A Data-Fusion Approach to Assessing the Contribution of Wildland Fire Smoke to Fine Particulate Matter in California

• Published in: Remote sensing (Basel, Switzerland) Vol. 15; no. 17; p. 4246
• Main Authors: Yang, Hongjian, Ruiz-Suarez, Sofia, Reich, Brian J, Guan, Yawen, Rappold, Ana G
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.08.2023
• Subjects: Air pollution; Air quality; Air quality management; Analysis; Bayesian analysis; Bias; calibration; California; citizen science; Data integration; Emissions; Environmental protection; Epidemiology; Forest fires; Fourier transforms; Humidity; Monitoring; Outdoor air quality; Ozone; Particulate emissions; Particulate matter; Remote sensing; Satellites; Sensors; Smoke; spatiotemporal methods; spectral analysis; Wildfires; California; United States > US

The escalating frequency and severity of global wildfires necessitate an in-depth understanding and monitoring of wildfire smoke impacts, specifically its contribution to fine particulate matter (PM2.5). We propose a data-fusion method to study wildfire contribution to PM2.5 using satellite-derived...