期刊
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
卷 55, 期 -, 页码 516-536出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.rser.2015.10.081
关键词
Industrial CO2 emissions; Extended LMDI model; Investment and R&D activities; Macroeconomic factors; Microeconomic factors; Shanghai
资金
- National Natural Science Foundation of China [71373153, 71503168, 71003068, 71461137008, 71250110083, 71325006]
- Program for New Century Excellent Talents in University [NCET-13-0890]
- Shanghai Philosophy and Social Science Fund Project [2014BJB001, 2015BJB005]
- Shuguang Program - Shanghai Education Development Foundation
- Shuguang Program - Shanghai Municipal Education Commission [14SG32]
- Key Project of Zhejiang Statistics Research Program [201527]
- Cultivation Fund Project for the Young Teachers of Shanghai University - Shanghai Municipal Education Commission
- Economic and Social Research Council [ES/L016028/1, ES/K006576/1] Funding Source: researchfish
- Natural Environment Research Council [NE/N00714X/1] Funding Source: researchfish
- ESRC [ES/K006576/1, ES/L016028/1] Funding Source: UKRI
- NERC [NE/N00714X/1] Funding Source: UKRI
Although investment and R&D activities can exert significant effects on energy-related industrial CO2 emissions (EICE), related factors have not been fairly uncovered in the existing index decomposition studies. This paper extends the previous logarithmic mean Divisia index (LMDI) decomposition model by introducing three novel factors (R&D intensity, investment intensity, and R&D efficiency). The extended model not only considers the conventional drivers of EICE, but also reflects the microeconomic effects of investment and R&D behaviors on EICE. Furthermore, talking Shanghai as an example, which is the economic center and leading CO2 emitter in China, we use the extended model to decompose and explain EICE changes. Also, we incorporate renewable energy sources into the proposed model to carry out an alternative decomposition analysis at Shanghai's entire industrial level. The results show that among conventional (macroeconomic) factors, expanding output scale is mainly responsible for the increase in EICE, and industrial structure adjustment is the most significant factor in mitigating EICE. Regardless of renewable energy sources, the emission-reduction effect of energy intensity focused on by the Chinese government is less than the expected due to the rebound effect, but the introduction of renewable energy sources intensifies its mitigating effect, partly resulting from the transmission from the abating effect of industrial structure adjustment. The effect of energy structure is the weakest. Although all the three novel factors exert significant effects on EICE, they are more sensitive to policy interventions than conventional factors. R&D intensity presents an obvious mitigating effect, while investment intensity and R&D efficiency display an overall promotion effect with some volatility. The introduction of renewable energy sources intensifies the promotion effect of R&D efficiency as a result of the green paradox effect. Finally, we propose that CO2 mitigation efforts should be made by considering both macroeconomic and microeconomic factors in order to achieve a desirable emission-reduction effect. (C) 2015 Elsevier Ltd. All rights reserved.
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