1165 Assessing Spatial and Temporal Variability in NO2 and O3 Along the Korean Peninsula Using Remote Sensing and Ground-Based Observations

Wednesday, 10 January 2018
Exhibit Hall 3 (ACC) (Austin, Texas)
Chi Yan Rachel Li, New York City College of Technology, Brooklyn, NY; and O. Parker and M. Tzortziou

Air pollutants, such as nitrogen dioxide (NO2) and tropospheric ozone (O3), play a vital role in the atmosphere, especially due to high nitrogen emissions in urbanized areas. Such elevated levels of tropospheric NO2 and O3 pose risks to the local and regional environment, human health, and vegetation. This particular research sought to use ground-based and satellite products to study the spatial and temporal variability of NO2 and O3 in urban and coastal South Korea. Data sets are derived from remotely sensed direct-sun irradiance measurements of TCNO2 and TCO3 using Pandora spectrometers located at 8 ground sites and 1 boat-mounted sensor, as well as satellite observations from the Ozone Monitoring Instrument (OMI) on the Aura satellite. The study focuses on the dates of the KORUS-AQ/KORUS-OC campaigns, which took place between May 18, 2016 through June 2, 2016, and provided coastal and off-shore measurements of atmospheric composition and coastal ocean biogeochemistry. The Pandora instrument offers continuous coverage of the local area, providing a detailed understanding of NO2 and O3 temporal variability. Ground-based stations are capable to capture the small-scale diurnal variability in urban and near-urban environments, while the ship-board Pandora deployed on the Onnuri research vessel provides valuable insight into off-shore behavior of trace gases. Collected data is then subjected to statistical and GIS (Geographic Information System) analysis, quantifying and mapping, respectively, the spatial and temporal variability of total column amounts of NO2 and O3 along the Korean Peninsula. Results are shown for the eight sites where different Pandora instruments are used. There is a notable difference in TCNO2 variability which correlates with population and land use.
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