Including satellite observations of nitrogen dioxide (NO 2 ) in land-use regression (LUR) models can improve their predictive ability, but requires rigorous evaluation. We used 123 passive NO 2 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 2 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 2 (predicted NO 2 regressed on independent measurements of NO 2 ), mean-square-error R 2 (MSE-R 2 ), RMSE, and bias. Our models captured up to 69% of spatial variability in NO 2 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 2 ) was similar to their correlation (measured by R 2 ). 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 2 monitors. We have demonstrated that such models are a valid approach for estimating NO 2 exposures in Australian cities.