Source Apportionment of Fine Particulate Matter in Wuhan: Application of Rolling Positive Matrix Factorization Under Different Seasons and Episodic Events

Abstract Introduction Source apportionment of fine particulate matter (PM 2.5 ) from positive matrix factorization (PMF) model with long-term measurements of chemical composition data can be biased due to changes of source profiles across the sampling period. Rolling PMF strategy with source profile constraints has been demonstrated as an effective tool for source apportionment of the non-refractory submicron aerosol, while its application in PM chemical speciation data under different pollution conditions was less studied. Methods Here, we conducted source apportionment of PM 2.5 using rolling PMF based on hourly chemical speciation data during winter (November 2021 to January 2022) and summer months (May to July 2023) at a suburban site in Wuhan, China. Rolling PMF runs were conducted with source profile constraints using the a -value method in the Source Finder Professional. Results Rolling PMF runs for both winter and summer data indicated major PM 2.5 contributors were secondary sources and biomass burning in Wuhan, contributing to 61.9% and 19.4% in winter and 58.9% and 22.7% in summer, respectively. Larger source profile variabilities were observed for winter data than summer data. The rolling PMF runs effectively reproduced the source contributions of seasonal PMF for most sources, with Pearson Correlation Coefficient (R) of 0.95–0.99 and slopes of 0.9–1.1. Analysis of the short-lasting episodic events further validated the applicability of rolling PMF, which can provide more timely and environmentally interpretable results. Conclusion This study improved our understandings of the seasonal variations of the PM sources and the formation of episodic events, providing valuable insights for formulating promptly effective air pollution control measures. Graphical abstract

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Publication Details

Journal
Aerosol and Air Quality Research
Published
2025-04-01
DOI
https://doi.org/10.1007/s44408-025-00005-1
Citations
4
Primary Topic
Atmospheric chemistry and aerosols
Type
article
Field-Weighted Citation Impact
5.20

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article

Source Apportionment of Fine Particulate Matter in Wuhan: Application of Rolling Positive Matrix Factorization Under Different Seasons and Episodic Events

Huan Yu, Bo Zhu, Mingjie Xie, Shaofei Kong et al.
4 citations
Aerosol and Air Quality Research
Atmospheric chemistry and aerosols
5.20
article

Source Apportionment of Fine Particulate Matter in Wuhan: Application of Rolling Positive Matrix Factorization Under Different Seasons and Episodic Events

Huan Yu, Bo Zhu, Mingjie Xie, Shaofei Kong, Qiongqiong Wang, Huang Zheng, Nan Chen, Z. J. Guo
article en
4 citations

Abstract

Abstract Introduction Source apportionment of fine particulate matter (PM 2.5 ) from positive matrix factorization (PMF) model with long-term measurements of chemical composition data can be biased due to changes of source profiles across the sampling period. Rolling PMF strategy with source profile constraints has been demonstrated as an effective tool for source apportionment of the non-refractory submicron aerosol, while its application in PM chemical speciation data under different pollution conditions was less studied. Methods Here, we conducted source apportionment of PM 2.5 using rolling PMF based on hourly chemical speciation data during winter (November 2021 to January 2022) and summer months (May to July 2023) at a suburban site in Wuhan, China. Rolling PMF runs were conducted with source profile constraints using the a -value method in the Source Finder Professional. Results Rolling PMF runs for both winter and summer data indicated major PM 2.5 contributors were secondary sources and biomass burning in Wuhan, contributing to 61.9% and 19.4% in winter and 58.9% and 22.7% in summer, respectively. Larger source profile variabilities were observed for winter data than summer data. The rolling PMF runs effectively reproduced the source contributions of seasonal PMF for most sources, with Pearson Correlation Coefficient (R) of 0.95–0.99 and slopes of 0.9–1.1. Analysis of the short-lasting episodic events further validated the applicability of rolling PMF, which can provide more timely and environmentally interpretable results. Conclusion This study improved our understandings of the seasonal variations of the PM sources and the formation of episodic events, providing valuable insights for formulating promptly effective air pollution control measures. Graphical abstract

Aerosol and Air Quality ResearchVol. 25(1-4)
Nanjing University of Information Science and Technology (CN), China University of Geosciences (CN), Zhejiang Environmental Monitoring Center (CN)
National Natural Science Foundation of China, Natural Science Foundation of Hubei Province, China University of Geosciences, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 5%
Atmospheric chemistry and aerosols
5.20
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