Highly resolved mapping of NO <sub>2</sub> vertical column densities from GeoTASO measurements over a megacity and industrial area during the KORUS-AQ campaign
Gyo-Hwang Choo, Kyunghwa Lee, Hyunkee Hong, Ukkyo Jeong, Wonei Choi, Scott J. Janz
Abstract
Abstract. The Korea–United States Air Quality (KORUS-AQ) campaign is a joint study between the United States National Aeronautics and Space Administration (NASA) and the South Korea National Institute of Environmental Research (NIER) to monitor megacity and transboundary air pollution around the Korean Peninsula using airborne and ground-based measurements. Here, tropospheric nitrogen dioxide (NO2) slant column density (SCD) measurements were retrieved from Geostationary Trace and Aerosol Sensor Optimization (GeoTASO) L1B data during the KORUS-AQ campaign (2 May to 10 June 2016). The retrieved SCDs were converted to tropospheric vertical column densities using the air mass factor (AMF) obtained from a radiative transfer calculation with trace gas profiles and aerosol property inputs simulated with the Community Multiscale Air Quality (CMAQ) model and surface reflectance data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). For the first time, we examine highly resolved (250 m × 250 m resolution) tropospheric NO2 over the Seoul and Busan metropolitan regions and the industrial region of Anmyeon. We reveal that the maximum NO2 vertical column densities (VCDs) were 4.94×1016 and 1.46×1017 molec. cm−2 at 09:00 and 15:00 LT over Seoul, respectively, 6.86×1016 and 4.89×1016 molec. cm−2 in the morning and afternoon over Busan, respectively, and 1.64×1016 molec. cm−2 over Anmyeon. The VCDs retrieved from the GeoTASO airborne instrument were correlated with those obtained from the Ozone Monitoring Instrument (OMI) (r=0.48), NASA's Pandora Spectrometer System (r=0.91), and NO2 mixing ratios obtained from in situ measurements (r=0.07 in the morning, r=0.26 in the afternoon over the Seoul, and r>0.56 over Busan). Based on our results, GeoTASO is useful for identifying NO2 hotspots and their spatial distribution in highly populated cities and industrial areas.