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Joseph Pinto

affiliation not provided to SSRN

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Prediction of Ambient Pm2.5 Chemical Components in Southern California Using Machine Learning

Number of pages: 47 Posted: 16 Jul 2025
Jiani Yang, Sina Hasheminassab, Meredith Franklin, Antong Zhang, David Diner, Joseph Pinto and Yuk Yung
California Institute of Technology (Caltech), Government of the United States of America - Jet Propulsion Laboratory, University of Toronto, Brown University, Government of the United States of America - Jet Propulsion Laboratory, affiliation not provided to SSRN and affiliation not provided to SSRN
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PM2.5 chemical composition, Machine Learning, XGBoost, Air pollution prediction, Southern California, Atmospheric aerosols, Speciation monitoring, SHAP analysis, Meteorological predictors, Air quality modeling