期刊
JOURNAL OF CLEANER PRODUCTION
卷 166, 期 -, 页码 1335-1346出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2017.08.136
关键词
Decomposition analysis; PDA approach; IDA method; Biennial Shephard distance functions
资金
- National Natural Science Foundation of China [71633006]
- National Social Science Foundation of China [13ZD024, 13ZD169, 14ZDB136]
Because industrial sector in China is energy-intensive, clarifying the main factors driving CO2 emissions in this sector is of great importance for the carbon emission reduction and further sustainable development of China's economy. This paper combines production-theoretical decomposition analysis (PDA) and index decomposition analysis (IDA) to decompose China's industrial CO2 emission changes into seven factors: energy mix change, potential energy intensity change, economic activity, energy usage efficiency, energy saving technology change, GDP technical efficiency, and GDP technology change. The main findings are as follows: (1) during 2000-2015, industrial CO2 emissions increased 2.6560 times, economic activity was the largest contributor to increasing industrial CO2 emissions but varied significantly across provinces. (2) GDP technology change and potential energy intensity change were the dominant contributors to industrial CO2 mitigation. However, in several western provinces, potential energy intensity change played a positive role in increasing CO2 emissions. Therefore, local governments should adopt effective measures to improve technology levels in western provinces. (3) Energy-saving technology change also led to a reduction in CO2 emissions in most provinces, although its inhibiting effect was very small (annual average decrease rates were less than 3%). (4) Energy mix change, energy usage efficiency, and GDP technical efficiency played insignificant roles in affecting industrial CO2 emissions and had mixed results across provinces. This detailed information about the factors driving industrial CO2 emissions will be important for central and local governments in China in formulating emission-reduction policies. (C) 2017 Elsevier Ltd. All rights reserved.
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