaches amplifies their individual impacts. Strengthening central-local coordination through unified frameworks, regular collaboration, and performance-based incentives can better align national and regional goals. Specifically, there is a recommendation to curtail the reliance on CC policies in favor of amplifying MB and PP approaches, thereby fostering a more synergistic and adaptable policy framework. To bolster China’s carbon emission reduction efforts, it is essential to refine the development of the carbon emission trading market by learning from global best practices. Incorporating market mechanisms into environmental assessments, monitoring, and governance can minimize direct governmental intervention, thus capitalizing on the market’s efficiency. Furthermore, the exploration of carbon taxation within the national tax regime is advocated, aligning with MB policies, to determine an optimal carbon tax rate that reflects the true marginal costs of carbon emissions reduction. This approach would incentivize businesses and consumers to adopt more environmentally friendly practices through market mechanisms. This approach should incentivize the adoption of green technologies while mitigating the tax’s potential adverse effects on various businesses. Promoting public awareness and education on carbon peak and neutrality goals is crucial., Cultivating a ‘green and low-carbon’ consciousness among citizens and transforming it into a motivational force for environmental action is vital., Enhancing access to information and accelerating the development of a professional platform for carbon emission disclosure and detection are key steps toward ensuring informed PP. In summary, the practical application of this research underscores the importance of transitioning towards a policy mix that emphasizes economic incentives and public engagement. Future policy formulation should prioritize the activation of market forces and community involvement to drive local government and business participation in China’s carbon neutrality and peak emissions initiatives. This strategic pivot aims to optimize the efficacy of carbon reduction policies by leveraging the unique strengths of each policy tool, ensuring a comprehensive and effective approach to carbon emission reduction.
This study is subject to two main limitations that warrant consideration. First, the scope of policy text collection was limited to two databases, PKULAW and Wanfang, potentially restricting the breadth of analyzed documents. Future research could benefit from a more extensive compilation of policy texts, drawing from a wider array of databases to include documents at finer levels of granularity. This expansion would enhance the comprehensiveness of the policy analysis and provide a more detailed understanding of China’s carbon reduction policy landscape. Second, while the scoring of policies based on their strength and goals has passed the reliability test, it is important to acknowledge the inherent subjectivity in such evaluations. Future studies could develop more systematic and objective methods for policy scoring, reducing biases, and improving the accuracy of policy assessments. This would enhance the analysis of carbon emissions reduction and environmental governance. Additionally, research could explore the long-term impact of policy intensity on emissions beyond the current study’s time frame, as well as the role of technological innovation and its interaction with different policy tools.

Author Contributions

Conceptualization, K.Z., Z.Q. and J.W.; methodology, K.Z., Z.Q., J.W. and J.C.; validation, K.Z., Z.Q., J.W., J.C. and J.Z.; formal analysis, K.Z., Z.Q. and J.C.; data curation, K.Z., Z.Q., J.W. and J.C.; writing—original draft preparation, K.Z., Z.Q. and J.W.; writing—review and editing, J.C. and J.Z.; visualization, K.Z., Z.Q., J.C. and J.Z.; supervision, K.Z., J.W. and J.C. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Shandong Province Natural Science Foundation, grant number ZR2023QG168.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Detailed workflow of the research methods.
Figure 1. Detailed workflow of the research methods.
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Figure 2. Number of central and local carbon reduction policies each year.
Figure 2. Number of central and local carbon reduction policies each year.
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Figure 3. Number of newly issued provincial policies in each year (with dotted lines separating east, middle, and west regions).
Figure 3. Number of newly issued provincial policies in each year (with dotted lines separating east, middle, and west regions).
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Figure 4. Number of central policies (above) and local policies (below) for each type.
Figure 4. Number of central policies (above) and local policies (below) for each type.
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Figure 5. Cumulative policy intensity by province and type (with dotted lines separating east, middle, and west regions).
Figure 5. Cumulative policy intensity by province and type (with dotted lines separating east, middle, and west regions).
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Table 1. Quantitative metrics of top journal sources.
Table 1. Quantitative metrics of top journal sources.
Policy TypesPolicy ToolsRelevant Literature
CC
(directly imposing regulations)		Laws
Government targets
Carbon emission control
Bans
Standard settings		Bergquist et al. [47]
Zhang et al. [5]
MB
(relying on price and market incentives)		Subsidy measures
Tax/Fee measures
Trading mechanism
Price measures
Green credit
Demonstration project		Damon and Sterner [48]
Wu and Lin [46]
PP
(an information management approach)		Public participation
Guiding measures
Information disclosure
Technology transfer
Environmental hearing
Cooperation mechanism		Sun et al. [51]
Ye et al. [6]
Table 2. The scoring standards for policy strength.
Table 2. The scoring standards for policy strength.
CategoryScoreCriteriaRelevant Literature
Document type5LawPeng et al. [22]
Zhang et al. [5]
Ji et al. [52]
4Resolution
3Regulation/Instruction/Provision/Decision
2Opinion/Measure/Scheme/Planning/Guideline/Interim Provision/Rule/Standards
1Notice/Announcement/Official Apply/Letter
Leading body5National People’s Congress/Standing Committee of the National People’s Congress/State CouncilPeng et al. [22]
Mi et al. [53]
4Provincial or Municipal People’s Congress/Provincial government
3Provincial or Municipal Department/Prefecture level government
2Prefecture-level Bureau/District level or county level government
1District level or county level Bureau
Table 3. The scoring standards for policy goals.
Table 3. The scoring standards for policy goals.
ScoreCriteriaRelevant Literature
5Detailed quantitative targetsPeng et al. [22]
Lan [7]
3Some quantitative targets
1Qualitative target
Table 4. Results of the regression analysis.
Table 4. Results of the regression analysis.
VariableLagCoefficientp-Value[0.0250.975]
Intercept 6.4680.0121.45611.481
C E j − 1 k 11.0400.0001.0271.053
C C j − l C C k 50.5840.0100.1421.025
M B j − l M B k 3−0.6300.016−1.144−0.116
P P j − l P P k 5−1.5500.014−2.784−0.316
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Zhou, K.; Qu, Z.; Wang, J.; Chen, J.; Zhang, J. Policies for Achieving Carbon Reduction in China from 1995 to 2022: A Review and Content Analysis. Sustainability 2025, 17, 1326. https://doi.org/10.3390/su17031326

AMA Style

Zhou K, Qu Z, Wang J, Chen J, Zhang J. Policies for Achieving Carbon Reduction in China from 1995 to 2022: A Review and Content Analysis. Sustainability. 2025; 17(3):1326. https://doi.org/10.3390/su17031326

Chicago/Turabian Style

Zhou, Kai, Ziyi Qu, Jun Wang, Jianli Chen, and Junkai Zhang. 2025. "Policies for Achieving Carbon Reduction in China from 1995 to 2022: A Review and Content Analysis" Sustainability 17, no. 3: 1326. https://doi.org/10.3390/su17031326

APA Style

Zhou, K., Qu, Z., Wang, J., Chen, J., & Zhang, J. (2025). Policies for Achieving Carbon Reduction in China from 1995 to 2022: A Review and Content Analysis. Sustainability, 17(3), 1326. https://doi.org/10.3390/su17031326

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