中国工业碳排放的因素分解与脱钩效应
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摘要
采用广义迪氏指数分解法(GDIM)分析2000～2016年中国工业碳排放的驱动因素,并在此基础上,创新性地结合DPSIR框架构建脱钩努力模型测度工业碳排放的脱钩效应.研究结果表明:产出规模效应、技术进步效应、能源消费规模效应和人均碳排放效应是导致工业碳排放增加的主要因素,而产出碳强度效应与技术进步碳强度效应是减少工业碳排放的关键因素;工业碳排放的脱钩效应呈"未脱钩～弱脱钩～强脱钩"的阶段性特点;产出碳强度效应与技术进步碳强度效应是工业碳排放实现强脱钩的决定性因素,同时更需要调整能源结构、降低能源强度与碳排放强度来实现工业碳排放强脱钩.
In this paper, a generalized divisia index decomposition method(GDIM) was used to analyze the driving factors of China's industrial carbon emissions from 2000 to 2016. On this basis, a decoupling effort model was innovatively constructed combing with the DPSIR framework to measure the decoupling effect of industrial carbon emissions. The empirical results showed that output scale effect, technological progress effect, energy consumption scale effect and per capita carbon emissions effect were the main factors leading to increased industrial carbon emissions, while output carbon intensity effect and technological progress carbon intensity effect were the key factors which reduce industrial carbon emissions. The decoupling effect of industrial carbon emissions was characterized by "negative decoupling～weak decoupling～strong decoupling". The output carbon intensity effect and technological progress carbon intensity effect were the decisive factors to achieve strong decoupling of industrial carbon emissions. At the same time, it was necessary to adjust energy structure, reduce energy intensity and carbon intensity to realize the strong decoupling of industrial carbon emissions.
In this paper, a generalized divisia index decomposition method(GDIM) was used to analyze the driving factors of China's industrial carbon emissions from 2000 to 2016. On this basis, a decoupling effort model was innovatively constructed combing with the DPSIR framework to measure the decoupling effect of industrial carbon emissions. The empirical results showed that output scale effect, technological progress effect, energy consumption scale effect and per capita carbon emissions effect were the main factors leading to increased industrial carbon emissions, while output carbon intensity effect and technological progress carbon intensity effect were the key factors which reduce industrial carbon emissions. The decoupling effect of industrial carbon emissions was characterized by "negative decoupling～weak decoupling～strong decoupling". The output carbon intensity effect and technological progress carbon intensity effect were the decisive factors to achieve strong decoupling of industrial carbon emissions. At the same time, it was necessary to adjust energy structure, reduce energy intensity and carbon intensity to realize the strong decoupling of industrial carbon emissions.
引文
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[3]范丹.中国能源消费碳排放变化的驱动因素研究——基于LMDI-PDA分解法[J].中国环境科学, 2013,33(9):1705-1713.Fan Dan. Driving factors of carbon emissions from energy consumption in China-based on LMDI-PDA method[J]. China Environmental Science,2013,33(9):1705-1713.
[4]孟彦菊,成蓉华,黑韶敏.碳排放的结构影响与效应分解[J].统计研究, 2013,30(4):76-83.Meng Yan-ju, Cheng Rong-hua, Hei Shao-min. Structure influence and effect decomposition of cardon emissions[J]. Statistical Research,2013,30(4):76-83.
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[7]马晓君,董碧滢,于渊博,等.东北三省能源消费碳排放测度及影响因素[J].中国环境科学, 2018,38(8):3170-3179.Ma Xiao-jun, Dong Bi-ying, Yu Yuan-bo, et al. Measurement of carbon emissions from energy consumption in three northeastern provinces and its driving factors[J]. China Environmental Science,2018,38(8):3170-3179.
[8]范建双,周琳.中国城乡居民生活消费碳排放变化的比较研究[J].中国环境科学, 2018,38(11):4369-4383.Fan Jian-shuang, Zhou Lin. A comparative study on the changes of residential living consumption carbon emissions in urban and rural China[J]. China Environmental Science, 2018,38(11):4369-4383.
[9] Vaninsky A. Factorial decomposition of CO2 emissions:A generalized Divisia index approach[J]. Energy Economics, 2014,45:389-400.
[10] Kaya Y. Impact of carbon dioxide emission on GNP growth:interpretation of proposed scenarios[R]. Paris:Presentation to the Energy and Industry Subgroup, Response Strategies Working Group,IPCC, 1989.
[11] Shao S, Liu J, Geng Y, et al. Uncovering driving factors of carbon emissions from China’s mining sector[J]. Applied Energy, 2016:S0306261916300277.
[12] Wang Y, Zhu Y, Zhu L, et al. Influencing factors and decoupling elasticity of china’s transportation carbon emissions[J]. Energies,2018,11(5):1157-1186.
[13] Zhu L, He L, Shang P, et al. Influencing factors and scenario forecasts of carbon emissions of the Chinese power industry:based on a generalized divisia index model and monte carlo simulation[J].Energies, 2018,11:2398.
[14]邵帅,张曦,赵兴荣.中国制造业碳排放的经验分解与达峰路径——广义迪氏指数分解和动态情景分析[J].中国工业经济,2017,(3):44-63.Shao Shuai, Zhang Xi, Zhao Xing-rong. Empirical decomposition and peaking pathway of carbon dioxide emissions of China’s manufacturing sector-generalized divisia index method and dynamic scenario analysis[J]. China Industrial Economics, 2017,(3):44-63.
[15]李治国,朱永梅,吴茜.山东省制造业碳排放驱动因素研究——基于GDIM方法[J].华东经济管理, 2019,33(4):30-36.Li Zhi-guo, Zhu Yong-mei, WU Xi. GDIM-based research on driving factors of carbon emissions from manufacturing industry in Shandong province[J]. East China Economic Management, 2019, 33(4):30-36.
[16]闫庆友,尹洁婷.基于广义迪氏指数分解法的京津冀地区碳排放因素分解[J].科技管理研究, 2017,37(19):239-245.Yan Qing-you, Yin Jie-ting. Factor decomposition of carbon emissions in Beijing, Tianjin, Hebei:a study based on generalized divisia index method[J]. Science and Technology Management Research, 2017,37(19):239-245.
[17]王崇梅.中国经济增长与能源消耗脱钩分析[J].中国人口·资源与环境, 2010,20(3):35-37.Wang Chong-mei. Decoupling analysis of China economic growth and energy consumption[J]. China Population, Resources and Environment, 2010,20(3):35-37.
[18] Román R, Cansino J M, Botia C. How Far is colombia from decoupling? Two-level decomposition analysis of energy consumption changes[J]. Energy, 2018,148:687-700.
[19] Wu Y, Zhu Q, Zhu B. Decoupling analysis of world economic growth and CO2 emissions:a study comparing developed and developing countries[J]. Journal of Cleaner Production, 2018,190:94-103.
[20]彭佳雯,黄贤金,钟太洋,等.中国经济增长与能源碳排放的脱钩研究[J].资源科学, 2011,33(4):626-633.Peng Jia-wen, Huang Xian-jin, Zhong Tai-yang, et al. Decoupling analysis of economic growth and energy carbon emissions in China[J].Resources Science, 2011,33(4):626-633.
[21] Freitas L C D, Kaneko S. Decomposing the decoupling of CO2emissions and economic growth in Brazil[J]. Ecological Economics,2011,70(8):1459-1469.
[22] Grand M C. Carbon emission targets and decoupling indicators[J].Ecological Indicators, 2016,67:649-656.
[23] Roinioti A, Koroneos C. The decomposition of CO2 emissions from energy use in Greece before and during the economic crisis and their decoupling from economic growth[J]. Renewable&Sustainable Energy Reviews, 2017,76:448-459.
[24]张娣.苏北地区能源消耗与经济增长的脱钩研究[D].江苏:中国矿业大学, 2014.Zhang Di. The decoupling study between energy consumption and economic growth in the northern Jiangsu area[D]. Jiangsu:China University of Mining and technology, 2014.
[25]刘惠敏.中国经济增长与能源消耗的脱钩——东部地区的时空分异研究[J].中国人口·资源与环境, 2016,26(12):157-163.Liu Hui-min. Can economic growth decouple with energy consumption:a temporal and spatial study of Eastern China[J]. China Population, Resources and Environment, 2016,26(12):157-163.
[26]徐盈之,徐康宁,胡永舜.中国制造业碳排放的驱动因素及脱钩效应[J].统计研究, 2011,28(7):55-61.Xu Ying-zhi, Xu Kang-ning, Hu Yong-shun. Driving factors and decoupling effect of carbon emissions:evidence from China's manufacturing sector[J]. Statistical Research, 2011,28(7):55-61.
[27]贺爱忠,刘盼.中国流通业CO2排放的因素分解和脱钩分析[J].中国环境科学, 2015,35(3):953-960.He Ai-zhong, Liu Pan. Factor decomposition and decoupling analysis on CO2emissions:evidence from China's circulation sector[J]. China Environmental Science, 2015,35(3):953-960.
[28]钱娟.能源节约偏向型技术进步对经济增长的影响研究[J].科学学研究, 2019,37(3):436-449.Qian Juan. The impact of energy-saving biased-oriented technological progress on economic growth[J]. Studies in Science of Science,2019,37(3):436-449.
[29]朱平芳,徐伟民.政府的科技激励政策对大中型工业企业R&D投入及其专利产出的影响——上海市的实证研究[J].经济研究,2003,(6):45-53+94.Zhu Ping-fang, Xu Wei-min. On the impact of governments S&T incentive policy on the R&D input and its patent output of large and medium-sized industrial enterprises in Shanghai[J]. Economic Research Journal, 2003,(6):45-53+94.
[30]申萌,李凯杰,曲如晓.技术进步、经济增长与二氧化碳排放:理论和经验研究[J].世界经济, 2012,35(7):83-100.Shen Meng, li Kai-jie, Qu Ru-xiao. Technological progress, economic growth and carbon dioxide emissions:Theoretical and empirical research[J]. The Journal of World Economics, 2012,35(7):83-100.
[31]金培振,张亚斌,彭星.技术进步在二氧化碳减排中的双刃效应——基于中国工业35个行业的经验证据[J].科学学研究, 2014,32(5):706-716.Jin Pei-zhen, Zhang Ya-bin, Peng Xing. The double-edged effect of technological progress in carbon dioxide emissions reduction:Empirical evidence from 35sub-industrial sectors in China[J]. Studies in Science of Science, 2014,32(5):706-716.
[2]王锋,吴丽华,杨超.中国经济发展中碳排放增长的驱动因素研究[J].经济研究, 2010,45(2):123-136.Wang Feng, Wu Li-hua, YANG Chao. Driving factors for growth of carbon dioxide emissions during economic development in China[J].Economic Research Journal, 2010,45(2):123-136.
[3]范丹.中国能源消费碳排放变化的驱动因素研究——基于LMDI-PDA分解法[J].中国环境科学, 2013,33(9):1705-1713.Fan Dan. Driving factors of carbon emissions from energy consumption in China-based on LMDI-PDA method[J]. China Environmental Science,2013,33(9):1705-1713.
[4]孟彦菊,成蓉华,黑韶敏.碳排放的结构影响与效应分解[J].统计研究, 2013,30(4):76-83.Meng Yan-ju, Cheng Rong-hua, Hei Shao-min. Structure influence and effect decomposition of cardon emissions[J]. Statistical Research,2013,30(4):76-83.
[5] González P F, Landajo M, Presno M J. Tracking European Union CO2emissions through LMDI(logarithmic-mean Divisia index)decomposition.The activity revaluation approach[J]. Energy, 2014,73(7):741-750.
[6] Cansino J M, Sánchez-Braza A, Rodríguez-Arévalo M L. Driving forces of Spain’s CO2 emissions:A LMDI decomposition approach[J].Renewable and Sustainable Energy Reviews, 2015,48:749-759.
[7]马晓君,董碧滢,于渊博,等.东北三省能源消费碳排放测度及影响因素[J].中国环境科学, 2018,38(8):3170-3179.Ma Xiao-jun, Dong Bi-ying, Yu Yuan-bo, et al. Measurement of carbon emissions from energy consumption in three northeastern provinces and its driving factors[J]. China Environmental Science,2018,38(8):3170-3179.
[8]范建双,周琳.中国城乡居民生活消费碳排放变化的比较研究[J].中国环境科学, 2018,38(11):4369-4383.Fan Jian-shuang, Zhou Lin. A comparative study on the changes of residential living consumption carbon emissions in urban and rural China[J]. China Environmental Science, 2018,38(11):4369-4383.
[9] Vaninsky A. Factorial decomposition of CO2 emissions:A generalized Divisia index approach[J]. Energy Economics, 2014,45:389-400.
[10] Kaya Y. Impact of carbon dioxide emission on GNP growth:interpretation of proposed scenarios[R]. Paris:Presentation to the Energy and Industry Subgroup, Response Strategies Working Group,IPCC, 1989.
[11] Shao S, Liu J, Geng Y, et al. Uncovering driving factors of carbon emissions from China’s mining sector[J]. Applied Energy, 2016:S0306261916300277.
[12] Wang Y, Zhu Y, Zhu L, et al. Influencing factors and decoupling elasticity of china’s transportation carbon emissions[J]. Energies,2018,11(5):1157-1186.
[13] Zhu L, He L, Shang P, et al. Influencing factors and scenario forecasts of carbon emissions of the Chinese power industry:based on a generalized divisia index model and monte carlo simulation[J].Energies, 2018,11:2398.
[14]邵帅,张曦,赵兴荣.中国制造业碳排放的经验分解与达峰路径——广义迪氏指数分解和动态情景分析[J].中国工业经济,2017,(3):44-63.Shao Shuai, Zhang Xi, Zhao Xing-rong. Empirical decomposition and peaking pathway of carbon dioxide emissions of China’s manufacturing sector-generalized divisia index method and dynamic scenario analysis[J]. China Industrial Economics, 2017,(3):44-63.
[15]李治国,朱永梅,吴茜.山东省制造业碳排放驱动因素研究——基于GDIM方法[J].华东经济管理, 2019,33(4):30-36.Li Zhi-guo, Zhu Yong-mei, WU Xi. GDIM-based research on driving factors of carbon emissions from manufacturing industry in Shandong province[J]. East China Economic Management, 2019, 33(4):30-36.
[16]闫庆友,尹洁婷.基于广义迪氏指数分解法的京津冀地区碳排放因素分解[J].科技管理研究, 2017,37(19):239-245.Yan Qing-you, Yin Jie-ting. Factor decomposition of carbon emissions in Beijing, Tianjin, Hebei:a study based on generalized divisia index method[J]. Science and Technology Management Research, 2017,37(19):239-245.
[17]王崇梅.中国经济增长与能源消耗脱钩分析[J].中国人口·资源与环境, 2010,20(3):35-37.Wang Chong-mei. Decoupling analysis of China economic growth and energy consumption[J]. China Population, Resources and Environment, 2010,20(3):35-37.
[18] Román R, Cansino J M, Botia C. How Far is colombia from decoupling? Two-level decomposition analysis of energy consumption changes[J]. Energy, 2018,148:687-700.
[19] Wu Y, Zhu Q, Zhu B. Decoupling analysis of world economic growth and CO2 emissions:a study comparing developed and developing countries[J]. Journal of Cleaner Production, 2018,190:94-103.
[20]彭佳雯,黄贤金,钟太洋,等.中国经济增长与能源碳排放的脱钩研究[J].资源科学, 2011,33(4):626-633.Peng Jia-wen, Huang Xian-jin, Zhong Tai-yang, et al. Decoupling analysis of economic growth and energy carbon emissions in China[J].Resources Science, 2011,33(4):626-633.
[21] Freitas L C D, Kaneko S. Decomposing the decoupling of CO2emissions and economic growth in Brazil[J]. Ecological Economics,2011,70(8):1459-1469.
[22] Grand M C. Carbon emission targets and decoupling indicators[J].Ecological Indicators, 2016,67:649-656.
[23] Roinioti A, Koroneos C. The decomposition of CO2 emissions from energy use in Greece before and during the economic crisis and their decoupling from economic growth[J]. Renewable&Sustainable Energy Reviews, 2017,76:448-459.
[24]张娣.苏北地区能源消耗与经济增长的脱钩研究[D].江苏:中国矿业大学, 2014.Zhang Di. The decoupling study between energy consumption and economic growth in the northern Jiangsu area[D]. Jiangsu:China University of Mining and technology, 2014.
[25]刘惠敏.中国经济增长与能源消耗的脱钩——东部地区的时空分异研究[J].中国人口·资源与环境, 2016,26(12):157-163.Liu Hui-min. Can economic growth decouple with energy consumption:a temporal and spatial study of Eastern China[J]. China Population, Resources and Environment, 2016,26(12):157-163.
[26]徐盈之,徐康宁,胡永舜.中国制造业碳排放的驱动因素及脱钩效应[J].统计研究, 2011,28(7):55-61.Xu Ying-zhi, Xu Kang-ning, Hu Yong-shun. Driving factors and decoupling effect of carbon emissions:evidence from China's manufacturing sector[J]. Statistical Research, 2011,28(7):55-61.
[27]贺爱忠,刘盼.中国流通业CO2排放的因素分解和脱钩分析[J].中国环境科学, 2015,35(3):953-960.He Ai-zhong, Liu Pan. Factor decomposition and decoupling analysis on CO2emissions:evidence from China's circulation sector[J]. China Environmental Science, 2015,35(3):953-960.
[28]钱娟.能源节约偏向型技术进步对经济增长的影响研究[J].科学学研究, 2019,37(3):436-449.Qian Juan. The impact of energy-saving biased-oriented technological progress on economic growth[J]. Studies in Science of Science,2019,37(3):436-449.
[29]朱平芳,徐伟民.政府的科技激励政策对大中型工业企业R&D投入及其专利产出的影响——上海市的实证研究[J].经济研究,2003,(6):45-53+94.Zhu Ping-fang, Xu Wei-min. On the impact of governments S&T incentive policy on the R&D input and its patent output of large and medium-sized industrial enterprises in Shanghai[J]. Economic Research Journal, 2003,(6):45-53+94.
[30]申萌,李凯杰,曲如晓.技术进步、经济增长与二氧化碳排放:理论和经验研究[J].世界经济, 2012,35(7):83-100.Shen Meng, li Kai-jie, Qu Ru-xiao. Technological progress, economic growth and carbon dioxide emissions:Theoretical and empirical research[J]. The Journal of World Economics, 2012,35(7):83-100.
[31]金培振,张亚斌,彭星.技术进步在二氧化碳减排中的双刃效应——基于中国工业35个行业的经验证据[J].科学学研究, 2014,32(5):706-716.Jin Pei-zhen, Zhang Ya-bin, Peng Xing. The double-edged effect of technological progress in carbon dioxide emissions reduction:Empirical evidence from 35sub-industrial sectors in China[J]. Studies in Science of Science, 2014,32(5):706-716.