Can regional joint prevention and control of atmospheric reduce border pollution? Evidence from China's 12th Five-Year Plan on air pollution

Synergies of air pollution control policies: A review

Air pollution control necessitates the implementation of multiple policy instruments in a coordinated manner. However, the enforcement of different policy combinations may generate complementary or offsetting synergistic effects, thereby influencing policy effectiveness. Nevertheless, the direction of synergy and the mechanisms of action among heterogeneous policies is undefined in existing academic research. This study systematically reviewed 773 articles from 1998 to 2023 and, for the first time, integrated four primary domains of air pollution control policies: policy synergy and integration, collaborative governance for pollution and carbon mitigation, joint control of multiple pollutants, and cross-regional cooperative governance. This study revealed the directions and mechanisms of air policy synergy and provided empirical evidence for cross-regional comparisons in global environmental governance, with the ultimate goal of enhancing the effectiveness of air pollution control policies. Specifically, the mechanisms underlying policy synergy suggest that the cumulative impact of policies leads to the synergistic effects of multiple policies being superior to the effects of implementing a single policy. Furthermore, due to market price signals or the characteristics of specific technologies, the concurrent application of multiple policies may occasionally yield negative synergistic outcomes. Despite these advancements, gaps remain particularly in broadening the scope of policy integration, refining the assessment of synergistic effects, developing control strategies, and enhancing stakeholder engagement. Further research is necessary to address these gaps and enhance air policy effectiveness.

Breathing life into equity: How air pollution influences corporate pay gap

Using a dataset encompassing 19,229 Chinese listed firm-year observations from 2014 to 2020, this study investigates the relationship between air quality and the pay gap between executives and employees. Our empirical results indicate that companies tend to reduce the pay gap in response to air pollution. These results exhibit robustness through various methodological approaches: employing thermal inversion as an instrumental variable (IV) for IV regressions, adopting quantile regressions, utilizing alternative metrics for assessing air pollution and corporate pay gap, expanding control variables, excluding firms undergoing reorganization, and applying firm-level clustering. This effect is especially strong in corporations with greater public scrutiny, strong corporate governance, and fewer financial constraints. Moreover, such strategic adjustments in compensation policies not only help firms retain valuable human resources, but also ultimately enhance their green innovation and ESG performance, as diminished pay gap contribute to fostering increased employee engagement and motivation within the work environment. Our research contributes to environmental management by demonstrating how air quality can be a pivotal factor in corporate compensation strategies. The findings provide actionable insights for executives and policymakers, advocating for the integration of environmental considerations into core business frameworks.

Strategic dynamics of local governments in regional collaborative governance: An evolutionary game theory analysis of haze pollution response in the Fen-Wei Plain, China

Regional collaborative governance has become a key strategy for environmental protection, especially in reducing transboundary pollution transfer. This study, set against the backdrop of environmental governance in China's Fen-Wei Plain, employs evolutionary game theory to deeply analyze the strategic choices of local governments in managing haze pollution. We developed a model incorporating 14 key variables to systematically explore the emission reduction strategies of local governments under various policy environments. Through numerical simulations, we not only validate the effectiveness of the model but also focuses on how incentives and punishments from the central government influence the stability of local governments adopting a "strict enforcement" strategy. We find that appropriate incentives from the central government can significantly enhance the tendency of local governments to choose a "strict enforcement" strategy for emission reduction. Under certain conditions, whether adopting "strict enforcement" or "superficial enforcement," both can lead to an Evolutionarily Stable Strategy (ESS). Moreover, the intensity of rewards and penalties from the central government and the benefits of collaborative governance by local governments are key factors determining the stability of strategies. Our findings underscore the importance of establishing performance-oriented incentive mechanisms, refining reward and punishment measures, and focusing on sustainable and adaptable governance strategies. The strategic recommendations provided by this study offer important guidance for balancing incentives and punishments, thereby stimulating local government enthusiasm for governance, which supports high-quality environmental protection and sustainable development goals.

The synergy effect of energy security and carbon-haze collaborative management: From the perspective of biased technological progress

It is important to ensure energy security and achieve carbon-haze collaborative management for sustainable development. Reducing imported energy dependence is necessary to maintain energy security, while its impact on environmental quality remains unclear. From the perspective of biased technological progress, this paper estimates the level of biased technological progress towards self-sufficient energy by a heterogeneous stochastic frontier analysis (SFA) function, and then empirically examines whether self-sufficient energy biased technological progress has a dampening effect on haze pollution and carbon emissions. It is found that: (1) Self-sufficient energy biased technological progress can effectively reduce haze pollution and carbon emissions, achieving a synergistic effect between energy security and carbon-haze collaborative management. (2) "Efficiency enhancement" and "quality improvement" are the essential mechanisms for the synergistic effect. (3) Environmental regulation, abundant resource and technology endowments can enhance the haze reduction effect. And the lower dependence on foreign trade and stable global economic policy environment are more conducive to achieving carbon-haze collaborative control. (4) In the Eastern and Western regions, self-sufficient energy biased technology can be sped up to alleviate haze pollution. The findings can enrich the research exploring pollution control from the perspective of biased technological progress, and provide policy recommendations for promoting high-quality development.

Enhancing urban ecological resilience through integrated green technology progress: evidence from Chinese cities

The effective resolution of environmental pollution caused by carbon haze through coordinated progress in green technology and urban ecological resilience is a crucial approach towards promoting sustainable development in Chinese cities. In this study, panel data from 281 cities in China from 2007 to 2019 were analyzed using the entropy method and the coupling coordination degree model to determine the coupling coordination degree between green technology progress and urban ecological resilience. The coordinated influence model and threshold model were applied to investigate coupled coordination types and influencing factors. Results indicate that green technology progress levels have shown an upward trend with increasing volatility from east to west and decreasing volatility with urban scale expansion. Ecological resilience levels have also steadily increased, albeit at a reduced rate. The coupling coordination degree of green technology progress and urban ecological resilience has evolved overall from low to high levels; however, the coupling coordination type has regressed to some extent, with most regions exhibiting lagging green technological progress. Pressure resilience has a positive impact on the coupling coordination degree, while state resilience and response resilience have a negative impact. Green technology progress has a dual threshold effect on the coupling coordination degree. By exploring the coupling and coordination mechanism between green technology progress and urban ecological resilience, this study not only facilitates collaborative management of pollutants and greenhouse gases in cities but also provides a comprehensive reference for the construction of an institutional system for collaborative carbon and haze management.

Environmental regulation, green technology progress and haze reduction and carbon reduction

Coordinated efforts to reduce haze and carbon emissions are important in promoting global climate governance and sustainable development. In this paper, based on prefecture-level data of China from 2005 to 2019, we investigate the impact of environmental regulatory intensity on the emissions of the concentration of PM2.5 and carbon dioxide (CO2). The research indicates that environmental regulation facilitates synergistic governance for PM2.5 reduction and carbon mitigation. Green technological advancement emerges as the primary mechanism through which environmental regulation achieves haze reduction and carbon mitigation. This conclusion remains robust after a series of robustness tests. Furthermore, the results from quantile regression reveal that the haze reduction and carbon mitigation effects of environmental regulation are subject to certain conditional dependencies. Environmental regulation exhibits a significant negative impact on carbon emissions across various quantile points. However, their influence on different quantile levels of PM2.5 concentration displays an asymmetric pattern. Finally, threshold regression findings suggest that there is no significant threshold effect of environmental regulation on CO2 emissions, but there are dual threshold effects on the PM2.5 concentration. Therefore, it is recommended that local governments judiciously implement environmental regulatory intensity, establish interregional policies for haze reduction and carbon mitigation, and fully harness the driving force of green technology to promote a comprehensive green transformation of economic and social development.

Other's shoes also fit well: AI technologies contribute to China's blue skies as well as carbon reduction

Artificial intelligence (AI) technology represents a disruptive innovation that has garnered significant interest among researchers for its potential applications in ecological and environmental management. While many studies have investigated the impact of AI on carbon emissions, relatively few have delved into its relationship with air pollution. This study sets out to explore the causal mechanisms and constraints linking AI technologies and air pollution, using provincial panel data collected from 2007 to 2020 in China. Furthermore, this study examines the distinct pathways through which AI technology can ameliorate air pollution and reduce carbon emissions. The findings reveal the following key insights: (1) AI technologies have the capacity to significantly reduce air pollution, particularly in terms of PM2.5 and SO2 levels. (2) AI technologies contribute to enhanced air quality by facilitating adjustments in energy structures, improving energy efficiency, and strengthening digital infrastructure. Nonetheless, it is important to note that adjusting the energy structure remains the most practical approach for reducing carbon emissions. (3) The efficacy of AI in controlling air pollution is influenced by geographical location, economic development level, level of information technology development, resource dependence, and public attention. In conclusion, this study proposes novel policy recommendations to offer fresh perspectives to countries interested in leveraging AI for the advancement of ecological and environmental governance.

Synergistic effect of combating air pollutants and carbon emissions in the Yangtze River Delta of China: spatial and temporal divergence analysis and key influencing factors

Synergizing the reduction of air pollutants and carbon emissions (APCE) has become a critical tactic alternative to address the issue of climate change. Taking the Yangtze River Delta (YRD) region of China as a case study, this paper explores the spatial and temporal distribution pattern of the coupling coordination degree (CCD) of combating APCE from 2011 to 2022, analyzes the dynamic change in CCD using the convergence test, and investigates the key factors affecting CCD via the Tobit regression model. The results show that (1) from 2011 to 2022, the air pollutants (AP) and CO2 emission (CE) in the YRD region decrease at the annual rate of 10.32% and 0.85%, respectively; (2) the CCD of reducing APCE in the YRD presents a W-shaped fluctuation before 2016 and then steps into a steady increase status after 2016; (3) the order of CCD in four provincial-level units by 2022 is Shanghai > Zhejiang > Jiangsu > Anhui. The proportion of cities where the CCD of reducing APCE enters the high-coordination period has reached 87.8%; and (4) the Tobit regression results affirm that economic growth, industrial structure, and green technological innovation exacerbate the CCD of combating APCE, while opening-up level mitigates it. The findings offer policymakers valuable insights into the importance of pursuing collaborative governance over APCE and ensuring sustainable development.

Does Market-Based Environmental Regulation Improve the Residents' Health: Quasi-Natural Experiment Based on DID

Improving the residents' health is an important strategy for addressing the declining population dividend in China under the new development paradigm. Based on the panel data of 290 prefecture-level cities in China from 2010 to 2021, this paper uses environmental tax as a quasi-natural experiment, and adopts a DID model to explore the impact of market-based environmental regulation on the residents' health. The results show that the implementation of environmental tax can significantly reduce the population mortality rate, indicating an enhancement in residents' health outcomes. Mechanism analysis shows that environmental tax mainly relies on air quality to improve the residents' health. Also, the heath effect of environmental tax will be effective with the increase of income, and it's stronger in administrative border areas. Heterogeneity analysis shows that the effect of environmental tax on residents' health in western regions and resource-based cities is significantly stronger than those in central and eastern regions and non-resource-based cities. This paper provides new evidence for a comprehensive understanding of the impact of market-based environmental regulations on residents' well-being, offering insights for the implementation of green development strategies.

Is air pollution joint prevention and control effective in China-evidence from "Air Pollution Prevention and Control Action Plan"

This paper examined the effect of air pollution joint prevention and control on pollution emissions in China. Specifically, based on the panel data of 290 cities from 2007 to 2021, taking the implementation of the "Air Pollution Prevention and Control Action Plan" as a natural experiment, the difference-in-difference-in-difference (DDD) model was used to explore the effect of air pollution joint prevention and control on haze pollution. Results show that air pollution joint prevention has a significant impact on pollutant emissions either as a whole or as a single pollutant. In terms of individual urban agglomeration, whether the Yangtze River Delta or the Pearl River Delta urban agglomerations, the air pollution joint prevention and control policy has a significant impact not only on the overall reduction of pollutant emissions but also on the reduction of single PM2.5 or industrial sulfur dioxide emissions alone. Environmental regulations have also achieved the effect of haze control in general and have a significant impact on the reduction of PM2.5 or industrial sulfur dioxide emissions. Environmental regulations also significantly reduced PM2.5 emissions in these three urban agglomerations. These findings provide a scientific basis and essential reference for understanding the implementation effect of regional joint prevention and control policies comprehensively and objectively.

A regional cooperative reduction game model for air pollution control in North China

Due to variations in economic scale, economic structure, and technological advancement across different Chinese provinces and cities, the cost of air pollution reduction differs significantly. Therefore, the total reduction cost can be decreased by capitalizing on these regional discrepancies in reduction cost to carry out cooperative emission reduction. In this paper, taking NOx reduction in North China as an example, a regional cooperative reduction game (CRG) model was constructed to minimize the total cost of emission reduction while achieving future emission reduction targets. The fair allocation of benefits from cooperation plays a crucial role in motivating regions to participate into the cooperation. A comprehensive mechanism of benefits allocation was proposed to achieve fair transferred compensation. The mechanism combines the consumption responsibility principle based on input-output theory and the Shapley value method based on game theory. Compared to the cost before the optimized collaboration, the CRG model will save 20.36% and 13.71% of the total reduction cost in North China, respectively, under the target of 17.68% NOx reduction by 2025 and 66.44% NOx reduction by 2035 relative to 2020. This method can be employed in other regions to achieve targets for air pollution reduction at minimum cost, and to motivate inter-regional cooperation with this practical and fair way of transferred compensation.