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Spatiotemporal inhomogeneity of total column NO2 in a polluted urban area inferred from TROPOMI and Pandora intercomparisons

DATE2022-10-31 HIT99

Spatiotemporal inhomogeneity of total column NO2 in a polluted urban area inferred from TROPOMI and Pandora intercomparisons

GIScience & Remote Sensing


Authors : Jong-Uk Park, Jin-Soo Park, Daniel Santana Diaz, Manuel Gebetsberger, Moritz Muller, Lena Shalaby, Martin Tiefengraber, Hyun-Jae Kim, Sang Seo Park, Chang-Keun Song, Sang-Woo Kim

ISSN : 1548-1603

  The spatiotemporal inhomogeneity of the total column NO2 amounts (TCN) in the Seoul Metropolitan
Area (SMA), Korea, was quantitatively assessed through year-round (October 2019 May 2021) TROPOMI
and ground-based Pandora measurements. The average TCN over the SMA was comparable to that of
major Chinese megacities, being consistently high (> 0.8 DU; Dobson Unit) during the daytime
(10 17 local standard time). The autocorrelation scores of the Pandora-measured TCNs demonstrated high
temporal variability attributed to the spatial inhomogeneity of NO2 emissions within the SMA and
near-surface advection. Accordingly, the adequate temporal collocation range for Pandora measurements
for the intercomparison with the satellite sensors was considered to be ± 5 min to avoid significant uncertainty
from the temporal variability (RMSE < 0.1 DU, R2 > 0.96). TROPOMI showed better agreement with conventionally
collocated Pandora measurements (0.73 < R2 < 0.76, 26 29% negative bias) than the other two satellite sensors
(OMI and OMPS) attributed to its highest spatial resolution. The application of the wind-based collocation revealed
that the TROPOMI showed a greater negative bias on the upwind side, which was less affected by anthropogenic
emissions from the urban area, than the downwind side, and the increasing distance of the TROPOMI pixel from
Pandora was the most critical factor deteriorating the intercomparison scores. The FRESCO-S TROPOMI cloud
algorithm update to FRESCO-wide yielded a general increase in TROPOMI TCN, especially in the partially cloudy
pixels, leaving only 11% (downwind) and 29% (upwind) negative bias from coincident Pandora measurements.
Furthermore, the wind-based collocation method revealed the spatial distribution pattern of NOX (NO + NO2)
emissions in the SMA, with significant emission sources in the northeastern and southeastern sides of the
ground-based Pandora site in Seoul.

Keyword : TROPOMI, Pandora, total column NO2, spatiotemporal variability, Seoul metropolitan area

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