4.7 Article

What matters for carbon emissions in regional sectors? A China study of extended STIRPAT model

期刊

JOURNAL OF CLEANER PRODUCTION
卷 180, 期 -, 页码 595-602

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2018.01.116

关键词

CO2 emissions; Extended STIRPAT model; Climatic factor; Zhejiang Province

资金

  1. National Natural Science Foundation of China [41371188]
  2. Philosophy and social sciences study foundation of Zhejiang Province [18NDJC196YB]
  3. Zhejiang business research center foundation [17ZSJD04YB]
  4. Remote sensing Lab in UC, Davis

向作者/读者索取更多资源

The surge in energy consumption and CO2 (carbon dioxide) emissions is exacerbating global warming. The Chinese government has promised to reduce CO2 emission by 60%-65% per unit of GDP over the 2005 level by around 2030. Analyzing the factors influencing CO2 emissions is one of the key aspects involved in effectively reducing greenhouse gas emissions. In this paper, we add climatic factors based on socio-economic factors, and adopt the extended STIRPAT model to investigate the mechanism driving emissions by the co-action of natural and socio-economic factors. The results show that the 1995-2014 emissions in China's Zhejiang province had an upward trend with growth rates varying between intermediate periods. The order of the factors' elasticity coefficients is urbanization rate (0.181) > GDP per capita (0.180) > population (0.177) > energy intensity (0.170) > trade openness (0.170) > cooling degree days (0.127) > mean temperature anomaly (0.116). Economic development and urbanization were the main factors promoting CO2 emissions in 1996-1999, while economic development and foreign trade were the main factors in 2000-2014. Policy makers should pay more attention to keeping a healthy pace of economic development, introducing more low energy consumption and low pollution enterprises and encouraging technological innovation. Improving the quality of urbanization, guiding a sustainable lifestyle, adjusting the structure of foreign trade and curbing energy intensity are also expected to reduce emissions. (C) 2018 Elsevier Ltd. All rights reserved.

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