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Updated: Jun 25, 2026

Composition and Distribution Analysis of Bioaerosols Under Different Environmental Conditions
Published on: January 7, 2019
[Analysis of O3 and PM2.5 Mass Concentration Characteristics and Differences Between the Urban and Control Sites in
Bao-Ling Liang1, Qi-Bin Sun2,3, Jin-Pu Zhang1,4
1Guangzhou Sub-branch of Guangdong Ecological and Environmental Monitoring Center, Guangzhou 510006, China.
Abstract:
Based on the O3 and PM2.5 mass concentration from 2019 to 2023 in Guangzhou, this study analyzed the spatial distribution and difference in O3 and PM2.5 mass concentrations between the urban and control sites. The results revealed that O3 mass concentrations at both the urban and control sites exhibited a high-value fluctuation trend, while PM2.5 mass concentrations declined significantly. The difference in O3 and PM2.5 mass concentration between the urban and control site gradually narrowed. The variation trends of ΔO3 and ΔPM2.5 shifted from a synchronous pattern during 2019 to 2020 to a divergent pattern during 2020 to 2023. Monthly variations in O3 mass concentrations displayed a bimodal pattern at the urban station and a trimodal pattern at the control site, whereas PM2.5 mass concentrations consistently exhibited a "U-shaped" distribution. Seasonal variations showed that O3 mass concentration followed the characteristics of autumn>summer>spring>winter, with a notable upward trend in O3 levels and a shift in peak occurrence from summer to autumn. In contrast, PM2.5 mass concentrations were highest in winter, followed by those in autumn, spring, and summer. Implementing the extreme gradient boosting (XGBoost) model and the Shapley additive explanation (SHAP), the analysis identified surface net solar radiation and wind speed as the most significant factors affecting O3 mass concentrations at both the urban and control sites. Their contributions increased on polluted days, and control sites were more sensitive to the photochemical formation of ozone precursors (NO2), indicating that NOx emission reductions were more effective in lowering background O3 levels. For PM2.5 mass concentrations, NO2, relative humidity, and CO were the primary influencing factors at the urban station, while relative humidity, NO2, and wind speed were the top contributors at the control site. Sensitivity analysis further revealed that O3 mass concentrations significantly increased under conditions of surface net solar radiation≥135 W·m-2, wind speed≤1.8 m·s-1, and NO2 concentrations exceeding the lower threshold (urban/control sites: 34/22 μg·m-3). PM2.5 mass concentrations significantly increased under stagnant conditions (wind speed≤1.6 m·s-1), humidity≤78%, and concentrations exceeding the lower thresholds of NO2 (urban/control sites: 40/22 μg·m-3) and CO (urban/control sites: 0.8/0.7 mg·m-3). This study provides insights into the long-term evolution of O3 and PM2.5 mass concentrations at urban and control sites and offers quantitative evidence to support the development of differentiated strategies for controlling regional complex pollution.
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