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Using an extended LMDI model to explore techno-economic drivers of energy-related industrial CO2 emission changes: A case study for Shanghai (China)

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  • Shao, Shuai
  • Yang, Lili
  • Gan, Chunhui
  • Cao, Jianhua
  • Geng, Yong
  • Guan, Dabo

Abstract

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, taking 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.

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  • Shao, Shuai & Yang, Lili & Gan, Chunhui & Cao, Jianhua & Geng, Yong & Guan, Dabo, 2016. "Using an extended LMDI model to explore techno-economic drivers of energy-related industrial CO2 emission changes: A case study for Shanghai (China)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 516-536.
    • Handle: RePEc:eee:rensus:v:55:y:2016:i:c:p:516-536
    DOI: 10.1016/j.rser.2015.10.081
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