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In the context of global low-carbon emission reduction, how to achieve green and high-quality development has become a major issue for the Communist Party of China (CPC) and the Chinese government recently. Based on the data of China's listed companies from 2013 to 2020, this paper uses Python to implement text analysis of annual reports, and explores the relationship between political acuity and carbon-efficiency synergies (CES) from the perspective of enterprise initiative. We found that (1) political acuity positively affects carbon-efficiency synergies. (2) Increased political acuity can reduce carbon emissions, but the effect on economic efficiency is not obvious. That is, low carbon takes the lead in raising the level of carbon-efficiency synergies. (3) Environmental regulations can positively regulate the relationship between political acuity and carbon-efficiency synergies. (4) Political acuity in southern China, carbon neutral and non-state-owned enterprises (NSOEs) will have a more pronounced effect on carbon-efficiency synergies. From the perspective of the root causes of political linkages, we find the synergies between formal and informal institutions, and the key factors for policy implementation. This paper is helpful for enterprises to improve the synergies of emission reduction and efficiency promotion, and has practical implications for the government to promote green and high-quality development. • Assess the value of the low-carbon economy from its political roots. • We build a carbon-efficiency synergy evaluation system. • Political acuity and formal institutions are synergistic. • The influence of political acuity on CES can be replicated. • This paper expands the technical approach to low-carbon research. [ABSTRACT FROM AUTHOR]

Green innovation is important and beneficial for the green development of enterprises. The development of digital technology could improve the asymmetry of information and affect the enterprise's financing modes. Currently, a definitive conclusion about the relationship between the digital transformation and green technology innovation has not reached. Additionally, studies have not yet fully explored the impact pathways of corporate digital transformation on green innovation through corporate financing modes. To fill this void, this study collected data of Chinese A-share listed companies from 2010 to 2020. The empirical analysis results showed that digital transformation significantly enhanced enterprises' green innovation abilities. Furthermore, mediating models were utilized to explore how enterprise financing modes mediate the impact of digital transformation on the enterprise green innovation. Results indicated that through internal financing and bank loans as "bridges", digital transformation promoted enterprise green innovation. However, digital transformation did not have a significant impact on enterprise green innovation through venture capital. Moreover, heterogeneity analyses revealed significant differences among different groups of enterprises. This study expands the research field related to digital transformation and enterprise green innovation by providing empirical evidence to uncover the impact of digital transformation on enterprise green innovation. Findings of this study contribute not only to enterprise managerial decision-makers to better leverage digital transformation through corporate financing to accelerate green innovation, but also to government policymakers to design policies to stimulate enterprise green innovation. • Firstly, our paper empirically examines and validates the impact of digital transformation on enterprise green innovation again by using empirical data of biggest development counties, i.e., China. • Secondly, our paper combines enterprise digital transformation, financing modes, and green innovation within the same framework to study the "bridge" role of financing modes between digital transformation and enterprise green innovation. • Thirdly, Thirdly, heterogeneity analyses were carried out, the results of the different enterprises groups are significant different. [ABSTRACT FROM AUTHOR]

"Carbon peaking and carbon neutralization" is an important measure to promote China's ecological and environmental protection and high-quality economic development, and the innovation and application of green technology are critical factors in achieving the "double carbon" goal. Based on the number of citations of green patents of listed enterprises in 30 provinces in China from 2011 to 2020, this paper uses GGDP to replace traditional GDP and calculate carbon emission intensity. Based on the relevant panel data at the provincial level, this paper constructs a spatial Durbin model to analyze the impact mechanism of whether the promotion and application of green technologies promote regional carbon emission reduction. The specific research results are as follows: (1) Through regression of the core explanatory variables with a one-stage lag, it is verified that the promotion and application of green technology has a significant positive promoting effect on regional carbon emission reduction, and there are significant spatial spillover effects and "learning by doing" effects. (2) In the part of heterogeneity test, the impact of green technology promotion and application on carbon emission reduction presents apparent regional heterogeneity and factor endowment heterogeneity. (3) The mediating effect test verifies the mediating effect of energy structure and industrial structure on the influence of green technology promotion and application on regional carbon emission reduction. (4) In the part moderating effect test, it is verified that marketization level and new infrastructure construction have a positive moderating effect in their influencing process, financial development, and government support will weaken the influence of green technology promotion and application on carbon emission reduction effect, and human capital level has a nonlinear regulating effect. The research conclusions of this paper provide necessary enlightenment for the coordination and unification of China's economic transition to innovation-driven and green and low-carbon development. • The impact of GTPA on reduction in China was analyzed from a macro perspective. • The GS and FDL plays a negative moderating role in the influence process. • The HCL plays a nonlinear moderating role in the influence process. • The GTPA can significantly reduce regional CEI except in Western China. • Regions with high EDL and high GTI have better carbon reduction effects of GTPA. [ABSTRACT FROM AUTHOR]

High carbon emissions and population aging are two obstacles to China's development as an emerging economy. It is urgent to scientifically examine the impacts of population aging on carbon emissions to discover new pathways for urban carbon emission reduction. However, existing studies face challenges in terms of focusing on and methodology for accurately capturing the role of industrial production and energy consumption in the environmental effects of population aging. This paper constructs a chain mediation analytical framework and systematically examines the intrinsic linkages between population aging and carbon emissions in Chinese cities from 2000 to 2020 using a two-way fixed effects model. This paper has three main findings. (1) The positive correlation between urban population aging and carbon emissions development is generally low, with coupling coordination degree values of 0.4233, 0.4458, 0.4220, 0.4715, and 0.4665 for each yearly cross-section. (2) For every 1% increase in the population aging rate, carbon emissions decrease by 0.3478% on average. The carbon reduction effect of population aging is significantly greater in low-emissions cities and high-income cities than in other cities. (3) The industrial upgrading (IU) path, energy conservation (EC) path and chain mediation (CM) path account for 72.43%, 7.23% and 20.34%, respectively, of the indirect effects. If the causal link between IU and EC is not considered, the EC effect will be overestimated by 281.16%. The results of the study suggest that properly coping with population aging and reducing carbon emissions are not completely opposed to each other, a conclusion that passes both endogeneity exclusion and robustness check. This paper advocates replacing the one-size-fits-all approach in carbon emissions management and investing more in policy preferences to support carbon emission reduction in both high-emissions and low-income cities. [Display omitted] •The synergistic trends of carbon emissions and population aging are not apparent. •Population aging significantly reduces carbon emissions at the city scale. •Linkage effect of industrial upgrading and energy conservation on carbon emission reduction. •Energy conservation effect of population aging amplified by industrial upgrading. [ABSTRACT FROM AUTHOR]

Enhancing the green economy efficiency (GEE) is crucial for building a sustainable economy. How can the rapidly advancing digital transformation contribute to this process? The paper empirically examines the direct and spatial spillover effects of digital transformation on cities' GEE in China. This study utilizes the National E-commerce Pilot City (NEPC) policy as a quasi-natural experiment of regional digital transformation and employs the staggered difference-in-differences (DID) method with heterogeneous effects. The findings reveal that (i) implementing the NEPC policy significantly increases urban GEE by 2.6%, corresponding to a 16% increase in the mean of GEE. This effect is particularly pronounced in non-resource-based cities and cities with high Internet penetration. (ii) The mechanism test shows that the pilot policy positively affects GEE by promoting green structural transformation, enhancing green innovation, and strengthening public environmental concerns. (iii) The study highlights a positive spatial spillover effect of the NEPC policy on the GEE of nonpilot cities. (iv) The adoption of the NEPC plays a pivotal role in advancing energy use and carbon emission efficiency. This paper expands the existing knowledge on the green development effects of the digital economy while offering valuable policy insights for building an "Inclusive Green Economy". [Display omitted] • The staggered differences-in-differences method is employed to examine the direct and spatial spillover effects of NEPC on cities' GEE in China. • This paper uses NEPC as a quasi-experiment for digital transformation. • NEPC significantly improves green economic efficiency by 2.6%. • Green structural transformation, innovation, and environmental concerns are main channels. • Positive spillover effect of NEPC on green economy efficiency in non-pilot cities. [ABSTRACT FROM AUTHOR]

China's double carbon target aims to improve human well-being and sustainable development. Energy transformation welfare performance (ETWP) is the efficiency of energy transition (ET) in enhancing human well-being. ETWP considers both human well-being and sustainable development. Research on its driving force is helpful in achieving the double carbon goal. Thus, this paper used Logarithmic Mean Divisia Index Model, Fixed Panel Regression Model and Grey Relational Analysis Model to analyze China's ETWP from 2006 to 2022 and predicted ETWP of 31 provinces from 2023 to 2030. The results showed that: (1) ETWP had two rising periods in 2006–2014 and 2015–2022. (2) The government's rationalization policy on energy and environment and technological innovation ability were fundamental driving forces for improving ETWP. (3) There were obvious spatial and temporal distinctions in ETWP, and it would bring out different degrees in most areas. Thus, ET should be promoted by improving the ecological environment and resource utilization efficiency; The importance of the role of scientific and technological innovation and policies should be focused on in promoting ETWP; ET policies based on local developments should be formulated and the energy structure should be changed. Figure Geographical map of ETWP from 2014 to 2022. [Display omitted] • The concept of energy transition welfare performance was defined and accounted for. • The driving factors of energy transition welfare performance were assessed. • The spatial differences of energy transition welfare performance was studied. [ABSTRACT FROM AUTHOR]

In order to deal with the environmental problems such as pollution emissions and climate change, sustainable development in the field of transportation has gradually become a hot topic to all sectors of society. In addition, promoting the green and low-carbon transformation of China's transportation is also an important issue in the new era. Thus, it is particularly important to correctly identify the green effect of high-speed rail. However, the traditional causal reasoning model faces several challenges such as 'dimensional curse' and multicollinearity. Based on the panel data of 283 prefecture-level cities in China from 2003 to 2019, this study uses the double machine learning model to explore the impact of transportation infrastructure upgrading on the efficiency of urban green development in China. The research shows that the upgrading of transportation infrastructure can effectively improve the efficiency of urban green development by 4%. Service industry agglomeration and green innovation are verified as two mediating channels. Moreover, the synthetic difference in difference model is employed to evaluate the regional impact of high-speed rail, and finds that the regional impact of transportation policies often exceeds the impact of individual cities. We further apply the conclusions of this paper to the research at the micro enterprise level. Goodman-Bacon decomposition and a variety of robustness tests confirm the validity of our conclusions. The study's comprehensive empirical analysis not only validates the positive effects of transportation upgrades on green development, but also offers novel insights into the underlying mechanisms and policy implications of transportation upgrading. • We investigate the nexus between transportation facilities and green development. • We employ the double machine learning model to perform quasi-merge regression. • We affirm this positive effect from the micro enterprise level. • We verify the mediation channels of service industry agglomeration and green innovation level. [ABSTRACT FROM AUTHOR]

Numerous studies have discussed the economic impacts of the COVID-19 pandemic in recent years. However, the effectiveness and trade-offs of diverse countermeasures still need to be investigated, particularly under the long-term goal of low-carbon transition, which is crucial for understanding the potential impacts of the future public health emergency (PHE) related economic crisis. Given that China still faces big pressures from the potential PHE and carbon neutrality, this paper assesses the effectiveness of policy instruments in restoring the economy and advancing green development after the PHE using the Dynamic Stochastic General Equilibrium framework. Our findings reveal that the PHE imposes more constraints on the economy because of the decrease in productivity on the supply side and in consumption on the demand side. Compared to the other counterparts, the mixed stimulus can overcome the adverse impacts of the PHE while contributing to carbon reduction. Furthermore, all types of low-carbon policies investigated in this study can contribute to carbon reduction at the expense of economic growth. Meanwhile, the carbon tax realizes the target of reducing emissions with the smallest negative impact on economic growth. Thus, we suggest adopting the carbon tax policy as the most effective low-carbon measure to address uncertainties associated with the PHE. • This study explores pathways for advancing economic recovery and green development after the public health emergency. • We develop a scenario-based dynamic stochastic general equilibrium (DSGE) model. • We characterize public health emergency shocks from a supply and demand perspective. • The model introduces different carbon abatement mechanisms. [ABSTRACT FROM AUTHOR]

Promoting green and low-carbon development has become the consensus of the policymakers and the academic, with green transformation of enterprises being the top priority. This paper adopts the difference-in-difference model to investigate the effect of green credit policy on green transition in China, by utilizing the "Green Credit Guidelines" (2012 Guidelines) policy as a quasi-natural experiment. Using panel data from publicly listed companies in China, an empirical investigation is conducted, we explain the dependent variable from two dimensions: economic performance and environmental performance, leading to the following results. First, the green credit policy affects the economic performance and environmental performance of treated firms positively, and the robust tests confirm the reliability of this primary conclusion. Second, the indirect impact of green credit policy on green transition can be explained through two mediating mechanism channels including internal capacity building and external market attention. In addition, the proposal of "Dual Carbon Targets" makes the impact a slight change. Finally, heterogeneous test also shows that the implementation effect of green credit policy is better in non-state-owned enterprises with high political relevance. These findings are providing valuable insights to promote green transition by designing more effective green credit policies. • We identify the effect of green credit policy on green transition. • We employ multiple econometric models to ensure the robustness. • We provide the empirical evidence for heterogeneity. • We investigate the intermediary channels from two ways. [ABSTRACT FROM AUTHOR]

Rapid developments in environmental infrastructure have contributed to significant improvements in green total factor productivity, but further investigation is required to provide a detailed assessment to understand the policy mechanisms involved. This paper analyzes environmental progress in China through MMQR, CCEMG, and AMG as empirical strategies for 30 provinces in China. Our empirical results reveal that energy optimization through renewable energy is the most effective channel to improve green total factor productivity, though it is not the only available option. Since environmental regulations, infrastructure development, and green technology innovation also directly impact energy efficiency, adopting these within policy channels will positively impact environmental sustainability. Our empirical approach helps suggest novel environmental policy suggestions. In particular, policymakers must introduce structural changes within energy developments to foster renewable energy. Furthermore, China must increase environmental spending to upgrade its energy infrastructure further and solve ecological issues. These insights offer valuable policy guidance for decision-makers in China and globally, aiming to foster economic and environmental sustainability and achieve zero-carbon transition goals. • The current study analyses the role of green factor productivity in zero carbon transition. • We use 30 chinese provincial datasets from 2005 to 2020. • Energy transition is the most effective channel to improve green total factor productivity. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has been proved to be an important engine of green economic development, yet how it will affect the internal structure of green economy is unknown. The aim of this study is to examine the impact and its mechanism of AI on green total factor productivity (GTFP) from the internal-structure perspective, by using provincial panel data of China from 2009 to 2021 and global Malmquist index. The main research results show that: (1) the development of AI contributes to China's GTFP growth. And this effect is more significant in undeveloped areas; (2) AI promotes China's GTFP growth mainly by improving resource allocation efficiency, while it exerts little impact through the paths of technological progress and scale efficiency; (3) the transmission mechanism of AI on GTFP varies greatly among China's three main regions. In the eastern region, AI improves GTFP mainly by both advancing technological progress and improving resource allocation efficiency, while in central region AI contributes to GTFP growth mainly through technological progress. Compared with the eastern and central regions, AI in the western region plays a stronger impact on GTFP through the channel of improving scale efficiency. This study helps to understand the pathways of artificial intelligence affecting the transformation of green economic growth and formulate differentiated regional policies in light of local conditions. • This paper studies the effects of AI on China's GTFP from internal-structural perspective. • GTFP is decomposed into three internal factors by the global Malmquist index. • AI has positive effect on GTFP through different impacts on internal factors. • Improving resource allocation efficiency is the most critical channel of AI on GTFP. • AI plays a more significant role in promoting GTFP in less developed areas. [ABSTRACT FROM AUTHOR]

To address global climate change, achieving carbon peak and carbon neutrality has become a global consensus. However, the means to simultaneously achieve carbon reduction and promote green economic development, particularly in developing countries, require further investigation. This study evaluates the impact of e-commerce on CO 2 emissions. Through an examination of the effects of the National E-Commerce Demonstration City (NEDC) policy from 2006 to 2017, this paper reveals that e-commerce growth facilitated by the NEDC policy resulted in a 7.89% reduction in total CO 2 emissions and a per capita reduction of 1.1146 tons in the pilot cities. Mechanism analysis demonstrates that the upgrading of industrial structure, development of digital finance, and the growth of innovation and entrepreneurship serve as primary pathways for this impact. The robustness of the findings is supported by parallel trend tests, placebo tests, and additional sensitivity analyses. Furthermore, the research reveals that the NEDC policy exhibits a more significant reduction in CO 2 emissions in cities with higher levels of economic development and non-resource-based cities. Welfare analyses show that the NEDC policy has significant socio-economic effects. These findings provide new evidence on the environmental effects of the digital economy and offer insights into achieving carbon neutrality. • The National E-commerce Demonstration Cities (NEDC) policy reduced CO 2 emissions. • Optimizing industrial structure, enhancing digital finance, and promoting innovation and entrepreneurship are mechanisms. • The effect is more pronounced in cities with high economic levels and high resource dependence. • The NEDC policy substantially enhanced social welfare by reducing CO 2 emissions. [ABSTRACT FROM AUTHOR]

Theoretically, agricultural insurance influences farmers' use of pesticides by changing the expected income of agricultural production. Full-cost insurance, with high guarantee and high compensation characteristics, may significantly affect farmers' pesticide use. First, this paper constructs a production function to characterize and compare the marginal incomes of insured and uninsured farmers under risk uncertainty and analyses how insured farmers can increase marginal income by increasing or reducing factor inputs. Considering scale differentiation, it discusses pesticide use strategies different types of farmers may adopt to maximize household utility. Second, using survey data of the pilot counties of full-cost insurance for wheat in Henan Province, China, the simultaneous equation model is used for empirical testing. The results reveal the following: (i) Farmers' insurance participation and pesticide application behaviour are not mutually independent. (ii) For the whole sample, full-cost insurance for wheat has a significant pesticide reduction effect. (iii) However, considering scale differentiation, pesticide application decreases significantly among insured ordinary farmers but does not change significantly among insured large-scale farmers. Third, policy measures are proposed to activate the green development function of agricultural insurance. • Construct a production function and a utility function to conduct mechanism analysis. • Estimate simultaneous equation model based on pilot area household level dataset. • Analyse the effect of full-cost insurance on pesticide input behavior. • Find full-cost insurance significantly reduces the pesticide use of ordinary farmers. • But insignificant effect on the pesticide use of large-scale farmers. [ABSTRACT FROM AUTHOR]

Agricultural and Rural Green Development (ARGD) and economic growth are major challenges prevalent in China, but also in other developing countries. A notable gap in current literature lies in the limited holistic approach to agriculture and rural areas, with scant attention being paid to the spatiotemporal evolution of ARGD and its coordination relationship with economic growth. This paper first offers a theoretical analysis of the interactive relationship between ARGD and economic growth and subsequently examines the policy implementation process in China in this regard. It observes 31 provinces in China from 1997 to 2020 to uncover the spatiotemporal evolution of Agricultural and Rural Green Development Efficiency (ARGDE). Using the coupling coordination degree (CCD) model and the local spatial autocorrelation model, this paper analyses the coordination relationship and spatial correlation between ARGDE and economic growth. The results show that ARGDE in China exhibited a phased growth trend and was greatly affected by policies during 1997–2020. The interregional ARGD produced a hierarchical effect. However, provinces with a higher ARGDE did not necessarily exhibit faster growth, leading to a differential pattern of optimization that involved continuous optimization, phased optimization, and continuous deterioration. Over a long period, ARGDE exhibited a trend of significant upward leaps or jumps. Finally, the CCD between ARGDE and economic growth improved, with a clear trend of high-high agglomeration characteristics that shifted from the eastern and northeastern provinces to the central and western ones. This suggests that promoting "quality agriculture" and "green agriculture" can have practical significance in accelerating the development of ARGD. In the future, it is vital to promote ARGD's transformation while mitigating the risk of degrading the coordinated relationship between ARGD and economic growth. • China's Agricultural and Rural Green Development Efficiency (ARGDE) increased. • Provinces with higher ARGDE did not necessarily have a faster growth rate. • ARGDE exhibits a leapfrogging improvement in a period of 4–5 years. • The coupling coordination degree between ARGDE and economic growth improved. • The High-High cluster have shifted to the central and western regions. [ABSTRACT FROM AUTHOR]

Data center is a very important infrastructure to support the development of information technology, and its development and increment are very remarkable. However, with the rapid and large-scale development of data centers, the problem of energy consumption turns to be also very prominent. Under the background of global carbon peak and carbon neutrality, developing green and low-carbon data centers has become an inevitable trend. This paper reviews and analyzes the policies and their roles in promoting China's green development of data centers in the past 10 years, summarizes the current situation of the implementation of green data center projects in China and gives the changes of PUE limits of data centers under the policy constraints. Application of green technologies is an important measure for energy-saving and low-carbon development of data centers, so encouraging innovation and application of green technologies in data center is also a priority task in relevant policies. This paper points out the green and low-carbon technology system of data centers, further summarizes energy-saving and carbon-reducing technologies in IT equipment, cooling system, power supply and distribution system, lighting, intelligent operation and maintenance, and provides an outlook on the future green development of data centers. • China's green data center policy in recent 10 years has played an important role in promoting the development of green data centers. • Summarizes the status of green data centers under policy guidance. • Provides energy saving and carbon reduction technology path for data centers. • Prospects for the future development of green data centers. [ABSTRACT FROM AUTHOR]

Numerous studies have revealed that developing green technology innovation is extremely important for minimizing haze pollution. However, limited by serious endogenous problems, research rarely focuses on the effect of haze pollution on green technology innovation. Based on a two-stage sequential game model including both production and government departments, this paper mathematically deduced the effect of haze pollution on green technology innovation. Then China's central heating policy is considered a natural experiment in our study to verify whether haze pollution is the key factor affecting the development of green technology innovation. The result that haze pollution significantly inhibits green technology innovation is confirmed, and this negative impact is mainly concentrated on substantive green technology innovation. Robustness tests have been performed, and the conclusion is still valid. Moreover, we find that government behavior can significantly affect their relationship. Specifically, the government's economic growth target will increase the haze pollution's ability to block the development of green technology innovation. However, if the government has a clear environmental target, their negative relationship will weaken. Based on the findings, targeted policy insights are presented in this paper. • Introducing a two-stage sequential game model and mathematically deduced how haze pollution affects green innovation. • China's central heating policy is considered a natural experiment. • The result that haze pollution significantly inhibits green technology innovation is confirmed. • The economic and environmental target constraints affect the impact of haze pollution on green technology innovation. [ABSTRACT FROM AUTHOR]

Resource-based cities generally face the dual pressures of ecological damage and high carbon emissions. Taking the National Sustainable Development Plan for Resource-Based Cities (NSDP) issued in China as a quasi-natural experiment, this paper for the first time, uses the difference-in-difference method to test the coordinated effect of green expansion and carbon reduction brought by NSDP at the county level using rich remote sensing data. The results show that NSDP has significantly promoted the ecological quality improvement and CO 2 emission mitigation in resource-based cities, and the above coordinated benefits mainly occur in energy, mature, declining, northeastern, and municipal resource-based cities. Through the mechanism analysis, we find that NSDP mainly works by promoting the transformation of industry sector to agriculture, animal husbandry, accommodation and catering, finance, and environment management sectors, which are reflected in output, employment, product yield, land type and land transaction area. Further discussion on the tertiary industry suggests that developing tourism, easing financing constraint and strengthening environment regulation, are the key channels to borne fruit in green expansion and carbon reduction. • Analysis of placed-based policy on resource at the county-level. • Coordinated effects of green expansion and carbon reduction are tested. • Key areas of policy effects are identified. • Industrial structure transformation and its related mechanisms are discussed. [ABSTRACT FROM AUTHOR]

The environmental effects of the urban agglomeration planning policy (UAPP) are an exploration by rapidly developing China and a concern for countries seeking development and urban reform around the world. This paper takes the three regional urban agglomerations in the Yellow River Basin (YRB) as the research object and collects the panel data of 106 prefecture-level cities from 2006 to 2019 to study the reduction effects of UAPP on the industrial wastewater discharge (IWD). The empirical results from Difference-in-Differences models indicate that UAPP can significantly inhibit IWD. UAPP reduces IWD by promoting green innovation, and the development of service industries can strengthen this effect. UAPP shows a stronger IWD reduction effect in the northeast YRB than that in the southwest region. Compared to urban agglomerations with a single provincial jurisdiction, UAPP exerts stronger IWD reduction effects on urban agglomerations with multiple jurisdictions. Moreover, there exist spatial spillover effects of UAPP on IWD. These findings provide support and references for urban reform and the development of green cities in countries around the world, especially in developing countries. • Urban agglomeration planning policies can reduce industrial wastewater discharge. • Green innovation is the main intermediary factor. • Service industry development strengthens the discharge reduction effects. • The discharge reduction effects are stronger with multiple jurisdictions. • There exist spatial spillover effects of the discharge reduction effects. [ABSTRACT FROM AUTHOR]

Due to the acceleration of urbanization and industrialization, air pollutants has been increasing, posing a major threat to human health and the ecological environment. During the past period of rapid growth, with the booming development of real estate, the air pollutants brought about by the construction of housing buildings have become more and more serious, especially sulfur dioxide, nitrogen dioxide, and dust, which cast a great threat to human life and seriously jeopardize human health. Compared with the traditional construction of houses, prefabricated buildings construction procedures are reduced, to some extent, can reduce air pollutants. Therefore, this paper takes an empirical perspective to include prefabricated buildings and air pollutants into the same research framework and analyze the inherent logical relationship. We found that prefabricated buildings have a substantial role in mitigating urban air pollution. This conclusion remained solid after various robustness tests including constructing instrumental variables. The effect is observed to be greater in cities above the non-sub-provincial level and those positioned within central regions. The conclusions explore new areas for the green and sustainable development of the construction industry, which in the future will have to fill the requirements of green development in order to survive. Else, perspectives from the construction industry, it provides a realistic solution to economic development and ecological protection, helping to alleviate or resolve the conflict between development and survival. • The air pollution abatement effect of prefabricated buildings is investigated. • The results are robust after controlling the endogenous issue. • The heterogeneity is supported for different samples and air pollutants. [ABSTRACT FROM AUTHOR]

In recent years, China has achieved numerous economic miracles but it has also been plagued by severe air pollution. The frequent hazy weather has severely restricted China's sustainable development. To investigate the nonlinear threshold effect of socio-economic factors on urban haze in China, this study constructs a spatial econometric Smooth Transition Autoregressive Regression (STAR) model based on the STIRPAT theory by using the remote sensing inversion PM 2.5 data of 223 prefecture-level and above cities in China mainland during 2004–2016. In this study, the ARAR-STAR model is estimated by quasi-maximum likelihood estimation, and the accuracy of parameter estimation is verified by Monte Carlo simulation, which proves that the ARAR-STAR model constructed in this study is robust. It is concluded that: there is a complex spatial nonlinear relationship between socio-economic factors such as economic development level, population density, advanced industrial structure, energy consumption, opening-up, and haze pollution. The effect of socio-economic factors on haze emission reduction under the spatial influence has complex heterogeneity with the smooth transition between high and low regimes with economic development. The ARAR-STAR model constructed in this paper, which has both individual fixed effects and time fixed effects, expands the form of existing spatial panel nonlinear models and enriches and implements the application of spatial panel smooth transfer threshold models in the environmental field. Not only can it provide policy recommendations for China to achieve "coordinated efficiency in pollution reduction and carbon reduction" as soon as possible, but it also contributes to China's plan to address global climate change and promote global sustainable development. • Using spatial panel smooth transition autoregressive regression model for 2004–2016, we revisit the nonlinear effects of socio-economic factors on urban haze in China. • The ARAR-STAR model is estimated by quasi-maximum likelihood estimation. • We employ Monte Carlo simulation to obtain robust results. • The effect of population density, industrial structure, energy consumption, opening-up on haze emission has heterogeneity with the smooth transition between high and low regimes with economic development. [ABSTRACT FROM AUTHOR]

Based on the unique perspective of local environmental regulations promulgated in Chinese prefecture-level cities from 2000 to 2018, this paper examines the impact of urban environmental legislation on green total factor energy efficiency (GTFEE). The results show that implementing environmental legislation significantly improves local GTFEE , with comprehensive protection regulations contributing to local energy efficiency improvements, while the impact of pollution prevention regulations is insignificant. This conclusion remains robust to multiple scenarios. Potential mechanisms through which environmental legislation can guide urban green transition include the industrial upgrading effect represented by "clean industry development" and "polluting industry exit", as well as the technical innovation effect achieved through "new technology generation" and "old technology upgrading". Furthermore, environmental legislation with a higher degree of regulatory effectiveness has a greater potential for energy saving. Environmental legislation has a more significant impact on improving GTFEE in cities in non-old industrial bases, with less frequent turnover of officials, and in central and western regions in China. This study evaluates the positive impact of urban environmental legislation on GTFEE , aiming to advancing the rule of law in local environmental pollution governance and thereby promote urban green transition. • Use a Difference-in-Differences model to explore the effect of urban environmental legislation. • Environmental legislation guides urban green transition development. • The impact of heterogeneous urban environmental regulations on green transition development. • Industrial upgrading and Technical innovation have positive mediating roles. • Environmental legislation policy has city attributes, official turnover and location heterogeneity. [ABSTRACT FROM AUTHOR]

Green power trading is an institutional innovation proposed by China to promote green and sustainable development. This policy aims to relieve the serious debt pressure of renewable energy generation enterprises, thus laying the foundation for achieving carbon reduction targets. This paper empirically examines the role of green power trading by constructing the difference-in-differences (DID) model. Our findings indicate that green power trading significantly reduces the debt levels of policy-covered generation enterprises. This effect is more pronounced for state-owned enterprises, companies with better ESG performance, companies in regions with higher degree of marketization and companies specializing in renewable energy power generation. Further research discusses the impact mechanism of green power trading in terms of external and internal environmental channels. We find that a strong green development atmosphere, especially the external atmosphere, will significantly reinforce the weakening effect of green power trading on corporate debt. Our research provides empirical evidence for the success of green power trading policy in its pilot phase. • Green power trading significantly alleviates the policy-covered firms' debt burden. • The role of green power trading presents heterogeneity in enterprise characteristics. • A better regional environment for green growth can stimulate the effect of green power trading. [ABSTRACT FROM AUTHOR]

Policies directly or indirectly influence the development of industrial symbiosis (IS). Quantitatively analyzing the effects of policies on IS at a national level is necessary, but current research has lagged. Focusing on the symbiotic system that includes the thermal power industry, cement industry, iron and steel industry, and social sector in China, this paper assesses the efficacy of policies on this nationwide IS system between 2015 and 2022. A policy influence framework is proposed, combining a cost-benefit analysis, agent-based model, and comparative analysis. Results show: (1) the symbiosis probability of the nationwide IS system experiences a fluctuating increase. The maximum increments of the symbiosis probability are 5%, and the resulting environmental benefits are equivalent to an emission reduction of 6.99 Mt from blast furnace slag, 20.97 Mt from iron mine tailing, 36.02 Mt from household waste, 25.01 Mt from steel slag, and 22.95 Mt from fly ash. However, the stimulation effects of policies vary across different subsystems. (2) Thermal power-chemical subsystems, thermal power-environmental protection subsystems, iron and steel-environmental protection subsystems, and social sector-cement subsystems need policy support in the future. (3) Approximately 50% of fields in this nationwide IS system is insensitive to current policies; policy approaches should shift from economic stimulation to symbiotic guidance. This paper fills the research gap by quantitatively studying the IS policy efficacy from a national level. The findings can contribute to the improvement of the Chinese IS policy system. [Display omitted] • Quantitatively analyzing the effects of policy on industrial symbiosis at a national level. • Policy-sponsored incentive effects vary across different types of waste and subsystems. • Half of the symbiotic utilization fields are insensitive to current policy. • The policy should shift from economic stimulation to symbiotic utilization guidance. [ABSTRACT FROM AUTHOR]

This study analyzed the theoretical mechanism of the carbon emission effect embodied in the Sino-USA manufacturing trade. We constructed a trade and carbon emission input-output model for 16 manufacturing sub-sectors in China and the USA from 2000 to 2018. A comprehensive empirical test of the systematic emission reduction mechanism was conducted. There were four main findings: (1) indirect and direct carbon emissions indicators can comprehensively analyze the link between production and demand across sectors; (2) indirect carbon emissions are higher than direct carbon emissions in half of the sectors in both China and the USA, and other sectors bear part of the carbon emissions for these sectors; (3) compared to 2000, the change in net exports of both countries is the main reason for the change in indirect carbon emissions, while the change in net exports of intermediate goods is the main reason for the change in direct carbon emissions; and (4) the Sino-USA trade surplus comes at the expense of China's environmental losses, while the USA obtains environmental benefits. Overall, the theoretical analytical framework not only comprehensively considers the interlinkages between production and demand across sectors but also provides a more reasonable evaluation of the environmental effects of Sino-USA trade. Additionally, this study provides a solid theoretical and empirical basis for China to achieve its dual-cycle and dual-carbon goals, thus promoting the rapid transformation of China's economy toward green and high-quality development. [Display omitted] • The carbon emission effect mechanisms of Sino-US manufacturing trade are analyzed. • Carbon emissions indicators reveal production-demand linkages across sectors. • The economic and environmental gains and losses of Sino-USA trade are evaluated. • Sino-USA trade harmed China's environment and benefited USA. • This paper identifies the key path to cut China's manufacturing CO2. [ABSTRACT FROM AUTHOR]

Environmental taxation is an essential tool employed by governments to compel polluting enterprises to undergo green transformation, thereby achieving sustainable development. This paper uses Differences-in-Differences (DID) approach to assess the impact of the China's environmental tax law on the ESG performance of heavily polluting industries. Furthermore, it examines the moderating effect of stakeholder behavior on the relationship between the environmental tax law and the ESG performance of firms. The research findings indicate that the environmental tax law significantly enhances the ESG performance of heavy polluting enterprises by improving the environmental factor. However, heterogeneity is observed based on ownership characteristics and regional variations. Auditors, mass media and corporate ethical behavior exhibit a significant positive moderating effect on the causal relationship between the environmental tax law and the ESG performance of heavily polluting enterprises. This study contributes to a clearer understanding of the intrinsic relationship between environmental tax laws and ESG performance, and offers insights from the perspective of stakeholder behavior for formulating a path towards sustainable development in the country, thereby providing policy lessons for numerous developing countries worldwide. • Matching data of Chinese listed companies with Bloomberg ESG scores. • Environmental tax law boosts ESG in polluters (E-focused impact). • Auditors reinforce tax law's ESG effect via opinions. • Media shapes ESG by affecting social perception (S factor). • Ethics matter: corruption risks inflate ESG in targeted firms. [ABSTRACT FROM AUTHOR]

The main factor behind green economic development is green technology innovation (GTI). Environmental regulation and green finance (GF), as important ways to promote ecological civilization construction, run through the entire procedure of GTI. The purpose of this study is to investigate the influence of heterogeneous environmental regulation on GTI and the moderating effect of GF on GTI from both theoretical and empirical perspectives, to provide useful ideas for China's economic reform path selection and environmental governance system optimization. This paper uses information from 30 provinces between 2002 and 2019, and a bidirectional fixed model was constructed. The results show that: First, regulatory environmental regulation (ER 1), legal environmental regulation (ER 2), and economic environmental regulation (ER 3) all have greatly boosted the degree of GTI in each province. Second, GF acts as a highly effective moderator between heterogeneous environmental regulation and GTI. Finally, this article investigates how GF can act as a moderator in various circumstances. The beneficial moderating effect of it is found to be more pronounced in inland areas, areas with weak spending on research and development, and areas with high energy consumption. These research results provide valuable references for accelerating the green development process in China. • Constructs environmental regulation indexes from regulatory, legal, and economic. • Heterogeneous environmental regulation promotes green technology innovation. • Green finance plays a positive moderating role. • The moderating effect of green finance varies greatly in different regions. [ABSTRACT FROM AUTHOR]

Accounting for the ecosystem service values (ESVs) and discussing the relationship between the ESVs and economic development can help achieve sustainable ecological development. Therefore, this paper evaluates the county-level ESVs of various land types in China, and depicts the distribution of ESVs in various urban agglomerations. In addition, the nonlinear relationship between ESVs and economic development is revealed. The main findings are as follows: (1) From 2000 to 2018, the ESVs in China decreased, and the decline rate of ESVs in urban agglomerations is much higher than that of China as a whole. (2) The decline rate of ESVs in core cities is much higher than in urban agglomerations, and the decline rate of ESVs is higher in areas close to core cities and lower in areas far from core cities. (3) The ecological Kuznets curve of China has a positive "U" shape, and the ecological Kuznets curve of urban agglomerations has an "N" shape; the ecological Kuznets curve of core cities has a positive "U" shape, while the ESVs of other cities decreases monotonically with the increase of the economic level. • This paper fills the data gap of ESVs at the county level in China. • The reduction rate of ESV in urban agglomeration is larger than the national level. • The reduction rates of ESV in core cities are larger than the urban agglomerations. • The ecological Kuznets curve is "U"-shaped in China. • Non-urban agglomeration cities are still left to the inflection point. [ABSTRACT FROM AUTHOR]

Digital technology is an effective way to realize the carbon neutrality target in China. Therefore, based on panel data at the city level in China from 2006 to 2016, we take the e-commerce pilot policy as a quasi-natural experiment, using the staggered difference-in-differences (DID) method to explore the effect of digital technology development on carbon emissions and its transmission mechanism. The conclusion of this paper shows that (ⅰ) the e-commerce pilot policy has significantly reduced carbon emissions. After a series of robustness tests, this empirical conclusion is still valid. (ⅱ) The inhibitory effect of different waves of e-commerce pilot cities on carbon emissions sequentially decreases. The e-commerce pilot policy has a greater effect on reducing carbon emissions in non-old industrial based cities and non-resource-based cities. (ⅲ) Implementing the e-commerce pilot city policy mainly reduces urban carbon emissions by optimizing resource allocation, reducing energy consumption and upgrading the industrial structure. (ⅳ) In addition, implementing the e-commerce pilot city policy has a significant positive carbon-reducing linkage effect with the carbon trading pilot policy and the low-carbon city pilot policy. The findings of this paper provide empirical evidence for carbon emission reduction, which has implications for upgrading urban construction patterns and promoting green urban development. • The construction of national e-commerce pilot cities has significantly reduced the carbon emission of cities. • The inhibitory effect of different batches of e-commerce pilot cities on carbon emissions sequentially decreases. • Playing more significant effect in non-old industrial based cities and non-resource-based cities. • Reducing urban carbon emissions by optimizing resource allocation and reducing energy consumption. • Having a significant positive carbon-reducing linkage effect with carbon emissions mitigation policies. [ABSTRACT FROM AUTHOR]

This paper examines the drivers of distribution of pollution-intensive enterprises (PIEs) at the intraurban level that are less studied. Employing the complete spatial database of PIEs obtained from the National Economic Census of 2004, 2008, and 2013, the paper analyses the spatial restructuring of PIEs within Foshan, China, a typical manufacturing city in transition. We find that the changing role of environmental regulation induced by the environmental policy regime transformation has resulted in the siting strategy shift of PIEs, and both the 'Pollution Haven Hypothesis' and the 'Porter Hypothesis' have been overly simplified in the research conducted at the regional or global level. Based on the Foshan case, we further conceptualize the pattern of spatial restructuring of PIEs that would help to understand the fast green economy transition taking place in Chinese cities, followed by some policy and research implications. • The relocation and drivers of polluting firms at a local level are studied. • The environmental policy regime shift leads to the siting strategy shift of firms. • Polluting firms initially seek a pollution haven before 2008. • New firms after 2008 site in areas with strict environmental regulation. • The local government motivation is more important in the Chinese context. [ABSTRACT FROM AUTHOR]

Green technology innovation (GTI) is an effective way to promote the green development of economy, and government environmental regulations are an important means to encourage enterprises to carry out GTI. Taking Chinese A-share listed enterprises from 2010 to 2019 as samples, this paper divides environmental regulations into three categories: command-based environmental regulation (ER 1), market-based environmental regulation (ER 2) and voluntary environmental regulation (ER 3), studies their impact on enterprise GTI, and discusses the joint effect of enterprise research and development (R&D) investment and government support from the perspective of internal and external linkage of enterprises. In addition, this paper also analyzes the compound effect and time effect of environmental regulation. The research conclusions are as follows: (1) From the perspective of policy types, both ER 1 and ER 2 could stimulate enterprises to carry out GTI, and the promotion effect of green utility model patents is slightly higher than that of green invention patents. ER 3 inhibits enterprise GTI. In addition, this paper finds that the effect of three environmental regulations acting at the same time is greater than that of one of them. (2) The mechanism analysis shows that the R&D investment of enterprise positively could moderate the relationship between ER 2 and green invention at the significance level of 5%, positively moderate the relationship between ER 2 and green utility model patent at the significance level of 1%, and negatively moderate the relationship between ER 3 and green utility model patent at the significance level of 5%. The government support could moderate the relationship between environmental regulation and green utility model patents at the significance level of 5% and 10%. (3) The effect analysis shows that the transformation rate of GTI in China needs to be improved. The three environmental regulations could have an effect on enterprise GTI in a short period, and ER 1 has the fastest effect. (4) Considering the differences in the level of economic development and resource endowments in various regions of China, this paper classifies the sample enterprises and finds that the impact of environmental regulation on enterprise GTI is heterogeneous in terms of location, ownership nature, factor density and industry type. The research results provide the important reference for the formulation and implementation of environmental regulation policies according to local conditions. • ER 1 and ER 2 could stimulate enterprise GTI. • The union effect of ER 1 , ER 2 , and ER 3 is better than one of them. • R&D positively moderates the relationship between ER 2 and GTI. • ER 1 has the fastest effect on GTI in three kinds of environmental regulations. • The effect of ER on GTI shows heterogeneity for different enterprise features. [ABSTRACT FROM AUTHOR]

Abstract Dietary-related risks rank top among all the health risks in many countries. The 2nd United Nations Sustainable Development Goal aims to end hunger, achieve food security and improved nutrition and promote sustainable agriculture. Yet whether improving nutritional quality also benefits the environment is still under-explored, particularly for developing countries. China is an interesting and important case because of its rapidly changing dietary patterns distinct from the western countries studied in the literature, sub-national level heterogeneity, socio-economic characteristics and lifestyles, as well as its considerable population. This paper evaluates greenhouse gas (GHG) emissions, water consumption, and land appropriation resulting from shifting the Chinese population to healthy diets. We quantify the environmental impacts of individual diets using the latest available data of China Health and Nutrition Survey (2011), and compare them with the environmental impacts of suggested healthy dietary patterns in accordance with the 2016 Chinese Dietary Guidelines. If all Chinese would follow healthy diets rather than their current diets revealed in the survey, GHG emissions, water consumption, and land occupation would increase by 7.5% (63.9 Mt CO 2 e annually), 53.5% (510 billion m3), and 54.2% (1256 billion m2), respectively. Urban and high-income groups have higher diet-related environmental impacts but could achieve less additional environmental impacts when moving to healthier diets. These findings indicate an expense of increased GHG emissions, and consumption of water and land resources in improving health. They also highlight the need to focus on the effects of improved economic conditions and urbanization in reconciling environmental impacts and human nutritional adequacy. Highlights • Shifting to healthy diets in China leads to 7.5% lower GHG emissions. • Water consumption and land use increase by 53.5% and 54.2% because of the shift. • Urban dwellers and high-income groups deliver larger reductions in GHG emissions. • Increase of water consumption and land use is also smaller for these groups. [ABSTRACT FROM AUTHOR]

This paper studies the impact of electricity price reduction policy on the economic activities and carbon emissions of different industries. Since 2018, the Chinese government has advocated reducing electricity price for industrial customers in order to alleviate the non-tax burden on businesses. Using monthly electricity consumption and user data from 2016 to 2019, we find that the electricity price reduction has significantly increased the industrial electricity consumption and users. Heterogeneity analyses show that the effect is greater in heavy polluted industries and industries in low and medium GDP regions. The results of threshold impact analysis show that the threshold value of heavy pollution industries was lower than that of general industry and commerce, while heavy pollution industries are more sensitive to electricity prices than general industries. Moreover, the reduction of electricity prices results in a higher percentage of carbon emissions growth in heavy pollution industries. Our result can also help the policymakers access the costs and benefits of electricity price reduction for industrial customers more accurately. • Electricity price reduction contributes to increase industrial activities and users. • The effect on high polluted industries is larger than that of general industries. • The promotion effect is better in medium and low GDP regions. • A non-linear relationship exists between electricity price and consumption. • The electricity reduction policy causes carbon leakage risk among industries. [ABSTRACT FROM AUTHOR]

The evaluation of regional water resource carrying capacity has been repeatedly conducted to provide a scientific basis for the local water resource management and the sustainable development, in particular in the water-limited regions. However, the definition of regional water resource carrying capacity and its evaluation method are still arguable. Through a case study of Inner Mongolia, located in the arid and semi-arid northern China, this paper developed an improved method to calculate regional water resource carrying capacity by the combination of the water supply-demand analysis and the S-shaped curve threshold analysis. The spatial and temporal patterns of the regional water resource carrying capacity in Inner Mongolia during 2000–2019 was evaluated at three scales, namely the province scale, the basin scale and the city scale. The results showed that the average regional water resource carrying capacity of the whole province was 0.25 (the full mark is 1.00); at the basin scale, the Yellow River Basin had the lowest regional water resource carrying capacity (0.17) among all the basins, showing that the utilization of the water resources was unreasonable; at the city scale, the average regional water resource carrying capacities in Hulunbuir and Xilingol were both over 0.25, while those in Alxa, BayanNur and Wuhai were below 0.1; Hulunbuir had 25.48 billion m3 water surplus, while BayanNur suffered from an average water deficit of 4.51 billion m3 from 2000 to 2019. This paper has provided a reasonable way to measure the regional water resource carrying capacity using an improved method by incorporating S-shaped curve threshold analysis, which may have a wider application for the clustering and optimization of regional water management. In addition, the spatial and temporal patterns of regional water carrying capacity are beneficial for policymakers in the implementation of the effective water usage. • Regional water resource carrying capacity is evaluated by water supply-demand analysis and temporal threshold analysis. • The evaluation method is improved by considering temporal threshold at different regional scales. • "S"-shaped logistic curves are used to simulate the temporal pattern of water resource carrying capacity. • Spatial and temporal water resource carrying capacity analysis benefits policymakers. [ABSTRACT FROM AUTHOR]

The "Air Pollution Prevention and Control Action Plan" is regarded as China's war against air pollution, which is also noted as China's Clean Air Action (CAA policy). Although abundant studies have focused on the impact of CAA policy on social activities, such as air quality, pollutants emission, and economic output, limited studies explore its impact on enterprise competitiveness from a more micro perspective. Improving total factor productivity (TFP) is essential to achieve economic efficiency and sustainable development. Identifying the impact and influence mechanism of the CAA policy on TFP is important for China to realize the coordinated development of environment and economy and promote high-quality economic development. Based on the difference-in-differences model, this paper evaluates the impact of the CAA policy on enterprise productivity. The empirical analysis shows that there is a significantly negative effect from the CAA policy to the TFP of polluting enterprises, indicating that the CAA policy has decreased enterprise productivity. Our finding is robust, after conducting several robustness tests, such as replacing different dependent indicators, adopting different policy measurement variables, considering other policy interventions and using propensity score matching. Besides, this paper also discusses the possible heterogeneities. This paper adds additional empirical evidence to understand the relationship between air pollution control and enterprise competitiveness. The conclusions of this paper have important practical significance for China to further promote air pollution control and perfect the environmental control system. • We analyze the impact of China's Clean Air Action on enterprise competitiveness. • There is a negative effect from the Clean Air Action policy to enterprise total factor productivity. • Possible heterogeneities have been discussed from several aspects. • This paper adds additional empirical evidence to understand China's Clean Air Action. [ABSTRACT FROM AUTHOR]

The relationship between industrial structure (IS) and eco-efficiency (EE) is intricate with mutual influence and constraint. Exploring the coordinated relationship between IS and EE is beneficial to the sustainable development of ecologically fragile areas. This paper estimates and analyses the levels of EE and IS in 39 prefecture-level cities of the Loess Plateau, discussing the comprehensive and coordinated development levels between industrial structure rationalization (ISR) and EE, industrial structure advancement (ISA) and EE based on the coupling coordination degree model (CCDM). The results showed that the comprehensive development of the Loess Plateau has rough and imbalanced issues. The EE and IS are developing at a relatively low level, and the spatial distribution shows the development trend of high in the east and down in the west. The CCD of ISA and EE performs better than that of ISR and EE, but neither has reached the collaborative coupling state. The poor CCD score in the Loess Plateau is primarily attributable to its relatively backward degree of integrated EE and IS. The results are expected to provide decision-making support for EE improvement and industrial restructuring in the Loess Plateau and other ecologically fragile areas. • Industrial structure rationalization and industrial structure advancement are quantified. • ISA performs better than ISR when coupling with EE. • Comprehensive coupling of all cities is at basic coordination level and below. • The backward level of EE and IS is the main reason for the low CCD score of the Loess Plateau. [ABSTRACT FROM AUTHOR]

While the Paris Agreement and 2030 Agenda for Sustainable Development are the two most important global governance agendas, in practice they have been implemented in isolation. This calls for the need to focus on the potential policy synergies between emission reduction policies and Sustainable Development Goals (SDGs). This paper therefore aims to explore whether the emissions trading scheme (ETS) policy—one of the most effective ways to fulfill the target determined by the Paris Agreement, would facilitate reducing income inequality (SDG10). By combining a difference-in-difference estimation and propensity score matching technique based on a balanced panel dataset for 31 Chinese provinces from 2010 to 2018, we quantify the impact of ETS policy on income inequality between urban and rural areas in China. The results demonstrate that compared with the regions without ETS, the Theil index between rural and urban areas with ETS decreased by 0.018 on average in China. In addition, the ETS would perform better in regions with low urbanization level and high coal dependence. Hence it is vital to speed up the establishment of a unified ETS market in China. This is particularly true for inner underdeveloped regions in China. These findings proven to be robust according to a series of tests challenge the view that SDG 10 has the least relevance to climate action and suggest rethinking the effectiveness and applicability of ETS. Therefore, our research can not only serve as a reference for the development of ETS in China and elsewhere, but also inform decision makers who are seeking for policy synergies between the Paris Agreement and SDGs. [Display omitted] • We quantify for the first time the impact of ETS on urban-rural income inequality. • We make joint use of DID model and PSM technique with data for 31 Chinese provinces. • Overall the ETS exerts a mitigation effect of 0.009 on urban-rural income inequality. • The ETS performs better in low urbanization level and high coal-dependent pilots. • The ETS generates policy synergies between the Paris Agreement and SDG 10. [ABSTRACT FROM AUTHOR]

The Belt and Road Initiative (BRI), which was first put forward by China in late 2013, has made a significant contribution to international economic activities and inevitably reshaped the pattern of carbon dioxide (CO 2) emissions. Considering the spatial spillover effects of CO 2 emissions among countries, this paper employs spatial difference-in-differences models in order to investigate the BRI's effects on total CO 2 emissions (TCE), per capita CO 2 emissions (PCE), and CO 2 emissions intensity (CEI), respectively. The results of global Moran's I index prove the existence of spatial correlations of CO 2 emissions. The BRI's effect on TCE is significantly positive, while the effects on PCE and CEI are significantly negative, suggesting the BRI has aggravated the amount of CO 2 emissions in the partner countries, but has promoted green development by decreasing PCE and CEI. Besides, the spatial effects of control variables on CO 2 emissions are also evaluated. Some tests, including placebo test and employing alternative weight matrices, are further conducted to verify the robustness of the model. The findings indicate the BRI has facilitated green economic growth, by eventually achieving emission reduction targets in the partner countries. [Display omitted] • The spatial interactions between the BRI and CO 2 emissions are investigated. • There are strong spatial autocorrelations of CO 2 emissions from 2008 to 2018. • The BRI's effect on TCE is positive, while the effects on PCE and CEI are negative. • The direct effects of determinants are far larger than their indirect effects. [ABSTRACT FROM AUTHOR]

The digital economy has demonstrated strong resilience and great potential, under the interwoven influence of the global pandemic and severe environmental concerns across the world. Therefore, there is a need to focus on the value of green economic growth in the digital economy. This paper constructs an evaluation index system and adopts the SEEA (System of Environmental and Economic Accounting) method to measure the digitalization level (Digi) and green economy growth level (GEG) of China. The internal mechanism and linear relationship between digitalization and green economy growth are examined based on the panel data from 2013 to 2019. Moreover, this study explores the spatial spillover effect. The major study findings are as follows: (1) Digitalization and green economy growth represent a steady growth trend, and the former as a whole significantly promotes the latter, with a marginal effect of 1.648. (2) The mechanism analysis indicates the intermediary effects' size of three crucial intermediaries: green technology innovation > advanced industrial structure > the rationalization of industrial structure. (3) Both the "local effect" (0.556; 0.574) and "neighboring effect" (1.382; 1.415) of digitalization on green economy growth are positive under the two weight matrices and display "simultaneous resonance" characteristics based on the spatial perspective. (4) There exists obvious regional spatial heterogeneity and resource endowment heterogeneity. Finally, this study put forward corresponding policy implications, such as construction of new digital infrastructures and guiding green-energy consumption. • The green economic growth (GEG) level is measured by the SEEA method. • The linear relationship shows digitalization (Digi) can significantly promote GEG. • The spatial effect of Digi on GEG shows "positive simultaneous resonance". • Three crucial intermedia's effects are compared. • The heterogeneous impact is explored from different dimensions. [ABSTRACT FROM AUTHOR]

Under the strict control measures, China has achieved phased victory in combating with the COVID-19, production activities have gradually returned to normal. This paper examined whether air pollution was rebounded or realized green recovery in the post-COVID-19 era with a dataset of weather normalized pollutant concentrations using difference-in-differences models. Results showed that air pollution experienced a significant decline due to the wide range of control measures. With entering the post-epidemic period, air pollution raised due to the orderly production resumption. Specifically, production resumption increased the PM 2.5 concentrations of lockdown cities and non-lockdown cities by 43.2% (22.3 μg/m3) and 35.9% (17.3 μg/m3) compared with that in the period of COVID-19 breakout. Although the economic activities of China have been gradually recovered, PM 2.5 concentrations were 8.8–11.2 μg/m3 lower than the level of pre-epidemic period. In addition, the environmental effects varied across cities. With the process of production resumption, the PM 2.5 concentrations of cities with higher GDP, higher secondary industry output, more private cars and higher export volume rebounded less. Most developed cities realized green recovery by economy growth and air quality improvement, such as Beijing and Shanghai. While cities with heavy industry reflected pollution rebound with slow economy recovery, such as Shenyang and Harbin. Understanding the environmental effects of control measure and production resumption can provide crucial information for developing epidemic recovery policies and dealing with pollution issues for both China and other countries. • Production resumption increased PM 2.5 concentrations in the post-COVID-19 era. • PM 2.5 concentrations in the post-COVID-19 era were lower than that during the period without epidemic. • PM 2.5 concentrations of cities with higher GDP, secondary industry output, and export volume rebounded less. [ABSTRACT FROM AUTHOR]

In order to control air pollution better, China has adopted the central environmental inspection mechanism. This paper adopts the data of 290 prefecture-level cities in China to evaluate the air improvement effect of the central environmental inspection mechanism. Firstly, based on the Mechanism Design Theory and Principal-agent Theory, this paper analyzes the government incentive measures and effort levels under the conditions of information as symmetry and asymmetry. Then, this paper introduces Regression Discontinuity Design (RDD) Model to evaluate the air improvement effect of the central environmental inspection mechanism. Lastly, this paper explores the sustainability of the environmental inspection mechanism through the regression analysis of environmental inspection revisit. The results show that: under the condition of information symmetry, the central government can make the local governments reach the Pareto optimal effort level through the design of incentive contract. In a short period of time, the first round of environmental inspection and environmental inspection revisit have significantly improved air quality, and significantly reduced PM2.5 and PM10 and other major single pollutants. In general, this system has had an immediate effect. The environmental inspection revisit has also significantly reduced the concentrations of AQI, PM2.5 and PM10. Compared with the first round of environmental inspection and environmental inspection revisit, the latter has a higher level of air pollution reduction and better effect. The sustainability of the improvement effect of environmental inspection mechanism is questioned. It is of great significance to evaluate the actual effect of the central environmental inspection system and tap the unique experience of "Chinese style" to explore how to control air pollution and promote green development. • This paper explored the effect of central environmental inspection. • The Regression Discontinuity Design (RDD) Model was used in this paper. • The sustainability of the environmental inspection mechanism was explored. [ABSTRACT FROM AUTHOR]

Green innovation activities of enterprises often fall into the dilemma of financing constraints. Hence, it is urgent that the financial system develops and becomes innovative, especially for a developing country like China. Existing literature mainly explores the influencing factors of green innovation from the environmental regulation, economic growth and government subsidies perspective. However, few papers critically study how digital finance influences green innovations. To explore the internal influencing mechanism of digital finance on the quantity and quality of green technology innovation, panel data of 271 prefecture-level cities from 2011 to 2019 in China is used. Based on theoretical analysis and empirical research, we get the following conclusions. First, digital finance can improve the quantity and quality of green technological innovation, which has become a significant driving force for green innovations in China. The results are still robust after the endogeneity tests. Second, the results of heterogeneous analysis indicate that the different dimensions of digital finance can improve green innovations. They include breadth of coverage, depth of use, and degree of digitization. The positive effect of digital finance is most substantial in eastern cities, followed by central cities, and weakest in western cities. Third, digital finance indirectly improves green innovation mainly by alleviating financing constraints. Our empirical results provide policy enlightenment for realizing the coordination of China's urban digital transformation and green economic development. • The effect of digital finance on the quantity and quality of green innovation is explored based on the actual background in China. • Digital finance has become a significant driving force for green innovation in China. • The different dimensions of digital finance can improve green innovations. • Digital finance plays a positive role in green technology innovation mainly by alleviating financing constraints. [ABSTRACT FROM AUTHOR]

Chinese officials play an important role in air pollution control. This paper used a sample of 282 prefecture-level cities in China to discuss the impact of promotion incentives of officials on air pollution from the perspectives of heterogeneity, mechanism and spatial effects. We found that the promotion incentives of officials reduced air pollution, and GDP per capita had positive moderating effects. The effects of promotion incentives were more significant in cities with less air pollution, in the central and western regions, for officials with higher education levels, or years after 2007. The promotion incentives could promote the development of green finance and green technology innovation, both of which were conducive to mitigating air pollution. Using the dynamic spatial Durbin model (DSDM), we found that the promotion incentives had negative spatial spillover effects. The promotion incentives in surrounding cities reduced air pollution in the local city; however, it had only short-run effects and no long-run effects. • The promotion incentives of officials could significantly reduce air pollution. • The effects of promotion incentives on air pollution have heterogeneity. • Green finance and green technology innovation have positive mediating effects. • Promotion incentives have negative spatial spillover effects in the short-run and no long-run effects. [ABSTRACT FROM AUTHOR]

Protecting our environment while maintaining economic growth, requires a delicate balance among interlinked sustainable development policies. In this paper, we examine China's economic industries, including a high-resolution of the country's electricity sector during 2020–2030, using a multi-objective optimization model based on Input-Output analysis. This model, investigates the synergy and trade-offs of sustainable development goals in maximizing employment and GDP while minimizing energy and water consumption, CO 2 emissions, and five major pollutants to advance a sustainable industrial structure adjustment pathway for China. Our results reveal that there exists both synergies and trade-offs among multiple objectives, e.g., synergy among goals of minimizing air pollutant emissions and trade-offs between minimizing energy consumption and maximizing employment. Through the planned industrial restructuring period (2020–2030), the GDP, employment, carbon emission, and energy consumption will increase respectively by, 96.1%, 7.2%, 16.8%, 16.8%, and 6.3%, while pollutant emissions would decrease. Moreover, our research indicates that energy and water conservation should be prioritized in industrial structure adjustment strategies and policies. Our model demonstrates how the synergies and trade-offs among multiple policy targets can empower policy-makers, especially in developing nations, to make more informed and optimized industrial structure adjustment policies for sustainable development. • A multi-objective optimization model based on the Input-Output model is proposed. • Synergies and trade-offs among policy targets are examined. • The structural adjustment of economic sectors with fine-resolution power sectors is investigated. • The compromise solution and the most recommended policy priority are explored. [ABSTRACT FROM AUTHOR]

Surface water provides a basic resource for life and is vital for maintaining climate stability, hydrological cycles, and natural ecosystems. Lakes, which are an important part of surface water, play a crucial role in sustaining the hydrological balance and maintaining a healthy environment. The onset of climate change and anthropogenic disturbance on lakes and the environment, however, have drastically changed the morphological characteristics of lakes, leading to undesirable negative effects on the ecological environment. In recent years, many lakes around the world are undergoing phenomenal changes due to climate change and human activities. These changes have greatly affected the availability of freshwater resources, leading to a series of regional ecological and environmental problems, which constrain the regional sustainable development. Changes in lake parameters often indicate environmental change. Therefore, it is of great practical significance to extract lake water information to reflect the water quantity changes in the lake, understand its implications, and come up with timely solutions. This paper summarizes the existing research methods of lake water estimation in China and abroad and draws the following conclusions: (1) In the study of lake water volume estimation, it can be roughly divided into with topographic data and without topographic data. The most representative methods are the estimation methods based on topographic parameters and the Triangle Irregular Network (TIN) model method. In the actual research process, most of the scarce data that are difficult to obtain are lake topographic data, prompting researchers to constantly put forward new methods; (2) From the perspective of research methods, estimation of lake water volume can be divided into remote sensing-based and non-remote sensing-based research. With the continuous improvement of scientific and technological levels, current geographical researchers tend to use remote sensing to monitor lake water volume; (3) Although researchers have proposed a series of models for lake water volume estimation for the long-time process. However, many models are based on the ideal static estimation process, which poses challenges for researchers to make a long-term dynamic estimation of lake storage capacity in the future. At the same time, the accuracy of the model can be a problem that researchers need to work out solutions in the future. Finally, combined with the current development of remote sensing technology, the application potential and the future prospect of remote sensing in lake monitoring are briefly discussed. • Lake water volume estimation, it can roughly be divided into with topographic data and without topographic data. • Estimation of lake water volume can be divided into remote sensing-based and non-remote sensing research. • The application potential and the future prospect of remote sensing in lake monitoring are briefly discussed. [ABSTRACT FROM AUTHOR]

The uncertainty of the hydrological environment and unbalanced water resource allocation result in a high risk of irrigation water shortages in regional agriculture, which seriously affects the sustainable development of agricultural systems. In this paper, we propose a risk regulation based modeling approach for the optimal allocation of agricultural water resources in a complex stochastic environment. The approach includes a conditional value-at-risk (CVaR) model, two-stage stochastic programming (TSP) model, two-dimensional joint distribution probability (JP) model, fractal criteria, and a multiple forms of chance-constrained programming (CCP) model. The model can weigh the contradiction between the intended target and associated penalties attributed to unknown hydrological events, measure the risk between system benefits and expected losses in agricultural water allocation at different confidence levels, and address the randomness in the objective function and constraints (including the left end term, right end term, and left and right end terms). To verify the applicability of the method, it is applied to the Jinxi Irrigation District in China to optimize the allocation and risk regulation of limited water resources under the variable runoff conditions of the Songhua River and crop water demands in the irrigation area. By adjusting parameters such as risk preference and probability of violation, the risk of water shortages in the irrigation area can be regulated, and the multidimensional impacts of different water allocation schemes on agricultural economic benefits, social benefits, ecology and environment can be determined. The case study reveals that the CTSP-CCJP method is sensitive, applicable to complex and uncertain environments and important for the efficient use of agricultural water resources and risk reduction. • The stochastics of water supply and demand linkage are considered. • The multiparameter stochastic uncertainty is transformed. • The risks between system benefits and expected losses are balanced. • The sustainability of a risk regulation-based water allocation scheme is evaluated. • The impact of water scarcity on sustainable development is mitigated. [ABSTRACT FROM AUTHOR]

Marine spatial planning (MSP), which is a step-by-step approach for the ecosystem-based management (EBM) of global oceans, enables human activity and marine and coastal ecosystems conservation to occur simultaneously. It contributes to the implementation of the 2030 Agenda, particularly Sustainable Development Goal 14. However, the MSP, supposed as a transboundary policy-making process, is hampered by obstacles. Although existing studies have revealed significant obstacles and enablers for transboundary marine spatial planning (TMSP), they have not analyzed how these factors affect government decision-making. To fill this gap, this paper takes the Xiamen–Kinmen Sea area in China as an example and analyses the interaction between the Xiamen–Zhangzhou–Quanzhou (XZQ) governments, the Kinmen government, and an introduced transboundary institution using evolutionary game theory. Numerical simulation is used to analyse the impact of influencing factors on the behaviors of different actors. The results demonstrate that: (1) the initial probability of the three parties directly affect the final stability; (2) net benefits have a positive incentivizing effect on the performance of the Promotion Group; (3) the value of eco-environmental losses reflects the urgency of collaborative governance by implementing TMSP; (4) transaction costs do not undermine collaboration, but do reduce the willingness of governments to participate if they are too high; and (5) the appropriate value of the transaction cost allocation coefficient should not exceed 0.9. This research may serve as an essential reference for the Xiamen–Kinmen Sea area for implementing EBM and provide general insights into the design of incentive policy recommendations for other regions for developing TMSP in shared waters. [Display omitted] • A tripartite evolutionary game model to explore factors for TMSP is developed. • The players' evolution routine and optimal result for TMSP are revealed. • Initial possibilities affect the player's decision-making behavior. • The choice of the transboundary institution relies on the benefits from TMSP. • Transaction costs do not undermine the collaboration unless they are too high. [ABSTRACT FROM AUTHOR]

With the firm level datasets from 2004 to 2014, this paper uses the difference in differences (DID) estimator to explore the effects of China's high-speed rail (HSR) on firms' environmental efficiency. We find that China's HSR lowered SO 2 intensity (SO 2 per unit output value) by approximately 7.9%. More importantly, firms reduce SO 2 intensity mainly through innovation, productivity improvement, and the agglomeration of firms. Our additional analyses show that these observed effects of HSR are mainly driven by firms in core cities, while the environmental efficiency of firms in the peripheral cities seems to be unaffected. Heterogeneous effects indicate that the HSR has a more significant effect on dirty firms, state-owned firms, foreign firms, and large firms. Our results suggest that HSR construction could have contributed to the China's environmental governance. • Using a difference-in-differences estimator, it is the first study to analyze the effect of China's high-speed rail (HSR) on firms' environmental efficiency. • The HSR can significantly improve the environmental efficiency of firms in the affected areas. The results indicate that China's HSR significantly reduced the SO 2 intensity of affected firms by an average of 7.9 percent. • The affected firms improve the environmental efficiency mainly through innovation, productivity improvement, and the agglomeration of firms. • Our additional analyses show that these observed effects of HSR are mainly driven by firms in core cities. Other heterogeneous effects of the HSR are also examined. • There are important implementations for the present, especially for environmental protection and green development. [ABSTRACT FROM AUTHOR]

Air pollution, especially haze pollution is a serious environment problem that directly affects the sustainable development in China. Identifying the key factors affecting PM2.5 concentration and the interaction mechanism between them through quantitative analysis can greatly help a city devise PM2.5 pollution control strategy. Using the geographical detector model, we quantitative measured 13 cities in the Beijing-Tianjin-Hebei region's social factors and their interaction impacts on PM2.5 concentration in 2016. In the analysis process, factor analysis method is used to separate the factors preliminary. According to the results, the factors mainly divided into two categories, i.e. economic factor and environment factor. R&D ranks top in the studied cities in terms of factor detection results, presenting closely relationship between PM2.5 concentration and R&D. We also find the interaction between any two factors all enhance impact on PM2.5 concentration than any one alone. This study provided a scientific basic and guidance for measure the driving degree of social factors and their interaction effects. • This paper identifies the key elements affecting PM2.5 concentration. • The geographical detector model is used to study the interaction mechanism of those factors. • This paper takes 13 cities in the Beijing-Tianjin-Hebei region as an example. [ABSTRACT FROM AUTHOR]

Air pollution and ageing populations are two of the most important issues facing in the development of all countries around the world, and the resulting debate between air pollution and labour supply has become increasingly intense. This paper uses data from the 2017 China Migrants Dynamic Survey (CMDS data), exploring the impact of perceived air pollution on labour supply of the migrants based on the perspective of the heterogeneity of different groups' sensitivity to air pollution. After overcoming the reverse causality between perceived air pollution and labour supply using an instrumental variables approach, we find that there is a significant negative effect of perceived air pollution on labour supply. At the same time, this negative effect shows some heterogeneity in terms of the presence of susceptible persons in the family, workers' income levels and household registration. Therefore, in the current economic and social development, in addition to improving measured air quality, it is also necessary to focus on improving the perceived air quality of citizens, as well as improving the working environment of the vulnerable groups in the labour market and protecting their basic labour rights and interests, which is of positive significance for the continuation of the demographic dividend and providing impetus for high-quality and sustainable economic development. • Perceived air pollution has a more direct impact on labour supply. • There is a significant negative effect of perceived air pollution on labour supply. • There is heterogeneity in the effects of perceived air pollution on labour supply. • Vulnerable groups are more negatively affected by perceived air pollution. [ABSTRACT FROM AUTHOR]

Government management is the main tool to solve environmental pollution. Considering the unique fiscal decentralization institution in China, this paper investigates the effect of foreign direct investment (FDI) on urban haze pollution in China from the perspective of spatial econometrics. The Generalized Spatial Two Stage Least Squares (GS2SLS) method is employed to treat the spatial correlation of air pollution. Based on a panel dataset comprising 276 Chinese cities during 2004–2018, we find a positive effect of FDI on urban haze pollution. For one standard deviation increase in FDI, the average annual PM2.5 concentration increase by 1.5%, ceteris paribus. Evidence also suggests that this effect varies across regions with different levels of fiscal decentralization. Through the test of the moderating effect and the threshold effect, we found that the higher of the fiscal decentralization, the weaker of the impact of FDI on haze pollution. This study proposes a new solution for sustainable development: increasing the financial autonomy of local governments to restrain the attraction of non-cleaner investment. • Examining the impact of FDI and fiscal decentralization on haze pollution in Chinese cities. • The GS2SLS method is employed to treat the spatial correlation of air pollution. • An increase in FDI by one standard deviation causes a 1.5% increase in average annual PM2.5 concentration. • The higher of the fiscal decentralization, the weaker of the impact of FDI on haze pollution. [ABSTRACT FROM AUTHOR]