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1. Decoupling economic growth from energy-related PM2.5 emissions in China: A GDIM-based indicator decomposition.

Author

Yu, Bolin and Fang, Debin

Subjects
*ECONOMIC expansion, *SUSTAINABLE development, *DECOMPOSITION method, *ENERGY consumption, *MATHEMATICAL decoupling, *AIR quality, *INPUT-output analysis
Abstract

• GDIM is used to investigate the influencing factors of energy-related PM 2.5 emissions in China. • A novel decoupling indicator is constructed based on GDIM decomposition results. • The increase of PM 2.5 emissions is primarily due to output scale and energy use effects. • Emission intensity and emission coefficients are the main factors decreasing PM 2.5 emissions. • Technical effect plays an important role in promoting the decoupling of PM 2.5 emissions. Haze pollution has become a severe threat to China's sustainable development. It is crucial to provide a complete explanation for the mechanism behind the changes in PM 2.5 pollution and explore how to decouple economic growth from PM 2.5 pollution. Compared with the traditional decomposition analysis methods, the Generalized Divisia Index Method (GDIM) integrates multiple influencing factors and provides a fuller understanding of the influence mechanism of PM 2.5 pollution. In addition, the decomposition of the monitored PM 2.5 concentration in previous studies leads to ambiguous economic meanings of some relative impact indicators. In this paper, GDIM decomposition is applied to study the driving factors of energy-related PM 2.5 emissions changes in China. Then, based on the GDIM decomposition results, this paper constructs a novel decoupling indicator to study the decoupling relationship between PM 2.5 emissions and economic growth, and the contributions of the technical and non-technical factors to the decoupling indicator are quantified. The main results are summarized as follows. (1) The output scale effect and energy use effect are the main reasons for the increase of PM 2.5 emissions, while the emission intensity effect and emission coefficient effect make major contributions to decreasing PM 2.5 emissions. The effects of population, per capita emissions, per capita output, and energy intensity are relatively minor. (2) China and its three economic regions move from strong decoupling in 1998–2000 to weak decoupling during 2000–2010, and then into strong decoupling over the period of 2010–2014. (3) Technical effect plays an important role in promoting the decoupling between PM 2.5 emissions and economic growth, but its contribution shows a downward trend over time. In contrast, non-technical effect hinders the decoupling process, and its contribution is decreasing from 2000 to 2014. This paper is supportive for formulating emissions reduction policies and improving China's air quality. [ABSTRACT FROM AUTHOR]

Published
2021
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2. Energy sustainability evaluation of 30 provinces in China using the improved entropy weight-cloud model

Author

Jie Xu, Xu Deng, Xiaoran Hou, Tao Lv, Feng Liu, and Duyang Pi

Subjects
0106 biological sciences, Consumption (economics), Sustainable development, Ecology, business.industry, Natural resource economics, Fossil fuel, General Decision Sciences, Energy security, Energy consumption, Energy sustainability index system, 010501 environmental sciences, 010603 evolutionary biology, 01 natural sciences, Provincial perspective, Greenhouse gas, Environmental science, Elasticity coefficient, Improved entropy weight-cloud model, business, China, QH540-549.5, Ecology, Evolution, Behavior and Systematics, 0105 earth and related environmental sciences
Abstract

Energy sustainability is one of the largest challenges for sustainable development. Energy sustainability in China varies by regions because of the differences in energy resources, technology and economic levels. Previous studies have assessed national energy sustainability, few to none have looked internally on a regional or provincial scale. This paper defined energy sustainability from the four dimensions of security, efficiency, cleanness and low carbon emissions, established an index system and evaluated the energy sustainability levels of 30 provinces in China by the Improved Entropy Weight-Cloud Model (IEW-CM). The results show that: (1) General energy sustainability in Chinese provinces is deficient, and energy cleanness and efficiency perform better than security and low carbon emissions. (2) Chinese energy sustainability has obvious spatial heterogeneity and within the same province, the level is unbalanced in four dimensions. The characteristics of energy sustainability exhibit significant differences in different regions. (3) Energy security and low carbon emissions play a crucial role in achieving energy sustainability. Natural gas deliverability, energy consumption elasticity coefficient, CO2 emission per unit of energy and share of fossil energy consumption are the primary factors affecting energy sustainability differences among provinces.

Published
2021