Spatial spillover effects of environmental regulations on air pollution: Evidence from urban agglomerations in China

Exploring the correlation between rising temperature and household electricity consumption: An empirical analysis in China

This study investigates the nexus between rising temperatures and household energy consumption using data from respondents' electricity bills in the "China Residential Energy Consumption Survey." Our analysis reveals a significant correlation, with an 8.9 % increase in yearly energy consumption observed when the average temperature exceeds 32 °C. Additionally, we explore potential shifts in power usage due to global warming by integrating baseline estimates with daily temperature forecasts from eight contemporary climate models. Our findings project alarming trends: without interventions to curb greenhouse gas emissions, home electricity consumption could surge by 9.59-30.09 % in the medium term and by 9.77-47.70 % in the long run. By shedding light on these critical connections, our research underscores the urgent need for policy actions to mitigate the adverse impacts of climate change on energy consumption patterns.

Can PM2.5 concentration reduced by China's environmental protection tax?

The responsibility of enhancing environmental quality is shouldered by China's Environmental Protection Tax (EPT), which constitutes a vital element of China's tax system greening initiative. Using the difference-in-differences (DID) method, the effects of the EPT on PM2.5 concentration were empirically examined in this study, through panel data of 218 cities in China from 2015 to 2021. The results indicate that the EPT can effectively reduce PM2.5 concentration by approximately 2.4 %, and this conclusion remained unchanged after a series of robustness tests. In the channel analysis, it can be found that the reduction of PM2.5 concentration by the EPT was achieved through the alleviation of financing constraints, technological advancements, and optimization of industrial structure. Heterogeneity analysis indicates that the negative impact of the EPT on PM2.5 concentration was more significant in northern cities, inland cities and non-national environmental protection model cities. Further analysis found that EPT has a stronger inhibitory effect on PM2.5 concentration within 100 % of tax increase. The conclusions remain consistent when spatial spillover effects of PM2.5 are taken into account. This paper provides important empirical evidence to support the effectiveness of emission reductions of EPT and provides valuable insights for the future improvement of EPT.

Spatial difference-in-differences analysis of smart city pilot policy and industrial pollution reduction: the mediating role of S&T fiscal expenditure

Smart city has become one of the most important tool to achieve digital transformation and intelligent development. However, the impacts of smart city pilots (SCP) on different industrial pollution have yet to be tested, and the mechanisms of SCP affect industrial pollution could be richer. In this paper, we construct a spatial difference-in-difference model for 2004-2019 by mapping SCP policy to Chinese city data to systematically quantify the impact and its potential mechanisms of digital transformation on industrial pollution. Our results show that the SCP policy achieves industrial pollution reduction targets, on average, wastewater and SO2 emissions decreased by 6.4% and 6.5%, respectively. Cities with SCP policy have more industrial pollution compared to cities without SCP policy, implying a beggar-thy-neighbor effect of SCP policy. Furthermore, significant regional disparities come to light; SCP policy in the Pearl River Delta exceeds other regions such as the Yangtze River Delta and Jing-Jin-Ji city cluster in terms of realizing the impact of industrial pollution reduction. Importantly, mechanism analysis indicated that the SCP reduced industrial pollution was partially mediated by government S&T fiscal expenditure.

Advancing nuanced pollution control: Local improvements and spatial spillovers of policies on key enterprises

This paper examines the impact of air pollution control policies targeting key polluting enterprises, highlighting a strategic shift towards precision pollution control that concentrates on high-emission, high-risk businesses. The paper explores the efficacy of these policies and their potential spatial spillover effects, utilizing panel data from 259 Chinese cities from 2013 to 2021. Employing the difference-in-differences (DID) model and spatial Durbin model, the study analyzes both the direct local effects and the broader spatial consequences of these regulatory measures on air quality. The findings indicate a significant reduction in air pollutant concentrations in urban areas, attributing this improvement to factors such as industrial restructuring, increased investment in science and technology, and economic growth. Spatial econometric analysis further reveals a substantial positive correlation in air quality among Chinese cities. However, estimates of the spillover effect indicate that while such policies successfully reduce pollution locally, they could unintentionally degrade air quality in adjacent areas. The study highlights the need for nuanced policy strategies to mitigate unintended spatial spillovers and enhance overall effectiveness. It recommends tailored policies that integrate environmental and socioeconomic objectives, national and regional coordination for consistent enforcement, technology-driven compliance strategies, and incentives for sustainable enterprise practices.

The allocation of carbon resources in marine capture fisheries

Marine fishery carbon emissions play a significant role in agricultural carbon emissions, making resource allocation a crucial topic for the overall marine ecological protection. This paper evaluates the dynamic iteration method as a research approach with the factors of resource allocation consisting of value assessment, optimization objective, difference between value assessment and objective, and optimization calculation. The paper selects the shadow price from the Super-SBM model as the judgment function for the goal value, aiming for the fairness criterion. From an equity standpoint, the allocation of carbon resources in marine capture fisheries proves to be unreasonable. The fishery model exhibits an excessive supply of carbon resources, resulting in wastage, while the green fishery model faces a relatively limited supply, with a focus on energy conservation and environmental protection. To address this issue, this paper proposes a new method and discusses the corrective results. This result shows that the stabilization point achieved is a short-term equilibrium rather than a long-term one. By rectifying the social contradiction of profit-oriented approaches, this research provides a fresh perspective for economic studies and applications, particularly in industrial layout and resource utilization optimization.

Investigation of the spatial effects on PM2.5 in relation to land use and ecological restoration in urban agglomerations

Heavy pollution of particulate matter with an aerodynamic diameter of <2.5 μm (PM2.5) poses increasing threats to the living environment worldwide. Urban agglomerations often lead to regional rather than local air pollution problems. This study explored the underlying global and local spatial driving mechanisms of PM2.5 variations of the 195 county-level administrative units in the urban agglomeration in the middle reaches of the Yangtze River, China, in 2020, using the global spatial regression and geographically weighted regression methods. Results showed that (1) at the county level, there were spatial variations of PM2.5, fluctuating from 20.1263 μg/m3 to 44.8416 μg/m3. (2) The concentrations of PM2.5 presented a positive spatial autocorrelation with a remarkable direct spatial spillover effect. (3) Forestland, grassland, elevation and ecological restoration were negatively correlated with PM2.5 concentrations, the indirect spatial spillover effect of elevation was noticeable. (4) The indirect reduction effects of ecological restoration on PM2.5 concentrations were substantial in the Wuhan urban agglomeration. (5) The reduction effect of forestland, grassland, ecological restoration and elevation on PM2.5 showed a noticeable spatial heterogeneity. In the future, it is suggested regional variability and the spatial spillover effect of air pollution be taken into account in environmental governance. Simultaneously, utilization of the mitigation effect of ecological restoration on PM2.5 is anticipated for the concerted effort in air pollution governance.

Spatiotemporal patterns and drivers of the urban air pollution island effect for 2273 cities in China

Air pollution levels tend to be higher in urban areas than in surrounding rural areas, and this air pollution has a negative effect on human health. However, the spatiotemporal patterns of urban-rural air pollution differences and the determinants of these differences remain unclear. Here, we calculate the Urban Air Pollution Island (UAPI) intensity for PM2.5 and PM10 on a monthly, seasonal, and annual scale for 2273 cities in China from 2000 to 2020. Subsequently, we analyze the influence of urban characteristics using a combined approach of a two-way fixed effects model and a spatial Durbin model. Results show a strong downward trend in the UAPI intensity since 2013, with reductions ranging from 42 % to 61 % until 2020, for both pollutants and in summer as well as winter. Consistently, the proportion of the cities experiencing the UAPI phenomenon decreased from 94.5 % to 77.3 % for both PM2.5 and PM10. We find a significant influence of urban morphology on UAPI. Specifically, urban sprawl, polycentric development, and an increase in urban green spaces are associated with a reduction in UAPI, while dense urban areas intensify it. Our study also reveals a robust inverted U-shaped relationship between stages of economic development and UAPI. Moreover, economic development and air pollution itself show spillover effects that oppose their direct impacts. These results suggest that urban and regional planning and more ambitious climate change mitigation policies could be more effective strategies for mitigating air pollution in cities than end-of-pipe control.

Does environmental regulation lessen health risks? Evidence from Chinese cities

Introduction

Atmospheric pollution is a severe problem confronting the world today, endangering not only natural ecosystem equilibrium but also human life and health. As a result, governments have enacted environmental regulations to minimize pollutant emissions, enhance air quality and protect public health. In this setting, it is critical to explore the health implications of environmental regulation.

Methods

Based on city panel data from 2009 to 2020, the influence of environmental regulatory intensity on health risks in China is examined in this study.

Results

It is discovered that enhanced environmental regulation significantly reduces health risks in cities, with each 1-unit increase in the degree of environmental regulation lowering the total number of local premature deaths from stroke, ischemic heart disease, and lung cancer by approximately 15.4%, a finding that remains true after multiple robustness tests. Furthermore, advances in science and technology are shown to boost the health benefits from environmental regulation. We also discover that inland cities, southern cities, and non-low-carbon pilot cities benefit more from environmental regulation.

Discussion

The results of this research can serve as a theoretical and empirical foundation for comprehending the social welfare consequences of environmental regulation and for guiding environmental regulation decision-making.

The impact of informality and institutional quality on environmental footprint: The case of emerging economies in a comparative approach

The endeavor to implement the 2030 Agenda of national and international stakeholders became increasingly impetuous, considering the wide range of uncertainties and risks. The new humans-centered development model built on the prominence of environmental and social values seeks to reinforce communities' resilience and mitigate environmental risks, leaving no one behind. For this to happen, solid and effective institutions, the right environmental policies, and a safe statutory labor framework are the sine qua non. In this study, we evaluated the effects of informality, institutional quality, and renewable energy consumption on ecological footprint of two groups of emerging countries from Europe and Asia from 2002 to 2018. Our results by PMG-ARDL approach highlight dissimilarities between the two groups, showing greater heterogeneity. In this sense, informality is found to have positive and significant effects on ecological footprint in the long run in emerging European countries. In contrast, the effect is negative for emerging Asian countries. In the short run, the effects are less critical in the studied countries between the two groups. Institutional quality variables impacted environmental quality differently. In this sense, it is detrimental for policymakers to consider concerted measures to decrease institutional vulnerabilities and reduce the level of the informal economy. The outcome of this study concurs with a complete awareness of the importance of informality and institutional quality to mitigate social and environmental risks conjunctively.

Spatial correlation and coupling between industrial enterprise agglomeration and water pollutant discharge

Industrial wastewater discharge has become the main cause of water pollution in China. However, the spatial interaction mechanism between industrial structure and water pollution is still unclear. Accordingly, we evaluated and analyzed spatiotemporal changes of the agglomeration pattern of pollution-intensive industrial enterprises and the evolution of the water environmental pollution pattern, as well as the correlation between them. The study results show that the polluting industrial enterprises were located mainly along the Yangtze River and Taihu Lake Basin in southern Jiangsu in 2013 and 2018. However, we observed a spatial trend of pollution transfer to northern Jiangsu. The industrial water pollution discharge presents the distribution pattern of facing rivers, seas, lakes and cities. Papermaking and paper products industry are the leading factors of COD and NH3-N pollution, with explanatory power of 0.3666 and 0.6201 respectively. The spatial positive coupling effect between the concentration degree of polluting enterprises and the intensity of water environment pollution discharge is 94.95% of the region. The spatial agglomeration of polluting industrial enterprises is an important cause of water environment pollution. They promote and couple each other, proving the existence of "Pollution haven" and "Porter hypothesis".

How digital finance affects environmental pollution management: evidence from China

Due to people's insufficient anticipation of the negative impact of highly developed industries and the lack of prevention, global environmental pollution has occurred. These pollutants include air pollution, water pollutants, and land pollution, which not only cause direct damage and impact the ecosystem but also endanger the health of urban residents and economic development. Therefore, researching environmental pollution management is necessary to help solve these imminent environmental problems. In addition, digital finance, based on digital technology, can identify bottlenecks in environmental pollution management, formulate more effective governance strategies, and reduce environmental pollution at the source. In this context, this study uses the environmental pollution data of 287 cities in China from 2011 to 2021. It uses the fixed-effects and mediation effect models to analyze digital finance's role in environmental pollution management. The research shows that digital finance can promote environmental pollution management and play a promoting role through two channels of influence: green technology innovation and government green subsidies. At the same time, the effect of this promotion is more significant in cities in the Midwest and in resource-based cities. The research results propose strategies for government organizations in environmental pollution management, and alleviate current resource and environmental problems, in addition to realizing sustainable urban development.

Empirical linkages of the construction sector, intensive energy consumption, and economic openness with chemical oxygen demand pollution

Though construction sector development and economic openness contribute to regional economic development, they have also been debated to pose some environmental challenges. Along these lines, we explored the long- and short-term connections of intensive energy consumption, economic openness, and construction sector development with the chemical oxygen demand throughout the scales of regional development of China's 30 provincial units over the 2004-2021 period. Theoretically, we contribute to the existing knowledge by incorporating chemical oxygen demand pollution, construction sector development, and economic openness to the Kaya identity's baseline framework. Empirically, we apply a series of advanced methods of panel data econometrics for robust results. Our key findings are as follows: First, we revealed a long-term stable cointegrating association among our variables of interest. Second, using the common correlated effect mean group estimator, we unfolded that the intensive energy consumption showed a chemical oxygen demand pollution reduction influence in both the long and short term, demonstrating the most substantial influence in the high regional development panel while expressing the least powerful influence the least regional development setting. Third, we unveiled that economic openness and construction sector development showed a linear chemical oxygen demand pollution enhancement influence in moderately and least developed regions. Nevertheless, both established an inverted U-shaped linkage with chemical oxygen demand pollution for the whole country as well as for high regional development data samples. Eventually, we found consistent estimates across long- and short-term investigations regarding signs of relationships; however, long-term effects remained more powerful than short-term ones. These findings would serve as factual scientific knowledge to help local as well as national governments create the optimal environmental regulations for the construction sector to achieve the sustainable development goals (SDGs), especially the Climate Action Plan (i.e., SDG-13).

Environmental quality assessment and spatial spillover effects of three urban agglomerations in China: A Meta-EBM approach

The new development form of urban agglomeration has greatly promoted economic and social progress in recent years, but it is also facing severe environmental pollution problems. Understanding the status quo of environmental efficiency in urban agglomerations and its leading driving forces is an important prerequisite for formulating energy conservation and emission reduction policies. This research uses the Meta Epsilon Based Measure (Meta-EBM) model to measure the environmental emission efficiency of the Beijing-Tianjin-Hebei（BTH）, Yangtze River Delta (YRD) and Pearl River Delta (PRD) urban agglomerations in China from 2014 to 2018 so as to improve on the inability of traditional Data Envelopment Analysis (DEA) to combine linear and non-linear characteristics, and employs Moran's I index and spatial econometric methods to analyze their spatial dependence and main driving factors. The results demonstrate that the overall environmental efficiency of the three major urban agglomerations in the five years from 2014 to 2018 presents a wave-like development and then tends to be flat. The itemized efficiency of economic outputs has maintained a relatively high level with the environmental output index exhibiting the best efficiency for industrial wastewater, followed by industrial sulfur dioxide (SO2). The scores of the two indicators for inhalable fine particle emissions (PM2.5) and industrial smoke and dust in each urban agglomeration are not ideal, and there are obvious differences between regions. Among them, YRD and PRD are relatively inferior. From the perspective of spatial spillover effects, various indicators show diverse characteristics at different development stages of the regions. Population and Normalized Difference Vegetation Index (NDVI) have a positive effect on environmental efficiency, while both Gross Domestic Product (GDP) per capita and transportation tend to show greater negative effects on regional environmental optimization. This study proposes countermeasures as follows. Each urban agglomeration should set up measures suitable to local conditions and give full play to their location advantages. They can also use space radiation to promote sector economic development and optimize urban environmental benefits.

Environmental regulations, green development of agriculture, and residents' health-empirical analysis of Yangtze River Economic Belt in China

Environmental pollution and food safety have become key public health issues to be addressed in China. Since they are closely related to the green development of agriculture, it is of great practical significance to elucidate the intrinsic relationships between green development of agriculture, environmental regulation and residents' health. Based on the panel data of the Yangtze River Economic Belt from 2011 to 2020, this study investigates the impacts of environmental regulation and green development of agriculture on residents' health and the influencing mechanism by applying fixed effects method, mediating effectsmethod and the spatial Dubin method. Results show that the use of chemical fertilizers, pesticides and agricultural films is harmful to residents' health; environmental regulation has a negative correlation with the green development of agriculture and affect residents' health through mediating effects; the green development of agriculture has negative spillover effects on residents' health, indicating that purchasing finished products instead of producing locally reduces the input of production factors such as chemical fertilizers and pesticides and transfers health risks associated with agricultural production activities to neighboring areas. Intensifying command-and-control environmental regulation will induce the expansion of hidden economic activities and harm local residents' health, while intensifying market-incentive environmental regulation will lead to the 'Pollution Haven' phenomenon because of the 'race to the bottom', in government and is harmful to the health of residents in neighboring areas. Therefore, it is necessary to formulate reasonable and feasible policies and strengthen the control and prevention of agricultural pollution to enhance green development of agriculture and improve residents' health.

Does the low-carbon city pilot contribute to the blue sky defense? Evidence from China

China's goal of ecological civilization construction simultaneously faces the dual strategic tasks of pollution control and carbon reduction (PCCR). In addition to carbon reduction, does the low-carbon city pilot (LCCP) further contribute to the blue sky defense? This study investigates the impact of the LCCP on air pollution by employing a multiperiod difference-in-differences (DID) model based on data from 276 Chinese cities. The results show the following: (1) Compared with nonpilot areas, the LCCP reduces PM_2.5 levels in pilot areas by approximately 1.50% on average, which is achieved by "industrial restructuring", "government investment in science and technology (S&T)", and "green lifestyle". (2) The LCCP has heterogeneous effects on air quality across cities with different resource endowments and industrial attributes, showing a greater air quality improvement in nonresource-based cities (NREB cities) and old industrial base cities (OIB cities) than in other city types. (3) The positive impact of the LCCP on air improvement in the pilot areas is derived from "pollution control effects" rather than "pollution transfer effects". This study provides useful policy implications for the comprehensive green transition and exploration of synergistic governance for PCCR in China.

Can heterogeneous environmental regulations improve industrial green total factor energy efficiency?

Whether heterogeneous environmental regulations in China can improve industrial green total factor energy efficiency (IGTFEE) is essential to sustainable industrial development nationwide. However, under China's fiscal decentralization system, the impact of heterogeneous environmental regulations on the IGTFEE and its underlying mechanism needs further exploration. This study incorporates capital misallocation and local government competition into the research framework and systematically investigates the mechanisms and effects of environmental regulations affecting the IGTFEE under China's fiscal decentralization system. Based on provincial panel data from 2007 to 2020, this study measured the IGTFEE using the Super-SBM model with undesirable outputs. Based on efficiency, this study uses a bidirectional fixed-effects model, an intermediary effect model, and a spatial Durbin model for empirical testing. The results show that the effect of command-and-control environmental regulation on the IGTFEE presents an inverted U shape, while the effect of market-incentive environmental regulation on the IGTFEE presents a U shape. Conversely, the effect of command-and-control environmental regulation on capital misallocation presents a U shape, while the effect of market-incentive environmental regulation on capital misallocation presents an inverted U shape. Capital misallocation is the mediating variable of heterogeneous environmental regulations affecting IGTFEE, but heterogeneous environmental regulations do not affect the IGTFEE through the same mechanisms. The spatial spillover effects of command-and-control and market-incentive environmental regulations on IGTFEE present a U shape. Local governments adopt a differentiation strategy for command-and-control environmental regulation and a simulation strategy for market-incentive environmental regulation. Environmental regulations have spillover effects on the IGTFEE under different competitive strategies, but only the imitation strategy, characterized by the race-to-the-top, can promote local and neighboring IGTFEE. Therefore, we propose the following recommendations: the central government should flexibly adjust the intensity of environmental regulations to maximize the capital allocation effect, set diversified performance assessment indicators to motivate local governments into the healthy competition and reform the modern fiscal system to correct distortions in the behavior of local governments.

Green finance, the low-carbon energy transition, and environmental pollution: evidence from China

With 2008-2020 China's provincial panel data as the research object, we use the entropy weight method to compute green finance and pollution, and we empirically study the scope of the spillover effects and threshold impacts of green finance on environmental pollution using the spatial Durbin model and threshold regression model. The findings are as follows: first, under different spatial weight matrices, green finance has a spatial spillover effect on pollution. And the effect boundary is approximately 500 km. Second, with the low-carbon energy transition, technological progress, and green finance as threshold variables, there are a single threshold, single threshold, and double threshold, respectively, that have significant threshold effects. Third, the spillover and threshold effects of green finance on pollution differ by region. The indirect effect is negative in the eastern region and positive in the central and western regions. There is a single threshold effect of low-carbon energy transition and green finance in the western region, a single threshold effect of green finance in the central region, and a single threshold effect of technological progress in the eastern region. On this basis, we put forward. specific policy recommendations.

Assessing the impact of economic growth target constraints on environmental pollution: Does environmental decentralization matter?

In the context of the goal of "carbon neutrality", an economic development model that achieves emission reduction goals and ensures stable economic growth is currently being advocated by China. Based on provincial panel data in China from 2005 to 2016, we analyse the impact of economic growth target (EGT) constraints on environmental pollution using a spatial econometric method. The results indicate that EGT constraints significantly exacerbate environmental pollution in local regions and adjacent areas. Local governments are motivated to achieve economic growth goals at the expense of the ecological environment. The positive effects are attributed to a reduction in environmental regulation (ER), industrial structure upgrading and technological innovation and an increase in foreign direct investment (FDI). Moreover, environmental decentralization (ED) plays a positive regulatory role and can weaken the adverse influences of EGT constraints on environmental pollution. Interestingly, the nonlinear impact of EGT constraints on environmental pollution relies on different types of ED. Environmental administration decentralization (EDA) and environmental supervision decentralization (EDS) can reduce the positive effect of EGT constraints on environmental pollution, while an improvement in environmental monitoring decentralization (EDM) can increase the promoting influences of the constraints of economic growth goals on environmental pollution. The above conclusions still hold under a series of robustness tests. Based on the above findings, we suggest that local governments set scientific growth targets, establish scientific assessment indicators for officials, and optimize the ED management institution.

Governance matters: Urban expansion, environmental regulation, and PM2.5 pollution

Increasing PM2.5 pollution in urban expansion threatens citizens' health. Environmental regulation has proven to be an effective tool to directly combat PM2.5 pollution. However, whether it can moderate the impacts of urban expansion on PM2.5 pollution, in the context of rapid urbanization, is an interesting and unexplored topic. Therefore, this paper constructs a Drivers-Governance-Impacts framework and explores in depth the interactions among urban expansion, environmental regulation, and PM2.5 pollution. Based on 2005-2018 sample data from the Yangtze River Delta region, the estimation results of the Spatial Durbin model imply that (1) urban expansion has an inverse U-shaped association with PM2.5 pollution. The positive correlation may reverse when the ratio of urban built-up land area hits 0.21. (2) Of the three environmental regulations, investment in pollution control has little impact on PM2.5 pollution. Pollution charges and public attention exhibit a U-shaped and inverted U-shaped relationship with PM2.5 pollution, respectively. (3) In terms of moderating effects, pollution charges can exacerbate PM2.5 pollution from urban expansion, while public attention can inhibit it through its monitoring role. Therefore, we suggest that cities adopt differentiated strategies of urban expansion and environmental protection according to their urbanization levels. Meanwhile, appropriate formal regulation and strong informal regulation will help improve air quality.

Spatial effects of air pollutants reduction on CO2 emissions

The sources of air pollutants and CO₂ are basically the same, hence the reduction of air pollutants will affect CO₂ emissions. Considering the regional integration of economic development as well as air pollution control, it is necessary to analyze the impact of air pollutants reduction in a region on CO₂ emissions in its surrounding regions. Furthermore, as different stages of air pollutants reduction have different effects on CO₂ emissions, it is also important to study the heterogeneity of this impact. In this article, we took China as the research case and built a spatial panel model based on the data of 240 cities above the prefecture level from 2005 to 2016 to study the impact of two different stages of air pollutants reduction-front reduction of air pollutants (FRAP) and end-of-pipe treatment of air pollutants (EPAP) on CO₂ emissions-and their spatial spillover effects. On this basis, we further modified traditional spatial weight matrix and constructed the matrices of cities in the same and different provinces to discuss the influence of provincial administrative boundaries on the spillover effect between cities. The results show that FRAP affects CO₂ emissions mainly through the local synergistic effect, and its spatial spillover effect is not significant. The local effect of EPAP on CO₂ emissions is antergic, and the spatial spillover effect is significant. The increase of a city's EPAP will increase the CO₂ emissions in surrounding regions. Besides, provincial boundaries weaken the spatial spillover effects of FRAP and EPAP on CO₂ emissions in prefecture-level cities. There is a significant spatial spillover effect between cities in the same province, but the spillover effect does not exist for cities in different provinces nearby.

How does population agglomeration influence China's energy eco-efficiency? Evidence from spatial econometric analysis

The contradiction between rapid urbanization and energy supply and demand is constraining the green development of Chinese cities. The impact of population agglomeration on urban energy eco-efficiency is still unclear. We used DMSP/OLS and NPP/VIIRS night lighting data, LandScan population dynamics statistics to extract "real urbanized areas" and "real urbanized populations" to measure the population agglomeration index. Considering the spatial interaction effects of economic behavior, we used panel data of 260 Chinese cities from 2006 to 2020 to construct a dynamic spatial Durbin model to explore the impact of population agglomeration on energy eco-efficiency. The study finds that population agglomeration contributes to regional energy eco-efficiency, with a spillover effect to surrounding areas. Endogeneity and robustness tests support the credibility of the results. Technological innovation plays a positive mediating role in the relationship between agglomeration and energy eco-efficiency. Heterogeneity analysis shows that the effect of population agglomeration on energy eco-efficiency varies across temporal and spatial dimensions. Our study provides valuable information for promoting urban energy eco-efficiency from the perspective of population agglomeration.

How do urban socio-economic characteristics shape a city's social recovery? An empirical study of COVID-19 shocks in China

The COVID-19 pandemic outbreak significantly challenged the cities' abilities to recover from shocks, and cities' responses have widely differed. Understanding these disparate responses has been insufficient, especially from a social recovery perspective. In this study, we propose the concept of social recovery and develop a comprehensive perspective on how a city's socioeconomic characteristics affect it. The analytical framework is applied to 296 prefecture-level cities in China, with social recovery measured by the changes in intercity intensity between the pre-pandemic baseline (2019 Q1 and Q2) and the period in which the pandemic slightly abated (2020 Q1 and Q2) through anonymized location-based big data. The results indicate that the social recovery of Chinese cities during the COVID-19 pandemic are significantly spatially correlated. Cities with larger populations, a higher proportion of GDP in the secondary industry, higher road density or more adequate medical resources tend to recover socially better. Moreover, these municipal characteristics have significant spatial spillover effects. Specifically, city size, government intervention and industrial structure show negative spillover effects on neighboring areas while information dissemination efficiency, road density, and the number of community health services per capita have positive spillover. This study fills the knowledge gap regarding the different performances of cities when they face pandemic shocks. The assessment of a city's social recovery is an insight into the theoretical framework of vulnerability that aids in translating it into urban resilience. Hence our findings provide practice implications for China and beyond as the interest in urban-resilience development surges around the post-pandemic world.

Physical and virtual nutrient flows in global telecoupled agricultural trade networks

Global agricultural trade creates multiple telecoupled flows of nitrogen (N) and phosphorus (P). The flows of physical and virtual nutrients along with trade have discrepant effects on natural resources in different countries. However, existing literature has not quantified or analyzed such effects yet. Here we quantified the physical and virtual N and P flows embedded in the global agricultural trade networks from 1997 to 2016 and elaborated components of the telecoupling framework. The N and P flows both increased continuously and more than 25% of global consumption of nutrients in agricultural products were related to physical nutrient flows, while virtual nutrient flows were equivalent to one-third of the nutrients inputs into global agricultural system. These flows have positive telecoupling effects on saving N and P resources at the global scale. Reducing inefficient trade flows will enhance resource conservation, environmental sustainability in the hyper-globalized world.

The impact of vertical fiscal asymmetry on carbon emissions in China

Facing the double pressure of promoting economic growth and achieving the goal of "emission peak" by 2030, China must cut down the carbon emission intensity. Focusing on the typical characteristics of China's financial system arrangement, we theoretically analyze the mechanism of vertical fiscal asymmetry affecting carbon emission intensity and use a panel data from 30 Chinese provinces to conduct an empirical examination. The results show that (1) vertical fiscal asymmetry significantly increases the local carbon emission intensity. After a series of robust tests, such as replacement variables and sample data, the conclusion is still valid. (2) The analysis of regional heterogeneity shows that the influence of vertical fiscal asymmetry in carbon emission intensity is the largest in the central area of China, followed by the eastern provinces, and not evident in the western area. The rise in carbon emission intensity brought on by vertical fiscal asymmetry can be successfully reduced by the central transfer payment. The impact of vertical fiscal asymmetry on carbon emission intensity will be greatly lessened when the central transfer payment surpasses the threshold. (3) The mechanism test shows that vertical fiscal asymmetry increases the carbon emissions intensity by three paths: reducing the intensity of environmental regulation, strengthening local governments' dependence on land finance, and local government competition. The above analysis further enriches the relevant research on how China's vertical fiscal asymmetry system affects carbon emission intensity through land finance and local government competition while pointing out the role of transfer payment, and it can help to provide new ideas and empirical evidence for further improving the financial system and promoting the green development of the economy.

The heterogeneous effects of environmental regulation on industrial carbon emission efficiency in China using a panel quantile regression

In order to verify how environmental regulation affects the improvement of urban industrial carbon emission efficiency, this study first measures the balanced panel data of industrial carbon emission efficiency of 282 cities in China from 2003 to 2019, and evaluates the direct and regulating impact of environmental regulation on China's urban industrial carbon emission efficiency. Meanwhile, in order to investigate the potential heterogeneity and asymmetry, the panel quantile regression method is used. The empirical results show that (1) during the period 2003-2016, China's overall industrial carbon emission efficiency showed a upward trend, with a decreasing spatial pattern from the east-central-west-northeast region. At the urban scale in China, environmental regulation has a significant direct effect on industrial carbon emission efficiency, which is lagged and heterogeneous. At the low quantiles, a one-period lag in environmental regulation has a negative effect on the improvement of industrial carbon emission efficiency. At the middle and high quantiles, a one-period lag in environmental regulation has a positive effect on the improvement of industrial carbon emission efficiency. Environmental regulation has a moderating effect on industrial carbon efficiency. With increasing industrial emission efficiency, the positive moderating effect of environmental regulation on the relationship between technological progress and industrial carbon emission efficiency shows a pattern of diminishing marginal benefits. The main contribution of this study is the systematic analysis of the potential heterogeneity and asymmetry of the direct and moderating effects of environmental regulation on the industrial carbon emission efficiency at the city scale in China by using panel quantile regression method.

How does environmental regulation affect industrial structure upgrading? Evidence from prefecture-level cities in China

This study examines whether and how environmental regulation affects industrial structure upgrading with a panel data of 270 cities between 2006 and 2019. We first adopt two indicators-rationalization and advancement-to quantify industrial structure upgrading and then use kernel density estimation as well as trend surface analysis to investigate these indicators' spatial-temporal pattern. With a spatial Durbin model, we find that environmental regulation has inverted U-shaped and U-shaped direct impacts on rationalization and advancement, and inverted U-shaped indirect impacts on both rationalization and advancement in neighboring regions. Moreover, our subsample tests demonstrate that environmental regulation has various impacts on industrial structure upgrading in different regions. Last, a mediating effect analysis shows that technological innovation is an important path for environmental regulation to promote advancement. Our study provides new evidence for the Porter hypothesis, and offers suggestions for the authorities to formulate and optimize environmental regulation intensity.

Decomposition, decoupling, and future trends of environmental effects in the Beijing-Tianjin-Hebei region: A regional heterogeneity-based analysis

The green growth of Beijing-Tianjin-Hebei (BTH) urban agglomeration plays a leading and exemplary role in overcoming internal resource restrictions, addressing climate change, and supporting China's high-quality growth. From the standpoint of pollution reduction and carbon reduction, this paper first conducts a comprehensive evaluation of the environmental impact based on combined weighting technique. The Logarithmic Mean Divisia Index (LMDI) model is used to decompose the environmental impact drivers in distinct areas. A decoupling effort index is further constructed to measure the effect of various efforts on the decoupling of economic growth and environmental impact, the improved grey Markov model is applied to predict the future trend of regional decoupling efforts. The results of empirical analysis based on data of the BTH region during 2011-2018 show that: 1) the environmental impact index of Beijing is the lowest followed by Tianjin and Hebei; 2) environmental regulation exerts the most significant impact on reducing environmental pressure in Beijing while technology progress and energy intensity have the most significant effect on easing environmental pressure in Tianjin; 3) strong decoupling efforts have been found in Beijing, Tianjin and Hebei, however, such effect is more significant in Beijing; 4) Beijing's decoupling state is mostly driven by regulatory effect, intensity effect, and scale effect, while Tianjin and Hebei's decoupling states are primarily driven by improvements in environmental regulation and energy intensity; 5) according to the forecast outcome of the improved grey Markov technique, a state of strong decoupling effort will be maintained in the BTH area by 2025, and the decoupling effort index in Beijing will remain the highest while the index in Hebei will remain the lowest.

Comparing the impacts of carbon tax and carbon emission trading, which regulation is more effective?

While many literatures have examined the influence of environmental regulation policy, which environmental regulation policy is more effective is still controversial. Taking China and two different economic regions as samples, we explore the effect of two popular environmental regulation policies, that is carbon tax and carbon emission trading, by a multi-regional environmental dynamic computable general equilibrium model. The results show that for the economic development, the carbon emission trading outperforms the carbon tax for the carbon emission trading will generate the lower economic cost. But for the emission reductions, the carbon tax outperforms the carbon emission trading for the total emissions from 2020 to 2030 are smallest when introducing carbon tax policy. We further study the effect of environmental regulation on different industries. It is found that the environmental regulation has a more obvious effect on energy industry, heavy industry and transport service industry.

Construction of Urban Environmental Performance Evaluation System Based on Multivariate System Theory and Comparative Analysis: A Case Study of Chengdu-Chongqing Twin Cities, China

Based on the related environmental data of Chengdu and Chongqing from 2011 to 2020, this paper constructs a multivariate environment performance evaluation system, combines the self-built indicator system determination criteria and rules, evaluates and compares the environmental performance of Chengdu and Chongqing, and also discusses the impact of COVID-19 on urban environmental performance. The research results show that the overall environmental performance increased from 2011 to 2020, but there are differences between different subsystems, mainly manifested in the best water environment performance, followed by air environment and solid waste; moreover, the noise environment maintains a relatively stable level. By comparing the average levels of various subsystems of the Chengdu-Chongqing dual cities from 2011 to 2020, it can be seen that Chengdu City has better environmental performance in air environment and solid waste, while Chongqing City has better environmental performance in the water environment and noise environment. In addition, this paper also found that the impact of the epidemic on urban environmental performance mainly comes from the impact on the air environment. At present, the overall environmental performance of the two places has shown a trend of environmentally coordinated development. In the future, Chengdu and Chongqing should further optimize and improve their relatively weak environmental subsystems, deepen the joint action mechanism between the two places, and build a green and high-quality development economic circle for the Chengdu-Chongqing twin cities.

Causality and dynamic spillover effects of megacities on regional industrial pollution reduction

Regional economic power and local environmental policies have a substantial impact on pollution reduction in urban agglomerations (UAs); however, whether megacities in UAs exert spillover effects of pollution reduction on surrounding cities remains unknown. This study presents a causal analytic framework to evaluate the spillover effects of megacities on regional industrial pollution reduction in three major UAs in China between 2005 and 2016. The interaction between industrial pollution reduction and infrastructure investment indicators was also examined. Results indicated a good fit for spatial spillover of sulfur dioxide reduction (SR) in the Pearl River Delta (PRD) and Yangtze River Delta (YRD) but not in the Beijing-Hebei-Tianjin cluster (JJJ). Spatial spillover of dust reduction (DR) was evident in the PRD and JJJ but not the YRD. Spatial analysis showed that infrastructure investment indicators, at megacity and UA levels, had short-term spillover effects on surrounding cities for DR but not SR. However, spatial spillover effects, at both the city and UA levels, were substantial over the long term. In addition, the results of the spatial-time lag analysis suggest a linear relationship between pollution control-related infrastructure investment indicators and long-term pollution reduction. This study provides new information regarding the spatial spillover effects of megacities on regional industrial pollution reduction in UAs.

Influence of air quality ranking on China's energy efficiency: spatial difference-in-differences model with multiple time periods

Exploring the impact of air quality ranking on energy efficiency and its spatial spillovers will help improve the pollution and carbon reduction effects of environmental governance policies. Based on the panel data of 285 cities at or above prefecture level in China during 2009-2019, this study pioneers in adopting difference-in-differences (DID) model with multiple time periods, spatial DID (SDID) model with multiple time periods, and mediating effect to explore the direct influence of ranking on China's energy efficiency, as well as its spatial effect and influence mechanism. Results show that air quality ranking is of significant positive impact on energy efficiency, proved by parallel trend hypothesis, placebo control, and policy heterogeneity. With spatial effect considered, such impact still exists, and ranking of the experimental group has significant positive spatial spillover effect on efficiency of the control group, meaning the ranking also promotes the efficiency of nearby cities in control groups via spatial spillover effect. In addition, air quality ranking greatly elevates energy efficiency via industrial structure and technological innovation, the mechanism of which is of significant positive spatial spillover effect. Based on the above results, some policy recommendations on environmental competition policy, industrial structure adjustment, and low-carbon applicable technology promotion were proposed to promote the energy efficiency of China.

Spatial Differentiation of PM2.5 Concentration and Analysis of Atmospheric Health Patterns in the Xiamen-Zhangzhou-QuanZhou Urban Agglomeration

Exploring the spatial differentiation of PM2.5 concentrations in typical urban agglomerations and analyzing their atmospheric health patterns are necessary for building high-quality urban agglomerations. Taking the Xiamen-Zhangzhou-Quanzhou urban agglomeration as an example, and based on exploratory data analysis and mathematical statistics, we explore the PM2.5 spatial distribution patterns and characteristics and use hierarchical analysis to construct an atmospheric health evaluation system consisting of exposure-response degree, regional vulnerability, and regional adaptation, and then identify the spatial differentiation characteristics and critical causes of the atmospheric health pattern. This study shows the following: (1) The average annual PM2.5 value of the area in 2020 was 19.16 μg/m3, which was lower than China's mean annual quality concentration limit, and the overall performance was clean. (2) The spatial distribution patterns of the components of the atmospheric health evaluation system are different, with the overall cleanliness benefit showing a "north-central-south depression, the rest of the region is mixed," the regional vulnerability showing a coastal to inland decay, and the regional adaptability showing a "high north, low south, high east, low west" spatial divergence pattern. (3) The high-value area of the air health pattern of the area is an "F-shaped" spatial distribution; the low-value area shows a pattern of "north-middle-south" peaks standing side by side. The assessment of health patterns in the aforementioned areas can provide theoretical references for pollution prevention and control and the construction of healthy cities.

The local-neighborhood effects of low-carbon city pilots program on PM2.5 in China: A spatial difference-in-differences analysis

Using the balanced panel of 260 cities in China from 2005 to 2018, this study explores the local-neighborhood effects of the low-carbon city pilots (LCCPs) program on PM_2.5 concentration by utilizing the spatial difference-in-differences (SDID) method. The results show that the LCCPs program can not only reduce the local PM_2.5 concentration but also effectively alleviate the smog pollution in neighboring cities. The reduction effect of LCCPs on PM_2.5 in local cities is more significant in central and western areas, second-tier and above cities and resource-based cities. Nevertheless, the spillover effect on neighboring cities is more significant in central and western areas, third-tier and below and non-resource-based cities. In addition, the impact of policy is mainly through green innovation, while the intermediary role of industrial structure upgrading is not significant. These findings can provide useful policy inspiration for scientifically implementing air pollution prevention and control actions and winning the battle to defend the blue sky.

Analysis of Spatiotemporal Changes of Ecological Environment Quality and Its Coupling Coordination with Urbanization in the Yangtze River Delta Urban Agglomeration, China

It is inevitable that urban agglomeration will have a coercive impact on the regional Ecological Environment Quality (EEQ) as a consequence of high-speed urbanization. Balancing the EEQ and urbanization development has become a problem worthy of attention. In order to objectively evaluate the EEQ of the Yangtze River Delta Urban Agglomeration (YRDUA) and explore the impact of the urbanization process on it, this paper is based on the Modified Remote Sensing Ecological Index (MRSEI) and the Comprehensive Night Light Index (CNLI), respectively, and conducts a quantitative assessment of the YRDUA in China from 2000 to 2020. The results show that: (1) From 2000 to 2020, the MRSEI of the YRDUA first decreased and then increased, and the ecological environment quality degraded first and then improved; however, there were significant differences between regions. The ecological environment quality in the south is obviously better than that in the north, and the ecological environment quality in the north changes more drastically, and the low value area of MRSEI will gradually move downstream as time changes; (2) During the study period, the YRDUA formed a hierarchical and progressive urbanization pattern. The inland urbanization process expanded from east to west along the Yangtze River, and the urbanization process of coastal cities expanded from Shanghai as the center to the north and south with high-intensity urbanization cities concentrated in Shanghai and its surrounding cities and low-intensity urbanization cities distributed in the western part of the urban agglomeration; (3) The Coupling Coordination Degree (CCD) between urbanization and EEQ in the YRDUA has continuously improved with an increase of 28.57% in the past 21 years, and the number of cities with high level coupling continues to rise, while the number of medium level coupling cities and low level coupling cities has declined. As a large-scale and long-term analysis of changes in the EEQ and the urbanization process, this study can provide theoretical support for policymakers to formulate mesoscale development planning, EEQ monitoring, and environmental protection policies.

Spatiotemporal characteristics of air pollution in Chengdu-Chongqing urban agglomeration (CCUA) in Southwest, China: 2015-2021

Studying the spatiotemporal characteristics of air pollutants in urban agglomerations and their response factors will help to improve the quality of urban living. In combining air quality monitoring data and wavelet analysis from the Chengdu-Chongqing urban agglomeration (CCUA), this study assessed the spatiotemporal distribution characteristics and influential factors of air pollutants on daily, monthly and annual scales. The results showed that the concentration of air pollutants in the CCUA has decreased year by year, and air quality has improved. Except for O₃, pollutants in autumn and winter were higher than those in summer. The spatial distribution of air pollutants was obvious distributed in Chengdu, Chongqing, Zigong and Dazhou. Pollution incidents were mainly concentrated in winter. The 6 air pollutants and air quality index (AQI) have dominant periods on multiple time scales. AQI showed positive coherence with PM_2.5 and PM₁₀ on multiple time scales, and obvious positive coherence with SO₂, CO, NO₂ and O₃ in the short term scale. AQI was not strongly correlated with the fire point, but exhibited obvious negative coherence in the long term scale. In addition, AQI showed an obvious positive correlation with temperature and sunshine hours in short term, and a clear negative correlation with humidity and rainfall. The research results of this paper will provide a reference for pollution prevention and control in the CCUA.

Environmental regulation effect on green total factor productivity in the Yangtze River Economic Belt

As a typical watershed ecological economy in China, the Yangtze River Economic Belt has two equally important objectives, namely ecological protection and economic development. Improving green total factor productivity is an essential approach to achieve these two objectives and promote sustainable growth in this area as well as the whole country. Therefore, this study explores the impact of environmental regulation on green total factor productivity with a panel data of 108 cities in the Yangtze River Economic Belt between 2003 and 2019. We first adopt the super slacks-based measure model to estimate city-level green total factor productivity. With kernel density curve, we find that green total factor productivity shows a downward pressure, and its absolute difference among cities shows a narrowing trend. Trend surface analysis displays an inverted U-shaped as well as a U-shaped spatial structures of green total factor productivity in the north-south as well as east-west directions, respectively. By using Spatial Durbin Model, we find a U-shaped direct impact of environmental regulation on green total factor productivity for the entire sample and three subsamples. For an indirect effect, environmental regulation has a positive spatial spill-over impact in the entire area; an insignificant effect in upstream and midstream areas; and an inverted U-shaped spatial spill-over in downstream area. Besides, we utilize threshold effect analysis to explore the impacts of technology innovation. The results show a single-threshold effect of technology innovation and the promotion effect decreases when technology innovation expenditure exceeds the threshold value. Based on our research findings, we suggest that the authorities should adhere to implementing and increasing the intensity of environmental regulation, so as to achieve better policy results. Moreover, local governments should keep technological innovation expenditure at a reasonable level to maximize the promoting effect of environmental regulation on green total factor productivity.

The impact of heterogeneous environmental regulations on regional spatial differences in net carbon emissions

Effected by spatial difference and types of environmental regulation, enhanced environmental regulation does not necessarily lead to reduce net carbon emissions (NCE). Based on panel data of 30 province-level administrative regions in China from 2003 to 2018, this paper analyzed the impact of heterogeneous environmental regulations on NCE using geographically weighted regression (GWR). The results showed that (1) the total NCE of each province in China presented an increasing trend followed by fluctuation, with obvious spatial aggregation characteristics. (2) The intensity of four environmental regulations, command-and-control (CAC), market-incentive (MI), public-participation (PP), and voluntary environmental program of firm (VEPF) tended to increase slightly over the study period with decreasing spatial heterogeneity. (3) CAC environmental regulations had a "green paradox" effect on NCE, meaning an improving CAC environmental regulation would surprisingly increase its negative effects and contribute to NCE growth. The effect of MI environmental regulation on NCE shifted from overall promotion to partly promotion and even suppression. PP and VEPF environmental regulation would reduce NCE. The suppressive effect of PP environmental regulation grew over time, while VEPF did not. Finally, based on the research conclusion, some policy suggestion are proposed for differentiated management, diverse system of governance, and collaborative governance.

Can Expanding Cultural Consumption Improve Urban Air Quality? An Analysis Based on China's Cultural Consumption Pilot Policy

As an important reform exploration to promote economic transformation and upgrading in China, can the national cultural consumption pilot policy improve urban air quality? What are the impact paths? Based on a theoretical analysis of the intrinsic mechanism of expanding cultural consumption affecting urban air quality, this paper constructs the DID model with a quasi-natural experiment, namely the national cultural consumption pilot, to assess the impact of expanding cultural consumption on urban air quality. The results show that: expanding cultural consumption has a significant improvement effect on urban air quality, and the emission reduction effect is also increasing year by year; the heterogeneity analysis shows that expanding cultural consumption has a stronger pollution reduction effect in cities north of the Qinling-Huaihe line, and the effect on air quality is more significant in non-resource cities; the mechanism test indicates that government intervention and public participation have a significant moderating role in the emission reduction effect of cultural consumption. In other words, the higher the level of government intervention and the greater the degree of public participation in the cultural consumption pilot, the stronger the pollution reduction effect of expanding cultural consumption. In addition, cultural consumption has an impact on urban air quality mainly through the industrial structure effect and innovation effect. The findings of this study provide policy insights to further promote the emission reduction effect of cultural consumption and promote urban air quality.

Natural and anthropogenic factors on China's ecosystem services: Comparison and spillover effect perspective

With the development of urbanization, ecological space is increasingly disturbed and invaded by human activities. From 2000 to 2020, the value of ecosystem services in China decreased from 28.05 to 27.77 trillion yuan. This paper combines the natural and social data of 370 administrative units in China from 2000 to 2020 with the GTWR model. Our results show that in most regions of China, the coefficient value of factor GDP or POP is significantly higher than that of other factors. The regions with higher natural factors coefficient value are concentrated in the northwest and southeast. In addition, this study found that the driving factors and ESV have geographical spillover effects. The above conclusions have important practical significance for planning policies according to local conditions.

Central environmental protection inspection and green technology innovation: empirical analysis based on the mechanism and spatial spillover effects

In this study, the central environmental protection inspection (CEPI) policy is considered a quasi-natural experiment. Based on the data of 216 Chinese cities from 2008 to 2018, the influence of CEPI on green technology innovation (GTI) is empirically examined mainly using difference-in-differences (DIDs), propensity score matching DID and spatial DID methods. The results indicate that CEPI can effectively promote GTI. Regarding different types of GTI, CEPI mainly promoted utilitarian GTI. Regarding the mechanism, CEPI significantly promotes local GTI mainly through the increase of environmental protection expenditure and research and development investment. Considering the dynamic marginal effect, CEPI starts to significantly promote GTI in the second year after the policy implementation but exhibited no effects in the third year. The extended study shows that GTI effect of CEPI only occurs in small-medium cities and big cities. Furthermore, there is a certain beggar-thy-neighbor effect between inspected and uninspected cities. Finally, the spatial decomposition of CEPI effects shows that the inhibitory effect of CEPI on GTI mainly occurs in the neighboring uninspected cities, while CEPI has no evident inhibition on GTI in neighboring inspected cities.

Policy, technical change, and environmental efficiency: Evidence of China's power system from dynamic and spatial perspective

Feed-in tariff (FIT) and renewable portfolio standard (RPS) policies have been implemented to facilitate wind and solar power technologies with the aim of achieving sustainable development in power system. It is essential to study how efficient these policies are in accelerating technical progress and how efficient the power system is in balancing development and environmental protection. Dynamic network data envelopment analysis and the global Malmquist productivity index are first employed to study the environmental efficiency and technical progress, after which a dynamic spatial Durbin model is applied to analyze the impact of policies on technical progress. The results reveal that both FIT and RPS lead to technical progress which is the main driving force in environmental efficiency improvement, but that RPS performs better than FIT. From a spatial perspective, the adjacent regions usually show similar characteristics in technical progress. Therefore, future policy design should carefully consider the regional agglomeration effects and should effectively strengthen the implementation of RPS policy.

Urban land expansion, fiscal decentralization and haze pollution: Evidence from 281 prefecture-level cities in China

Urban land expansion will influence aspects of economy and society, including the quality of the urban environment. This study aims to examine the impacts of urban land expansion in China on haze pollution under the fiscal decentralization system using the spatial Durbin model. Urban land expansion is measured using two dimensions of urban land expansion, namely, intensity and orderliness of the structure of urban land expansion. The results reveal that urban haze pollution in China exhibits significant positive spillover characteristics, which manifest as "high-high" and "low-low" characteristics of spatial agglomeration. In general, improving the expansion intensity of urban land and the orderly structure of urban land expansion can reduce haze pollution in local and surrounding areas. With the improvement of the degree of fiscal decentralization, the positive effect of an orderly urban land structure in reducing haze pollution will be weakened. The above-mentioned influences depict distinct heterogeneities at the levels of city size, type, and location.

Evaluating the effects of air pollution control policies in China using a difference-in-differences approach

Air pollution has caused wide concern in China, and many governance policies and plans have been implemented in recent years. Based on counterfactual quasi-natural experiments, we analyzed the implementation effects of autumn and winter air pollution control policies in the Jing-Jin-Ji region and surrounding areas using a difference-in-differences (DID) model. The control group was selected based on geographical and meteorological factors, and we analyzed the impact of the policies on six pollutants. The results show that the policies reduced air pollution overall, but not every pollutant. Due to the policy contribution, the concentrations of PM_2.5 and PM₁₀ in autumn and winter from 2017 to 2018 decreased by 6.9 % and 8.5 %, respectively. The numerical value of PM_2.5, PM₁₀, CO, and AQI in 2018-2019 decreased by 18.2 %, 7.2 %, 13.9 %, and 8.8 %, respectively. The role in the reduction of O₃, SO₂, and NO₂ was not obvious. This work provides a research paradigm for evaluating the effects of atmospheric environment policy which can be applied to other studies and provide references for formulating additional policies.

Impacts of Social Inequality, Air Pollution, Rural-Urban Divides, and Insufficient Green Space on Residents' Health in China: Insight from Chinese General Social Survey Data Analysis

Attention to physical and mental health is becoming more intensive. In China, factors and mechanisms are now a focus of research. We used dynamic air quality monitoring data and the Chinese General Social Survey (CGSS) to assess the spatial differences and the coupling between subjective and objective air pollution. In addition, a logistic model was used to explore the impact mechanisms of social inequality, air pollution, food safety, and lack of green space on health. The results show that (1) the impact of subjective and objective air pollution on the health level of the population is significant; (2) income inequality, air pollution, food pollution, and travel behavior significantly affect the residents' health; and (3) environmental health has a significant differentiation mechanism between urban and rural areas. The negative health effects of air pollution and insufficient green space are more significant in cities; food pollution is more likely in rural areas. In terms of socioeconomic inequality, gender, family size, travel, and physical exercise had no significant effect on rural health. Health improvement was higher in the low-income group than in the high-income group. The adverse effect of travel behavior on environmental pollution is conducive to improving health. Therefore, social equality, strictly controlled environmental pollution, exercise, and travel can help narrow the gap between rich and poor, promote urban-rural health equity, and improve human health.

Efficiency measurement and spatial spillover effect of provincial health systems in China: Based on the two-stage network DEA model

The effectiveness of a health care system is an important factor for improving people's health and quality of life. The purpose of this research is to analyze the efficiency and spatial spillover effects of provincial health systems in China using panel data from 2009 to 2020. We employ the two-stage network DEA model to evaluate their efficiencies and use a spatial econometric model for empirical estimation. The results suggest that the overall efficiency, resource allocation efficiency, and service operation efficiency of health systems in different regions of China generally have fluctuating upward trends, with large differences in efficiency among the various regions. Further analysis reveals that the efficiency of China's health system has a significant spatial spillover effect. The level of economic development, fiscal decentralization and old-age dependency ratio are important factors affecting the health system efficiency. Our findings help to identify the efficiency and internal operating mechanisms of China's health system at different stages, and are expected to contribute to policymakers' efforts to build a high-quality health service system.

What drives the spatio-temporal distribution and spillover of air quality in China’s three urban agglomerations? Evidence from a two-stage approach

Beijing-Tianjin-Hebei urban agglomeration (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) are the most important economic hinterlands in China, offering high levels of economic development. In 2020, their proportion of China’s total GDP reached 39.28%. Over the 5 years of 2014–2018, the annual maximum air quality index (AQI) of the three major urban agglomerations was greater than 100, thus maintaining a grade III light pollution (100 &lt; AQI &lt; 200) in Chinese air standards. This research thus uses a two-stage empirical analysis method to explore the spatial-temporal dispersal physiognomies and spillover effects of air quality in these three major urban agglomerations. In the first stage, the Kriging interpolation method regionally estimates and displays the air quality monitoring sampling data. The results show that the air quality of these three major urban agglomerations is generally good from 2014 to 2018, the area of good air is gradually expanding, the AQI value is constantly decreasing, the air pollution of YRD is shifting from southeast to northwest, and the air pollution of PRD is increasing. The dyeing industry shows a trend of concentration from northwest to south-central. In the second stage, Moran’s I and Spatial Durbin Model (SDM) explore the spatial autocorrelation and spillover effects of air quality related variables. The results show that Moran’s I values in the spatial autocorrelation analysis all pass the significance test. Moreover, public transport, per capita GDP, science and technology expenditure, and the vegetation index all have a significant influence on the spatial dispersal of air quality in the three urban agglomerations, among which the direct effect of public transport and the indirect effect and total effect of the vegetation index are the most significant. Therefore, the China’s three major urban agglomerations (TMUA) ought to adjust the industrial structure, regional coordinated development, and clean technology innovation.

The effect of environmental regulation competition on haze pollution: evidence from China's province-level data

Haze pollution has drawn lots of public concern due to its potential damages to human health. Strategic interaction of environmental regulation among local governments may lead to a race to the bottom and hinder air quality improvement. Still, current empirical evidence is scarce, especially from developing countries. Based on province-level panel data from 2004 to 2015, the paper employs a dynamic fixed effect spatial Durbin model to identify interactive patterns of environmental regulation and then investigate its environmental impact. Empirical results indicate that regional differences are observed in environmental regulation and haze pollution, and high-high and low-low clusters dominate the spatial pattern. Interactive patterns of economically similar provinces are dominated by strategic substitution, whereas provinces sharing common borders or belonging to the same region are dominated by strategic complementation. Further, both race to the bottom and race to the top effect are discovered in the asymmetric test. The reaction coefficient values are much more extensive when competitors implement laxer policies, indicating a more significant racing trend to the bottom. Overall, after controlling for the spillover effect and hysteresis effect of haze pollution, the strategic interaction of environmental regulation among provinces is not conducive to improve air quality. The consequence might be correlated with low environmental standards, weak regulation enforcement, and the "free-ride" motive in China. These findings will be of great significance for optimizing local government behavior and improving air quality.

Is the sky of smart city bluer? Evidence from satellite monitoring data

How to win the "Blue Sky Protection Campaign" is becoming the focus all over the world, especially in developing economies, while the implementation of the smart cities initiative (SCI) is seen to be a feasible program to address the negative environmental externalities through Information and Communication Technologies (ICTs), but it lacks the quantitative evidence so far. This study aims to examine the impacts and potential mechanisms of SCI on air pollution governance from the objective satellite monitoring data within a quasi-natural experiment framework. We find that SCI directly reduces the air pollutants concentration such as PM2.5, SO₂, NO₂, and smog in urban China and improves the air quality very well, which also has significant and positive spillovers on air pollution governance in adjacent cities. This encouraging phenomenon can also be achieved through contributing to green technological innovation, industrial structure upgrading, and decentralizing urban spatial structure, such that most of can be attributed to the technological effect. Heterogeneity analyses demonstrate that the governance effect of air pollution is more obvious in large smart cities, and increases with the expansion of city size. Additionally, the effect performs better in resource-based smart cities and smart cities with stronger financing capacity and air pollution pressure.

Environmental regulation, market demand, and green innovation: spatial perspective evidence from China

This paper used a dynamic spatial panel model to empirically analyze the effects of environmental regulation, market demand, and the associated spatial spillovers on regional green innovation in China, from which the following was found. (1) The environmental regulations had a positive "U-shaped" effect on local green innovation and a positive neighborhood spillover effect, and market demand had a significant positive effect on local green innovation and a "ripple effect." (2) The mechanism analysis found that the environmental regulations tended to inhibit regional green innovation input through a "cost compliance" effect, and market demand had a stronger incentive effect on innovation input than the environmental regulations, thus promoting the improvement of green innovation level. (3) The environmental regulation and market demand effects on green innovation had obvious spatial and temporal heterogeneity. The results of this study could help to promote regional green innovation by formulating reasonable environmental policies and stimulating the vitality of green technology market.

Air pollution and innovation performance of Chinese cities: human capital and labour cost perspective

Environmental protection and innovation performance are key issues that affect the sustainable development and value growth of cities. Using data of 272 prefecture-level cities during 2002-2016 and 2,169 listed companies, and the air ventilation coefficient and government environmental regulations, as the instrumental variables for PM_2.5 concentrations, this paper applies two-stage OLS (2SLS) to investigate how air pollution affects China's technological innovation and its realization mechanism. The results indicate that the rise in air pollution significantly inhibits the technological innovation level of regions as a whole as well as individual enterprises. When considering the spatial effect of the spread of PM_2.5 concentrations, due to positive spillover effects on innovation activities, the spread of air pollution has negative impacts on technological innovation activities in surrounding cities. Human capital and labour costs are important channels through which air pollution influences China's technological innovation. The implementation of pilot carbon trading policies can effectively reduce air pollution and then contribute to the achievement of the goals of the green growth strategy.