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This study aims to investigate the impact of environmental technological innovations and environmental policy stringency on green economic growth in China. The empirical analysis of the study is based on the ARDL model. Findings confirm that environmental technology positively impacts green economic growth in the short and long run. In the robust model, the estimates of all technologies appeared to be significantly positive in the short and long run. Conversely, the estimated coefficients of environmental policy stringency, in the basic and robust model, have only negatively impacted the green economic growth in China in the short run. In the long run, the environmental policy stringency has not shown any significant impact on green economic growth in China in the basic and robust model. China needs to increase environmental technology and environmental policy stringency for achieving green growth and sustainability targets., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This research focuses on the impact of the digital economy on total factor carbon productivity. Based on the panel data of China's provinces from 2009 to 2019, this paper incorporates undesired output, namely carbon emissions, into the evaluation index system, and uses the SBM-ML index to measure regional total factor carbon productivity, and uses the RAGA-PP model to measure the digital economy development index, which includes three dimensions: digital infrastructure, digital industry development, and digital economic environment. Moreover, this paper incorporates the heterogeneous threshold of technological accumulation into the framework of the impact mechanism of total factor carbon productivity and builds a threshold model to examine the impact of the digital economy on total factor carbon productivity under different technological accumulation thresholds. The research shows that, first, during the sample period, total factor carbon productivity fluctuated around the frontier, showing a certain upward trend, with significant regional heterogeneity. Second, the digital economy has a promotional effect on the total factor carbon productivity level in China and can become the new energy for the country to improve the level of green development. Third, the impact of the digital economy on total factor carbon productivity presents a significant heterogeneous threshold effect of technological accumulation, along with the increasing level of technology accumulation, the effective coefficient of the digital economy on total factor carbon productivity is increasing, and the level of significance is increasing. Last, the low-carbon driving mechanism of the digital economy has temporal and spatial heterogeneity of regional technology accumulation levels. The conclusions of this paper provide an effective reference for exploring the realization mechanism of regional total factor carbon productivity improvement, ecological civilization construction, and high-quality economic development., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The transformation of the traditional high-carbon economy to a low-carbon economy and the change in the economic development mode urgently require the transformation and development of traditional finance to green finance. This study examines the impact of green finance on the transition to a low-carbon economy in 30 Chinese provinces from 2001 to 2019 and further explores the role of low-carbon technological innovation in this facilitation process. We use the Global Malmquist- Luenberger index to measure low-carbon total factor productivity using gross regional product as the desired output, CO2 emissions as the undesired output, and capital stock, employment, and total energy consumption as input indicators to represent the low-carbon economic transition. We select seven indicators in four dimensions of green credit, green securities, green insurance, and green investment to construct a comprehensive green finance evaluation system, and then apply the entropy value method to calculate green finance indicators. The number of patents granted for low-carbon innovation is used to measure low-carbon technology innovation. Foreign direct investment, industrialization level, economic development level, and urbanization level are selected as control variables. Through panel data model, mediating effect model and 2SLS, we find that green finance can significantly contribute to the transformation of low-carbon economy, but this contribution decreases with the intervention of low-carbon technology innovation. The implications of our empirical results can help China to improve the development of green finance and thus promote the transformation and upgrading of a low-carbon economy., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Strict environmental regulations may change the behavioral decisions of firms. Based on the exogenous impact of the Chinese Central Government's inclusion of environmental performance in the assessment targets of municipal officials in 2007, this study uses the difference-in-difference method to explore the impact of environmental regulations on employee income. We find that (1) environmental regulations will significantly reduce the average wage level of employees in polluting industries and have no significant impact in nonpolluting industries. (2) This effect is more pronounced in eastern China, where environmental regulations are more stringent, and in areas where political promotion incentives are stronger. (3) Mechanistic analysis finds that environmental regulations will affect employee income by increasing costs and constraining financing. (4) More importantly, we find that the decline in the average wage level of firms is mainly due to the decline in the average wage level of ordinary employees, and the average wage level of management has not decreased significantly, which means that environmental regulations have expanded the functional income distribution. Our findings contribute to a comprehensive understanding of the effectiveness of environmental regulatory policy implementation and associated economic cost issues., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Green finance is the main way to solve financing problems and support green technology innovation. The development of higher education is the source of innovative human capital and a key factor in promoting green economic growth. Studying the relationship between the three is an important realistic meaning for achieving green economic growth. Based on the idea of system coupling, this paper adopts the analysis method of the three-system coupling coordination model. This paper constructs a three-system coupling model, which incorporates green finance, higher education, and green economic growth into a unified framework, and based on a comprehensive review of the interaction and mechanism, the degree of system coupling is analyzed from the regional and provincial levels. Conclusions of the study are as follows: (1) the composite indexes of green finance, higher education, and green economic growth are all on the rise. The highest increase has been found in the index of higher education. In addition, the green finance index has also shown an accelerated upward trend in recent years, and green economic growth index has also shown a steady rise in recent years. (2) The upward trend of the coupling degree is relatively observable, but the overall coupling degree is still at low level. The coupling state has jumped from the low-degree coupling stage to the primary coupling stage, and the coupling degrees of the three major regions all show a fluctuating rising trends, but there are apparent regional differences. The degree of coupling between the eastern region and the other two regions is quite different. (3) During the sample period, the degree of coordination between green finance, higher education, and green economic growth in each province has increased to varying degrees. The degree of coordination in the eastern region is the best, the western region is the worst, and the central region is somewhere in between. The study concludes with implications for the protection of the environment. Finally, based on the empirical analysis results, this paper puts forward corresponding countermeasures and suggestions from the perspectives of improving the ability of green technology innovation, promoting the development of green finance and the high-quality development of higher education, and hoping to provide theoretical reference for the coordinated development of China's regional economy., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Encouraging rural residents to adopt biogas is of great practical significance in tackling environmental degradation in China. Based on the survey data of 540 rural households in Sichuan Province, China, this paper studies the peer effects of biogas adoption in rural households, focusing on the influence of relatives and friends on the biogas adoption behavior of rural households. According to whether there is a Chinese New Year visit, the relatives and friends of rural households are divided into strong ties and weak ties. The peer effects are further discussed from the perspective of strong and weak ties, and the probability score matching (PSM) method is used to correct the estimation errors that may be caused by selection bias. In addition, the study further revealed the internal mechanism of peer effects through heterogeneity analysis. The results found that (1) the adoption of biogas by relatives and friends significantly promotes the adoption of biogas in rural households. (2) Compared with relatives and friends who did not visit during the Chinese New Year (weak ties), relatives and friends who visited (strong ties) had a more significant impact on the biogas adoption behavior of rural families. (3) Farmer groups with lower education levels and farther from the market are more affected by the peer effects and are more likely to adopt biogas. The driving effect of biogas behavior choice of relatives and friends on biogas behavior decision of rural households can provide a reference for decision-makers to make relevant measures., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Green innovation undoubtedly plays a significant role in generating employment opportunities, improving green economic activity, and increasing environmental sustainability. This study scrutinizes the effect of energy efficiency and green innovation on CO2 emissions for China using nonlinear autoregressive distributed lag (NARDL) from 1991 to 2019. Findings show that energy efficiency and green innovation contribute to reducing CO2 emissions in China. Energy efficiency and green innovation are also important nonlinear determinants of CO2 emissions. An increase in energy efficiency and green innovation lowers CO2 emissions, while a fall in energy efficiency and green innovation increases CO2 emissions in China in the long run. Some policy measures are suggested to attain carbon neutrality., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Under the pressure of environmental crisis caused by production and economic development, a policy for Leading Officials' Accountability Audit of Natural Resources (LOAANR) was issued in 2014 to reduce the environmental risks and gain high-quality economy. Taking LOAANR policy as the research object, and based on 2011 to 2018 panel data from Chinese heavy-polluting enterprises, this paper employed a two-way fixed difference-in-differences (DID) model to explore the relationship between the LOAANR, environmental costs (ECs) and green innovation (GI). It was found that the implementation of the LOAANR significantly promoted enterprise GI, with the regulating impact mechanism, EC. GI efficiency was measured by continuous DID method. A heterogeneity analysis revealed that non-state-owned enterprises (NSOEs) were more eager to environmentally innovate. A corporate life cycle heterogeneity analysis of the GI policy effect found that the policy effect was negative in the decline stages. Compared with the eastern Chinese enterprises, enterprises in other regions were found to be more prone to positively adopting GI to maximize benefits in the face of the LOAANR. The policy was observed to have inhibited GI in central Chinese enterprises. It was also demonstrated that the policy effect has time and regional dynamic effect. Common trend, placebo, PSM-DID tests, and another robustness regressions were applied to support the conclusions. All the findings are expected to provide basic theoretical guidance for more environmental policies and high-quality production., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

China's power sector has received great research attention because of its large energy consumption and CO 2 emissions. This study assesses the environmental efficiency and technology inequality of China's power sector from 2008 to 2017. Methodologically, this study proposes a non-radial FDH (free disposable hull) model and a super non-radial FDH model. The non-radial FDH model relaxes the convex assumption and captures all inefficiencies of inputs, desirable output and undesirable output. The super non-radial model is capable of discriminating efficient power sectors and always has feasible solutions. We also compare their performance with the non-radial data envelopment analysis (DEA) model. The main conclusions are summarized as follows: First, the environmental efficiency of China's power sector has experienced steady growth; the power sectors in the east region outperform those in other regions. Second, the proposed FDH models are more applicable and reliable than the non-radial DEA model in efficiency measurement of China's power sector, due to the indivisibility of labor. Third, there has been growing technology inequality and the main driving factor determining technology inequality is the inter-region efficiency Gini coefficient. To improve environmental efficiency and eliminate technology inequality, the government should mainly solve the issue of excessive labor input and establish a free technology market for technology trading., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Whether green credit policy is conducive to improving the green innovation efficiency of heavy polluting industries is of great significance for China's sustainable economic development and the construction of ecological civilization. This paper uses China's Green Credit Guidelines to conduct a quasi-natural experiment based on relevant panel data of industries from 2007 to 2018. Specifically, it employs the Super-SBM model including non-expected output to measure the green innovation efficiency of 35 industries in China, and constructs the propensity score matching difference-in-difference model to explore how green credit policy impact on the green innovation efficiency of heavy polluting industries. The results show that the coefficient of difference-in-difference ([Formula: see text]) was 0.262, which was significant at the 1% level; the coefficient of [Formula: see text] was not significant; the coefficient of [Formula: see text] was 0.490, which was significant at the 1% level; and the coefficient of [Formula: see text] was 0.173, which was significant at the 1% level, indicating that green credit policy significantly contributes to the green innovation efficiency of heavy polluting industries, though with a lag effect. Further study finds that green credit policy pushes heavy polluting industries to improve green innovation efficiency by increasing financing cost and R&D investment; meanwhile, the heterogeneity test shows that the higher the state-owned share of the industry, the greater the positive effect of green credit policy on its green innovation efficiency. Finally, in order to accelerate the implementation of green credit policy and promote the green innovation efficiency of heavy polluting industries, banks can guide heavy polluting industrial enterprises through credit to carry out green technological transformation, heavy polluting industries should raise awareness of green innovation, and government should encourage heavy polluting industrial enterprises to carry out green innovation, and guide and supervise the state-owned enterprises in particular, so that they can improve cleanliness and achieve green economic development., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Water resource carrying capacity (WRCC) is an important index for measuring the relations between water resource systems and socio-economic-environmental development. In view of the difficulty in describing the complex and nonlinear relationships between the WRCC and indicators using traditional methods, this study introduces deep learning theory and proposes a novel deep neural network named WRCC-Net for WRCC assessment. Unlike typical network structures, we constructed a hierarchical structure that can indicate the index system in WRCC evaluation. Furthermore, we utilized a residual learning technique to increase the network depth for fitting the complex relationship between the WRCC state and indicators. The proposed deep learning method was applied to solve the real-world WRCC problem by taking the Yunnan province (Southwest China) as the case area. The WRCC was assessed from the following five dimensions: the water resources, social, economic, ecological environment, and coordination subsystems. Performance evaluation shows the advantages of the proposed WRCC-Net over the typical deep feed-forward network and shallow methods. Therefore, the proposed method provides a new way of evaluating the WRCC state and has potential for WRCC research. Overall, the WRCC evaluation using the WRCC-Net shows that the state of the WRCC in Yunnan constantly decreased from 2008 to 2018. These central-eastern areas in the Yunnan province, such as Kunming, Qujing, and Yuxi, are under an unfavorable capacity state. Measures, such as improving water resources management and increasing water utilization efficiency, should be considered in water resource planning in Yunnan province for the sustainable development of water resources., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Worldwide degradation of the ecological environment could be the cause of poverty. The poverty-stricken areas may face the dilemma of a "vicious circle of poverty." The complex ecological conditions have intertwined with poverty alleviation, which makes the demand for ecological poverty alleviation particularly prominent in these areas. However, the research on the relationship between agro-ecological efficiency and poverty are limited. It is far from clear what is the impact of the agro-ecological efficiency on poverty. To explore the impact of agro-ecological efficiency on poverty reduction, we adopt the panel data model based on cross-correlation and regression coefficient, using the data from 25 counties/districts in the Three Gorges Reservoir Region (TGRR) from 2006 to 2017. The results show that (1) there is significant heterogeneity in agro-ecological efficiency in the TGRR, and the agro-ecological efficiency in the middle area is significantly lower than that of the head and tail areas of the TGRR; (2) the improvement of regional agro-ecological efficiency could accelerate the alleviation of poverty; and (3) the widening of urban-rural income disparity is not conducive to poverty alleviation and eradication. This study would provide basis for further policy recommendations aimed at improving agro-ecological efficiency and alleviating poverty., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Farmland not only provides human being with food and industrial materials, but also has non-market value. However, few studies have explored the impact of livelihood capital configuration and their willingness to pay (WTP) for the farmland non-market value, from farmers' perspective. Based on the field survey data of 434 households in Jianghan Plain, China, this paper divided the research process into two stages to explore the impact of farmers' livelihood capital on their WTP by using binary logistics model and qualitative comparative analysis method of fuzzy sets (fsQCA). The results show that (1) The total livelihood capital of farmers was 2.667, with psychological capital 0.649, natural capital 0.621, social capital 0.127. 79.49% of the households were willing to pay for the farmland non-market value, and the most concentrated range of it is 50-200 yuan/hm 2 . (2) Both social capital and psychological capital had positive impacts on farmers' WTP for the non-market value of farmland protection. (3) There were two livelihood capital configurations that could improve the WTP of farmers. When lacking of human capital, physical capital and psychological capital, the improvement in farmers' financial capital and social capital will improve farmers' WTP. When the natural, financial, and psychological capital are poor, the rich human capital, physical capital and social capital will also increase farmers' WTP. In view of the results, policy implications on livelihood capital structure optimization and ecological compensation system differentiation were proposed., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study aims to analyze the asymmetric long-run relationship between economic growth (EG), foreign direct investment (FDI), and carbon emissions (CO 2 ) within the context of the environmental Kuznets curve (EKC) and the pollution haven hypothesis (PHH) in China. Employing the quarterly data from 1982Q1 to 2018Q4, we have used novel techniques to meet the stated objectives of our study, named quantile ARDL and quantile Granger causality. The study provides novel outcomes using the advanced quantile ARDL and quantile Granger causality tests. The significant implication of this method is that it provides locational asymmetry. We find strong evidence of the EKC and PHH for China based on the empirical results of linear and nonlinear ARDL models. Similarly, findings of quantile Granger causality validate the bidirectional relationship among all variables in upper and lower quantiles. Moreover, the results of the Wald test confirm the asymmetric long-run relationship between FDI and carbon emissions (CO 2 ). Thus, legal measures must be enhanced, accepted, rigorously imposed, and monitored in all provinces to assure a further reduction in carbon emissions. This study will be conducive for the policymakers to combat environmental contamination concerning economic growth and FDI inflow in China., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Although studies on the influencing factors of electricity consumption are rich, the focus on the relationship between financial development and electricity consumption is scarce due to the characteristics of financial sector. In fact, the financial development cannot only increase electricity consumption, but also have the spatial spillover effects. Based on the global spatial modeling techniques, the long-term and short-term relationship between financial development and electricity consumption is examined, and the intermediary effect of financial development on electricity consumption through economic growth, urbanization, and industrial structure optimization is also verified. Results show that there is a global co-integration relationship between financial development, economic growth, urbanization, industrial structure optimization, and China's electricity consumption, rather than a local co-integration relationship. When the short-term change of electricity consumption deviates from the equilibrium state, the global error correction mechanism can promote the unbalanced system to return to equilibrium from time and spatial dimension. This study confirms not only the spatial spillover effects, but also heterogeneous influences of financial development on electricity consumption, which provides new evidence to make relevant policies., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Carbon emission reduction in the construction industry is vital for realizing sustainable development, and the development of the digital economy plays an important role in this process. The impact of the digital economy on reducing carbon emissions in the construction industry is empirically explored through econometric analyses on a sample of panel data from 30 provinces in China from 2012 to 2021. The empirical results show that developing a digital economy can significantly reduce the construction industry's carbon emission intensity. Additionally, this impact has a significant spatial spillover effect and can benefit the neighboring regions. The mechanism test shows that the digital economy can reduce carbon emissions by improving the technological level of the construction industry. Moreover, the inhibiting effects of the digital economy on carbon emissions in the construction industry vary across different regions. They are more pronounced in the eastern and western regions of low coal-consuming regions. These findings offer valuable insights for policymakers to help drive the deeper integration of the digital economy with the construction industry and facilitate its transition to low-carbon development., Competing Interests: Declarations. Ethics approval: Not applicable. Consent to participate: This study has not directly/indirectly involved humans and/or animals. Consent to publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Large-capacity toluene storage tank leakage accidents can lead to severe casualties and environmental damage. In this study, numerical simulation of the toluene leakage accidents is performed using PHAST and ALOHA softwares across 16 scenarios. The present research focuses on the dispersion of toluene lethal and toxicity clouds, as well as the associated risks from vapor cloud explosions and pool fires resulting from the large-capacity toluene storage tank leakage. Meanwhile, the effects of influential factors such as leakage height, wind speed, ambient temperature, and atmospheric stability on toluene leakage accidents are also discussed, and then the worst-case scenario of the toluene leakage accident is obtained. The effects of wind speed, ambient temperature, leakage height, and atmospheric stability on outcomes such as toxic clouds, vapor dispersion, explosions, and pool fires are also analyzed. The result reveals that toxic cloud dispersion increases with ambient temperature, while the impact of vapor cloud explosions and pool fires decreases with the increase of leak heights. Wind speed significantly affects pool fire spread. The influential factors related to maximizing hazard range including low leak heights, low wind speeds, high temperatures, and stable conditions are obtained. Risk analysis indicates that vapor cloud explosions significantly impact outdoor potential loss of life (PLL outdoor ) compared with other incidents. Scenario 4 within a directional range from 33.8 to 56.3° shows the highest incident frequencies, highlighting its importance for risk monitoring. These findings are crucial for enhancing emergency response strategies and safety protocols in industrial safety management., Competing Interests: Declarations. Ethical approval: Not applicable. Consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Green industrial policies (GIPs) aim to promote the adoption of green technology within a sustainability framework. While previous evaluations of GIP have focused more on the policy itself and the impacts within the policy boundaries, this paper further introduces the geographical factor to analyze the impact of different spatial geographic distances on implementing GIP. By integrating geographic distances into a spatial difference-in-differences analysis to assess the effects of municipal green industry policies (referred to as green industry pilot policies in this paper) enacted in 11 cities in China from 2006 to 2010, we find that these policies not only improve environmental and economic outcomes in targeted regions but also have spillover effects that may affect neighboring areas negatively, highlighting the importance of geographic considerations. The effectiveness of green industrial policies varies across cities, influenced by local socio-technical systems and regional characteristics such as infrastructure and information technology. These findings suggest that policy impacts are complex and multifaceted, requiring a comprehensive understanding of geographic interdependencies. By incorporating geographic factors, this research contributes to sustainability transition theory by offering insights into the spatial and temporal dynamics of socio-technical systems. The results underscore the need for policymakers to consider spatial-temporal aspects and potential secondary effects on adjacent regions when designing and implementing green industrial policies., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In 2020, China pledged carbon reduction targets at the United Nations: peaking emissions by 2030 and achieving carbon neutrality by 2060. Research and prediction of regional carbon emissions are crucial for achieving these dual carbon targets across China. This study aims to construct an indicator system for regional carbon emissions and utilize it for forecasting. Analyzing carbon emission data from a specific area in Hainan Province from 2010 to 2020, we established an indicator system. Using the interpretable SHAP model, we assessed indicator importance and trends. Employing an improved STIRPAT model with partial least squares regression to address multicollinearity among influencing factors, we developed a carbon emission prediction model. Based on this, we forecasted carbon emissions from 2021 to 2060 in the specified area under three scenarios: natural, baseline, and ambitious. The results show that the growth of resident population and per capita GDP has the most significant promoting effect on carbon emissions in the region while optimizing industrial structure, energy consumption structure, and reducing energy intensity will inhibit carbon emissions. The prediction results indicate that in the natural scenario, regional carbon emissions will peak in 2035, and achieving carbon neutrality by 2060 is not feasible, while the baseline scenario and ambitious scenario can achieve the dual carbon targets on time or even earlier. The research results of this article provide a reference method for predicting carbon emissions in other regions and a guide for future regional emission reduction., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Digital inclusive finance eases credit constraints on innovative small and medium-sized enterprises which contributes to urban green technology innovation in China. Government intervention plays an essential role in the development of digital inclusive finance. Based on the panel data of 243 cities in China from 2011 to 2019, this paper empirically examines the relationship between digital inclusive finance and urban green technology innovation as well as the intrinsic mechanism of government intervention. The findings show that, even after a series of robustness tests, digital inclusive finance can promote the quantity and quality of green technology innovation. In terms of its mechanism, digital inclusive finance can empower green technology innovation by complementing traditional financial development and stimulating green consumption, both in terms of supply and demand. At the same time, in the dynamic process of digital financial inclusion from low to high, the development of traditional finance and green consumption level on the marginal promotion of green technology innovation continues to strengthen. The nonlinear relationship test reveals that there is a significant double threshold effect on the positive impact of digital inclusive finance on urban green technology innovation with the evolution of government intervention. The innovation incentive effect of digital financial inclusion will be marginal decreasing with the increase of government intervention. Further considering the heterogeneity of urban geographic location and environmental regulation, it is found that digital financial inclusion promotes green technology innovation more in eastern and high-environmental regulation cities. Based on the above research conclusions, this paper argues that while developing digital inclusion finance, government support policies should be adjusted promptly to constantly stimulate the "Metcalfe's law" effect of digital inclusive finance enabling green technology innovation., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Drawing on the textual contents of the Chinese local government work reports, this paper focuses on the impact of leading officials' audits of natural-resource assets on the local environmental attention allocation. The study has found that during the pilot period of audits, compared with the non-pilot cities, the local government in the pilot cities has concentrated more on the ecological environment field and has placed greater emphasis on the actual environmental governance. The results of mechanism analysis show that differences in the personal and take-office characteristics of local officials, may lead to different promotion pressure and performance evaluation modes, and then have a different impact on local environmental attention. The test results of consequence analysis show that the environmental attention in the pilot cities can be further transformed into environmental administrative and financial governance behavior. The paper discusses the policy effect and internal mechanism of leading officials' audits of natural-resource assets from the perspective of local governments' environmental attention, providing empirical evidence for China to carry out the top-level design of environmental policy based on the idea of optimizing officials' performance evaluation mechanism., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Environmental justice is an important safeguard for pollution control, and this paper is interested in its ability to promote carbon emission reduction. One unique facet of reinforcing local environmental justice involves the establishment of environmental courts by Intermediate People's Courts. Taking this as the starting point, this study constructs a quasi-natural experiment to investigate the strengthening of urban environmental justice. Analyzing empirical data from 283 prefecture-level cities in China spanning 2006 to 2019, we employ multi-period and spatial difference-in-differences approaches to probe the impact of environmental justice strengthening on carbon reduction. Our results indicate a substantial contribution of strengthened environmental justice to reducing carbon emissions. Specifically, the establishment of environmental courts can curtail carbon emissions by an estimated range of 11.7 to 12.9%. Also, the mechanism analysis underscores that the carbon reduction effect primarily arises from enhanced efficiency in processing environmental cases. Moreover, this effect is notably pronounced in regions with robust governmental environmental regulations. Notably, in areas with limited public environmental concern, environmental courts effectively complement existing environmental regulations. Furthermore, a significant positive spillover effect of environmental courts on carbon emission reduction is observed in geographically adjacent economic zones., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Most Chinese companies face financing constraints and thus lack sufficient funding for operations and investments that would better control their pollutant emissions. A sample selection bias corrected model is constructed to study the impact of financing constraints on the Chinese companies' pollutant emissions using company-level emissions data. The empirical results revealed that financing constraints increase the pollutant emissions of the Chinese companies, including the emissions of industrial wastewater, industrial solid waste, and sulfur dioxide. The heterogeneity analysis showed that the impacts of financing constraints on the pollutant emissions of companies operating in highly polluting industries and non-state-owned companies are more significant. And compared with internal financing, bank financing can better mitigate the impact of financing constraints on pollutant emissions through green loan projects. The results are stable after controlling for other important company factors and testing the robustness using the subdivided regression. Several political implications are drawn based on these findings that can help control the pollutant emissions of Chinese companies from the perspective of financing constraints., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Campaign-style environmental implementation (CEI) is widely exerted in environmental protection, while its benefits and costs are controversial. We take advantage of the Central Environmental Protection Inspection (CEPI) System-a latest and distinguished form of CEI launched by China in 2016, as a quasi-natural experiment, to compare the benefits and costs of CEI based on water pollution effect estimates. Our results based on the annual panel data from 500 cities during 2009-2018 show that CEPI significantly reduced water pollution by an average of 20.7%. Further cost-benefit analysis based on the estimates of water pollution reduction shows that the potential health benefits of mortality and morbidity reduction resulting from CEPI are at least $12.26 billion, without bearing additional economic costs. We also explore why CEPI is cost-effective and find that CEPI reduces water pollution and becomes cost-effective mainly through deterring local officials, punishing polluting enterprises, and increasing public participation in environmental governance., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Free-trade zones are highlands of regional development that have a radiating effect on surrounding cities. This paper uses Yangtze River Delta Urban Agglomeration (YRDUA) data from 2003 to 2018, to examine the impact of the China (Shanghai) pilot free-trade zone (SPFTZ) on green total factor productivity (GTFP) in the YRDUA. It uses the regression discontinuity (RD) method and analyzes the influence mechanism with the help of the mediating effect model. The paper presents the following major findings. The establishment of the SPFTZ significantly promoted GTFP in the YRDUA, with technological progress being the main driving force. An analysis using the mediating effect model found that financial efficiency and industrial structure upgrading play a complete mediating role in GTFP growth in the YRDUA. Therefore, the SPFTZ should make use of its policy advantages, take full advantage of the effect of the green growth pole, and promote green mutual development with the YRDUA., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Very few studies exist in rationalizing comprehensively the relationship between market integration and green economic growth in China. This paper tries to answer the question whether and how market integration influences regional green economic growth in China. Based on the panel data of 285 city-level regions from year 2004 to 2018 in China, this paper develops explanatory mechanism and discusses the influence theoretically and empirically. To advance the analysis, we construct market integration indicator through relative price variance method based on commodity retail price index and employ the Malmquist-Luenberger (ML) productivity index and DEA-SBM (data envelopment analysis-slacks-based measure) model to evaluate green total factor productivity (GTFP) as indicator for green economic growth. Our empirical findings are: (1) Apparent regional imbalance exists in both the development of market integration and green growth and gaps are expanding from year 2004 to 2018. (2) Market integration promotes regional green growth significantly. (3) Mechanism analysis illustrates that market integration fosters green growth through economies of scale effect, composition effect and spillover effect, respectively. (4) Heterogeneous analysis suggests that the influence from market integration on green growth varies depending on region's difference in traffic situation and in overall development level., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

China's Going Global Strategy and Belt and Road Initiative gained great attention among scholars. Moreover, it is believed that Chinese investments abroad cause serious social and environmental externalities. Hence, in this paper, we examine how China's foreign direct investments influence the carbon emissions of 35 Belt and Road Initiative countries from 2000 to 2019. To do so, we use a panel model that accounts for heterogeneity and country cross-section dependence. Our results show that while other countries' foreign direct investments have contributed to the deterioration of the environment in these countries, Chinese investments have not. This substantiates the hypothesis of the halo effect influence of China's foreign investments as opposed to other countries' investments which may seek a haven for its carbon emissions. These results highlight the importance of source and destination regulations of foreign direct investments in terms of their environmental impact and carbon emissions in the Belt and Road Initiative countries. It also provides a fresh finding on the efficacy of China's foreign investment management policies and regulations in producing the desired environmental outcome in hosting countries., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Using data from Chinese industrial firms from 2003 to 2012, this paper utilizes a difference-in-differences approach to investigate the impact of stringent command-and-control environmental regulations on firm productivity through Chongqing's daily penalty policy (DPP). Unlike the previous command-and-control environmental regulations of "low penalty amounts", "one-size-fits-all", and "one-off penalties", the DPP with "high deterrent effect" and "high cost of non-compliance" imposes continuous high fines of a fixed daily amount on persistent environmental violators. This is conducive to improving environmental quality while significantly increasing firms' total factor productivity (TFP). It provides empirical evidence for the validity of the strong Porter hypothesis in developing countries. A series of robustness tests ensure the credibility of these findings. The mechanism analysis shows that DPP can improve TFP of firms by stimulating the innovation compensation effect of firms and crowding out high polluting and inefficient firms in the industry. Heterogeneity analysis shows that the productivity of highly polluting, private, non-exporting and small-scale firms is significantly increased under the influence of DPP. This study provides new ideas for improving command-and-control environmental regulation to bring into play its Porter effect, and offers experiences and insights for regulating firms' emission behaviors to achieve a win-win situation for both economic growth and green development., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Existing researches verify Porter hypothesis mainly through one of its core establishment paths, innovation compensation, but ignore the other one, first-mover advantages. This paper considers both these paths and further distinguishes environmental R&D and non-environmental R&D in empirical study. Based on the smooth transition principle of "charge to tax" in China, this paper, taking Chinese A-share listed companies that have disclosed environmental R&D from 2008 to 2017 as sample and predicting environmental tax by pollution charge, analyzes the relationship between environmental tax and firm performance and its transmission mechanism. First, our results show that environmental tax can improve firm performance, and this influence remains in long term. After introducing instrument variable (IV) to deal with endogeneity and conducting a series of robustness tests, we then find that the relationship between environmental tax and firm performance is a robust causality. Eventually, we apply mediating effect model to further confirm the two core paths of Porter hypothesis by manifesting that environmental tax can affect firm performance through both innovation compensation and first-mover advantages. Our contributions are revealing the micro mechanism of environmental tax on firm performance, providing evidence from China to support strong Porter hypothesis, and offering some key points regarding environmental tax reform and corporate green strategy., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Labor agglomeration with heterogeneous skills has different effects on urban air pollution. Based on the panel data of 263 prefecture level cities in China from 2006 to 2019, this paper constructs a Spatial Durbin Model to explore the impact of skill heterogeneous labor agglomeration and the interaction between skill heterogeneous labor agglomeration on urban air pollution. The results show that there is a positive U-shaped relationship between high-skilled labor agglomeration, low-skilled labor agglomeration, and urban air pollution. From the perspective of restraining urban air pollution, high-skilled labor agglomeration is stronger than low-skilled labor agglomeration. Under the influence of high skilled labor agglomeration, the inhibitory effect of low-skilled labor agglomeration on urban air pollution is enhanced. High-skilled labor agglomeration and low-skilled labor agglomeration reduce the degree of urban air pollution by promoting the improvement of urban innovation level. Based on this, this paper puts forward some policy suggestions, such as further promoting urban labor agglomeration, formulating reasonable urban population management policies, strengthening labor exchange and learning, and carrying out labor knowledge and skills training., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Whether high-speed rail (HSR) can promote the coordination between the economy and environment is a critical issue that needs to be investigated. We used balanced panel data of 281 prefecture-level or above cities in China from 2005 to 2017 to consider the opening of HSR as a quasi-natural experiment. We integrated the difference-in-differences (DID) model, the spatial difference-in-differences (SDID) model, and social network analysis (SNA) to empirically investigate the impact of HSR on urban environmental efficiency (UEE). The results showed that HSR significantly improved UEE by 4.6% annually during the study period, although the effect of HSR on UEE exhibited a time lag and varied dramatically in different cities. An analysis of the mechanism showed that the effect of technological innovation and the structural effect brought by the opening of HSR were the main contributors to the improved UEE. Further analysis showed that HSR service centrality also significantly improved UEE and HSR opening and HSR service centrality both had positive spatial spillover effects on the UEE of neighboring cities. Several policy implications are proposed accordingly to make full use of the advantages of HSR to improve UEE for China., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Environmental quality and economic growth are important factors that need to be balanced for sustainable development, especially in developing countries where technology is relatively backward. Many studies have shown that technology imports may be beneficial to economic growth, but once the resources and environment are taken into consideration, the role of technology imports becomes blurred. Based on provincial panel data of China from 2004 to 2019, this paper investigates the influence mechanism of domestic and foreign technology imports on the green economic efficiency (GEE) of 30 provinces in China. There are two main conclusions: First, GEE is spatially related and the impact of technology imports on GEE has a significant spillover effect. Besides, the relationship between technology imports and GEE is non-linear, both in terms of direct and indirect effects. Second, independent innovation plays an important role in the influence mechanism of technology imports on GEE. As the level of independent innovation increased, the impact of technology imports on GEE turns from negative to positive, and it is strengthened through the channel of "transfer-absorption-diffusion-re-innovation." In this regard, some measures should be taken to enhance the role of technology imports in improving GEE., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This paper is a pioneer attempt using ecological footprints, the latest environment sensitivity proxy to be regressed, contributing to the scarce literature concerning one of the most burning global dilemmas of the era. For econometric analysis, fiscal and monetary tools, green energy consumption, and economic growth have been chosen as a set of regressors data spanning 1990-2020 in China facing the highest total ecological footpaths. And giving priority to the relevancy, reliability, and robustness autoregressive distributed lag (ARDL), fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) have been applied for instant and eternal sensitivities, followed by the widely used stationarity tests (augmented Dicky-Fuller and Phillips-Perron tests) and bounds test. Granger's ordeal has also noticed causal inferences. Cointegrating findings are robust across all techniques, and ARDL results remain consistent regardless of short and prolonged duration. We witness positive and statistically significant (at 10%) responsiveness of ecological footprints (EFP) to China's rapid gross domestic output (GDP) growth per capita fueled by fossil fuels (primarily coal). Contrarily, negative/inverse sensitivity to expansionary fiscal (higher government expenditures, GEx), contractionary monetary policies (higher policy rate, DR), and green energy use (REnC). Besides, EFP demonstrates statistically significant reciprocal interconnection with GDP and REnC but a unidirectional connection with DR (DR → EFP). GDP has effective collaboration with REnC and GEx whereas single-sided relationship DR as (GDP → DR). Finally, some policy choices are endorsed., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This paper aims to examine the nexus among carbon dioxide (CO 2 ) emissions, urbanization level and industrial structure in North China over the period 2004-2019, according to an expanded Cobb-Douglas production function. The panel econometric techniques are employed to complete the empirical analysis, including cross-sectional correlation test, panel unit root test, panel co-integration test, and panel Granger causality test. The empirical results support the long-term equilibrium relationship among CO 2 emissions, urbanization level and industrial structure in North China, and the urbanization level contributes most to CO 2 emissions, followed by fossil energy consumption. Furthermore, the bidirectional causality between CO 2 emissions and urbanization level and unidirectional causality from industrial structure to CO 2 emissions are found in North China, indicating that urbanization level and industrial structure have significant impacts on CO 2 emissions. Finally, according to the empirical findings, several policy suggestions are proposed for the purpose of reducing CO 2 emissions in North China., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Air quality issues, especially haze pollution, have become an important aspect that threatens the sustainable development and health of human beings. Previous studies on the environmental effects of emissions trading system (ETS) mainly focused on carbon emission reduction, instead of focusing on the synergistic governance effect between carbon emission and PM 2.5 reduction. Based on the PSM-DID method and the World Development Index (WDI) database, this paper examines whether the EU ETS has a spillover effect on PM 2.5 damage reduction, and discusses the related impact mechanisms. The research results show that the EU ETS promotes the reduction of PM 2.5 damage, and in different phases of implementation, the impact of the EU ETS on the reduction of PM 2.5 damage has a dynamic effect. The robustness test results also show that the research conclusions of this paper are highly reliable. Finally, this paper gives relevant policy suggestions, which can encourage countries to achieve carbon emission reduction targets while helping to reduce PM 2.5 damage, and eventually achieve a win-win situation between economic growth and environmental improvement., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Taking industrial waste gas control as an example, this study explores the impact of fiscal decentralization on the efficiency of local governments' environmental governance under the pressure of competition, and analyzes the role of competition among local governments and support for R&D activities. The results demonstrate that fiscal decentralization can significantly promote the efficiency of local governance on control of waste gas, and this positive effect is mainly realized through the support from local government for R&D activities. As for the influence of inter-governmental competitions, only the competition in terms of governance efficiency delivers a significant U-shaped impact, and competition in expenditure scale and economy area weakly inhibits the positive influence of decentralization, meaning that the evaluation system centered on economic growth and the imitation strategy of local expenditure will not lead to a great decline in the efficiency of the use of environmental governance. Overall, this study suggests that further fiscal decentralization, emphases on government support for R&D activities, and enhanced environmental assessment in official evaluation are all the important directions for boosting the efficiency of governance., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Regional density is a useful tool for analyzing regional spatial structure as well as a good starting point for analyzing regional CO2 emissions per capita. This paper empirically analyzes the relationship between regional density and per capita CO 2 emissions in China's prefecture-level administrative regions. We improve the CO 2 emission measurement method for prefecture-level administrative regions and estimate the per capita CO 2 emissions of 252 prefectural-level cities in China from 2003 to 2013. Using panel fixed effect model regression, and taking the terrain roughness index as an instrumental variable to solve endogeneity, we find that the relationship between regional density and per capita CO 2 emissions presents in an inverted U-shape, per capita CO 2 emissions first increase with the increase of regional density, and after reaching the turning point, it decreases with regional density. In a mechanism test, analyzing the interaction terms between regional density and industrial structure, and regional density and urbanization level respectively. We found that industrial structure and urbanization are important mechanisms for regional density to affect CO 2 emissions. In order to reduce per capita CO 2 emissions, we propose corresponding policy implications for the regions in different positions of the "U" curve., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The progress of agricultural green technology is an important means and fundamental way to achieve high-quality development of agriculture. The current study takes the panel data of 31 provinces in China from 1998 to 2018 and uses the Epsilon Based Measure-Global Malmquist-Luenberger (EBM-GML) model to measure China's agricultural green technological progress (AGTP) and discusses its dynamic evolution characteristics in the spatiotemporal dimensions. Finally, we analyze the spatial spillover effects of AGTP by the spatial Dubin model. The results show that China's AGTP showed a trend of first rising and then falling, and the average value is 1.0525. AGTP has obvious regional unbalanced development, and the regional differences are expanding. It shows that AGTP between adjacent areas is closely linked. The Moran's I index shows that AGTP has a significant positive spatial correlation. The local Moran's I index shows that AGTP is concentrated in Northwest, Northeast, and North China, and green technological is degraded in East and South China. From the spatial spillover effects of AGTP, the level of agricultural economic development, real GDP per capita, and urbanization have significantly promoted AGTP in the local and neighboring areas, while the agricultural internal structure and the level of labor inhibit AGTP in the local and neighboring areas. In addition, the administrative environmental policy (ENVP) and the economic environmental policy (ECOP) have negative impacts in neighboring areas, while the policy has negative spillover effects and positive spillover effects in the local area, respectively. Therefore, we should adhere to the concept of green development, pay attention to the regional exchange of green technology, concentrate policies on low-low concentration areas, and increase the follow-up tracking and supervision mechanism of the policy design and implementation process., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Exploring the low-carbon energy transformation pathway is vital to coordinate economic growth and environmental improvement for achieving China's carbon peak target. Three energy-target scenarios are developed in this paper, considering the targets of energy structure, electrification rate, and carbon mitigation towards 2030 announced by the Chinese government. A dynamic multi-sectoral computable general equilibrium model, CHINAGEM, is employed to examine the economic and environmental effects under different pathways of long-term low-carbon transformation. It detects that China's energy structure would substantially transfer to the low-carbon and clean one, whereas CO 2 , SO 2 , and NO X emissions in 2020-2030 would vastly abate along with all three energy-target scenarios. Different pathways would produce varying positive impacts on China's macro-economy and achieve the different extent of double dividend effects. It is highly conceivable for China to peak its carbon emission at 12.4 GtCO 2 by 2028 if it serves the comparatively more stringent low-carbon transformation pathways., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The sustainable development of China's economy is bottlenecked by resource shortage and environmental pollution. As the leading resource consumer and pollutant source, the industrial sector needs to improve its energy efficiency. This paper establishes a super epsilon-based measure (Super-EBM) model with bad outputs like environmental cost and evaluates the industrial green total-factor energy efficiencies (IGTFEEs) of 30 provinces in China during 2000-2017. Unlike previous research, the main contribution of this paper is to choose four environmental pollutants as bad outputs (industrial carbon dioxide, industrial sulfur dioxide, industrial chemical oxygen demand, industrial solid waste). By contrast, the previous studies mostly only take one environmental pollutant as bad output, i.e., the bad outputs are not fully measured. Then, the spatiotemporal dynamics and spatial correlations of the IGTFEEs were analyzed, and the influencing factors of IGTFEE were examined empirically with a spatial econometric model. Finally, this paper adopts generalized method of moments (GMM) to solve the endogenous problem, trying to assure the robustness of estimation results. The results show significant provincial differences in IGTFEE. Most eastern coastal provinces achieved satisfactory IGTFEEs, while most inland provinces had undesirable IGTFEEs. Eastern region achieved the highest IGTFEE, followed by central region; western region had the lowest IGTFEE. The IGTFEE improved over time in some provinces while worsened greatly in some provinces. The IGTFEE in most provinces need to be further improved. Global Moran's I values indicate that the provincial IGTFEEs were clustered in space, rather than randomly distributed. Local indication of spatial association (LISA) map reflects significant local spatial clustering of provincial IGTFEEs. In addition, IGTFEE is significantly promoted by industrial structure, technological innovation, human capital, opening-up, and energy structure yet significantly suppressed by ownership structure and environmental regulation. Considering the endogeneity, GMM results show that the estimation results of the model were robust. Specific policy recommendations include vigorously developing high-tech industries, deepening state-owned enterprises reform, diverting more funds to research and development, cultivating versatile talents, introducing environmentally-friendly foreign capital, accelerating the implementation of clean energy development strategy, and widening the fund channels of pollution control investment., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The employment effect of enterprises embedded in global value chains (GVCs) has important theoretical value, but existing research has ignored the impact of environmental costs on employment under the division of labor system within the value chain. By constructing a GVC-embedded index considering environmental costs, this study investigates the impact of Chinese industrial enterprises' embedding into GVCs on employment at both the theoretical and empirical levels. It is found that when the environmental cost is considered, the improvement of GVC embeddedness has a significant inhibiting effect on employment, especially for female laborers, lower-skilled laborers, state-owned enterprises, private enterprises, and enterprises in the eastern region of China. The research also shows that when considering environmental costs, the labor cost increase effect enhances the negative effect of increased GVC embeddedness on employment, while the innovation promotion effect and the foreign direct investment effect serve to mitigate the negative effect. The results provide a reference for developing countries seeking to effectively protect people's livelihood and employment while achieving a leap in the division of labor along the green value chain., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Saline loess is an important cause of environmental geo-issues in northwest China. In this research, electrical resistivity of loess with different moisture contents and NaCl concentrations was measured at three test frequencies. Results indicates the plastic limit (16%) and around 2% NaCl concentration are the critical content affecting the variation of loess electrical resistivity. The variation and conductivity for conductive paths are affected by moisture content and NaCl concentration respectively. Combined with three-phase composition and diffuse double-layer structure, new models that consider the effect of moisture content and NaCl concentration indicate good applicability in the validation datasets from different types of soil. A new model was verified by comparison between previous studies and experimental results. This research provides (i) theoretical support for the calibration of large-scale electrical field surveys and the observation of saline loess and (ii) a valuable reference for the prevention of environmental geo-crisis and the utilization of soil resources in northwestern China., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Environmental sustainability concerns are growing worldwide. Many recent studies have focused on key indicators of CO2 emissions, but less consideration has been given to human capital. This study examines the impact of human capital on CO2 emissions in Brazil, Russia, India, China, and South Africa (BRICS) economies from 1991 to 2019 using a nonlinear panel autoregressive distributed lag approach. Findings show that positive change in education has reduced CO2 emissions, while a negative change in education has increased CO2 emissions in the long run in a group of BRICS. Regarding economy-wise analysis, a positive change in education reduces CO2 emissions in Russia, China, and South Africa in the long run, but a negative change in education has an increasing impact on CO2 emissions in Brazil and China. The results of robustness are also maintained in group and economy-wise empirical analysis. Policymakers should develop the education sector infrastructure in order to support the decrease of CO2 emissions., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

An improvement in total factor productivity of the power industry (TFPPI) is crucial for achieving China's green transformation and high-quality development. Considering the technological heterogeneity of different regions, the Meta-frontier Global Malmquist-Luenberger(MGML) index was constructed to measure TFPPI in China's 30 provinces from 2003 to 2017, and then we investigated the dynamic evolution and regional differences of TFPPI. On this basis, the two-step system GMM method was used to explore the influencing factors of TFPPI. The results showed that: (1) During the survey period, the average annual growth rate of China's TFPPI was 4.2%, and average values of TFPPI in all provinces were greater than 1. The innovation effect was the key to TFPPI growth, while the catch-up effect and leading effect were not significant. (2) TFPPI showed a decreasing trend from the western to eastern and central regions, with average annual growth rates of 5.69%, 3.66%, and 2.89%, respectively, and the driving factors of each region were different. Moreover, the technology gap was narrowing. (3) Both the economic development level and R&D level had a positive impact on TFPPI, whereas the power consumption intensity was negatively correlated with TFPPI. Based on the conclusions of this paper, some effective recommendations were put forward to improve TFPPI., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Against the backdrop of current global collaboration on mitigating carbon emissions, how to reduce the energy uses in the Belt and Road Initiative area becomes an urgent and big challenge facing the global community. Using the Eora input-output database, this paper accounts the embodied energy trade between Belt and Road countries in 2015, followed by an investigation of the factors influencing the embodied energy trade through a panel gravity model. Global value chain participation and position are two newly considered factors in analyzing the determinants of embodied energy flow. We find that the main bilateral embodied flow paths are from South Korea to China, China to South Korea, Singapore to China, Ukraine to Russia, and Malaysia to Singapore. Five percent embodied energy flow paths account for 80% of the total bilateral embodied energy flow volume between Belt and Road countries. The gravity model results indicate that gross domestic product (GDP) per capita, population, global value chain participation are the key drivers of bilateral embodied energy trade, while the industrial share of GDP and global value chain position are negatively related to the trade. Energy intensity plays a crucial role in reducing the bilateral embodied energy flow. These results are useful in the policymaking of sustainable development for the Belt and Road Initiative., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Management of economic growth targets is a universal measure employed by worldwide governments for macroeconomic regulation. This paper aims to empirically investigate the impact of economic growth targets set by governments of prefecture-level cities on the environmental regulation intensity. We extracted panel data on annual economic growth targets and environmental regulation indicators from the government work reports (2009-2016) of 284 China's prefecture-level cities. The study concludes that an increase in economic growth target significantly weakens the intensity of environmental regulation. The conclusion still holds true after robustness tests, including changing measurement variables, regression samples, and conducting endogenous tests. The underlying reason for the inhibitory effect may be that in order to achieve economic growth targets, local governments prefer less stringent environmental regulations. They subsequently expand outputs in the short term by increasing the proportion of secondary industry in GDP, land transfer area, and fixed asset investment. Further research in this paper also finds that only cities with low economic development levels and low openness to the outside world experience the negative effect of a local government's annual economic growth target on environmental regulation intensity., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study aims to explore the driving determinants on the export-related carbon intensity (ECI) of China, to better understand the impact of international trade on climate change governance and facilitate China's carbon intensity mitigation goals. First, China's ECI evolution and its gaps with the USA and India are measured during 2002-2014. Then, the main drivers of China's ECIvert study further discusses the influencing factors of ECI in the manufacturing industry using the environmental-extended STIRPAT model and GMM method. The results show that (1) China's overall ECI increases from 1.50 Kg/US$ in 2002 to 1.92 Kg/US$ in 2005 and then decreases to 1.27 Kg/US$ in 2014. The ECI of the manufacturing industry is significantly higher than that of the agriculture and service industry. China's ECI gap with the USA is greater than that with India, and both show a downward trend. (2) Carbon emission coefficient is the domain factor to reduce China's ECI during 2002-2014; the effects of the value-added coefficient, input-output structure, and final demand are limited. The input structure dominantly expands China's ECI gaps both with the USA and India, followed by the value-added coefficient. The carbon emission coefficient enlarges the ECI gap with the USA while reduces that with India. (3) Industrial productivity and value-added rate are negatively correlated with ECI in the manufacturing industry, while per capita capital stock plays the opposite role. The positive correlation between energy intensity and CIE becomes significant after distinguishing technology heterogeneity. In contrast to the non-tech-intensive manufacturing industry, the increase of backward GVCs participation of tech-intensive ones will reduce the ECI. The threshold effect of backward GVCs participation exists in the whole manufacturing industry. Targeted ECI reduction policy implications are suggested., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

As a key economic resource, energy plays an important and strategic role in the national economy. Conserving energy and improving energy efficiency are of great significance to the sustainable economic development of a country. Based on provincial panel data from 2006 to 2017 in the Yangtze River Economic Belt (YREB), this article set up two econometric models and applied the panel regression analysis techniques to examine the impact of environmental investment and resource endowment on energy efficiency, and the combined impact of environmental investment and resource endowment on energy efficiency, and tested fixed effects and random effects to obtain detailed and specific results. The results of the study are as follows: (1) resource endowment is significantly and negatively correlated with energy efficiency, and there exists a resource curse in terms of energy efficiency in YREB. (2) Current environmental investment has a catalytic effect on energy efficiency, and lagged environmental investment has a greater effect on energy efficiency improvement than current environmental investment. (3) Environmental investment can effectively reduce the negative impact of resource endowment on energy efficiency. The results of the study will help improve YREB's energy efficiency and promote the coordinated development of economic development and resource conservation and environmental protection., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This paper examines the impact of earthquake risk on the lending behavior of local Chinese banks. The results show that when facing earthquake risk, banks will adjust their lending behavior, including decreasing the amount of loans and mortgage loans and increasing credit loans and loan loss provision, but the effect only exists for banks without inter-provincial branches or that are located in cities with a higher population density. In general, earthquake risk cannot significantly affect the performance of banks, but it can deteriorate the performance of banks that have not adjusted their lending behavior., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

More recently, the COVID-19 pandemic outbreak has created massive economic policy uncertainty (EPU). EPU and its economic fallout have been a hot topic of study; however, the impact of EPU on CO 2 emissions has been seldom addressed to date. This paper investigates the effects of the EPU on CO 2 emissions. It elucidates the role of EPU in moderating the environmental regulation-CO 2 emissions nexus at the national and regional levels using the panel data model and provincial panel data from 2003 to 2017 in China. The main empirical results are as follows. The EPU has a negative impact on carbon emissions; however, this relationship is non-significant even at the 10% level in the central and western region datasets. Environmental regulation positively increases the CO 2 emissions implying that the green paradox occurs in the whole and western regions datasets. From the perspective of the moderating effect of uncertainty, EPU exerts a positive impact upon the environmental regulation-CO 2 emissions nexus in the whole and western region datasets. The moderating effect is not significant in the eastern and central regions. The results demonstrate that the re-examination of the EKC hypothesis is inconclusive. Kuznets relationship between economic growth and CO 2 emissions for the national, eastern, and central samples was confirmed. In contrast, CO 2 emissions monotonically rise as GDP grows for western datasets. Based on the overall findings, some policy implications were put forward. We recommend that the local government should consider EPU to improve the institutional environment. Further, different regions should implement various environmental policies according to regional conditions maximizing the emission reduction potential., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)