Estimating particle speciation concentrations using MISR retrieved aerosol properties in southern California
Abstract
Ambient fine particle (PM2.5) has been positively associated with increased mortality and morbidity worldwide. Recent studies highlight the characteristics and differential toxicity of PM2.5 chemical components, which are important for identifying sources, developing targeted particulate matter (PM) control strategies, and protecting public health. Modelling with satellite retrieved data has been proved as the most cost-effective way to estimate ground PM2.5 levels; however, limited studies have predict PM2.5 chemical components with this method. In this study, the experimental MISR 4.4 km aerosol retrievals were used to predict ground-level particle sulfate, nitrite, organic carbon and element carbon concentrations in 16 counties of southern California. The PM2.5 chemical components concentrations were obtained from the National Chemical Speciation Network (CSN) and the Interagency Monitoring of Protected Visual Environments (IMPROVE) network. A generalized additive model (GAM) was developed based on 16-years data (2000-2015) by combining the MISR aerosol retrievals, meteorological variables and geographical indicators together. Model performance was assessed by model fitted R2 and root-mean-square error (RMSE) and 10-fold cross validation. Spatial patterns of sulfate, nitrate, OC and EC concentrations were also examined with 2-D prediction surfaces. This is the first attempt to develop high-resolution spatial models to predict PM2.5 chemical component concentrations with MISR retrieved aerosol properties, which will provide valuable population exposure estimates for future studies on the characteristics and differential toxicity of PM2.5 speciation.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2016
- Bibcode:
- 2016AGUFM.A32A..04M
- Keywords:
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- 0305 Aerosols and particles;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 0345 Pollution: urban and regional;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 0365 Troposphere: composition and chemistry;
- ATMOSPHERIC COMPOSITION AND STRUCTUREDE: 3360 Remote sensing;
- ATMOSPHERIC PROCESSES