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The contradiction between industrial agglomeration and energy constrains the development of cities. Government competition can affect the flow of factors for industrial agglomeration. Based on the data of 274 cities in China from 2005 to 2020, this paper constructs improved non-radial directional distance function (NDDF) and dynamic spatial durbin model (SDM). The paper further uses a threshold effect model and a mediating effects model to examines the impact and spillover effects of local government competition (LGC), new energy industry clustering and their integration on ecological total factor energy efficiency (ETFEE) from the perspective of the role of knowledge. To solve the problem of endogeneity, this paper uses the presence or absence of highway entrances and exits in cities in 2004 as an instrumental variable. The study found that new energy industry agglomeration and LGC can promote ETFEE in the short term, but it will inhibit ETFEE in the long term. New energy industry agglomeration affects local ETFEE through two types of mediating effects: narrowing knowledge breadth and widening knowledge distance between cities. At the same time, new energy industry agglomeration and LGC has a significant spatial spillover effect on urban ETFEE in the short term. Areas with high urban ETFEE can promote the improvement of ETFEE in neighbouring areas. However, from the perspective of regional differences, it finds that the concentration of new energy industries and LGC have different effects on ETFEE. There is a significant impact in the eastern region, but not in the central and western regions. Finally, the paper gives constructive advice for the adaptation of the knowledge structure and the improvement of energy efficiency through the national and governmental levels. • First examination of local government competition, new energy industry agglomeration and energy efficiency from a perspective on the role of knowledge. • The relationships among new energy industry agglomeration, local government competition and energy efficiency are all inverted U-shape. • The level of government competition above 2.097 will inhibit the increase of ETFEE. [ABSTRACT FROM AUTHOR]

Digital transformation has the potential to significantly impact household energy consumption (HEC) by promoting the adoption of energy-efficient technologies. This paper utilizes the time-varying Difference-in-Differences (DID) model to evaluate the causal effect of digital transformation on HEC within China's households. We find that HEC is positively impacted by digital transformation, as embodied by the "Broadband China" strategy; and the results remain reliable when many robustness tests are taken into account. Specifically, digital transformation has the potential to indirectly increase HEC by consumption upgrade and internet development mechanisms. The heterogeneity analysis reveals that the impact of digital transformation on HEC varies significantly across different household and regional. High-income, low skilled, rural areas, as well as households in areas with higher levels of development and marketization, are more likely to be affected by the digital revolution in production and consumption, which will inevitably lead to an increase in HEC. These insights are crucial for developing effective strategies to reduce HEC and promote sustainable development. [Display omitted] • Assesses digital transformation's impact on China's household energy use. • Identifies significant increase in energy consumption due to digitalization. • Examines mechanisms of how digital transformation affects energy use. • Provides insights for harmonizing digital and green transformations. [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]

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]

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]

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]

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]

Green total factor productivity is a vital measure of sustainable progress, holding immense implications for attaining both economic growth and environmental preservation in a mutually beneficial manner. Focusing on green total factor productivity, this paper examines its nexus with low-carbon energy technology using the Instrumental Variable Generalized Method of Moments (IV-GMM) model, based on a panel dataset in China during 2005–2018. This paper also examines the asymmetric impact of low-carbon energy technology on green total factor productivity. In addition, the moderating and mediating effects are checked. The main findings are that (1) low-carbon energy technology is a promoting factor for green total factor productivity. (2) Low-carbon energy technology exerts a more prominent marginal impact on green total factor productivity when green total factor productivity is at higher quantile levels. (3) Renewable energy generation not only drives green total factor productivity directly, but also further increases the promotion effect of low-carbon energy technology on green total factor productivity, showing a positive moderating role. (4) Energy structure transition and industrial structure transition are two internal impact mechanisms between low-carbon energy technology and green total factor productivity. These findings suggest that the government can promote green total factor productivity development by developing policies related to low-carbon energy technology and fully releasing the effects of technology on sustainable development. • This paper assesses the level of low-carbon energy technology (LCET) in China. • This paper examines the effect of LCET on green total factor productivity (GTFP). • LCET plays a significant role in enhancing GTFP. • Renewable energy generation positively moderates the nexus between LCET and GTFP. • Energy structure transition and industrial structure transition are two mechanisms. [ABSTRACT FROM AUTHOR]

The difficulty of the sulfur dioxide (SO 2) pollution control task has deepened step by step in recent years, while the marginal cost of environmental protection in China has also been higher. Therefore, it is necessary to study the main impact factors of China's industrial SO 2 pollution. Based on China's Industrial Environmental Statistics Database from 2004 to 2013, this paper extends the Index Decomposition Analysis (IDA) with firm entry and exit to conduct a micro-level decomposition study. The industrial SO 2 emission in China is decomposed into scale effect, composition effect, firm growth effect, and firm selection effect. Also, we use the Dagum Gini coefficient to analyze the spatial differences of firm growth effect and selection effect between the eastern, central, and western regions in China. This paper finds that the main contribution of industrial SO 2 emission control in China is the firm growth effect, which was −103% between 2004 and 2013. And the second largest contribution term is the firm selection effect, which is −18%, while the composition effect is −15%. In terms of temporal patterns, the size of the firm growth effect shrinks as time grows, and the composition effect changes from negative to positive after 2009. For spatial difference analysis, the Dagum Gini coefficient of technique effect and firm growth effect between different regions have become smaller and smaller over time, while the spatial differences of firm selection effect between regions remain unchanged. [ABSTRACT FROM AUTHOR]

This paper aims to study the significance of China's Industrial Structure Rationalization (ISR) in reducing carbon emissions. To this end, this study uses panel data from 30 Chinese province from 2000 to 2019 to measure the Industrial Structure Rationalization of each province by calculating the Thiel index, base on which a nonlinear autoregressive lagged distribution (NARDL-PMG) model is established to explore the impacts of industrial structure rationalization on carbon emissions. The results show that: (1) There still exist significant regional differences between Eastern and Central-Western regions in industrial structure as illustrated by the ISR index. The industrial structure in Eastern region is more rational; (2) In the long run, the carbon emission in China will drop when the industrial structure becomes more rational; (3) However, in the short run, the carbon emission in China will increase when the industrial structure becomes more rational. Besides the findings above, the major difference between this paper and the extant researches is that this paper pays attention to the relationship between industrial structure rationalization and environmental quality by investigating the asymmetric influences of industrial structure rationalization index's positive and negative shocks on carbon emission, which lays solid foundations for government aiming to set more detailed policies. • Focus on the impact of rationalization of industrial structure on CO2 emissions. • Focused on the linear relationship between industrial structure and carbon emissions. • Attempts to analyze three regional pairs from the East, Central and West regions. • Provide a reference for developing countries to achieve sustainable development. [ABSTRACT FROM AUTHOR]

This paper has observed pivotal changes in innovative frameworks at the intersection of the digital revolution and sustainable initiatives. Within Industry 4.0, the fusion between intelligent manufacturing and green innovation has become a central driver for sustainability. Integrating these two pivotal forces to harness their collective efficiency is crucial. However, current literature offers limited insights into their combined impact, and the direction of their evolving trends still needs to be defined. Considering this, the research elucidates the core concepts and traits of digital-green fusion (DGF) within regional advanced manufacturing (RAMIDGF). Moreover, this research proposes a double-helix fusion mechanism model. Utilizing data from the advanced manufacturing sectors in six key Chinese urban clusters, this paper adopts a comprehensive analytical toolkit that includes the Coupling Modified Model, Kernel Density Estimation, Markov Chain algorithms, and the Dagum Gini Coefficient for trend analysis. The findings indicate that between 2009 and 2021, RAMIDGF exhibited a trend of initial growth followed by a decline, showing a strong correlation with per capita GDP (RGDP). The principal source of variation in RAMIDGF stems from differences between urban agglomerations, with the Yangtze River Delta and the Beijing-Tianjin-Hebei clusters exhibiting transitional behavior and a 'ladder-type trend' in RAMIDGF. As metropolitan clusters become more economically integrated, the probability of transitional behavior in RAMIDGF heightens. However, achieving elevated leapfrog development proves challenging, with an inherent risk of decline. Spatial spillover implications, agglomeration characteristics, and club convergence tendencies mark the RAMIDGF process. These findings expand upon new paradigms for regional sustainable development, offering novel avenues for realizing high-quality growth. [Display omitted] • The conceptual connotation and characteristics of RAMIDGF are proposed. • The double helix fusion model is constructed to analysis the fusion mechanism. • The RAMIDGF level of urban agglomerations is evaluated. • The trend and characteristics of RAMIDGF in urban agglomerations are demonstrated. [ABSTRACT FROM AUTHOR]

The urgent need to address climate change, driven by the increasing concentrations of greenhouse gases, has made it imperative for the world to focus on enhancing carbon emission mitigation and carbon utilization. Consequently, carbon-negative technologies have garnered significant attention, such as Carbon Capture, Utilization, and Storage (CCUS). In order to achieve the circular utilization of carbon and improve the economic viability of conventional carbon-negative technologies, this paper proposes the innovative concept of Carbon Capture, Circular Utilization, and Sequestration (CCCUS). This multifunctional carbon-negative technology couples underground biomethanation of carbon dioxide and hydrogen-rich industrial by-product gases with geothermal energy production. CCCUS also offers several additional functions, such as renewable natural gas storage, natural gas displacement, and carbon dioxide geological sequestration. Furthermore, a preliminary assessment of the techno-economic feasibility of CCCUS is undertaken. A numerical case study, conducted using the XGS gas storage in the Sichuan Basin, China, unveiled that over a 425-day period, the conversion ratio of carbon dioxide to methane in the working gas can achieve 98.9%. Moreover, the net present value (NPV) of CCCUS over a 30-year period is estimated to be approximately 4.67 × 108 CNY under the base scenario. These findings, along with field monitoring and laboratory experiments, preliminarily present evidence supporting the potential techno-economic feasibility of CCCUS. This paper offers a fresh perspective on the development of the circular carbon economy. [ABSTRACT FROM AUTHOR]

Under the background of high-quality development, the e-commerce industry needs to seek more comprehensive development, and the logistics industry should not only maintain higher efficiency, but also meet the requirements of green and low-carbon transportation. This study aims to investigate the link between the logistic density and the proportion of e-commerce transaction scale. There are few studies on how logistics density affects the development of e-commerce quantitatively. In order to solve this gap, this study establishes an impact model of high-quality growth of e-commerce, and based on Solow production model, constructs a calculation method of logistics density, and analyzes the impact mechanism of logistics density on the scale ratio of e-commerce transactions. Using the bidirectional fixed effect model, this paper makes an empirical analysis of the panel data of 31 provinces consisting of 248 observations and autonomous regions in China from 2014 to 2020. The results show that logistic density has a positive and significant impact on the growth of e-commerce, thus promoting the optimization of economic structure. The acceleration of logistics density decreases the expansion of the ecommerce. Finally, there are obvious regional differences between the development of e-commerce and logistics infrastructure in China. Finally, based on the empirical result, this paper puts forward recommendations for government and companies. [ABSTRACT FROM AUTHOR]

Manufacturing is both an essential pillar of China's economy and a significant source of environmental pollution, and there is an urgent need for the manufacturing industry to use green innovation to accelerate its goal of sustainable development. From the intellectual property protection (IPP) perspective, this paper uses Chinese manufacturing and its 26 sub-sectors as a sample from 2003 to 2018, examining the impact of two-way foreign direct investment (FDI) coordinated development in manufacturing green innovation capability. The empirical results suggest that two-way FDI coordinated development enhances manufacturing green innovation, and this finding still holds after endogeneity and robustness tests. Under the influence of IPP, the relationship between two-way FDI coordinated development and manufacturing green innovation capability is nonlinear. Under the influence of macroscopic, mesoscopic, and microscopic dimensions IPP, the effect of two-way FDI coordinated development on manufacturing green innovation capability is U, Steps, and N shaped respectively. This paper's findings can provide empirical evidence for the government to formulate industrial development strategies and for manufacturing enterprises to improve their green innovation capabilities to achieve sustainable development. [ABSTRACT FROM AUTHOR]

Plastic pollution is currently one of the environmental pollution issues of global concern, and microplastics (plastics with a size ≤ 5 mm) have also attracted much attention due to their large specific area, higher pollutant adsorption capacity, and higher migration performance. As the population increases and more chemical products are manufactured, the level of microplastic pollution continues to increase. Microplastics discharged from sewage treatment systems will enter the ocean and rivers, so estuary ecosystems are vital to controlling marine microplastics. As the estuary of China's most significant river entering the East China Sea, the Changjiang River Estuary has become one of the typical areas for microplastic research in estuaries. This paper systematically reviews the sources, hazards, and impacts of microplastics in the Changjiang Estuary. Firstly, the research on microplastics in the Changjiang Estuary was analyzed, and we found that the bioaccumulation, removal, and interaction with microorganisms of microplastics have become a new research hotspot. At the same time, the current abundance of microplastics in the surface water of the Changjiang River Estuary is 1.71 ± 3.12 MP/L, which is lower than that of the Changjiang River area and the river farmland in Shanghai, but still higher than the 0.22 ± 0.27 MP/L in the area adjacent to the East China Sea. Microplastics smaller than 1000 μm accounted for 68% of the total, while transparent, white, blue, and black were the primary colors of microplastics in the Changjiang Estuary. In addition, polyethylene and polypropylene are the primary materials of microplastics in the central Changjiang River Estuary and related water bodies, and fibers are the main shape of microplastics. Industry, agriculture, domestic sewage, and air deposition may be the primary sources of microplastics in the Changjiang Estuary. The numerous lakes and water conservancy facilities in the Changjiang River Basin can reduce the number of microplastics reaching the Changjiang Estuary to a certain extent. At the same time, seasonal rainfall and ocean currents will affect the abundance of microplastics in the surface waters of the Changjiang River Estuary. Finally, this paper puts forward relevant suggestions based on the actual situation of the Changjiang River Estuary and the developed microplastic treatment technologies. This article will provide a structured reference for future research on microplastics in the Changjiang Estuary and assist in assessing microplastics' impact on the ecological environment. The Fate of Microplastic Pollution in the Changjiang River Estuary. [Display omitted] • Microplastics' sources, hazards, and impacts in the Yangtze Estuary were reviewed. • Bioaccumulation, removal, and interaction with microorganisms are the hotspots. • The microplastics in the water of the Changjiang mainly exists in the form of fibers. • Source control and establishment of MPs barriers will help to solve MPs pollution. [ABSTRACT FROM AUTHOR]

Existing studies have primarily examined the impact of farmland fragmentation on agricultural production from the perspective of crop yield per unit of land. However, they generally overlook the effects of farmland fragmentation on the productivity of both labor and capital. Drawing upon micro-level data from rice, wheat, and maize farmers across 14 provinces in China for the years 2019 and 2020, this paper measures the effects of farmland fragmentation on the labor productivity, land productivity, and capital productivity of these three different crops, within the same temporal and spatial dimensions. We utilize the internal instrumental variable method (KV-IV) to address potential endogeneity issues in the model. The research findings indicate: (1) Farmland fragmentation hampers the use of machinery, resulting in a significant decrease in the labor productivity of farmers. On average, for every 1% increase in the level of farmland fragmentation, labor productivity for rice, wheat, and maize farmers drops by 21.3%, 19.9%, and 21.9% respectively. (2) Farmland fragmentation has significantly increased the land productivity of rice. With every 1% increase in farmland fragmentation, the land productivity of rice farmers increases on average by 3.4%. However, the impact of farmland fragmentation on the land productivity of wheat and maize is not significant. (3) The capital productivity of rice, influenced by farmland fragmentation, mirrors the changes seen in land productivity. Rice farmers with higher levels of farmland fragmentation exhibit greater capital productivity. On average, with every 1% increase in the level of farmland fragmentation, the capital productivity of rice farmers increases by 6.7%. Conversely, farmland fragmentation has a significant negative impact on the capital productivity of both wheat and maize farmers. On average, for every 1% increase in farmland fragmentation, the capital productivity of wheat and maize farmers drops by 9.1% and 7.0% respectively. Based on the empirical results of this paper, we propose corresponding policy recommendations. In the conclusion, we delve into the underlying causes of farmland fragmentation in China and ascertain that, to address the issue of farmland fragmentation in the country, the government must take a leading role. The significance of this paper lies in analyzing the varying degrees and directions of the impact of farmland fragmentation on different crops, providing a basis for the government to implement differentiated farmland fragmentation management policies in different crop-producing regions in the future. [ABSTRACT FROM AUTHOR]

Rational assessment of the regional sustainable development level is an important prerequisite for formulating development strategies and achieving the UN Sustainable Development Goals (SDGs). Currently, little literature provides nuanced understanding for national sustainable development from the perspective of county sustainability. Such studies can provide more accurate regional heterogeneity characteristics and policy decision support. Thus, this paper applies the entropy weight method and Chinese county data from 2000 to 2017 to reassess the sustainability of Chinese counties. The results show that China's county sustainability (Sustainable Development Index, SDI) is slowly improving. County sustainability performance is poorer in ethnic minority agglomerations, poor counties, old revolutionary counties, and central and western regions, better in county-level cities and eastern regions. The decomposition results show that economic sustainability and environmental sustainability are the main supporters of SDI growth, and livelihood sustainability is in urgent need of improvement. The regional inequality of SDI in Chinese counties gradually decreases, and inter-group differences are the main contributors to regional inequality in SDI. This paper provides support for China to develop county-level sustainable development measures and practice the SDGs. The findings could be useful for policymakers. [Display omitted] • Based on the entropy weight method and the Chinese county data, the sustainable development levels of 1533 counties in China from 2000 to 2017 are estimated. • Analyses of spatial-temporal dynamic heterogeneity, Linear decomposition, and Dagum decomposition are conducted to study the features of sustainable development in Chinese counties. •The influence of natural features and national concern preferences on county sustainable development are discussed. [ABSTRACT FROM AUTHOR]

The rapid development of urbanization in China inevitably leads to a sharp increase in building energy consumption, and Passive House (PH) have received much attention in China in recent years. In this paper, the annual energy demand (AED) and summer discomfort hours (SUH) of PH are used as optimization objectives to establish a set of design solutions for multi-objective optimization (MTO) and economic analysis of a PH in Shandong Province, China. It is found that (1) the algorithm based on nearest neighbor component analysis (NCA) feature extraction applies to the sensitivity analysis of multivariate nonlinear high-dimensional data, and the NCA-GA-RBF neural network technique is proposed, which has significantly improved the goodness of fit and generalization ability for AED and SUH. (2) The NSGA-II genetic algorithm is used for the optimization search, and the results show that the overall improvement rates of AED and SUH are 25.5% and 21.6%, respectively, among the nine solutions after comprehensive evaluation; (3) Finally, the optimal scheme of energy saving and the optimal scheme of the economy are selected for economic evaluation. By comparing the economics of the two options and the improvement rates of AEDs and SUHs, the guidelines for design decision-makers are provided. In summary, the design scheme of this paper is forward-looking and reference-oriented and provides some reference suggestions for the development of PH in China. • The NCA algorithm is suitable for multivariate nonlinear sensitivity analysis. • NCA-GA-RBF has stronger and more stable generalization ability and accuracy. • In this paper, climate is the main factor affecting thermal parameters. • Global costs have a stronger economic interpretation. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive system for assessing contaminant emissions, including the dominant contaminant reduction effects, recessive contaminant reduction effects, and contaminant reduction efficiency indexes. The system is used to evaluate the linkage changes in contaminant emissions reduction across different sectors, the ease of regulation, and the returns on emissions reduction efforts. The study's results demonstrate that firstly, COVID-19 initially reduced contaminant emissions across almost all sectors, although this effect waned over time. Secondly, applying conventional regulatory measures to sectors with high reductions in contaminant emissions may not yield the expected results. Thirdly, while some sectors may be more difficult to regulate, they may offer a higher return on investment in terms of emissions reduction. Based on the above results, the paper advocates for timely measures to consolidate environmental gains, prevent rebounding of contaminant emissions, prioritize supervision and management of easily regulated sectors, prioritize upgrading of cleaner production in sectors with high reduction efficiency indices, and increase investment in environmental technology. • Created a new comprehensive system for assessing contaminant emission changes. • Quantified the unique linkage changes of contaminant emissions during COVID-19. • Developed new models to reveal contaminants' regulatory difficulty and return. • The innovative reduction effects of four key contaminant indicators were measured. • Applied WHEM firstly in research across multiple areas of contaminant emissions. [ABSTRACT FROM AUTHOR]