42 43 Word count (excl. title page, captions, references): 5,458 44 Small tables: 2 45

Including satellite observations of nitrogen dioxide (NO) in land-use regression (LUR) models can improve their predictive ability, but requires rigorous evaluation. We used 123 passive NO samplers sited to capture within-city and near-road variability in two Australian cities (Sydney and Perth) to assess the validity of annual mean NO 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 R (predicted NO regressed on independent measurements of NO), mean-square-error R (MSE-R), RMSE, and bias. Our models captured up to 69% of spatial variability in NO 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-R) was similar to their correlation (measured by R). 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 NO monitors. We have demonstrated that such models are a valid approach for estimating NO exposures in Australian cities.

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