Search

In 2017, a carbon emissions trading market will be launched nationwide by the China government. Calculating the enterprise carbon emissions is an important prerequisite and basis for trading. This paper discussed types of greenhouse gases, calculation boundaries and methods, energy consumption, carbon emissions, and intensity of a representative integrated pulp and paper mill in China based on China Guidance and Greenhouse Gas Protocol Tools. The results showed that there were 435,000 tonnes (t) of CO2 emissions from that mill in 2014 that did not contain emissions of biomass energy, which was 8 times higher than that of fossil energy. The pulp carbon intensity based on the mill was 0.230 t CO2/Adt, which accounted for 7.50% to 57.4% in other pulps' based on the product. Intensity based on Gross Domestic Product (GDP) was 1.090 t CO2e/1000 USD and accounted for 56.8% intensity in the China paper industry. The intensity based on sales accounted for 52.6% in the firstclass enterprise in the developed country. It also showed that intensity was influenced by the species of raw material, energy, and products, which provided the mill with measures for energy saving and emissions reduction to obtain the redundant carbon emissions in the trading. [ABSTRACT FROM AUTHOR]

Energy is known as the lifeline of national development, and from the last decade or so, the security of human energy supply has been frequently disturbed by natural disasters due to global warming and frequent geological activities. In this paper, by combing the literature, we found that the past literature on the relationship between energy and natural disasters mainly focused on measuring energy consumption under natural disasters, but less on the integrated evaluation of human economic activities, energy security and natural disasters, and less on the evaluation of the energy governance efficiency of each provincial, municipal, and autonomous region government in preventing and managing exposure to natural disasters from the perspective of Chinese provinces. Therefore, in order to fill the gap in the literature in this field, this paper collects panel data of energy consumption efficiency stages and natural disaster treatment stages from 2013 to 2017 for 30 provinces in China (excluding Hong Kong, Macao and Taiwan as well as Tibet Autonomous Region) and uses the two-stage undesirable dynamic DDF model as a framework to study the relationship between economic, environmental pollution and natural disasters for the sample data and to analyze the phase-by-phase evaluation of energy and natural disaster efficiency and make corresponding policy recommendations. The following conclusions are drawn: (1) The overall efficiency of China's eastern coastal provinces is higher than that of the central and western provinces. (2) The first-stage efficiency of Chinese provinces is better than the second stage, and the difference in efficiency of the first stage of each province is smaller than that of the second stage. (3) In terms of the efficiency of disaster prevention and relief inputs, the efficiency values are generally lower in most regions of China. (4) Finally, the annual efficiency of natural disaster losses is not high in all regions, and the efficiency values are higher in the eastern coastal regions than in the central and western regions. Accordingly, this paper proposes that each province should formulate relevant disaster prevention and economic development strategies according to regional characteristics, while the central government should also propose locally appropriate coordinated governance policies to effectively control carbon dioxide emissions and air pollution, as well as increase disaster prevention publicity and incorporate disaster prevention education-related work into the performance assessment mechanism of local governments to promote the interactive development of the two. [ABSTRACT FROM AUTHOR]

At present, China is in the period of large-scale tax and fee cuts and external pandemic shocks. Local governments' financial pressure has intensified. There is a lack of existing studies on how it will affect local carbon emissions. This paper uses the quasi-natural experiment of the 2010 educational authority reform to measure exogenous changes in financial pressure. It adopts the continuous double differential method to empirically investigate the impact of local financial pressure on carbon emissions. The results of the paper are as follows. First, the financial pressure generated by the educational authority reform has significantly increased local carbon emission intensity. This indicates that local governments will address carbon emissions in other ways when they feel financial pressure. Second, to ease financial pressure, local governments will regulate high energy-consuming enterprises and utilize their high production value and strong tax-generating ability to scale up their production capacity and obtain more tax revenues, which will lead to a large amount of carbon emissions. This study is of important reference significance for how to deal with financial pressure from now on and how to well handle the relationship between local finance and carbon emissions. [ABSTRACT FROM AUTHOR]

With the rapid growth rate of China's economy, the extensive pattern of economic growth of "high energy consumption and low output" has magnified the constraints of energy issues on China's economic development and environmental protection, which highlights the importance of improving energy efficiency. As one of the three major economic zones in China, the Pearl River Delta region also faces high energy consumption and pollution emissions while developing at a high speed. Hence, improving the energy efficiency of the Pearl River Delta region is needed, as it not only is conducive to driving its development of the surrounding green economy, but also promotes the subsequent sustainable economic development. However, there are few literatures on the calculation and analysis of energy efficiency in the Pearl River Delta, and lacking a systematic analysis of input–output index system of energy efficiency measurement. Therefore, this paper calculates the energy efficiencies and the Malmquist indexes based on the panel data of the nine cities in the Pearl River Delta from 2005 to 2019 through super-efficiency SBM model and Malmquist index method by using MAXDEA and MATLAB software. The result illustrates that all regions in the Pearl River Delta except Guangzhou and Shenzhen show obvious energy inefficiency, which is mainly caused by the imbalance between technical efficiency and scale efficiency. Based on the calculation results, this paper gives some relevant suggestions for the further approach of energy reform in the Pearl River Delta according to the calculation results. [ABSTRACT FROM AUTHOR]

Air pollution is an important part of ecological environment problems. Gaseous energy combustion pollution is a key part of air pollution. Analysis of its spatial distribution and drivers is important to effectively manage air quality and promote regional green development. This paper uses panel data of 30 provinces in China from 2006 to 2019 to analyze the spatial distribution and drivers of gaseous energy combustion pollution in each province of China through a combination of quantitative and qualitative analysis based on the spatial Durbin model, and further decompose the spatial effects of each influencing factor. The empirical results show, firstly, that inter-provincial gaseous energy combustion pollution in China shows significant spatial differences and cluster characteristics. Secondly, most areas are located in high–high aggregation area and low–low aggregation area. Finally, population, energy consumption and other independent variables have different impacts on gaseous energy combustion pollution in different regions. The changes of these variables will affect the adjacent areas through spatial transmission while affecting a region. According to the empirical results, this study proposes policy recommendations to balance the pollution degree of gaseous energy combustion in various regions and effectively reduce the emissions of various pollution sources. The research results are helpful to understand the spatial distribution of gaseous energy combustion pollution in various regions of China, provide reference for the future development of various regions, and have important practical significance for the reduction and balance of pollution levels. [ABSTRACT FROM AUTHOR]

Urban carbon emissions are one of the most important areas contributing to the growth of carbon emissions, and resource-dependent cities with natural resource extraction and processing as their leading industries tend to have higher carbon emissions. Ordos is the city with the highest coal production in China, and its economic development is dominated by coal, oil and gas, and other resource extraction and processing industries, with industrial activities making a large contribution to carbon emissions. At the same time, Ordos has undergone rapid industrialization in recent years, but still faces the problem of environmental pollution, epitomizing a typical resource-dependent city in China. Therefore, this paper takes Ordos as an example and uses the Generalized Divisa Index Method (GDIM) to study the drivers of industrial carbon emissions in Ordos from 2005–2020, a typical resource-dependent city in China, and further analyzes are conducted in relation to the three phases of development. Based on the key drivers, the Monte Carlo method is used to forecast industrial carbon emissions from 2021 to 2030. The results show that the most important factors driving the growth of industrial carbon emissions are the scale of industrial output and industrial energy consumption, while the intensity of industrial energy investment is the most important factor mitigating industrial carbon emissions, and that energy efficiency and carbon intensity of energy consumption can also mitigate carbon emissions after economic transformation. At the same time, investment is the factor with the greatest potential for optimization on the path to emissions reduction. [ABSTRACT FROM AUTHOR]

Under the policy background of "joint prevention and control" of global greenhouse gas emission reduction and regional air pollutants, the power industry, as an important target industry of energy conservation and emission reduction policies, has become an effective choice to release dual pressures. In this paper, the "bottom-up" emission factor method was used to measure the emission of CO2 and NOX from 2011 to 2019. Then, the contributions of six factors to NOX emission reduction in China's power industry were identified using the Kaya identity and logarithmic mean divisia index (LMDI) decomposition methods. The research results show that (1) there is a significant synergistic emission reduction effect between CO2 emission reduction and NOX emission reduction; (2) the factor that inhibits the growth of NOX emissions reduction in the power industry is economic development factor; and (3) the main factors that promote the reduction of NOX emission from the power industry are synergy effect, energy intensity, power generation intensity, and power production structure factors. Several suggestions are proposed, which are the power industry should adjust its structure, improve energy intensity, focus on applying low-nitrogen combustion technology, and improve the air pollutant emission information disclosure system to reduce NOX emissions. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to reveal the mechanism and process of the dynamic evolution of the economy-energy-environment (EEE) system and study the variables that determine the speed of system evolution and development. The innovation is to overcome the defect of single index by constructing a system evaluation index and reveal the regional EEE system's evolution mechanism based on Haken's synergetic theory to supplement a systematic perspective's empirical evidence. It selects 30 provinces, municipalities, and autonomous regions in China to empirically analyse the evolution mechanism of the EEE system from 2005 to 2019. The empirical results show that economic development is the order parameter of the evolution and development of the EEE system. In the process of system evolution, the economic development subsystem is the decisive factor in EEE system evolution. In terms of the positive feedback mechanism of order parameter combination, the EEE system forms a positive feedback mechanism for increasing economic development in the stage of evolution and development. The negative feedback mechanism of decreasing environmental pollution emissions is formed in the EEE system. The increase in pollutant emissions has a certain inhibitory effect on economic growth. The improvement in the economic development level has no promoting effect on pollutants, and economic development, in turn, reduces environmental pollution. [ABSTRACT FROM AUTHOR]

During Covid-19 pandemic world economy experienced negative growth rate, therefore energy consumption and consequently emission pollution decreased. According to Environmental Kuznets Curve, it is expected that energy consumption and emission pollution increase in response to Covid-19 economic recovery, even higher than its pre-pandemic level. The goal of this paper is to study the environmental risk of Covid-19 economic recovery. We use an Environmentally-Augmented Global Vector Autoregressive Model (E-GVAR) to trace dynamic effects of Covid-19 economic recovery on pollution emission. Using generalized impulse response functions (GIRFs), we investigated the effect of positive economic shocks in real per capita income in China and USA economies on total C O 2 equivalent emission pollution. The results show that positive economic recovery affects emission pollution significantly. China and emerging economies may experience high risk while Europe region is moderately affected by this positive shock. A positive Economic Shock in China decrease pollution emission in USA over time. It can be attributed to substitution effect of Chinese product in global market. Generally, our results demonstrate spillover effect of transition shocks from large economies to the rest of world and highlights the importance of linkages in the world economy. [ABSTRACT FROM AUTHOR]

The industrial sector is China's major element of energy consumption and carbon emissions, and carbon emissions reduction in industrial parks has become an important foothold in carbon reduction work. Predicting the future evolution trend of carbon emissions in industrial parks under different policy orientations is of great significance for China to achieve the carbon emissions peaking and carbon neutrality goals. Based on the current status of electricity consumption and carbon emissions in industrial parks, this paper takes a light industrial park as the research object, analyzes the source of carbon emissions in this park, combines the characteristics of resource endowment and industrial structure, and considers the factors influencing society, load curve, energy supply and carbon sink, thus constructing a system dynamics model of carbon emission evolution for this park. Different influencing factors are selected to set multiple target scenarios, and the GDP, carbon emissions, carbon emissions reduction and near‐zero carbon evaluation coefficient of light industrial parks are used as characterization indicators for simulation analysis. The analysis results revealed that the comprehensive scenario set by increasing the maximum installed capacity of renewable energy units and raising the proportions of environmental and science and technology inputs while adjusting the industrial growth rate of the park performed best. In this scenario, the economic development of the park and the process of carbon emissions reduction are considered. [ABSTRACT FROM AUTHOR]

The excessive carbon emissions not only intensify the global climate change, but also seriously restrict the sustainable development of social economy. However, improving industrial carbon emissions efficiency is the most directly effective way to reduce emissions. Therefore, accurate measurement and analysis of carbon emissions efficiency and evolution characteristics of China's industrial system is the basis for China to improve carbon emissions efficiency. Based on this, we adopted energy consumption method and input-output method to calculate and analyze the industrial carbon emissions efficiency and evolution characteristics of China from 2002 to 2015. The results show that (1) If carbon emissions from cement production are ignored and only energy-related carbon emissions are considered, the calculation results of carbon emissions efficiency of heavy industry will be overestimated about 30%. (2) Compared with 2002, China's industrial carbon emissions efficiency increased by about twice in 2015. Specifically, the optimization of carbon emissions efficiency in agriculture, construction, light industry and service industry is very obvious, which has increased by 5.65, 5.00, 4.69 and 4.68 times respectively; The optimization of carbon emissions efficiency in power sector, heavy industry, transportation and chemical industry was obvious, which increased by 2.55, 2.01, 1.86 and 1.47 times respectively; The carbon emissions efficiency of the fossil energy sector has decreased by 0.36 times. (3) The carbon emissions efficiency of various industries has significant differences. Among them, agriculture, service industry, light industry and construction industry are generally industries with higher carbon emissions efficiency, while power sector, fossil energy sector, transportation industry, chemical industry and heavy industry are generally industries with lower carbon emissions efficiency, especially power and fossil energy sectors. Based on these, this paper provides policy implications and scientific evidence for accurately improving carbon emissions efficiency from the perspective of carbon emissions efficiency. [ABSTRACT FROM AUTHOR]

Combined decomposition of relative productivity growth and absolute changes in input/output variables helps to identify the driving forces of energy conservation and emission reduction. This paper proposes a framework based on the Luenberger productivity indicator (LPI) and the logarithmic mean Divisia index (LMDI) approach to analyze the energy–economy–environment nexus. The empirical case of the China's industrial sector for 2006–2014 is analyzed. Following this approach, we present a variable‐specific decomposition framework which attributes the overall productivity change and its sources to individual input/output variables. Empirically, we examine the relationships between the productivity growth and energy consumption within the LPI–LMDI framework across China's province‐level regions. The results show important spatial variation in the productivity measures. The LPI–LMDI decomposition implies that the industrial energy consumption increased with productivity growth appearing as the only mitigating factor. As regards the industrial SO2 emission, the individual productivity growth effect and the efficiency change effect remained as suppressing factors for emission abatement. These results can be used for evidence‐based decision making. [ABSTRACT FROM AUTHOR]

In the context of promoting high-quality development in the Yellow River Basin (YRB) of China, urgent action is needed to achieve the “Dual Carbon” goal through energy savings, emission reductions, and industrial upgrading. This study measures carbon emissions from eight types of energy consumption across 43 industries from 2000 to 2019. Using the KayaLMDI model, factors affecting carbon emissions are analyzed, and the relationship between industrial structure and carbon emissions is explored through the coefficient of variation (CV). The findings reveal that coal consumption remains significantly higher than other energy sources, and the effect of energy structure adjustment on carbon emission reduction is limited compared to the impact of energy consumption increase on carbon emission growth. Moreover, the economic output effect is identified as the primary driving factor of carbon emissions, while energy utilization rate is crucial in achieving energy savings and emission reductions. Finally, the CV of carbon emissions across 43 industries is increasing. Based on these results, we suggest several policy recommendations, including prioritizing ecological concerns, developing comprehensive and scientifically sound plans, optimizing energy consumption structure, improving energy utilization efficiency, and adjusting industrial structure to promote sustainable development in the YRB. [ABSTRACT FROM AUTHOR]

Globally as well as in China, cities have contributed to most of economic output and have accordingly given rise to most of CO2 emissions. In particular, given unprecedented urbanization, cities will play an even greater role in shaping energy demand and CO2 emissions. Therefore, cities are the key to meeting its proposed carbon intensity target in 2020 and whatever climate commitments beyond 2020 that China may take. Given the paramount importance of cities, China is practicing low carbon city (LCC) development. Against this background, this paper first summarizes the general situation and main characteristics of China's LCC development. The paper then indentifies eight problems and challenges for China's LCC development including the absence of sound carbon accounting systems, lack of low-carbon specific evaluation system, rare use of market-based instruments, insufficient government-enterprise interactions, excessive budget dependence on land concession, increasing difficulty in further carbon mitigation, inevitable emissions growth due to rising living standards, and coal-dominant energy structure in the foreseeable future. Since these challenges are not applied to one or few cities, but are to all cities across the country, finally, the paper discusses how governments, in particular the central government, should address these problems and challenges. Given that China has faced great difficulty ensuring that local governments act in accordance with centrally-directed policies, the paper in particular discusses ways to incentivize local governments not to focus on economic growth alone and to move away from a heavy reliance on land concession. The paper ends with emphasizing on putting a price on carbon a crucial step for China's endeavor of harnessing the market forces to reduce its energy consumption and carbon emissions and genuinely transiting into a low-carbon economy. [ABSTRACT FROM AUTHOR]

The impact of trade on the environment and the climate has become a focus of attention. Tending to develop industries with higher added values, developed countries rely on importing high energy consumption goods from developing countries, and however, some CO emissions are embodied in the process of import. Currently, the accounting method of the territorial responsibility used to get the international data of greenhouse gas inventories ignores the difference between domestic consumption and export demands. Thus, developing countries bear the responsibility of pollution emissions from the export. The steel industry is an important basic industry of China's national economy as well as a vital part in the industrial system. With the expansion of trade scale, the impact of the export and import of China's steel on CO emissions is growing. This paper studied the embodied CO emissions in the trade of China's steel from 2005 to 2014, using the input-output model and the trade data of the China's steel imports and exports. The results indicate that (1) the complete CO emissions of China's steel industry are high. (2) The increase in the export scale makes the embodied CO emissions in the trade of China's steel export increase, and (3) China is a net exporter of CO emissions in the steel trade. Especially after 2007, the value of China's steel exports has been larger than that of China's steel imports, so China had borne much CO emissions responsibility in the trade of China's steel. Therefore, this paper puts forward that, in the future, the export structure of goods should be optimized into the high-tech products with the high added value, low energy consumption and low carbon emissions, and meanwhile, service industry is promoted to improve technical support to reduce CO emissions in the steel industry. [ABSTRACT FROM AUTHOR]

This paper explores the relationship between CO2 emissions and economic growth for China. This relationship is of considerable interest in the literature. There is a major focus on the underlying causes of the improvement in energy efficiency for China post the market reforms and whether such improvements in energy efficiency are likely to be maintained. The results demonstrate the importance of allowing for structural breaks in the econometric modelling to capture the impacts of the economic reforms on energy efficiency. The reforms have produced large gains in energy efficiency and an analysis of their likely continuation is important in forecasting the impacts of future growth in the Chinese economy. The paper concludes by outlining some possible forecast scenarios. [ABSTRACT FROM AUTHOR]

Identifying the carbon emission characteristics, driving factors, and decoupling status of the industrial subsectors is important for developing effective policy measures. This allows for implementing industrial emission reduction that, eventually, decouple carbon emission and economic growth. Such an analysis is especially important for the case of China on its way towards sustainable development and increasing global interrelationships. However, the literature still lacks comprehensive analysis, especially, at the industry level. This study uses the Logarithmic Mean Divisia Index and decoupling indicator to analyze how different factors contribute to CO2 emissions in 28 industries in China during 2002–2017. The results reveal that the growth of industrial CO2 emissions has been positive but decreasing. The highest CO2 emission change is observed for production and supply of electric and heat power, processing of petroleum, coking, and nuclear fuel, and smelting and pressing of metals. These sectors also show high carbon intensity levels. The economic output (scale) effect and population effect comprise the two major factors promoting the CO2 emission. The energy intensity effect is the key inhibiting factor of the industrial energy-related CO2 emission in China. The suppressive effects of energy and industrial structure have been continuously increasing. The economic growth and CO2 emission has been gradually decoupling in the case of the 28 sectors analyzed. Manufacture of cloths, leather, fur, feather, and related products as well as production and supply of gas exhibit a relatively stable strong decoupling. Based on the decoupling analysis, this study shows that energy intensity has induced the decoupling, whereas the opposite effect has occurred due to economic growth, and the other factors showed little effect on CO2 emission decoupling. [ABSTRACT FROM AUTHOR]

Due to ongoing urbanization and industrialization, the energy and electricity demand and consumption are rapidly growing in China, resulting in large air pollutant and greenhouse gas emissions. The coal‐fired power industry is a key to achieving synergistic reduction of air pollutant and carbon emissions. This paper quantifies and compares synergistic effects of technology and policy reduction measures in the coal‐fired power industry. Using 2158 coal‐fired power generators of different types at 833 coal‐fired power plants in 24 Chinese provinces as research samples, this study quantifies and assesses the synergistic effects of structural and technical emission reductions at coal‐fired power plants through top‐down analysis of structural emission reduction and bottom‐up analysis of technical emission reduction. Comparing the synergy coefficients of both types of emission reduction measures, it is determined that structural emission reduction has a significant positive synergistic effect on energy consumption, pollutant and carbon emissions, with no extra emissions and energy consumption. On the other hand, technical emission reduction results in the negative synergistic effect of CO2 emissions due to electric power consumption and chemical reactions emissions in end‐of‐pipe measures of emission control, which demonstrated that prevalent desulfurization measure WFDG synergistically led to 0.688 tons of CO2 and 5.132 MWh electric power consumption for 1 ton of SO2 removed. Therefore, the structural emission reduction is an important means for multi‐target energy conservation and emission reduction. It is necessary for technical emission reduction to reduce related negative synergistic effects while enhancing target pollutant removal. [ABSTRACT FROM AUTHOR]

This paper develops an environment input-output (EIO) model to calculate embedded carbon footprints (ECF) from a consumption perspective, based on which an analysis is conducted on the trends and spatial distribution of urban households' ECF in China. The results demonstrate that energy efficiency improvements might not definitely result in a reduction of China's ECF, which is consistent with the Jevons paradox. Survival-oriented emissions account for over 35% of China's ECF, but the percentage is declining gradually. Although development-oriented emissions only take up 15% of the total ECF, the recent years has witnessed a dramatic increase of the percentage. These findings indicate the broad scope of China's ECF. Furthermore, a significant discrepancy on the spatial distribution of ECF is observed and is attributed to the diversity of economic development stages, consumptive policies, and consumption patterns among regions. Finally, relevant policy implications are derived and discussed. [ABSTRACT FROM AUTHOR]

The rapid economic growth after the new millennium could be characterized by the reappearance of heavy industrialization and land urbanization. In the literatures, extensive studies have examined the impact of energy and emissions on the growth quality during the heavy industrialization process, but few have paid attention to the land dimension. This paper aims at studying the role of land use in changing the total-factor efficiency (TFE) in China's regional economy, together with the energy factors. The basic conclusions obtained are as follows: (1) the land and energy factors do have a statistically significant influence on the total-factor integrated efficiency (TFIE), leading to a much lower and not improved efficiency performance in the sample period. The integrated efficiency is dominated by the land factor rather than energy ones; and (2) the total-factor land efficiency (TFLE) is lower than the energy efficiency and has more room to improve. The land factor has a statistically significant influence on the total-factor energy efficiency (TFEE) but not vice versa. As compared to single-factor efficiency, the total-factor energy/land efficiency provides us a more precise measure of factor efficiency in China. [ABSTRACT FROM AUTHOR]

China is one of the largest energy consumers and CO emitters globally. The growth rate of energy consumption in China is about 6 % per year, and it consumed 21 % of the world's total energy in 2012. In recent years, the Chinese government decided to introduce several energy policy instruments to promote energy efficiency. For instance, the reduction targets for the level of energy intensity have been defined for provinces in China. However, energy intensity is not an accurate proxy for energy efficiency because changes in energy intensity are a function of changes in several socioeconomic factors. In this paper, we present an empirical analysis on the estimation of the persistent and transient energy efficiency of Chinese provinces by employing a log-log aggregate energy demand frontier model. The model is estimated by using data on 29 provinces observed over the period 2003 to 2012. Several econometric model specifications for panel data are used: the random effects model and the true random effects model along with other versions of these models. Our analysis shows that energy intensity cannot measure accurately the level of efficiency in the use of energy in Chinese provinces. Further, our empirical analysis shows that the average value of the persistent energy efficiency is around 0.81 whereas the average value of the transient energy efficiency is relatively high and shows a value of approximately 0.97. By improving the level of efficiency in the use of energy to 100 %, the total energy consumption in China would decrease by approximately 1000 Mtce, which corresponds to 25 % of total energy consumption in 2012. [ABSTRACT FROM AUTHOR]

With increases in the economy and standards of living, energy consumption has grown significantly in China, which has resulted in serious local air pollution and greenhouse gas emissions. Because both carbon dioxide (CO2) and air pollutant emissions mainly stem from fossil energy use, a co-control strategy is simulated and compared with single control in China, using an integrated assessment model (Global Change Assessment Model-Tsinghua University (GCAM-TU)) in this paper. We find that end-of-pipe (EOP) control measures play an important role in reducing air pollution in the near future, but in the long run, optimizing the energy system is an effective way to control both emissions. Reducing air pollutant might take a "free-ride" of decarbonizing the energy system. Compared with a single control of air pollutants, a co-control strategy is likely to reduce the requirement of EOP control measures. The result guides the Chinese government to consider a systemic and scientific plan for decarbonizing the energy system and co-controlling CO2 and air pollutant, in order to avoid duplicate investments in infrastructure and lockup effect. The solution could be extended to many other developing countries, such as India and Africa, which is helpful to realize the goals of United Nations (UN) Sustainable Development Agenda. [ABSTRACT FROM AUTHOR]

In order to explore the comprehensive assessment method of air quality of pollutant emission of energy consumption in China's urban internal industrial parks, based on the full consideration of the actual situation of air pollution control in Nanjing HX Industry Park, this paper selects 15 air quality assessment indicators. According to the national air quality standard, the air quality standard of Nanjing and the air quality standard of Nanjing HX Industry Park, the air quality assessment standard is determined about pollutant emission of energy consumption in Nanjing HX Industry Park. Through the technical treatment of the selected assessment indicators, the niche suitability model is introduced, and based on this, the spatial niche suitability model is reconstructed to comprehensively assess the air quality of pollutant emission of energy consumption in Nanjing HX Industry Park. The study found that the air quality of Nanjing HX Industry Park has been improved from level III in 2012 to level I in 2020. According to the assessment results, the differences of assessment results of different niche suitability models are discussed, which fully reflects the advantages of spatial niche assessment methods. The change law and influencing factors of the assessment results are further discussed. [ABSTRACT FROM AUTHOR]

Understanding the causal relationships among economic growth, energy consumption, and CO emission is important for formulating energy conservation and emission reduction policies. In this paper, we explore the causal relationships among economic growth, energy consumption, and CO emission in China during 1978-2012 by using both the linear and nonlinear causality tests. The obtained results show that the links examined by the linear and nonlinear causality tests are not all same. Both linear and nonlinear causality tests indicate a unidirectional causality from CO emission to GDP and a bi-directional causality between energy consumption and CO emission. Linear causality test indicates a unidirectional causality from energy consumption to GDP, while nonlinear causality test indicates a unidirectional causality from GDP to energy consumption. Finally, policy recommendations are proposed for achieving the target of coordinated, sustainable development of China. [ABSTRACT FROM AUTHOR]

China has a large number of rural-urban migrant workers in the 'semi-urban' states, and their consumption pattern differs from that of rural residents and urban residents. To ensure that society develops sustainably and stably, it is necessary to be concerned about the issues of migrant workers. Based on the data gathered and processed, this paper focuses on the impacts of the consumption of China's migrant workers on energy use and CO emissions using the input-output method. The results show that: the living conditions, health care and allocation of educational resources have not been effectively ensured for migrant workers. The total CO emission per capita of migrant workers is relatively low, at two-thirds of the national average and less than one-third that of urban residents. Marginal energy consumption and marginal carbon emission coefficients of migrant workers are slightly lower than the national average level, at 4.9 tce (tonne of standard coal equivalent) per million yuan and 11.6 t CO per million yuan lower than those of urban residents. The sectors of food manufacture, and production and distribution of electricity make the greatest contributions to the total carbon emissions of migrant workers, at up to 36.3 %. The citizenization of migrant workers will lead to an increase of 272 million tons of CO emissions of primary energy, and the top ten sectors, led by the sectors of electricity production and distribution, and health, will produce more than 60 % of the total increase in carbon emissions. With the acceleration of urbanization and citizenization, the total carbon emissions embodied in the consumption of migrant workers are likely to rise. Further efforts are required to control and reduce the indirect carbon emission, such as by improving energy price mechanism and optimization of the power structure. [ABSTRACT FROM AUTHOR]

This study explores how an institutional innovation in the 20th Century – Coasean bargaining - could contribute to build a low carbon China in the 21st Century. China has surpassed all nations and become the world's largest emitter of CO 2 since 2007. A time-series analysis has revealed that crude oil and coal consumption, inter alia, are the primary factors contributing to the variations in CO 2 emissions in China. To honour China's commitments in the Paris Agreement 2015, this paper, with reference to the empirical results, estimates the impacts on various sources of energy consumption before 2030. Developed upon the Coasean bargaining framework (1960), the cap-and-trade (CAT) markets have contributed to reduce the pollutants and greenhouse gas emissions in the US and EU. This paper will illustrate how the CAT market can be complementary to administrative measures for CO 2 reduction in China. It will also discuss the institutional settings and constraints of the 7 pilot CAT markets in China, and also the national one to be rolled out in 2017. [ABSTRACT FROM AUTHOR]

In the face of global warming, energy depletion, and air pollution, controlling greenhouse gas and air pollutant emissions has become an urgent task for an emerging economy. Therefore, this study investigates the synergistic relationship between haze decoupling and carbon emission decoupling in China, one representative emerging economy. Effect of synergistic decoupling is explored by decomposition model. Based on Geographically and Temporally Weighted Regression, this study also investigates spatiotemporal variation of the synergistic relationship between the two decoupling indices and the synergy effect of various factors. The main results are as follows. (1) Technological progress in CO2 is the main negative driving factor, and the ratio of potential CO2 to potential haze (potential ratio) is the main positive driving factor in the synergistic decoupling. (2) There is a synergy effect between two decoupling indices, and in the later period, the value of synergy effects tends to be flat. (3) The emission factor has the largest synergy effect. In the short term, the synergy effect of the population is greater than the energy intensity, but in the long run, the synergy effect of the energy intensity is greater than the population. These novel findings not only contribute to advancing the existing literature on synergistic emission reduction of environmental pollutions, but also merit particular attention from policy makers in the emerging economy. [ABSTRACT FROM AUTHOR]

This paper presents a forecast and analysis of population, economic development, energy consumption and CO2 emissions variation in China in the short- and long-term steps before 2020 with 2007 as the base year. The widely applied IPAT model, which is the basis for calculations, projections, and scenarios of greenhouse gases (GHGs) reformulated as the Kaya equation, is extended to analyze and predict the relations between human activities and the environment. Four scenarios of CO2 emissions are used including business as usual (BAU), energy efficiency improvement scenario (EEI), low carbon scenario (LC) and enhanced low carbon scenario (ELC). The results show that carbon intensity will be reduced by 40–45% as scheduled and economic growth rate will be 6% in China under LC scenario by 2020. The LC scenario, as the most appropriate and the most feasible scheme for China’s low-carbon development in the future, can maximize the harmonious development of economy, society, energy and environmental systems. Assuming China's development follows the LC scenario, the paper further gives four paths of low-carbon transformation in China: technological innovation, industrial structure optimization, energy structure optimization and policy guidance. [ABSTRACT FROM AUTHOR]

Based on the logarithmic mean Divisia index (LMDI) approach, this paper presents a decomposition analysis of China's energy-related industrial CO2 emissions from 1985 to 2007, as well as a comparative analysis of differential influences of various factors on six sectors. Via the decomposition, five categories of influencing factors are included: (1) Per capita GDP (PCG) was the largest positive driving factor for industrial CO2 emissions growth for all sectors in China, with the largest cumulative contribution value; Population (P), economic structure (YS) and energy structure (ES) also played a positive driving role, but with weak contributions. As the only negative inhibiting factor, energy intensity (EI) significantly reduced the energy-related CO2 emissions from industrial sectors. Meanwhile, CO2 emissions reduction based on the efficiency of energy use still held a large space. (2) Various influencing factors imposed differential impacts on CO2 emissions of six sectors. [ABSTRACT FROM AUTHOR]

As the energy supply shortage and environmental pollution have increasingly become the major obstacles to China's economic development, the Chinese government has proposed various policies to reduce energy consumption, one of which is to implement a differentiated electric power price scheme (DEPP) on the energy-intensive industries (EIs). Although it is only imposed on EIs, its indirect impact on other sectors or national economy could be profound. This paper applies an input-output (IO) model, which composes 42 sectors calibrated with data in 2002 to examine the potential impact of DEPP. The results show that DEPP would result in significant energy savings at the expense of declines in gross domestic product (GDP) and increases in consumer price index (CPI). The ancillary benefits include reduction of emissions from the energy-intensive sector. [ABSTRACT FROM AUTHOR]

European energy policy has not faced up to something about which there is increasingly little doubt: global reduction, or even stabilisation in energy use will not be achieved unless Europe and the other rich OECD countries aim at significantly curbing their energy services (heat, light, motive power, mobility and so on). The policy makers at the centre of the policy discourse on energy sustainability suffer from a form for self-deception which revolves around the equation of 'efficiency' with 'reduction' and 'sustainability', i.e., the untenable contention that technological and market efficiency alone will offset continued growth in energy services to the extent that deep reductions in energy use are possible. Many researchers and environmentalists seem to have, partly for strategic reasons, adapted to this view and thereby supported politicians in the selfdeception. In this paper we use results from India and China, with more than one third of the world population, to show how there is likely to be dramatic increases in energy use and greenhouse gas emissions in those countries over the next halfcentury. Much of this increase will be in conjunction with the development of basic services and infrastructure for homes, businesses, transport, health and public services, so that it is neither ethical nor even practical to argue for restrictions in overall energy growth in these and other developing countries. This places the onus for deep reductions in energy use on Europe, North America and the other affluent countries. The paper explores what such a change of focus would mean for policy and research agendas, and why there is friction to moving the policy envelope from 'efficiency' to also include 'sufficiency'. [ABSTRACT FROM AUTHOR]

Nighttime light data can characterize urbanization, economic development, population density, energy consumption and other human activities. Additionally, carbon dioxide (CO2) emissions are closely related to the scope and intensity of human activities. In this study, we assess the utility of nighttime light data as a powerful tool to reflect CO2 emissions from energy consumption, analyze the uncertainty associated with different nighttime light data for modeling CO2 emissions, and provide guidance and a reference for modeling CO2 emissions based on nighttime light data. In this paper, Mainland China was taken as a case study, and nighttime light datasets (the Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime light data and the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime light data) as well as a global gridded CO2 emissions dataset (PKU-CO2) were used to perform simple regressions at provincial, prefectural and 0.1° × 0.1° grid levels, respectively. The analyses are aimed at exploring the accuracy and uncertainty of DMSP-OLS and NPP-VIIRS nighttime light data in modeling CO2 emissions at different spatial scales. The improvement of nighttime light index and the potential factors influencing the effects of modeling CO2 emissions based on nighttime light datasets were also explored. The results show that DMSP-OLS is superior to NPP-VIIRS in modeling CO2 emissions at all spatial scales, and the bigger the scale, the more evident the advantages of DMSP-OLS. When modeling CO2 emissions with nighttime light datasets, not only the total amount of lights within a given statistical unit but also the agglomeration degree of lights should be taken into account. Furthermore, the geographical location and socio-economic conditions at the study site, such as gross regional product per capita (GRP per capita), population, and urbanization were shown to have an impact on the regression effect of the nighttime lights-CO2 emissions model. The regression effect was found to be better at higher latitude and longitude areas with higher GRP per capita and higher urbanization, while population showed little effect on the regression effect of the nighttime lights - CO2 emissions model. The limitation of this study is that the thresholds of potential factors are unclear and the quantitative guidance is insufficient. [ABSTRACT FROM AUTHOR]

Abstract: With increasing attention on energy shortage and global warming, bioenergy is a promising alternative energy to mitigate CO 2 emissions. Despite the environmental friendly potential, a certain quantity of bioenergy-related CO 2 is still emitted in China. This paper investigates the temporal dynamics of bioenergy-related CO 2 emissions in 2000–2010 in China, and explores the underlying influence factors based on logarithmic mean Divisia index (LMDI). Then the core results are verified with a GIS-based approach from a spacial perspective. The results show that four impact factors: emission intensity, energy structure, energy efficiency and economic development have different impacts on bioenergy-related CO 2 emissions, of which economic development is the major factor contributing to its increase, while energy efficiency is the major determinant for the decline. Per capita bioenergy-related CO 2 emissions in different areas are verified in accordance with either economic development factor or energy efficiency factor to some extent. To achieve the dual purpose of sustainable development and CO 2 emissions reduction, this paper provides a practical policy framework for rural bioenergy and economic development. [ABSTRACT FROM AUTHOR]

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]

With the growth of global population and economic development, people are facing the problem of increasing scarcity of renewable energy and unsustainable energy use. To achieve the sustainable development goals (SDGs) proposed by the United Nations, research on energy consumption efficiency has become particularly important. This research evaluates the energy consumption efficiency of 270 cities in China through an improved EBM model and finds a common phenomenon of low energy consumption efficiency in the cities, with the highest efficiency in northeast China and the lowest efficiency in eastern China. In addition, the efficiency of industrial exhaust emissions most significantly positively correlates with the efficiency of employed population and total energy consumption efficiency, while the efficiency of regional GDP does not significantly correlate with the efficiency of the two input variables. Using the LMDI method to decompose the driving factors of energy consumption efficiency in the cities, we find that the most important factor affecting energy consumption efficiency is their own energy endowment. Therefore, to improve the energy consumption efficiency of its cities, the China government should comprehensively consider factors such as regional economic development level, industrial structure, and technological level differences, formulate relevant energy-saving and emission-reduction policies, focus on optimizing the energy consumption structure, encourage technological progress and innovation, and help increase investment in science and technology. [ABSTRACT FROM AUTHOR]

Abstract: This paper analyzed the interactions among China’s economic growth and its energy consumption, air emissions and air environmental protection investment during 2000–2007. Conventional energy and emergy are applied to quantify energy consumption and emissions’ impact, respectively. The five indicators based on money, energy and emergy, including ratio of nonrenewable energy to renewable energy (RNR), energy use per unit GDP (EUPG), environmental cost per unit GDP (ECPG), impact of emissions per unit energy consumption (IEPEC), and environmental benefit per unit environmental protection investment (EBPEI), are presented to depict the relationships among economic growth and energy consumption and impact of air emissions and air environmental protection investment. The results show that energy consumption rapidly rises with China’s fast economic growth; however, energy efficiency and environmental loading intensity from energy consumption are reduced simultaneously but their improvements fall far behind economic growth rate. Impact of air emissions, mainly composed of impact of emissions on human health (especially dust), is slightly decreased. The performance of air environmental protection investment is obviously declined in the study period. Generally speaking, the conflict among economy, energy and air environment protection is slightly mitigated but still acute due to great dependence of China’s economy on fossil energy and inefficient environmental protection measures. Finally, this paper discusses the corresponding issues, and then puts forward some related suggestions. [Copyright &y& Elsevier]

Abstract: In this paper we give an overview of the situation of CO2 emissions in both Beijing and Tokyo and discuss and compare the causes for their emission changes according to decomposition based on both social activities and fuel varieties. We find that in order to enjoy a sustainable development, Beijing needs to learn from Tokyo especially in energy consumption area. At the end of the paper, the cooperation between these two metropolises is summarized. [Copyright &y& Elsevier]

Abstract: This paper, by adopting the carbon emission calculating method for all kinds of energy proposed by IPCC in 2006, calculates the amount of carbon emissions of Shandong province. It turns out that carbon emissions in Shandong increased 2.63 times, carbon emission intensity increased 2.45 times and the carbon emission intensity and the energy intensity by GDP is obvious higher than the average level of China from 1997 to 2008.Taking into account the characteristics of carbon emissions in Shandong Province, the paper tries to propose the corresponding strategies to develop low-carbon economy. [Copyright &y& Elsevier]

Abstract: Making new coal-fired power plants carbon capture ready (Carbon Capture Ready) in China has been recognised as a crucial by a number of stakeholders academics, energy companies and regional government, based on a study in EU-UK-China NZEC project. A number of publications have investigated the definition, engineering requirements, economic and finance of CCR for China. However there remain a number of questions regarding the extent to which a plant’s physical location might constrain the feasibility of CCS retrofit. To address this issue, a Geographical Information System (GIS) has been used as a tool for mapping current and planned large carbon dioxide sources in Guangdong, also illustrating potential storage sites and calculating possible carbon dioxide transportation route. This paper investigates the location factors that should be considered when locating new build CCR power plants and demonstrates the methodology of using GIS software with spatial analysis in planning new build power plant in Guangdong. A preliminary study has identified over 30 large power plants within the region, with plant locations and historical emission data collected and presented in ArcGIS. Factors such as distance to potential storage site, route of CO2 pipeline, extra space on site and potential development plan etc. were investigated in the modelling and calculated the potential source and sink solution. The study then moves on to suggest possible new build plant locations which can be easily fitted in to the current network, based on economic optimisation. The scope for future coal plant development combined with a possible nuclear plant siting plan is discussed towards the end of the paper. Guangdong province, which owns the third largest coal-fired power installed capacity out of 31 provinces, generated over 8% of China’s total electricity every year for the past 15 years. CO2 storage opportunities could be found in the surrounding South China Sea, where Guangdong has a total of 4,300 km of coastline and some small scale oil fields on shore within the region. It is also among the first places to start the national open and reform policy in China. The province is one of the richest in China, with the highest GDP among all other provinces since 1989, and the foreign trade accounts for more than a quarter of China’s total amount. It also contributes around 12 of the total national economic output. Currently, the provincial government is proposing a low carbon roadmap, which is the first of its kind in China. The work has created a totally new thinking on capture ready power plant planning. This differs from existing studies (e.g., which aim to investigate the existing carbon dioxide emission sources at specified location and provide source and sink matching analysis. Instead the study focuses on policy implementation for new build capture ready power plants. Three clusters within Guangdong province are identified as potential temporary CO2 storage hubs before transporting the gas to a long term storage site. When officials are planning new power plant locations from a capture ready perspective, the plants should not necessarily be close to storage sites in straight line, but rather should be within a reasonable distance of a cluster. Transport of the captured CO2 will not be limited to pipelines, but could be extended to road and rail tankers. Power plant parameters and storage site data were collected for this research. Public transportation, utilities, landscapes, river, land used and population data were referenced from various sources; therefore, some of the data could be out of date. Nevertheless, it should still provide enough information when deciding the location of the transport cluster. Any future work could build on the existing model with updated data. Moreover, it could fit in with the national natural gas transportation network and utility planning network to provide long term integrated energy system analysis. The paper could provide policy makers, investors and urban planning officials with a view on how conventional thermal power plant investment and planning could be optimised, using Carbon Capture Ready designs, to keep the CCS retrofitting option open. [Copyright &y& Elsevier]

Abstract: The construction of buildings has a very important impact on the environment, and the process of manufacturing and transporting of building materials, and installing and constructing of buildings consumes great energy and emits large quantity of greenhouse gas (GHG). The present paper defines four sources of GHG emissions in building construction, which are: manufacture and transportation of building materials; energy consumption of construction equipment; energy consumption for processing resources; and disposal of construction waste, and then establishes the calculation method of GHG emissions. This paper presents a case study of GHG emissions in building construction in Hong Kong. The results show that 82–87% of the total GHG emissions are from the embodied GHG emissions of building materials, 6–8% are from the transportation of building materials, and 6–9% are due to the energy consumption of construction equipment. The results also indicate that embodied GHG emissions of concrete and reinforced steel account for 94–95% of those of all building materials, and thus the use of recycled building materials, especially reinforced steel, would decrease the GHG emissions by a considerable amount. [Copyright &y& Elsevier]

Industrial SO2 is the most important air pollutant in China. This paper outlines the technological impacts on industrial SO2 emissions in China in terms of: amount, intensity, structure of energy consumption and structure of energy-intensive industries. It shows that industrial SO emissions have linear growth alongside increases in energy consumption, particularly the rise in coal consumption. The contribution of technological factors to decreases in the intensity of energy consumption is 25%, while the structural factor is 75%. The power industry accounts tor 52.6% of total industrial SO2. Optimisation of the structure of energy consumption can reduce SO2 emissions by 1.98 million tonnes per year. We propose the following technological strategies for industrial SO2 abatement: adjustment of the system and structure of thermal power generating units, acceleration of flue gas desulphurisation projects, transformation of industrial structures, development of eco-industries and a reduction in energy consumption per unit product. In addition, an effective way to abate industrial SO2 emissions is to promote governance strategies to stricly enforce SO2 emission standards, conduct emission trading, and formulate incentives for encouraging cleaner production and clean energy, development. [ABSTRACT FROM AUTHOR]

The environmental protection tax (EPT) is an important environmental policy in China. However, it remains unclear whether the EPT has reduced environmental pollution effectively since its implementation in 2018. Based on the panel data of 229 prefecture-level cities in China during 2015–2019 and the difference-in-differences (DID) model, this study empirically assesses the causal effect of the EPT on environmental pollution. It is found that the EPT has a significantly negative effect on industrial sulfur dioxide (SO2) and industrial soot (dust) emissions but has no significant impact on industrial wastewater emissions. The mechanism analysis reveals that the EPT has the tax enforcement effect and energy efficiency effect, that is, the EPT reduces pollution emissions through increasing actual tax burden and improving the efficiency of energy utilization. However, the innovation effect is weak, which is only effective in reducing industrial SO2 emissions. Finally, we compare how different types of cities responded to the EPT. The results show that the EPT has limited effect on environmental pollution in large cities and southern China. [ABSTRACT FROM AUTHOR]

There has always been controversy over how renewable energy technologies can play a role in reducing carbon emissions. Based on the energy patent data and the economic data of 244 prefecture-level cities from 2007 to 2017 in China, we explore the carbon reduction effect of renewable energy technology and its mechanism from the perspective of energy production, conservation, and management. The two-way fixed effect, instrumental variable, spatial Durbin, and mediation effect models are employed to explore empirical results. We found that (1) the impact of renewable energy technologies on carbon emissions is nonlinear, with an inverted U shape. However, this inverted U-shaped relationship only exists locally in cities and there are uncertainties in adjacent cities, which indicates that cross-regional cooperation in renewable energy technology needs to be improved. (2) The mechanism analysis shows that industrial agglomeration and energy consumption scale are the channels that renewable energy technologies affect carbon emissions. Thus, the implicit carbon emissions generated by industrial agglomeration and the failure to green upgrade energy consumption are the main reasons for the inverted U-shaped relationship. (3) The carbon reduction effect of renewable energy technologies of conservation type takes effect first, and renewable energy technologies of production type do not reduce carbon emissions in non-eastern cities, which means that non-eastern cities are likely to become pollution havens. This study provides evidence for renewable energy technologies to achieve efficient carbon emission reduction and cross-regional technical cooperation. [ABSTRACT FROM AUTHOR]

With the continuous increase in China's carbon emission reduction efforts, energy transformation and energy revolution are advancing in multiple dimensions. To optimize the energy structure and carbon emission management, researchers must conduct in-depth studies on various factors and influencing mechanisms. Based on remote sensing data, such as aerosol optical thickness and nighttime light images, and natural and socioeconomic statistical data from 2013, 2016, and 2019, this study used a multiscale geographical weighted regression model (MGWR) to study the characteristics and factors influencing energy carbon emissions and air pollution indicators in the Ningxia Hui Autonomous Region. The energy structure and energy transformation models were characterized by analyzing the scale and spatial heterogeneity characteristics of the factors influencing energy carbon emissions and air pollution in Ningxia. The research results show that for energy carbon emissions, energy consumption has changed from a global-scale variable to a small-scale variable, and per capita disposable income became the largest impact-scale variable in 2019. Energy consumption is the most significant positive index of energy carbon emissions and air pollution, followed by per capita disposable income and river network distance. The per capita GDP is a significant negative indicator. The energy transformation in the Ningxia region shows temporal differences and regional imbalance, and the air quality, energy carbon emission index, and its influencing factors in the energy transformation industrial upgrading region have significantly changed, highlighting the achievements of China's energy transformation policy and the construction of the Ningxia new energy comprehensive demonstration zone. This study analyzes the scale and spatiotemporal heterogeneity of factors influencing energy carbon emissions and air pollution indicators and has strong practical reference significance for promoting energy transformation, energy conservation, and emission reductions according to local conditions. [ABSTRACT FROM AUTHOR]

Household carbon emissions are important components of total carbon emissions. The consumer side of energy-saving emissions reduction is an essential factor in reducing carbon emissions. In this paper, the carbon emissions coefficient method and Consumer Lifestyle Approach (CLA) were used to calculate the total carbon emissions of households in 30 provinces of China from 2006 to 2015, and based on the extended Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, the factors influencing the total carbon emissions of households were analyzed. The results indicated that, first, over the past ten years, the energy and products carbon emissions from China's households have demonstrated a rapid growth trend and that regional distributions present obvious differences. Second, China's energy carbon emissions due to household consumption primarily derived from the residents' consumption of electricity and coal; China's products household carbon emissions primarily derived from residents' consumption of the high carbon emission categories: residences, food, transportation and communications. Third, in terms of influencing factors, the number of households in China plays a significant role in the total carbon emissions of China's households. The ratio of children 0–14 years old and gender ratio (female = 100) are two factors that reflect the demographic structure, have significant effects on the total carbon emissions of China's households, and are all positive. Gross Domestic Product (GDP) per capita plays a role in boosting the total carbon emissions of China's households. The effect of the carbon emission intensity on total household carbon emissions is positive. The industrial structure (the proportion of secondary industries' added value to the regional GDP) has curbed the growth of total carbon emissions from China's household consumption. The results of this study provide data to support the assessment of the total carbon emissions of China's households and provide a reasonable reference that the government can use to formulate energy-saving and emission-reduction measures. [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]

The inter-provincial inequality of per capita CO 2 emissions in China's electricity sector means that their responsibilities for CO 2 emission reduction are different. Considering the spatial separation of CO 2 emissions in power production and consumption, with respect to the large scale inter-provincial electricity trade in China, this paper innovatively investigates the sub-national inequality and polarization degree of per capita CO 2 emissions in China's electric power sector from the perspectives of both production and consumption. The overall tendencies of the sub-national polarization degrees of per capita CO 2 emissions embodied in the both electric power consumption and production in China show an increasing trend. The results indicate that the polarization distribution of per capita CO 2 emissions is still one of the important factors leading to difficulties in achieving the new reduction arrangements. The evolution of the bi-polarization analysis shows that the grouping results of per capita CO 2 emissions are different from production and consumption perspectives, as well as the high- and low-emission groups have significantly different characteristics. The inequality and polarization degree of per capita CO 2 emissions in China's electric power sector have changed as the CO 2 emissions embodied in the electricity trade had been taken into account. One-Size-Fits-All Strategies are unlikely to be successful in advancing the provincial cooperation on CO 2 emissions reduction. [ABSTRACT FROM AUTHOR]

The heat source types in China were not limited to the coal, other types of energy were introduced into the heating energy consumption in recent years, and therefore the specific regional impact of the heating emissions could not be obtained accurately according to the current achievement. Based on this, this study aimed to quantify the impact of the heating emissions on the air quality in an efficient and accurate way. A new method was proposed for investigating the quantitative impact of the heating emissions on the air quality index in this paper and its assumptions and accuracy were verified as well. The data employed in this method is extracted from Ministry of Environmental Protection Data Centre, Qingyue open source and Shanghai Central Meteorological Observatory. The key prerequisites of the proposed method were discussed in this study. By calculating, the averaged absolute difference of the meteorological parameters, namely Clo, WD, WS and P, is 3.58%, 2.40%, 3.21% and 3.94%, respectively. The difference ratio of the industrial emissions relative to the total emissions is as low as 4.3%. The optimal principal component number is six for the proposed method, which can satisfy the accuracy requirement with minimum workload. Compared with the results in previous similar studies, the proposed method showed excellent performance in analyzing the regional impact of the heating emissions on ambient air quality in China. Moreover, a total of 64 North cities in China were analyzed based on the proposed method to promote the knowledge on the influence of heating emissions on the environmental quality and the related parameters were provided in this study. [ABSTRACT FROM AUTHOR]

• A dynamic time-delay calculation algorithm based on MI and adaptive sliding window (MIDTA) is proposed. • MIDTA algorithm is used to solve the problem of long time-delay of cement kiln. • An algorithm of residual network and bidirectional novel gated recurrent unit (ResNet-BiNGRU) is proposed. • A Gaussian-weighted multi-model fusion method is proposed. • MIDTA-ResNet-BiNGRU multi-model fusion algorithm can be used to measure the temperature of cement rotary kiln with high precision. China's cement production energy consumption accounts for more than 10% of the country's total energy consumption, and its emissions account for about 60% of the country's industrial emissions. The temperature of a cement rotary kiln directly affects the quality of the final product, the energy consumption of a plant, and emissions. Therefore, it is necessary to measure, to a high degree of accuracy, the temperature of a cement rotary kiln to reduce energy consumption, emissions, and improve product quality. However, the conditions in cement kilns are complex and variable; and there are large time-delays, while temperatures are affected by historical working conditions, making temperature measurement extremely difficult. In this paper, a modelling algorithm with a residual network and a bidirectional novel gated cycle unit is used to predict the clinker exit temperature of the rotary kiln. In addition, to solve the problem of large time-delays in cement kilns, a dynamic time-delay calculation algorithm based on Mutual information and adaptive sliding windows is proposed for time series data reconstruction, and finally a Gaussian-weighted multi-model fusion is applied to the prediction results for cement rotary kilns that produce a wide range of working conditions. To verify the advantages and feasibility of the proposed method, experimental validation is carried out using original production data from a large cement manufacturing enterprise in South China. The results demonstrate that the single step prediction time of the presented approach is 0.66 s, which can predict cement kiln temperatures quickly and accurately, compared to a single conventional forecasting algorithm, the average temperature difference dropped from 11.76 °C to 3.51 °C, R2 increased from 0.43 to 0.89, 94% of the depicted temperature errors are at ± 10 °C This will provide an effective solution for online decision-making during actual cement production. [ABSTRACT FROM AUTHOR]