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Satellite-Based Land-Use Regression for Continental-Scale Long-Term Ambient PM2.5 Exposure Assessment in Australia.
Knibbs, Luke D; van Donkelaar, Aaron; Martin, Randall V; Bechle, Matthew J; Brauer, Michael; Cohen, David D; Cowie, Christine T; Dirgawati, Mila; Guo, Yuming; Hanigan, Ivan C; Johnston, Fay H; Marks, Guy B; Marshall, Julian D; Pereira, Gavin; Jalaludin, Bin; Heyworth, Jane S; Morgan, Geoffrey G; Barnett, Adrian G.
Afiliação
  • Knibbs LD; Faculty of Medicine, School of Public Health , The University of Queensland , Herston , Queensland 4006 , Australia.
  • van Donkelaar A; Centre for Air Pollution , Energy and Health Research , Glebe , New South Wales 2037 , Australia.
  • Martin RV; Department of Physics and Atmospheric Science , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada.
  • Bechle MJ; Department of Physics and Atmospheric Science , Dalhousie University , Halifax , Nova Scotia B3H 4R2 , Canada.
  • Brauer M; Smithsonian Astrophysical Observatory , Harvard-Smithsonian Center for Astrophysics , Cambridge , Massachusetts 02138 , United States.
  • Cohen DD; Department of Civil and Environmental Engineering , University of Washington , Seattle , Washington 98195 , United States.
  • Cowie CT; School of Population and Public Health , The University of British Columbia , Vancouver , British Columbia V6T 1Z3 , Canada.
  • Dirgawati M; Centre for Accelerator Science , Australian Nuclear Science and Technology Organisation , Locked Bag 2001 , Kirrawee DC, New South Wales 2232 , Australia.
  • Guo Y; Centre for Air Pollution , Energy and Health Research , Glebe , New South Wales 2037 , Australia.
  • Hanigan IC; South Western Sydney Clinical School , The University of New South Wales , Liverpool , New South Wales 2170 , Australia.
  • Johnston FH; School of Population and Global Health , The University of Western Australia , Perth , Western Australia 6009 , Australia.
  • Marks GB; Environmental Engineering , Institut Teknologi Nasional , Bandung , Jawa Barat 40213 , Indonesia.
  • Marshall JD; Centre for Air Pollution , Energy and Health Research , Glebe , New South Wales 2037 , Australia.
  • Pereira G; Department of Epidemiology and Biostatistics, School of Public Health and Preventive Medicine , Monash University , Melbourne , Victoria 3004 , Australia.
  • Jalaludin B; Centre for Air Pollution , Energy and Health Research , Glebe , New South Wales 2037 , Australia.
  • Heyworth JS; School of Public Health , The University of Sydney , Sydney , New South Wales 2006 , Australia.
  • Morgan GG; Centre for Air Pollution , Energy and Health Research , Glebe , New South Wales 2037 , Australia.
  • Barnett AG; Menzies Institute for Medical Research , The University of Tasmania , Hobart , Tasmania 7000 , Australia.
Environ Sci Technol ; 52(21): 12445-12455, 2018 11 06.
Article em En | MEDLINE | ID: mdl-30277062
ABSTRACT
Australia has relatively diverse sources and low concentrations of ambient fine particulate matter (<2.5 µm, PM2.5). Few comparable regions are available to evaluate the utility of continental-scale land-use regression (LUR) models including global geophysical estimates of PM2.5, derived by relating satellite-observed aerosol optical depth to ground-level PM2.5 ("SAT-PM2.5"). We aimed to determine the validity of such satellite-based LUR models for PM2.5 in Australia. We used global SAT-PM2.5 estimates (∼10 km grid) and local land-use predictors to develop four LUR models for year-2015 (two satellite-based, two nonsatellite-based). We evaluated model performance at 51 independent monitoring sites not used for model development. An LUR model that included the SAT-PM2.5 predictor variable (and six others) explained the most spatial variability in PM2.5 (adjusted R2 = 0.63, RMSE (µg/m3 [%]) 0.96 [14%]). Performance decreased modestly when evaluated (evaluation R2 = 0.52, RMSE 1.15 [16%]). The evaluation R2 of the SAT-PM2.5 estimate alone was 0.26 (RMSE 3.97 [56%]). SAT-PM2.5 estimates improved LUR model performance, while local land-use predictors increased the utility of global SAT-PM2.5 estimates, including enhanced characterization of within-city gradients. Our findings support the validity of continental-scale satellite-based LUR modeling for PM2.5 exposure assessment in Australia.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Poluentes Atmosféricos Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Poluentes Atmosféricos Idioma: En Ano de publicação: 2018 Tipo de documento: Article