Decomposition analysis of China's CO 2 emissions (2000-2016) and scenario analysis of its carbon intensity targets in 2020 and 2030
To address the unprecedented increase in China's CO emissions over the past decades, the Chinese government has implemented many policies that are aimed at reducing carbon intensity. Applying the LMDI method, this study conducts a decomposition analysis of the drivers influencing China's C...
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Veröffentlicht in: | The Science of the total environment 2019-06, Vol.668, p.432 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
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Zusammenfassung: | To address the unprecedented increase in China's CO
emissions over the past decades, the Chinese government has implemented many policies that are aimed at reducing carbon intensity. Applying the LMDI method, this study conducts a decomposition analysis of the drivers influencing China's CO
emissions by examining the details of 41 industry sub-sectors during 2000-2016; further, it predicts the carbon intensity reduction potential in 2020 and 2030 based on various official policies and documents. We conclude that energy intensity was the primary indicator that reduced CO
emissions, whereas the effects of carbon intensity, energy mix, and industrial structure were relatively minor. During the study period, the effect of industrial structure optimization on the change in CO
emissions shifted from the promotion of emissions to their suppression, with the inhibiting influence becoming greater over time. Finally, scenario analysis indicated that CO
intensity would decrease 21.5% by 2020 compared to the 2015 level, and the reduction target of 65% would be achieved fully in 2030 in the outlook scenario. Energy intensity is the largest contributor to the decrease in CO
emissions during 2016-2020, whereas industrial structure optimization shows the greatest potential for environmental improvement during 2020-2030. This paper concludes that more stringent policies are essential to reducing CO
emissions in the near future. |
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ISSN: | 1879-1026 |
DOI: | 10.1016/j.scitotenv.2019.02.406 |