Source contribution analysis of PM2.5 using Response Surface Model and Particulate Source Apportionment Technology over the PRD region, China

• Published in: The Science of the total environment 2022-04, Vol.818, p.151757-151757, Article 151757
• Main Authors: Li, Zhifang, Zhu, Yun, Wang, Shuxiao, Xing, Jia, Zhao, Bin, Long, Shicheng, Li, Minhui, Yang, Wenwei, Huang, Ruolin, Chen, Ying
• Format: Article
• Language: English
• Subjects: Air quality model; Particulate Source Apportionment Technology; PM2.5; Response Surface Model; Source contribution
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2021.151757

Identifying the emission source contributions to PM2.5 is essential for a sound PM2.5 pollution control policy. In this study, we conduct a comparative analysis of PM2.5 source contributions over the Pearl River Delta (PRD) region of China using two advanced source contribution modeling techniques: Response Surface Model (RSM) and Particulate Source Apportionment Technology (PSAT). Our comparative analyses show that RSM and PSAT can both reasonably predict the contribution of primary PM2.5 emission sources to PM2.5 formation due to its linear nature. For the secondary PM2.5 formed by the nonlinear reactions among PM2.5 precursors, however, our study shows that PSAT appears to have limitations in quantifying the nonlinear contribution of PM2.5 precursors to emission reductions, while RSM seems to better address the nonlinear relationship among PM2.5 precursors (e.g., PM2.5 disbenefits due to local NOx emission reductions in major cities with high NOx emissions). The pilot study case results show that for the ambient PM2.5 in the central cities (Guangzhou, Shenzhen, Foshan, Dongguan, and Zhongshan) of the PRD, the regional source emissions contribute the most by 42–66%; the dust emissions are the top contribution sources (29–34% by RSM and 27–31% by PSAT), and the mobile sources are listed as the secondary contributors accounting for 16–25% by RSM and 19–30% by PSAT among the anthropogenic emission sources. The city-scale cooperation on emission reductions and the enhancement of dust and mobile emission control are recommended to effectively reduce the ambient PM2.5 concentration in the PRD. [Display omitted] •PM2.5 source contributions are comparatively analyzed using RSM and PSAT.•Both RSM and PSAT can reasonably assess the primary PM2.5 emission contributions.•PSAT has the limitation of quantifying the nonlinear contributions to secondary PM2.5.•RSM can well capture the PM2.5 disbenefits by local NOx emission reductions.•Dust and mobile sources are two major contribution sectors to PM2.5 in PRD, China.