A novel approach to deriving the fine-scale daily NO dataset during 2005-2020 in China: Improving spatial resolution and temporal coverage to advance exposure assessment.

Surface NO pollution can result in serious health consequences such as cardiovascular disease, asthma, and premature mortality. Due to the extensive spatial variation in surface NO, the spatial resolution of a NO dataset has a significant impact on the exposure and health impact assessment. There is currently no long-term, high-resolution, and publicly available NO dataset for China. To fill this gap, this study generated a NO dataset named RBE-DS-NO2 for China during 2005-2020 at 1 km and daily resolution. We employed the robust back-extrapolation via a data augmentation approach (RBE-DA) to ensure the predictive accuracy in back-extrapolation before 2013, and utilized an improved spatial downscaling technique (DS) to refine the spatial resolution from 10 km to 1 km. Back-extrapolation validation based on 2005-2012 observations from sites in Taiwan province yielded an R of 0.72 and RMSE of 10.7 μg/m, while cross-validation across China during 2013-2020 showed an R of 0.73 and RMSE of 9.6 μg/m. RBE-DS-NO2 better captured spatiotemporal variation of surface NO in China compared to the existing publicly available datasets. Exposure assessment using RBE-DS-NO2 show that the population living in non-attainment areas (NO ≥ 30 μg/m) grew from 376 million in 2005 to 612 million in 2012, then declined to 404 million by 2020. Unlike this national trend, exposure levels in several major cities (e.g., Shanghai and Chengdu) continued to increase during 2012-2020, driven by population growth and urban migration. Furthermore, this study revealed that low-resolution dataset (i.e., the 10 km intermediate dataset before the downscaling) overestimated NO levels, due to the limited specificity of the low-resolution model in simulating the relationship between NO and the predictor variables. Such limited specificity likely biased previous long-term NO exposure and health impact studies employing low-resolution datasets. The RBE-DS-NO2 dataset enables robust long-term assessments of NO exposure and health impacts in China.