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Investigating uncertainties in air quality models used in GMAP/SIJAQ 2021 field campaign: General performance of different models and ensemble resultsoa mark
  • Cha, Yesol ;
  • Lee, Jong Jae ;
  • Song, Chul Han ;
  • Kim, Soontae ;
  • Park, Rokjin J. ;
  • Lee, Myong In ;
  • Woo, Jung Hun ;
  • Choi, Jae Ho ;
  • Bae, Kangho ;
  • Yu, Jinhyeok ;
  • Kim, Eunhye ;
  • Kim, Hyeonmin ;
  • Lee, Seung Hee ;
  • Kim, Jinseok ;
  • Chang, Lim Seok ;
  • Jeon, Kwon ho ;
  • Song, Chang Keun
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Publication Year
2025-01-01
Publisher
Elsevier Ltd
Citation
Atmospheric Environment, Vol.340
Keyword
Air qualityGMAP/SIJAQ 2021 field campaignModel ensemblePerformance evaluation
Mesh Keyword
'currentChemical transport modelsElemental carbonField campaignGMAP/SIJAQ 2021 field campaignModel ensemblesPerformancePerformances evaluationPM 2.5Uncertainty
All Science Classification Codes (ASJC)
Environmental Science (all)Atmospheric Science
Abstract
The international field campaign, GMAP/SIJAQ 2021, was conducted in Korea from October 18th to November 25th to enhance the performance and validation of the Geostationary Environment Monitoring Spectrometer (GEMS) products algorithm and obtain a better understanding of the current air pollution status of the Korean Peninsula. Five chemical transport models (CTMs), including CMAQ, CMAQ-GIST, CAMx, WRF-Chem, and WRF GEOS-Chem, were utilized during the campaign to assist in organizing the observation plan and identifying changes in pollutant concentrations and their spatiotemporal distribution in Korea following the Korea–United States Air Quality (KORUS-AQ) 2016. In this study, we evaluated the forecasting performance, strengths, and limitations of these five CTMs and their ensemble in simulating air quality. Intensive measurement data and intercomparisons were employed to explain discrepancies between observed and simulated results. A comparison of the CTM ensemble results for PM2.5 and various gaseous pollutants between the current GMAP/SIJAQ 2021 and previous KORUS-AQ 2016 campaigns showed the R-value for the total mass PM2.5 concentration increased from 0.88 to 0.94. This improvement is related to CTM updates, including the emission inventory and better reproductions of the concentrations of gaseous species. However, the models consistently underestimated carbon monoxide (CO) concentrations, similar to the results from KORUS-AQ. This finding still suggests a further challenge that requires consideration of missing anthropogenic sources. The results of the ensemble model agreed well with the chemical composition of PM2.5 observed at the intensive monitoring station. However, for NO3− and NH4+, discrepancies were primarily due to inaccuracies in the meteorological inputs, such as precipitation, relative humidity (RH), and nighttime planetary boundary layer height (PBLH) in the CTMs. Hence, all models overestimated the concentration of elemental carbon (EC), therefore, it is necessary to revise EC emissions in the SIJAQv2 inventory, as these apply to unusual levels recorded in Seoul during the reference year of 2018.
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/34563
DOI
https://doi.org/10.1016/j.atmosenv.2024.120896
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Type
Article
Funding
This work was supported by grants from the Korea Environment Industry & Technology Institute ( KEITI ) through \\\Climate Change R&D Project for New Climate Regime\\\ funded by the Korea Ministry of Environment ( MOE ) [Grant Number 2022003560002] and the National Institute of Environment Research ( NIER ) funded by the Ministry of Environment ( MOE ) of the Republic of Korea [Grant Number NIER-2022-04-02-037, NIER-2024-03-02-014, and NIER-2021-03-03-007].
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Kim, Soontae  Image
Kim, Soontae 김순태
Department of Environmental and Safety Engineering
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