Different roles of primary and secondary sources in reducing PM2.5: Insights from molecular markers in Pearl River Delta, South China. (1st February 2023)

• Record Type: Journal Article
• Authors: Yang, Kong; Chen, Duo-Hong; Ding, Xiang; Li, Jun; Zhang, Yu-Qing; Zhang, Tao; Wang, Qiao-Yun; Wang, Jun-Qi; Cheng, Qian; Jiang, Hao; Liu, Ping; Wang, Zi-Rui; He, Yun-Feng; Zhang, Gan; Wang, Xin-Ming
• Is Part Of: Atmospheric environment. Volume 294(2023)
• Publication Date: 2023-02-01
• Subjects: PM2.5 -- Chemical characterization -- Source apportionment -- Primary emission -- Secondary pollution; Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2022.119487
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: It is essential to understand the variations of PM2.5 sources under different pollution levels for improving air quality. The Pearl River Delta (PRD) was one of the most polluted areas by PM2.5 in China and is now the advanced region with the most significant improvement in PM2.5 pollution. In the year that regional PM2.5 over the PRD met the National Air Quality Standard (35 μg m −3 ) for the first time, we conducted a year-round PM2.5 sampling campaign at 9 sites and measured organic tracers for primary and secondary sources as well as water-soluble ions and heavy metals. Based on the daily PM2.5 concentrations in these samples, we divided the data into four pollution levels: Polluted (PM2.5 > 75 μg m −3 ), Moderate (75 μg m −3 > PM2.5 > 35 μg m −3 ), Clean (35 μg m −3 > PM2.5 > 25 μg m −3 ), and Good (PM2.5 < 25 μg m −3 ). The average concentrations of PM2.5 under the Polluted, Moderate, Clean, and Good levels were 91.8 ± 18.8 μg m −3, 47.6 ± 10.7 μg m −3, 30.1 ± 3.22 μg m −3, and 17.3 ± 4.67 μg m −3, respectively. Under different pollution levels, the reduction rates of molecular markers for biomass burning, vehicle exhaust, anthropogenic secondary organic aerosol (ASOA), nitrate aerosol, and industrial emission were rapider than or close to those of PM2.5, implying that the control measures on these sources were effective in the PRD. Based on the chemical characterization of specific molecular markers and source apportionment by the Positive Matrix Factorization model, we found that PM2.5 over the PRD predominantly originated from anthropogenic sources (82% on average), and the contributions of primary sources (53% on average) were slightly higher than those of secondary sources (41% on average). Compared with the Polluted days, the Good days had large decreases in anthropogenic sources of PM2.5 with significant reductions in both primary (industrial emission, vehicle exhaust, and biomass burning) and secondary (secondary nitrate, secondary sulfate and ASOA) contributions. The declines of PM2.5 from Polluted to Moderate and Clean to Good were mainly due to the reductions of primary (69% on average) and secondary (58% on average) sources, respectively. Our findings highlight the different roles of reducing primary and secondary aerosols in improving PM2.5 air quality under different pollution levels. Highlights: The concentrations of molecular markers significantly decreased with the decline of PM2.5 . Emission controls on major anthropogenic sources were effective in reducing PM2.5 in the PRD. Decrease of PM2.5 from Polluted to Moderate was largely due to the reductions in primary sources. Decline of PM2.5 from Clean to Good mainly resulted from the reductions in secondary aerosols.