Revealing dynamic impacts of socioeconomic factors on air pollution changes in Guangdong Province, China.

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ID: 62388
2019
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Abstract
The rapid development of cities leads to the frequent occurrence of air pollution incidents, which seriously hinders urban sustainability. This study develops a dynamic regional air pollution analysis (DRA) model to explore the mechanism of air pollutant emission changes. Specifically, the emissions differences among various sectors are distinguished by multi-angle accounting (MAA) method, and sectors' evolutionary trajectories are described by sector evolution analysis (SEA). Through combining emission deconstruction analysis (EDA) and structural decomposition analysis (SDA), key emission patterns and decisive socioeconomic factors are identified. The empirical results indicate that different sectors play different roles in the urban emission system and differentiated regulation policies should be formulated according to their characteristics. Changes of demand and supply patterns can result in the fluctuation in regional air pollutant emissions. Exports and worker's reward are the most significant contributors to air pollution on demand and supply sides, accounting for more than 54.3% and 44.0% of total emissions, respectively. The final demand level and the primary input level are the two biggest drivers of the emission increase, while emission intensity is the most crucial factor that offsets the emission growth. Also, there are significant differences in demand and supply structure. The contribution of primary input structure to emission reduction was more significant than that of final demand structure, which contributed 14.6% in 2015. The findings in this study will provide reliable information for developing more comprehensive and effective mitigation policies.
Reference Key
xu2019revealingthe Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Xu, Xinli;Huang, Guohe;Liu, Lirong;Guan, Yuru;Zhai, Mengyu;Li, Yongping;
Journal The Science of the total environment
Year 2019
DOI
S0048-9697(19)34155-5
URL
Keywords
structural decomposition analysis air pollutant equivalent ghosh-supply io model leontief-demand io model

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