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Spatial misallocation of resource elements impedes the coordination in regional co-benefit in carbon emission and pollution reduction. Guided by scope economy principles, this study aims to quantifies co-benefits and explores spatial variation patterns to facilitate mutual synergy. The findings offer valuable insights for identifying optimal focus points and shaping targeted collaborative policies. Based on the multi-source provincial panel data spanning 2000 to 2021, this paper quantitatively assesses the co-benefit through the lens of marginal abatement cost. Then, the Dagum Gini coefficient was employed to investigate the disparities at the spatial level. Additionally, geographical detector is introduced to analyze the source of disparities at the factor level. Results indicate: (1) Under joint reduction, the marginal abatement cost reduces by 57.86% and 79.97% respectively, with an overall 68.77% increase in co-benefit fluctuation. (2) Provinces with low co-benefit significantly decreased after 2007, while provinces with high co-benefit concentrated in the northwest, southwest, and east. (3) Overall disparities decreased, east-central regions hold the lowest spatial disparities in co-benefit and east-west hold the most; intragroup differences and supervariable density primarily contributes to the disparity. (4) FDI significantly influence the co-benefit over the past two decades, with spatial disparities influenced by both endogenous and exogenous factors across development stages., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

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 PM 2.5 and SO 2 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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The relationship between fiscal regimes and urban industrial pollution emissions is unclear. This paper aims to explore the effects and mechanisms of fiscal centralization on urban industrial pollution emissions and environmental quality. Using the vertical reform of environmental administrations (VREA) in China as a quasi-natural experiment of fiscal centralization, this study applies a staggered difference-in-differences (DID) model to explore the differences in industrial pollution emissions between centralization cities and decentralization cities. The main findings are: (1) VREA significantly inhibits regional industrial pollution emissions, and the reform effect increases over time. This conclusion still holds after considering a series of robustness issues. (2) Industrial sulfur dioxide (SO 2 ) and solid particulate emissions in the fiscal centralization cities have decreased significantly by 0.3281% and 0.2240%, respectively. However, there is no significant change in industrial wastewater discharges. (3) Environmental regulations, environmental expenditures, and pollution control investments of local governments are the main channels through which VREA reduces industrial pollution emissions. (4) The effects of VREA are more significant in central and western cities and small cities. (5) Relative to decentralization cities, centralization cities have improved air and water quality by 0.0825% and 0.1628%, respectively. These findings help to accurately assess the effects of fiscal centralization on regional environmental governance and provide a decision-making reference for further deepening environmental centralization reform in China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The pollution control effect of seasonal environmental regulation policies in developing countries still lacks empirical evidence. In 2017, China implemented its first Atmospheric Environmental Policy in Autumn and Winter (AEPAW) to coordinate efforts among cities in reducing air pollutant emissions. Taking the daily panel data of 174 cities in northern China from July 2017 to July 2020 as samples, this paper empirically examines the pollution control effect of the AEPAW using a difference-in-differences model, a difference-in-difference-in-differences model, and a regression discontinuity design. The results show that the AEPAW significantly improves air quality in autumn and winter, with the air quality index decreasing by 5.6% on average by reducing PM 2.5 , PM 10 , SO 2 , and O 3 emissions. However, the AEPAW only creates a short-term "policy-induced blue sky", and there exists a phenomenon of "retaliatory pollution" after the AEPAW ends. Besides, the pollution control effect of the AEPAW is moderated by the heterogeneity of the national "Two Sessions" and the Central Environmental Protection Inspection. The implementation of the AEPAW also has a significant spillover effect on air pollution control in surrounding areas. The net benefit from the AEPAW is estimated to be approximately US$ 670 million per year. These findings not only have practical significance for strengthening the comprehensive control of air pollution in China, but also give some important references for other developing countries., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Border pollution is usually a difficult problem in environmental governance. Based on the data at the county level in China from 2005 to 2019, this study takes the 12th Five-Year Plan (FYP) for atmospheric pollution as a policy shock, and uses the difference-in-differences (DID) method to explore the impact of regional joint prevention and control (JPC) of atmospheric pollution policy on air pollution of the border regions. Empirical results show that: (1) After implementing the JPC of atmospheric pollution policy, the PM 2.5 concentration in the border regions is reduced by 3.5%. (2) The mechanism analysis shows that there is a spillover effect in the governing behaviors of local governments. In the border areas under low economic growth pressure and high environmental protection pressure, the reduction effect of the JPC of atmospheric pollution policy is more significant on the PM 2.5 concentration of the border regions. The research conclusions have new insights into the role and effect of macro-regional environmental JPC policy and border pollution control, and provide practical guidance for social green governance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

In recent years, China has focused its development on technological innovation, trying to achieve a win-win situation between environmental protection and economic growth, and it has formulated a series of policies to promote technological innovation. Taking China's national independent innovation demonstration zone (NIIDZ) policy as an example, this paper empirically investigates the impact of China's innovation policy on haze pollution by using a difference-in-differences (DID) model. The results show that the NIIDZ policy promotes the governance of urban haze pollution and confirms the applicability of the experimentalist governance model in the practice of innovation policy in developing countries. Dynamic analysis shows that the NIIDZ policy has an experience accumulation effect. This policy can continue to promote haze control for at least 6 years, and the policy effect increases year by year. Action mechanism analysis shows that the NIIDZ policy can inhibit urban haze pollution by promoting urban technological innovation and high-tech industrial agglomeration. The estimation results of the spatial DID model show that the NIIDZ policy not only inhibits haze pollution in NIIDZ cities but also has an inhibitory effect on haze pollution in the surrounding non-NIIDZ cities and the NIIDZ cities, which confirms the positive externality characteristics of policy diffusion theory and environmental governance. The conclusions of this paper have important theoretical value for understanding the ecological effect of innovation policy and provide experience for developing countries to implement an experimentalist governance model., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

To solve the increasingly serious air pollution problem, regional air pollution collaborative governance as an effective way is introduced in this paper. Firstly, this study constructs a game model of regional air pollution collaborative governance, and three classic cost sharing methods are used to allocate the cost of air pollution governance; Then the emission reduction cost of regional cooperative governance is obtained; Finally, the study makes an empirical analysis on the cost sharing of SO 2 emission reduction by four local governments of the Yangtze River Delta region in 2017. The results show that: (i) The emission reduction cost of regional cooperative governance is better than that of individual governance, and in 2017 the cost of SO 2 cooperative governance in Yangtze River Delta region is reduced by about 1.8% compared with the individual governance; (ii) The Shapley value method is utilized to allocate the benefits of the cooperative SO 2 governance of four provinces in the Yangtze River Delta region, which indicates that all local governments can obtain certain profits from this cooperation and the cooperative alliance is stable; (iii) Collaborative governance of regional air pollution can meet the requirements of both collective rationality and individual rationality at the same time., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

In the reforms pertaining to the energy structure in the automotive industry, new energy vehicles (NEVs) have long been the focus of government attention, as an effective means to reduce air pollution. Therefore, this paper employs the rolling-window Granger causality test, in order to discuss the environmental benefits of new energy vehicles, so as to explore the active role of the transportation sector in reducing air pollution. By studying the interactions between NEVs and particulate matter (PM 2.5 ) from the time period spanning from 2013:M1 to 2020:M9, we have found that the positive influences from NEVs to PM 2.5 ascertain that NEVs cannot be considered as an efficient measure to mitigate air pollution. Moreover, these results are not supported by the energy and environment interaction model, which essentially indicates that replacing traditional energy with renewable energy is an effective measure for controlling environmental pollution. In fact, PM 2.5 tends to have a negative impact on NEVs, which underlines that the air quality index is a leading indicator, particularly when it comes to analyzing the development of the NEVs market. This essentially highlights that in China, NEVs still do not account for a high proportion of car sales, and therefore, its environmental protection effect is not obvious. At the same time, the factor of public awareness regarding environmental protection will thus occupy a considerable proportion in the transmission of NEVs sales. These revelations will help the government to formulate environmental governance policies, and expand the new energy vehicle market to achieve carbon neutrality targets in China., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Fine particulate matter (PM 2.5 ) has become a major pressing challenge for China and remains a concern of its central government. This paper draws on a natural experiment generated by the National Ambient Air Quality Monitoring Network (NAAQMN) program in China to explore whether national air quality monitoring reduces local air pollution. In this study, we use a city-level dataset for 4200 Chinese cities covering 2001-2015 and a difference-in-differences (DID) assessment design to assess the impact of the NAAQMN program on local PM 2.5 emissions in China. The results suggest that the NAAQMN program significantly reduces the local PM 2.5 concentrations by 1.325 mg/m 3 , and each additional NAAQMN program will cause a decrease of 0.154 mg/m 3 in the local PM 2.5 concentrations. Furthermore, we determine the heterogeneous impacts of the NAAQMN program on local PM 2.5 emission levels through the local government leaders' characteristics, PM 2.5 emission levels, and economic development levels. In addition, a mediation effect is found between the NAAQMN program and local PM 2.5 emissions through the efficiency of environmental governance. The Chinese government should continue to promote the implementation of the NAAQMN program by promoting the NAAQMN program to the county and rural areas as well as adding the sites of the NAAQMN program in the existing cities. Also, during the process of promoting the NAAQMN program, sufficient differentiation in policies should be developed for different cities., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Collaborative governance plays an important role in air pollution prevention (APP). This paper aims to evaluate the policy effects of collaborative governance for APP in the Yangtze River Delta (YRD) region, analyze the collaborative mechanism from the perspective of institutional collective action (ICA) theory, and discuss its implications for improving the policy effects and regional collaboration. First, the causal relationship between collaborative environmental governance and air pollutant reduction is confirmed using the regression discontinuity design (RDD). However, it is also established that regional APP policies initiated by the Regional Cooperation Office of Yangtze River Delta (RCOYRD) did not have a long-term effect on reducing air pollutants. Second, initiative heterogeneity and administrative hierarchy heterogeneity of policy effects between cities are analyzed. It demonstrates that the mechanism formulated by RCOYRD has very limited impact on the reduction of transaction costs and collaborative risks of collaborative environmental governance. Third, clear division of responsibilities, balanced cost-benefit sharing, and coordinated enforcement between local governments are needed to improve the policy effects of collaborative governance for APP., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Improving air quality is an era task for China to transform its economic development model and enhance its environmental governance capabilities. This article take the Chinese government's Three-year Action Plan to Win the Blue Sky Defense War (abbreviated as the Blue Sky Defense War) as a quasi-natural experiment and use regression discontinuity design (RDD) to evaluate the governance effect of this policy. The study found that the Blue Sky Defense War reduced the monthly average concentration of PM2.5 and PM10 in cities by 14.49 and 23.43, respectively. Heterogeneity analysis shows that the Blue Sky Defence War has a more prominent effect on urban air quality management based on PM10 assessment; Jing-Jin-Ji region and surrounding areas are the key points to ensure the achievement of air management. Consistent and effective environmental governance policies, transparent and timely information disclosure and structural adjustment are all powerful guarantees for the effectiveness of the Blue Sky Defense War. These research conclusions provide new ideas for developing countries to formulate practical environmental pollution control policies., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

The significant role of high-quality data in environmental policymaking has led to the Chinese central government's concrete efforts to improve its monitoring system, which had long been plagued with data manipulation by local governments. The most remarkable policy innovation of the last decade in this area has been the introduction of a critical external oversight-profit-making third-party organizations-by the central government to monitor local governments' environmental performance. Despite the significance of third-party environmental monitoring, little is known about its effectiveness in improving data accuracy and whether and how it brings about changes to China's environmental governance. Framed within the literature on China's intergovernmental relationship and adopting a regression discontinuity model with a national database of air quality, this study examines whether third-party monitoring improves the accuracy of environmental data in China, and if so, how this approach can remedy the problem of data manipulation. Results show that data accuracy has been improved after the involvement of third-party organizations, providing evidence that supports China's efforts to advance its environmental governance from a mono-centric and non-participatory policy process to one that integrates both authoritarian control and market-based mechanisms. We discuss policy implications of this finding for environmental governance in China., (Copyright © 2019. Published by Elsevier Ltd.)

Information disclosure in environmental governance, or informational governance conceptualized by Arthur Mol, has been increasingly utilized as a policy instrument to incentivize environmental policy enforcement in not only democratic societies but also authoritarian regimes like China. This study uses an explicit regulation, the air pollution ranking in Chinese cities as an example to illustrate how such informational governance policy instrument has an impact on local air pollution governance. Empirical evidence is based on monthly comprehensive air quality index ranking data of 74 key monitoring cities in China from 2013 to 2018. And a regression discontinuity design is applied to explore the relationship between air pollution ranking and air quality improvement in localities. The results show that (1) air quality of the bottom ten cities in the ranking will improve in the coming month compared with their counterparts; (2) such improvement happens upon the releasing of the ranking, but would not last for more than a month; (3) while top ten cities in the ranking do not experience such change in air quality. Therefore, we argue that the air pollution ranking system in China can be a useful informational governance instrument in providing negative incentives for environmental administrations in bottom cities to strengthen air pollution control. However, as a top-down environmental information disclosure program, such ranking institution could only mobilize local air quality governance temporarily. And new institutions ought to be established to further internalized local governments' environmental externalities., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Using firm establishment-level data combined with provincial socio-economic characteristic panel data in China for the period of 2011-2015, this study seeks to empirically examine the impact of environmental regulation on location choices of polluting firms. The results of the conditional logit model provide compelling evidence that environmental regulations do affect the location choice of firms in polluting industries. Instead of supporting the pollution haven effect, our results consistently confirm the Porter effect at the country level. This result is robust when taking endogeneity problem into account, adopting various model specifications and estimation strategies, using alternative measurements of environmental regulation and location choices, and subsampling excluding international political events. However, the results also show divergent effect of environmental regulation on location choices for heterogeneous firms. Specifically, polluting firms in eastern region prefer to invest in provinces with stringent environmental policies but those in other regions, especially in northeastern region, choose to locate in provinces with lax environmental regulation. While water-dependent polluting firms with a low level of footlooseness are more likely to enter locations with loose environmental regulation, air pollution-intensive firms tend to locate in provinces with tight environmental legislation. These results have policy implications for transitional China as well as other developing countries with similar experience., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Transboundary air pollution is a global environmental and public health problem including in the U.S., where pollution emissions from China, the largest emitter of anthropogenic air pollution in the world, can travel across the Pacific Ocean and reach places like California and Oregon. We examine the effects of transboundary air pollution following major events in China, specifically sandstorms, a natural-occurring source of air pollution, and Chinese New Year, a major 7-day holiday, on background air quality in the U.S. We focus on high elevation sites on the west coast between 2000 and 2013. We use regression analysis and a natural experiment to exploit the variation in the timing of these events in China, which are plausibly uncorrelated to other factors that affect air quality in China and the U.S. We find that sandstorms are associated with statistically significant increases in background coarse and fine particulate matter (PM) in the U.S., representing between 16 and 39% of average weekly PM levels. We also find Chinese New Year is associated with modest reductions in background air quality in the U.S., representing between 0.4 and 2.5% of PM levels. Findings are robust to different models and falsification tests. These results suggest that regression analysis could be a powerful tool to complement other, more widely used techniques in the environmental sciences that study this problem. This also has important implications for policymakers, who could track major sandstorms in China and prepare for possible increased foreign pollution emissions in the U.S. [ABSTRACT FROM AUTHOR]