Modeling Wildfire Smoke Pollution by Integrating Land Use Regression and Remote Sensing Data: Regional Multi-Temporal Estimates for Public Health and Exposure Models

Modeling Wildfire Smoke Pollution by Integrating Land Use Regression and Remote Sensing Data: Regional Multi-Temporal Estimates for Public Health and Exposure Models

To understand the health effects of wildfire smoke, it is important to accurately assess smoke exposure over space and time. Particulate matter (PM) is a predominant pollutant in wildfire smoke. In this study, we develop land-use regression (LUR) models to investigate the impact that a cluster of wi...

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Bibliographic Details
Main Authors: Mojgan Mirzaei, Stefania Bertazzon, Isabelle Couloigner
Format: Article
Language:English
Published: MDPI AG 2018-08-01
Series:Atmosphere
Subjects:
particulate matter PM2.5
AOD (aerosol optical depth)
wildfire smoke
LUR (land use regression)
spatial analysis
public health
Online Access:http://www.mdpi.com/2073-4433/9/9/335

Internet

http://www.mdpi.com/2073-4433/9/9/335

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