TY - JOUR
T1 - Dynamic efficiency evaluation of electric power and environmental treatment efficiency in China
AU - Li, Y.
AU - Chiu, Y.
AU - Lin, T. Y.
AU - Wang, S. M.
AU - Chang, T. H.
N1 - Publisher Copyright:
© The Author(s) under exclusive licence to Iranian Society of Environmentalists (IRSEN) and Science and Research Branch, Islamic Azad University 2024.
PY - 2024/4
Y1 - 2024/4
N2 - Energy and especially power generation are key requirements for economic growth; however, the excessive use of fossil fuels for power generation has resulted in serious environmental pollution problems. Past research has examined the relationship between power energy efficiency and CO2 on a single level, but there has been little focus on other damaging pollutants such as PM2.5 or their treatment. Further, most past efficiency analyses have been static and have lacked dynamic time considerations. Therefore, to go some way to filling these research gaps, this study proposed an undesirable directional distance function (DDF) dynamic data envelopment analysis (DEA) to explore power production and environmental efficiency in 31 Chinese provinces/municipalities/autonomous regions from 2008 to 2017, from which it was found that Beijing, Guangdong, Hunan, Jilin, Jiangsu, Shanghai, Tianjin and Tibet all had efficiencies of 1, but the power industry efficiencies in the western provinces/municipalities/autonomous regions—Inner Mongolia, Gansu, Ningxia and Xinjiang— needed significant improvements; Most areas, especially Liaoning, Inner Mongolia, Fujian, Shandong, and Tibet, needed environmental treatment efficiency improvements; and the need for carbon dioxide emissions improvements in most provinces/municipalities/autonomous regions was relatively stable, but there were large differences in the need for PM2.5 improvements.
AB - Energy and especially power generation are key requirements for economic growth; however, the excessive use of fossil fuels for power generation has resulted in serious environmental pollution problems. Past research has examined the relationship between power energy efficiency and CO2 on a single level, but there has been little focus on other damaging pollutants such as PM2.5 or their treatment. Further, most past efficiency analyses have been static and have lacked dynamic time considerations. Therefore, to go some way to filling these research gaps, this study proposed an undesirable directional distance function (DDF) dynamic data envelopment analysis (DEA) to explore power production and environmental efficiency in 31 Chinese provinces/municipalities/autonomous regions from 2008 to 2017, from which it was found that Beijing, Guangdong, Hunan, Jilin, Jiangsu, Shanghai, Tianjin and Tibet all had efficiencies of 1, but the power industry efficiencies in the western provinces/municipalities/autonomous regions—Inner Mongolia, Gansu, Ningxia and Xinjiang— needed significant improvements; Most areas, especially Liaoning, Inner Mongolia, Fujian, Shandong, and Tibet, needed environmental treatment efficiency improvements; and the need for carbon dioxide emissions improvements in most provinces/municipalities/autonomous regions was relatively stable, but there were large differences in the need for PM2.5 improvements.
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U2 - 10.1007/s13762-023-05410-w
DO - 10.1007/s13762-023-05410-w
M3 - Article
AN - SCOPUS:85182674561
SN - 1735-1472
VL - 21
SP - 5955
EP - 5970
JO - International Journal of Environmental Science and Technology
JF - International Journal of Environmental Science and Technology
IS - 7
ER -