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Lee, Myong-In
UNIST Climate Environment Modeling Lab.
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dc.citation.startPage 120896 -
dc.citation.title ATMOSPHERIC ENVIRONMENT -
dc.citation.volume 340 -
dc.contributor.author Cha, Yesol -
dc.contributor.author Lee, Jong-Jae -
dc.contributor.author Song, Chul Han -
dc.contributor.author Kim, Soontae -
dc.contributor.author Park, Rokjin J. -
dc.contributor.author Lee, Myong-In -
dc.contributor.author Woo, Jung-Hun -
dc.contributor.author Choi, Jae-Ho -
dc.contributor.author Bae, Kangho -
dc.contributor.author Yu, Jinhyeok -
dc.contributor.author Kim, Eunhye -
dc.contributor.author Kim, Hyeonmin -
dc.contributor.author Lee, Seung-Hee -
dc.contributor.author Kim, Jinseok -
dc.contributor.author Chang, Lim-Seok -
dc.contributor.author Jeon, Kwon-ho -
dc.contributor.author Song, Chang-Keun -
dc.date.accessioned 2024-12-04T10:05:06Z -
dc.date.available 2024-12-04T10:05:06Z -
dc.date.created 2024-11-29 -
dc.date.issued 2025-01 -
dc.description.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. -
dc.identifier.bibliographicCitation ATMOSPHERIC ENVIRONMENT, v.340, pp.120896 -
dc.identifier.doi 10.1016/j.atmosenv.2024.120896 -
dc.identifier.issn 1352-2310 -
dc.identifier.scopusid 2-s2.0-85207867468 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/84671 -
dc.identifier.wosid 001350436500001 -
dc.language 영어 -
dc.publisher PERGAMON-ELSEVIER SCIENCE LTD -
dc.title Investigating uncertainties in air quality models used in GMAP/SIJAQ 2021 field campaign: General performance of different models and ensemble results -
dc.type Article -
dc.description.isOpenAccess TRUE -
dc.relation.journalWebOfScienceCategory Environmental Sciences; Meteorology & Atmospheric Sciences -
dc.relation.journalResearchArea Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences -
dc.type.docType Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor Model ensemble -
dc.subject.keywordAuthor Performance evaluation -
dc.subject.keywordAuthor Air quality -
dc.subject.keywordAuthor GMAP/SIJAQ 2021 field campaign -
dc.subject.keywordPlus EMISSIONS -
dc.subject.keywordPlus WRF-CHEM -
dc.subject.keywordPlus SOUTH-KOREA -
dc.subject.keywordPlus CUMULUS PARAMETERIZATION -
dc.subject.keywordPlus IMPACTS -
dc.subject.keywordPlus MULTIMODEL SIMULATIONS -
dc.subject.keywordPlus LAND-USE -
dc.subject.keywordPlus AEROSOL -
dc.subject.keywordPlus CHEMISTRY -
dc.subject.keywordPlus CHINA -

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