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Energy and water are interdependent. Water is essential for energy production, and energy is indispensable for water processes. This paper develops a Stackelberg game based bi-level multi-objective model for optimal water allocation under uncertainties from an energy-water nexus perspective, which considers energy-related water consumption and water-related energy production. It handles the hierarchical decision-making problem between the river basin authority and the subareas, as well as the tradeoffs between social equality and ecological damage. The upper level of the model makes schemes on water allocation for multiple subareas, and the lower level decides on water allocation for different types of power generation. To generate reasonable and practical strategies for water allocation, ɛ -constraint method and KKT conditions are used. A case study of Minjiang River, China is given to demonstrate the applicability and practicality. Scenarios analysis is also conducted to demonstrate the effectiveness of the model and the effects of the control parameter changes. The results indicate that the river basin authority would allocate larger water resources to the subareas with higher energy demand. It is concluded that the proposed allocation method is advantageous to the subareas with higher water utilization efficiency. The proposed bi-level model demonstrates its reasonableness and superiority to the single-level model. Policy implications are finally provided to support the sustainable development of energy-water nexus. • A bi-level model for water allocation in energy-water nexus system is proposed. • The hierarchical decision sequence between the river basin and subareas is solved. • The tradeoffs between social equality and ecological damage are made. • Optimal water allocation for multiple subareas and energy resources are quantified. • Uncertainties in decision-making environment are handled by fuzzy set theory. [ABSTRACT FROM AUTHOR]

The battery electric vehicle (BEV) industry, commanding over half of the global market share in China, has garnered significant attention in response to escalating concerns about climate change. NCM (LiNi x Co y Mn z O 2) batteries, prized for their high energy density, are pivotal in this industry. However, their production relies on critical metals, posing environmental challenges. Recycling processes aim to address this issue by recovering critical metals from end-of-life batteries. The industry is updating from NCM 111 to NCM 811 batteries to enhance energy density and reduce costs, but the key factors influencing the material flows and environmental impacts remain uncertain. This paper aims to identify the key factors contributing to the potential differences in material flows and environmental impacts introduced by the NCM battery upgrading in China. Following the new energy vehicle sales projections in China until 2035, a dynamic material flow analysis was employed to calculate material demands, recovered amounts, and substitution rates for various upgrading scenarios. The study reveals that the majority of retired batteries until 2035 were sold between 2022 and 2029. Material substitution rates prove to be more sensitive to the upgrading scenario than the lifetime and growth rate of BEVs. Faster NCM 811 penetration results in over 2.5 times more saved cobalt demand compared to additional nickel demand. A life cycle assessment of NCM batteries reveals a 39% lower global warming impact for NCM 811 compared to NCM 111, highlighting environmental benefits from increased energy density and reduced cobalt consumption. The energy density improvement contributed 85%, while the alteration in material composition contributed 15% to the global warming reduction in NCM 811. Recycling emerges as a crucial strategy in mitigating environmental impacts across all categories, particularly addressing eutrophication, previously deemed challenging due to the difficulty in recovering Li 2 CO 3. [ABSTRACT FROM AUTHOR]

Addressing the urgent need for accurate carbon emissions forecasting to support global emissions reduction goals, this paper introduces a novel approach for carbon emissions prediction that dynamically considers the spatial–temporal correlation of carbon emissions across forecasting targets. Traditional statistical and machine learning models have limitations, such as oversimplification and inefficiency in capturing evolving dynamics among multiple forecasting targets, alongside a focus on longer forecasting horizons like monthly or yearly. To tackle these, we propose an innovative Dynamic Spatial–Temporal Graph Convolutional Recurrent Network (DSTGCRN), a blend of graph convolutional and recurrent neural network structures customized for up-to-date multi-regional spatial–temporal predictions at a daily level. Comprehensive empirical analyses on datasets from China, the US, and the EU confirm DSTGCRN's superior performance and robustness across diverse geographical contexts. It outperforms the second-best among 10 baseline models, achieving 40.6%, 24.6%, and 38.5% improvements in MAE, RMSE, and MAPE, respectively, across various horizons. The incorporation of environmental data, including temperature and Air Quality Index, as supplementary predictors in the DSTGCRN model, has demonstrated its efficacy in the context of the China dataset. The DSTGCRN model's improved accuracy and daily multi-regional forecasting deepen emission dynamics understanding, supporting the development of informed and region-specific environmental policies that can respond promptly to changes. [ABSTRACT FROM AUTHOR]

This study delves into the nexus between the efficiency of carbon emission allocation and the efficiency of green development within the context of innovative city construction. Leveraging data from 283 prefecture-level cities and corresponding provincial-level panel data spanning the period from 2005 to 2019 in mainland China, the research employs the zero-sum gain DEA model to compute provincial carbon emission allocation efficiency and allocate allowances. Furthermore, it utilizes the all-factor non-radial directional distance function and the SBM-DEA model to gauge the green development efficiency of prefecture-level cities. The double-difference method is applied to evaluate the impact of innovative city construction on regional green development efficiency. The results indicate that an imbalance between carbon emission allocation efficiency and emission quotas detrimentally affects urban green development. However, technological progress, factor accumulation, and the institutional environment associated with innovative city building mitigate this negative impact. Heterogeneity analysis reveals a differentiated effect of innovative city building on regional green development efficiency. This paper not only explores the concept of achieving an equitable distribution of carbon emission allowances but also examines how innovative city building influences regional green development. By establishing connections between urban policies, the equitable distribution of carbon emission allowances, and regional green development, it introduces a new perspective for promoting high-quality development at the regional level. [ABSTRACT FROM AUTHOR]

Given the phase-out of subsidies, the Chinese government has issued a series of non-subsidized industrial policies to support the development of the power Lithium-ion Battery (PLiB) industry, recognized as pivotal for achieving carbon neutrality in the transportation department. However, existing literature provides limited evidence on the contribution of non-subsidized industrial policies, particularly to the PLiB industry. To bridge this gap, using data of 31 PLiB listed firms and 279 relevant non-subsidized industrial policies, this paper analyzes the effects of non-subsidized industrial policies on the global value chain (GVC) embedding position. The results reveal that non-subsidized industrial policies significantly raise the GVC embedding position of Chinese PLiB firms, and the positive effects are prone to increase over the research period. Further investigation shows that there is heterogeneity among PLiB firms, with the raising effects on the GVC embedding position being more significant in eastern and middle PLiB firms, private PLiB firms and midstream PLiB firms. The mechanism verification shows that non-subsidized industrial policies raise GVC embedding position of PLiB firms through technological innovation effect and scale economy effect, while competitiveness effect does not give full play. These findings provide important recommendations for better design of the industrial policies to improve the international competitiveness of PLiB industry and other strategic emerging industries. • This study investigates the effects of industrial policy from the perspective of non-subsidized industrial policies. • Non-subsidized industrial policies raise global value chain embedding position of China's Power Lithium-ion Battery firms. • Mechanisms of technological innovation effect, scale economy effect and competition effect are verified. [ABSTRACT FROM AUTHOR]

Different from developed markets, China capital market is dominated by retail investors. In the digital age, retail investors are increasingly making their voice heard through online channels, which is a new form of shareholder activism in China. This paper examines the association between retail investor activism (RIA) and corporate greenwashing behavior (CGB) using the data of question raised by investors on official investor interactive platforms (IIPs) in China. We discover that the RIA on IIPs is negatively associated with CGB. The mechanism analysis shows that the RIA helps to curb CGB through promoting information transparency and improving internal corporate governance level. We also find that the association between RIA and CGB is strengthened in regions with weaker green finance and environmental regulation, and in industries with weaker product market competition. This indicates that the RIA, a type of private governance, can serve as a substitute to the governance effect of the government and the product market. Further studies show that RIA on unofficial channels such as stock forums or search engines can promote CGB, contrary to the conclusion about IIPs. Our research suggests that strengthening the rights of retail investors through official channels helps to reduce CGB and demonstrates the importance of official channels in the governance role of RIA in emerging markets. [ABSTRACT FROM AUTHOR]

The factors that influence residents' willingness to accept long-term compensation are largely ignored, which leads to coal-to-electricity compensation failures. The core of Internet use is a viable solution to the inefficient coal-to-electricity transition for clean energy. This study employs the Heckman two-stage model to show that the compensation standard for coal-to-electricity transition should range from 25.61 to 174.07 yuan per person. Internet use has significantly promoted the compensation amount for the coal-to-electricity transition among residents. The conclusion is consistent with the theory of "information transmission", indicating that netizens are particularly concerned about the positive information that interferes with the clean energy subsidy standards. The propensity score match method and replacement variables ensure the stability of the research conclusion. Secondly, a subdivision of the sample has shown a significant positive impact of internet use on women in rural areas with lower education levels in northern China. The paper also found that the increase in the importance of different Internet use promotes the amount of compensation for residents' coal-to-electricity transition. The driving mechanisms behind the increase include the learning effect, transaction cost effect and marketization effect, and the family life cycle was found to exhibit an inverted "U" regulation function in the relationship. Therefore, this study provides new policies for the determinants of compensation standards for the coal-to-electricity transition with Internet use. [ABSTRACT FROM AUTHOR]

The implementation of new-type infrastructure plays a crucial role in driving low-carbon economic development in China and worldwide. This work employs fixed-effects model, mediated-effects model, spatial Durbin model, and meta-analysis to thoroughly examine the influence of new-type infrastructure on total factor carbon productivity using panel data of 274 Chinese cities spanning from 2011 to 2021. The findings indicate that: firstly, new-type infrastructure has a notable and beneficial impact on total factor carbon productivity, but there is heterogeneity in resource endowment, city scale, and policy intensity. New-type infrastructure can only promote total factor carbon productivity enhancement in non-resource cities and large cities. Under the influence of smart city policies, new-type infrastructure has a stronger effect on total factor carbon productivity enhancement. Secondly, digital finance and marketization are important ways for new-type infrastructure to improve total factor carbon productivity. Thirdly, via spatial spillover effect, new-type infrastructure may boost total factor carbon productivity not only in the local region but also in places that are spatially connected. Accordingly, this paper offers policy recommendations for the government to encourage the investment and development of new-type infrastructure to support total factor carbon productivity growth. • Increasing total factor carbon productivity can achieve a balance between "carbon reduction" and "economic growth". • In the digital age, the construction of new-type infrastructure is crucial. • Quantitative indicators at the city level can provide a more detailed study of issues. • There are direct, indirect and spatial effects of new-type infrastructure on total factor carbon productivity. [ABSTRACT FROM AUTHOR]

The application of a photovoltaic (PV) system for zero energy buildings is crucial to balance energy consumption. This paper investigated the potential of PV systems for buildings in different climate zones of China. The tilt angle, orientation, plot ratio, PV conversion efficiency and location were selected to study their influences on electricity production. The performance of the PV system was analyzed based on a residential building, and employed RETScreen in combination with TRNSYS. The results indicate that southwest China is the best place to develop zero energy buildings. Low-rise residential buildings can realize zero energy in China when the PV conversion efficiency is higher than 20%. However, an energy balance only occurs in the southwest when the PV conversion efficiency is 10%. For different building heights, with a high conversion efficiency (20%), the energy consumptions rates are less than 15 kW h/m2a all over China. In the southeast, the effect of the building shape on energy generation can be ignored due to the high solar elevation angle in the summer. Although the optimal tilt angle varies for different cities, the energy deviations are less than 10% when tilt angle is within 10° of the optimal angle. This study proposed a formula to evaluate the potential of a building PV system. The maximum difference between the simulated and calculated results is approximately 10%, which is reasonable and acceptable. This paper provides some references for the application of PV systems in zero energy buildings. [ABSTRACT FROM AUTHOR]

Air pollution presents a serious public health risk globally, particularly in fast industrializing countries such as China. Effectiveness of local air pollution control measures is influenced by external forces such as atmospheric emission transport and interprovincial trade. However, there is lack of research on comparison of these two indicators and local indicators (e.g. per capita income and emissions) determines the responsibility allocation in pollution control. In this paper, cross-provincial air pollution is stimulated via atmospheric transport (atmospheric linkage indicator) based on Weather Research and Forecasting/Comprehensive Air Quality Model with Extensions (WRF/CAMx) model. The air pollutants embodied in interprovincial trade (trade linkage indicator) was studied by using the latest multi-regional input-output (MRIO) model. This study revealed the significant influence of atmospheric transport on neighboring provinces. However, transport of trade-induced embodied emissions affects both neighboring areas and larger areas. According to aggregation analysis of these two indicators, in most provinces of China, direction of atmospheric transport contradicts to that of the trade-induced transport. These findings are used to analyze the rationality of regional differences in environmental tax rate in the new environmental protection tax law of China. By comparing the local and interregional linkage indicators, we found the current environment tax for air pollutants was mainly affected by per capita income whereas other environment and linkage indicators show little correlation. Therefore, we integrated environment and linkage indicators to propose adjusted provincial environment tax rates plan for air pollutants as a cost sharing mechanism. The results of this paper provide novel perspective for central government to adjust fairness environmental responsibility between provinces of China by tax policy. Image 1 • Cross-provincial air pollution via atmospheric transport was simulated by WRF/CAMx. • Interprovincial air pollution embodied in trade was traced using MRIO model. • The influence range via trade is greater than that of atmospheric transport. • The environmental tax rate is advised to be adjusted base on linkage indicators. [ABSTRACT FROM AUTHOR]

The life cycle includes the "planning stage – construction stage – operation stage" of a project. For soft soil subgrade, life-cycle quality management refers to the construction stage and operation stage. The health of soft soil subgrade in the operation stage cannot be separated from the influence of other factors, such as maintenance technology, operation management and construction technology. Only relying on the monitoring data of the construction stage cannot satisfy the requirements of comprehensive evaluation of soft soil subgrade. Currently, there is no perfect information management system to store, process and analyse all the index data from construction stage to the operation stage. This paper puts forward indexes that are suitable for evaluating the health of soft soil subgrade. Among all these indexes, we selected 8 indexes to evaluate the construction stage subgrade health, and chose 13 indexes to evaluate the operation stage subgrade health. In this paper, the Analytic Hierarchy Process was employed to structure the judgment matrix of each level indexes and calculate the weight of each index. In this way, we established soft soil subgrade life-cycle health assessment system. We found that construction stage and operation stage contribution the weight of 30% and 70% to the health of expressways soft soil subgrade lifecycle. Respectively, for construction stage subgrade health, the greatest influence come from apparent indexes and weight reached 0.75. For operating stage subgrade health, the greatest influence come from internal indexes and weight reached 0.5813. The assessment system was used to evaluate and analyse the health condition of an expressway section with soft soil subgrade. It is found that slope problem is the main problem that affects the health of the soft soil subgrade in this section. Based on the situation, suggestions for improving the health of the subgrade and key points being noted in future operation are given. [ABSTRACT FROM AUTHOR]

The achievement of the environmental sustainable development goals (SDGs) mainly lies with national governments, who play a crucial role in internalising environmental externalities within their countries. As a supplement to governmental intervention, corporate environmental responsibility (CER) practice will help correct environmental externalities and, thus, contribute to the implementation of national environmental plans. Therefore, a framework is needed that shows the drivers for a firm to pursue CER practice, while also demonstrating the organisational journey a firm needs to take towards environmental sustainability. However, most existing CER frameworks are based on free market mechanisms; therefore, they are not fully applicable in mixed economies due to the different institutional contexts. This paper contributes to the CER literature by providing a general framework for CER research applicable to both free-market and mixed economies, using multiple lenses that incorporate institutional theory, stakeholder theory, legitimacy theory and environmental externality theory. Based on a Chinese and English literature review of CER issues in China, this paper incorporates the findings of Chinese indigenous research and provides an extended framework for the Chinese context. Thus, the extended framework adds to the Chinese CER literature by synthesising influential factors on CER practice and performance, which in turn provides a conceptual model for policy makers to promote national environmental champions at a micro level, for example, the implementation of China's SDG 2030 Agenda. In addition, the construction of the Chinese CER framework illustrates how the general framework can be modified for a mixed economy where the institutional supports for CER are significantly different from those in a free market economy. • A general CER framework for both free-market and mixed economies. • Drivers for Chinese CER practices identified from Chinese and English literature. • An extended framework for Chinese CER practice. • Frameworks incorporating multiple theoretical perspectives. [ABSTRACT FROM AUTHOR]

With the rapid development of China's industrialization, the extensive development of industrial models has led to increasing environmental pressure. In this paper, we use China as an example, combined with the Tapio elastic analysis method (Tapio model), modified gravity model, social network analysis (SNA), quadratic assignment procedure (QAP) regression and logit model, to explore a network effect on the decoupling of industrial waste gas emissions and industrial added value (industrial GDP). We use the special network structure of industrial waste gas emissions and industrial GDP to capture the network effect. The results show the following: (1) For industrial sulfur dioxide (SO 2), nitrogen oxide (NO x) and soot (dust) (SD), most provinces in China show obvious strong decoupling, and provinces with faster economic growth, such as the eastern coastal areas, have a larger proportion of strong decoupling than provinces with poor economic development. (2) According to the network analysis of the industrial GDP, SO 2 , NO x and SD, economically developed provinces such as Shanghai, Jiangsu, Zhejiang, Beijing and Guangdong are generally located at the core of the network and have a strong spatial spillover effect on other provinces; (3) The QAP regression results show that the spillover effects of industrial SO 2 , NO x and SD are largely influenced by industry structural similarities, geographic proximity, and the development of economy. (4) The logit regression results show that the decoupling of industrial waste gas emissions will be greatly affected by the spatial network structure of industrial waste gas emissions and industrial GDP. The provinces at the core of the network are more likely to undergo strong decoupling. Finally, based on the research results, this paper provides some recommendations. • A network effect on decoupling of industrial emissions and industrial added value. • The modified gravity model is used to build the network. • Provinces with faster economic development are more prone to pollution decoupling. • Provinces at the core of the network are more prone to pollution decoupling. [ABSTRACT FROM AUTHOR]

The dramatic increase in textile waste and the ineffective disposal of textiles as emerging global issues are driving researchers to study new ways of thinking and designing textile waste policies with the aim of conserving resources and reducing the environmental impact of textile waste. However, there is limited research that systematically and comprehensively examines the development processes of policies that govern textile waste management. It is important to identify the underlying issues and improve textile waste management systems. This paper fills this gap by presenting a comprehensive study of the development and characteristics of policies related to textile waste in China. All the major textile waste policies issued between 1991 and 2017 at the central-government level have been examined to ensure accuracy and reliability. To achieve the descriptive objective of the study, content analysis was employed, and the following conclusions were derived: (1) The number of policies has gradually increased since more stringent textile waste management was introduced in 2001, and although the Chinese government has continuously reinforced its supervision from 2010 onwards, stringency remains low; (2) most policies regulate the recycling level of the waste hierarchy, as in open-loop recycling, and only a couple of polices regulate higher levels; and (3) the highly imbalanced structure of policy instrument types has been changing, and the variety of policy instruments has peaked in recent years. This paper contributes a general and important reference relating to textile waste policies for governments and businesses in other industrialized nations. [ABSTRACT FROM AUTHOR]

Global warming has aroused the attention all over the world, because not only can it directly damage the living environment, but it can also impact on the social and economic development, of a region in an obvious and far-reaching way. In this paper, we builded a trans-log production function model incorporating variables, such as rainfall, labor force, technology and temperature to simulate how climate changes impacted on the regional economics. Time series data of the domestic economy of Nanjing, a city in the southeast China, between 1996 and 2017, were used to verify the production theory of trans-log production frontier. The results showed that: with the rainfall increased and the temperature declined, the climate impact on the economy and the absolute value of the output elasticity of the frontier diminished. In addtion, the climate change was also positively related to the capital investment. The larger variation of temperature negatively impacted on the economic development. • This paper builds a trans-log production function model. • Time series data are used to verify the production theory of trans-log production frontiers. • Analyzing the effect of climate change on the regional economy. • The larger variation of temperature negatively impacted on the economic development. [ABSTRACT FROM AUTHOR]

It is found that in order to ensure the polishing slurry involved in polishing process is sufficient, the supply of polishing slurry has to be excessive in conventional polishing process. However, actually only a limited amount of polishing slurry is involved in polishing process compared with the supplied polishing slurry, and the overwhelming majority is directly discharged which increases waste emissions. On the other hand, the issue of industrial waste is increasingly attracting scientific and public attention due to the magnitude of the problem in China, and various types of polishing slurries will cause serious pollution to rivers and soils. This paper focuses on a novel and successful polishing slurry waste reduction method which realizes waste reduction on the premise of ensuring the polishing performance. The proposed method is based on ultrasonic atomization, which can make the polishing slurry with low supply rate form a soft and low velocity fine mist spray and realize the even distribution of abrasive particles in slurry, and is called ultrasonic atomization polishing. In order to prove the feasibility of this waste reduction method, this paper has proved that (i) the introduction of ultrasonic atomization contributes the improvement of surface quality and polishing efficiency and (ii) ultrasonic atomization polishing can greatly realize polishing slurry waste reduction, moreover, multi-objective optimization scheme of polishing parameters for ultrasonic atomization polishing is obtained, which are all of great significance to guide the waste reduction in actual production. [ABSTRACT FROM AUTHOR]

Based on China's provincial panel data from 2001 to 2015, the drivers of energy technological innovation, e.g., energy price, public financial policy, knowledge stocks, energy structure, and environmental regulation, are analyzed by using the generalized method of moment (GMM) in this paper. Through the construction of one kind of geometric distribution lag model, which is also called partial adjustment model, we empirically analyze and compare the influencing factors of energy technological innovation from the perspectives of fossil energy and renewable energy. The specific conclusions obtained in this paper are: (1) The impact of the energy price on fossil energy technological innovation is greater than renewable energy, which means that the current energy price in China is much lower than its optimal level and the development of renewable energy technology needs the support of price mechanism. (2) The development of these two kinds of energy technology innovation heavily relies on governmental policy support. (3) The accumulation of energy technology innovations will be conducive to the vertical spillover effect of knowledge, and further encourage the development of energy technology. Based on the above findings, we then propose some relevant policy proposals to promote energy technological innovation in China. [ABSTRACT FROM AUTHOR]

Based on the panel data of 30 provinces in China from 2006 to 2016, the Gaussian kernel density estimation was initially used to describe the characteristics of the inter-provincial differences in household energy consumption (HEC), a dynamic panel data model was established secondly to study the main factors affecting HEC, and finally the counterfactual decomposition method was used to calculate the contribution of each factor to the inter-provincial differences in HEC. The research results are shown as follows: First, the inter-provincial HEC in China shows a phenomenon of agglomeration and growth, and the HEC level of different regions presents difference and imbalance. Second, the logarithms of consumption habits, total population and residents' income have significant effects on the logarithm of HEC, the influence coefficients are 0.191, 0.073 and 0.745, respectively; HEC not only has significant inertia characteristics, but also has certain population size effect and wealth effect. Third, the logarithms of technological progress, urbanization and household energy price have significant effects on the logarithm of HEC, the influence coefficients are 0.864, 0.195 and −0.346, respectively; the HEC saved by technological transformation is not sufficient to offset the increase in HEC demand, urbanization can improve HEC significantly, but the household energy price significantly inhibits HEC. Finally, from the perspective of contribution, the total population, residents' income and urbanization contribute a lot to the inter-provincial differences, totaling 73.02%. The possible innovations of this paper are as follows: First, the contribution of the influencing factors to the difference of inter-provincial HEC is studied, which is rarely seen in the previous literature. Second, compared with traditional decomposition method, counterfactual decomposition method is more convenient for economic interpretation. Third, the divergent conclusions of scholars are pointed out in this paper, and the actual impact of influencing factors on HEC are clarified. Image 10086681 • The level of inter-provincial HEC shows difference and imbalance. • HEC has significant inertia characteristics, population size effect and wealth effect. • HEC saved by technology is not sufficient to offset the increase in HEC demand. • Total population, residents' income and urbanization contribute 73.02%. • The statistical analysis tool used in this paper is Stata15. [ABSTRACT FROM AUTHOR]

The expansion of resource tax to the occupation of natural ecological space is an important part of China's tax reform. This paper quantifies the occupation of natural ecological space based on the demand for energy, water, and agriculture resources in terms of an ecological footprint, and creatively convert the carbon emissions from energy consumption to occupation of carbon sinks such as woodlands and grasslands, to obtain the ecological deficits in various regions of China. Based on the evaluation of the ecological service value, the paper determines the correspondence between consumption projects, land types and ecological functions, realized the accounting of the economic value of the national ecological deficit as the sum of the regional deficits. Based on this, the ecological deficit is used as an unpaid input factor in the construction of a green Social Accounting Matrix table, and a recursive dynamic Computable General Equilibrium model is used to analyze the effects of a tax policy on the compensation for the ecological deficit value. The simulation results show that the double-dividend hypothesis exists in the primary and tertiary industries, and employment in the secondary industry that with a high value-added labor decreased, resulting in decreases in both the labor income of residents and their proportion of the national income. The growth rate of GDP decreases in the short term and then gradually increases. Capital appreciation and net exports contribute greatly to economic growth. Based on the positive role of taxation schemes in reducing ecological deficits and their negative impacts on economic growth and the income distribution, this paper suggests that, with the improvement of big data on ecological occupation, an ecological deficit tax can be introduced to target the energy sector, which has a large ecological footprint. In addition, household income should be protected through tax cuts, transfer payments, and earmarked funds, among other means, to promote economic growth and protect the environment. • Ecological deficit tax can control ecological space occupation and realize ecological value compensation. • The double dividend hypothesis is not universal in every industry. • Environmental tax has short-term impact on economic growth and regressive effect on income distribution. • Capital appreciation and net exports growth contribute greatly to economic growth in the long run. • Labor returns and tax revenue recycling affect the effectiveness of tax programs. [ABSTRACT FROM AUTHOR]

Environmental information disclosure has been widely used as an approach of pollution reduction. But its impact on firms' competitiveness is not adequately studied in the literature. To fill this gap, this paper empirically investigates how China's first national environmental information disclosure program affects the profitability of a panel of Chinese industrial firms using China's annual surveys of manufacturing firms and its pollution information transparency indexes at the city level. We find that stricter environmental disclosure in China leads to increased firm profitability, lending support to the Porter hypothesis. And the results are robust to various robustness checks. In addition, the results show that the environmental disclosure program in China increases industrial firms' propensity to innovate as well as innovating firms' innovation intensity. Thus, the findings of this paper provide more rationales for governments to use environmental information disclosure as a mean of pollution reduction. Image 1 • China's environmental information disclosure program increases firm profitability. • Stricter environmental disclosure also leads to increased firm innovation. • Increased innovation is necessary for increased profitability. • The results lend support to the Porter hypothesis. • The results encourage the use of environmental information disclosure programs. [ABSTRACT FROM AUTHOR]

Since China entered the 'new normal', China has begun to aim at high-quality green development. Therefore, the government proposes building an environmental governance system that is government-led, is enterprises-oriented, and includes the participation of social organizations and the public in multi-governance and source prevention. China must implement the concept of green development and jointly promote the construction of ecological civilization. However, there is no scholarly research on the impact of pluralistic governance on green development. Based on this information, this paper will use the panel data of China's 30 provinces from 2004 to 2014. This paper divides green development into the green development modes and the green development effect, and we study the impact of public participation and regulation compliance on green development. The results show that: (1) the improvement of corporate regulatory compliance is conducive to improving the green development mode and promoting the green development effect; and is thus conducive to achieving green development. (2) Different means of public participation have different effects on green development. (3) The interactive effect of corporate regulation compliance and public participation can promote the improvement of green technology and improve the green effect. That is, public participation can guide enterprises to improve compliance and promote green development. (4) The degree of public participation has a positive effect on the improvement of the green development mode in the eastern and central regions, and it has an obvious effect on the green development effect in the western region. [ABSTRACT FROM AUTHOR]

Renewable portfolio standard (RPS) is a compulsory institutional change to achieve low-carbon energy transformation in China. Its success depends on the scientific system quasi-parameter design, the most important system quasi-parameter is the benchmark price of the tradable green certificate (TGC). Setting the benchmark price of TGC scientifically and reasonably in line with China's national conditions is conducive to the effective implementation of RPS in China. Based on the system dynamics (SD) to construct China's green certificate trading market model, this paper analyzes the interaction between the TGC market and the electricity market under the RPS, and uses Vensim simulation to simulate the optimal TGC benchmark price based on the maximization of social welfare. The results show that the TGC market and the electricity market are mutually influential. As the benchmark price of TGC increases, the total power generation increases and the on-grid price decreases. Consumer surplus, producer surplus and social welfare all reach the maximum when the TGC benchmark price is 0.4yuan/KWh, so determines 0.4yuan/kWh as the optimal benchmark price of TGC. • The cyclical influence mechanism of TGC price are studied. • The trading process of TGC market and electricity market is analyzed by SD model. • This paper reveals the optimal TGC's benchmark price from China perspective. • This paper simulates the operation of the TGC market in China. [ABSTRACT FROM AUTHOR]

Rare earth elements sources in China have been overexploited and have caused serious soil pollution. The hyperaccumulator Dicranopteris dichotoma was discovered to have the ability to remove rare earth elements from contaminated soil and was widely planted as part of the remediation process for rare earth elements contaminated soil. Therefore, abundant hazardous Dicranopteris dichotoma biomass containing a high concentration of rare earth elements was generated. However, treatment methods for Dicranopteris dichotoma have not been previously investigated. In this paper, the eco-friendly technology of vacuum-pyrolysis-condensation was proposed for disposing the biomass of this fern, it was employed to change biomass accumulated with rare earth elements in to chemical resource. Ethylene oxide was the main component of the chemical resources, constituting 49.4 wt%. However, no ethylene oxide was detected in the pyrolytic products from non-accumulated biomass. The residual ash contained 6160 mg kg−1 of rare earth elements and was suggested as a rich 'bio-ore' of rare earth elements. No hazardous wastes were produced in the reclamation of these hyperaccumulators. We concluded that rare earth elements strongly influenced the pyrolysis process of dicranopteris dichotoma biomass and caused the generation of ethylene oxide. This paper takes the vacuum-pyrolysis-condensation of rare earth elements accumulated Dicranopteris dichotoma as the guidance, in order to attract more attention and develop more eco-friendly disposal technologies for hyperaccumulator biomass from the remediation process of contaminated soil, recovering the biomass resources and realized its high value. Image 1 • Rare earth elements (REEs) has caused serious soil pollution in China. • Quantities of REEs were accumulated in D. dichotoma in the remediation process. • A new technology to recover REEs from hyperaccumulator biomass was developed. • Higher yield of ethylene oxide was produced from contaminated D. dichotoma. [ABSTRACT FROM AUTHOR]

An increasing amount of resources is being utilized to combat the pollution problem in China. Measuring and improving the efficiency of this resource allocation is an effective way to promote pollution treatment at the present technical level. This paper utilizes a two-stage data envelopment analysis (DEA) model to attain allocation results based on the zero-sum gain and fixed-sum gain assumptions. We divide all the inputs into discretionary and non-discretionary inputs and construct two models for allocating resources based on the environmental efficiency scores. The new models are applied to calculate the performance and resource allocation scheme of 30 Chinese provinces from 2011 to 2015. Most provinces are inefficient at controlling pollution emission or treating pollution while using the given level of input resources. Based on the production possibility set of each province in 2015, the processing capacity of wastewater and gas could be increased by 1% and 3%, respectively, by reallocating resources for pollution treatment among different provinces. Environmental efficiency scores and resource allocation plans based on various assumptions are obtained in this paper to enlighten the corresponding decision-makers. Image 1 • The paper constructs two resource allocation models based on the DEA approach. • This research considers the allocation of public pollution treatment resources between different sectors. • Two strategies for resource allocation are composed to deal with different conditions relating to resources. • We apply the new models to measure the performance of 30 regions in China. [ABSTRACT FROM AUTHOR]

Poverty remains one of the long-term chronic dilemmas facing the sustainable development of human society during the 21st century. The spatiotemporal dynamics of poor regions, particularly in developing countries, is crucial for realizing fundamental sustainable development goals (SDGs). For decades, many scholars have sought to accurately measure, identify and alleviate poverty at different geographical scales. However, reliable data about the estimation of poverty remain scarce for developing countries, hindering efforts to accurately identify poverty. This paper utilizes the Defense Meteorological Satellite Program Operational Linescan System (DMSP/OLS) sensor nighttime light imagery to identify poor counties in China from 1992 to 2013. Using 16 statistical and spatial features extracted from this nighttime light imagery and using 96 poor counties and 96 nonpoor counties from 2010 as the classification sample, we describe the spatiotemporal dynamics of poor counties based on a random forests approach. Our study finds that the number of poor counties is decreasing in a fluctuating pattern and that contiguous poverty-stricken areas are becoming fragmented. The reduction in poor counties exhibits a manner of moving horizontally from the eastern regions to the central and western parts of China, while the number of poor counties in the central and western regions has decreased around the central cities or areas. The Aihui-Tengchong Line is not the dividing line in the distribution of poor counties in China, which means that China's poor can also be found in areas with relatively high population density. Together, the findings reveal that the key to reducing regional poverty is the development of regional economies and the implementation of national macro policies. This paper provides references for formulating antipoverty strategies for each county and offers new insights into poverty estimation and regional sustainable development for other developing countries. Image 1 • A new research framework is proposed to identify poverty. • Imagery and random forests are used to classify poor counties. • Spatiotemporal dynamics of poor counties are monitored in China. • Poverty dynamics generate implication for poverty policy and sustainable development. [ABSTRACT FROM AUTHOR]

Shale gas plays an important role in energy transformation. The sustainable development of the shale gas industry is a prerequisite for achieving an efficient, green, and long-term use of shale gas resources. This paper uses the WSR (Wuli-Shili-Renli) methodology to determine a comprehensive indicator system for assessing the sustainability of the shale gas industry. Game theory was used to combine two objective weighting methods and determine the comprehensive weight. The sustainability of the shale gas industry was evaluated based on the fuzzy matter-element extension theory. The results of the evaluation show that the overall sustainable development of China's shale gas industry is relatively poor. Shale gas industry in most regions is in a critically sustainable state (The critically sustainable state indicates the sustainability of the shale gas industry in general. The industry as a whole has the basic conditions for sustainable development in the short term; however, efficiency needs to be further improved to avoid the risk of degradation.) and is susceptible to degradation due to environmental changes. The shale gas industry in a few other regions is in an unsustainable state and cannot achieve an efficient and green development of shale gas. This paper evaluated the sustainability of the shale gas industry from a unique perspective. It is expected that the results of this research will contribute to the formulation of sustainable development strategies and further promote the green development of the shale gas industry. • The sustainability of the shale gas industry in some areas of China was studied. • We developed an evaluation model using the WSR methodology and the fuzzy matter-element extension method. • Expanded the application scope of game theory methods. • China's shale gas industry has a poor level of sustainable development. [ABSTRACT FROM AUTHOR]

The metal industry (MI) in China is energy and emissions intensive. This paper tries to provide guidance for the green development transformation of China's MI, by investigating the green total-factor productivity (GTFP) and its influencing factors using a global data envelopment analysis and a spatial Tobit regression model. The estimation results show that: (1) from 2000 to 2015, GTFP of China's MI enjoyed a considerable improvement. However, the current value of GTFP of China's MI is still less than 0.5, indicating that GTFP of China's MI is far from efficient; (2) the spatial correlation test shows that GTFPs of China's provincial MIs have positive spatial correlations. Most of the provinces scattered in "high-high" and "low-low" agglomerations; (3) GTFP of China's MI is significantly positive related to the degree of marketization, fiscal decentralization, environmental regulation, industrial scale, is significantly negative related to resources endowment and product structure, and has "U" shaped relationship with the level of economic development. The above results suggest that China already has made remarkable achievements in promoting green development of its MI. However, there is much room for further improvement. Policy options for the green development transformation of China's MI include but are not limited to promoting market-oriented and financial system reforms, strengthening environmental supervision, and optimizing industrial scale and product structure. Finally, recommendations for the effective implementation of these policies are provided at the end of the study. • This paper analyzed the historical performance and influencing factors of GTFP of China's MI. • Results show that GTFP of China's MI achieved considerable improvement in the past few years. • However, the current level of GTFP of China's MI is still very low. • There are many effective policy options for further promoting GTFP growth of China's MI. • Some implications for the implementation of these policies are provided in this paper. [ABSTRACT FROM AUTHOR]

The objective of the traditional dispatching optimization model is to find the most economical scheduling mode, while ignoring the efficient use of renewable energy. To properly arrange thermal power generation and renewable energy power generation, this paper constructs an optimization model of the combined wind–photovoltaic (PV)–thermal dispatching system under a carbon emissions trading (CET) mechanism. The contribution of this paper is twofold. First, a dispatching optimization model is proposed, which not only considers the total cost but also takes into account the impact of the renewable energy spillage rate on the dispatching system. As a factor affecting renewable energy consumption, a carbon emissions trading mechanism has also been introduced into the dispatching system. The second contribution is to develop a model for predicting the output of renewable energy generation. Then, the optimization model is applied to the auxiliary power dispatching system of the Tianzhong ±800 kV UHV DC transmission channel in Xinjiang. The results indicate that under a carbon emissions trading mechanism, thermal power generation will be limited by the carbon emissions cost, thereby reducing the total cost of the system. Optimizing the spillage rate increases the share of renewable energy in the dispatching system, resulting in a 3.5% reduction in the actual spillage rate. The proposed model alleviates the serious problem of electricity being abandoned in the existing scheduling mode and helps to realize economical low-carbon dispatching of the power system. [ABSTRACT FROM AUTHOR]

Accurate PM 2.5 forecasting provides a possibility for establishing an early warning system to notify the public and take precautionary measures to prevent negative effects on ambient air quality and public health. Considering strong seasonal variation in meteorological conditions, in this paper, a seasonal stacked autoencoder model combining seasonal analysis and deep feature learning is proposed for forecasting the hourly PM 2.5 concentration, named DL-SSAE model. The original data are firstly decomposed into four seasonal subseries according to the Chinese calendar, and then the Kendall correlation coefficient method is employed to search inherent relationships between PM 2.5 concentrations and meteorological parameters within 1-h ahead for each seasonal time series. The inherent relationships of each seasonal subseries are finally extracted, learned, and modeled by different deep neural networks (stacked autoencoders for regression), and the hourly PM 2.5 forecasts are yielded. The addressed model is tested by the dataset collected from three environmental monitoring stations in Beijing, China. The results demonstrate that the proposed model outperforms all other considered models with/without seasonality consideration in this paper. [ABSTRACT FROM AUTHOR]

Throughout the imminent water crisis era and stringent water environment management, enterprises play a vital role in environmental governance. However, there is seldom analysis on how the water environment regulation influences an enterprise's innovation due to data deficiency. Using our database from 2000 to 2022, we combine geographic information from water quality monitoring stations with the data on listed companies in China to pinpoint what distance firms are exposed to the monitoring stations. Results from a spatial regression discontinuity design along the geographic distances demonstrate that water environmental regulation has a significant positive impact on the quantity and quality of enterprise innovation. This paper found that it is primarily driven by the decreased usage of intermediate goods, rising industry profits from the exit of low-productivity firms, and enhanced enterprise research and development (R&D) investment. Furthermore, the positive impact is more pronounced for privately-owned firms, firms closer to suppliers, polluting firms, and politically unaffiliated firms. Our study offers scientifically valuable insights for emerging market countries in formulating effective water environmental regulation policies to incentivize firms to innovate in environmental protection. Additionally, it provides novel ideas on synergizing water environmental regulation and firm innovation to foster a mutually beneficial relationship between environmental protection and sustainable development. [ABSTRACT FROM AUTHOR]

With the comprehensive progression of China's electric power reform, the participation of hydropower in the spot market has become inevitable. For hydropower-dominated power grids, the tight hydraulic and electric coupling relationship between cascade hydropower plants and the policy requirement of clean energy consumption greatly increase the challenge of optimal scheduling. Based on the market characteristics and actual demand of the hydropower-dominated power grids, this paper discusses the day-ahead spot market trading mechanism to promote the guaranteed consumption of renewable energy. On this basis, a day-ahead optimal scheduling model is established which aims to minimize the comprehensive power purchase cost of the power system. The nonlinear factors in the scheduling model, such as the relationship between the water level and storage capacity of hydropower plants, the relationship between the water level and water consumption rate, and the constraints on the start-up and shutdown durations of thermal power units, are linearized through multiple linearization techniques. The original nonlinear model is transformed into a mixed integer linear programming (MILP) model and is then solved using a CPLEX solver. The developed model is verified by taking 10 thermal power plants and 22 hydropower plants in Yunnan Power Grid as a case study. The calculation time is 183.6s, the comprehensive power purchase cost of the system is 155.35·million CNY, and no abandoned water is generated in the three basins. The simulation results show that the proposed model has high solution accuracy and efficiency, and maximizes the hydropower consumption under the premise of meeting the minimum comprehensive power purchase cost. The findings of this study can provide a scientific basis for the development of the day-ahead spot market of hydropower-dominated power grids. [Display omitted] • A day-ahead spot market trading mechanism to promote consumption of renewable energy. • Day-ahead optimal scheduling of hydropower-dominated power grids under a spot market environment. • A novel MILP approach is employed to solve the model. • Proposed model has high solution accuracy and efficiency. [ABSTRACT FROM AUTHOR]

Mitigating greenhouse gas emissions is a significant global challenge, and precise prediction of carbon emissions holds the utmost importance for China to attain its dual carbon goal. To overcome the limitations of existing studies using a single forecasting method, based on quadratic exponential smoothing, multiple linear regression, and Gaussian process regression models, this paper constructs a carbon emission combination forecasting model with the generalized induced ordered weighted average (GIOWA) operator and analyzes carbon emission reduction performance. Empirical testing utilizing China's carbon emission data from 1980 to 2020 reveals the following findings: (1) The GIOWA combination forecasting model significantly enhances the accuracy of carbon emission forecasts, with an average accuracy exceeding 99.5% over the sample period, surpassing various single forecasting methods. (2) The carbon emission reduction target can be achieved under three different scenarios of low, average, and high GDP growth rates. Specifically, under the low growth rate scenario, China can achieve a 60% reduction in carbon intensity by 2025 and a 65% reduction by 2030. This study offers valuable decision support for the development of effective carbon reduction policies. [ABSTRACT FROM AUTHOR]

The accurate prediction of China's CO 2 emissions provides a reference and early warning for the implementation of the government's environmental strategy and has far-reaching significance for the world's environmental protection. The carbon emission system is a nonlinear dynamical system influenced by multiple factors with multiple data features. This paper establishes a novel grey differential dynamic multivariate prediction model with recurrent neural network. It uses the grey differential dynamic multivariate prediction model to describe the dynamic characteristics of the nonlinear system. And it uses recurrent neural network to extract data features. The new model is used to compensate for the shortcomings of the grey prediction model that use the least squares method to solve the model parameters affecting the accuracy of the model. The numerical solution of the whitening equations of the new model visualizes the hidden layer state function of the recurrent neural network. The optimal parameters of the new model are obtained through repeated training to improve the prediction accuracy of the model. Finally, the new model is applied to the prediction of China's CO 2 emissions to verify the validity of the new model from four different perspectives. The results show that the simulation and prediction errors of the new model for data of different lengths are less than 5%. The average simulation error in the optimal scheme is 3.01%, and the average prediction error is 0.78%. The results of the new model are better than the results of the other models. This indicates that the new model has better prediction results. Applying the scenario in forecasting the amount of carbon dioxide in China from 2020 to 2026 yields a forecast that matches the actual trend, further illustrating the validity and feasibility of the model. Finally, the forecast results are analysed, and relevant policy recommendations are provided. • A novel neural network grey prediction model is developed. • The model uses neural networks to deeply explore the time-series type data features. • The dynamic nature of the system is reflected using multiple differential grey models. • Successful prediction of CO2 emissions in China. [ABSTRACT FROM AUTHOR]

Energy quota trading is critical to both energy conservation and the achievement of dual-carbon goals. However, little remains to be done on total factor productivity and economic potential for Chinese industry. The purpose of this paper is to counterfactually model and explore the effects of energy quota trading on total factor productivity and economic potential in industrial sector. We propose a command-controlled DEA model and an energy quota trading DEA model through non-parametric linear programming based on two policy strategies of energy consumption control. We then assess total factor productivity and its growth sources for 35 two-digit industrial sector in China, as well as examine economic potential and optimal path forecasts for carbon peaking. The results show that total factor productivity and economic potential for energy quota trading are higher than those for command-controlled energy policy. Energy-saving effect can be achieved for energy quota trading because the total energy input is lower. Additionally, the sources of productivity growth differ in timing. The average economic potential and total factor productivity of different industries differ due to the heterogeneity of the production conditions and scale of development of individual market players. Moreover, the catch-up emission reduction path with an increase of 8% in output and 4.76% in energy consumption is the optimal carbon peaking path under energy quota trading. Our findings shed valuable light on China's efforts to expand energy quota trading for high-quality development in the context of carbon peaking. • Propose a command-controlled DEA model and an energy quota trading DEA model. • Assess TFP and its growth sources for industrial sector in China. • Compare the impact of different energy policies on economic potential and TFP. • Estimate the energy saving and emission reduction potential of energy quota trading. • Examine the optimal energy-saving and emission-reduction path forecasts for carbon peaking.. [ABSTRACT FROM AUTHOR]

Temperature shocks can cause various adverse effects on manufacturing firms, such that the adaptation activities of manufacturing firms to temperature shocks need to be focused on. Accordingly, this paper aims to investigate whether and why temperature shocks could be an accelerator for digital transformation of manufacturing firms. Empirical results suggest that extreme heat waves can propel manufacturing firms to strengthen their digital transformation orientation, while cold waves cannot. The effect of extreme heat waves on digital transformation orientation is likely to be performance-driven, rather than pro-environmental responsibility-driven. In addition, we indicate that there exist temperature adaptation effects, such that manufacturing firms located in areas with long-term exposure to extreme temperatures are less likely to strengthen digital transformation orientation after extreme temperature shocks, relative to those located in long-term temperature comfort regions. [ABSTRACT FROM AUTHOR]

Existing studies on water resource issues focus on water scarcity while largely lacking an integrative water balance health assessment and ignoring the combined impacts of water quality, water transfer, and unconventional water resources on water balance. Here, we proposed a novel framework for assessing regional water balance health considering three dimensions of water problems about imbalances: water scarcity, water inequality, and systems incoordination. This paper first quantified the levels of water balance health at multiple geographic and temporal scales in China, and then investigated the critical components and the impacts of improved surface water quality, inter-basin water transfer, and unconventional water use on the local water balance health. Results showed that China was under an unhealthy water balance due to multiple imbalances based on the annual average assessments during 2014–2018. More than 45% of the national population (∼615 million people) was affected by an unhealthy water balance. Hotspots with unhealthy water balance exhibited spatial heterogeneity and temporal variability, with Northern China experiencing unhealthy water balance throughout the year, while Southern China usually faced this issue during the winter. Unhealthy water balance in Northern China was primarily driven by water scarcity, while in the west of the Hu-Huanyong Line, water inequality exacerbated the situation. Southeastern China faced systems incoordination, particularly vulnerable during extreme events, such as severe droughts. More than 400 and 150 million people benefited significantly from improved surface water quality and inter-basin water transfer, respectively, relieving unhealthy water balance. However, the effectiveness of unconventional water use was found to be limited. This study contributed to a better understanding of water balance health and facilitated the development of policies for integrated water resources management in China. [Display omitted] • A novel method is proposed to quantify water balance health level at a basin scale. • China is experiencing an unhealthy water balance with multiple imbalances. • Over 45% of the national population is affected by an unhealthy water balance. • Geographic patterns of the critical components responsible for unhealthy water balance are determined. • Effectiveness of multiple measures in improving water balance health level is evaluated. [ABSTRACT FROM AUTHOR]

In response to the global call for biodiversity conservation and sustainable development, China plans to reform its protected areas (PAs) system. Despite positive progress, there are still challenges in defining PAs boundaries, allocating management authority, and securing sustainable funding. This paper reviews the current state and challenges of China's PAs management and advocates a paradigm shift towards comprehensive public governance. This shift aligns with the Ecological Conservation Redline (ECR) and integrates PAs into the National Territorial Spatial Planning, for a coordinated layout of Ecological-Productive-Living Spaces. The current study emphasizes the need for a refined assessment of PAs, including ecosystem services, to balance human development rights and environmental sustainability. It also advocates for multi-stakeholder consultation mechanisms to ensure broader social participation, particularly for indigenous peoples and local communities. The current investigation highlights the importance of valuing ecological products to harmonize environmental protection with community welfare. This review contributes to the discourse on balancing ecological integrity with socio-economic progress and provides insights into the difference between human rights, ecological conservation, and sustainable development, marking a significant stride towards global sustainability goals. [Display omitted] [ABSTRACT FROM AUTHOR]

Given the worsening environmental pollution and China's carbon peak and carbon neutrality goals, it is imperative to study the low-carbon travel behavior of urban residents. Previous research has mainly focused on objective environmental factors, subjective behavioral factors, and low-carbon travel behavior. However, the evolving decision-making of local governments, community residents, and individuals within the low-carbon travel system still needs to be explored. Tripartite evolutionary game theory is an effective method for studying the dynamic changes in strategies among limited rationality multiple actors in long-term repeated games, making it applicable to this study. Therefore, this paper simulates participants' behavior using evolutionary game theory, conducts stability analysis of equilibrium points of the replicator dynamic system using the Lyapunov first method, derives evolutionarily stable strategy combinations under different conditions, and finally performs simulation analysis using Matlab. The simulation results indicate: (1) By implementing reasonable incentive mechanisms, Local governments can encourage citizens to adopt low-carbon travel and community transformation. They should pay attention to their expenditures and subsidies, manage their spending to reduce consumption, maximize efficiency, and strive to achieve carbon emission reduction goals. (2) The likelihood of residents choosing low-carbon travel is mainly influenced by direct advantages such as health and economy in the initial stages, and later, it is more affected by the indirect benefits brought about by subsequent objective environmental changes. (3) The cost of renovation significantly affects the built environment of communities, leading to a reduction in renovation costs and the adoption of uniform standards and, consequently, stimulating enthusiasm for community transformation. The research findings suggest that the government can collaborate with the public to reduce carbon emissions by implementing specific environmental changes and providing incentives to encourage citizens to participate in low-carbon transportation. Simultaneously, the government can cooperate with the public, considering the quality of environmentally friendly transportation for citizens, formulating uniform regulations, reducing renovation costs, and achieving the highest low-carbon goals with minimal financial expenditure. [ABSTRACT FROM AUTHOR]

Battery electric industrial vehicles (BEIVs) offer significant environmental protection and decarbonization potential for rapidly growing logistics and transportation sectors in China. However, the limited driving range remains a major obstacle to the widespread adoption of BEIVs. Eco-driving is an effective solution that can improve energy efficiency and extend the driving range of vehicles by controlling driving behavior and speed. Therefore, this paper introduces an energy efficient speed planning method for BEIVs, in which data-driven models are developed to estimate energy consumption. Real-world driving data collected from a BEIV are used to model the energy consumption by curve fitting, random forest, and LSTM. The speed planning process is considered a Markov Decision Process, which is solved using Dynamic Programming and Q-learning, respectively. The case study of a battery electric forklift shows that speed planning can reduce energy consumption by 13%–27% compared to time-optimal speed, while only increasing the driving time by 10%–20%. • Energy efficient speed planning methods for electric industrial vehicles are proposed. • The speed planning method uses data-driven vehicle energy consumption models. • The energy consumption models are developed using random forest and LSTM. • The speed planning problem is formulated as a Markov decision process. • The speed planning problem is solved by Dynamic Programming and Q-learning. [ABSTRACT FROM AUTHOR]

Under the research background of China vigorously promoting the planning and construction of multi-energy complementary energy bases as well as the steady advancement of the electricity market, how to better promote the participation of large-scale multi-energy complementary bases in the electricity market has become a new research focus. In this paper, a joint optimization model for the participation of multi-energy systems in the electric energy market and auxiliary service market is proposed based on the Nash negotiation theory with coordinated wind-photovoltaic-pumped-storage-hydropower (WPPSH) generation systems as the research objects. Further, the joint optimization model is equated into two subproblems, namely, maximizing the net return of the alliance and negotiating the payment of the multi-energy complementary transaction, and the alternating direction method of multiplier algorithm (ADMM) is used to solve the above two subproblems separately. The simulation results show that the revenue of WPPSH increased by 25.82%, 30.67%, 49.35% and 3.78% respectively after joint operation, and the absorption rates of wind power (WD), photovoltaic (PV) and hydropower (HY) increased by 17.69%, 21.87% and 9.01% respectively. Through the cooperation of WPPSH generation systems, the income of each entity and the alliance can be improved, the fair distribution of incremental income is basically realized, and the consumption of clean energy can be promoted. In addition, the capacity allocation cap ratio of pumped storage (PS) units in the energy market and auxiliary service market will have a certain impact on the returns of WPPSH generation systems in multi-principal cooperation. [Display omitted] • The WPPSH can improve the profits of the alliance and individuals. • The WPPSH can improve the consumption rate of all kinds of clean energy. • The capacity allocation ceiling ratio of PS will have a certain impact on the cooperative benefits of WPPSH. • Nash negotiation theory is helpful for each agent to achieve the optimal trading strategy. [ABSTRACT FROM AUTHOR]

In order to probe collaborative environmental governance (CEG) in China's "1 + N" policy framework for carbon peak and carbon neutrality, this paper applies the Actor-network theory (ANT) as an analytical framework to explore carbon reduction policy coordination. We then model ANT's relations with an evolutionary game theory (EGT) model to examine the evolutionarily stable strategies in CO 2 emission reduction by various actors including the central government, local governments, commercial banks, and polluting enterprises. Our objective is to examine policy coordination as the key enabler for governing success via an ANT-based mechanism design in China's institutional context. Combining the strength of ANT with a four-party EGT model, we investigate how to improve policy coordination to mobilize the actor-network for promoting CEG. Simulations are conducted to examine the effectiveness of policy coordination involving multiple policy instruments for controlling carbon emissions. The central government fulfills leadership in translating the interests of other actors and shaping the desired collaborative network. Without proper coordination, environmental policies may counteract each other. Government transfers and subsidies have direct impacts, but in the long run enhanced competitiveness and profitability of enterprises represent the intrinsic key to CEG success. From a methodology perspective, policy simulation in an EGT framework represents a novel addition to the research toolbox that expands ANT. [ABSTRACT FROM AUTHOR]

The aim of the paper is to evaluate empirically the main implications of digital technology (DT) on carbon emissions (CE). Our sample focuses on 283 cities of China over the period from 2003 to 2019, and the effect of DT on CE is examined with a threshold spatial effect model. Empirical results show that DT has a negative impact on carbon emissions and the transmission mechanism contains both a direct impact on local region and a spillover effect across regions. There is empirical evidence of a threshold effect in the relationship between DT and CE, with stronger carbon reduction effect for DT values larger than the established threshold. Moreover, CE reduction effect of DT appear to be amplified by the level of marketization. Regions with a higher level of marketization thus show a more significant manifestation of CE reduction effect attributed to DT. Our results provide empirical evidence that DT development may contribute to achieving carbon neutrality at least partially. [ABSTRACT FROM AUTHOR]

Australia is a long-term key partner of China in coal trading, which is famous for high-quality coal and its price advantage. However, affected by the evolution of international political and economic situation, China has issued a coal ban on Australian coal since the end of 2020. The potential environmental consequences of this coal ban remain unclear. So, this paper quantifies the ban's impact on air pollution, human health and climate change by simulating the emission difference between the port scenario (simulating the emissions due to Australian coal import under business as usual) and the mine scenario (simulating the emissions due to domestic coal mining that converted from import share of Australian coal), and monetizes the losses into economic costs for direct comparison. The results illustrate the emission of SO 2 , VOCs and GHG in mine scenario grows up to 102, 12 and 6 times the amount of that in port scenario, mainly deriving from coal mining process in the North China Plain and Yunnan-Guizhou Plateau. It shows that the potential alternative of replacing import with mining leads to PM 2.5 pollution exacerbation and O 3 pollution abatement, which causes 148 (95 % CI: 101–183) non-communicable diseases and respiratory disease-related deaths in total. As for GHG, the emission of BC in transportation process and fugitive methane in coal mining process contribute to an impressive effect on warming potential with few quantities, which is worth noting in control process. In total, the environmental deterioration resulted in an economic loss of approximately 934 million yuan. The undiminished demand for high-quality industrial coal as well as growing carbon tax could make the economic value of the coal ban's environmental consequences more considerable in the near future. This research emphasizes the contradiction between economic development and environmental improvement caused by excessive dependence on coal and addresses a critical knowledge gap in assessing the ban's environmental impact by economic value. The result directly demonstrates the environmental consequences of the potential mining-replacing-import alternative and helps better understand environmental influences on the Chinese government's decision. [ABSTRACT FROM AUTHOR]

In the dynamic landscape of rapid change and the pervasive influence of the digital revolution, the discussion surrounding the impact of digital transformation on the innovation performance of firms has become a focal point of intense debate. This paper aims to contribute to the evolution and advancement of traditional organizations toward high-quality development by addressing this issue through the integration of technology into the framework, leveraging the resource-based theory. The study seeks to explore the influence of digital transformation on innovation performance, specifically examining the role of supplier concentration in this relationship. Additionally, we investigate the moderating effect of CEO financial experience on the association between digital transformation and innovation performance. Utilizing multiple regression methodologies and analyzing data from Chinese listed firms spanning the period from 2007 to 2022, our empirical findings reveal a direct positive relationship between digital transformation and innovation performance. Furthermore, the study uncovers an indirect pathway through which digital transformation enhances innovation performance by mitigating supplier concentration. Notably, the positive impact of digital transformation is amplified by a CEO's background in finance. Finally, the effect of digital transformation on innovation performance is particularly pronounced in sectors such as state-owned entities, advanced technology companies, large-scale businesses, and those in their maturity phase. These insights provide valuable contributions to addressing concerns related to digital transformation, particularly in emerging economies like China. The findings offer essential lessons for navigating the transition to Industry 4.0 and fostering sustainable innovative practices. By emphasizing the role of supplier concentration and the moderating influence of CEO financial experience, this research contributes to a nuanced understanding of how digital transformation can positively impact innovation performance across diverse sectors. [ABSTRACT FROM AUTHOR]

Being one of the significant conduits linking international and domestic markets, agricultural trade is an area of study that commands attention. While it may bring about transnational carbon emission transfers, it begs the question: does it promote carbon reduction in a country's agricultural sector? Such an inquiry holds profound implications for optimizing agricultural trade and promoting low-carbon agricultural advancement. Utilizing two-way fixed effect model, mediating effect model and dual-fixed spatial Durbin model, this paper examines the impact effects, mechanisms and spatial characteristics of agricultural trade openness (ATO) on agricultural carbon reduction using panel data from Chinese provinces spanning 2000 to 2021. The main findings include: (1) ATO markedly and positively influences the reduction of agricultural carbon emissions (ACE), this conclusion maintains its validity under endogeneity treatment and robustness tests. (2) ATO contributes to reducing ACE through three intermediary channels: scale effect, technological effect, and structural effect. (3) From a spatial perspective, a notable positive spatial spillover effect is observed from agricultural trade openness to agricultural carbon reduction, with the spatial carbon reduction effect being more apparent. (4) The spatial carbon reduction effect of agricultural trade liberalization exhibits heterogeneity across different natural geographical locations and levels of ATO. The study confirms the vital role of ATO in promoting agricultural carbon reduction in typical countries, underscoring the urgency and importance of bolstering cross-border agricultural trade cooperation and domestic agricultural product circulation in the domain of climate change. • The impact of agricultural trade openness (ATO) on agricultural carbon reduction is investigated in China. • The scale, technological, and structural effect of ATO serve as intermediary channels in reducing carbon emissions. • ATO engenders positive spatial spillover effects on agricultural carbon reduction. • Bolstering cross-border agricultural trade cooperation are of importance and urgency in the domain of climate change. [ABSTRACT FROM AUTHOR]

Modern agriculture involves the cooperation of stakeholders in multi-fields where their interaction significantly impacts the planning and operation of rural power systems. However, the traditional planning and operation for rural power systems assumes the power consumption as a given input without considering its unique feature caused by human factors. Particularly in China's rural areas, power consumption will rapidly increase and decrease due to the human-factor-based activity of farmer households' off-farm employment in urban and their home-returning during some important festivals. Therefore, this work proposes a multi-agent decision-making framework to realize the planning and operational optimization of power systems in a human-factor-based rural community. The framework integrates multiple agents' decision-making models including various stakeholders in modern agricultural systems and analyses their interaction. The meteorology-load and meteorology-generation models of power are materialized and embedded in the intensive agriculture and power system agent's decision-making models, which are used by the two agents to estimate the power consumption and photovoltaic (PV) generation, respectively. This work first quantizes the macro choice process of human-factor-based farm and off-farm employment and the numbers innovatively. Further, the farmer behavior for farm employment is simulated by the agent-based modeling system, and the power consumption of the farmer household group is estimated. Based on the overall agents' power consumption in the community, the planning and operation model of the power system is proposed to decide the optimal size and dispatch of the electrical devices. A multi-agent rural community is conducted for the case study to verify the effectiveness of the proposed decision-making framework. The results show that the farmer households who choose off-farm employment account for 66 % of the total households and their power consumption in most of the daytime on weekends is higher than on weekdays. The transportation system agent decides to purchase the electric truck with 5 tons of struck capacity for crop transportation. The power system agent decides to construct a hybrid system of PV, battery energy storage, and a transmission line of less transmission capacity, which can reduce its total system cost. Additionally, this paper finds that the solar radiation obtained by the greenhouse, which is considered the intensive agriculture agent, and its power consumption show opposite variation tendency, and the power consumption of the farmer household group in the Spring Festival is the largest. • A multi-agent decision-making framework of a rural community is proposed. • A meteorology-load and meteorology-generation models are materialized. • A macro choice process of human-factor-based farm/off-farm employment is quantized. • A bottom-up estimation method of power consumption is established by farmer behavior. [ABSTRACT FROM AUTHOR]

Understanding how municipal solid waste (MSW) classification influences the physiochemical properties and incineration emission characteristics of MSW is imperative for sustainable waste management. To investigate how long-term changes in the composition and physical properties of MSW resulting from MSW classification affect the emissions of polychlorinated dibenzo-p-dioxins/dibenzofurans (PCDD/Fs) and multiple flue gas pollutants, a five-year experiment (2018–2022) was conducted in a full-scale MSW incinerator in Shenzhen City, China. After MSW classification, the food waste in MSW was substantially reduced while the paper, textile, and wood components were notably increased. MSW classification also remarkably decreased the water and chlorine contents of MSW while concomitantly increasing the wet-based calorific value, sulfur content, and nitrogen content. Consequently, the PCDD/Fs emissions declined from 106.7 ng I-TEQ/t MSW in 2018 to 26.0 ng I-TEQ/t MSW in 2022. Moreover, a process-tracing experiment demonstrated noticeable decreases in PCDD/F synthesis in the post-combustion area, with mass-reduction efficiencies of 23.6 %–95.4 %. In a correlation analysis, the PCDD/F emissions were significantly positively correlated with food waste, water content, and chlorine and negatively correlated with the wet-based calorific value and nitrogen content. Furthermore, MSW classification reduced the emissions of conventional flue gas pollutants (SO 2 , CO, and HCl) and multiple heavy metals (total sum of Sb, As, Pb, Cr, Co, Cu, Mn, and Ni). In summary, the long-term study demonstrated that MSW classification can feasibly separate incombustible waste, improve combustion quality, and reduce pollutant emissions from sources. These findings offer practical guidance for promoting MSW classification. [Display omitted] • MSW classification remarkably changes composition and physical properties of MSW. • MSW classification mitigates PCDD/F emission from 106.7 to 26.0 ng I-TEQ/t MSW. • MSW classification effectively reduces the emission of various flue gas pollutants. • The long-term experiment demonstrated the feasibility of MSW classification. [ABSTRACT FROM AUTHOR]

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

We try to expand the political promotion tournaments in Chinese local governments from raising GDP to the level of increasing fiscal revenues. From the vantage point of officials' performance appraisal, we investigate the impact of local government officials' political ambitions, represented by the ex-ante commitment level of fiscal revenue targets, on carbon emission intensity (CEI). Utilizing a sample of 209 prefecture-level cities in China spanning 2006 to 2019, this paper empirically scrutinizes the influence of local government political ambition on CEI. The findings reveal that the greater the political ambition of local government officials, the more pronounced the reduction in CEI. Furthermore, our study demonstrates that political ambition contributes to the decline of CEI by elevating the levels of environmental attention and green innovation. This research not only aids in comprehending the rationale and necessity of the political promotion tournaments implemented by the Chinese central government but also offers valuable insights for other developing countries seeking to mitigate CEI. [ABSTRACT FROM AUTHOR]

With the rising awareness of green and sustainable development, corporate environmental, social, and governance (ESG) performance has become an essential topic in academia. Existing studies have focused on the driving role of formal institutions on corporate ESG performance while ignoring the motivational role of informal institutions such as culture. Based on the data of Chinese A-share listed companies from 2009 to 2021, this study adopts textual analysis to quantify corporate culture and discusses the impact of corporate culture on ESG performance and its internal mechanism. We find that corporate culture significantly enhances ESG performance. Mechanism test indicates that corporate culture can promote green innovation and improve information transparency through resource and information effect, enhancing ESG performance. We further demonstrate differences in the impact of corporate culture dimensions on ESG performance, with innovation culture and quality culture being the most prominent. In addition, there is heterogeneity in the impact of corporate culture on ESG performance. In the context of non-state-owned property rights, low market attention, and high economic policy uncertainty, the impact of corporate culture on ESG performance is more significant. This paper enriches the related research on ESG performance drivers from the informal system perspective and provides decision-making references for enterprises to promote ESG practices and achieve sustainable development. [ABSTRACT FROM AUTHOR]