Neighborhood-scale ambient NO concentrations using TROPOMI NO data: Applications for spatially comprehensive exposure assessment.

This study estimated long-term average ambient NO concentrations using TROPOspheric Monitoring Instrument (TROPOMI) tropospheric NO data and land use information at the spatial resolution of 500 m in California for the years 2018-2019. Our satellite-land use regression model demonstrated reasonably high predictive power with cross-validation (CV) R = 0.76, mean absolute error (MAE) = 1.

Spatial analysis of concentrations of multiple air pollutants using NASA DISCOVER-AQ aircraft measurements: Implications for exposure assessment.

In recent years, multipollutant approaches have been employed to investigate the association with health outcomes to better represent real-world conditions than more traditional analysis that considers a single pollutant. With regard to the exposure assessment of a mixture of air pollutants, it is critical to understand the spatial variability in multipollutant relations in order to assess their potential health implications. In this study, we investigated the spatial relations of multiple pollutant concentrations (i.

Enhancing the Applicability of Satellite Remote Sensing for PM2.5 Estimation Using MODIS Deep Blue AOD and Land Use Regression in California, United States.

We estimated daily ground-level PM2.5 concentrations combining Collection 6 deep blue (DB) Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) data (10 km resolution) with land use regression in California, United States, for the period 2006-2012. The Collection 6 DB method for AOD provided more reliable data retrievals over California's bright surface areas than previous data sets.