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China's paper industry development is rapid, but the recycling rate of China's waste paper has been low all the time. Meanwhile, material flow analysis can help determine the flow of waste paper, and life cycle assessment (LCA) is the methodological framework for quantifying greenhouse gas emissions. Therefore, present study integrates these two methods into the model construction of China's waste paper recycling decision system. Present study constructs a benchmark model of China's waste paper recycling decision system in 2017, focusing on the impact of nonstandard waste paper recycling on the economic and environmental benefits of China's domestic waste paper recycling system. This model construction is followed by sensitivity analysis of the relevant parameters affecting the efficiency of the waste paper recycling system. Finally, present study forecasts the system's economic benefits and greenhouse gas (GHG) emissions in the context of integrating and regulating nonstandard recycling vendors. The results show that the economic benefit of China's waste paper recycling in 2017 is approximately 458.3 yuan/t and that the GHG emissions are 901.1 kgCO 2 eq. The standard recovery rate and nonstandard recovery acceptance rate will both have a significant impact on the system's economic benefits and improve the GHG emissions structure. In the context of integrating nonstandard recycling enterprises and individual recycling vendors, the economic benefits will rise to 3312.5 yuan/t in 2030, while GHG emissions will rise to 942.9 kgCO 2 eq. Present study can play a certain guiding role for policy makers in formulating waste paper recycling industry specifications and formulating relevant policies., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Countries worldwide consider solid waste collection and recycling necessary due to the recent emphasis on conservation of resources and environmental protection. Due to the constraints from resource depletion and the need for sustainable economic growth, solid waste recycling has become a critical issue in China. Several indigenous researchers in China have studied the potential benefits of solid waste recycling. However, most studies limited the environmental assessment of solid waste recycling to greenhouse gas (GHG) emissions and considered only one type of solid waste (paper or plastic). Therefore, the present study analyzed the energy (electricity) and environmental (GHG and air pollutant emissions) benefits of recycling steel, nonferrous metal, plastic, and paper wastes from 2005 to 2017 in China. The study used the formulation of model equations method to estimate the electrical energy and environmental benefits. Prominent findings show that the total amount of electricity saved by recycling solid waste from 2005 to 2017 was 3743.3 Mtce. On average, solid waste recycling during the period led to a 43.2% saving on electricity. Solid waste recycling avoided 4765.9 billion kg of carbon dioxide emission and 22.502 billion kg of methane emission. It was also found that the recycling of solid waste saved a total amount of 10,669.8 M kg of NO X emission but had a burden of −6263.2 M kg of VOCs emission on the environment. Solid waste recycling avoided the emission of CO 2 , CH 4 , NO X , and SO X, but the recycling of steel, plastics, and paper waste had negative impacts on the environment in terms of VOCs and PM emissions. Proper measures such as installing air pollution control devices should be put in place to minimize the emission of pollutants during the recycling of these solid wastes. • The energy and environmental benefits of solid waste recycling is assessed. • The formulation of model equations method was used for the assessment. • On average, the recycling of solid waste saved 43.2% of electricity. • Recycling of waste avoided a significant amount of GHG and air pollutant emissions. • Solid waste recycling had no essential benefit on the emission of VOCs and PM. [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]

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]

The impact investing literature largely focuses on private equity investing and overlooks the investments made through debt financing that actually dominate the market. To address this research gap, this paper investigates whether impact financing is associated with financial benefits. By using COVID-19 as an exogenous shock to China's stock market, this paper applies fixed effects panel data analysis with a difference-in-differences research design to provide robust empirical outcomes. The results reveal those financial institutions that better integrated environmental impacts into their financing process experienced positive stock return changes in response to the shock. This study answers the question of how well an impact scales. The findings suggest that impact financing is an effective model, as the impacts incorporated in the debt can be scaled up compared to impact investing funds with low volumes. Impact financing has enormous potential for financial institutions to engage in the green transition since they can derive pecuniary utility while delivering environmental impacts. The revelation of financial benefits also contributes to overcoming the lack of knowledge about impact financing and helps to remove the barriers that advance industry growth. • This paper studies whether impact financing is associated with financial benefits. • Financial firms that better integrate environmental impact in financing have positive stock return changes during COVID-19. • Financial firms can derive pecuniary utility from pursuing impact financing. • The findings suggest that impact financing can be an effective model to bring impact to a substantial scale. [ABSTRACT FROM AUTHOR]

In the global context, countries must reduce carbon dioxide emissions to "net zero" by 2050 to limit global warming to 1.5 °C above pre-industrial levels. China's Nationally Determined Contributions (NDCs) are to peak carbon dioxide emissions by 2030 and achieve the carbon neutrality target by 2060. To monitor the achievements of the NDCs, establishing an annual-based accounting mechanism is necessary to record the carbon stocks in China, especially for Blue Carbon. The paper aims to present China's first national-scale systematic Blue Carbon accounting for mangroves, salt marshes, and seagrasses, covering the accounting subjects of physical and monetary assets, as well as relevant indicators for investors. It focuses on the design of the accounting method and system, the selection of data categories applied to this system, and the application of China's Blue Carbon accounting based on this accounting system. Taking Blue Carbon accounting as a starting point, this paper analyses the restoration prospects of these ecosystems and their application potential for NDCs in China compared with the terrestrial ecosystems. The results indicate that mangroves are the most cost-effective type of ecosystem, even compared to terrestrial forests. Thus, the paper provides policymakers with a new perspective on the decision-making of carbon sequestration relevant decisions, aiming to promote the monitoring, restoration, and expansion of China's coastal blue carbon ecosystem through the establishment of a sound Blue Carbon accounting system, and to help achieve the carbon neutrality goal in China's NDCs through regular and systematic monitoring of its national Blue Carbon inventories. • China's coastal blue carbon ecosystems are carbon sources rather than carbon sinks. • Mangroves are the most cost-effective coastal blue carbon ecosystem compared to salt marshes and seagrass beds. • The Blue Carbon of mangroves is more cost-effective than the Green Carbon of terrestrial forests when meeting China's Nationally Determined Contributions target of increasing forest stocks. • Establishing guidelines for Blue Carbon data requirements will lay a scientific foundation for formulating strategies and policies to cope with global climate change. [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]

Building a marine ecological security shelter (MESS) has become the main strategy to adapt marine ecological threats in China. As China's marine policy lacks a robust framework document, it is necessary to consider whether the policy system can effectively support the construction of MESS. However, the linkage between the construction measures of MESS and related policies is not clear. Therefore, the purpose of this paper is to clarify the concept of MESS and its connection with policy, by adopting the policy content analysis method to analyze the evolution process of MESS-related policy system. The legislative shortcomings and implementation obstacles of the MESS-related policy system are then summarized and discussed. The results show that from 1981 to 2021 the MESS-related policy system has been continuously improved. However, the policy system's support and guarantee capacity for building MESS still needs to be improved. (1) Due to the lack of basic laws and special laws, the coordination among governance subjects and among policies lacks legislative guarantee. (2) The construction of MESS continues the inter-regional and inter-department administrative barriers in collaborative governance of marine environment. To establish an effective collaborative governance model, it is essential to improve the governance structure and mechanism. (3) The government-led governance pattern faces the problem of mechanism failure. The command and control instrument accounts for more than 82%, and the public and enterprises lack strong policy guarantees to participate in marine governance. (4) The policy system's adaptability to emerging threats must be improved. Marine policies rarely involve emerging threats such as climate change and new pollutants. Meanwhile, the real-time supervision and monitoring mechanism is weak. The real-time supervision is only accounting for about 10%. Generally speaking, as a complex and long-term system engineering, the construction of MESS will inevitably encounter contradictions in politics, culture, and economy. China should deepen the construction of marine ecological civilization and form a governance concept based on ecosystems. Overall, this paper helps to understand the internal connection between MESS and policy comprehensively and provides a new perspective for improving China's marine governance capacity. [Display omitted] • We conduct a content analysis of 403 Chinese marine ecological security policies. • The policy instruments are mainly regulatory but lack flexibility and precision. • The policy implementation lacks assurance for poor governance mechanisms. • The policy system lacks adaptiveness to climate change and new pollutants. • The study provides ideas to enhance climate change adaptation of marine governance. [ABSTRACT FROM AUTHOR]

The proposal of the dual carbon goal and the blue economy in China has sparked a keen interest in carbon emissions reduction from sewage treatment. Carbon accounting in urban sewage plants serves as the foundation for carbon emission reduction in sewage treatment. This paper re-evaluated carbon accounting in the operational processes for urban sewage treatment plants to develop a novel carbon emission evaluation model for anaerobic-anoxic-oxic treatment plants. The results show that the carbon emissions generated by non-carbon dioxide gases far exceed the carbon emissions from carbon dioxide alone. Moreover, the recycling of sewage leads to carbon emissions reduction that offsets the carbon emissions generated during the operation of the sewage plant. Also, the carbon emissions generated by sewage treatment plants are lower than those generated by untreated sewage. The findings and insights provided in this paper provide valuable references for carbon accounting and the implementation of low-carbon practices in urban sewage treatment plants. [Display omitted] • A novel carbon emission evaluation model for AAO treatment plants was proposed. • Mechanical processes generated higher carbon emissions than energy and chemicals. • The determination of direct and indirect emissions of CO 2 from sewage plants. • Sewage recycling can offset carbon emissions from the operation of sewage plants. [ABSTRACT FROM AUTHOR]

Corporate water performance and sustainable development are currently vital focus areas for scholars. Therefore, this paper investigates the experience of Chief Executive Officers (CEOs) with water shortage influences corporate water performance by focusing on listed companies in water-intensive and high-water-risk industries in China between 2014 and 2019. This paper manually collected information relative to the cities and provinces where CEOs grew up to evaluate their early exposure to water shortages. Furthermore, this paper develops an evaluation scale, based on the Enterprise Water Conservation Evaluation Guide (GB/T 7119-2006), to compute the enterprise water management practices scores. These results will constitute the enterprise water performance evaluation score. Moreover, this paper focuses on CEOs who have experienced water resource shortages through a positive impact on the water resource performance of their companies. As for the findings, they demonstrate that CEOs who grew up in regions with higher water scarcity have a more pronounced positive effect on their water shortage experience through corporate water performance. Furthermore, CEO power intensity positively moderates the relationship between the CEO's water shortage experience and corporate water resource performance. Further investigation reveals generational differences in the impact of CEO water shortage experience on company water performance. CEOs, who grew up during periods with a higher incidence of droughts, demonstrate a more significant promoting effect on corporate water performance. To sum up, this study expands the understanding of factors influencing corporate water resource performance and deepens the knowledge of the early life experiences of CEOs. • We construct a set of scales to measure corporate water performance. • We explore the relationship between CEO water shortage experience and corporate water resource performance. • CEO water shortage experience has a positive effect on corporate water performance. • CEO power intensity plays a positive moderating role. [ABSTRACT FROM AUTHOR]

China's rapid economic development in recent decades has come at a considerable environmental cost. This paper explores whether atmospheric quality monitoring policy (AQMP) improves eco-efficiency by using AQMP as a natural experimental group. We assessed the eco-efficiency of 285 cities in China from 2009 to 2019 using the super-efficient SBM model and estimated the impact of AQMP using the propensity score method Difference-in-Difference (PSM-DID) model. The key findings of this paper are as follows: First, AQMP can enhance eco-efficiency, promoting sustainable urban development. Second, governmental and non-governmental organizations play contrasting roles in either fostering or reversing the positive effects of AQMP. Factors like innovation, clean energy adoption, and industrial structure have a positive mediating influence. Finally, the impact of AQMP on eco-efficiency varies across cities, displaying heterogeneity. Specifically, AQMP has a positive effect on eco-efficiency in resource-rich cities, small and medium-sized urban centers, smart cities, and coastal areas. These findings carry significant implications for the establishment of dynamic monitoring networks and the advancement of eco-efficiency in emerging countries, including China. • Impact of atmospheric quality monitoring policy on eco-efficiency is discussed. • Governmental organizations promote the positive impacts of AQMP. • Non-governmental organizations reverse the positive impacts of AQMP. • Innovation, clean energy, and industrial structure have a positive mediating role. • The impact of AQMP on eco-efficiency has city heterogeneity. [ABSTRACT FROM AUTHOR]

Quantity-based and concentration-based limits are two common environmental permitting approaches utilized by government worldwide in environmental management. While existing literature is still unambiguous about roles played by quantity-based versus concentration-based limits in environmental management, it becomes evident that relying exclusively on concentration-based or quantity-based limits to control plant emissions may not necessarily result in improved environmental quality. This paper leverages a unique opportunity arising from a recent reform in China's Pollutant Emission Permit System (PEPS) initiated in 2016 to analyze how the introduction of quantity-based limits in addition to concentration-based limits through the PEPS reform impact emissions at the plant level. Utilizing a unique plant-level continuous emission monitoring system data collected from Shaanxi Province (located in western China), the paper finds a significant reduction in air pollutant emissions as a result of the PEPS reform (nitrogen oxides (NOx) by 39%, sulfur dioxide (SO 2) by 15% and particulate matter (PM) by 13%). The heterogeneity analyses show emission reductions in plants differ across those with varying quantity limits specified in their permits, distinct emission ratios and diverse ownership structures. Furthermore, plants that fall under the classified management system with more stringent regulations imposed, especially those operating in high-pollution sectors, situated within industrial parks, or classified as large-sized plants, attain higher pollutant quantity limits. Findings of the paper carry important implications for effective environmental management, particularly within developing countries, and shed some light on carbon emission reduction policies in China. [Display omitted] • Quantity-based limits reduce air pollutant emissions significantly. • Distinct behaviors observed in air and water pollutants. • Varied quantity limits and emission ratios influence emission behavior. • State-owned plants show better emission reduction under quantity limits. • Stricter regulations could allow higher quantity limits for plants. [ABSTRACT FROM AUTHOR]

As the global carbon emission problem is getting more and more serious, the European Union has proposed the Carbon Border Adjustment Mechanism (CBAM) to prevent carbon leakage, which will have an impact on China's foreign trade. Based on this background and the problems of current research that ignores factors such as commodity prices, long-term impacts, intertemporal substitution analysis, and changes in national strategies for foreign exports, this paper propose a Computable General Equilibrium (CGE) model based on an evolutionary game as a dynamic recursive basis to study the impact of the CBAM on the Chinese manufacturing industry. For the industries mentioned in the CBAM, 18 affected sectors are collated, and a CGE model containing multiple blocks such as production, trade, and carbon emissions is built. Meanwhile, we establish an evolutionary game model with EU suppliers, manufacturers, and the government, allowing Chinese suppliers to compete with EU suppliers. Based on the above model, the impact of carbon tariff policies from 2020 to 2050 is studied. The results indicate that under the intra-EU competition condition, carbon tariffs will reduce the price of Chinese exports and slightly decrease China's real GDP, as well as the carbon emission intensity of 18 sectors and fossil energy. However, the impact of carbon tariffs on overall carbon emissions is small and is essentially a protective policy. In addition, the evolutionary game-based CGE model takes into account the dynamic strategies of both sides and is therefore less affected by carbon tariff shocks and recovers more quickly and more realistically. Finally, the article argues that the advantage of carbon tariffs for local suppliers is unsustainable and Chinese suppliers will still dominate, and local suppliers need more subsidies from the EU government. On the other hand, the Chinese government needs to implement a stricter carbon tax regime and export subsidies to improve the competitiveness of Chinese products in terms of green levels and price advantages. The purpose of this paper is to examine the quantitative impacts of CBAM on China's related manufacturing industries and strategies to maximize the benefits to both governments. • A new dynamic recursive approach to CGE is proposed that uses evolutionary games. • The strategy of the importing country is taken into account in the CGE model and is changed according to the multi-stage game strategy to simulate reality better. • The influencing factors of export commodity prices are explored, including the effects of consumer sensitivity, green input coefficients, and carbon emission rights prices. • The impact of CBAM on the income and savings of firms in 18 sectors in China to 2050 was studied. • The impact of CBAM on the carbon intensity of China's fossil energy sources, Coal, Oil, and Gas, the carbon intensity of enterprises in 18 sectors, and the national carbon emissions to 2050 were studied. [ABSTRACT FROM AUTHOR]

Our paper focuses on how firms strategically respond to environmental regulations on environmental actions. Given the greater discretion in environmental information disclosure and relaxed environmental regulations enforcement in China, we propose that firms tend to say more while do less to obtain environmental legitimacy, namely corporate environmental actions decoupling. Using a sample of 5422 Chinese firm-year observations over the period of 2012–2018, we document that stringent environmental regulations contribute to a significant inconsistency between environmental reporting and actual environmental performance. Moreover, we demonstrate that this inconsistency is exacerbated when firms possess greater bargaining power and fewer financial resources. Our paper not only advances the understanding of how firms navigate external regulations by examining the tradeoffs between symbolic and substantive actions, but also sheds light on factors influencing decoupling/greenwashing practices from the perspective of government-business relations in China, and potentially in other emerging economies. • Firms tend to say more while do less to obtain environmental legitimacy. • Greater bargaining power amplifies the disparity between reporting and performance. • Limited financial resources promote corporate environmental actions decoupling. • Legitimacy theory is more applicable to guide environmental practices in China. [ABSTRACT FROM AUTHOR]

With the aggravation of global warming and the increasing demand for energy, the development of renewable energy is imminent. Floating photovoltaic (FPV) is a new form of renewable energy generation. However, the impact of FPV on the aquatic environment is still unclear. By long-term empirical monitoring and data analysis, this paper reveals the shading effect of large-scale FPV power station on aquatic environment for the first time. The results show that: (1) Compared with the non-photovoltaic (NP) zone, FPV only significantly reduces the concentration of dissolved oxygen in the photovoltaic (P) zone. (2) The concentration of chlorophyll a , nitrate nitrogen and total phosphorus increase, while pH and ammonia nitrogen decrease. FPV only causes an effect of the same order of magnitude as the initial concentration, and has no significant adverse effects on the nutritional status of the water body at a coverage ratio less than 50%. (3) FPV has a cooling effect on the water body during the daytime and a thermal insulation effect at night, with the most pronounced impact on peak water temperature (T w). The heating and cooling process of T w in P zone usually lags behind the NP zone by 1–3 h. The diurnal fluctuation and vertical difference of T w as well as the stability of water body are reduced under the shading of FPV, alleviating the influence of climate change on T w and water body stratification. (4) If 10% of the water area larger than 1 km2 in China are used to develop FPV, more than 900 million tons of CO 2 emissions can be reduced, and about 5 billion m3 water can be saved, which is significant in the context of climate change. In general, this paper provides a reference for the future aquatic environmental impact assessment of FPV and the formulation of related policies. • The impact of FPV on aquatic environment has been assessed. • The scale effect of FPV and impact of "fish-photovoltaic integration" are revealed. • Spatial-temporal and object specificity of impact on aquatic environment is reviewed. • The responds of FPV to the challenges of global climate change are further discussed. [ABSTRACT FROM AUTHOR]

Air pollution is an inevitable negative environmental externality in the process of industrialization and urbanization in countries around the world. Land misallocation in the process of urbanization and industrialization and the resulting urban sprawl exacerbates the above problems. As a major country in the stage of rapid urbanization and industrialization, China also faces severe air pollution problems. Therefore, this paper will systematically study the impact of land misallocation and urban sprawl on air pollution. We first set up the utility maximization problem of each economic entity in the process of land misallocation in the mathematical model, and form a general equilibrium theory model to analyze the relationship between land misallocation, urban sprawl and air pollution, and then put forward the research hypotheses. We further use the big data of land market transactions of China Land Market Network and LandScan global population data to build the land misallocation index and urban sprawl index respectively, and use an extended mediating effect model to empirically test the hypotheses. The results suggest that the effect of land misallocation on air pollution is significantly positive, and the impact of land misallocation on urban sprawl largely depends on the return rate of land relative to labor (RRIRL). When the RRIRL is relatively low, the impact is weak, or even has a negative effect to some extent. At this time, low transportation costs are conducive to reducing air pollution. On the contrary, when the RRIRL is relatively high, land misallocation has a significant role in promoting urban sprawl. At this time, high traffic costs are conducive to reducing air pollution. In addition, we also find that there is an inverted U-shaped relationship between urban sprawl and air pollution. When the urban sprawl level is low, its impact on air pollution increases with the increase of its level, but once it exceeds a specific node, the impact will decrease. Based on the characteristics of the relationship among land misallocation, urban sprawl and air pollution under different RRIRL, we summarize four environmentally friendly urban development paths. We bring the land bid rent theory and environmental pollution research into a same theoretical model framework, which provides a modeling idea and research perspective with a micro-foundation for subsequent research on land misallocation. We integrate the research conclusions of existing literature and unify them under the research frameworks concerning different RRIRL in the empirical results, which greatly improving their applicability. The four urban development paths summarized in this paper will also provide inspiration for future researchers and policy makers. • We posit that urban sprawl is an important intermediate mechanism by which land misallocation affects air pollution. • We build a general equilibrium framework. • Land misallocation leads to an increase in air pollutant concentrations. • Land misallocation has a nonlinear impact on air pollution by restraining urban sprawl. [ABSTRACT FROM AUTHOR]

In a large-scale region, governance for connectivity in an ecological system often conflicts with management boundaries, causing inefficiencies. Collaboration among management organizations in different areas can help overcome this problem. However, few studies quantified the collaborations' practical relationship with connectivity, considering that some potentially connected paths are easy to neglect by managers. In this paper, collaborations among government agencies in project application process were analyzed, and a multilevel social-ecological network analysis (SENA) approach was developed to identify the collaboration's effect on genetically connected coastal areas. The network framework and methods were shown in a case of coastal saltmarsh conservation and development in the Yellow River Delta, China. Collaboration patterns in conservation and development networks were analyzed and compared among local, subregional, and regional government agencies working in genetically connected coastal areas. Project information flow, reflecting communication frequency and decision-making chances among government agencies was quantified and correlated with ecological connectivity to inform governance effects. Results showed areas with the potential to realize social-ecological alignment, where collaborative networks were measured by network density (percentage of connected network edges). The current reveals that development has more significant potential than conservation at most levels to overcome the misalignment of the social-ecological system, also known as scale mismatch. Empirical evidence also showed a correlation between communication capacity in development networks and improved ecological conditions. The multilevel SENA advanced in this paper can be used for natural resource management when connectivity plays a major role. [Display omitted] • We advanced a multilevel network approach for better evaluating social–ecological (mis)fit with connectivity. • We mapped collaborations among projects in a genetically connected region in the Yellow River Delta. • Development acts better than conservation with modeled network to realize social ecological alignment. [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]

Increasing aluminum demand under the clean energy and low-carbon transformation background increases the fuzziness of relationships between economic growth and aluminum use or aluminum related carbon emissions. To figure this out, this paper established an aluminum use and carbon emissions integrated decoupling model within the framework of anthropogenic aluminum cycle. A material flow analysis (MFA) during 2000–2020 for China's aluminum cycle was firstly conducted to quantify both aluminum flow and carbon emissions in each aluminum life-cycle process. Then, this paper evaluated and decomposed the decoupling index of aluminum use-economy and carbon emission-economy via the LMDI decomposition model. Results show that: (1) secondary aluminum has not become effective supplement for primary aluminum in China; (2) the expansive negative decoupling state was the most prevalent state. The decoupling effects of carbon emission were better than that of aluminum use; (3) technology improvement was an important impactor to decoupling process but didn't offset the growth in aluminum consumption or carbon emissions at most of the time. The government and industry organizers should implement active countermeasures to stimulate aluminum companies developing technology to improve aluminum use efficiency and reduce carbon emissions. [Display omitted] • Secondary aluminum supply was limited because the scrapping period of BC and TE department did not come. • Promoting aluminum recycling and remelting are the key to decarbonize the aluminum industry. • The decoupling effects of carbon emission were better than that of aluminum use. • Technology improvement had rebound effect in aluminum consumption before the 13th Five Year Plan. [ABSTRACT FROM AUTHOR]

Economic efficiency gains in tourism are considered a crucial approach to reducing carbon emissions in the tourism sector, especially in tourism transport. However, as a significant source of carbon emissions from tourism activities, the total carbon emissions from tourism transport have not decreased proportionally to the reduction in the intensity, despite China's overall improvement in the tourism economic efficiency. This phenomenon is commonly known as the "rebound effect", which means that although technological progress can achieve emission reductions by efficiency improvement, but it can also indirectly stimulate socio-economic growth and creates new energy demands, results in expected emission reductions being offset by the additional economic growth effect. Based on the multi-source data structure, this paper takes Yangtze-river delta urban agglomeration as an example, quantitatively evaluated the carbon rebound effect of tourism transport through the rebound effect measurement model; simulated the spatiotemporal dynamics evolution pattern of the carbon rebound effect in tourism transport through the spatial kernel density; extracted and identified the dominant factors of carbon rebound effect in tourism transport by the geographic detector. The conclusions summarized as follow: (1) The overall carbon emissions from tourism transport in the agglomeration primarily exhibit a weak rebound effect. (2) The carbon rebound effect is significantly influenced by spatiotemporal factors, which impact its development trend and interaction relations. (3) The level of tourism consumption exerts the greatest influence on the carbon rebound effect of tourism transport, while environmental regulation intensity is commonly employed as a measure to address the rebound effect. This paper aims to enhance the diversity of research on carbon emissions in tourism transport while addressing the existing limitations in spatial-temporal extension. The objective is to restrain the spread of the carbon rebound effect at the regional level, thereby providing a novel decision-making reference for the sustainable development of regional tourism. • Quantitatively analyzed the carbon rebound effect in tourism transportation. • Revealed the influence of spatiotemporal factors on rebound effect. • Identified the dominant factors of carbon rebound effect. [ABSTRACT FROM AUTHOR]

Climate warming impact on excessive nitrogen (N) load in sediment favours cyanobacterial blooms in eutrophic waters. The nitrate (NO 3 −-N) and ammonium (NH 4 +-N) are two forms of N loads that contribute to algae blooms. However, little attention is paid to the impact of environmental factors on N loads variations at different time scales. This paper used a well-calibrated and validated EFDC model to investigate the temporal patterns and trends of ammonium and nitrate from June 2016 to June 2017. This paper presented the relationship and effects between these variations and environmental factors using data from satellite and reanalysis-based observations obtained for six meteorological parameters. The relationship and effects between these variations and environmental factors were also examined at different timescales (i.e., daily, monthly and seasonal scales). Model calibration results indicated that measured values reasonably matched simulated values. T he validation results revealed that relative error (RE) values were within an acceptable range. The REs of ammonium at East Taihu (S12) and Xu Lake (S23) sampling sites were 55.83% and 57.61%, while that of nitrate was 24.37% (S12) and 41.08%, respectively. The daily analysis of NH 4 +-N and NO 3 −-N variations was 7.318 ± 3.876 (g/m2/day) and 0.0275 ± 0.222 (g/m2/day), respectively. The monthly analysis showed NH 4 +-N and NO 3 −N range from 2.04 to 12.04 (g/m2/day) and 0.0008 to 0.064 (g/m2/day), respectively. The magnitude NH 4 +-N and NO 3 −-N varied and showed distinct inter-monthly variations. , The relationship between sediment fluxes and meteorological parameters showed the magnitude of correlation coefficient (r) and strength of correlation varied significantly. At daily scales, the relationship of NH 4 +-N and NO 3 −-N had a significant positive correlation with all meteorological parameters. At monthly, the correlation coefficient (r) of NH 4 +-N and NO 3 −N were heterogenous. At daily and monthly scales, air temperature and wind speed are the main drivers affecting sediment N loads' dynamics; however, the influence of relative humidity, precipitation, and evaporation on N loads are smaller. The study demonstrates the contribution of meteorological conditions to the magnitude and timing of N loadings variability in water bodies. The findings provide more insight into lake ecosystem protection and environmental remediation. [Display omitted] • The simulated nitrate and ammonium nitrogen were calibrated and validated with field observation data. • The driving factors influencing nitrogen variations were quantified, and their impacts were identified. • Five meteorological variables significantly correlated with Nitrogen variations. • The strength of the correlation coefficient (r) varied across the multiple time scales. • Changes in meteorological conditions affect the timing and magnitude of nitrogen variations in Taihu lake. [ABSTRACT FROM AUTHOR]

Information development is a necessary means for China to achieve technology force and an effective path toward sustainable development. Regarding the "information benefiting people" policy led by the Chinese government as a quasi-experiment of information technology, this study builds an analysis framework for the impact of informatization on green total factor productivity (GTFP). Based on panel data at the Chinese city level from 2006 to 2019, this study further empirically evaluates the mechanism path, heterogeneity, and spatial spillover effects between informatization and GTFP by using a difference-in-difference (DID) model, a mediating model, and a spatial DID model. The results show that (1) the information benefiting people policy contributes considerably to greater GTFP levels in the pilot cities; (2) the policy also promotes the rapid growth of GTFP by fostering the advancement of education, the share of the number of ICT employees, and green technology innovation; (3) the information benefiting people policy raises GTFP in the eastern cities, small cities, and non-old industrial based cities; and (4) the policies lead to a large rise in local GTFP levels, but a decline in GTFP in surrounding cities. This paper offers valuable reference suggestions for the Chinese government to implement informatization-policies to support green development. • This paper investigates the effect of informatization on green total factor productivity (GTFP). • We use "information benefiting people" policy as a quasi-experiment. • The informatization promotes GTFP in China. • The education level, ICT employment share, and green technology innovation are suitable mediators. • The impact of informatization on GTFP is heterogeneous and spatially spillover. [ABSTRACT FROM AUTHOR]

Renewable energy is not only an efficient way to ensure energy independence and security but also supports the transition to a low carbon economy and society. The progress of renewable energy technological innovation is an important factor that influences the development of renewable energy. An in-depth analysis of the driving factors that influence this progress is crucial to China's energy transition. Based on Chinese provincial data over 2000–2015 and panel data models, this paper regards the CO 2 emissions as climate change and explores the response of renewable energy technological innovation to intensive CO 2 emissions. We also analyze the effect of the driving factors such as energy price and R&D investment on this innovation process. The main conclusions drawn are: (1) There are significant differences in technological innovation levels across China's provinces. (2) We observe that the intensive CO 2 emissions have promoted renewable energy technological innovation level, meaning that innovation process responds actively to climate changes. (3) R&D investment from government and enterprise both are conducive for promoting the innovation level. (4) Energy price has an insignificant effect on innovation in renewable energy technologies and we attribute this to the unreasonable energy price mechanism. This paper provides clear evidence for understanding the role of innovation on climate change. • The drivers of the renewable energy technological innovation are explored. • There are significant differences in technological innovation across provinces. • Renewable energy technological innovation responds actively to climate changes. • R&D investment is conducive for promoting the technological innovation levels. • The government should give full play to the role of the energy price mechanism. [ABSTRACT FROM AUTHOR]

An emission permit system (EPS) is a fixed-source environmental management system that is widely practiced worldwide. Since 2016, China has been building a fixed-source environmental management system with the EPS as its core. This paper summarizes the evolutionary process of China's EPS over the past 40 years considering four main stages: embryonic stage, local pilot stage, total emission control-based exploration stage, and reform stage of the core management system. This paper notes that China initially established a system of laws and technical specifications for emission permits, and emission permits are clearly becoming a mainstream trend in fixed-source management. The paper argues that there are still four problems in the current EPS reform (i.e., insufficient support of laws and regulations, poor integration of the EPS with other systems, unscientific design of the EPS, and insufficient implementation capacity after permit allocation). This paper puts forward 7 suggestions for further EPS reform, e.g., accelerating the formulation of the regulations on the EPS, strengthening the coordination with other fixed-source systems, improving the technical support system for the EPS, establishing a database system for emission permits, building a scientific and reasonable allocation method, improving the autonomy of pollutant monitoring in enterprises, and increasing information disclosure and public participation. The results may more accurately evaluate China's EPS in China's environmental protection system, provide scientific support for the promotion and development of the ongoing EPS reform and environmental management systems. The results may promote the development of pollution prevention, and an improvement in the environmental quality in China, and offer scientific guidance and reference for other countries to implement their own EPS. • This paper summarizes evolutionary process of China's EPS over the past 40 years. • There are 4 reform achievements and 4 reform problems of current China's EPS. • This paper puts forward 7 further reform suggestions for the China's EPS. • The results offer scientific support for promotion and development of EPS reform. • The results offer scientific guidance and reference for the EPS in other countries. [ABSTRACT FROM AUTHOR]

It's critical for environmental governance to understand the effectiveness of various policy interventions as well as their working mechanisms. This paper focuses on the campaign-style enforcement, a sort of policy intervention understudied in environmental governance literature. Specifically, we study the central environmental protection inspection (CEPI), an unprecedented environmental campaign recently launched by the central authority of China. Apart from the dominant recoupling perspective that emphasized the role of environmental campaign in addressing decoupling problems, we assert in this paper that CEPI could serve as strong external stimulus that help to overcome various root problems in environmental governance system and therefore engender long-term improvements for environmental performance. Empirically, based on the city-day air pollution data, difference-in-difference (DID) model with multiple treatment periods was applied to estimate both the short- and long-term policy effects of CEPI. We found that CEPI did has positive effects on improving environmental performance. Moreover, this positive policy effect, rather than fading away after CEPI, bumped up and persisted in the aftermath of the inspection. These findings imply that campaign-style enforcement, when properly used, could be an effective tool for policymakers to improve environmental performance. • Central Environmental Protection Inspection is a new type of campaign-style enforcement in China. • DID model with multiple treatment periods is used to estimate the policy effects. • Central Environmental Protection Inspection has a positive role in environmental governance. • The positive effects bumped up and persisted in the post-inspection periods. • Campaign-style enforcement could serve as an effective tool to reform environmental governance when properly applied. [ABSTRACT FROM AUTHOR]

Effectively treating industrial SO 2 emissions depends on the synergy of different factors from the industrial SO 2 generation source to the end of treatment. Applying a whole process treatment perspective, this paper decomposes industrial SO 2 emissions into six specific driving factors in three whole process treatment dimensions (i.e. source prevention, process control, and end-of-pipe treatment), and economic scale. A temporal index decomposition analysis (Temporal-IDA), attribution analysis (AA), and spatial index decomposition analysis (Spatial-IDA) methods are then applied to quantify each dimension's treatment effect and its spatial differences. The empirical study across 30 regions in China using data from 2005 to 2015 shows that: (1) The end-of-pipe treatment is the dominant dimension for decreasing industrial SO 2 emissions, followed by process control. The contribution of source prevention to reduce industrial SO 2 emissions has begun to appear, however, there remains room for further improvement; (2) End-of-pipe treatment strength and energy intensity are key factors in reducing industrial SO 2 emissions; Inner Mongolia, Henan, and Shandong are the main contributors; (3) The treatment emphasis are different among regions; as such, there are different treatment effects across the three dimensions of the whole process treatment. Regions can be classified into four categories: the Leading type , Process-dependent type , End-dependent type, and Lagging type. Based on the empirical results, this paper identifies the policy implications of promoting whole process treatment on China's industrial SO 2 emissions. • We study China's industrial SO 2 emissions from a whole process treatment perspective. • Both temporal and spatial index decomposition analysis methods are used. • End-of-pipe treatment and process control majorly reduce industrial SO 2 emissions. • Industrial SO 2 emissions whole process treatment performances vary among regions. [ABSTRACT FROM AUTHOR]

Water, energy and carbon are three basic environmental factors that affect countries. An in-depth study of the water-energy-carbon (WEC) nexus is of great significance for realizing regional sustainable development. However, at present, research on the evaluation and prediction of large-scale WEC nexus based on multiple perspectives is not sufficiently mature, especially the prediction of WEC nexus efficiency. This study evaluates and predicts the WEC nexus efficiency in 30 regions of China based on a new comprehensive perspective. The WEC efficiency and the slack variables of 30 regions from 2006 to 2020 were calculated by using the slack-based measure model. The 30 regions were divided into 4 efficiency groups using hierarchical cluster analysis. Efficiency trends in 2006-2020 were analyzed for specific regions. The coupling interaction between the WEC nexus is studied based on the perspective of the coupling degree and coupling coordination degree. More importantly, this study is the first to quantitatively predict the WEC efficiency of 30 regions in China from 2021 to 2030, using the rank set pair analysis model. The following results were obtained in this paper. The WEC efficiency has a slow decreasing trend in 2006-2020. A total of 16.7% and 33.3% of the regions are in the extreme and high coupling coordination stages, respectively, and are mainly concentrated in the northern and southeastern parts of China. Fifty percent of the regions have moderate coupling coordination, mainly concentrated in the central and southern regions. From 2021 to 2030, the WEC efficiency of Beijing, Tianjin and Qinghai will remain at a high level; the WEC efficiency of Shandong and other regions will remain at a low level; and 70% of the regions' water efficiency will remain low. This paper has important guiding significance for promoting the regional WEC nexus balance and sustainable development of the economy, society and environment. According to the characteristics of the four efficiency groups, some valuable suggestions on regional sustainable development are proposed. [Display omitted] • The establishment of multiregional input-output index system is proposed from a new perspective. • This research divides 30 regions in China into four feature groups according to different WEC nexus characteristics. • The water-energy-carbon nexus efficiency of 30 regions in China in the next decade is quantitatively predicted. • Improving the water-energy-carbon nexus efficiency and promoting the balance of water-energy-carbon subsystems. [ABSTRACT FROM AUTHOR]

Based on the panel data of 22 inland provinces in China from 2010 to 2020, this study constructs and measures the level of rural ecological environment in China. The impact of the financial performance of green-listed companies on the rural ecological environment and its moderating and threshold effects are analyzed. The following conclusions are drawn: (1) During 2010–2020, China's rural ecological environment shows a trend of "fluctuating-decreasing-rising" with significant regional non-equilibrium characteristics. (2) The financial performance of green-listed companies has a significantly negative impact on rural ecology. This negative impact has a crucial heterogeneous feature, with a more significant negative impact in areas with a higher rural ecological environment index and less substantial performance in regions with a lower rural ecological environment index. (3) There is a significant positive moderating effect of education level and digitalization on the relationship between the financial performance of green-listed companies on the level of rural ecological development. As moderating variables, the digitalization and education level weakens the negative impact of green-listed companies' performance on the ecological environment. The positive impact of the financial performance of green-listed companies on the development level of the rural ecological environment is more vital in areas with higher per capita education levels and digitalization in rural areas. (4) There is a significant threshold effect on the financial performance of green-listed companies on the level of rural ecological development. When the financial performance of green-listed companies exceeds a particular threshold value, the impact of the financial performance of green-listed companies on the development level of the rural ecological environment is significantly positive. Based on the above findings, this paper puts forward corresponding countermeasure suggestions. • From 2010 to 2020, the development level of China's rural ecological environment showed a trend of "fluctuating-decreasing-rising," with noticeable regional differences. • The income level of green-listed companies has a negative impact on the rural ecological environment, and there is regional heterogeneity in this impact. • The rural education and digitalization levels have a positive moderating effect on the ecological environment. • It is found that the impact of green-listed companies on the ecological environment has a threshold effect. [ABSTRACT FROM AUTHOR]

The increasing volume of electronic waste (e-waste) poses significant challenges for efficient collection in China. Despite many measures were taken over the past two decades, the e-waste collection rate was still not high. To this end, the Chinese government issued a new policy, the collection target responsibility (CTR) policy. Under the CTR policy, however, it is essential for participants to know how to share the responsibility of collection and how much reasonable targets are set to ensure the efficiency of the collection models. Therefore, the purpose of this paper is to explore the determination of optimal collection targets and the corresponding performance from the perspective of responsibility sharing to support the successful implementation of the CTR. Firstly, the study focuses on participants including the government, manufacturers, and recyclers, and develops three CTR models, independent collection model, government cost-sharing model, and enterprise collaboration model. Secondly, collection target equations for each model are established by employing dynamic differential game analysis, and corresponding collection performances are derived. Thirdly, through practical case simulations, the evolution of collection performance is dynamically analyzed to determine reasonable collection targets for the three models, as 23.8%, 32.3%, and 34.4%, respectively. The findings highlight the effectiveness of CTR in improving e-waste collection targets and performance, with the highest levels attained when the collection responsibilities are shared by government cost-sharing and enterprise collaboration. This study provides theoretical support for setting reasonable collection targets under CTR, and assists decision-makers in developing targeted CTR implementation measures. • The CTR model frameworks involving the main participants are developed. • Three CTR models are constructed from the perspective of shared responsibility. • The collection target for each CTR model is analyzed and determined. • The performances of CTR models are analyzed and compared. • Differences in the CTR models from cost-sharing and enterprises collaboration are observed. [ABSTRACT FROM AUTHOR]

As digital economy develops, its impact on green innovation and energy efficiency has become the focus of current research. To explore the impact of the current development of the digital economy on the energy industry, this paper selects the parameter of green innovation resilience, analyzes the impact mechanism of green innovation resilience on energy efficiency under the shock of digital economic development, and uses relevant data from 284 cities in China from 2011 to 2019 for empirical testing. It is found that: green innovation resilience promotes energy efficiency; low level of green innovation resilience inhibits the improvement of energy efficiency, while high level of resilience promotes energy efficiency; the initial stage of digital economic development generates resource grabbing and the effect of technological constraints, which weakens the role of green innovation resilience in promoting energy efficiency. The results indicate that the resilience of the green innovation system should be strengthened in order to fully tap the potential for promoting energy efficiency; the policy orientation of "digital greening—energy efficient" should be pursued in the development of digital economy; the rational allocation of resources and the implementation of green standards should be strengthened in the process of digital economic development; and the constraints on energy efficiency improvement in the early stage of digital economic development should be broken through by accelerating the digitalization process. • Green innovation resilience can promote energy efficiency. • Early digital economy development can lead to resource grabbing and technology constraints effects. • Pursuing the policy orientation of "digital greening—energy efficient". [ABSTRACT FROM AUTHOR]

Spatial misallocation of resource elements impedes the coordination in regional co-benefit in carbon emission and pollution reduction. Guided by scope economy principles, this study aims to quantifies co-benefits and explores spatial variation patterns to facilitate mutual synergy. The findings offer valuable insights for identifying optimal focus points and shaping targeted collaborative policies. Based on the multi-source provincial panel data spanning 2000 to 2021, this paper quantitatively assesses the co-benefit through the lens of marginal abatement cost. Then, the Dagum Gini coefficient was employed to investigate the disparities at the spatial level. Additionally, geographical detector is introduced to analyze the source of disparities at the factor level. Results indicate: (1) Under joint reduction, the marginal abatement cost reduces by 57.86% and 79.97% respectively, with an overall 68.77% increase in co-benefit fluctuation. (2) Provinces with low co-benefit significantly decreased after 2007, while provinces with high co-benefit concentrated in the northwest, southwest, and east. (3) Overall disparities decreased, east-central regions hold the lowest spatial disparities in co-benefit and east-west hold the most; intragroup differences and supervariable density primarily contributes to the disparity. (4) FDI significantly influence the co-benefit over the past two decades, with spatial disparities influenced by both endogenous and exogenous factors across development stages. • Joint reduction significantly lowers the marginal abatement cost and enhanced co-benefit. • East-central regions holds the lowest spatial disparity in co-benefit and east-west holds the most. • Intragroup disparities and supervariable density primarily contributed to spatial disparity. • The interplay between internal and external factors increasingly influences spatial disparities. [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]

Global warming has accentuated the effects of extreme heat on health. Health insurance, functioning as a risk management tool, has the potential to alleviate these impacts. Consequently, this paper investigates the correlation between extreme heat events and the demand for health insurance in China. Using data from the China Health and Nutrition Survey, we have observed a substantial increase in the likelihood of residents purchasing health insurance during extreme heat events. To be specific, for every extra day of extreme heat events annually, there is a 0.3% increase in the probability of purchasing health insurance. This effect is not uniform across different demographic groups. It is particularly pronounced among middle-aged and elderly individuals, rural residents, those with lower educational levels, higher income brackets, and individuals residing in underprivileged areas with limited access to green spaces and healthcare facilities. Furthermore, our study indicates that the increased frequency of extreme heat events not only impacts individuals' physical health but also triggers negative emotions, which in turn drive risk-averse behavior related to health insurance purchases. These findings carry substantial policy implications for mitigating the economic consequences of climate change. • Extreme heat increases the likelihood of residents purchasing health insurance. • Each additional day of extreme heat boosts health insurance purchases by 0.3%. • This effect varies among different populations. • Mechanistic analyses indicate extreme heat impacting physical and mental health. [ABSTRACT FROM AUTHOR]

When evaluating climate policy, previous researchers tend to exaggerate positive employment benefits at aggregate level. Nevertheless, distributional employment at sectoral level is usually neglected, and consequently policy implementation may be impeded by the sectors with severe employment loss. Hence, distributional employment impacts of climate policy should be comprehensively studied. To achieve this target, in this paper, a Computable General Equilibrium (CGE) model is employed to simulate the Chinese nationwide Emission Trading Scheme (ETS). The CGE model results show that the ETS decreased total labor employment by approximately 3% in 2021, and then this negative impact will diminish to zero in 2024; the ETS will positively affect total labor employment in 2025–2030. The ETS increases labor employment in the electricity sectors and also agriculture, water, heat, and gas production sectors, as these sectors are complementary to the electricity sectors or do not have intensive use of electricity. In contrast, the ETS decreases labor employment in the sectors with intensive use of electricity, including the coal and petrol production, manufacturing, mining, construction, transport, and service sectors. Overall, a climate policy, which covers electricity generation only and is time-invariant, tends to have time-decreasing employment impacts. Because this policy increases labor employment in electricity generation from nonrenewable energy, it cannot help achieve low-carbon transition. [Display omitted] • This paper focuses on employment impacts of climate policy at sectoral level rather than aggregate level. • Emission Trading Scheme decreases employment in short term but increases employment in medium or long term. • Emission Trading Scheme increases employment in sectors complementary to electricity sectors. • Emission Trading Scheme decreases employment in sectors with intensive use of electricity. • A time-invariant climate policy, targeted at electricity sectors only, cannot help achieve low-carbon transition. [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]

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]

Digital finance is playing an increasingly prominent role in economic development. This paper examines the impact of digital finance on industrial structure upgrading based on panel data from 289 Chinese prefecture-level cities from 2011 to 2020. The paper adopts fixed effects, mediating effects, and spatial econometric models and the findings are as follows. First, digital finance development significantly boosts industrial structure upgrading in Chinese cities. The evidence remains valid after various robustness tests. Second, digital finance and industrial structure upgrading exhibit positive spatial spillover effects. Third, digital finance indirectly affects industrial structure upgrading through innovation, entrepreneurship and the structure of household consumption channels. Fourth, the influence of digital finance is more significant in cities with more developed economies, less financialization and lower income inequality. Finally, among the sub-indicators of digital finance, the breadth of coverage plays the most significant role, inspiring policymakers and financial institutions to speed up the digitization infrastructure in backward areas. [Display omitted] • Digital finance facilitates industrial structure upgrading in cities in China. • Digital finance has a significant positive spillover impact on industrial structure upgrading. • The impact comes from adjusting household consumption structure, entrepreneurship, and urban innovation. • The impact is more significant in cities with more developed economies, less financialization, and lower-income inequality. [ABSTRACT FROM AUTHOR]

Accurately predicting carbon trading prices using deep learning models can help enterprises understand the operational mechanisms and regulations of the carbon market. This is crucial for expanding the industries covered by the carbon market and ensuring its stable and healthy development. To ensure the accuracy and reliability of the predictions in practical applications, it is important to evaluate the model's robustness. In this paper, we built models with different parameters to predict carbon trading prices, and proposed models with high accuracy and robustness. The accuracy of the models was assessed using traditional survey indicators. The robustness of the CNN-LSTM model was compared to that of the LSTM model using Z-scores. The CNN-LSTM model with the best prediction performance was compared to a single LSTM model, resulting in a 9% reduction in MSE and a 0.0133 shortening of the Z-score range. Furthermore, the CNN-LSTM model achieved a level of accuracy comparable to other popular models such as CEEMDAN, Boosting, and GRU. It also demonstrated a training speed improvement of at least 40% compared to the aforementioned methods. These results suggest that the CNN-LSTM enhances model resilience. Moreover, the practicality of using Z-score to evaluate model robustness is confirmed. • Deep learning by combined CNN-LSTM networks for carbon price forecasting. • Hyperparameter tuning of deep learning models for improving forecast accuracy. • CNN-LSTM models outperform single CNN models and single LSTM models. • Performance metric of deep learning for abrupt changes in carbon price variation. [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]

A significant milestone in China's carbon market was reached with the official launch and operation of the National Carbon Emission Trading Market. The accurate prediction of the carbon price in this market is crucial for the government to formulate scientific policies regarding the carbon market and for companies to participate effectively. Nevertheless, it remains challenging to accurately predict price fluctuations in the carbon market because of the volatility and instability caused by several complex factors. This paper proposes a new carbon price forecasting framework that considers the potential factors influencing national carbon prices, including data decomposition and reconstruction techniques, feature selection techniques, machine learning forecasting techniques for intelligent optimisation, and research on model interpretability. This comprehensive framework aims to improve the accuracy and understandability of carbon price projections to respond better to the complexity and uncertainty of carbon markets. The results indicate that (1) the hybrid forecasting framework is highly accurate in forecasting national carbon market prices and far superior to other comparative models; (2) the factors driving national carbon prices vary according to the time scale. High-frequency series are sensitive to short-term economic and energy market indicators. Medium- and low-frequency series are more susceptible to financial markets and long-term economic conditions than high-frequency series. This study provides insights into the factors affecting China's national carbon market price and serves as a reference for companies and governments to develop carbon price forecasting tools. • A hybrid carbon price prediction model named FS-CEEMDAN-VMD-GWO-LightGBM is proposed. • Accurately predicted the national carbon price in China using multi-influence factor time series data. • Using a data decomposition and reconstruction strategy, the model's accuracy was improved. • The SHAP algorithm is used to assess the impact of various influencing factors on the fluctuations of carbon prices. [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]

Renewable energy (RE) plays a crucial role in global energy transformation, and a thorough study of the potential impact of RE on regional carbon emissions is of great significance. This is particularly relevant to China, which needs to clarify its path to carbon reduction. Using the sample data of 30 provinces in China from 2000 to 2021, this paper uses the Granger causality test to verify the causal relationship between carbon emission intensity (CEI) and other factors. It builds a mediation effect model on this basis to explore the direct impact effect and indirect transmission path of renewable energy utilization (REU) on CEI. The results show that REU has a one-way causal relationship with CEI. REU can directly and indirectly reduce CEI by improving social wealth and changing the direction of energy investment. In addition, REU indirectly increases CEI through the transmission paths of investment in the energy industry - social affluence and industrial level-social affluence. The CEI is indirectly reduced through the conduction paths of (social affluence-Urbanization rate), (Investment in the energy industry-Urbanization rate), (Industrial level-Urbanization rate), and (Industrial level-Investment in the energy industry). These conclusions will assist policymakers in exploring targeted pathways for low-carbon power development, providing a reference for strategic and sustainable carbon reduction policies. [Display omitted] • Enrich the view of renewable energy's indirect impact on carbon emissions. • Renewable energy's carbon emission reductions go beyond replacing fossil fuels. • Constructed a mediating effect model between renewable energy and carbon emissions. • Renewable energy can promote or inhibit carbon emissions through various pathways. • Research helps develop more effective renewable energy sustainability strategies. [ABSTRACT FROM AUTHOR]

The effects of global climate change and human activities are anticipated to significantly impact ecosystem services (ESs), particularly in urban agglomerations of arid regions. This paper proposes a framework integrating the dynamic Bayesian network (DBN), system dynamics (SD) model, patch generation land use simulation (PLUS) model, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model for predicting land use change and optimizing ESs spatial patterns that is built upon the SSP-RCP scenarios from CMIP6. This framework is applied to the oasis urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang (UANSTM), China. The findings indicate that both the SD model and PLUS model can accurately forecast the distribution of future land use. The SD model shows a relative error of less than 2.32%, while the PLUS model demonstrates a Kappa coefficient of 0.89. The land use pattern displays obvious spatial heterogeneity under different climate scenarios. The expansion of cultivated land and construction land is the main form of land use change in UANSTM in the future. The DBN model proficiently simulates the interactive relationships between ESs and diverse factors. The classification error rates for net primary productivity (NPP), habitat quality (HQ), water yield (WY), and soil retention (SR) are 20.04%, 3.47%, 4.45%, and 13.42%, respectively. The prediction and diagnosis of DBN determine the optimal ESs development scenario and the optimal ESs region in the study area. It is found that the majority of ESs in UANSTM are predominantly influenced by natural factors with the exception of HQ. The socio-economic development plays a minor role in such urban agglomerations. This study offers significant insights that can contribute to the fields of ecological protection and land use planning in arid urban agglomerations worldwide. • An integrated framework combining DBN, SD, PLUS and InVEST models was proposed. • Impact of natural and socioeconomic factors on ESs was determined under climate scenarios. • The spatial pattern of ESs was optimized and partitioned using DBNs. • ESs in arid oasis urban agglomerations are mainly affected by natural factors. [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]

To mitigate global climate change and achieve CO 2 emissions reduction goals, China proposed to shift to dual control of total CO 2 emissions (CE) and CO 2 emissions intensity (CEI) as early as possible. Accurately assessing provincial sectoral CE and CEI and developing reasonable regulatory strategies is a prerequisite for achieving the goal of dual control. However, there is a lack of comprehensive analysis from different perspectives of the supply chain. Therefore, this paper evaluates the CE and CEI in provincial sectors of China in 2017 from production-based and consumption-based perspectives according to multi-regional input-output (MRIO) model. Then, we analyze the supply chain of transmission sector by betweenness-based method as a supplementary perspective. The results show that: (1) The CE and CEI from different perspectives are different and can complement each other. (2) Production and distribution of electric power and heat power in Inner Mongolia (P5D24), construction in Jiangsu (P10D27), distribution of electric power and heat power in Beijing (P1D24) are the critical sectors for dual control of CE and CEI from production, consumption, betweenness-based perspectives, respectively. (3) Construction in Jiangsu (P10D27) and Shanxi (P4D27) have the highest embodied CE and CEI in China respectively. Energy and raw material sectors from upstream supply chain contribute large CE to construction sectors. This research suggests that paying attention to critical sectors from different perspectives of the supply chain and taking different measures to decrease CO 2 emissions. Taking both CE and CEI into consideration and allocating CO 2 emissions reduction pressures reasonably among provincial sectors. At the same time, taking care of relevant upstream sectors of the supply chain to help a single sector achieve CO 2 emissions reduction goals and promote China's transition to dual control of CE and CEI. [Display omitted] • Identify the critical provincial sectors from both CO 2 emissions and intensity. • Use betweenness-based results as complementary strategies. • The energy and raw material sectors contribute large CO 2 emissions to construction. • Explore dual control of CO 2 emissions and intensity. [ABSTRACT FROM AUTHOR]

The widespread implementation of feed-in tariff (FIT) policies has played a crucial role in fostering the development of wind power, with their positive effects firmly established in numerous studies. However, the impact of regionally differentiated FIT policies on the misallocation of wind power resources remains a topic of contention, with limited research dedicated to this area. This paper aims to address this gap by examining the implications of such policies on the intensive and extensive margins of wind power installed capacity in China, shedding light on the underlying mechanisms driving resource misallocation. Empirical findings indicate that, concerning the intensive margin, the policy amplifies the concentration of wind power investments in regions characterized by abundant wind resources but low electricity demand. These regions present favorable conditions for large-scale wind farms with cost advantages, consequently exacerbating the misallocation of wind power resources. However, on the extensive margin, the policy promotes the likelihood of locating small and medium-sized wind farms in regions with poor wind resources but higher tariff rates, thus partially mitigating resource misallocation. In summary, China's policy hampers wind power investments in regions characterized by high electricity demand but limited wind resources. This suggests that the negative impact on the intensive margin outweighs the positive impact on the extensive margin. The findings of this study bear significant implications for the development of renewable energy support policies, particularly in countries grappling with substantial regional disparities in renewable energy resources. • We cope with the controversial effect of FIT policies on the resource misallocation • We provide novel perspectives as the intensive and extensive margins • China's regionally differentiated FIT policy hampers wind power investments • We provide implications for countries implemented regionally differentiated FIT [ABSTRACT FROM AUTHOR]

The relationship between fiscal regimes and urban industrial pollution emissions is unclear. This paper aims to explore the effects and mechanisms of fiscal centralization on urban industrial pollution emissions and environmental quality. Using the vertical reform of environmental administrations (VREA) in China as a quasi-natural experiment of fiscal centralization, this study applies a staggered difference-in-differences (DID) model to explore the differences in industrial pollution emissions between centralization cities and decentralization cities. The main findings are: (1) VREA significantly inhibits regional industrial pollution emissions, and the reform effect increases over time. This conclusion still holds after considering a series of robustness issues. (2) Industrial sulfur dioxide (SO 2) and solid particulate emissions in the fiscal centralization cities have decreased significantly by 0.3281% and 0.2240%, respectively. However, there is no significant change in industrial wastewater discharges. (3) Environmental regulations, environmental expenditures, and pollution control investments of local governments are the main channels through which VREA reduces industrial pollution emissions. (4) The effects of VREA are more significant in central and western cities and small cities. (5) Relative to decentralization cities, centralization cities have improved air and water quality by 0.0825% and 0.1628%, respectively. These findings help to accurately assess the effects of fiscal centralization on regional environmental governance and provide a decision-making reference for further deepening environmental centralization reform in China. • The vertical reform of environmental administrations (VREA) achieves fiscal centralization in environmental governance. • VREA inhibits urban industrial pollution emissions. • Potential mechanisms include environmental regulations, environmental expenditures, and pollution control investments. • The effect of the reform varies with city location and city size. • VREA has downstream effects on regional air and water quality improvement. [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]

Eco-compensation is a type of institutional arrangement that uses economic measures to adjust the relationships among stakeholders in order to conserve and/or sustainably use ecosystem services. The externality of the value of ecosystem services is one of the theoretical bases for eco-compensation. Different types of ecosystem services are consumed by people from different regions. Some are consumed by people living where the services originate, while some are carried by rivers, wind, vehicles or other natural or manmade means to other areas. Thus, the flow and consumption of ecosystem services should be seen as the basis for establishing eco-compensation funds. This paper uses satellite images of the Zhang-Cheng area near Beijing in 2013 to discuss how to establish an eco-compensation fund for stakeholders in this area. Firstly, six important types of ecosystem services in the Zhang-Cheng area were identified based on ecological function zoning, and the value of these ecosystem services was calculated based on ecological pricing methods. Secondly, the field intensity model from physics was used to analyze where Zhang-Cheng area ecosystem services flowed and calculate how much of these services were used by other areas. Thirdly, based on this analysis and calculation, the paper proposes the rates that different stakeholders should invest in the eco-compensation fund, based on their consumption of eco-services. [ABSTRACT FROM AUTHOR]