Characterizing PM2.5 Secondary Aerosols via a Fusion Strategy of Two-stage Positive Matrix Factorization and Robust Regression

Characterizing PM2.5 Secondary Aerosols via a Fusion Strategy of Two-stage Positive Matrix Factorization and Robust Regression

Abstract Positive Matrix Factorization (PMF) is a commonly used receptor model for source apportionment of PM2.5. However, PMF results often retrieve an individual factor mainly composed of secondary aerosols, making it difficult to link with primary emission sources and formulate effective air poll...

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Bibliographic Details
Main Authors: Chun-Sheng Huang, Ho-Tang Liao, Chia-Yang Chen, Li-Hao Young, Ta-Chih Hsiao, Tsung-I Chou, Jyun-Min Chang, Kuan-Lin Lai, Chang-Fu Wu
Format: Article
Language:English
Published: Springer 2023-10-01
Series:Aerosol and Air Quality Research
Subjects:
Secondary air pollution
Online measurements
Receptor model
Constraint
Online Access:https://doi.org/10.4209/aaqr.230121
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https://doi.org/10.4209/aaqr.230121

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