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Urbanization and the release of carbon emission are two significant features of contemporary economic and social progress in China. However, there are few studies that consider how urbanization policy goals affect carbon emission. This paper aims to study the nonlinear effects of urbanization policy goals on carbon emission in 13 cities of the Beijing-Tianjin-Hebei region. In this paper, a multi-dimensional spatial disturbance grey model is proposed. Based on matrix perturbation theory, this paper explores the spatial perturbation bounds of the novel model and verifies that the spatial property of the model is consistent with the viewpoint of the First Law of Geography. Then, the novel model is used to predict the urban carbon emission under different urbanization policy goal scenarios. The results showed that the novel model has spatial regional correlation in spatial region prediction. With the development of urbanization level, carbon emissions show a downward trend in more than 50% of cities from 2022 to 2025. In addition, the improvement of urbanization policy goals will promote the carbon peak time of most cities. The carbon emission intensity will exhibit an inverted U-shaped trend distribution in space. The research results are conducive to providing scientific guidance for the formulation of new-type urbanization policies and helping to achieve the dual carbon goals. • A multi-dimensional spatial disturbance grey model is proposed. • The novel grey model is consistent with the viewpoint of the First Law of Geography. • The spatial distribution of carbon intensity showed an inverted U-shaped pattern. [ABSTRACT FROM AUTHOR]

• Urban green spaces have direct and indirect effects on improving residents' health. • The health benefits of urban green spaces exhibit regional heterogeneity. • Economic development weakens the health benefits of urban green spaces. • Environmental regulations can enhance the health benefits of urban green spaces. Urban green spaces have long been cherished as the "lungs of the city", it can not only improve air quality and enhance residents' health. The impact of urban green spaces on air pollution and residents' health has attracted great attention. In this paper, we select 31 provinces in China as research samples and use ArcGIS software to draw spatial distribution maps of urban green spaces, air pollution, and residents' health in China, characterizing their spatiotemporal changes in order to explore whether there is a correlation among the three. On this basis, this paper utilizes panel data of Chinese provincial-level from 2010 to 2020 and conducts empirical tests through a two-way fixed effect model and a threshold regression model. The research findings are as follows: (1) Urban green spaces not only bring environmental benefits, but also health benefits, and the health benefits are greater than the environmental benefits. (2) There is a health risk of air pollution in northern China, and the health benefits of urban green spaces are not significant. Conversely, there is no health risk of air pollution in southern China, and the health benefits of urban green spaces are significant. (3) Although environmental regulations can enhance the health benefits of urban green spaces, the role of environmental regulations in enhancing the health benefits of urban green spaces may be further weakened as the economy develops. [ABSTRACT FROM AUTHOR]

Under the background of high-quality development, the e-commerce industry needs to seek more comprehensive development, and the logistics industry should not only maintain higher efficiency, but also meet the requirements of green and low-carbon transportation. This study aims to investigate the link between the logistic density and the proportion of e-commerce transaction scale. There are few studies on how logistics density affects the development of e-commerce quantitatively. In order to solve this gap, this study establishes an impact model of high-quality growth of e-commerce, and based on Solow production model, constructs a calculation method of logistics density, and analyzes the impact mechanism of logistics density on the scale ratio of e-commerce transactions. Using the bidirectional fixed effect model, this paper makes an empirical analysis of the panel data of 31 provinces consisting of 248 observations and autonomous regions in China from 2014 to 2020. The results show that logistic density has a positive and significant impact on the growth of e-commerce, thus promoting the optimization of economic structure. The acceleration of logistics density decreases the expansion of the ecommerce. Finally, there are obvious regional differences between the development of e-commerce and logistics infrastructure in China. Finally, based on the empirical result, this paper puts forward recommendations for government and companies. [ABSTRACT FROM AUTHOR]

• Coupling coordination indicators for pollution and carbon reduction is proposed. • The first time to focus on the issue in cities along the Yellow River Basin. • "East-high and west-low" spatial differentiation characteristics of coupled degree. • "Pollution reduction is hindered and carbon reduction is lagging". • There is a phenomenon of "spatial club" clustering in the coordination degree. Collaborative efforts to reduce pollution and carbon emissions are a notable feature of the current era. Achieving the "pollution reduction" and "carbon reduction" dual-driven new development model is the inevitable requirement and significant practical measure for building a new development pattern and realizing a comprehensive green transformation of economic and social development. The synergistic effects between pollution reduction and carbon reduction (PRCR) have been demonstrated. However, the measurement and quantitative analysis of the coupling coordination degree (CCD) of PRCR have not received enough attention. Therefore, the evaluation index system was constructed based on the scientific connotation of PRCR, and the CCD of PRCR in cities along the Yellow River Basin (YRB) from 2009 to 2018 was measured quantitatively by constructing the coupling coordination model in this paper. In addition, we comprehensively investigated its spatial pattern, distribution characteristics, and evolution trend using ESDA, Kernel density estimation, and Markov chain. The primary findings can be summarized as: (1) PRCR levels and their CCD fluctuated and increased in the YRB, with "east-high and west-low" spatial differentiation characteristics, and the coupling phenomenon of "pollution reduction is hindered and carbon reduction is lagging". (2) There is a phenomenon of "spatial club" clustering in the coordination degree of PRCR in the YRB, with most cities in the downstream areas belonging to the type of high-high clustering, while the middle and upstream areas had the opposite type. (3) The CCD of PRCR in the whole and upper reaches of the YRB have transformed from low-level divergence to high-level convergence. (4) Spatial geographic factors have a significant spillover effect on the evolution of the CCD of PRCR, and there is a phenomenon of the "Matthew effect". This paper provides a comprehensive framework for analyzing the synergistic effects between PRCR, and the research findings can also provide insights for other regions. [ABSTRACT FROM AUTHOR]

• Environmental regulation affects economic growth through green innovation. • When green innovation exceeds the second threshold, the marginal of environmental regulation on economic growth effect is weakened. • The regional specific heterogeneity effect. • The panel threshold models are less commonly used in environmental research, this paper employ these to analyze. Behind the rapid economic growth, the problems of environmental pollution have gradually become prominent. Environmental regulation is an important means for the government to deal with environmental problems in economic development and promote the construction of ecological civilization. Using the provincial data of China from 2005 to 2020, this paper studies the intermediary effect and threshold effect of green innovation in the process of environmental regulation affecting economic growth. The stepwise regression model of intermediary effect shows that environmental regulation promotes green innovation significantly, which further promotes economic growth. The panel threshold regression model shows that when green innovation is below 7.984 (the second threshold), environmental regulation positively affects economic growth, and when green innovation exceeds the second threshold, their marginal effects weaken. Further research shows that there is the regional specific heterogeneity effect. This paper analysis from 4 regions of China. When green innovation exceeds a certain threshold (eastern threshold is 4.382, central threshold is 6.553, western threshold is 5.037, northeastern threshold is 5.347), it decreases the marginal impact effect each region. The research results can provide reference for the government to formulate reasonable policies to balance environment and economy. [ABSTRACT FROM AUTHOR]

In 2020, China formally proposed the goal of achieving carbon peaking in 2030 and achieving carbon neutrality in 2060. Since then, widespread attention has been devoted to determining when and how this goal will be achieved. This paper creatively puts forward the view of low-carbon digital economy from the perspective of resource flow, digital flow and energy flow, and studies the synergy effect of low-carbon digital development by constructing the synergy model of low-carbon digital development economic and social development. Based on theoretical research, this paper constructs a synergy model and evaluation index system between low-carbon digital development and economic and social development, and an empirical analysis was conducted based on data related to regional low-carbon digital development and economic and social development in China from 2014 to 2019. The empirical results show that the development of China's low-carbon digital economy is the main driving force for future economic and social development. The effects of low-carbon digital economy on economic and social development varied across regions due to their different regional development patterns. The spatial pattern shows a trend of "high in the east and low in the west". Further, if the low carbon economy and the digital economy included in the stimulus policies can play a synergistic role, it will be able to play the greatest role in promoting economic and social development. And such a scenario is used as a practice in different regions of China in future. The research conclusion of this paper enriches the discussion on the construction of ecological civilization and the construction of a community with a common future for mankind. The conceptualized model of low-carbon digital economy and economic-social development. [Display omitted] [ABSTRACT FROM AUTHOR]

Energy plays a vital part in stimulating economic progress, and the shift towards a cleaner energy system is highly significant for ensuring the sustainable development of the economy. China's energy structure urgently needs to be transitioned. The fast advancement and implementation of artificial intelligence (AI) has provided a new and important tool for promoting the transition of energy structure. So, what is the relationship between the application of artificial intelligence and the transition of the energy structure? This research introduces artificial intelligence into the energy sector, focusing on the relationship between artificial intelligence and energy transition. Since nonlinear models are better able to study the complex effects and phase differences of artificial intelligence. Using China's provincial panel data spanning from 2006 to 2019, this study employs nonlinear modeling to explore the stage differences in the process of AI in facilitating energy structure transformation. This paper derives the following findings based on empirical research. First, there is a U-shaped relationship between artificial intelligence and the transition of energy structure. Specifically, before the inflection point, the initial application of artificial intelligence, artificial intelligence may adversely impact energy transition. When the inflection point is passed, AI will help facilitate the energy transition. Second, the U-shaped relationship between AI and energy transition is more pronounced in coastal and non-resource-based regions. Third, energy intensity, government investment in science and technology, and informatization will moderate the U-shaped relationship between artificial intelligence and energy transition, changing the steepness of the original U-shaped relationship and even reversing it. Hence, it is imperative to effectively utilize the technological benefits of artificial intelligence through the development patterns and distinctive features of different regions, thereby facilitating the smooth transition of the energy structure. [Display omitted] • The role of artificial intelligence in the energy transition process is studied. • Stage differences in the role of AI are analyzed. • The nonlinear relationship between AI and energy transition is investigated. • Provide insights into the factors affecting the relationship between AI and energy transition. • This research helps the government to advance the energy structure transition. [ABSTRACT FROM AUTHOR]

• Decoupling state of ecological footprint in 30 province of China is analyzed. • There are four decomposition indicators for decoupling. • Technological factors, and economic factors are important factors driving decoupling. • The methods of realizing environmental sustainability are discussed. Nowadays, economic development and ecological environment protection are difficult to synergize, which poses a challenge to global sustainable development. This paper uses the Tapio decoupling model to evaluate the decoupling between ecological footprint and economic growth, and uses the Logarithmic Mean Divisia Index (LMDI) decomposition methods to identify the driving factors of decoupling at national and provincial levels. There are four driving factors: industrial structural, technological innovation, economic development, and population size. It is found that: (1) The ecological footprint of 28 provinces show an upward trend, with an average increase of 40.26%. Among them, the ecological footprint of three provinces in the northwest region increased by more than 100%, and there is an urgent need to reduce natural resource consumption and ensure resource sustainability; (2) The number of provinces with good decoupling show a change of first declining and then rising. Moreover, the spatial distribution characteristics of the decoupling state are obvious, with the northeastern region in negative decoupling; and (3) Technological innovation plays a positive and leading role in decoupling, with a contribution rate of 0.5402. However, economic development inhibits decoupling, with a contribution rate of 0.3829. According to the results, this paper suggests countermeasures and approaches to promote the decoupling of ecological footprint and economic growth, and establishes three key regional concerns. It provides a basis for further analysis of environmental governance in China. Not only that, the regulatory measures and methods proposed in this study will also help promote the decoupling process of other developing countries in the world. [ABSTRACT FROM AUTHOR]

This paper takes 31 provincial regions in mainland China as the research object, measures the development level of digital finance through digital inclusive finance index, empirically analyzes the development of digital finance on regional economy, and further analyzes the breadth, depth and service support of digital inclusive finance. Research shows that digital finance can promote regional economic development, and digital finance also has a positive impact on economic development in terms of breadth, depth and service support. [ABSTRACT FROM AUTHOR]

• A composite index named GLCDES is developed to dynamically assess the level of Green Low-carbon Circular Development. • The combined-assignment VIKOR model based on game theory is developed to thoroughly estimate the construction level of GLCDES. • Southwest China's Green Low-carbon Circular Development Economic System construction level is examined from 2012 to 2021, showing how the long-side principle governs each region's value. • Selecting and strengthening the long side in combination with its reality is an effective way to improve the construction level of GLCDES. Emission peak and carbon neutrality are critical components of China's overall ecological civilization, and the establishment of a sound Green Low-carbon Circular Development Economic System (GLCDES) is a fundamental countermeasure for solving China's resource, environmental, and ecological problems. This paper used the new development concept as entry points to establish a comprehensive evaluation index system encompassing six subsystems: development dynamics, production and living systems, green benefits, low-carbon benefits, circularity benefits and socio-economic benefits. The combined-assignment VIKOR model, based on game theory, was used to thoroughly estimate the construction level of GLCDES by combining panel data from four southwestern provinces, including Chongqing, Sichuan, Guizhou and Yunnan, from 2012 to 2021. The study discovered that: the construction level of GLCDES in all four southwestern provinces increased over the past ten years, but the increase was not significant, the four development effectiveness indices, including green, low-carbon, circularity and socio-economic, were significantly improved, the development dynamics index was not significantly enhanced, and the index of production and living systems declined in fluctuation from year to year. The construction level of GLCDES between regions was very uneven and can be divided into two echelons, with the gap between Chongqing and Guizhou being particularly obvious. Regions can be categorized into three major categories based on the number of dominant subsystems. According to the above results, the total value of the dynamic comprehensive evaluation of each region is governed by the principle of the long side, which is an effective way to improve the construction level of GLCDES by selecting and strengthening the long side in combination with its reality. [ABSTRACT FROM AUTHOR]

A sustainable economy through the rational spatial expansion of coastal areas is an increasingly essential global topic. This paper aims to explore the mechanism by which supporting cities influence the spatial expansion of economic development zones (EDZs) in 264 coastal EDZs of China during 1995–2020. Meanwhile, the effects of variations in the distance between supporting cities and coastal EDZs and different city scales are considered. The results provide new explanations for realizing the sustainable development of the coastal economy by planning EDZs at a suitable location from the supporting city. The supporting cities' economic strength can significantly contribute to the spatial expansion of coastal EDZs. The influence shows a distance decay law when the distance is less than 47.692 km, between 47.692 and 58.039 km, and greater than 58.039 km, with impact coefficients of 0.479, 0.393, and 0.212, respectively. The average spatial scale of coastal EDZs varies in an "inverted U–shape" with increasing distance. The average spatial scale of the urban general radiation type (47.692 km ≤ distance <58.039 km) is the largest. Supporting cities' scale affects the economic radiation range of supporting cities. The results suggest three implications for the future development of coastal EDZs. 1) Building the EDZ while incorporating practical development needs; 2) Scientifically planning the spatial layout of EDZs; 3) The synergistic development of supporting cities, transportation hubs, and EDZs. [Display omitted] • Supporting cities can promote coastal economic development zones' expansion. • The contribution of supporting cities to zone expansion shows a distance decay law. • The average spatial scale of coastal zones shows an "inverted U-shaped" change. • Supporting cities scale affects the economic radiation range by supporting cities. [ABSTRACT FROM AUTHOR]

• Construct the uncertain multi-stage nonparametric technologies. • Perform efficiency analysis at each level from national and regional viewpoints. • The number of efficient units and innovation efficiency is higher under nonconvex. • Efficiency of the technology development is higher, especially under nonconvex. As an important role in China's economy, the high-tech industry should evaluate and analyze the innovation activities from a systematic perspective to obtain innovation efficiency, thus improving high-quality development. In fact, for the efficiency assessment system of the high-tech industry, the indicators information is imprecise due to the inherent randomness, measurement error, incomplete information on economic phenomena, etc. However, few studies to date have considered and described the imprecise information. Moreover, data indivisibilities and the economic scale of the high-tech industry cause nonconvex technologies. However, little research has been conducted using the nonconvex measure to estimate innovation efficiency. In this regard, this paper is the first to combine convex and nonconvex technologies with uncertainty theory in a multi-stage system to compare the efficiency of the high-tech industry. More specifically, this paper first divides the innovation activities of the high-tech industry into a technological development stage and an economic transformation stage from the perspective of the innovation value chain. Second, uncertainty theory is adopted to express imprecise information, and uncertain multi-stage nonparametric frontier techniques are constructed to measure the innovation efficiency of the high-tech industry. Third, the high-tech industrial efficiency evaluation based on two-stage nonparametric techniques is established. Empirical results indicate that efficiency in the technology development stage is higher, particularly under nonconvex. Furthermore, the inefficiency of the whole system is mainly due to the inefficiency in the economic transformation under nonconvex, while under convex, the primary reason becomes the joint inefficiency of the two stages. [ABSTRACT FROM AUTHOR]

National civilized city selection activity organized by Chinese government is a kind of policy taking both environmental protection and economic growth into consideration. It is of great importance to high-quality economic growth of China. This paper mainly selects data of 280 at and above prefecture-level cities in China from 2005 to 2016 and combines multi-stage difference-in-differences model to test the impacts of national civilized city selection on green total factor productivity (GTFP). The empirical results show that national civilized city selection activity can significantly promote the GTFP and have strong robustness. And the positive influence can be achieved through the mechanism of city innovation. In addition, heterogenous effects exist under different city administrative hierarchies and different regions. Finally, conclusions of this research for one thing provide empirical evidences for mutual development of economic growth and environmental protection; for another thing, this paper enriches policy evaluation researches of national civilized city by including environmental factors in total factor productivity calculation. • City carbon emission is used in evaluating green total factor productivity (GTFP). • National civilized city selection has positive impact on GTFP and is robust. • City innovation plays a vital role in the process of the policy promotes GTFP. • The policy effect varies in different city administrative hierarchies and regions. [ABSTRACT FROM AUTHOR]

The green transformation of economic growth mode is one of the keys to promote high-quality development. This paper starts with the collaborative agglomeration of manufacturing and producer services, demonstrates the impact of collaborative agglomeration on industrial pollution emission through theoretical analysis, and then uses panel data of 285 prefecture level cities in China from 2004 to 2019 to verify the relationship between them. The results show that collaborative agglomeration significantly increased industrial pollution emission, but the effect mainly existed in small and medium-sized cities, cities with more development zones, cities with provincial high-tech industrial parks and the observation range from 2009 to 2015. The results of subdividing producer services show that transportation, warehousing and postal services, finance, information transmission, computer services and software industries have intensified industrial pollution emission in the collaborative agglomeration with the manufacturing industry. Mechanism analysis shows that collaborative agglomeration fosters the city's "low-level innovation preference" and promotes the expansion of the number of enterprises characterized by the entry and extension of the duration of highly polluting enterprises. It objectively forms a "quantity-priority orientation", thus increasing industrial pollution emission. The above conclusions mean that the development of urban industry at this stage should be based on quality and efficiency, rather than pursuing the disordered expansion of quantity. This paper provides beneficial policy implications for reducing local governments' blind behavior and awakening the awareness of environment-friendly economic growth. • Collaborative agglomeration increases industrial pollution emission. • The effect of emission increase varies with different urban and industrial characteristics. • "Low-level innovation preference" and "quantity-priority orientation" are important mechanisms. • The entry and long-term existence of high polluting enterprises led to "quantity-priority orientation". [ABSTRACT FROM AUTHOR]

High-quality economic development focuses on achieving effective qualitative improvement and reasonable quantitative growth in the economy, which is the essential way for China to achieve sustainable development. This paper aims to investigate the role of financial development in the impact of foreign direct investment on high-quality economic development. GDP and green total factor productivity are used to measure the quantity and quality of economic development, respectively. We construct benchmark panel regression models, nonlinear interaction term models, and panel threshold models to examine the threshold effect of FDI on high-quality economic development based on the scale, structure, and efficiency of financial development. A series of tests are conducted to check the robustness of the estimates. Our results show that green total factor productivity in China is primarily driven by green technology progress. Additionally, foreign direct investment has a positive impact on China's high-quality economic development, with a threshold effect and nonlinear characteristics. Specifically, the scale of financial development affects the influence of foreign direct investment on the quantity of economic development, while the efficiency of financial development affects its influence on the quality of economic development. Furthermore, the structure of financial development affects both the quantity and quality of economic development. This study presents novel findings that contribute to understanding the role of financial development in the impact of foreign direct investment on high-quality economic development. Likewise, our research has implications for achieving high-quality development. The introduction of foreign direct investment under the high-quality development of the economy should comprehensively consider financial development. • The impacts on high-quality economic development of financial development and FDI were discussed. • The scale, structure and efficiency of financial development were considered. • Both quantity and quality of economic development were focus on. • The green total factor productivity in China was measured. • Policy implications of introducing FDI in China were proposed. [ABSTRACT FROM AUTHOR]

Exploring multi-goal sustainable development paths is a global concern. To date, little is known about the characteristics of and logic behind the evolution of China's land use policies (LUPs), especially when they are linked to China's governance philosophy of an ecological civilization (EC). An EC is a unique development concept in China that emphasizes human-nature coexistence alongside economic progress. Therefore, we examine the evolutionary process of China's LUPs in the context of an EC. We identify meaningful shifts that have occurred in those policies, as well as reveal the logic behind the changes. Based on staged text mining of 220 national LUPs initiated in China between 1986 and 2021, by disclosing the changes in the number, foci, goals, concepts, measures, and reform methods of LUPs, this paper provides an overview and four-dimensional deconstruction of the country's LUP evolution in the context of an EC. Three major findings emerge from text mining. First, China's LUP has evolved through three stages, with modifications in the number, dominant foci, and themes of the policies across each stage. Second, comprehensive and significant alterations have transpired in the orientation, goals, concepts, measures, and reform approaches of the policies. Third, the transformation in LUP has transpired centering on four dimensions: improving economic efficiency; balancing production, living, and ecology; promoting social equity; and conserving ecology. These four aspects accord with four governance concepts of an EC—efficient development, symbiosis of humans and nature, social harmony, and green development. We also discuss how China's LUP evolution offers a valuable case for exploring sustainable development at a global level. [Display omitted] • Ecological civilization (EC) and land use policies (LUPs) are interactive in China. • Key changes of China's LUP are tracked by text mining. • An overview and deconstruction of China's LUP evolution are provided under an EC. • Four concepts of an EC are matched with four evolutionary benchmarks of LUP. • China's LUP provides a case for exploring multigoal sustainable development. [ABSTRACT FROM AUTHOR]

Under the background of the gradual scarcity of terrestrial resources and the increasingly fierce competition for global marine resources, the task of green development of marine economy and green transformation of marine industry is imminent. Carbon finance is a product of low-carbon economic development and a derivative of green finance. It is an effective way to alleviate the global climate crisis and promote the transformation of the global economy to a low-carbon economy to achieve sustainable development. Studying the mechanism of carbon finance on the development of marine economy will help to grasp the influencing factors of the green transformation of the marine industry in an all-round way, better promote the sustainable development of China's marine economy, and realize the strategy of marine power at an early date. Based on this, this paper selects China's data from 2006 to 2020, and uses the AHP-entropy method to select 26 indicators from five levels: economic growth, energy conservation and emission reduction, marine ecology, structural adjustment and scientific and technological innovation to construct a comprehensive evaluation index system for the green transformation of China's marine industry. Based on the PLSR model, the impact of carbon finance on the green transformation of China's marine industry is empirically analyzed, and the results show that: (1) The comprehensive score of China's marine industry green transformation from 2006 to 2020 fluctuates and rises: from 2006 to 2009, the comprehensive score of China's marine industry green transformation is low, and the transformation effect is not obvious. From 2009 to 2012, the comprehensive score of green transformation of the marine industry improved significantly. From 2012 to 2018, the comprehensive score of China's marine industry green transformation fluctuated little and showed a slow growth trend, while China's marine economic transformation grew steadily at a low speed. In 2019–2020, due to the impact of the epidemic, the speed of transformation has decreased again. (2) The carbon ratio and the green credit balance of commercial banks have a role in promoting the green transformation of China's marine industry, while the carbon trading volume and carbon intensity have a restraining effect on the green transformation of China's marine industry. From the perspective of effect, carbon intensity has the strongest effect, followed by carbon ratio, carbon trading volume is slightly weaker, and the role of green credit balance of commercial banks is the weakest. Based on the research conclusions, relevant policy recommendations were put forward. [ABSTRACT FROM AUTHOR]

The coordination relationship and the balance of development between green finance and environmental performance are crucial to guaranteeing sustainable development under circumstances of economic transition. The current paper demonstrates the construction of index systems pertaining to green finance and environmental performance. Based on a panel dataset of 30 Chinese provinces from 2008 to 2019, the coupling coordination degree model, spatial autocorrelation model, and spatial panel model are used to analyze the spatial-temporal characteristics and driving factors of the coordinated development of green finance and environmental performance across the country. The results show that, first, an overall upward trend in the green finance index appeared, with most high-value areas located in the eastern regions. In terms of environmental performance, the number of provinces with efficient environmental performance values rose from 3 to 17. These provinces were mainly distributed in the eastern and central regions. Second, the coupled coordination of green finance and environmental performance rose from mild incoordination to primary coordination during the study period, with marked spatial autocorrelation and a downward trend from east to west. Finally, industrial structure, economic development level, and environmental regulations were found to positively impact the coordinated development of green finance and environmental performance, while population density exerted an inhibiting effect on it. These effects differ across regions. The paper concludes with several policy implications, offered to guide the coordinated development of green finance and environmental performance. [Display omitted] • The provincial green finance and environmental performance are calculated. • The coordinated degree of green finance and environmental performance (GFEP) is estimated. • The driving factors of GFEP are identified. [ABSTRACT FROM AUTHOR]

In recent years, countries have actively promoted green economic transformation. Formulating reasonable and effective environmental regulation policies is an important way to realize this transformation. Based on a policy of raising standard sewage charges in China, this paper selects the panel data of 30 provinces from 2000 to 2018 and adopts the multi-time Differences-in-Differences (DID) method to empirically examine the effect of raising environmental costs on industrial green total factor productivity (GTFP). This paper finds that industrial GTFP is significantly increased by raising standard sewage charges. The conclusion is still valid after alleviating the endogenous problem and conducting robustness tests. The policy gives a boost to industrial GTFP in Eastern and Western regions, but not significantly in Central regions, according to the heterogeneity test. Further analyses of its transmission process reveal that raising environmental costs can promote industrial green growth, mostly via technological and structural effect. As a result, if all provinces can optimize and upgrade their industrial structures and improve their levels of technological innovation when faced with increasingly strict environmental regulations, they will be able to better change the model of economic growth and realize green industrial development. [ABSTRACT FROM AUTHOR]

• The score function is proposed for hesitant Fermatean fuzzy set. • Unify the framework of Regional Green Development Level Evaluation. • Improve MULTIMOORA method is proposed with hesitant Fermatean fuzzy information. • Level Difference Maximization Method to combine subjective and objective weights. • Case study of RGDL is presented to show the potentiality of the developed method. Economic green development has received increase attention. However, the uncertainty decision processes in the development of green economic growth has brought challenges to the evaluation, which leads to the evaluation index system has not yet reached a consensus. In order to solve the above problems, this paper, based on the established and developed regional green development level evaluation (RGDLE) system in existing literature, employed improved MULTIMOORA group decision model under the hesitant fuzzy Fermatean environment (HFFS-MULTIMOORA) and an innovative weighting method to develop the RGDLE process. This evaluation framework describes the complexity of the RGDLE process. The Level Difference Maximization Method to combine the average-based subjective weight-determining method and the Shannon-entropy-based objective weight-determining method is developed to fit RGDLE problems with cognitive complex information. This innovative index system and HFFS-MULTIMOORA method based group decision-making framework is further applied to evaluate the green development level of five provinces and municipalities along the Yangtze River Economic Zone, China. Results showed the optimal green development levels ranking of the five alternative provinces and municipalities of the Yangtze River Economic Zone, China. Moreover, the effectiveness and feasibility of the model framework was verified by robustness and comparative analysis between the existing method. This paper contributes not only to the literature on RGDLE but also to giving decision-makers and researchers inside and outside China valuable inspiration and references for improving the evaluation efficiency and giving policy suggestions. [ABSTRACT FROM AUTHOR]

• The impact of economic growth pressure on energy efficiency improvement is discussed. • Economic growth pressure has hindered the improvement of energy efficiency. • Heterogeneity effects exist in individual dimension and temporal dimension. Economic growth target management has been a typical feature of Chinese governments at all levels for a long time in the past decades. Based on a panel data of 188 Chinese cities, this paper examines the impact of pressure brought by economic growth target on energy efficiency improvement. The results suggest that economic growth pressure has hindered the improvement of energy efficiency. For every unit of increase in economic growth pressure, the improvement indicator of energy efficiency will decrease by 3.3%. This finding is robust, after replacing explained variables and core explanatory variables, no substantial changes are found. Sub-sample regression confirms the existence of heterogeneity effects in individual dimension and temporal dimension. Finally, by summarizing existing studies, this paper finds that the investment imbalance effect, the hindrance effect on industrial structure upgrading, and the crowding-out effect on innovation are three important ways for economic growth pressure to restrain the improvement of energy efficiency. Our findings are helpful to understand the role of the government's economic growth target management in resource allocation and energy utilization and provide a certain practical reference for China to promote high-quality economic development. [ABSTRACT FROM AUTHOR]

Promoting sustainable development in resource-based cities is required to accelerate transformative economic development, which also can promote harmonious development and accelerate progress of industrialization while playing a critical role in China's urbanization. However, the role of regional sustainable development plans within resource-based cities is unclear. This paper selected 87 resource-based cities as the treated group, matching propensity scores of city characteristics on a total of 253 cities in China from 2008 to 2018. The paper used the difference-in-differences method to evaluate the impact of the implementation of the "National Plan for Resource-based City Sustainable Development (2013-2020)", measuring six years before and five years post-planning implementation. We found: (1) The implementation of the plan has promoted economic, social, and ecological transformation by 19.6%, 55.4% and 74.5% respectively (p < 0.01), but there appeared to be no additional effects on sustainable utilization of resources. (2) Among driving factors, market development affected all forms of transformation the most. (3) The impact of this transformation varied by stages of urban development according to the full life cycle of the resource-based city and its local resources. Specifically, the transformation effect of the growing type city in economic, social, ecological and resource transformation was the strongest among that of all type stages. • Regard pilot policy of Resource-based City Sustainable Development as a quasi-natural experiment. • Employ a differences-in-differences method with panel data of 253 cities in China from 2008 to 2018. • Evaluate policy effects upon resource-based city sustainable transformation. • Exploit drive mechanism and market development is an important driving factor. • Transformation effects vary from stages of urban development. [ABSTRACT FROM AUTHOR]

It is of equal importance to improve the efficiency of environmental protection enterprises (EPEs) and polluting enterprises (PEs) for Environmental Protection and Green Development, which is a micro-foundation for China's economic transformation and high-quality development. This paper redefines the efficient frontier of enterprises, distinguishing between "absolute technical efficiency" (ATE) and "relative technical efficiency" (RTE), and conducts two-dimensional measurements and dynamic comparison to examine the technical efficiency characteristics of China's EPEs and PEs listed on the A-share market, based on the stochastic frontier analysis (SFA) method. The results demonstrate that, first, the ATE of EPEs exhibits a reverse upward trend, while the ATE of PEs and A-share enterprises as a whole is declining simultaneously. Second, in contrast to the shrinkage of the ATE and RTE of PEs, the efficient frontier of EPEs has experienced rapid expansion. Third, capital utilization efficiency, rather than economies of scale effects, appears to be the main obstacle impeding the technical efficiency performance of EPEs. Therefore, improving the capital utilization efficiency and the extent of coupling and coordination between capital and labor is the key to promoting the technical efficiency of EPEs. Fourth, targeted government subsidies and tax refunds for EPEs need to be improved and an external evaluation mechanism focusing on Environment, Social and Governance (ESG) rating needs to be strengthened. Consequently, it is essential to promote the combination of top-down targeted policy support and multi-dimensional external evaluation to guide capital flows and achieve their efficient utilization, which is also the basis of the environmental protection industry's high-quality development. • First, the ATE of EPEs exhibits a reverse upward trend, while the ATE of PEs is declining simultaneously. • Second, in contrast to the shrinkage of the ATE and RTE of PEs, the efficient frontier of EPEs has experienced rapid expansion. • Third, capital utilization efficiency is the main obstacle impeding the technical efficiency performance of EPEs. • Fourth, targeted government subsidies and tax refunds for EPEs need to be improved and an external evaluation mechanism needs to be strengthened. [ABSTRACT FROM AUTHOR]

To perform better future trend prediction for an economy-energy-environment (3E) system and address the shortcomings of traditional multivariate grey models, this paper introduces a spatial correlation term into the multivariate discrete grey model, thus creating the SLDGM(1,n) model, and improves the final calculation of the model according to the priority of new information. The validity of the SLDGM(1,n) model is assessed using data from the 3E system in North China, and the SLDGM(1,n) model is applied to predict the future trends of the 3E system in North China. The following conclusions are obtained. First, the introduction of the spatial correlation term and the improvement of the final calculation method are reasonable; the prediction accuracy of the multivariate grey model is improved, and multiple systems are modeled simultaneously. Second, the SLDGM(1,n) model calculates the spatial spillover effect, and according to the simulation results for North China from 2010 to 2019, Hebei's energy consumption and carbon emissions are subject to the largest influence from other provinces, while its economic development level is subject to the smallest influence, and the carbon emissions of Shanxi and Inner Mongolia are subject to a negative spatial influence effect. Third, the prediction results indicate that under the effect of spatial correlation, the energy consumption of all five provinces in North China will continue to rise; the carbon emissions of Beijing will gradually decline while the carbon emissions of the other four provinces will all gradually rise, and the per capita GDP of the five provinces is expected to increase by more than 50% by 2025. [ABSTRACT FROM AUTHOR]

Prior studies have explored the relationship between public environmental concerns and air pollution, but the interaction effects and spatial factors under a systematic framework have been ignored. This paper investigates the interaction effect between public environmental concern and air pollution, moreover, a spatial panel simultaneous equation approach is employed to reduce the endogenous interference and the potential impact of spatial factors. Based on the balanced panel data of 269 prefecture-level cities in China from 2011 to 2017, we find that a 1% increase in public environmental concern will lead to a 0.049% decrease in PM 2.5 concentration, while a 1% increase in PM 2.5 concentration will lead to a 1.398% increase in public environmental concern. Meanwhile, there is a significantly spatial spillover effect of both public environmental concern and air pollution to the surrounding areas. Furthermore, our findings suggest that public environmental concern reduces air pollution by promoting government environmental regulation, and air pollution promotes public environmental concern by threatening the health of the residents. In addition, the results of heterogeneity analysis show that the interaction effect of public environment on air pollution significantly differs across regions with different heating characteristics and economic development levels. Practicable policies to promote favorable feedback on public environmental concern and air pollution are suggested. [ABSTRACT FROM AUTHOR]

• Constructing a new welfare function considering economy, equity and ecology. • Optimizing carbon emission pathways from multiple perspectives. • Focusing on the emission pathways in China achieving the ambitious targets. With the increasing climate warming, reducing carbon emissions has gradually become a consensus around the world. However, the process of carbon emission reduction will inevitably lead to the transformation of economic structure, industrial structure and energy structure, which will bring huge changes in economic output, employment and other aspects, thus affecting the overall social welfare and equity. Therefore, it is particularly important for each country to determine a scientific and effective carbon emission pathway which take into account both social development and climate targets. As the largest carbon emitter, China has put forward the targets of carbon peak and carbon neutrality. In this regard, the corresponding carbon emission reduction scenarios are designed according to the new situation of China's emission reduction in this paper, firstly. Furthermore, under the premise of maximizing social welfare, an optimization model which integrating economic growth-equity-environment is developed to determine China's emission pathways under different scenarios from 2020 to 2050. Besides quantitatively showing the future total amount and peak value of carbon emissions under different scenarios, the results can also identify its evolution pathway over time. Therein, the peak under most scenarios will concentrate in 2025–2030, which is about 10.7 to 11.8 billion tons. With the increasingly stringent constraints on carbon emission reduction, the cost of emission reduction will increase correspondingly, but the overall social welfare will increase slightly. Finally, our findings provide practical guidance on achieving carbon emission reduction and enlightenments on policymaking. [ABSTRACT FROM AUTHOR]

[Display omitted] • A new spatial autoregressive threshold panel model and its estimation method are proposed. • PM 2.5 concentration in adjacent provinces increases 1% can lead to that in observing province increases 0.7678%. • The influence effects of socioeconomic and climatic factors on PM 2.5 are different at low and high economic levels. • Applying nonlinear spatial econometric techniques in environment research. Reducing PM 2.5 is an important way to ameliorate air quality. Research on driving factors of PM 2.5 can provide empirical support for controlling cross-regional linkage air pollution. In this paper, we first propose a new spatial autoregressive threshold panel model and its estimation method, and then apply this methodology to study influencing elements of PM 2.5 using the panel data of China during 2000–2019. The results reveal that China's provincial PM 2.5 has a significant positive spatial spillover effect, and its major driving factors have significant two regimes threshold characteristic when economic development is divided into low and high levels. Specifically, (1) PM 2.5 concentration in adjacent provinces increases 1% can lead to that in observing province increases 0.7741%. (2) The positive impacts of population size, energy structure and humidity on PM 2.5 are significant at low economic level, and become not significant at high economic level. (3) The influence of industrialization, economic development, energy intensity, urbanization and wind speed on PM 2.5 in two regimes is significantly positive, and elasticity coefficients of industrialization and economic development decrease with improvement of economic level while energy intensity, urbanization and wind speed are on the contrary. (4) The influence of possession of civil vehicles on PM 2.5 changes from negative to positive as economic level increases. (5) Temperature has no significant effect on PM 2.5 concentration. (6) The influence of precipitation on PM 2.5 is significantly positive in regime II and not significant in regime I. Therefore, local governments should strengthen cooperation with adjacent provinces and jointly adopt effective measures to cut down on PM 2.5 pollution. The provinces with low economic level should accelerate economic transformation, improve industrial production efficiency, optimize energy structure, and advocate green and low-carbon lifestyle. The provinces with high economic level need to further expand consumer demand, actively develop tertiary industries, promote new energy vehicles and vigorously develop public transport. [ABSTRACT FROM AUTHOR]

• The island development of functional polycentricity was lagging than that of the morphological dimension. • Spatial regression model performs well in fitting the association between polycentric urban variables and island landscape changes. • The effects of dual polycentric urban indicators on island landscape changes varied spatially and temporally. • Polycentric urban development generally contributed to fragmented and complex island landscape patterns on the periphery areas of subcenters and reclamation. Polycentric urban development has become popular worldwide as expected to generate greater agglomeration externality and facilitate socioeconomic achievements. Despite much insightful work on urban polycentricity in coastal agglomerations or megacities, few studies have focused on how polycentric urban development affects landscape sustainability in vulnerable island cities. This paper characterized the urban polycentricity from the perspective of morphological and functional dimensions during 1990–2020 in Yuhuan island city, China, and quantified the association between polycentric urban variables and island landscape changes by spatial regression. The results showed that there was a mismatch in development between the morphological and functional polycentricity, in which the functional dimension was lagging. In response, island landscape patterns became fragmented and scattered. With the application of GWR models, the effects of two polycentric factors on island landscape changes varied spatially and temporally. The stronger relationships between them were identified in regions where more heterogeneous patterns were presented, such as the subcenters and their surroundings and reclamation areas. These trends were mainly attributed to industrial suburbanization and the development of new economic zone and Damaiyu port. Our findings call for a more balanced functional urban polycentricity; and local-specific landscape effects should be scheduled in island planning practice and sustainable development. [ABSTRACT FROM AUTHOR]

Financial agglomeration is a key way to promote the green transformation of the global economy and environmental governance. The existing literature mainly analyzed the impact of financial agglomeration on economic development, but rarely examines its comprehensive impact on economic growth and environmental governance considering spatial spillover effects. Based on the perspective of spatial spillover effects, this paper uses panel data of 285 cities above the prefecture-level in China to examine the impact and mechanism of financial agglomeration on green development. The results show that: (1) During the study period, financial agglomeration and green development in China are significantly different in directions of spatial distribution and expansion, but the spatial correlation between the two is relatively high. (2) Financial agglomeration can exert significant spatial spillover effects on green development. (3) Financial agglomeration has more obvious positive spatial spillover effects on green development of cities in the servitization stage or with high administrative level. (4) Industrial structure upgrading effect, labor upgrading effect and technological innovation effect are the main paths that financial agglomeration affects green development. The research results can provide a new perspective and approach to promote the green transformation of economy and sustainable development of the world. [ABSTRACT FROM AUTHOR]

• Eco-economy coupling coordination (CCD) index at county level in was evaluated. • Obvious spatial agglomeration of eco-economy CCD index in north China was found. • The driving factors of eco-economy CCD index was studied by geodetector. • Terrain has the greatest influence on eco-economic coupling, then is transportation. Coordinating ecological and socioeconomic development is the only way to achieve regional sustainability. In this paper, the total output value of ecosystem services was selected to evaluate the ecological environment, and socioeconomic indicators were selected to evaluate socioeconomic development. The coupling coordination degree (CCD) between the ecological environment and economy of counties in northern China was evaluated by combining an entropy method and a coupling coordination model. Spatial autocorrelation and a geographical detector model were used to reveal the spatial agglomeration characteristics and factors that influence the coordination degree of the ecological–economic system in northern China. Results showed that, in 2019, most counties were in the ecological–economic transition development stage. Among them, 321 counties had a CCD index between 0.4 and 0.5 (basic coordination stage); 209 counties had a CCD index between 0.5 and 0.6 (primary coordination stage); and 77 counties had a CCD index between 0.6 and 0.8 (moderate coordination stage). The global Moran's I was 0.349, indicating that there was spatial agglomeration of ecological–economic coupling coordination at a county level. Low-low clusters were mainly found in the central and eastern central part of the study area, and high–high clusters were mainly found in northern Hebei province, Shandong peninsula, and northern Henan province. The factors that influenced the CCD index, ordered from the largest to the smallest, were landscape, terrain, traffic, and climate factors. The interactions between driving factors showed nonlinear and bilinear enhancement. The findings show that the coordination of socioeconomic and ecological development in northern China can be further improved. Relevant policies should emphasize the local ecological advantages, promote the transformation to ecological industrialization, and encourage ecologically and economically balanced development. [ABSTRACT FROM AUTHOR]

The 2030 Agenda for Sustainable Development stipulates 17 Sustainable Development Goals (SDGs). The implementation of this agenda will mobilize countries worldwide to incorporate the SDGs into their national development strategies. The agenda does not specify how these goals are interconnected, thus limiting their implementation. In addition, air quality affects human life and plays a vital role in achieving these SDGs. Clarifying the interconnections between SDGs related to air pollution and other SDGs will accelerate the implementation of air protection and SDGs while simultaneously promoting policy coherence. In this paper, we use the latest calculation of the SDGs in China to construct national and provincial panel data to investigate the trade-offs and synergies among Chinese air pollution-related SDGs. The findings are as follows. First, most air pollution-related SDGs have synergetic relationships, except for SDG12, which has a trade-off relationship with other air pollution-related SDGs. Second, the synergies between air pollution-related SDGs and other SDGs far outweigh the trade-offs. Third, rapidly developing areas are more likely to experience a trade-off between economic development and air pollution problems. Fourth, geographic advantages in reducing air pollution, such as being adjacent to the sea, may weaken the synergies among air pollution-related SDGs and their synergies with other SDGs. These findings indicate that most air-pollution-related SDGs and interactions between air-pollution-related SDGs and other SDGs have substantial synergy; that is, measures aimed at one goal are conducive to the advancement of other goals. However, SDG12 reflects a trade-off relationship between economic development, environmental protection, and resource utilization. [ABSTRACT FROM AUTHOR]

• The EE of three urban agglomerations considering environmental benefits is calculated. • The EE of BTH, YRD, and PRD urban agglomerations exists significant differences. • The economic development and EE of BTH urban agglomeration is "inverted U-shaped". • Urbanization and energy structure have significant negative effects on EE. China's three major urban agglomerations, Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD), are expected the key areas of energy saving and emission reduction. Based on the connotation of energy saving and emission reduction, we constructed the input–output index system considering environmental benefits, and then used the SBM-Undesirable (Slack-based Measure Considering Undesirable-outputs) model to evaluate the energy saving and emission reduction efficiency (EE) of 49 cities in China's three major urban agglomerations during 2006–2018. Finally, the paper applied the spatial econometric model to explore the influencing factors of EE. The research results indicate that the overall EE across cities is relatively low, only 7 cities have been on the production frontier. The EE of China's three urban agglomerations is significant, presenting the development state of "PRD > YRD > BTH". The spatial autocorrelation of BTH urban agglomeration changed from positive to negative, the YRD urban agglomeration kept relatively stable positive spatial autocorrelation, while the spatial autocorrelation of PRD urban agglomeration was negative during the study period. The results of the spatial econometric analysis show that the relationship between economic development and EE is an "inverted U-shaped" in BTH urban agglomeration, while an "S-shaped" in YRD and PRD urban agglomerations. The urbanization and energy structure have significant negative effects on EE in three major urban agglomerations, and the effect of urbanization on EE is much greater than that of energy structure. Besides, the industrial structure has a significant negative impact on the EE of BTH urban agglomeration. The opening-up degree can significantly inhibit the improvement of EE in YRD urban agglomeration. The impact of resource endowment on the EE of three urban agglomerations is not significant. According to the empirical results, some policy commendations are proposed. [ABSTRACT FROM AUTHOR]

Rapid economic growth and social development in China have led to serious water pollution problems and water resource shortages, limiting the sustainable and coordinated development that could support both the socio-economy and water environment (WE). However, the spatial heterogeneity and evolutionary characteristics of the coordination between economic development (ED) and WE have not been adequately explored in China's provinces. In this study, we use the spatial global (local) autocorrelation and geographically weighted regression (GWR) model to explore the relationship between ED and WE subsystems and its influencing factors in China's provinces from 2010 to 2019. The main results are as follows, (a) The coupling coordination degree (CCD) between the two subsystems in southern China is higher than that of northern China. Transitional development areas have gradually spread to the middle of China, and there has been an increase trend in the number of moderate and high coordination provinces. (b) The ED-led (WE lags behind ED) type is mainly concentrated in central and eastern China, and the WE-led (ED lags behind WE) type is concentrated in the northeastern and western regions. The areas with synchronous development are relatively small in number and are mainly concentrated in east coastal China. (c) There is an obvious spatial dependence of the coordination between ED and WE from the perspective of global correlation, but this dependence is weakened with increasing geographical distance. The local mode of agglomeration shows a trend towards the evolution of high-high clustering in the eastern region. (d) The GWR analysis indicates that the factors of population density, energy consumption, fixed investment, and research and development (R&D) expenditure significantly influence the coordination between ED and WE. Fixed investment and R&D expenditure are mainly positive driving factors, while the impacts of population density and energy consumption vary among different regions as time evolves. Changes in driving force in a region can extend spatial effects to adjacent regions through the spatial transmission mechanism. Finally, we close the paper by recommending the different policy implications according to the GWR results. [ABSTRACT FROM AUTHOR]

Air pollution has become a key problem to be solved in the process of sustainable development in China. Most existing research on environmental regulation has focused on one dimension or several aspects of environmental regulation. This paper quantitatively scored environmental policies in China from multiple dimensions to construct the index of environmental regulation and used a spatial econometric model and satellite-monitored PM2.5 data for 280 cities in 2002–2016 to analyze the effects of environmental regulation on city air pollution treatment in the country. The empirical results showed that (a) there was a significant positive correlation for the spatial distribution of air pollution in China (0.87 in 2007) and the current air pollution situation was susceptible to the effects of its previous (the time lag effect of urban air pollution in eastern China is the strongest, which was 0.347); (b) environmental regulation could significantly improve the air pollution situation in the cities of northern and eastern regions; (c) the decomposition of the spatial spillover effect confirmed the role of environmental regulation in improving air quality in the region or surrounding areas. (d) we found the inverted U-shaped relationship between city economic development and air pollution in southern cities, the environmental Kuznets curve was verified; In the future, breaking the "barriers" in pollution treatment between regions and strengthening regional conversation and cooperation are effective approaches to treating air pollution. [Display omitted] • We studied the environmental regulation impacts on city air pollution in China. • We quantitatively scored environmental policies from multiple dimensions. • The evolution of city air pollution and its spatial correlation were discussed. • The heterogeneity influence and its spatial spillover effect of environmental regulation were discussed. • The nonlinear relationship between economic development and environmental protection was revealed based on EKC hypothesis. [ABSTRACT FROM AUTHOR]

• Eco-efficiency is evaluated from manufacturing and environmental protection stage. • Eco-efficiencies of two stages in most China's provinces are at a low level. • There are differences in two-stage eco-efficiency among China's provinces. • The effects of "Belt and Road" on the eco-efficiency of two stages are opposite. This paper divides the industrial eco-economic system into manufacturing stage and environmental protection stage, uses the improved metabolic GM(1,1) model and TOPSIS-DEA cross-efficiency model to evaluate the two-stage eco-efficiency of China's provinces from 2005 to 2020. On this basis, regression discontinuity is utilized to analyze the heterogeneous impact of "Belt and Road" initiative (BRI) on the eco-efficiency of industrial eco-economic system and two stages. The results show that: the eco-efficiency of industrial eco-economic system (EIES) and the eco-efficiency of manufacturing stage (EMS) have been at a relatively high level, while the eco-efficiency of environmental protection stage (EEPS) is still at a low level so far. The EIES and EMS of the provinces in eastern region are higher than those of the central, western and northeastern regions, while the EEPS of the western region is higher than that of the other three regions. The impacts of BRI on EIES and EEPS are significantly positive, while the BRI has a negative effect on EMS. In addition, there is a significant positive relationship between economic development level and EIES, EMS, and EEPS, industrial structure can promote EIES and EMS, and technological innovation has a significant positive correlation with EMS, a significant negative correlation with EEPS. [ABSTRACT FROM AUTHOR]

In recent years, China's fisheries economy has expanded dramatically. As a result, environmental pollution caused at least partially by such an expansion has endangered human health and the sustainable development of fisheries in some coastal regions. This paper establishes an indicator system for fisheries economic growth and environmental quality and evaluates the coordinated level of the two systems in 12 regions in China. Results show that i) it is necessary to expand the relative scale of fisheries economy, optimize the structure of fisheries industry, and improve the utilization capacity of pollutants; ii) the selected regions are evaluated as half each the fisheries economic lagging type and the environmental lagging type; iii) most of the selected regions exhibit a high coupling coordination degree, and the highest of those is Shandong. In the last section, the policy implications and further research directions are discussed. • The coupling coordination degree of fisheries economic and eco-environment systems is evaluated. • The selected regions are evaluated to be half each of the fisheries economic lagging and environmental lagging types. • Most selected regions exhibit a high coupling coordination degree, and Shandong's is the highest one. [ABSTRACT FROM AUTHOR]

Assessing the linkage between trade development and environmental quality has recently attracted increasing attention because of the rapid advancement of trade globalization along with the severe degradation of the environment. However, neglecting the possible nonlinear relationship between the variables, the existing studies mainly use linear models to explore the trade-environment linkage. To fill this gap, this paper introduces a novel partially linear additive panel model that highlights nonlinear and heterogeneous features to investigate the direct and indirect influences of trade development on environmental performance over the period 2005–2017 in China. The results show that trade has an inverse "U-shaped" direct effect on the environment. In contrast, trade development can indirectly improve environmental quality through economic growth. Nonlinear marginal analysis demonstrates that such an impact not only presents individual differences but also embodies the trait of temporal dynamics. Empirical results further reveal the importance of our model, which can automatically identify the variable nexus and thus reduce the setting error of the parametric models. Model evaluation also confirms the superiority of the used model over existing parametric and nonparametric models. The partially linear additive panel model provides a new evaluation method for environmental impact regarding trade development, and can be applied to other fields where an assessment of the effect of socio-economic factors on the environment is needed. • Investigate the effects of trade development on environmental quality. • Execute the latest method of partial linear additive panel model. • Reveal an inverse "U-shaped" direct effect of trade development on environmental quality. • Show a serious regional mismatch between trade-related pollutants and economic gains. • Evaluate the performance of different methods by model evaluation and selection. [ABSTRACT FROM AUTHOR]