Search

The increasing demand for economic development in the coastal zone is exerting greater pressure on the eco-environment in this region. Therefore, it is imperative to conduct comprehensive research on the sustainable development of the eco-environment in coastal areas. Grounded in sustainable development theory and Integrated Coastal Zone Management (ICZM), this study assessed sustainable development of Jiaozhou Bay (JZB), China over the period from 2015 to 2019 under multiple pressures applying the Driver-Pressure-State-Impact-Response (DPSIR) framework. Subsequently, a SWOT (Strengths, Weaknesses, Opportunities and Threats) analysis was employed to propose specific countermeasures and recommendations. In terms of weight within the criterion layer, Response (R) and Pressure (P) were assigned higher weights. The comprehensive assessment value Z in the target layer indicated a slight decrease in 2016 followed by a gradual increase that eventually led to stabilization. The comprehensive assessment values of the indicators varied depending on different conditions, implying that higher values would contribute to sustainable development of the eco-environment. Based on a SWOT analysis, strategies for Qingdao were derived from a combination of research findings and future development policy. These strategies include preventing and controlling land and sea pollution, governing reclamation activities, optimizing industrial structure, and strengthening public opinion guidance. This study highlights the application of quantitative and qualitative analysis methods in ICZM, providing specific recommendations based on policy analysis for achieving sustainable development in JZB's eco-environment under multiple pressures., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

China's double carbon target aims to improve human well-being and sustainable development. Energy transformation welfare performance (ETWP) is the efficiency of energy transition (ET) in enhancing human well-being. ETWP considers both human well-being and sustainable development. Research on its driving force is helpful in achieving the double carbon goal. Thus, this paper used Logarithmic Mean Divisia Index Model, Fixed Panel Regression Model and Grey Relational Analysis Model to analyze China's ETWP from 2006 to 2022 and predicted ETWP of 31 provinces from 2023 to 2030. The results showed that: (1) ETWP had two rising periods in 2006-2014 and 2015-2022. (2) The government's rationalization policy on energy and environment and technological innovation ability were fundamental driving forces for improving ETWP. (3) There were obvious spatial and temporal distinctions in ETWP, and it would bring out different degrees in most areas. Thus, ET should be promoted by improving the ecological environment and resource utilization efficiency; The importance of the role of scientific and technological innovation and policies should be focused on in promoting ETWP; ET policies based on local developments should be formulated and the energy structure should be changed., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

In order to deal with the environmental problems such as pollution emissions and climate change, sustainable development in the field of transportation has gradually become a hot topic to all sectors of society. In addition, promoting the green and low-carbon transformation of China's transportation is also an important issue in the new era. Thus, it is particularly important to correctly identify the green effect of high-speed rail. However, the traditional causal reasoning model faces several challenges such as 'dimensional curse' and multicollinearity. Based on the panel data of 283 prefecture-level cities in China from 2003 to 2019, this study uses the double machine learning model to explore the impact of transportation infrastructure upgrading on the efficiency of urban green development in China. The research shows that the upgrading of transportation infrastructure can effectively improve the efficiency of urban green development by 4%. Service industry agglomeration and green innovation are verified as two mediating channels. Moreover, the synthetic difference in difference model is employed to evaluate the regional impact of high-speed rail, and finds that the regional impact of transportation policies often exceeds the impact of individual cities. We further apply the conclusions of this paper to the research at the micro enterprise level. Goodman-Bacon decomposition and a variety of robustness tests confirm the validity of our conclusions. The study's comprehensive empirical analysis not only validates the positive effects of transportation upgrades on green development, but also offers novel insights into the underlying mechanisms and policy implications of transportation upgrading., Competing Interests: Declaration of competing interest No conflict of interest exits in the submission of this manuscript, and the manuscript is approved by all authors for publication., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Drylands, as highly vulnerable ecosystems, support environmental functions and human well-being. Nevertheless, widespread land degradation and desertification present significant global and regional environmental challenges, with limited consensus on their area and degree. This study used time-series vegetation productivity and meteorological data from 2000 to 2020 to quantify global land degradation trends and driving factors in drylands. The results show a notable restoration of land degradation in drylands worldwide, with the area of improved land exceeding the degraded area by 1.4 times, although the threat of degradation persists. India and China emerge as pioneers in effective land improvement strategies, offering valuable experiences for other regions. Combined effects, as quantitatively distinguished by our established model, dominate the degradation and improvement processes. Notably, human activities play a decisive role in influencing land degradation trends, with the potential for either exacerbation or reversal. This study provides new perspectives on environmental health and human activities from global and regional observations. Finally, our research provides scientific support for desertification control and contributes to the overall advancement of the SDGs globally., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Urban greenness serves as a key indicator of sustainable urban development, with smart city construction emerging as a primary strategy for its enhancement. However, there is little empirical evidence considering multi-dimension between urban greenness and smart city construction on the city level. This study focuses on the impact on urban greenness of smart city construction in megacities, using the difference-in-differences regression model to evaluate the impact based on urban development conditions in various aspects from 2010 to 2021 in 10 megacities in China. The results of panel data of different indicator samples show unique conclusions. First, smart city pilot policy in megacities has significant impact on urban greenness, primarily due to demographic and economic developments. Second, the impact is different between the megacity and national level, and different factors of urban greenness have different effects on smart city construction. Third, the effects are time-lagged and lasted for years, and regional heterogeneity divided by building climate zones is existed, where the effect is more obvious in city agglomeration. These findings of smart city construction reveal the unique influences on megacity greenness, and can be generalized to cities with similar characteristics accordingly., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

The 2030 agenda of the United Nations provides a framework of 17 Sustainable Development Goals (SDGs) and 232 indicators for its members to fulfill. The overall achievement critically depends on how nations understand the interactions between these SDGs and set priorities for development pathways. This study provides a comprehensive network analysis of global SDG complementarities, measured by the co-occurrences of SDG pairs' comparative advantages in the same region by adopting the 'product space' concept from economics. We construct the 'SDG space' at goal and indicator levels with the most recently available data and then validate its robustness by comparing it to the commonly used correlation network and confirm its predictive power using historical data. Network analysis reveals a strongly connected socioeconomic-related core and an environmental-related periphery, with 'bridge' indicators connecting different clusters. The goal-level space identifies the 'bridge' goals as SDG 17 (Partnerships for the Goals), SDG 8 (Decent Work and Economic Growth), and SDG 15 (Life on Hand) in the environmental-related cluster, while identifying SDG 7 (Affordable and Clean Energy), SDG 6 (Clean water and Sanitation), and SDG 16 (Justice and Strong Institutions) in the socioeconomic cluster. The indicator-level space provides details to explain how they act as 'bridges' in the network. In particular, 16-9: Free Press Index is the 'bridge' indicator with the highest betweenness centrality value and acts as the bottleneck indicator in China for its overall sustainable development. Improving it can enhance connected indicators' performance, leading to positive cascading effects on different aspects of sustainability., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Achieving sustainable economic development and mitigating climate change require effective green transformation management. This study builds an evolutionary game model for industrial enterprises, local governments, and the central government, analyzing the dynamic interactions among vertical decentralization, environmental regulation, and enterprise pollution. Our research reveals that increasing environmental taxes can incentivize industrial enterprises to adopt green transformation practices and promote governments at all administrative levels to supervise and enforce environmental regulations. Moreover, in the context of vertical decentralization, financial incentives provided by the central government to local governments become critical drivers for promoting green transformation. Furthermore, the additional social benefits resulting from local government supervision and governance are key factors in green transformation management, while the negative social effects of industrial enterprises not rectifying their actions are noteworthy. Our study emphasizes the need for an integrated framework incorporating these critical elements for successful green transition management. The findings of this research provide valuable insights for developing nations seeking to enhance their governance capacity throughout the green transformation process., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Ecosystem services (ESs) play vital roles in meeting the needs of human well-being and supporting sustainable development. However, there is limited research on how the types, amounts, interactions, and changes of the ESs collectively impact human well-being under the context of sustainable development goals (SDGs) of the United Nations. This study selected Qinghai Province of China as the study area and intended to make such an attempt to fill this gap in terms of the following aspects: (1) analyzing the spatial patterns and changing trends of ten ESs (food supply, water supply, carbon sink, soil retention, sand fixation, hydrological regulation, flood mitigation，cultural service，net primary productivity, and habitat quality) in Qinghai Province from 2000 to 2018; (2)constructing a multi-level index system of human well-being under the framework of the SDGs, and setting the criteria to assess the level of local human well-being; and (3) building a structural equation model to explore the direct and indirect impacts of the types, amounts, interactions and changes of the ESs on actual human well-being and the gaps between actual and targeted human well-being. The findings revealed that: (1) most of the ecosystem services fluctuated with significant downward or upward trends during 2000-2018, except for four ESs (i.e., carbon sink, soil retention, flood mitigation, and habitat quality); (2) only a few indicators of local residents' well-being such as meat production, milk production, the numbers of medical technical personnel in hospitals and health centers, and the numbers of scientific and technical personnel met the SDG criteria in most time, while other indicators remained at low levels and there were large gaps between them and the SDG criteria; (3) actual human well-being and the gaps between actual and targeted human well-being were affected by the types, amounts, interactions and changes of the ESs with different degrees directly or indirectly. The approaches and results in this study are instructive for other regions of the world to make certain the roles of ESs in promoting human well-being and substantiating the SDGs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper, (Copyright © 2023. Published by Elsevier Ltd.)

As urbanization progresses, the number of resource and environmental problems that impede sustainable growth in cities is increasing. The urban resource and environment carrying capacity (URECC) serves as a crucial indicator for understanding the interaction between human activities and urban resource and environmental systems, guiding the practice of sustainable urban development. Thus, accurately comprehending and analyzing the URECC and coordinating the balanced growth of the economy and the URECC is essential to ensure cities' sustainable development. In this research, we combine DMSP/OLS and NPP/VIIRS night-time light data to assess the economic growth of Chinese cities using panel data for 282 prefecture-level cities in China from 2007 to 2019. The findings reveal the following outcomes: (1) Economic growth significantly contributes to the enhancement of the URECC, and the economic expansion of neighboring areas also promotes the URECC within the region. Economic growth can indirectly improve the URECC by fostering internet development, industrial upgrading, technological progress, opening up opportunities, and educational advancements. (2) The results from the threshold regression analysis suggest that as the level of internet development improves, the influence of economic growth on the URECC is initially constrained and then facilitated. Similarly, as financial development improves, the effect of economic growth on the URECC is initially constrained and subsequently promoted, with the promotion effect gradually increasing. (3) The relationship between economic expansion and the URECC varies across regions with different geographic locations, administrative levels, scales, and resource endowments., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

In recent years, the sustainable development of resource cities has become a challenge for all countries. It aims to transform the traditional monolithic economic model and find a way to develop the city's economy and environment in harmony. In this context, we uncover the relationship between sustainable development plan of resource-based cities (SDPRC) and corporate sustainable performance and examine possible pathways for action. Using a difference-in-differences (DID) model and a series of robustness tests, our study reveals the following. First, SDPRC enhances corporate sustainability. Second, possible mechanisms for SDPRC are explored. SDPRC achieves corporate sustainability by optimal resource allocation and increasing green innovation outputs. Third, urban heterogeneity is explored and it is found that SDPRC only has a positive impact on the sustainable performance in growth and mature cities, but not in declining and regenerating cities. Finally, firm heterogeneity was examined, with SDPRC having a more positive impact on the sustainable performance of state-owned firms, large firms and heavily polluting firms. This study sheds light on the impact of SDPRC at the firm level and provides new theoretical insights for urban planning policy reform in developing countries such as China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Globally, nations are increasingly focusing on green innovation in their environmental protection efforts as part of sustainable development, and digital finance is playing a vital role in enhancing green innovation. Employing annual data from 220 prefecture-level cities between 2011 and 2019, we empirically analyze the connections among environmental performance, digital finance, and green innovation via the Karavias panel unit root test with structural breaks, the Gregory-Hansen structural break cointegration test and pooled mean group (PMG) estimation. The following four points are the key conclusions: (1) The results support cointegration links between these variables when structural breaks are considered. (2) The PMG estimation outcomes indicate that green innovation and digital finance may have a favorable long-term effect on environmental performance. (3) For better environmental performance and more green innovation, the level of digitalization of digital finance is crucial. (4) The potential of digital finance and green innovation to improve environmental performance has not been fully realized in the western region of China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

This paper studies the impact of electricity price reduction policy on the economic activities and carbon emissions of different industries. Since 2018, the Chinese government has advocated reducing electricity price for industrial customers in order to alleviate the non-tax burden on businesses. Using monthly electricity consumption and user data from 2016 to 2019, we find that the electricity price reduction has significantly increased the industrial electricity consumption and users. Heterogeneity analyses show that the effect is greater in heavy polluted industries and industries in low and medium GDP regions. The results of threshold impact analysis show that the threshold value of heavy pollution industries was lower than that of general industry and commerce, while heavy pollution industries are more sensitive to electricity prices than general industries. Moreover, the reduction of electricity prices results in a higher percentage of carbon emissions growth in heavy pollution industries. Our result can also help the policymakers access the costs and benefits of electricity price reduction for industrial customers more accurately., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The relationship between industrial structure (IS) and eco-efficiency (EE) is intricate with mutual influence and constraint. Exploring the coordinated relationship between IS and EE is beneficial to the sustainable development of ecologically fragile areas. This paper estimates and analyses the levels of EE and IS in 39 prefecture-level cities of the Loess Plateau, discussing the comprehensive and coordinated development levels between industrial structure rationalization (ISR) and EE, industrial structure advancement (ISA) and EE based on the coupling coordination degree model (CCDM). The results showed that the comprehensive development of the Loess Plateau has rough and imbalanced issues. The EE and IS are developing at a relatively low level, and the spatial distribution shows the development trend of high in the east and down in the west. The CCD of ISA and EE performs better than that of ISR and EE, but neither has reached the collaborative coupling state. The poor CCD score in the Loess Plateau is primarily attributable to its relatively backward degree of integrated EE and IS. The results are expected to provide decision-making support for EE improvement and industrial restructuring in the Loess Plateau and other ecologically fragile areas., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Payments for ecosystem services (PES) are becoming a global ecological protection strategy used to promote sustainable social and economic development. However, the current PES research and applications are often local and one-sided. The lack of a unified framework for PES results in a high policy cost and low ecological and social benefits. A large number of local PES experiences need to be comprehensively analyzed to construct a unified PES framework, which can provide support for the implementation and optimization of nature conservation policy in different regions of the world. Here, we combined natural language processing methods to analyze 1919 global studies on PES. We obtained the topics and spatiotemporal distributions of PES, as well as the compensation modes of hotspot ecosystem services in 114 countries worldwide. PES have been studied in 80% of the world (excluding Antarctica), but the research topics and distributions are very uneven. We found a disconnection between PES socioeconomic strategies and knowledge of natural ecosystem dynamics. Therefore, the knowledge and experience of PES must be exchanged globally, and PES need to be further integrated with the sustainable development goal (SDG) framework. We propose a PES framework that couples socioeconomic and ecosystem dynamics and be oriented toward sustainable development to make comprehensive management decisions. On this basis, a consistent PES solution may be provided for future theoretical research and implementation strategies of conservation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

This research measures energy-based carbon intensity based on energy consumption of 30 Chinese provinces and investigates the impact of digital finance. First, the baseline results were examined through panel data model. Second, we reveal the "black box" system of digital finance and energy-based carbon intensity through mediating effects model. Third, by employed panel quantile regression model, we examine the heterogeneity of the effects of various factors under different carbon intensity quantile. The main quantitative results are as follows: (1) Digital finance shows significant sustainable effect, and its growth of 1% will reduce the carbon intensity by about 0.092%. (2) The intermediary effects of technological innovation and energy structure are -0.0663 and 0.007, respectively, accounting for 41.88% and 19.36% of the total effects. Both are significant transmission mechanisms. (3) When the carbon intensity in >0.9 quantile, digital finance shows a positive coefficient. On the contrary, the coefficient at <0.75 quantile is negative and its absolute value increases with the decrease of quantile. It shows that with the reduction of carbon intensity, the positive impact of digital finance gradually increases. (4) In the eastern, central and western regions, a 1% increase in digital finance will reduce the carbon intensity by 0.147%, 0.096% and 0.089% respectively. This research provides a reference for regional governments to use digital finance tools to promote sustainable development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Rapid urbanization poses great challenges to China's urban land use sustainability (ULUS). Land is the essential space to achieve the Sustainable Development Goals (SDGs) of the United Nations, so SDGs provide a new guide to evaluate land use sustainability. However, there is still a lack of SDGs-oriented assessment of urban land use at national level. Moreover, there is still a need to address the problems about the randomness and fuzziness within evaluation, which tends to cause more uncertainties. Here we developed a SDGs-oriented evaluation framework based on the cloud model and derived the spatial and temporal patterns of urban land use sustainability for China at the prefecture-level from 2004 to 2019. Then, we used the McKinsey matrix to classify the types of urban land use sustainability, and examined their main drivers using the Geodetector method. The results showed that the development level of ULUS in China was high in the east and low in the west. High-value hotspots were mainly distributed in primary and secondary urban agglomerations in China. From 2004 to 2019, the development level of ULUS in China gradually increased, but the growth rate slowed down. In 2009 the value of central China exceeded that of the northeast. In contrast, the coordination level of ULUS had declined in more than 50% of Chinese cities during the study period. The high values were in southern China, northeast China, and Chengdu-Chongqing urban agglomeration, while the low values were in central and southern Liaoning and the urban agglomeration in the Central Plains. The development level was mainly controlled by anthropogenic activities and urban development, while natural conditions constrained the improvement of the coordination level. Combining the development and coordination, we found that cities with higher development level often had a wide range of coordination level, and suggestions were put forward for different regions to achieve sustainable land use. Our research provides scientific guidance for China's territory planning and sustainable urban development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

To achieve sustainable development, local governments are under enormous pressure to simultaneously achieve the three assessment tasks (TATs) of energy saving, CO₂ reduction, and pollution reduction. However, the TATs are often managed by different authorities and have three types of measures (TTMs) that correspond to them. The lack of adequate cooperation between these authorities has led to the inefficient investment of policy resources and even to policy conflicts, and the interactions among the TTMs are not yet known. To this end, this paper uses the MCEE model to assess the interactions among the TTMs quantitatively using Guangzhou, China, as a case study. The results showed the following. (1) According to the current development trend, if the authorities managing the TATs continue to work alone, they will not be able to fulfill the corresponding assessment tasks in the future. (2) The TTMs have interactions with each other, and their synergies are far greater than their trade-offs. From 2015 to 2035, it is expected that energy-saving measures can accomplish 54.39% of the CO₂ reduction tasks and 32.74% of the pollution reduction tasks indirectly, and low-carbon measures can accomplish 55.53% of the energy saving tasks and 27.20% of the pollution reduction tasks indirectly, However, environmental-protection measures will cause fewer trade-offs (energy demand and CO 2 emissions increase by 3.76% and 2.88%, respectively). (3) In some years, the contribution of interactions among the TTMs are even higher than their direct contribution to the TATs. Our findings suggest that intensive cooperation between authorities is necessary, and that the benefits of such cooperation will outweigh the disadvantages., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Due to insufficient understanding of human-water interaction, many water-related problems arise in watersheds, posing severe threats to the sustainability of watershed development. Although water environmental carrying capacity (WECC) is a powerful tool to support sustainable development of watersheds, few studies considered aquatic ecological factors and uncertainty in indicator values, leading to losses of sample information in the evaluation of WECC. This paper developed a systematic framework for comprehensive WECC assessment that included the indicator system and a novel variable fuzzy pattern recognition (VFPR) approach. The WECC index system incorporated aquatic ecological factors, and addressed uncertainties associated with the indicator values. The proposed VFPR-based assessment model could realize successive evaluation to retain more original information of the sample and distinguish similar result values by treating the sample as having a continuous degree of membership instead of the traditional point form. In addition, it could be more adaptable to various circumstances including extreme cases, and closely reflect the impacts of indicator changes on the results. The established evaluation framework has been applied to Dongjiang River Basin in Guangdong Province. The spatial differences and main influencing factors of WECC in the study area were analyzed. Results show that 50% and 16.7% of the sub-regions in the study area would be subject to a poor level of WECC under pessimistic and optimistic circumstances, respectively. WECCs in the upper and lower reaches are the best and worst, respectively, which is in line with the levels of economic development in the Dongjiang River Basin. The proposed method can also be applicable to many other problems involving numerous indicators., (Copyright © 2021. Published by Elsevier Ltd.)

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

To direct financial resources to cleaner production enterprises and achieve the goal of environmental governance, the Chinese government has devoted increasing efforts to facilitating green finance. As one of the major policies of green finance, the Green Credit Policy (GCP) was issued in 2012. Evaluating whether the GCP can promote green development has important significance, but few studies have explored its policy effects for the investment and financing behavior of "two high" (high energy consumption and high pollution) enterprises and environmental quality from both micro and macro perspectives. Taking the promulgation of the GCP as a quasi-natural experiment, based on a panel dataset involving 945 A-share listed companies and 30 provinces for the period of 2004-2017, this paper adopts the difference-in-difference model to explore the investment and financing behavior changes of enterprises and environmental impacts of the GCP. The following conclusions are derived. (1) The GCP provides incentives for the short-term financing behavior of "two high" enterprises, but it has a punitive effect in the long term and significantly inhibits the investment behavior of such enterprises. (2) The GCP contributes to the mitigation of sulfur dioxide and wastewater emissions. (3) The GCP has a greater effect on investment and financing behavior among state-owned and large-scale "two high" enterprises than among medium-sized and micro enterprises. (4) There exists regional heterogeneity in the effects of the GCP on the investment and financing of "two high" enterprises and environmental quality. The GCP has positive impacts in the eastern and western regions, and the policy effect is not obvious in the central region., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

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]

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

China is now facing the formidable tasks of saving energy and reducing emissions, so it is very important to analyze China's energy and environmental efficiency. However, previous studies have rarely paid attention to the cross-impacts that different forms of public environmental concern (PEC) have simultaneously on energy and environmental efficiency. To investigate how these two types of efficiency change along with PEC variations, this paper employs six extended programming models which are developed based upon the theory of Data Envelopment Analysis (DEA) and the directional distance function (DDF). An empirical analysis of data from 239 Chinese prefecture-level cities demonstrates the techniques. The empirical results show that PEC variations can significantly affect the environmental efficiency only if the city is experiencing unsustainable development. This work also shows that PEC about input resources may exaggerate the environmental efficiency, implying that the public may be more tolerant of resource over-consumption than of pollutant over-emission., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

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]

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]

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

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

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

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]

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

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

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

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

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

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

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

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

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

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

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

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

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

Increased soil erosion on sloped land has become a significant environmental concern in China that has been attributed to human activities such as deforestation, over-cultivation, and over-grazing of livestock. In order to reduce soil erosion on sloped lands, the Chinese government has responded by implementing large-scale, ecological rehabilitation programs, including the “Grain for Green” reforestation project. This program involves financial incentives to transition farmers into other economic activities with the goal of reducing ecological pressures and degradation. Because of the scope and potential impacts from these programs, detailed research is needed to understand their social and ecological effects. This paper reports on research conducted in Tianquan County, Sichuan Province, and Wuqi County, Shaanxi Province, that evaluates the effects of the program upon local economies and household livelihood systems. The paper argues that the successful conversion of farmland under “Grain for Green” depends upon local government involvement, local economic development, and funding for local projects. Without economic development within rural economies, we conclude that farmers will remain dependent upon continued subsidy assistance to meet the policy’s ambitious environmental restrictions, thereby undermining the program’s long-term sustainability. [Copyright &y& Elsevier]

An understanding of flood impact in terms of sustainability is vital for long-term disaster risk reduction. This paper utilizes two important concepts: conventional insurance related flood risk for short-term damage by specific flood events, and long-term flood impact on sustainability. The Insurance Related Flood Risk index, IRFR, is defined as the product of the Flood Hazard Index (FHI) and Vulnerability. The Long-term Flood Impact on Sustainability index, LFIS, is the ratio of the flood hazard index to the Sustainable Development Index (SDI). Using a rapid assessment approach, quantitative assessments of IRFR and LFIS are carried out for 2339 counties and cities in mainland China. Each index is graded from ‘very low’ to ‘very high’ according to the eigenvalue magnitude of cluster centroids. By combining grades of FHI and SDI, mainland China is then classified into four zones in order to identify regional variations in the potential linkage between flood hazard and sustainability. Zone I regions, where FHI is graded ‘very low’ or ‘low’ and SDI is ‘medium’ to ‘very high’, are mainly located in western China. Zone II regions, where FHI and SDI are ‘medium’ or ‘high’, occur in the rapidly developing areas of central and eastern China. Zone III regions, where FHI and SDI are ‘very low’ or ‘low’, correspond to the resource-based areas of western and north-central China. Zone IV regions, where FHI is ‘medium’ to ‘very high’ and SDI is ‘very low’ to ‘low’, occur in ecologically fragile areas of south-western China. The paper also examines the distributions of IRFR and LFIS throughout mainland China. Although 57% of the counties and cities have low IRFR values, 64% have high LFIS values. The modal values of LFIS are ordered as Zone I

This paper introduces an integrated assessment (IA) approach for a Canada-China joint research project that linked forest carbon sequestration, forest resource management, and local sustainability enhancement. The purpose of the IA was to improve the measurement of carbon in different land uses and vegetation covers, as well as to direct decision makers to those land uses or options as an CO2 emission reduction strategy while supporting rural sustainable development. In this connection, three questions are addressed in this paper: [1)] How will forestry carbon sequestration land use policies affect regional sustainability prospects in rural China? [2)] How could carbon sequestration land use plans be better integrated into sustainable development strategies? and [3)] How can the IA approach assist Chinese government agencies in design effective forestry land use policies? The IA approach was applied in three rural sites of western China. These case studies are described in detail by following articles in this volume. The project improved the capacity of local resource managers in identifying the economic, social and environmental impacts of rural land use decisions that might increase carbon sequestration and enhance local livelihood. [Copyright &y& Elsevier]

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