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Examining the synergistic effect of CO2 emissions on PM2.5 emissions reduction: Evidence from China

Dong, Feng, Yu, Bolin, Pan, Yuling
Journal of cleaner production 2019 v.223 pp. 759-771
carbon, carbon dioxide, climate change, coal, econometrics, economic development, emissions factor, greenhouse gas emissions, models, particulates, pollutants, pollution control, population density, synergism, China
Under the background of global climate change, China has been confronted with the dual pressure of CO2 emissions reduction and PM2.5 pollution control. This research aims to explore the mechanism of changes in PM2.5 emissions, which are the key airborne pollutants causing haze. Furthermore, it quantifies the impacts of CO2 emissions reduction activities on PM2.5 emissions reduction. This study takes aggregate PM2.5 emissions instead of PM2.5 concentration index as the research object. Based on an extended kaya identity, LMDI approach is first performed to decompose the changes of PM2.5 emissions during 1998–2014, taking into consideration the synergistic effect of carbon emissions on PM2.5 emissions. Furthermore, following LMDI decomposition, this study adopts the econometric methods to quantify the synergistic effect of CO2 emissions reduction on PM2.5 emissions reduction over the period 1999–2014. The empirical results are as follows: (1) the LMDI decomposition results specify that the synergistic emissions reduction accounts for the most of the reduction in PM2.5 emissions. In addition, energy intensity changes also contribute to the reduction in PM2.5 emissions; (2) by contrast, it is found that the economic development effect is the main factor resulting in the increase of PM2.5 emissions, while the contributions of the energy emission intensity effect and population effect to PM2.5 emissions changes are relatively little; (3) all the models show CO2 emissions reduction activities will significantly contribute to PM2.5 emissions reduction; (4) for every 10,000 t increase in CO2 emissions reduction, PM2.5 emissions reduction will increase by 3.3 t, and the potential for synergistic emissions reduction of PM2.5 differs distinctly among different provinces; (5) technological progress and population density positively influence PM2.5 emissions reduction, while coal consumption rate has a negative impact on PM2.5 emissions reduction, in addition, there is an inverted U-shaped curve relationship between per capita GDP and PM2.5 emissions reduction.