A high-resolution and observationally constrained OMI NO₂ satellite retrieval

• Main Authors: D. L. Goldberg, L. N. Lamsal, C. P. Loughner, W. H. Swartz, Z. Lu, D. G. Streets
• Format: Article
• Language: English
• Published: Copernicus Publications 2017-09-01
• Series: Atmospheric Chemistry and Physics
• Online Access: https://www.atmos-chem-phys.net/17/11403/2017/acp-17-11403-2017.pdf

This work presents a new high-resolution NO₂ dataset derived from the NASA Ozone Monitoring Instrument (OMI) NO₂ version 3.0 retrieval that can be used to estimate surface-level concentrations. The standard NASA product uses NO₂ vertical profile shape factors from a 1.25°  ×  1° (∼  110 km  ×  110 km) resolution Global Model Initiative (GMI) model simulation to calculate air mass factors, a critical value used to determine observed tropospheric NO₂ vertical columns. To better estimate vertical profile shape factors, we use a high-resolution (1.33 km  ×  1.33 km) Community Multi-scale Air Quality (CMAQ) model simulation constrained by in situ aircraft observations to recalculate tropospheric air mass factors and tropospheric NO₂ vertical columns during summertime in the eastern US. In this new product, OMI NO₂ tropospheric columns increase by up to 160 % in city centers and decrease by 20–50 % in the rural areas outside of urban areas when compared to the operational NASA product. Our new product shows much better agreement with the Pandora NO₂ and Airborne Compact Atmospheric Mapper (ACAM) NO₂ spectrometer measurements acquired during the DISCOVER-AQ Maryland field campaign. Furthermore, the correlation between our satellite product and EPA NO₂ monitors in urban areas has improved dramatically: <i>r</i>²  =  0.60 in the new product vs. <i>r</i>²  =  0.39 in the operational product, signifying that this new product is a better indicator of surface concentrations than the operational product. Our work emphasizes the need to use both high-resolution and high-fidelity models in order to recalculate satellite data in areas with large spatial heterogeneities in NO_<i>x</i> emissions. Although the current work is focused on the eastern US, the methodology developed in this work can be applied to other world regions to produce high-quality region-specific NO₂ satellite retrievals.