改革开放40年中国经济增长与碳排放影响因素分析
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摘要
改革开放40年来中国经济保持高速增长,2005年中国成为全球碳排放第一大国。运用EKC和STIRPAT模型对1978年至2018年中国人均GDP和人均碳排放的关系以及影响中国碳排放的因素进行分析。结果表明:中国人均GDP和人均碳排放的关系,符合环境库兹涅茨曲线倒U型的规律和趋势;中国人均GDP和人均碳排放尚处在递增阶段;经济增长是对中国碳排放影响最大的因素,其后依次是化石燃料使用、城镇人口、可替代能源与核使用、人口总数、服务业增加值、进出口总额。通过对中国碳排放影响因素的分析,希望能为中国实现绿色、低碳和可持续发展提供理论基础。
In the past 40 years of reform and opening up, China's economy has maintained rapid growth. In 2005, China became the world's largest carbon emitter. The EKC and STIRPAT models were used to analyze the relationship between China's per capita GDP and per capita carbon emissions from 1978 to 2018 and the factors affecting China's carbon emissions. The results show that the relationship between per capita GDP and per capita carbon emissions in China is consistent with the law and trend of the inverted U-shaped environmental Kuznets curve; China's per capita GDP and per capita carbon emissions are still in an increasing stage; economic growth is the most influential to China's carbon emissions. The factors are followed by fossil fuel use, urban population, alternative energy and nuclear use, total population, value added in services, and total imports and exports. Through the analysis of the factors affecting China's carbon emissions, we hope to provide a theoretical basis for China to achieve green, low carbon and sustainable development.
In the past 40 years of reform and opening up, China's economy has maintained rapid growth. In 2005, China became the world's largest carbon emitter. The EKC and STIRPAT models were used to analyze the relationship between China's per capita GDP and per capita carbon emissions from 1978 to 2018 and the factors affecting China's carbon emissions. The results show that the relationship between per capita GDP and per capita carbon emissions in China is consistent with the law and trend of the inverted U-shaped environmental Kuznets curve; China's per capita GDP and per capita carbon emissions are still in an increasing stage; economic growth is the most influential to China's carbon emissions. The factors are followed by fossil fuel use, urban population, alternative energy and nuclear use, total population, value added in services, and total imports and exports. Through the analysis of the factors affecting China's carbon emissions, we hope to provide a theoretical basis for China to achieve green, low carbon and sustainable development.
引文
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[16]陈炜,殷田园,李红兵.1997-2015年中国种植业碳排放时空特征及与农业发展的关系[J].干旱区资源与环境,2019,33(2):37-44.
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[2] 陆旸.从开放宏观的视角看环境污染问题:一个综述[J].经济研究,2012,47(2):146-158.
[3] 宋马林,王舒鸿.环境库兹涅茨曲线的中国"拐点":基于分省数据的实证分析[J].管理世界,2011(10):168-169.
[4] 曹飞.中国省域城镇化与用水结构的空间库兹涅茨曲线拟合与研判[J].干旱区资源与环境,2017,31(3):8-13.
[5] Selden T M,Song D.Environmental quality and development:Is there a Kuznets curve for air pollution emissions?[J].Journal of Environmental Economics & Management,1994,27(2):147-162.
[6] Cole M A.Trade,the pollution haven hypothesis and the environmental Kuznets curve:examining the linkages[J].Ecological Economics,2004,48(1):71-81.
[7] Dinda S.Environmental Kuznets curve hypothesis:A survey[J].Ecological Economics,2004,49(4):431-455.
[8] Perman R,Stern D I.Evidence from panel unit root and cointegration tests that the Environmental Kuznets Curve does not exist[J].Australian Journal of Agricultural & Resource Economics,2003,47(3):325-347.
[9] Gill A,Viswanathan K K,Hassan S,The Environmental Kuznets Curve (EKC) and the environmental problem of the day[J].Renewable and Sustainable Energy Reviews,2018,81:1636-1642.
[10] 林伯强,蒋竺均.中国二氧化碳的环境库兹涅茨曲线预测及影响因素分析[J].管理世界,2009(4):27-36.
[11] 吴昊,车国庆.中国人口年龄结构如何影响了地区碳排放?-基于动态空间STIRPAT模型的分析[J].吉林大学社会科学学报,2018,58(3):67-77,204-205.
[12] 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.
[13] Liu Y,Lei W.The peak value of carbon emissions in the Beijing-Tianjin-Hebei region based on the STIRPAT model and scenario design[J].Polish Journal of Environmental Studies,2016,25(2):823-834.
[14] Shuai C,Shen L,Jiao L,et al.Identifying key impact factors on carbon emission:Evidences from panel and time-series data of 125 countries from 1990 to 2011[J].Applied Energy,2017,187:310-325.
[15] Wang C,Wang F,Zhang X,et al.Examining the driving factors of energy related carbon emissions using the extended STIRPAT model based on IPAT identity in Xinjiang[J].Renewable &Sustainable Energy Reviews,2017,67:51-61.
[16]陈炜,殷田园,李红兵.1997-2015年中国种植业碳排放时空特征及与农业发展的关系[J].干旱区资源与环境,2019,33(2):37-44.
[17] Dietz T,Rosa E A.Effects of population and affluence on CO2 emissions[J].Proceedings of the National Academy of Sciences,1997,94(1):175-179.
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