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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]

As an effective technology to reduce traffic pollution emissions, the new energy vehicle industry has developed rapidly in recent years, and the sales of new energy vehicles have doubled in 2021. Accurately forecasting methods provide important references for industrial policy deployment, infrastructure construction and energy demand estimation. In order to predict the development trend of China's new energy vehicle industry under the limited data samples, this paper proposes an optimized discrete grey power model to fit the nonlinear relationship between grey information factor and temporal factor. Firstly, the grey differential equation and its discrete form are directly constructed by using power accumulated data, which simplifies the integral solution process of the traditional grey power model. Secondly, fractional accumulation operator is introduced into the discrete model to ensure the new information priority of the original data. Then, the heuristic algorithm is used to accurately estimate the new parameters of the proposed model. Thirdly, the proposed discrete model is the unified form of two existing discrete grey power models, which expands the scope of modeling and has higher adaptability. Simulation experiments and two numerical cases are used to verify the effectiveness of the proposed method. Finally, the proposed method is used to predict the annual sales and ownership of new energy vehicles in China. The predicted results show that by 2025, China's new energy vehicle sales will reach 8.84 million, accounting for about 24% of the total vehicle sales, surpassing the industry development target (20%) set by the Chinese government. [ABSTRACT FROM AUTHOR]

Municipal heating by coal contributes considerably to the haze pollution in Chinese cities during cold period, e.g., Beijing 53%. It is widely considered that, as a supplement of natural gas, the use of coal-based synthetic natural gas (SNG) to replace coal for municipal heating is conductive to mitigate the haze pollution in metropolitan areas. Would it still be a good alternative if the whole life cycle of SNG were taken into consideration? In this study, SNG as an alternative for municipal heating is analyzed in comparison with coal. To target cleaner production, life cycle assessment methodology is used to analyze SNG contribution to haze pollutants and greenhouse gases (GHGs) emissions, as well as energy consumption. Compared to coal heating route, SNG heating route could reduce 44% of the haze pollutants emissions from life cycle perspective and up to 98% of the emissions in urban area. Thus, if municipal heating were entirely supplied by natural gas and SNG, there would be 52% less haze pollutants emissions in winter of Beijing. However, this “good” performance is at the cost of transferring haze pollutants emissions from urban areas to SNG-producing regions. It is also at the cost of consuming 90% more coal and emitting 65% more GHGs than the coal heating route from life cycle point of view. To tackle the problems of haze pollutants transfer and the increase of GHGs emissions, the paper suggests implementing ecological compensation and carbon tax policies in the coal-based SNG industry. [ABSTRACT FROM AUTHOR]

Pollution emissions have become a matter of public concern in recent years. However, the vast majority of existing researches on PM 2.5 pollution are from the natural science perspective, and few studies have been conducted from an economic point of view. This paper adopts provincial panel data from 2001 to 2012 and panel data models to analyze the key driving forces of PM 2.5 emissions at the regional level in China. The results show that economic growth is a decisive factor of PM 2.5 emissions. The impacts of urbanization on PM 2.5 emissions vary across regions and decrease continuously from the central region to the western and eastern regions. The effects of private cars and coal consumption on PM 2.5 emissions in the eastern region are greater than that in the central and western regions because of significant differences in R&D investment, private car ownership and total coal consumption. Energy efficiency improvement has greater potential to mitigate PM 2.5 emissions in the central and western regions than that in the eastern region due to its low level of technology. Hence, in order to effectively reduce emissions, the Chinese government should consider all these factors as well as regional heterogeneity in developing appropriate mitigation policies. [ABSTRACT FROM AUTHOR]

Carbon Capture and Storage (CCS) has been viewed as an emission abatement option with great potential in China as coal has dominated China's energy consumption. China has already started to pay attention to CCS, as well as to the proposed the concept of ‘CCUS’ (which adds CO 2 Utilization into the chain of capture, transportation and storage). However, CCS is still in the early stages of its technological development, and the high cost, with several internal and external uncertainties make the role that CCS can play in China's future emission reduction unclear. From the perspective of general equilibrium analysis, this paper introduces CCS into a regional energy–economy–environment integrated assessment model, and makes a comprehensive evaluation of CCS's potential for future development and contribution to emission abatement in China. At climate policy level, the potential contribution of CCS in emission abatement has been evaluated against different future emission constraint scenarios in China. At technological level, the effects of endogenous learning and policy incentives on CCS have been investigated, and the substitution capacities of CCS and Non-hydro renewables to fossil energy have been discussed, as well as their technology penetration rates. Furthermore, the impact of CO 2 utilization on the development of CCS has also been discussed. [ABSTRACT FROM AUTHOR]

Abstract: Reducing environmental pressure is a major concern for China but despite the improvements in energy efficiency, its gross carbon dioxide (CO2) emissions have maintained an upward trend, consistent with the Jevons Paradox. A fundamental shift is thus needed at all levels, including the household. This paper explores the embedded carbon footprint (ECF) of Chinese urban households associated with activities, such as food, personal transport, communications, education, recreation, health and hygiene. It uses an input–output model for carbon emissions and 2003–2009 urban household data. The results show that the total ECF emission intensity increases when an individual''s consumption is higher than 10,000 Yuan (¥). Structural changes are further observed with consumption expenditure above ¥10,000: food, clothing and other survival-oriented emissions intensities as well as education, health and development-oriented emissions intensities reduce; transport, recreation, housing and enjoyment-oriented emissions intensities increase or remain stable and the total emissions intensity increases. Currently per capita consumption expenditure of Chinese urban residents exceeds ¥10,000 and as income continues to rise, China will remain on a high-carbon track. There is a need for better policies, management and behavioural change and the study provides some policy suggestions, including a carbon quota system to guide individual consumption. [Copyright &y& Elsevier]

Abstract: In China, Rapid economic growth has stimulated fast urban expansion and rural household income and consumption expenditure. In current paper, an input–output method is used to determine the impact of China’s increased urban and rural household consumption on carbon emissions. The results shows that the direct and indirect CO2 emission from household consumption accounted for more than 40% of total carbon emissions from primary energy utilization in China in 1992–2007. The population increase, expansion of urbanization and the increase of household consumption per capita all contribute to an increase of indirect carbon emissions, while carbon intensity decline mitigates the growth of carbon emissions. Therefore, at the domestic level, household consumption is of great significance for CO2 emission, which could be mitigated through changing the composition of goods and services consumed by households, and switching to consumption pattern of less carbon-intensive products. The government must consider the substantial contribution of household consumption to carbon emissions when China is encouraging consumption in order to address the current global financial crisis. [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]

The compression of the industrialization process has forced China to confront the double pressure of greenhouse gas emissions and air pollution. This paper constructs an energy system optimization model for China's power industry; establishes four energy consumption scenarios with different constraints; and forecasts and analyses the energy consumption structure, power consumption demand and production composition of China's power industry from 2020 to 2050. Furthermore, based on synergistic effects, the emission characteristics, emission reduction potential and costs of CO 2 and air pollutants are quantitatively analysed, and the obtained synergistic emission reduction effect and influencing factors are decomposed based on technical effect and structural effect. Finally, a low-carbon emission reduction path that can realize the synergistic control of CO 2 and traditional air pollutants in China's power industry is obtained. The results show that in the future, China's power industry will continue to grow at a greater rate than primary energy consumption and the focus of power demand will gradually shift from industry to transportation and construction. The power industry can introduce and maximize the application of optimal control technologies while optimizing the energy consumption structure in order to realize synergistic emission reduction for CO 2 and traditional air pollutants in China's power industry. While saving energy, the corresponding cost of emission reduction will remain relatively low. After CO 2 emissions peak in the power industry, the main way to reduce CO 2 emissions will be to optimize the structure and upgrade the technology for CO 2 self-governance. For the reduction of air pollutants, the promotion effect is limited only by the implementation and promotion of structural emission reduction measures focused on non-fossil energy. Image 1 • A bottom-up energy system optimization model for China's electric power industry. • Energy consumption scenarios with different constraints. • Synergistic control path by structure optimization and control technology upgrading. • Emissions characteristics, reduction potential and cost are quantitatively analysed. • Synergistic emission reduction effect and influencing factors are decomposed. [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]

On the basis of literature review and current situation analysis, models were established to carryout scientific measurement for carbon emissions and its intensity in China in this paper. With full consideration to the actual situation of energy consumption growth and carbon emission intensity controlling of energy consumption in new-type urbanization construction, the Kaya model was revised. With population intensity of GDP production, urbanization rate, employment rate of urban population, per capita energy consumption of urban employed population and carbon emission density of energy consumption selected as independent variables, test models of multivariate linear correlation were established for new-type urbanization construction, energy consumption growth and carbon emission intensity controlling of energy consumption, and the empirical equilibrium equation and error correction equation were determined through stability test, lag order test and co-integration test. The results are shown as follows: the urban employment rate (UER) has the greatest impact on carbon emission intensity, the per capita urban employment energy consumption (PEC) has the least impact on carbon emission intensity, and the degree of other factors in proper order is: urbanization rate (UR), population intensity of GDP production (PG) and carbon emission density (CD). Image 10106 • Energy consumption is the main source of China's carbon emissions and environmental pollution. • China's urbanization has contributed to the reduction of energy consumption and carbon emission intensity. • The change law of energy consumption carbon emission intensity in China's urbanization construction is analyzed. • Kaya model was adopted to study the influencing factors of carbon emission intensity control. [ABSTRACT FROM AUTHOR]