Variations of Secondary PM_2.5 in an Urban Area over Central China during 2015–2020 of Air Pollutant Mitigation

Abstract

The lack of long-term observational data on secondary PM2.5 (SPM) has limited our comprehensive understanding of atmospheric environment change. This study develops an SPM estimation method, named Single-Tracer Approximate Envelope Algorithm (STAEA), to assess the long-term changes of SPM under different PM2.5 levels and in all seasons in Wuhan, Central China, over the period of anthropogenic pollutant mitigation in 2015–2020. The results show that: (1) the average proportions of SPM in ambient PM2.5 is 59.61% in a clean air environment, rising significantly to 71.60%, 73.73%, and 75.55%, respectively, in light, moderate, and heavy PM2.5 pollution, indicating the dominant role of SPM in air quality deterioration; (2) there are increasing trends of interannual changes of SPM at the light and moderate pollution levels of 1.95 and 3.11 μg·m−3·a−1 with extending SPM proportions in PM2.5 pollution, raising a challenge for further improvement in ambient air quality with mitigating light and moderate PM2.5 pollution; (3) the high SPM contributions ranging from 55.63% to 68.65% on a seasonal average and the large amplitude of seasonal SPM changes could dominate the seasonality of air quality; (4) the wintertime SPM contribution present a consistent increasing trend compared with the declining trends in spring, summer, and autumn, suggesting underlying mechanisms of SPM change for further deciphering the evolution of the atmospheric environment. Our results highlight the effects of air pollutant mitigation on long-term variations in SPM and its contributions with implications for atmospheric environment change.

Keywords

• particle pollution
• secondary pm_2.5
• long-term variations
• seasonal change
• central China