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Abstract
© 2016 American Chemical Society.
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 NO2 samplers sited to capture within-city and near-road variability in two Australian cities (Sydney and Perth) to assess the validity of annual mean NO2 estimates 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 NO2 regressed on independent measurements of NO2), mean-square-error R2 (MSE-R2), RMSE, and bias. Our models captured up to 69% of spatial variability in NO2 at 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 NO2 monitors. We have demonstrated that such models are a valid approach for estimating NO2 exposures in Australian cities. (Graph Presented).
Original language | English |
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Pages (from-to) | 12331-12338 |
Journal | Environmental Science and Technology |
Volume | 50 |
Issue number | 22 |
Early online date | 21 Oct 2016 |
DOIs | |
Publication status | Published - Nov 2016 |
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Dive into the research topics of 'Independent Validation of National Satellite-Based Land-Use Regression Models for Nitrogen Dioxide Using Passive Samplers'. Together they form a unique fingerprint.Projects
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Health in Men & Air Quality Study - HIMAQs
Heyworth, J., Hinwood, A., Nieuwenhuijsen, M., McCaul, K., Yeap, B. & Brunkereef, B.
National Health & Medical Research Council NHMRC
1/01/11 → 31/12/15
Project: Research