Explainable ensemble machine learning revealing spatiotemporal heterogeneity in driving factors of particulate nitro-aromatic compounds in eastern China

<p>Nitro-aromatic compounds (NACs) are important atmospheric pollutants that impact air quality, atmospheric chemistry, and human health. Understanding the relationship between NAC formation and key environmental driving factors is crucial for mitigating their environmental and health impacts....

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Main Authors: M. Li, X. Wang, T. Li, Y. Wang, Y. Jiang, Y. Zhu, W. Nie, R. Li, J. Gao, L. Xue, Q. Zhang, W. Wang
Format: Article
Language:English
Published: Copernicus Publications 2025-08-01
Series:Atmospheric Chemistry and Physics
Online Access:https://acp.copernicus.org/articles/25/8407/2025/acp-25-8407-2025.pdf
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Summary:<p>Nitro-aromatic compounds (NACs) are important atmospheric pollutants that impact air quality, atmospheric chemistry, and human health. Understanding the relationship between NAC formation and key environmental driving factors is crucial for mitigating their environmental and health impacts. In this work, we combined an ensemble machine learning (EML) model with the SHapley Additive exPlanation (SHAP) and positive matrix factorization (PMF) model to identify the key driving factors for ambient particulate NACs, covering primary emissions, secondary formation, and meteorological conditions based on field observations at urban, rural, and mountain sites in eastern China. The EML model effectively reproduced ambient NACs and recognized that anthropogenic emissions (i.e., coal combustion, traffic emission, and biomass burning) were the most important driving factors, with a total contribution of 49.3 %, while significant influences from meteorology (27.4 %) and secondary formation (23.3 %) were also confirmed. Seasonal variation analysis showed that direct emissions presented positive responses to NAC concentrations in spring, summer, and autumn, while lower temperatures had the largest positive impact in winter. By evaluating NAC formation and loss under various locations in winter, we found that anthropogenic sources played a dominant role in increasing NAC levels in urban and rural sites, while reduced ambient temperature, along with secondary formation from gas-phase oxidation, was the main reason for relatively high particulate NAC levels at the mountain site. This work provides a reliable modeling method for understanding the dominant sources and influencing factors for atmospheric NACs and highlights the necessity of strengthening emission source controls to mitigate organic aerosol pollution.</p>
ISSN:1680-7316
1680-7324