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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]

Abstract Currently, wind and solar energy have not been well utilized in China, and the rate of abandoned wind and solar facilities in China is increasing annually. Renewable portfolio standards (RPS) are an effective system for promoting large-scale renewable energy integration and consumption and realizing the goal of renewable energy development. To clarify the interactive relationship between the different levels and multiple actors in RPS, this paper uses policy network theory to analyze the interactive relationship of stakeholders from the three aspects of network subject, network structure and network interaction. The policy network of the RPS consists of the policy community, professional network, intergovernmental network, producer network and issue network. Under the RPS, to meet their own needs, participants affect the formulation and implementation of the RPS through the actions of confrontation, alliance, competition and cooperation. In different stages of developing the RPS, the openness and integration of policy networks change accordingly. This study overcomes the limitations of past simple analyses of the actor relationship in the policy process and thereby offers certain reference significance. Highlights • The actors of RPS policy networks are analyzed. • This paper analyze the game relationship of the stakeholders from three aspects. • This research reveals the network relationship between multiple stakeholders. • This study breaks through the limitations of past analysis of actor relationship. [ABSTRACT FROM AUTHOR]

Abstract In the process of underground coal gasification (UCG), there have been doubts or controversies if it is possible to control pollution of heavy metals such as arsenic and cadmium. To eliminate this suspicion, this paper first investigated the control method and design flow of reducing heavy metal pollution in the process of underground coal gasification (UCG) without shaft based on the analysis of the potential arsenic and cadmium pollution forms. The relationships between the development height of underground gasification mining-induced fractures and the parameters of gasifiers was revealed. The findings indicated that: 1) By rationally designing the parameters of the gasifier, it can be possible to control the development of mining-induced fractures, thus ensuring that the underground combustion space area does not penetrate the aquifer, surface water and atmospheric environment. Consequently, the pollution of arsenic and cadmium caused by UCG without shaft can be controlled from the source. Meanwhile, the validity of this method was verified from an engineering example. 2)When the gasifier height was constant and the isolated coal pillar was stable, the gasifier width was linearly positively correlated with the development height of the mining-induced fracture; When the widths of the gasifier and the isolated coal pillar were constant, the gasifier height and the development height of the mining-induced fracture was also linearly positively associated. As the contents of arsenic and cadmium in coal are high in China and the United States, the arsenic and cadmium control methods during the underground coal gasification proposed in this paper have valuable application prospects in these two major coal countries. [ABSTRACT FROM AUTHOR]

Abstract The huge energy intensity gaps among Chinese prefectures make the overall reduction of energy intensity extremely difficult. Energy intensity convergence (EIC), i.e., catching-up of the high energy intensity prefectures with the low ones, is imperative for narrowing these gaps. As one of the most important channels for international technology diffusion, foreign direct investment (FDI) has great impact on energy intensity and may be beneficial for the convergence. Based on pollution haven Hypothesis, however, FDI may result in energy intensity divergence. To provide an in-depth understanding of the mechanisms of FDI-induced convergence/divergence, this paper employs Markov Chain approach to examine the impact of FDI on EIC for 256 Chinese prefectures in the period from 2005 to 2014. Moreover, we particularly emphasis on the influences of local specific characteristics, such as human capital, resource endowment, and environmental regulation, on FDI-induced convergence/divergence. Our study on 256 Chinese prefectures finds that FDI helps prefectures with higher energy intensity to catch up with lower ones, which strengthens EIC. The impact of FDI on EIC varies depending on different local characteristics. Among all characteristics mentioned above, human capital and environmental regulation benefit the convergence-driving effect of FDI, while this effect is hindered by resource endowment. More comprehensive and detailed policies are recommended to address energy intensity gaps in China. Graphical abstract Image 1 Highlights • The impact of FDI on energy intensity convergence is investigated. • The Markov chain approach is employed in this paper. • The results suggest FDI strengthens energy intensity convergence in China. • Human capital and environmental regulation promote FDI-induced convergence. • FDI-induced convergence is hindered by resource endowment. [ABSTRACT FROM AUTHOR]

Abstract This paper builds an environmental Kuznets curve (EKC) multiple logistic regression model to analyze how socio-economic development impacts mainland China's coastal waters environment. China's coastal provinces have significantly different seawater quality at different stages of the seawater's EKC. Jiangsu and Hebei are still at the early stage of the seawater's EKC because of the large quantity of pollution-intensive industry, whereas the coastal provinces at the late stage of the seawater's EKC have presented obviously improved seawater quality based on adjustments in the industrial structure since 2001. Urbanization has a severe impact on the seawater quality of Shanghai and Zhejiang at the middle stage of the seawater's EKC. Furthermore, this paper proposes an overall strategy and several "tailored" strategies to address coastal waters environment improvement for current poorly targeted policies at different stages of the seawater's EKC. [ABSTRACT FROM AUTHOR]

Abstract The purpose of this paper is to evaluate greenhouse gas (GHG) emissions of a Chinese highway tunnel in the life cycle. Life cycle assessment (LCA) method is adopted in the paper. Based on rock mass classification and pavement categories, five different functional units have been proposed for the first time. The system boundaries, processes and assumptions are defined. The study results indicate: 1) the GHG emissions of a double-track four-lane Chinese highway tunnel in 100 years can be up to 375.5 thousand tons of CO 2 eq. Cement and electricity contribute to more than 80% of the total emissions in all functional units. 2) The construction stage, operation stage and maintenance stage emit 30.89%, 56.12% and 12.99% of the total GHG respectively. During the construction stage, casting and lining, rock support and road work are the top three GHG emission processes. 3) Rock conditions are discovered to be an important factor of affecting GHG emissions in tunnels. The GHG emissions of the 1-m Chinese highway tunnel are between 82 t to 113 t CO 2 eq. With the increase of rock mass grades, GHG emissions rapidly rise if the pavement design stays the same. The emission differences among the functional units are mainly from materials. 4) Asphalt pavements tend to generate more GHG emissions than concrete pavement due to the more frequent replacements of asphalt pavements. This paper investigates the influences of rock conditions and pavement types on the GHG emissions of Chinese tunnels in the life cycle, which can provide a scientific reference for policy making of the Chinese government. [ABSTRACT FROM AUTHOR]

Abstract Faced with the dual constraints of economic growth and energy conservation and emission reduction, the unified environmental regulation policy has posed a dilemma for China. First, this paper adopts the method of Metafrontier Malmquist-Luenberger (MML) to analyze the influence of technology gaps and pollution emissions on the total factor productivity (TFP) of Chinese industry in the period of 2000–2016. Second, from the perspective of heterogeneity, the paper uses the threshold model to investigate the nonlinear dynamic influence of different types of environmental regulations on the environmental total factor productivity (ETFP) of industrial sectors, attempting to identify the optimal intensity of the environmental regulation and tools combination. The results indicate that due to the presence of industry heterogeneity, the different types of environmental regulations exerted heterogeneous influences on the ETFP in different industries. In heavy-pollution industries, an excessively high intensity of environmental regulation weakened the technological innovation of these enterprises. In moderate-pollution industries, there was found a medium intensity of environmental regulation, with the command-and-control and market-based types of environmental regulation being quite well coordinated. Among slightly polluting industries, there was a significant "N-shaped" characteristic between the market-based type of environmental regulation and the ETFP. The outcomes further imply that considering the presence of obvious industry heterogeneity, the establishment of environmental regulations should avoid both the unified adoption of static standards and the blind increase of regulation intensity. Based on the characteristics and realities of different industries, flexible and dynamic regulatory standards should be adopted, and multiple regulation instruments should be used. Highlights • ETFP presented a pattern of progressive decrease going from slight-pollution industries to moderate-pollution industries and finally to heavy-pollution industries. • Different types of environmental regulations exert heterogeneous influences on the ETFP of industries. • Environmental regulations should avoid both the unified adoption of static standards and the blind increase of regulation intensity. • A balanced regulation system should be established to stimulate a more strategically based economic response. [ABSTRACT FROM AUTHOR]

Abstract With the increasing international attention paid to environmental issues, the ability to pursue continuous development while protecting the environment and thereby achieving a win-win situation has become a significant issue for developing countries such as China. In previous studies, environmental regulation has been proven to be an effective governance mechanism. However, few studies have attempted to analyse the comprehensive impacts and determine the optimal stringency of environmental regulation, especially for a specific industry, based on the actual situation in China. Therefore, this paper calculates the effects of the current and proposed environmental regulation of China's steel industry from 2006 to 2013 by adopting a pollution treatment approach, and based on this calculation, it constructs a recursive dynamic steel industry chain CGE model to investigate the macroeconomic, market and technology impacts from an industry chain perspective under 3 different levels of environmental regulation of the steel industry. The simulation results show that real GDP and the outputs of the downstream sectors of the steel industry will suffer slightly, while the outputs and exports of the steel industry itself will benefit from stringent environmental regulation over the long term. In addition, the material efficiency of steel use will be improved in the long term through the implementation of environmental regulation of the steel industry. Based on the results, it is recommended that a moderate level of environmental regulation should be adopted initially, which can then be smoothly transformed into more stringent regulation during a period of economic growth to avoid sudden and major shocks. In addition, this paper also provides a reference for other substantial industries in China when choosing the optimal pattern for the implementation of environmental regulations. Highlights • The current environmental regulation of China's steel industry is far from adequate for compensating for the full external environmental costs. • A recursive dynamic steel industry chain CGE model of China is constructed. • The outputs and exports of China's steel industry will benefit from stringent environmental regulation. • The material efficiency of steel use will be improved in the long term while not sensitive to the stringency of environmental regulation. [ABSTRACT FROM AUTHOR]

Abstract China is under great pressure to reduce CO 2 emissions (CEs). Meanwhile, China's economy is more reliant on domestic consumption (particularly household consumption) than on exports. So, to achieve large-scale CEs' reduction for China, there is urgent need to study the CO 2 emissions from household consumption (CEs HC). Based on the environmentally extended Multiregional Input-Output model, this paper not only calculates both the direct CO 2 emissions from household consumption (DCEs-CH) and the indirect CO 2 emissions from household consumption （ICEs CH）at the provincial level in China, but also splits ICEs CH into domestic and foreign CEs. The findings of this paper are as follows: (1) between 2002 and 2012, CEs HC in China increased significantly, by 2.27 times, from 1306.17 Mt in 2002 to 2971.01 Mt in 2012. The CO 2 emissions from urban household consumption (CEs UHC) in China accounted for 75% of the total CEs HC in 2012. (2) The per capita CEs HC in China increased from 1.02 t/person in 2002 to 2.19 t/person in 2012. There was a prominent disparity in the total CEs and per capital CEs HC among the provinces in China. The per capita CEs HC were larger in provinces with a higher level of urbanization and higher per capita income. (3) The large-scale interprovincial transfer of ICEs caused by household consumption mainly occurred either within the Yangtze River Delta, the Pearl River Delta, and the Jing-Jin-Ji region or among these three regions. In addition, to service the household consumption, the energy-abundant provinces transferred a considerable amount of CEs to eastern coastal provinces. To achieve CEs' reduction, consumption-based strategies, such as lifestyle changes, should be required in parallel with strategies to reduce emission intensities on the producer side in China. Urban households should take more responsibility for the reduction of CEs in China. The interprovincial "Carbon leakage" should be taken into account when making policies for CEs' reduction in China. [ABSTRACT FROM AUTHOR]

Abstract Cities do play significant roles in tackling global environmental changes. Decoupling economic growth from environmental pressures is critical for global sustainable development, however, few studies pay attention to the decoupling analysis at city level. This paper conducts a comparative study of the decoupling performance of economic output from CO 2 emissions between Beijing and Shanghai, the top two cities in China. In this paper, the decoupling trends and the decoupling effects are explored from a sectoral perspective, by combining the Tapio decoupling elasticity and the logarithmic mean Divisia index (LMDI) model. The results show that Beijing and Shanghai both experienced weak decoupling in construction, expansive negative decoupling in transport, expansive coupling in trade, and weak decoupling in others over the period 2000–2015. Moreover, agriculture appeared strong decoupling in Beijing, and recessive decoupling in Shanghai; industry showed strong decoupling in Beijing, and weak decoupling in Shanghai. The decoupling effects showed different magnitudes and patterns in industrial sectors between Beijing and Shanghai. Overall, per-capita GDP and population growth inhibited the decoupling, while energy intensity, industrial share, energy mix accelerated the decoupling process. Highlights • The decoupling of sectoral economic output from carbon emissions in Beijing and Shanghai are investigated. • Beijing's industry enjoyed better decoupling performance than Shanghai's industry. • Transport should be put more emphasis in further decoupling efforts. • Energy intensity is crucial effect accelerating the decoupling process. [ABSTRACT FROM AUTHOR]

Abstract With the development of China's economy, the use of fossil energy has become more and more, resulting in increasing carbon emissions. CO 2 emissions have caused global warming, threatening humans and creatures on Earth. In order to effectively suppress the growth of carbon emissions, it is necessary to analyze the influencing factors of carbon emissions and apply them to predict carbon emissions. This paper presents sixteen potential influencing factors and uses grey relational analysis to identify the factors that have a strong correlation with carbon emissions. The principal component analysis (PCA) is used to extract the four principal components, which reduce the redundancy of the input data. The long short-term memory (LSTM) method is established to predict carbon emissions in China. We use back propagation neural network (BPNN) and Gaussian process regression (GPR) to compare LSTM method. The simulation results show that the prediction accuracy of carbon emissions based on LSTM is better than that of BPNN and GPR, indicating the effectiveness of PCA and LSTM in prediction of carbon emissions. Finally, this paper provides the theoretical basis for China to reduce carbon emissions by studying prediction of carbon emissions. Highlights • Grey correlation analysis is applied to identify factors associated with carbon emissions. • Principal components analysis is used to simplify input variables and obtain the main factors affecting carbon emissions. • The long short-term memory model is used for the first time to predict carbon emissions. • The direction of reducing carbon emissions in China is given by analyzing the prediction results. [ABSTRACT FROM AUTHOR]

Abstract High-tech minerals are essential for strategic emerging industries, and urban mines have become principal potential reservoirs of secondary high-tech mineral resources. In order to evaluate high-tech urban mines to understand their criticality and determine their potential and priority for high-tech minerals recovery, this paper develops a model with three dimensions - resource index, technology index, and environmental index. This model is applied to data from China, and a Monte Carlo simulation is conducted to estimate uncertainty. The results show that high-tech urban mines in China are divided into three clusters. The first cluster includes urban mines which have high scores in all three indices, they should be the top priority of collection and recycling. The second cluster covers high-tech urban mines with middle scores in resource index and technology index, and environmental index span from low to high. They are important second resources reservoirs of high-tech metals and should be paid significant attention. In the third cluster, high-tech urban mines have low scores in all three indices, they are not the focus of development but can't be ignored. Spent batteries, mobile phones and magnet motors are key reservoirs of high-tech metals. Furtherly, this paper presents that the evaluation model construction and evaluation results are deeply affected by consumption behavior, technology level, industrial development and the policy direction of the country. Based on the results, this paper proposes that urban mining should be treated as a national strategy to release the dual constraints of resources and environment, catalogue of key urban mining should be made, and to build a dynamic evaluation system and adjust the catalogue over time, and develop technologies for more effective and environment-friendly extraction material of urban mines. Graphical abstract Image 1 Highlights • A three-dimension model is developed to evaluate high-tech urban mines in China. • High-tech urban mines in China are divided into three clusters. • Spent batteries, mobile phones and magnet motors are key reservoirs of high-tech metals. • The evaluation is deeply affected by country's actual conditions, and industrial characteristics. [ABSTRACT FROM AUTHOR]

Abstract Natural resource endowment has a significant influence on manufacturing structure which in turn influences CO 2 emissions. This paper investigates the effect of the rationalization and upgrading of manufacturing structure on carbon dioxide emissions in China, based on the perspective of natural resource dependence. The results of the STIRPAT model on provincial panel data of the manufacturing sector from 2003 to 2014 show that manufacturing structure rationalization and upgrading will help curb CO 2 emissions, while such effects are restricted by a region's reliance on natural resources. The panel threshold model estimations further indicate that the greater the ratio of industrial output to GDP, the weaker the restricting effect of resource dependence on the emissions reduction of manufacturing structure. These findings reveal that the development strategies of manufacturing structural rationalization and upgrading that aim to reduce emissions depend on the level of a region's resource dependence and industrialization. Highlights • The STIRPAT model and panel threshold model are employed in this paper. • Manufacturing structure rationalization and upgrading will help to curb carbon dioxide emissions. • The emissions reduction effect of structural transformation is affected by resource dependence. • A higher degree of industrialization can weaken the restricting effect of resource dependence. [ABSTRACT FROM AUTHOR]

Abstract Paying heed to a surge of concern about the serious and continuous environmental degradation that is currently being witnessed in China, in this paper we investigate whether income distribution contributes to environmental deterioration. Environmental degradation can be linked not only to income growth, we argue, but also to increases in income inequality. The study calculated the Gini coefficient of 31 province using a data set of 403 city level data in mainland China and estimated the linkage between income distribution and environmental deterioration utilizing balanced data for 31 Chinese provinces during the period 1996–2015. First, the degree of environmental pollution was calculated by constructing a comprehensive index system, which was formulated using the entropy method, based on six environmental indicators. Then, a spatial panel regression model was also employed in order to estimate whether income inequality is likely to be a relevant factor in environmental deterioration in China. The estimation results showed that: using the index and spatial analysis techniques, significant spatial positive agglomeration were found existing between Chinese provinces in terms of their levels of environmental degradation; the influencing factors estimation results substantiated the existence of an invert U-shaped relation, lending support to the Environmental Kuznets curve theory; more importantly, the study found that income inequality played a significant role in preventing environmental degradation, suggesting that an appropriate level of income inequality over a delimited period is beneficial to improving environmental quality. It should, however, also be emphasized that optimizing the country's income distribution is remains an important long-term task for the Chinese government; other factors were found to exert different types and magnitudes of impacts on environmental pollution. Results showed that many factors—for instance, energy intensity, the share of secondary industry, population density, and foreign direct investment—contribute to environmental deterioration. Conversely, our findings also indicate that rising urbanization levels can have a positive effect on environmental quality. In addition, no clear evidence was found to suggest that local government expenditure is related to environmental degradation. Graphical abstract Image Highlights • The paper estimated the influence of income inequality on China's environmental degradation. • A spatial panel regression model was adopted in this study. • We calculated the Gini coefficient and a comprehensive environmental pollution index. • Income inequality in a delimited period is conducive to prevent environmental degradation. • Factors were found to exert different types and magnitudes of impacts on environmental pollution. [ABSTRACT FROM AUTHOR]

Abstract The renewable energies of China have been through a fast-developing process for about ten years. But they suffer from curtailment in recent years, especially for wind and photovoltaic. China started a new power market reform in 2015, featured by the establishment of electricity wholesale market. Whether the deregulated power market will help renewable energy penetration has become a hot topic. This paper aims to review the cost and marketability of renewable energy before and after power market reform in China so as to provide suggestions and inspirations for the field. A review approach based on literature classification and analysis of selected studies is utilized for argumentative review. The main work of this paper is as follows. 1) Generation and integration costs of renewable energy are analyzed through empirical data and comparison. 2) Current cost allocation of power generation in China is analyzed. 3) The marketability of renewable energy is discussed. 4) This paper comes with a conclusion that the major obstacles for renewable energy marketability lie in the non-independence of the system operator, the faultiness of the market mechanism (thus the distortion of cost allocation) and the history problem of the power structure. 5) A market-premium-like regime is suggested for relieving these obstacles. The conclusions and suggestions can be helpful for further research and policy making. Highlights • The power market deregulation reform in China is reviewed. • The power generation cost hierarchy and allocation in China are reviewed. • The renewable energy pricing mechanism in China is analyzed. • The obstacles of marketability of renewable energy in China are identified. • The feasibility of a market-premium-like regime in China is discussed. [ABSTRACT FROM AUTHOR]

Abstract China has encountered the environmental issues and energy pressures in the middle-income stage. Strengthening environmental regulation is a crucial measure to prevent environment deterioration and energy dilemma. This paper investigates the three types of environmental regulations on energy consumption using feasible generalized least squares method during 1997–2015 in direct and indirect path. The main conclusions are as follows. In the direct path, the economical and supervised types of environmental regulations have inhibited energy consumption whilst legal environmental regulation has no significant impact. As for indirect path, the "rebound effect" of energy is greater than the energy conservation generated by technological innovation, which is embodied as an inhibitory effect. The effects of environmental regulation display regional difference. The legal and supervised types of environmental regulations have significant "cost effect" and "rebound effect" on energy consumption in the entire samples. On the contrary, the economical environmental regulation shows the opposite sigh in eastern regions. The counterfactual simulation results show that the net effects of environmental regulations on energy consumption are negative, which is beneficial for relieving energy pressures. Based on the findings, this paper provides pertinent policy implications. Graphical abstract Image 1 Highlights • Environmental regulation can be divided into three types. • Environmental regulation can affect energy consumption in direct and indirect path. • Differernt types of environmental regulation have distinct impacts on energy consumption. • The effect of environmental regulation displays regional difference. • Strengthening environmental regulation can relieve energy pressure. [ABSTRACT FROM AUTHOR]

Abstract In arid and semiarid regions of northwest China, there are abundant shallow coal reserves throughout the region, yet during the mining process, the shallow water resources available are typically depleted due to the formation of fractures in the shallow subsurface. Water-preserved mining is the only option for coal mining in arid regions of northwest China. Based on the geological and hydrogeological conditions of the study area, this paper investigates the basic conditions and mechanisms of goaf water storage. A time series model for goaf water storage is proposed, along with a method for estimating the quantity of goaf water storage. Finally, hydrochemical characteristics of mine water and water quality characteristics after purification in the study area were analyzed. As indicated by the analysis results, after simple purification, the goaf water can meet industrial, ecological and agricultural water consumption standards. In the end, combined with current monitoring results of goaf water pressure and the status of goaf water utilization in the study area, this paper describes the quantity and the effect of utilizing goaf water storage. Goaf water storage can effectively alleviate the scarcity of local production and domestic water, and provides the most effective approach of large-scale water-preserved mining of shallow coal seams in the arid regions of northwest China. [ABSTRACT FROM AUTHOR]

This paper created an Input-Occupancy-Output (IOO) table that was integrated with several alternative waste treatment management modes. Based on this table, a Ghosh price model was developed to evaluate the price changes in each sector compared with their traditional prices for the direct and indirect impacts of the costs of waste treatment management modes. The model was applied to the waste water treatment case in China. The data were sourced from the China Statistical Bureau and a survey made by Tan et al. (2015). In each waste treatment management mode, the price change of each sector was evaluated. The results revealed that different waste treatment management modes generated different ranks for the price changes by sector. There are 22 sectors whose prices increase are mainly caused by other sectors' added waste water treatment costs. An optimal combination of two waste treatment management modes for 42 sectors generates the minimum price increase for all industries. To limit the waste water discharged in China, one possible intervention would be to increase the fine imposed for unit waste water discharged, setting it at a higher level than the unit waste water discharge fee and its treatment cost. Furthermore, it is suggested that the waste water treatment cost needs to be reasonably incorporated in the products’ prices. The model proposed in this paper will be particularly appropriate to evaluate these price increases and their impacts. [ABSTRACT FROM AUTHOR]

Abstract To alleviate the high risks to oil supply caused by high dependency on oil imports, China is actively seeking alternative energy sources to reduce its imported oil (IO). Coal-to-liquid (CTL) is regarded as an option in China. However, few analyses have examined the net energy impact of substituting IO with CTL and determined how effective the substitution would be. Energy return on investment (EROI) analysis, an important index to characterise the viability of a natural resource from an energy standpoint, can provide insights into these issues. This paper first introduces new methods to calculate the EROIs between CTL and IO from a life-cycle perspective. Then, based on the EROI values, a new, simple method is provided to calculate the net energy change resulting from the substitution of IO with CTL. The results show that without considering the environmental inputs, the mean EROI of CTL with/without internal energy inputs is 0.29/1.44, and that of IO is approximately 5.60. When environmental inputs are considered, these values decrease to 0.27/1.09 and 5.07, respectively. In general, IO has a better net energy return than CTL. Moreover, substituting 1 MJ IO with CTL would lead to a net energy loss of 0.3–4.6 MJ. The above results suggest that China should be more cautious in developing the coal liquefaction industry from a net energy perspective. Highlights • New methods are provided to estimate the EROI of IO and CTL from a life-cycle perspective. • This paper considers the impact of the energy inputs to control GHG emissions on EROI. • The EROIs of IO and CTL are about 0.86–1.79 and 4.28–6.50 respectively. • Substituting 1 MJ IO with CTL would lead to a net energy loss of 0.3–4.6 MJ. [ABSTRACT FROM AUTHOR]

Policy ideas associated with the urban minerals industry in China have shifted focus from environmental protection to industrial development in recent years. A key factor influencing the development of this industry is whether the policy system can adapt to changing policy ideas. This paper analyzes a series of policies on urban minerals issued by the central government and related departments and ministries from 1987 to 2017. Using the content analysis method, which is a quantitative methodology, the paper proposes a framework of policy tools and objects of policy intervention to analyze the evolutionary characteristics and problems associated with the development of the urban minerals industry. The research results show that the policy system of urban minerals in China has changed from the germination stage, in which urban minerals policies were embedded in environmental protection policies; to an introduction stage, in which the urban minerals policy system initially took shape; to a development stage, in which the effects of urban minerals policies have stabilized. The changing trend of urban minerals policies can be summarized as follows. First, the National Development and Reform Commission (NDRC) gradually became the dominant policymaker. Second, the policy tools were enriched via restructuring. Third, the objects of policy intervention were continually extended to the whole industry chain. Although the policy system of urban minerals in China has promoted industrial development, certain problems remain to be resolved, such as the conflicting policies from different departments, the unreasonable combination of policy tools and improper object of policy intervention. To this end, we have proposed corresponding countermeasures and suggestions to better improve the development of the urban minerals industry. [ABSTRACT FROM AUTHOR]

Promoting industrial digitalization and deepening regional collaborative innovation is essential for achieving urban green and sustainable development. This paper constructs a differential game model based on theoretical analysis and reveals the influence mechanism of industrial digitalization and regional collaborative innovation on urban green development efficiency (GDE). After that, this paper uses the entropy method, Super-SBM model, and improved gravity model to measure the level of industrial digitalization, urban GDE, and regional collaborative innovation, respectively. Then, this paper constructs the fixed-effects model, SDM model, moderating-effects model, and threshold model, then uses the panel data of the Beijing-Tianjin-Hebei (BTH) urban agglomeration during 2011–2020 for empirical testing. The results show that: (1) industrial digitalization significantly improves urban GDE. (2) Overall, 2011–2015 is the rapid development period of BTH industry digitalization, and 2015–2020 is its stable development period. However, there are apparent spatial differences and imbalances. (3) Industrial digitalization has a significant spatial spillover effect that can enhance local and surrounding cities' GDE. (4) Regional collaborative innovation can directly enhance urban GDE, and has a positive moderating effect on industrial digitalization to enhance urban GDE. (5) The regional collaborative innovation has two thresholds of 3.9851 and 6.6184. With the collaborative innovation level improving, the main effect intensity steadily increases. [ABSTRACT FROM AUTHOR]

A fair and effective allocation of carbon quotas is crucial for China to achieve its "Double Carbon" goals and the effective operation of its carbon trading market. By constructing a differential game model, this study explored the effects of the technology spillovers and incremental costs of carbon transfers on the allocation of carbon quotas under centralised and decentralised decision-making scenarios with the purpose of maximizing social welfare. This paper proposes a cost-sharing contract to coordinate a supply chain for the loss of social welfare under decentralised decision-making. The results show that the effects of spillovers and incremental costs on carbon quota allocation depend upon the enterprises' abatement costs. The suppliers' carbon quotas are negatively correlated with the spillover effects. The incremental cost effects will be more pronounced for suppliers when their abatement costs are high and they could obtain more carbon quotas accordingly. When the manufacturer's abatement costs are low (high), its carbon quotas decrease (increase) with the spillover effects but increase (decrease) with the incremental costs. The cost-sharing contract achieves Pareto improvements based on improved social welfare and increased carbon quotas for both the manufacturer and supplier. Given the effects of carbon transfer on enterprises with different abatement costs, this paper can provide the government with a reference for designing an allocation mechanism for carbon quotas. [Display omitted] [ABSTRACT FROM AUTHOR]

Second emission trading market is not active in China so far, and the reason mainly lies in that enterprises do not have strong initiative for transaction. Thus it's meaningful to study related guiding mechanisms from the perspective of enterprises behavior. In this paper, an evolutionary game model and a small-world network model considering stock heterogeneity are constructed based on four given guiding mechanisms, and a simulation study is conducted through China Zhejiang emission trading market. The result shows that: (1) the optimal guiding mechanism is dynamic and changes from reward-punishment for both enterprises with surplus stock and enterprises with insufficient stock to reward-punishment for enterprises with insufficient stock when trading preferential profit coefficient increases to 1. (2) when penalty coefficient changes, the optimal guiding mechanism is the reward-punishment for both enterprises with surplus stock and enterprises with insufficient stock and keeps unchanged. (3) the enterprises with insufficient stock are more sensitive to penalty coefficient and trading preferential profit coefficient, especially to the latter, so it's better to stimulate the emission rights purchasing side and formulate positive reinforcement methods. The study of this paper can provide decision-making suggestions for Chinese government to stimulate the activity of second emission trading market. [Display omitted] • Four guiding mechanisms are given based on implementation objects. • An evolutionary game model is constructed. • A complex network model is constructed considering stock heterogeneity. • The optimal guiding mechanism is simulated and dynamically analyzed. • The policy recommendations are highlighted. [ABSTRACT FROM AUTHOR]

The failure of the global food system to produce food in a sustainable way needs to change urgently, and a solid push to harmonize low-carbon food production with stable supply security is the right direction in which modern agriculture must evolve, but it is more difficult for large food-producing countries, and finding the right practices or systems to help policymakers or producers address this dilemma is critical. This requires political will, increased financing and top-level design. Digital inclusive finance (DIFI) embodies the financial concept of a community of human destiny, and it is worth examining whether this more inclusive and comprehensive financial service can shoulder the "responsibility" of "ensuring food security and reducing carbon emissions" in agriculture. This paper takes China's grain production system as an example, measures the coordinated development level of food production ensuring supply and reducing carbon emissions, and then analyzes the overall and regional characteristics of it. It is found that the coordinated development trend of China's food production ensuring supply and reducing carbon emissions is relatively stable during 2011–2020, fluctuating slightly above and below 0.9, and the central region has the highest level of coordinated development. The empirical results show that DIFI has led to a 4.3 percentage point increase in the level of coordinated development of food production ensuring supply and reducing carbon emissions during the decade, showing a stronger spatial spillover effect on neighboring regions than the local effect. At the same time, in the research of regional division in China, the impact of DIFI on the level of coordinated development of food production ensuring supply and reducing carbon emissions varies across regions, with typical uneven characteristics, and the promotion effect is more significant in the central and northern regions of China. Overall, this paper provides a simple tool for policy makers or producers to understand the balance between guaranteed output and low-carbon development of agricultural production activities. This paper will provide a methodological basis for assessing and standardizing low-carbon agricultural practices, innovating financial development models and systems, and promoting sustainable agriculture. [Display omitted] • Measuring coordinated development level of ensuring food supply and low-carbon. • Digital inclusive finance had increased the coordinated development level by 4.3%. • Digital inclusive finance also had a significant spatial spillover effect. • The role of digital inclusive finance showed a typical non-equilibrium feature. • The study's results could help to sustainable agriculture in agricultural country. [ABSTRACT FROM AUTHOR]

Clean energy plays an essential role in responding to environmental crises. Accurate forecasting of clean energy power generation can provide necessary references for the formulation of energy policy. This paper proposes a novel fractional discrete grey model with a dynamic time delay function (DTDFF-DGM (1,1)) to forecast clean energy power generation. This model introduces the fractional accumulation operator and the dynamic time-delay function into the discrete grey model, which ensures the priority of new information in the original data and improves the model's adaptability to different sample data. The optimal parameters of the model are calculated by the dynamic linkage between the fitting error and the test error, which effectively avoids the overfitting problem. Empirical studies have proved that the model has better prediction accuracy compared to other methods. Finally, the proposed model is employed to forecast clean energy power generation in China. The results show that from 2020 to 2025, the overall growth rate of hydropower, wind power and nuclear power in China will be 9.27%, 119.61% and 36.38%, respectively. Based on the discussion of the forecast results, relevant policy suggestions were made. This paper realizes the transformation from a static model to a dynamic model in methodology and promotes the sustainable development of clean energy power generation in application. [Display omitted] • A novel fractional discrete grey model is established. • The model is the general paradigm of the existing six discrete grey models. • The jump error is avoided in the transition from discrete to continuous. • The dynamic time-delay function is introduced. • China's clean energy power generation is effectively predicted by the model. [ABSTRACT FROM AUTHOR]

The production and sales of electric vehicles in China are continuously increasing, and a massive wave of scrap batteries is about to emerge. However, there are many challenges in the power battery recycling, such as a disorganized recycling system, a lack of standards, and low efficiency. In addition, the power battery recycling supply chain faces issues such as a lack of transparency, inadequate data management, low trustworthiness, and counterfeit products. Therefore, it's crucial to establish an efficient and sustainable power battery supply chain recycling system. Blockchain technology can provide solutions in decentralized data management, privacy protection, and anti-counterfeiting traceability. It addresses existing problems and improves the Power Batteries Reverse Supply Chain (PBRSC) ecosystem. Thus, this paper proposes a blockchain-based PBRSC management integration framework. Firstly, a four-layer blockchain power battery recycling platform is designed. Secondly, based on the proposed PBRSC framework, this paper studies three key component technologies: double-chain structure and its storage mechanism, information tracing module, and smart contract enabled battery trading management. Then, the validity and feasibility of the double-chain structure was demonstrated experimentally. Finally, the above architecture and key technologies are implemented in the system, the main functional modules are displayed on the interface, and the effectiveness of the framework is explained in cooperation with related enterprises. [ABSTRACT FROM AUTHOR]

Green credit policy (GCP) is a measure the government takes to protect the environment, which will impact firms' behavior. Using a Chinese GCP launched in 2012 as a credit shock and the data of Chinese listed firms from 2007 to 2018, this paper investigates the impact of this credit policy on corporate charitable donations. This paper employs the difference-in-differences method, defining heavy-polluting firms as the treatment group and non-heavy-polluting firms as the control group. Our results show that the GCP significantly improves the charitable donations of heavy-polluting firms. Mechanism analysis indicates that GCP impacts charitable donations through financial constraints and environmental regulatory pressure. Heterogeneity analysis suggests that this effect is stronger for non-state-owned enterprises and firms with weaker external monitoring. Our findings enrich the research on the economic consequences of green credit policy and have practical implications for regulators and policymakers. [ABSTRACT FROM AUTHOR]

China facing the challenge of coordinated development of "ecology, economy, and well-being". Scholars have conducted some research on the relationship between enviromental regulation and employment, but there is less research on the role of clean technology innovation in the employment effect of environmental regulation, which is the purpose of this paper. Using the panel data of 22 industrial sectors in China, the paper uses the number of clean technology patents to measure the level of clean technology innovation, and examines the moderating effect of clean technology innovation in the employment effect of environmental regulations. The results show that: (1) With the gradual improvement of environmental regulation, the impact of environmental regulation on employment presents the characteristics of inhibition first and then promotion. (2) Clean technology innovation has a moderating effect on the employment effect of environmental regulation. It should encourage the green upgrading of traditional technologies, support the development and optimization of private enterprises in various industries, so as to promote enterprises to effectively reduce pollution emissions and create jobs through green technology upgrading at the initial stage. [Display omitted] [ABSTRACT FROM AUTHOR]

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

China has implemented a robust regime of livestock environmental regulations (LERs) to control pollution caused by livestock production. However, little is known about the effectiveness of LERs on the livestock industry chain. This paper explores the vertical integration (VI) of the livestock industry chain under the constraints of LERs during 2008–2019. Based on the financial statements of Chinese-listed livestock enterprises, the degree of VI during 2008–2019 is calculated by the input-output table (2018). Then, this paper delves into the treatment effects of LERs on VI by using the difference-in-differences (DID) model based on taking the LERs as a quasi-natural experiment. The findings reveal that (1) LERs can significantly promote the VI of the livestock industry chain and the forward integration of enterprises. This conclusion is still robust in multiple cases. (2) Mechanism analysis shows that LERs cause industrial structure adjustment and production layout relocation, accelerate the expansion speed and scale of capital in the breeding sector, and increase the transaction cost of breeding enterprises. (3) LERs contribute to a 48.45% increase in capital intensity and a 3.05% increase in the selling expense ratio of the breeding enterprises. Finally, this paper provides pertinent policy implications. • The degree of vertical integration was manually compiled by using input-output table. • The treatment effect was estimated by taking regulations as a quasi-natural trial. • The transaction cost and capital deepening of livestock enterprises play key roles. • We propose a layout to balance production and consumption by regional complementary. [ABSTRACT FROM AUTHOR]

Carbon emission policy aims to restrict carbon emissions from energy-intensive companies. It encourages target companies to take green innovation but brings fulfillment pressure. Policy prospects for a low-carbon economy are widely discussed in current studies while insufficient attention has been paid to the effect of the policy on the operating activities of target companies. Using the data of Chinese A-share listed companies from 2007 to 2020, this paper explores the effect of carbon emission policy on the financial performance of target companies. The main empirical results prove the significant positive effect of the policy on the financial performance of target companies and reject the interference of earnings management and survivor bias. Further analysis indicates that target companies significantly reduce the selling, general and administrative (SG&A) expenses and non-operating expenses. The trade of carbon quotas between target companies is allowed and it is regarded as non-operating activity. Results of non-operating revenues and expenses prove that target companies tend to actively reduce carbon emissions but the action does not exceed the policy expectation. The increasing efficiency of asset utilization represents that target companies have taken relevant measures to deal with overcapacity. This paper confirms the positive policy responses of target companies. Policy implications are proposed from the perspective of coverage expansion and market incentive mechanisms to realize the full potential of target companies for carbon emission reduction. [ABSTRACT FROM AUTHOR]

Policy has been the driving force behind the rapid development of China's new energy vehicle (NEV) industry. However, the policy network that supports NEV development has been underexplored. This paper explores NEV as an innovative niche for sustainable transition and investigates the evolutionary mechanism of its policy network by combining insights from policy network, strategic niche management and technology innovation system (TIS) theories. Operationally, this paper adopted a social network analysis method to study the NEV policy network in various niche development stages consisting of 377 NEV policy documents formulated by government agencies between 2000 and 2021. Results show the NEV policy network evolves towards bigger, newer actors and is more heterogeneous in creating joint efforts in policymaking that promotes niche development and facilitates a transition to a market niche. Specifically, the policy network expands continually, and network density reaches the maximum of 0.635 at the end of the technological niche. Six agencies are identified as dominators in NEV policymaking. Collaboration on NEV policymaking exhibits obvious organisational heterogeneity, especially in the market niche with an E-I value of 0.576. This study enhances understanding of the evolutionary patterns of policy network and its function on supporting TIS development for immaturely sustainable technologies. The findings also provide important insights into the NEV policymaking process. [Display omitted] • The policy network of China's new energy vehicle continually expanded as the niche evolved. • Several government agencies are identified as dominators that lead policymaking. • Collaboration on policymaking has evolved towards greater heterogeneity. • Network evolution pattern differs significantly in different stages of the technological niche. • Network evolution pattern tends to be stable when it comes to the market niche stage. [ABSTRACT FROM AUTHOR]

The five major power generation corporations dominate the power industry in China, and play vital roles in China's carbon trading scheme. Under this circumstance, this paper studies the allocation of carbon emission quotas to China's five major power generation corporations based on the fairness and efficiency principles, which proves the primary prerequisite for setting up the national carbon market. Specifically, a bi-level programming model is developed to optimally allocate carbon emission quotas to the corporations, and then a zero sum gains data envelopment analysis (ZSG-DEA) model is adopted to evaluate the efficiency of the allocation so as to adjust towards the optimal solution. The results indicate that power generation has significantly positive influence on the allocation of carbon emission quotas. Moreover, the difference between the sum of optimal carbon emissions and the sum of carbon quotas allocated is 1.431 billion tons, which implies that the emission reduction potential of the five major power generation corporations is tremendous. Finally, the bi-level model in this paper can well capture the context of China's power industry and provide effective results for the allocation of carbon quotas. [ABSTRACT FROM AUTHOR]

Under the context that entrepreneurial risk in clean energy industry has become increasingly complex, government subsidies are helpful to guide and promote the entrepreneurial companies' survival and development. This paper explored the roles of government subsidies, more specifically, in forms of government subsidies beforehand and government subsidies afterwards on the relationship between R&D and entrepreneurial companies' growth, particularly in the clean energy industry. To delve deeper into the roles, this paper analysed data from the 2013 and 2014 annual reports of 58 listed companies in clean energy industries in China. By using a moderating effect model, this paper derived following conclusions: (1) R&D investment does not have a lag effect on entrepreneurial companies' growth; (2) Government subsidies beforehand have negative moderating effects on the relationship between R&D investment and entrepreneurial companies' growth; (3) Government subsidies afterwards have positive moderating effects on the relationship between R&D investment and entrepreneurial companies' growth. This paper helped to understand the difference between the functions of government subsidies beforehand and government subsidies afterwards. To some extent, the results can revise prior studies about the function of government subsidies to influence the relationship between R&D and entrepreneurial companies’ growth. The results will also be helpful for the government to evaluate the performance of government subsidies and design appropriate subsidies strategies. [ABSTRACT FROM AUTHOR]

This paper primarily studies the air quality in China's cities during the urbanization stage. Using a cross-sectional data of 282 cities, we discuss the influencing factors and the existence of the Kuznets Curve for three air pollutants based on the EKC (Environmental Kuznets Curve) theory and the BMA (Bayesian Model Average) method. The results show that the concentration of SO 2 and PM 10 presents the characteristics of an inverse-U shape. The urbanization process has a significant and negative effect on air pollutant concentration, which means that cities with higher urbanization rate tends to have lower air pollutant concentration. Population density, possession of civil motor vehicles, the proportion of secondary industry, and annual average temperature are the main influencing factors of air pollution. Based on these results, this paper suggests that China should speed up the “new” type urbanization process, constantly optimize the industrial structure, and promote the harmonious development of the economy and environment. [ABSTRACT FROM AUTHOR]

Most empirical researches in behavioral finance have found that the air pollution can affect the stock market in the developed world, while a few works show some different results in China. This paper deeply discusses the reasons for the difference of air pollution effect, and attributes it to the intensity of public environmental awareness. This paper selects some important environmental events which can enhance the public environmental awareness as samples, to investigate the influence of public environmental awareness on the air pollution effect. The results firstly show that the air pollution effect in Chinese stock market is not significant during a long-term sample period. Secondly, the empirical findings support that these events have significant impacts on the air pollution effect in Chinese stock market. Finally, this paper provides direct evidence on that the air pollution effect has a significant negative change after these events, which is consistent with the expected impact of the air pollution effect's mechanism. This research extends the behavioral financial issue of air pollution effect and provides the empirical evidence for the public environmental awareness's obstacle to the air pollution effect. [ABSTRACT FROM AUTHOR]

Due to the ever-increasing quantity of produced and sold automobiles in China, many side effects such as resource depletion, energy shortages and air pollution have emerged. Remanufacturing, as the highest form of the recycling economy, has been promoted by the Chinese government as a major measure to save resources and energy. The remanufactured products, however, get very low market recognition from Chinese consumers. Thus, understanding how to cultivate consumers potential behavior of purchasing remanufactured products is the first step and also very important for developing the remanufacturing industry. This paper, focusing on heavy truck engines due to their short life expectancy and repair frequency, aims to identify the factors influencing remanufactured heavy truck engine (RHTE) potential purchase and analyze the relationship among those factors and potential purchasing behavior. Based on 301 questionnaires from Chinese heavy truck drivers, this paper develops a conceptual model to hypothesize how the influencing factors affect RHTE potential purchasing behavior. Hierarchical regression results show that individual factors (including product knowledge, product trust and environmental values) mediate the relationship between environmental factors (including product attribute and advertisement) and RHTE purchasing intention. Contextual factors (including incentive policy and purchasing convenience) moderate the relationship between RHTE purchasing intention and potential purchasing behavior. Our results indicate that individual factors are essential in cultivating RHTE purchasing intention and environmental factors are helpful for improving individual factors. Contextual factors can motivate the transformation from RHTE purchasing intention to potential purchasing behavior. [ABSTRACT FROM AUTHOR]

This paper measured province-level water resource efficiencies in China from both static and dynamic perspectives, applying the undesirable-output-based Malmquist-Luenberger productivity index to panel data of 30 provinces in China from 2006 to 2015. Then, the paper analyzed factors that affect water resource efficiency by using a panel Tobit model. Research results showed significant lack of water resource efficiency with notable differences among provinces; water resource efficiency was somehow related to the level of economic development. Technical improvement was an important factor in water resource efficiency. The level of economic development had a non-linear influence on water resource efficiency. Industrial structure upgrading and population expansion could significantly improve water resource efficiency while the effects of water supply and per capita educational level were insignificant. [ABSTRACT FROM AUTHOR]

The Computable General Equilibrium (CGE) model could capture the full range of interaction and feedback effects among different agents in the economic system. This study analyzes the economic impacts of differentiated carbon reduction targets by using a two-region CGE model in Tianjin Municipal City of China (hereafter “Tianjin”). Firstly, based on a business-as-usual (BaU) scenario and seven proposed carbon reduction scenarios, this paper quantifies the macroeconomic impacts of different carbon reduction targets in both regions, especially the carbon reduction costs and industrial output. Furthermore, several typical industries in Tianjin are chosen to explore how their competitiveness is affected under different carbon allocation scenarios. The results show that compared with the BaU scenario, the Gross Domestic Product (GDP) in Tianjin would achieve the highest growth rate if the carbon intensity reduction target is set at 65% in Tianjin whereas 55% in the rest of China (ROC). Meanwhile, residents’ welfare loss in Tianjin will be the largest if carbon intensity reduction target in 2030 is set to be 65% in Tianjin and 75% in ROC. Also, the local pillar industries (including electronic sector and the metal smelting sector) would benefit from the carbon reduction policy, while the paper sector would be negatively influenced. Policy recommendations are raised, in which several factors should be fully considered, including development stages, resource endowments, technical levels and local environmental carrying capacity. [ABSTRACT FROM AUTHOR]