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The frequent detection of persistent per- and polyfluoroalkyl substances (PFAS) in organisms and environment coupled with surging evidence for potential detrimental impacts, have attracted widespread attention throughout the world. In order to reveal research hotspots and trends of technologies for PFAS removal, herein, we performed a data-driven analysis of 3975 papers and 436 patents from Web of Science Core Collection and Derwent Innovation Index databases up to 2023. The results showed that China and the USA led the way in the research of PFAS removal with outstanding contributions to publications. The progression generally transitioned from accidental discovery of decomposition, to experimentation with removal effects and mechanisms of existing methods, and finally to enhanced defluorination and mechanism-driven design approaches. The keywords co-occurrence network and technology classification together revealed the main knowledge framework, which was constructed and correlated through contaminants, substrates, materials, processes and properties. Moreover, adsorption was demonstrated to be the dominant removal process among the current studies. Subsequently, we concluded the principles, advances and drawbacks of enrichment and separation, biological methods, advanced oxidation and reduction processes. Further exploration indicated the hotspots such as alternatives and precursors for PFAS ("genx": 1.258, "f-53b": 0.337), degradable mineralization technologies ("photocatalytic degrad": 0.529, "hydrated electron": 0.374), environment-friendly remediation technologies ("phytoremedi": 0.939, "constructed wetland": 0.462) and combination with novel materials ("metal-organic framework": 1.115, "layered double hydroxid": 0.559) as well as computer science ("molecular dynamics simul": 0.559, "machine learn"). Furthermore, the future direction of technological innovation might lie in high-performance processes that minimize secondary pollution, the development of recyclable and renewable treatment agents, and collaborative control strategies for multiple pollutants. Overall, this study offers comprehensive and objective review for researchers and industry professionals in this field, enabling rapid access to knowledge guidance and insights into research frontiers. [Display omitted] [ABSTRACT FROM AUTHOR]

China's coastal region is the major geographical unit for the future development of China's industrial sector. The transformation of basic structure to high-class development in China's coastal places is a significant tool for promoting the changes related to quality, power and efficiency in regional economic development. In the 21st century, environmental and energy issues have increased worldwide, and challenges related to environmental pollution, energy crises, and ecological imbalances have emerged. To climate change and energy utilization, the sustainable progress of clean energy is the new route of future energy development. Based on China's non-polluting energy growth process in the last ten years, this article explores China's clean/green energy policies and economic growth development plans. Clean energy utilization is crucial for sustainable development in the context of high-quality economic growth and climate change. However, the monetary evolution and carbon emission are not investigated whole from the clean energy aspects. Using Wind energy sources as the acceptable variable, this paper employs threshold regression and impulse functions to assess the energy consumption and economic growth on carbon emission in 30 Chinese provinces over the 2000 to 2020 period. The Deep Belief Network (DBN) model predicts wind energy utilization and efficiency. The results show that economic development and carbon emissions are connected. Further, growth influences promote the offset of carbon emissions. Green innovation alters the nexus of carbon emissions, and China's economy reduces carbon usage. It provides the decision-making policies for clean energy development. • China's Coastal region is the major geographical unit for the future development of China's industrial. • In high-quality economic growth and climate change, clean energy use is vital for sustainable development. • The utilization of wind energy and it's efficiency is predicted using Deep Belief Network (DBN) model. • Empirical results link economic growth with carbon emissions, showing growth promotes emissions offset. • Green innovation changes the economic growth-carbon link, aiding China's carbon reduction efforts. [ABSTRACT FROM AUTHOR]

Frontier studies have neglected the impact of digital transformation (DT) on the synergy for pollution and carbon reduction (SPCR) from the perspective of micro enterprises. This paper explores the SPCR effect of DT, as well as its mechanism at micro-firm level. The study found that: (1) DT significantly facilitates corporate SPCR. For every 10% increase in the level of DT, the ranking of SPCR will rise by about 2.3 places. This effect is more obvious in high-tech firms and non-heavy polluters, firms in the eastern region in China, and non-SOE. (2) DT creates innovation-driven and structure-optimizing effects, which enhance the corporate green innovation ability, optimize the business structure and capital allocation structure of enterprises, and then drive the SPCR. (3) External public environmental concerns (PEC) and internal corporate ESG governance act as "accelerators" promoting the SPCR effect of DT. Based on these, policy implications are made to accelerate the pace of corporate DT, give full play to the first-mover advantage, and break the "pollution (carbon) lock-in" with a view to providing theoretical references for the listed enterprises' digitalized governance of SPCR, as well as the governmental departments' formulation of relevant guiding policies, and striving to achieve the high-quality development goal. • Explore the effect of DT on synergy for pollution and carbon reduction (SPCR). • Analyze the heterogeneity of DT affects corporate SPCR. • Investigate the mechanism by which DT affects corporate SPCR. • Discuss the moderating effects of informal regulations that improve the SPCR effect of DT. [ABSTRACT FROM AUTHOR]

Air pollution has been one of the biggest environmental challenges for cities in their pursuit of sustainability. The removal of air pollutants usually entails a cost that can negatively impact economic activities. Assessing urban environmental performance can offer valuable insights for cities to balance their economic production and environmental protection. This paper develops a novel approach to measuring environmental performance by using the Euclidean distance function. An appealing feature of this approach is its ability in endogenously allocating the optimization pathway to each emitter, thereby avoiding arbitrary estimation results and distorted managerial implications. We apply this approach to study the environmental performance of Chinese key environmental protection cities. We find the heterogeneity in performance estimates and endogenous optimization pathways. Prioritizing the reduction of a specific type of emissions while simultaneously increasing industrial output value seems to be the most appropriate objective for the majority of cities. Our study can serve as a basis for urban governments to pinpoint the underlying factors contributing to low urban environmental performance and establish diverse objectives for enhancing environmental performance. • Environmental performance index is constructed based on endogenous directions. • A Euclidean distance function is used to identify endogenous directions. • Optimization pathways and environmental performance show heterogeneity among cities. • Mitigating NO x emissions can improve environmental performance significantly. [ABSTRACT FROM AUTHOR]

The fiscal system plays an important role in the government's environmental governance efforts. There is currently no consensus on how fiscal structure adjustments impact pollution and carbon reduction. This paper uses China's fiscal "province-managing-county" reform (FPMCR) implemented in 2004 as a quasi-natural experiment, utilizing panel data from 1670 counties in China from 2000 to 2020 to investigate the impact of fiscal decentralization on reduction pollution and carbon emissions (RPCE), as well as its underlying mechanisms. The results show that (1) from 2000 to 2020, China's RPCE shows an overall trend of fluctuating increase, with its value turning positive after 2013. China's RPCE exhibits a spatial pattern characterized by "lower in the north, higher in the south; higher in the east, lower in the west". (2) After implementing FPMCR , the RPCE levels in reformed counties decreased by −1.44%, showing that reformed county-level governments prioritize economic development over environmental protection. (3) The mechanism analysis found that after implementing FPMCR , reformed counties experienced a 9.16% increase in nighttime light intensity (NLI), and a 3.99% and 4.34% increase in the number of large-scale industrial enterprises (NLIE) and industrial agglomeration (IA), respectively. This suggests that FPMCR leads to radical urbanization and rapid industrialization in counties, which is detrimental to the improvement of RPCE levels. (4) The spatial heterogeneity analysis found that FPMCR's impact coefficient on RPCE levels in the eastern regions is −1.96%, while in the western regions it is −1.16%. This indicates that reformed counties in the eastern regions are more likely to invest expanded fiscal resources in economic development projects, leading to a decrease in RPCE levels. (5) The temporal heterogeneity analysis found that after the promulgation of the " Three-Year Action Plan to Win the Blue Sky Defense Battle " in 2018, the adverse impact of FPMCR on RPCE is completely reversed, leading to a 1.76% increase in RPCE levels. (6) Further analysis reveals that localizing leaders can slow down the promotion of county-level urbanization and industrialization by the FPMCR , benefiting the improvement of RPCE levels. In other words, "the outsider monk will not recite scriptures as well as a local one". This study has clarified the causal relationship and underlying mechanisms between fiscal decentralization and environmental governance, providing reliable theoretical support for optimizing grassroots fiscal systems and reducing environmental pollution in other transitional economies. It enriches the field of environmental economics related to fiscal decentralization. • Leader localization can shape government behavior following an increase in financial resources. • Enriched environmental economics research related to fiscal decentralization. • Increase more refined reduction of pollution and carbon emissions indicators to improve evaluability. • Clarify the causal relationship and internal mechanism between fiscal decentralization and environmental governance. [ABSTRACT FROM AUTHOR]

Although our knowledge of national carbon emission trading system and green certificate trading system are powerful incentive instruments that can deliver on increasingly ambitious climate targets in China, there remains an uncertainty of systems' structural reforms. This study builds on and extends a well-established dynamic computable general equilibrium (CGE) model to incorporate carbon trading system and green certificate trading system into the modeling framework, simulating a diverse of system development pathways further allows an exploration of the many possible policy effect. Then, using total factor productivity as a comprehensive indicator to asses policy effectiveness, the evolutionary trend of comprehensive effects under different paths are separately evaluated to discover the reforms' optimal range. Our work offers main results: First, these instruments provide a price signal. The introduction of a carbon allowance auction drive up carbon prices, while the implementation of a green certificate punishment and the expansion of the trading scope promote an increase in green certificate prices. Second, all policy scenarios that help reduce carbon emission intensity and optimize the power supply structure. However, in achieving the net-zero goal, the green certificate policy incurs more economic costs than the carbon trading policy. Indeed, the combination of multiple policy tools alleviates the decline of social welfare levels. Third, synergism design among policy tools: the focus should be on carbon trading policy from 2021 to 2030, green certificate trading policy from 2030 to 2050, and strengthened policy from 2050 to 2060. Reform measures within policies may need to be introduced in a timely manner. This study offers specific insights and tailored policy proposals to support policymakers in balancing environmental goals with economic and social needs in light of the aforementioned findings. Fig. 1. Introduction of the research questions Fig. 2. Framework of this paper. [Display omitted] • Carbon emission trading and green certificate trading policies were introduced into a dynamic CGE model. • The comprehensive performance of different scenarios were measured using total factor productivity index. • The policy effects of different scenarios were explored from 2020 to 2060. • The even more effective reform measures were adopt, within a single policy. • A sensible mix were proposed, within different policies. [ABSTRACT FROM AUTHOR]

Environmental problems associated with the inappropriate use of fertilizers by rural smallholders are a growing concern in many countries. This paper contributes to the literature by examining whether risk preferences, time preferences, and personality traits are related to farmers' use of synthetic and organic fertilizers. We rely on survey data collected from 815 farm households in three rice-producing provinces in eastern China in the empirical analyses. Results of OLS and rare events logistic regressions indicate that risk-seeking and patience are positively associated with the application of organic fertilizer in rice production but not with the intensity of synthetic fertilizer use. There is also no significant association between personality traits and (synthetic or organic) fertilizer use. In addition, personality traits do not mediate nor moderate the associations between economic preferences and fertilizer use. Robustness analysis using the two-stage probit least squares (2SPLS) model not only supports these findings, but also suggests that organic fertilizers complement the use of synthetic fertilizers and are only sporadically used in Chinese rice production. The insights gained in this study can provide important inputs for designing policies aimed at promoting sustainable agricultural intensification in China and elsewhere. • Risk-seeking and patience are positively associated with the use of organic fertilizer. • Risk-seeking and patience do not significantly affect synthetic fertilizer use. • Personality traits do not directly or indirectly affect fertilizer-use decisions. • Organic fertilizers complement the use of synthetic fertilizers in Chinese rice production. [ABSTRACT FROM AUTHOR]

The crime of endangering rare and endangered wild animals has gradually become frequent crimes in China, but the legal cognitive error in such cases has not been resolved. In this crime, the scope of the objects, wild animals, depends on prepositive laws such as "the List of Wild Animals under the State Key Protection Plan", which leads to the separation between the social meaning of "rare and endangered" and the legal meaning of "under the State Key Protection Plan". Since the structure of basic facts and normative values has been broken, the perpetrator's understanding of the precondition laws should be regarded as pure legal cognition. Considering the specific cognitive difficulty of administrative laws, the level of this mens rea should be raised to clear awareness. This paper examines judicial and prosecutorial cases in China from 2021 to 2022, aimed at determining whether the lack of illegal perception can serve as a defence and what type of evidence is required to prove it. The empirical findings indicate that the clarity of legal cognition differs significantly between cases of guilt and innocence, and that the most crucial proof relies on the perpetrator's comprehension of the scope of protected wildlife, which is a purely legal matter instead of a social one. [ABSTRACT FROM AUTHOR]

With digital technological change and the increasing frequency of interregional innovation links, the spatial correlation and diversity of strategic emerging industries' green innovation efficiency (SEI-GIE) need to be explored in depth. This paper innovatively constructs the SEI-GIE input-output index system under digital economy. The proposed grey model FINGBM(1,1) with ω -order accumulation and weighted initial value optimization realizes effective prediction of 7 input-output indicators of 30 provinces in China from 2021 to 2025. Super-SBM-DEA, gravity model, and social network analysis are applied to explore spatial network structure's dynamic process of SEI-GIE from 12th to 14th Five-Year-Plan period (2011–2025). Empirical results show that (1) Under the effect of digital economy, the SEI-GIE in China generally shows a U-shaped fluctuation trend, in which the growth trend in the central region is obvious, and the western region shows significant fluctuations. (2) The spatial correlation network of SEI-GIE presents a complex and stable center-periphery circle. Particularly, the overall increase in network efficiency highlights the strong small-world characteristics. (3) Beijing, Shanghai, Zhejiang and Jiangsu have always been in the leading core position, with strong influence and control; And Tianjin's core position in the network will decline. Additionally, Guangxi and Chongqing have great potential, but Guangdong needs to strengthen its radiation effect. (4) Block model shows that plate-I (Beijing, Tianjin) receive spatial spillovers from others, while plates-III,IV have significant spillover effects. This study provides theoretical reference for policymakers from a network perspective to promote development of China's SEI-GIE. • SEI-GIE input-output index under digital economy is innovatively constructed. • Indicators of China's 30 provinces are effective predicted by novel FINGBM(1,1). • Spatial correlation network dynamic process of SEI-GIE is explored from 2011 to 2025. • Complex center-periphery circles are presented in spatial network of SEI-GIE. • Theoretical reference for policymakers from a network perspective is provided. [ABSTRACT FROM AUTHOR]

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

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

Livestock is one of major sources of greenhouse gas (GHG) emissions in China. Clarifying spatiotemporal characteristics of GHG emissions from livestock and exploring influencing factors can provide reference for grasping regional changes of GHG emission and formulate strategies of carbon reduction for livestock industry. However, existing literatures considered both spatial and temporal impacts and dynamic evolution trend of these factors seldomly. This paper used the life cycle assessment (LCA) method to estimate GHG emissions of livestock in 114 cities of the YRB from 2000 to 2021. On this basis, spatiotemporal heterogeneity of influencing factors was analyzed by using geographically and temporally weighted regression (GTWR) model. Finally, future evolution trend of GHG emissions from livestock was predicted by combining traditional and spatial Markov chain. Four main results were listed as follows. Firstly, GHG emission in the life cycle of livestock industry increased from 57.202 million tons (Mt) carbon dioxide equivalent (CO 2 e) in 2000 to 77.568 Mt CO 2 e in 2021. Secondly, structure of livestock industry, labor flow and mechanization were vital factors that led to increase of GHG emissions from livestock. Positive effects of labor flow and mechanization were increasing year by year, while negative effect of urbanization and positive effect of economic development were decreasing year by year. Markov chain analysis shown that probability of keeping high level of GHG emissions of livestock in the YRB unchanged were 96% (T = 1) and 90% (T = 5), and there also existed a Matthew effect. In addition, probability of level transfer of GHG emission in urban livestock was spatially dependent. Government should formulate strategies for livestock development and optimize low-carbon transformation of energy structure for livestock and poultry husbandry based on local conditions and key driving factors in the future. Meanwhile, boundaries of administrative divisions should be broken to promote reduction of GHG emissions in livestock comprehensively. • GHG emissions from livestock in cities of the YRB continued to rise from 2000 to 2021. • GHG emissions per unit of GDP of livestock shown a downward trend. • Analyzing parameter of factors from spatiotemporal aspect by using GTWR model. • Probability of GHG emission transfer in urban livestock was spatially dependent. [ABSTRACT FROM AUTHOR]

Plastic waste trade has grown considerably in the last decades and has led to severe environmental problems in recipient countries. Being the largest recipient, China has permanently banned the imports of plastic waste since 2018. This paper examines the causal effect of plastic waste imports on air pollution by exploiting China's experience of importing plastic waste and the recent import ban. By combining data on plastic waste imports with PM 2.5 data at the city level for the years 2000–2011, we find that plastic waste imports increased PM 2.5 density significantly in recipient cities. To evaluate the impact of the import ban on air quality, we employ daily data on air pollution between 2015 and 2020. Our difference-in-differences results show that affected cities, relative to other cities, experienced considerable improvement in air quality following the ban. Further analysis reveals that increased incineration of non-recycled waste is the main channel. These findings provide insights into the costs of importing plastic waste and the potential environmental gains from banning such imports in other countries. • We assess the environmental impact of plastic waste trade in the context of China. • Chinese cities that imported more plastic waste experienced an increase in PM2.5 density between 2000 and 2011. • The primary factor contributing to worsened air quality was the increased incineration of non-recycled waste. • China's import ban in 2018 effectively improved air quality. • The findings highlight the importance of designing effective policies to regulate international trade in waste and domestic waste management. [ABSTRACT FROM AUTHOR]

This paper estimates the mortality impacts of ozone pollution in China and the moderating effects of two possible adaptation strategies. Using an instrument variable constructed from ozone concentrations of nearby upwind cities, we find that ozone pollution significantly increases all-cause, cardiovascular, and respiratory mortality. Healthcare service provision significantly decreases the impacts of ozone pollution on all-cause and cardiovascular mortality, but does not moderate the impact on respiratory mortality. The impact of ozone on RES mortality declines after COVID-19. Healthcare service provision also reduces the distributional impact of ozone across the elderly and younger groups. Projection shows that climate change would induce mortality costs of 0.08% of China's GDP through increasing ozone pollution. [ABSTRACT FROM AUTHOR]

Broflanilide is a newly-developed meta-diamide insecticide, proposed for the control of a wide variety of chewing pests on many crops. In view of the proposed use of broflanilide and its environmental fate, it may be exposed to consumers and non-target organisms, which adversely affect human and the environment. In this paper, a rapid, sensitive and valid UPLC-MS/MS method was established for simultaneous analysis of broflanilide and its two major metabolites, DM-8007 and S (PFP-OH)-8007, in cauliflower. Then, the dissipation behaviors and final residues of broflanilide and its two major metabolites in cauliflower from eight sites with different climatic conditions in China were studied via the described analytical method. In addition, the acute toxicity test of 9.5 % suspension concentrate of broflanilide, broflanilide standard, DM-8007 and S (PFP-OH)-8007 were conducted to non-target terrestrial organisms. Risk assessment for human and non-target terrestrial organisms in cauliflower production was evaluated based on the maximum annual application rates and intervals. The results showed that the highest residue of broflanilide detected in cauliflower samples was all lower than the corresponding MRLs (2 mg/kg) in Japan. Chronic food dietary risk estimates for broflanilide do not exceed 50 % for all the Chinese population groups. Moreover, broflanilide is of low acute toxicity to birds and earthworm, while broflanilide and its metabolites is classified as highly toxic to adult honeybees. Acute risks of broflanilide to birds and earthworms were deemed to be acceptable in a realistic worst-case scenario, while its risk to adult honeybees and ladybug was unacceptable. A protection statement for honeybees and ladybug is required to recognize the high toxicity of broflanilide on related product labels. The study will be conducive to provide guidance for the rational application of broflanilide in cauliflower production. [Display omitted] • Chronic food dietary risk does not exceed 50 % for all the Chinese population. • Broflanilide is of low acute toxicity to birds and earthworm. • Broflanilide and its metabolites is highly toxic to adult honeybees. • Acute risk to adult honeybees and ladybug was unacceptable. [ABSTRACT FROM AUTHOR]

We have obtained an attenuated rabies virus CTN181-3. In this paper, we make a comprehensive studies on CTN181-3. CTN181-3 showed no pathogenicity by i. c. or o. i. inoculation in 3-week-old mice, lower pathogenic in 2-week-old mice, and no virulence by o. i. inoculation in 8-week-old golden hamsters. CTN181-3 showed high immunogenicity, which produced high level neutralizing antibodies, 100% sero-conversation and >5.0 IU/ml GMT by one dose i. m. or o. i. vaccination in mice and golden hamsters. Cellular immune response by one dose i. m. or o. i. inoculation was detected. Especially in PEP, reduced dose of vaccination resulted in 50% (one dose) and 100% (2 doses) protections in golden hamsters. Molecular basis of the attenuation indicated that eight substitutions compared to its parental virus strain CTN-1, among them the two substitutions at the G276 (Leu→Val) and L1496 (Met→Trp) were the critical attenuated site. The phenotypic and genotypic characteristics of CTN181-3 were highly stable, no reversion was occurred when the virus was multiple passaged in suckling mice brains, guinea pig submandibular glands or BSR/Vero cell cultures. The gene homology compared to the Chinese rabies isolates showed much higher than rabies vaccine strains used in China, suggesting CTN181-3 is a promising and suitable oral rabies vaccine candidate strain. [ABSTRACT FROM AUTHOR]

This paper examines the effects of extreme temperatures on mortality rates, using random year-to-year variation in temperature based on county-level panel data from China. The analysis finds a robust, U-shaped relationship between temperature and mortality rates, indicating that extremely cold or hot temperatures lead to excess deaths. The heat-related (cold-related) effect is 3.5 times (3.2 times) as large as previous findings that used U.S. data, and it is especially large for the elderly population, mainly due to excess deaths caused by cardiovascular diseases. Applying these results to climate change predictions from Hadley Centre Global Environmental Model shows that by 2061–2080 the annual mortality rate is likely to increase by 14.2% if global greenhouse gas emissions continue to rise throughout the 21st century, the estimated health cost of which is around 0.98 trillion Chinese Yuan per year. The paper also explores households' adaptation behaviors to extreme temperatures. It finds that although urban households adaptively increase energy consumption when they are exposed to cold temperatures and purchase more air conditioners on hot and cold days, rural households are unresponsive to temperature fluctuations. This finding implies that rural people may be more resource constrained and suffer more when extreme temperatures occur. [ABSTRACT FROM AUTHOR]

The suppressor of cytokine signaling (SOCS) family members play crucial roles in regulating immune signal pathways by acting as inhibitors of cytokine receptor signaling. In this study, 10 SOCS genes were identified in soiny mullet (Liza haematocheila), an economically important aquaculture mugilid species in China and other Asian countries. Sequence comparison showed that the sequence identity between mullet SOCSs and their counterparts from other vertebrates ranged from 38.2% to 92.5%. All mullet SOCS genes were constitutively expressed in tissues examined, but their expression patterns were different. Further, following Streptococcus dysgalactiae infection, all mullet SOCS genes exhibited distinct expression patterns in tissues. These results suggest that SOCSs are involved in immune response to bacterial infection and provide the basis for understanding the complex cytokine regulatory network of teleosts. • Ten members of SOCSs family are obtained from soiny mullet. • This paper is the first report on SOCSs of Mugiliformes. • This paper investigates the expression of SOCSs under gram positive bacterial infection. [ABSTRACT FROM AUTHOR]

Abstract Wushu is an outstanding cultural heritage of the Chinese nation and one of the most extensive mass sports in China. As a traditional sports event in China, martial arts are undergoing rapid changes. However, martial arts are a systemic sport with high requirements for speed, explosiveness and coordination. In recent years, with the rapid development of martial arts, competitive competitions have become increasingly fierce. It is easy for athletes to suffer physical damage during the practice of difficult movements. This not only affects the normal exercise and physical health of martial arts enthusiasts, but also affects the improvement of sports level and teaching quality. Therefore, it studies the common parts of martial arts sports injuries. Distribution, looking for its causes, proposing preventive measures, rapid development of image processing technology, digital image has become an indispensable part of multimedia information technology. Digital image is an important carrier for people to obtain information and communicate. Under this background, the research of image quality evaluation has become a hot spot in the field of image processing. The purpose of this paper is to analyze the anatomical characteristics of knee joints of martial arts athletes, the mechanics of injury, the pathophysiological changes after injury, and establish a mathematical model by computer algorithm to accurately perceive the image quality of martial arts sports damage, and finally achieve the use of computer instead of human vision. The system goes to view and recognize images. In this paper, the application value of quantitative CT parameters of martial arts exercise in the evaluation of martial arts injury joints is based on image quality, in order to provide valuable reference for the treatment of martial arts injury selection and prognosis evaluation. [ABSTRACT FROM AUTHOR]

Abstract With the development of the game industry, and the new electronic consumption chain to promote the development of the game industry model continues to strengthen. Therefore, it is more necessary to make good use of good technology to do a good job of games. From the momentum of the development of mobile terminal games in recent years, the game industry has become a new economic growth point in China's economic transformation. With the development of computer and Internet, graphics and image processing technology has entered another unprecedented stage. In recent years, different image processing techniques have been used to process and analyze the game interface. Appropriate image processing methods include image enhancement, image binarization, image edge detection and image feature extraction. In this paper, by changing the mapping function from priority to probability and comparing the single mapping function of the previous algorithm, the mapping function of playback learning with higher probability of the important priority playback unit is found. In the experiment, the intuitive model strategy analysis of the improved algorithm is carried out firstly. Then the choice of CNN network layer structure, cost function analysis, efficiency analysis and game score comparison of each algorithm are carried out. Finally, the test results show that the new algorithm in this paper can make more effective decisions in video games and achieve the goal of winning higher scores and spending less time. [ABSTRACT FROM AUTHOR]

Abstract With the wide application of big data technology and the continuous innovation of the financial industry, the development of Internet finance has become irreversible. The new financial model has improved the efficiency of financial services and formed new ways of payment and transaction. The traditional credit information system has been unable to meet the needs of the development of the financial industry. The research methods adopted in this paper mainly include literature research, case analysis and comparative analysis. The development process, current situation and characteristics of China's personal credit system, as well as the development process and current situation of China's personal credit system under Internet finance are analyzed. It also points out the main problems faced by China's personal credit reporting system under the Internet finance. Then, aiming at the specific problems faced by China's personal credit reporting system under Internet finance, this paper makes case studies of representative market-oriented credit reporting institutions such as Beijing, Tianjin and Hebei, and uses convolutional neural network to analyze the specific practices of these individual credit reporting institutions and achieves results. At the same time, it compares how different credit agencies make up for the shortcomings of personal credit reporting system. Finally, it draws the conclusion of perfecting the personal credit system of our country under the Internet finance, points out the new problems that may be brought by the superposition of various solutions, and puts forward the countermeasures and suggestions of perfecting the personal credit system of our country under the Internet finance. [ABSTRACT FROM AUTHOR]

Abstract Smalt is a ground blue pigment made of potassium glass whose color comes from a small amount of cobalt oxide added during its preparation. It was very frequently used during the 15th to 19th centuries in Europe, but has by contrast been rarely mentioned or studied by Chinese researchers, despite having been identified in recent years on many Chinese antiques. This paper discusses analytical results from a selection of twenty-one samples of smalt, including wall paintings, architectural polychromy, polychrome sculptures, cave murals and textile paintings, each of which has been subject to a combination of polarized light microscopy, Raman spectroscopy and scanning electronic microscopy. This paper discusses the smalt's identification, as well as its historical uses and trade. Highlights • Smalt was used in China mainly in 16th to 18th centuries AD. • European and Chinese sample's have the same cobalt sources. [ABSTRACT FROM AUTHOR]

This paper exploits the information disclosure and dissemination of environmental punishments on housing prices. As environmental quality is hardly ameliorated in the short run, the environmental punishments normally convey bad news of environmental quality rather than good news to housing market. The information disclosure of environmental punishment adds new pollution source information to the public. Employing the micro databases of firm-level environmental punishments and housing resale transactions in Beijing from January 2015 to December 2017, this research reveals that the transaction prices of houses within 0.5 km distance from the environmentally punished firms decrease by 1.84% on average and the overlapping effects of environmental punishments are fortified by multiple environmental punishments. In addition, the negative effects are amplified in the heating seasons and in the national important events. Unfortunately, we find little evidence of environmental punishments in the rental housing market. This paper identifies three mechanisms of environmental punishments on housing prices. The first mechanism is information disclosure, which proves that the impacts of environmental punishments on housing prices magnify if the information of environmental punishments is released to the public and reinforce with environmental information searching. The second mechanism is information dissemination, which corroborates that the negative effects of environmental punishments on housing transaction prices decay with distance and over time. The third mechanism is health concern arising from environmental punishments, which documents that relative to the unmarried young homebuyers, the older homebuyers and homebuyers with children have stronger responses to the environmental punishments. [ABSTRACT FROM AUTHOR]

Ozone (O 3) pollution in the atmosphere is getting worse in many cities. In order to improve the accuracy of O 3 prediction and obtain the spatial distribution of O 3 concentration over a continuous period of time, this paper proposes a VAR-XGBoost model based on Vector autoregression (VAR), Kriging method and XGBoost (Extreme Gradient Boosting). China is used as an example and its spatial distribution of O 3 is simulated. In this paper, the O 3 concentration data of the monitoring sites in China are obtained, and then a spatial prediction method of O 3 mass concentration based on the VAR-XGBoost model is established, and finnally its influencing factors are analyzed. This paper concludes that O 3 features the highest correlation with PM 2.5 and the lowest correlation with SO 2. Among the measurement factors, wind speed and temperature are the most important factors affecting O 3 pollution, which are positively correlated to O 3 pollution. In addition, precipitation is negatively correlated with 8-hour ozone concentration. In this paper, the performance of the VAR-XGBoost model is evaluated based on the ten-fold cross-validation method of sample, site and time, and a comparison with the results of XGBoost, CatBoost (categorical boosting), ExtraTrees, GBDT (gradient boosting decision tree), AdaBoost (adaptive boosting), RF (random forest), Decision tree, and LightGBM (light gradient boosting machine) models is conducted. The result shows that the prediction accuracy of the VAR-XGBoost model is better than other models. The seasonal and annual average R2 reaches 0.94 (spring), 0.93 (summer), 0.92 (autumn), 0.93 (winter), and 0.95 (average from 2016 to 2021). The data show that the applicability of the VAR-XGBoost model in simulating the spatial distribution of O 3 concentrations in China performs well. The spatial distribution of O 3 concentrations in the Chinese region shows an obvious feature of high in the east and low in the west, and the spatial distribution is strongly influenced by topographical factors. The mean concentration is clearly low in winter and high in summer within a season. The results of this study can provide a scientific basis for the prevention and control of regional O 3 pollution in China, and can also provide new ideas for the acquisition of data on the spatial distribution of O 3 concentrations within cities. • VAR model estimate the dynamic relationships of all endogenous variables. • VAR-tree model estimate the spatial and temporal distribution of O 3. • The eight-tree model improve the accuracy of O 3 change prediction. • VAR-XGBoost method solve the problem of spatial heterogeneity of the study object. [ABSTRACT FROM AUTHOR]

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

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

Dexing City is an important mining city in China, abounding in copper ore, lead ore, zinc ore, and other metal resources, and there are two large open-pit mines in its territory, Dexing Copper Mine and Yinshan Mine. The two open-pit mines have been expanding their mining production scale since 2005, with frequent mining activities; and the expansion of the pits and the discharge of solid waste will undoubtedly increase the land use and cause the destruction of vegetation. Therefore, we plan to visualize the change in vegetation cover in Dexing City from 2005 to 2020 and the expansion of the two open-pit mines by calculating changes of the Fractional Vegetation Cover (FVC) in the mining area using remote sensing technology. In this study, we calculated the FVC of Dexing City in 2005, 2010, 2015 and 2020 using data from NASA Landsat Database via ENVI image analysis software, plotted the FVC reclassified maps via ArcGIS, and conducted field investigations in the mining areas of Dexing City. In this way, we can visualize the spatial and temporal changes of vegetation cover in Dexing City from 2005 to 2020, and appreciate the situation of mining expansion and its solid waste discharge in Dexing City. The results of this study showed that the vegetation cover of Dexing City remained stable from 2005 to 2020, as the expansion of mining scale and mine pits was accompanied by active environmental management and land reclamation, setting a positive example for other mining cities. • The change in FVC from 2005 to 2020 was used to visualize the impact of mining expansion in Dexing City, China. • The paper presented Dexing City as an example of a mining city that has achieved "healthy" development. • This paper described the environmental hazards associated with open-pit mining. [ABSTRACT FROM AUTHOR]

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

Intensive anthropogenic activities have led to drastic changes in land use/land cover (LULC) and impacted the carbon storage in high-groundwater coal basins. In this paper, we conduct a case study on the Yanzhou Coalfield in Shandong Province of China. We further classify waterbodies by using the Google Earth Engine (GEE) to better investigate the process of LULC transformation and the forces driving it in four periods from 1985 to 2020 (i.e., 1985–1995, 1995–2005, 2005–2015, and 2015–2020). We modeled the spatiotemporal dynamics of carbon storage by using InVEST based on the transformation in LULC and its drivers, including mining (M), reclamation (R), urbanization and village relocation (U), and ecological restoration (E). The results indicate that carbon storage had depleted by 19.69 % (321099.06 Mg) owing to intensive transformations in LULC. The area of cropland shrank with the expansion of built-up land and waterbodies, and 56.31 % of the study area underwent transitions in land use in the study period. U was the primary driver of carbon loss while E was the leading driver of carbon gain. While the direct impact of M on carbon loss accounted for only 5.23 % of the total, it affected urbanization and led to village relocation. R led to the recovery of cropland and the reclamation of water for aquaculture, which in turn improved the efficiency of land use. However, it contributed only 2.09 % to the total increase in carbon storage. Numerous complicated and intertwined processes (211) drove the changes in carbon storage in the study area. The work here provides valuable information for decision-makers as well as people involved in reclamation and ecological restoration to better understand the link between carbon storage and the forces influencing it. The results can be used to integrate the goals of carbon sequestration into measures for land management. [Display omitted] • The carbon storage impacted by LULC driving processes in high groundwater coal basins was investigated. • 56.31 % of the study area has undergone land use transition during 1985–2020. • The carbon storage decreased by19.69 % during the study years. • Urbanization and village relocation was the primary driver of carbon loss, ecological restoration was the leading driver of carbon gain. [ABSTRACT FROM AUTHOR]

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

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

Water scarcity has threatened the sustainability of human life, ecosystem evolution, and socio-economic development. However, previous studies have often lacked a comprehensive consideration of the impact of water quality and existing solutions, such as inter-basin water transfer and unconventional water resources, on water scarcity. In this paper, an improved approach was proposed to quantify water scarcity levels by comprehensively considering surface water quality and multiple solutions. China's water scarcity was first assessed at a high spatial resolution on a monthly basis over the 5-year period from 2014 to 2018. Then, the driving factors including water quality and solutions were identified by a geographic detector model. Finally, an in-depth investigation was conducted to unravel the effects of water quantity solutions (i.e., inter-basin water transfer and unconventional water use), and water quality solutions (i.e., improving surface water quality) on alleviating water scarcity. Based on monthly assessments considering water quality and multiple existing solutions, the results showed that over half of the national population (∼777 million) faced water scarcity for at least one month of the year. Agricultural water use and inadequate water quality were the main driving factors responsible for China's water scarcity. Over four-fifths of the national population (∼1.10 billion) could benefit from alleviated water scarcity through a combination of water quantity and quality solutions. However, the existing solutions considered were insufficient to completely resolve water scarcity in China, especially in Northern China, persisting as a challenging issue. The results obtained from this study provided a better understanding of China's water scarcity, which could contribute to guiding future efforts aimed at alleviating water scarcity and ensuring water security in China. • Water scarcity assessment incorporated water quality and multiple existing solutions. • China's water scarcity was assessed at a high spatial resolution on a monthly basis. • Over half of the national population faced water scarcity for at least one month of the year. • Agricultural water use and inadequate water quality were the main driving factors. • Over four-fifths of the national population could benefit from alleviated water scarcity by the combined water quantity and quality solutions. [ABSTRACT FROM AUTHOR]

Throughout the literature, the word "heavy metal" (HM) has been utilized to describe soil contamination; in this context, we characterize it as those elements with a density greater than 5 g per cubic centimeter. Contamination is one of the major global health concerns, especially in China. China's rapid urbanization over the past decades has caused widespread urban water, air, and soil degradation. This study provides a complete assessment of the soil contamination caused by heavy metals in China's mining and smelting regions. The study of heavy metals (HMs) includes an examination of their potential adverse impacts, their origins, and strategies for the remediation of soil contaminated by heavy metals. The presence of heavy metals in soil can be linked to both natural and anthropogenic processes. Studies have demonstrated that soils contaminated with heavy metals present potential health risks to individuals. Children are more vulnerable to the effects of heavy metal pollution than adults. The results highlight the significance of heavy metal pollution caused by mining and smelting operations in China. Soil contaminated with heavy metals poses significant health concerns, both carcinogenic and non-carcinogenic, particularly to children and individuals living in heavily polluted mining and smelting areas. Implementing physical, chemical, and biological remediation techniques is the most productive approach for addressing heavy metal-contaminated soil. Among these methods, phytoremediation has emerged as a particularly advantageous option due to its cost-effectiveness and environmentally favorable characteristics. Monitoring heavy metals in soils is of utmost importance to facilitate the implementation of improved management and remediation techniques for contaminated soils. [Display omitted] • This research investigates deeply the sources, distributions, and risks of heavy metal pollution in soil throughout multiple regions of China resulting from smelting. • The categorization and summarization of mechanisms for heavy metal pollution are presented. • This work is the inaugural investigation into ecologically sustainable approaches for the remediation of smelting byproducts. • This paper examines the remediation approaches for controlling soil heavy metal pollution and evaluates their applicability. [ABSTRACT FROM AUTHOR]

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

This paper reports a novel poplar mosaic disease that occurred on the leaves of Populus alba var. pyramidalis in China. Symptoms: mosaic and chlorosis leaves, leaf abscission, leaf and young branch withering, leaf growth retard, and the destroyed and hollowed cell structures of mesophyll cells in the diseased leaves. Electron microscopy observation showed that some typical (flexible rods, virus particles 10–14 nm in width, and ca. 700 nm in length) and atypical virus particles (1400 or 2000 nm in length) of genus Potyvirus were found in the leaf exudates of the diseased poplar. De novo assembly assembled a nearly complete genome sequence of bean common mosaic virus (BCMV, 10035 nt in length) from the transcriptome sequencing data of poplar leaves. Moreover, field observation illustrated that two larvae of white-striped longhorn beetle (Batocera lineolata) inhabited and almost completely destroyed the main branch and roots of the diseased poplar plant, and a high-density population of two Chaitophorus aphid species once infected poplar plants before the occurrence of mosaic symptoms. Results suggested that BCMV is the pathogen of this novel poplar mosaic disease; moreover, results also suggested beetle and aphids that might involve in the occurrence and development of poplar mosaic disease. • This study reported the symptoms and ultra-structral a novel mosaic disease that occurred in Populus alba var. pyramidalis in China. • Near complete genome sequence of BCMV (bean common mosaic virus) and BCMV-like virus particles suggested that BCMV was associated with the occurrence of poplar mosaic disease. [ABSTRACT FROM AUTHOR]

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

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

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

In this paper, we assess the effectiveness of early climate policy in emerging economies by causally evaluating the impact of China's Low-carbon City Pilot (LCCP) on city-level per-capita CO 2 emissions and CO 2 intensity of GDP over the period 2003–2017. The idiosyncrasies of the policy design pose significant challenges for causal identification, which we overcome within a synthetic control framework. Contrary to previous contributions, our results suggest that the LCCP had no significant impact on either carbon emissions or intensity. The main takeaway of our empirical investigation is that even in emerging economies, effective environmental policy requires transparent, quantifiable targets, and credible enforcement. [ABSTRACT FROM AUTHOR]

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

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

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

In recent years, one of the most important and innovative policy initiatives introduced by the Chinese government in the field of environmental protection and ecological civilization construction is the Central Environmental Protection Inspection (CEPI). CEPI is seen as a vital tool to encourage local implementation of environmental protection responsibility. Over the course of its operation (eight years), CEPI has transformed from the "campaign" phase to the "convention" phase. It is noted that while provincial governments face a common high-pressure environment created by CEPI, governance scenarios, behaviors, and performance vary across the country significantly. To better understand local governments' environmental governance behaviors under the transformation of CEPI, an integrated analysis framework consisting of two key elements, "central dominance" and "local proactiveness", is constructed based on the central-local interactions under the principal-agent model. Based on this framework, we conducted a multi-case comparative analysis of four classic cases, with the following findings. (1) Along with the operation of CEPI and its transformation, the interaction between the central and local governments leads to four governance scenarios: "control-active cooperation", "control-passive cooperation", "guidance-active promotion", and "guidance-passive promotion". (2) Influenced by various factors such as pressure by the central government, local governments' capabilities and governance motivations, local governments form governance behaviors with varying degrees of proactiveness and autonomy. (3) After examining the governance performance of varying behaviors, it is found that local government's "active promotion" behavior can achieve higher governance effectiveness in the "convention" phase. Therefore, it is of policy implication that local governments should be guided to transit from "passive cooperation" to "active promotion". This paper has important guiding significance for understanding local environmental governance behaviors under strong top-down institutional pressure. • CEPI is one of the most important policy initiatives introduced by the Chinese gocernment in eco-environmental protection. • The interaction between the central and local governments leads to four different governance scenarios. • Governance scenarios,behaviors and performance of local goverments vary acorss the country significantly under CEPI. • Local government's "active promotion" behavior can achieve higher governance effectiveness in the "convention" phase. [ABSTRACT FROM AUTHOR]

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

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

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

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

In this paper, the Cu and Ni accumulation and contamination levels in agricultural soils and wheat around a smelter in Jinchang City in northwest China were investigated with a combination of field investigations and indoor analytical tests, using a soil–wheat system as the study area. The average Cu and Ni contents in the soil were 119.50 mg kg–1 and 123.40 mg kg–1, respectively, both of which exceeded the local soil background values. The Cu and Ni contents in 46.15% o and 26.92% of sampling sites, respectively, exceeded the screening values for soil contamination risk in agricultural land in China. The average Cu content in different parts of wheat was in the order of roots (24.22 mg kg–1) > leaves (20.11 mg kg–1) > husks (5.51 mg kg–1) > grains (4.05 mg kg–1) > stalks (3.74 mg kg–1). Furthermore, the average Ni content ranked as leaves (24.64 mg kg–1) > roots (21.12 mg kg–1) > husks (6.95 mg kg–1) > stalks (1.75 mg kg–1) > grains (0.38 mg kg–1). The health risk evaluation showed that with average hazard index values of 0.88 for adults and 1.04 for children for Cu and Ni in wheat grain, wheat in this region is unlikely to pose a health risk to adults but may pose a lesser health risk to children. The Ni bio–concentration and translocation factors in the husk and leaves of wheat were greater than those of Cu and smaller than those of Cu in the other parts of wheat. The results of this study provide basic data for the remediation of heavy metal contamination in local agricultural soils. • The soil and wheat around smelters and mining areas are polluted. • Wind power and direction can affect the distribution of heavy metals. • Wheat grains can cause minor health effects for children. • Compared with Ni, Cu is more easily accumulated and transported in wheat. [ABSTRACT FROM AUTHOR]

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

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