Assessing distributional impacts of synergetic air pollution reductions under different power system decarbonisation policies in China.
Yu, Zhongjue, Geng, Yong, Calzadilla, Alvaro and Bleischwitz, Raimund ORCID: https://orcid.org/0000-0001-8164-733X (2023) Assessing distributional impacts of synergetic air pollution reductions under different power system decarbonisation policies in China. Environmental Impact Assessment Review, 102 . p. 107215. DOI https://doi.org/10.1016/j.eiar.2023.107215.
Text
YU-Assessing distributional impacts of synergetic air pollution reductions under different power system decarbonisation policies in China - 1-s2.0-S0195925523001816-main.pdf - Published Version Restricted to Registered users only Download (5MB) |
Abstract
Decarbonising the power system contributes to carbon emission reductions and synergetic air pollution reductions, but these co-benefits may be unevenly distributed across regions. These distributional consequences from national policies may lead to conflict of interests at subnational levels, which has often been overlooked. This study assesses provincial economic impacts and synergetic air pollutant reductions of power system decarbonisation in China, achieved by two different national policies, namely a mandatory phaseout policy and an Emissions Trading System (ETS). To this end, a multi-regional dynamic Computable General Equilibrium (CGE) model is developed and adopted. The scenario analysis shows that the mandatory phaseout policy is more effective in reducing air pollutant emissions from the power sector, while leading to greater GDP losses at the national level. At provincial levels, the ETS mitigates the trade-off between economic growth and air pollutant reductions, but the mandatory phaseout policy would be more favourable to the majority of provinces no matter whether the GDP growth or air pollution reduction is prioritised.
Document Type: | Article |
---|---|
Programme Area: | PA2 |
Research affiliation: | Science Management > Directorate |
Refereed: | Yes |
Open Access Journal?: | No |
DOI: | https://doi.org/10.1016/j.eiar.2023.107215 |
ISSN: | 01959255 |
Date Deposited: | 03 Aug 2023 08:15 |
Last Modified: | 03 Aug 2023 08:15 |
URI: | http://cris.leibniz-zmt.de/id/eprint/5235 |
Actions (login required)
View Item |