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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]

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]

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]

• 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]