The Experts below are selected from a list of 174378 Experts worldwide ranked by ideXlab platform
Peng Zhou - One of the best experts on this subject based on the ideXlab platform.
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Effects of Carbon Emission transfer on economic spillover and Carbon Emission reduction in China
Journal of Cleaner Production, 2016Co-Authors: Licheng Sun, Qunwei Wang, Peng Zhou, Faxin ChengAbstract:Abstract Accurately understanding the spatial features of regional Carbon Emission transfer and clearly identifying economic spillover effects and Emission reduction effects are important in guiding reasonable regional Carbon Emission transfer and promoting sustainable regional economic development. This study firstly calculated China's total provincial Carbon Emission import and export. Then, the Moran's I index and a geographical weighted regression model were used to illustrate the spatial features of provincial Carbon Emission transfer and its economic spillover effects. Finally, the reduction effects of provincial Carbon Emission were analyzed and optimization strategies of Carbon Emission transfer structure for China's provinces were proposed. The results show that: 1) The transfer amount of Carbon Emission in most provinces is relatively large, and on the whole, the Carbon Emission import is higher than the export. 2) Spatial cluster is a characteristic of the provincial Carbon Emission transfer in China, and the Moran's I index of Carbon Emission import and export is 0.17 and 0.14, respectively. 3) The Carbon Emission transfer in the developed central and eastern regions of China displays a High–High pattern; but a Low–Low pattern is displayed in the underdeveloped central and western regions; for the central regions, the transfer displayed mainly a Low-High or High-Low pattern. 4) The economic spillover effects of the Carbon Emission transfer can be classified into five different types. Generally, the economic spillover effects of the Carbon Emission import are greater than that of the export. 5) Carbon Emission transfer can reduce the coal consumption in 18 provinces and help those provinces continue to maintain cleaner production modes.
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total factor Carbon Emission performance a malmquist index analysis
Energy Economics, 2010Co-Authors: Peng Zhou, B W Ang, J Y HanAbstract:Abstract This paper introduces a Malmquist CO 2 Emission performance index (MCPI) for measuring changes in total factor Carbon Emission performance over time. The MCPI is derived by solving several data envelopment analysis models. Bootstrapping MCPI is proposed to perform statistical inferences on the MCPI results. Using the index the Emission performance of the world's 18 top CO 2 emitters from 1997 to 2004 is studied. The results obtained show that the total factor Carbon Emission performance of the countries as a whole improved by 24% over the period and this was mainly driven by technological progress. The results of a cross-country regression analysis to investigate the determinants of the resulting MCPI are presented.
Licheng Sun - One of the best experts on this subject based on the ideXlab platform.
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inter industrial Carbon Emission transfers in china economic effect and optimization strategy
Ecological Economics, 2017Co-Authors: Licheng Sun, Qunwei Wang, Jijian ZhangAbstract:Understanding inter-industrial Carbon Emission transfers and their economic effect informs approaches to achieve Emission reduction objectives and promote industrial economic development. This paper applies input-output theory to explore ways to optimize Carbon Emission transfers between industrial sectors. First, China's inter-industrial Carbon Emission imports and exports were measured for years 2002, 2005, 2007, and 2010. Next, the economic effects of inter-industrial Carbon Emission transfers were assessed. Finally, strategies to optimize the Carbon Emission transfer structure were proposed, with the goal of achieving a win-win between industrial Carbon Emission reduction and economic development. Key study conclusions are as follows. (1) Inter-industrial Carbon Emission imports and exports in China are significant, and are increasing each year. Traditional energy industries have high Carbon Emission imports; processing and manufacturing industries have high Carbon Emission exports; and most light industries have relatively low levels of both Carbon Emission imports and exports. (2) Carbon Emission transfer imports or exports can promote industrial development; combining both imports and exports leads to variable economic effects within specific industries. (3) To achieve the dual goals of Carbon Emission reduction and economic development, four strategies are proposed to optimize Carbon Emission transfer structures in different industries.
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Effects of Carbon Emission transfer on economic spillover and Carbon Emission reduction in China
Journal of Cleaner Production, 2016Co-Authors: Licheng Sun, Qunwei Wang, Peng Zhou, Faxin ChengAbstract:Abstract Accurately understanding the spatial features of regional Carbon Emission transfer and clearly identifying economic spillover effects and Emission reduction effects are important in guiding reasonable regional Carbon Emission transfer and promoting sustainable regional economic development. This study firstly calculated China's total provincial Carbon Emission import and export. Then, the Moran's I index and a geographical weighted regression model were used to illustrate the spatial features of provincial Carbon Emission transfer and its economic spillover effects. Finally, the reduction effects of provincial Carbon Emission were analyzed and optimization strategies of Carbon Emission transfer structure for China's provinces were proposed. The results show that: 1) The transfer amount of Carbon Emission in most provinces is relatively large, and on the whole, the Carbon Emission import is higher than the export. 2) Spatial cluster is a characteristic of the provincial Carbon Emission transfer in China, and the Moran's I index of Carbon Emission import and export is 0.17 and 0.14, respectively. 3) The Carbon Emission transfer in the developed central and eastern regions of China displays a High–High pattern; but a Low–Low pattern is displayed in the underdeveloped central and western regions; for the central regions, the transfer displayed mainly a Low-High or High-Low pattern. 4) The economic spillover effects of the Carbon Emission transfer can be classified into five different types. Generally, the economic spillover effects of the Carbon Emission import are greater than that of the export. 5) Carbon Emission transfer can reduce the coal consumption in 18 provinces and help those provinces continue to maintain cleaner production modes.
Yuejun Zhang - One of the best experts on this subject based on the ideXlab platform.
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energy efficiency Carbon Emission performance and technology gaps evidence from cdm project investment
Energy Policy, 2018Co-Authors: Yuejun Zhang, Junling HuangAbstract:Measuring the energy conservation and Carbon Emission reduction potential proves the fundamental basis for stakeholders in the cooperation over Clean Development Mechanism (CDM) projects. This research adopts the meta-frontier non-radial directional distance function based on the Data Envelopment Analysis (DEA) window analysis to measure the total factor energy efficiency and Carbon Emission performance of leading countries involved in CDM projects during 1990–2015. This study employs the panel quantile regression to investigate the dynamic impact of CDM projects on different energy efficiency and Carbon Emission performance of CDM host countries. The results indicate that, first of all, the total factor energy efficiency and Carbon Emission performance of CDM host countries appear much lower than those of investment countries. Second, the technology gap of energy-use and Carbon Emissions reduction between CDM host and investment countries is significant. Finally, with the increase of total factor energy efficiency and Carbon Emission performance in CDM host countries, the impact of CDM projects on their energy efficiency is always negative, and that on their Carbon Emission performance gradually varies from positive to negative, meaning that CDM projects are not necessarily helpful to improve the energy efficiency and Carbon Emission performance in host countries.
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Carbon Emission quota allocation among china s industrial sectors based on the equity and efficiency principles
Annals of Operations Research, 2017Co-Authors: Yuejun Zhang, Junfang HaoAbstract:The Carbon Emission of China’s industry accounts for more than 70 % of the total in the nation, thus the implementation of Carbon Emission quota trading in industry is of great importance to realize China’s national Carbon Emission reduction targets. Meanwhile, the allocation of Carbon Emission quota among sectors or enterprises proves the first and critical step. For this reason, this paper constructs a comprehensive index combined with the subjective, objective and linear combination weighting methods to allocate Carbon Emission quotas among the 39 sectors of China’s industry in 2020 based on the level of 2015, and employs the input-oriented ZSG-DEA model to examine the efficiency of allocation solutions in 2020. The results indicate that, first, when Carbon Emission reduction capacity, responsibility and potential are considered for the comprehensive index of Carbon Emission quota allocation, the mitigation responsibility plays a relatively higher role than other two indicators. Second, all of the subjective, objective and linear combination weighting methods can be used for effective allocation of Carbon Emission quotas, and the former two methods have less advantage in light of efficiency. Third, six key industrial sectors are respectively allocated over 500 million tonnes of Carbon Emission quotas in 2020, which together account for 91.77 % of the total in the industry. Finally, the final Carbon Emission quota allocation solution reflects both the equity and efficiency principles and achieve the Pareto optimal state.
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The allocation of Carbon Emission intensity reduction target by 2020 among provinces in China
Natural Hazards, 2015Co-Authors: Yuejun ZhangAbstract:According to the combined principles of fairness and efficiency, a comprehensive allocating indicator system is developed, and the TOPSIS approach is applied to allocate China’s 40–45 % Carbon Emission intensity (Carbon Emission per unit of GDP) reduction target by 2020. The results indicate that, first of all, the unequally weighted indicator system outperforms the equally weighted one according to regional developing situation in China; and the most important indicator affecting the allowance allocation is Carbon reduction responsibility, followed by future development right and Emission reduction efficiency. Second, China’s Carbon Emission intensity should be cut, but its absolute Carbon Emission volume may inevitably increase in the future due to the continuous economic growth, and we confirm that the western provinces may take the highest shares to increase Carbon Emissions, followed by the central, northeast and eastern provinces. Finally, in order to achieve the national target of Carbon Emission intensity reduction, the northeast and eastern provinces require reducing Carbon Emission intensity significantly from 2013 to 2020, while the central and western provinces should be given more developing room.
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the impact of economic growth industrial structure and urbanization on Carbon Emission intensity in china
Natural Hazards, 2014Co-Authors: Yuejun Zhang, Huan ZhangAbstract:China’s macroeconomic policy framework has been determined to ensure steady growth, adjust the industrial structure and advance the socioeconomic reforms in recent years. And urbanization is supposed to be one of the most important socioeconomic reform directions. Meanwhile, China also committed to reduce Carbon Emissions intensity by 2020, then it should be noted that what kind of impact of these policy orientations on Carbon Emission intensity. Therefore, based on the historical data from 1978 to 2011, this paper quantitatively studies the impact of China’s economic growth, industrial structure and urbanization on Carbon Emission intensity. The results indicate that, first, there is long-term cointegrating relationship between Carbon Emission intensity and other factors. And the increase in the share of tertiary industry [i.e., the ratio of tertiary industry value added to gross domestic product (GDP)] and economic growth (here we use the real GDP per capita) play significant roles in curbing Carbon Emission intensity, while the promotion of population urbanization (i.e., the share of population living in the urban regions of total population) may lead to Carbon Emission intensity growth. Second, there exists significant one-way causality running from the urbanization rate and economic growth to Carbon Emission intensity, respectively. Third, among the three drivers, economic growth proves the main influencing factor of Carbon Emission intensity changes during the sample period.
J Y Han - One of the best experts on this subject based on the ideXlab platform.
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total factor Carbon Emission performance a malmquist index analysis
Energy Economics, 2010Co-Authors: Peng Zhou, B W Ang, J Y HanAbstract:Abstract This paper introduces a Malmquist CO 2 Emission performance index (MCPI) for measuring changes in total factor Carbon Emission performance over time. The MCPI is derived by solving several data envelopment analysis models. Bootstrapping MCPI is proposed to perform statistical inferences on the MCPI results. Using the index the Emission performance of the world's 18 top CO 2 emitters from 1997 to 2004 is studied. The results obtained show that the total factor Carbon Emission performance of the countries as a whole improved by 24% over the period and this was mainly driven by technological progress. The results of a cross-country regression analysis to investigate the determinants of the resulting MCPI are presented.
Faxin Cheng - One of the best experts on this subject based on the ideXlab platform.
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Effects of Carbon Emission transfer on economic spillover and Carbon Emission reduction in China
Journal of Cleaner Production, 2016Co-Authors: Licheng Sun, Qunwei Wang, Peng Zhou, Faxin ChengAbstract:Abstract Accurately understanding the spatial features of regional Carbon Emission transfer and clearly identifying economic spillover effects and Emission reduction effects are important in guiding reasonable regional Carbon Emission transfer and promoting sustainable regional economic development. This study firstly calculated China's total provincial Carbon Emission import and export. Then, the Moran's I index and a geographical weighted regression model were used to illustrate the spatial features of provincial Carbon Emission transfer and its economic spillover effects. Finally, the reduction effects of provincial Carbon Emission were analyzed and optimization strategies of Carbon Emission transfer structure for China's provinces were proposed. The results show that: 1) The transfer amount of Carbon Emission in most provinces is relatively large, and on the whole, the Carbon Emission import is higher than the export. 2) Spatial cluster is a characteristic of the provincial Carbon Emission transfer in China, and the Moran's I index of Carbon Emission import and export is 0.17 and 0.14, respectively. 3) The Carbon Emission transfer in the developed central and eastern regions of China displays a High–High pattern; but a Low–Low pattern is displayed in the underdeveloped central and western regions; for the central regions, the transfer displayed mainly a Low-High or High-Low pattern. 4) The economic spillover effects of the Carbon Emission transfer can be classified into five different types. Generally, the economic spillover effects of the Carbon Emission import are greater than that of the export. 5) Carbon Emission transfer can reduce the coal consumption in 18 provinces and help those provinces continue to maintain cleaner production modes.