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Over the past decades, China's vast regional disparities in resource endowment, economic development, and industrial structure have driven large-scale relocations of high energy-consuming industries (RHEIs). Despite extensive research on broad-based industrial relocation and emission transfer, the trend, structure and environmental impact of China's RHEIs need further investigation. This paper employs the multi-regional input-output model (MRIO) to calculate the trend, scale, and structure of the RHEIs among China's 30 provinces. Additionally, we investigate the RHEIs' effect on green total factor energy efficiency (GEE) and its heterogeneity. Our results indicate that the net inflow of high energy-consuming industries decreases GEE, with a more noticeable effect observed in central provinces and after the execution of the Belt and Road Initiative (BRI). However, the positive effect of RHEIs on GEE in outflow areas is more substantial than their negative impact in inflow areas, suggesting that RHEIs can enhance overall efficiency. This study contributes to the understanding of China's industrial relocation by providing valuable insights into China's RHEIs. • China has a large-scale relocation of high energy-consuming industries. • The relocation of China's high energy-consuming industries is calculated. • The relocation's impact on green total factor energy efficiency is analyzed. • Regional heterogeneity is found among different provinces. [ABSTRACT FROM AUTHOR]

[Display omitted] • Exploring the industrial water-land-energy-carbon interaction help promote resource conservation and low-carbon development. • Constructing evaluation indicators and decomposition model to assess the carbon emission effect of industrial water and land use. • Industrial carbon emission intensity of water and land use in China increases, and inter-provincial difference expands. • Industrial matching index of water and land resources in China presenting great spatial agglomeration. • Matching index of water and land resources is the main inhibitory factor for all provinces in China. The industrial production requires the input of water, land and energy, and the water-land-energy interaction generates carbon emissions. Investigating the industrial water-land-energy-carbon nexus and exploring the influencing factors of the carbon emissions help promote the intensive use of water resources, land resources, and energy, as well as the low-carbon development of industry. This paper applied kernel density estimation and spatial auto-correlation analysis to explore the spatio-temporal variation of industrial carbon emission effect of water and land use and the industrial matching status of water and land resources in China, and then analyzes the influencing factors to industrial carbon emissions by introducing water and land resource factor into Kaya identity and Logarithmic Mean Divisia Index (LMDI) model. The main conclusions are: (1) From 2006 to 2020, China's industrial carbon emissions increased by 82.02%. The industrial carbon emission intensity of water use (CEIWU) and the industrial carbon emission intensity of land use (CEILU) increased by 158.02% and 55.53% respectively. The inter-provincial difference of CEIWU and CEILU expanded considerably, and the number of provinces with high CEILU had a large increase. (2) The industrial matching index of water and land resources (MIWL) in China showed a fluctuating downward trend, presenting great spatial clustering, and the provincial MIWL were mainly concentrated in the H-H and L-L regions. (3) The contributing and inhibitory effect of each influencing factor varied on regional and provincial level. The economic output of water use is a contributing factor to all regions and provinces, while the MIWL is an inhibitory factor to all regions and provinces. [ABSTRACT FROM AUTHOR]

An improvement in industrial carbon emission efficiency is crucial for achieving both reductions in carbon emissions and sustainable economic growth. In this paper, we use an improved non-radial directional distance function (NDDF) to construct a new meta-frontier total-factor carbon emission efficiency index ( TCEI ) with which we estimate the meta-frontier TCEI of China's 30 provincial industrial sectors in 2005–2015 and analyze their dynamic evolution. The results show that compared to traditional NDDF, the improved NDDF has more advantages in measuring both carbon emission efficiency and the technology gap ratio. For the study period, China's industrial meta-frontier TCEI is low, indicating that the industrial TCEI of many provinces still has much room for improvement. The meta-frontier TCEI has significant inter-group heterogeneity, with Eastern China having the largest carbon emission efficiency, followed by Central China, and Western China having the lowest. China's industrial meta-frontier TCEI increased significantly during the study period with technical progress playing a major role in promoting it. Over time, however, the meta-frontier TCEI growth rate decreased significantly as the deterioration in technological efficiency and the expansion of the technology gap have jointly inhibited the growth of carbon emissions efficiency. Carbon emission performance in various regions over different periods exhibit differing characteristics, that is, the carbon emission performance has significant spatial heterogeneity and period heterogeneity. [ABSTRACT FROM AUTHOR]

With the "carbon neutrality" target proposal, China is facing severe pressure on carbon reduction. Industrial economic activities form an essential emission source of carbon dioxide. Therefore, it is necessary to promote industrial sectors' coordinated emission reduction work. This paper uses non-competitive input-output model and structural path decomposition method to analyze the carbon emission changes from three levels of total, production layer and industrial chains, identifying the main paths and driving factors of carbon emission changes in China from 2017 to 2018. The results show that: (1) The first layer presents obvious low-carbon characteristics as a direct emission level, but the change in its carbon emissions accounted for 41.8%. (2) The increased emission of industrial chains is mainly caused by consumer spending and fixed capital formation, and emission reduction is mainly triggered by consumer spending. (3) Demand scale is an essential driving factor of carbon emission increase. The contribution rate of demand structure to emission increase and reduction industry chains is 55.1% and −16.5%, respectively, which is the biggest reason for the difference between them. Finally, targeted policy recommendations are put forward from the perspective of the emission transmission path and driving factors in the industrial chain. • The non-competitive IO model of China's CO 2 emissions is established. • SPD is applied to identify the emission increase and reduction industrial chains. • The driving factors of CO 2 emission changes in industrial chain are explored. • The comparative analysis of increase and reduction industrial chains is conducted. [ABSTRACT FROM AUTHOR]

To mitigate the climate change and reduce energy consumption, the Chinese government has applied a variety of polices during the last two decades. Based on data from Industrial enterprises emission and pollution database (IEPED) and Annual Survey of Industrial Firms (ASIF), this study takes Energy Saving and Emission Reduction Plan (ESER) since 2006 as a policy shock to explore the impact of the ESER on industrial firms' energy consumption behavior. The result shows: Firstly, ESER encourages industrial firms to consume less coal, petroleum and natural gas on average. Secondly, by dividing the firms into several groups by the ownership structure, the firm size and the firm age, this paper finds different firms have different strategies in terms of changing their energy consumption to respond ESER. For example, public firms work harder on reducing coal and petroleum consumption per production while private firms prefer to use more natural gas per production. Thirdly, the dynamic effect analysis portrays that traditional fossil fuel intensity declines immediately after energy conversation policy, while the negative effect on industrial firms' natural gas intensity could occur with some delay. Lastly, in terms of total energy consumption, average coal and petroleum consumption of polluted industries and that of non-polluted industries have no difference after the policy. In addition, ESER only has a short-term effect on energy consumption. These results are helpful in understanding how to design an efficient environmental regulation system and protect the environment simultaneously. • This study explores the impacts of the Energy Saving and Emission Reduction Plan (ESER) on firms' energy consumption behavior based on industrial firm data. • ESER encourages firms to consume less traditional energy (coal and fossil fuels) and clean gas. For different firms, their energy intensity changes distinctively in response to ESER. • The dynamic effect analysis portrays that traditional fossil fuel intensity declines immediately after energy conversation policy, while the negative effect on clean gas intensity occur with some delay. • ESER has a short-term and lagged effect on total energy consumption. [ABSTRACT FROM AUTHOR]

Abstract: Knowledge of influencing factors of industrial carbon emissions (ICE) is crucial to the efforts of reducing anthropogenic greenhouse gas emissions. In this paper, main factors responsible for the ICE in Shanghai between 1996 and 2007 were identified and quantitatively analyzed using the Log-Mean Divisia Index method. It was found that the industrial output was the main driving force of ICE. The decline in energy intensity and the adjustment of energy and industrial structure are major determinants for reduction of ICE, with the former alone accounting for 90% of the reduction. To better investigate the relative contribution of different industrial sectors and their changes over time, we divided the study period into two equal time intervals and analyzed some high-carbon emission sectors. The results suggested that the intensity of energy use should be reduced further, for it was far higher than the world average. Adjustment of industrial structure by developing low-carbon emission industries is more crucial than energy mix. [Copyright &y& Elsevier]

PM 2.5 emissions has become a serious issue in China with enormous regional variation in economic development, resource endowment, and consumption patterns, which leads to great variations in regional PM 2.5 emissions and embodied PM 2.5 transfer among provinces. The spatial and temporal evolution pattern of PM 2.5 and its influencing factors are important issues in the study of air pollution emissions and control, which could help policy makers allocate emission responsibilities and reduction targets. Based on the perspective of final consumption, this paper uses a multiregional input-output model to estimate PM 2.5 emissions in 30 provinces in different years in China, applies a geographically weighted regression model to analyze different driving factors, and then analyzes the spatial heterogeneity of consumption-based PM 2.5 emissions. The results show that consumption-based PM 2.5 presents a significant reduction trend, although the separation of production and consumption areas of PM 2.5 emission is further intensified. The provinces with rich energy but relatively backward economies and manufacturing industries correspond to the primary net inflow of PM 2.5 , while the provinces with strong consumption ability and the most developed economies and industries present a net outflow of PM 2.5. Moreover, the slowdown of consumption growth and the improvement of consumption quality have a positive impact on PM 2.5 emission reductions. The optimization of industrial structure has a more significant impact on pollution control and haze reduction in the western region, while the improvement of energy utilization efficiency and rational use of construction land are more conducive to the reduction of consumption-based PM 2.5 emissions in the eastern region. From the perspective of temporal and spatial changes, significant spatial differences occur between regions. Energy consumption, environmental protection investment and construction land show the trend of " high value area diffusion and low value area reduction". • Explores the spatial distribution characteristics of PM 2.5 emissions in China from the perspective of consumption. • Consider and analyze the inter-annual variation of pollutant emission transfer. • Clarifies the spatial heterogeneity characteristics of influencing factors. • Emphasizes the importance of further optimizing influencing factors to reduce haze from the consumption end. [ABSTRACT FROM AUTHOR]

Green production and pollution control matter a great deal for resource conservation and sustainable growth. Today, Chinese firms are facing the challenge of upgrading the modes of production of industries with high energy consumption and high pollution to align with green initiatives. Financial systems can be designed to intervene in modes of production to control firms' pollution emissions, but the degree of impact and design mechanism are not clearly understood up to now. Thus, evaluating the policy impact of such transactions related to firm production is indeed an important contribution to existing knowledge about these topics. Using novel firm-level data with pollution and financial variables, we exploit the causal effect of bank loans on firms' abatement performance by using a natural experimental of a green loan policy shock in China. The results show that green loan policy has the positive effect of pollution abatement by state-owned and private-owned firms. This paper also investigates how green loan policy may promote green production through strengthening financial constraint and decreasing fixed and intangible investments. Furthermore, we find that political ties transfer financial burdens from firms with strong political ties to firms with weak political ties. In closing, we articulate the implications of our study of a green financing system for sustainable growth and cleaner production. Image 1 • Green loan policy significantly decreases high polluting manufacturing firms' pollution emission. • Green loan policy significantly facilitates high polluting manufacturing firms' pollution abatement. • Green loan policy performs well in state-owned and private owned firms, but not for foreign firms. • The policy increases the financial constraints and substitutes the fixed and intangible investments. • Political tie transits financial burden to those firms with less political tie. [ABSTRACT FROM AUTHOR]

• Energy & environmental inefficiency of the 45 cities in China is analyzed. • Variable-specific productivity growth measures are used. • Bounded-adjusted Measure and Luenberger Productivity Indicator are applied. • Dagum Gini coefficient is employed to measure the regional disparities of energy use. • Policy guidelines are presented based on the productivity change directions. Analyzing green transformation of energy use and pollutant emissions in China's "Three Regions and Ten Urban Agglomerations" (TRTAs) allows effectively promoting sustainable development in the country. This paper applies Data Envelopment Analysis, namely the Bounded-adjusted Measure (BAM) relying on the additive structure, to measure the technical inefficiency and productivity change across TRTAs in China. The technical inefficiency and productivity change observed for TRTAs are 0.29 and 2.29% respectively. The decomposition results indicate that industrial energy consumption, industrial sulfur dioxide (SO 2), and industrial soot & dust emissions are the main variables causing TRTAs' industrial operation inefficiency. Spatially, environmental inefficiency of the above-mentioned three variables in North China Urban Agglomeration (NA) is higher than those in Northwest, Yangtze and Pearl River Delta Urban Agglomerations (NWA, YRDA, and PRDA respectively). Decomposition of the Gini coefficient shows that the performance associated with the three variables varies among the regions with intra-regional differentiation of the PRDA being the highest. Given the regional patterns in productivity change, more efforts should be directed towards improving technical progress on industrial energy conservation in NWA. Furthermore, regulations on industrial air pollutant emissions, joint mitigation and monitoring of the key indicators in PRDA should also be emphasized. [ABSTRACT FROM AUTHOR]

The Environmental Kuznets Curve (EKC) is an important tool to analyze the relationship between environment and per capital income. But two significant issues have been overlooked: why some points are above the EKC while others are below it? And what factors caused this phenomenon? Based on the data of 30 provinces in China over 2005–2016, this paper aimed to solve the above two questions. For the first question, we take the point on EKC as the theoretical pollution emission value of the different economic development stages; and use the difference between the theoretical pollution emission and the actual pollution emission under the same per capita income as the pollution emission efficiency. The difference value is used to reflect whether the pollution emission of the corresponding economic development stage of each region exceeds the standard and by how much. The result shows that most of the provinces with low pollution emissions concentrated in the north of the Yangtze River. Great progress has been made in China's pollution reduction work during 2015–2016. Then, for the second question, through the analysis of multiple mediating effects, we find that Environmental regulation, industrial transfer, proportion of output value of heavy pollution industry, energy consumption structure and energy using efficiency are important determinants to the pollution emission efficiency in Chinese province. [ABSTRACT FROM AUTHOR]

• A new indicator to evaluate total-factor air pollution emission efficiency is proposed. • China's total-factor air pollution emission efficiency is relatively low and exhibits significant differences in different regions. • China's total-factor air pollution emission efficiency is driven by technical progress rather than efficiency promotion. • The total-factor air pollution emission efficiency gap among China's different provinces will probably widen in the future. • The factors that influencing China's provincial total-factor air pollution emission efficiency are revealed. In recent years, air pollution situation becomes more severe and has seriously threatened sustainable economic development and public health in China. Combining the improved slacks-based measure (SBM) model, global Malmquist-Luenberger (GML) productivity index and panel Tobit model, this paper investigates the regional differences, dynamic evolution and influencing factors of China's provincial air pollution emission efficiency over the period 2006–2015 under the total-factor framework. Our results show that: (1) China's total-factor air pollution emission efficiency is relatively low and exhibits significant regional differences; (2) technological progress is the main contributor to ameliorate China's provincial total-factor air pollution emission efficiency; (3) the total-factor air pollution emission efficiency gap between the higher- and the lower-efficient provinces will probably widen in the future; (4) China's provincial total-factor air pollution emission efficiency is significantly positive related to the level of economic development, industrial structure optimization, technological innovation and foreign direct investment (FDI), is significantly negative related to the energy consumption structure. The above results indicate that China has made remarkable achievements in improving regional total-factor air pollution emission efficiency. However, there is considerable potential for further improvement. Policy options for China's regional total-factor air pollution emission efficiency improvement include but not limited to optimizing industrial and energy consumption structure, promoting environmental technology innovation, strengthening cooperation and exchange between different regions, deepening the reform of energy market and energy pricing mechanism, actively introducing foreign investment, and further improving environmental regulation level. [ABSTRACT FROM AUTHOR]

The aluminium industry, with its traditionally high energy consumption, high emissions and high pollution, is facing increasing pressure to reduce carbon emissions in China. Implementing effective policies and measures to promote carbon emissions reduction is of great importance. This study deploys the life cycle assessment (LCA) method to explore carbon emissions and CO 2 sources from aluminium manufacturing in China as well as a scenario analysis to evaluate the reduction potential and driving forces of carbon emissions in the industry. The evaluated scenarios include a new capacity allocation scheme, technological progress and energy structure optimization. The carbon emissions from the aluminium chain are mostly contributed by indirect emissions (more than 68%) from electricity generation. Significant regional discrepancies are observed in the total emissions and intensity, and a reasonable industry layout tends to transfer to the south and southwest areas from the perspective of the environmental pillar. Production output remains the dominant factors associated with total carbon emissions from manufacturing firms, such as the aluminium industry. Technological progress and the energy structure contribute to total reductions and carbon efficiency, although the former has a relatively limited scope for aluminium firms. This paper also shows that marginal carbon efficiency improvements are not very effective in lowering the total CO 2 emissions under the context of high output growth. [ABSTRACT FROM AUTHOR]