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Evaluation of correlated Pandora column NO.sub.2 and in situ surface NO.sub.2 measurements during GMAP campaign

To validate the Geostationary Environment Monitoring Spectrometer (GEMS), the GEMS Map of Air Pollution (GMAP) campaign was conducted during 2020-2021 by integrating Pandora Asia Network, aircraft, and in situ measurements. In the present study, GMAP-2020 measurements were applied to evaluate urban...

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Published in:Atmospheric chemistry and physics 2022-08, Vol.22 (16), p.10703
Main Authors: Chang, Lim-Seok, Kim, Donghee, Hong, Hyunkee, Kim, Deok-Rae, Yu, Jeong-Ah, Lee, Kwangyul, Lee, Hanlim, Kim, Daewon, Hong, Jinkyu, Jo, Hyun-Young, Kim, Cheol-Hee
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container_title Atmospheric chemistry and physics
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creator Chang, Lim-Seok
Kim, Donghee
Hong, Hyunkee
Kim, Deok-Rae
Yu, Jeong-Ah
Lee, Kwangyul
Lee, Hanlim
Kim, Daewon
Hong, Jinkyu
Jo, Hyun-Young
Kim, Cheol-Hee
description To validate the Geostationary Environment Monitoring Spectrometer (GEMS), the GEMS Map of Air Pollution (GMAP) campaign was conducted during 2020-2021 by integrating Pandora Asia Network, aircraft, and in situ measurements. In the present study, GMAP-2020 measurements were applied to evaluate urban air quality and explore the synergy of Pandora column (PC) NO.sub.2 measurements and surface in situ (SI) NO.sub.2 measurements for Seosan, South Korea, where large point source (LPS) emissions are densely clustered. Due to the difficulty of interpreting the effects of LPS emissions on air quality downwind of Seosan using SI monitoring networks alone, we explored the combined analysis of both PC-NO.sub.2 and SI-NO.sub.2 measurements. Agglomerative hierarchical clustering using vertical meteorological variables combined with PC-NO.sub.2 and SI-NO.sub.2 yielded three distinct conditions: synoptic wind-dominant (SD), mixed (MD), and local wind-dominant (LD). These results suggest meteorology-dependent correlations between PC-NO.sub.2 and SI-NO.sub.2 . Overall, yearly daytime mean (11:00-17:00 KST) PC-NO.sub.2 and SI-NO.sub.2 statistical data showed good linear correlations (R=â¼0.73); however, the differences in correlations were largely attributed to meteorological conditions. SD conditions characterized by higher wind speeds and advected marine boundary layer heights suppressed fluctuations in both PC-NO.sub.2 and SI-NO.sub.2, driving a uniform vertical NO.sub.2 structure with higher correlations, whereas under LD conditions, LPS plumes were decoupled from the surface or were transported from nearby cities, weakening correlations through anomalous vertical NO.sub.2 gradients. The discrepancies suggest that using either PC-NO.sub.2 or SI-NO.sub.2 observations alone involves a higher possibility of uncertainty under LD conditions or prevailing transport processes. However, under MD conditions, both pollution ventilation due to high surface wind speeds and daytime photochemical NO.sub.2 loss contributed to stronger correlations through a decline in both PC-NO.sub.2 and SI-NO.sub.2 towards noon. Thus, Pandora Asia Network observations collected over 13 Asian countries since 2021 can be utilized for detailed investigation of the vertical complexity of air quality, and the conclusions can be also applied when performing GEMS observation interpretation in combination with SI measurements.
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Overall, yearly daytime mean (11:00-17:00 KST) PC-NO.sub.2 and SI-NO.sub.2 statistical data showed good linear correlations (R=â¼0.73); however, the differences in correlations were largely attributed to meteorological conditions. SD conditions characterized by higher wind speeds and advected marine boundary layer heights suppressed fluctuations in both PC-NO.sub.2 and SI-NO.sub.2, driving a uniform vertical NO.sub.2 structure with higher correlations, whereas under LD conditions, LPS plumes were decoupled from the surface or were transported from nearby cities, weakening correlations through anomalous vertical NO.sub.2 gradients. The discrepancies suggest that using either PC-NO.sub.2 or SI-NO.sub.2 observations alone involves a higher possibility of uncertainty under LD conditions or prevailing transport processes. 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Air quality
Analysis
title Evaluation of correlated Pandora column NO.sub.2 and in situ surface NO.sub.2 measurements during GMAP campaign
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