title: Independent Validation of National Satellite-Based Land-Use Regression Models for Nitrogen Dioxide Using Passive Samplers.
abstract: Including satellite observations of nitrogen dioxide (NO2) in land-use regression (LUR) models can improve their predictive ability, but requires rigorous evaluation. We used 123 passive NO2samplers sited to capture within-city and near-road variability in two Australian cities (Sydney and Perth) to assess the validity of annual mean NO2estimates from existing national satellite-based LUR models (developed with 68 regulatory monitors). The samplers spanned roadside, urban near traffic (≤100 m to a major road), and urban background (>100 m to a major road) locations. We evaluated model performance using R2(predicted NO2regressed on independent measurements of NO2), mean-square-error R2(MSE-R2), RMSE, and bias. Our models captured up to 69% of spatial variability in NO2at urban near-traffic and urban background locations, and up to 58% of variability at all validation sites, including roadside locations. The absolute agreement of measurements and predictions (measured by MSE-R2) was similar to their correlation (measured by R2). Few previous studies have performed independent evaluations of national satellite-based LUR models, and there is little information on the performance of models developed with a small number of NO2monitors. We have demonstrated that such models are a valid approach for estimating NO2exposures in Australian cities.
authors: School of Public Health, The University of Queensland , Herston, Queensland 4006, Australia.
authors: Luke D
authors: LD
authors: Knibbs
authors: School of Medicine, The University of Queensland , Herston, Queensland 4006, Australia.
authors: Craig P
authors: CP
authors: Coorey
authors: Department of Civil and Environmental Engineering, University of Washington , Seattle, Washington 98195, United States.
authors: Matthew J
authors: MJ
authors: Bechle
authors: South Western Sydney Clinical School, The University of New South Wales , Liverpool, New South Wales 2170, Australia.|Ingham Institute for Applied Medical Research , Liverpool, New South Wales 2170, Australia.|Woolcock Institute of Medical Research, University of Sydney , Glebe, New South Wales 2037, Australia.
authors: Christine T
authors: CT
authors: Cowie
authors: School of Population Health, The University of Western Australia , Crawley, Western Australia 6009, Australia.
authors: Mila
authors: M
authors: Dirgawati
authors: School of Population Health, The University of Western Australia , Crawley, Western Australia 6009, Australia.
authors: Jane S
authors: JS
authors: Heyworth
authors: South Western Sydney Clinical School, The University of New South Wales , Liverpool, New South Wales 2170, Australia.|Ingham Institute for Applied Medical Research , Liverpool, New South Wales 2170, Australia.
authors: Guy B
authors: GB
authors: Marks
authors: Department of Civil and Environmental Engineering, University of Washington , Seattle, Washington 98195, United States.
authors: Julian D
authors: JD
authors: Marshall
authors: International Laboratory for Air Quality and Health, Queensland University of Technology , Brisbane, Queensland 4001, Australia.
authors: Lidia
authors: L
authors: Morawska
authors: School of Public Health, Curtin University , Perth, Western Australia 6000, Australia.
authors: Gavin
authors: G
authors: Pereira
authors: School of Geography, Planning and Environmental Management, The University of Queensland , St. Lucia, Queensland 4067, Australia.
authors: Michael G
authors: MG
authors: Hewson
mesh_terms: D000393:Air Pollutants; D000397:Air Pollution; D001315:Australia; D004784:Environmental Monitoring; D008962:Models, Theoretical; D009585:Nitrogen Dioxide; D012044:Regression Analysis
chemical_list: D000393:Air Pollutants; D009585:Nitrogen Dioxide