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  • Title: The environmental effect of capacity utilization in thermal power plants: evidence from interprovincial carbon emissions in China.
    Author: Wang Y, Chen J.
    Journal: Environ Sci Pollut Res Int; 2019 Oct; 26(29):30399-30412. PubMed ID: 31440971.
    Abstract:
    As the largest emitter of CO2 emissions, the installed capacity of thermal power generation in China is facing more and more strict restrictions, since the Chinese government proposed to dissolve overcapacity and intends to solve the problem of continuous reduction in utilization rate of electricity sector. Regretfully, the impact of power-generating capacity and its utilization on carbon emissions in the power sector has not yet been addressed. In this study, we incorporate the interaction between capacity and utilization of power sector into the dynamic spatial Durbin model, and estimate the specific impact on carbon dioxide emissions from the power sector based on the panel data set of China's provinces during 1991-2015. The results show that both installed capacity and utilization rate have positive effects on CO2 emissions. Interestingly, the estimation coefficient of their interaction term is negative, implying that the carbon emission reduction effect derives from the conflicting performance of capacity governance and utilization efficiency. Besides, the advantage of the emerging econometric method, the dynamic spatial Durbin model (SDM) with provinces and time-period fixed effects, is that it can estimate spatial interaction effects among the provinces and neighboring provinces and decompose those effects into two parts: long-term and short-term. However, the estimates indicate that only capacity has roughly significant spatial spillovers. As a result, dissolving overcapacity of thermal power generation and a necessary interprovincial coordination will promote carbon emission reduction rather than investing in coal-fired power plants, and the power authority should turn to alternative investment in cleaner power generation technologies.
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