{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,23]],"date-time":"2026-01-23T10:29:34Z","timestamp":1769164174365,"version":"3.49.0"},"reference-count":53,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2021,10,5]],"date-time":"2021-10-05T00:00:00Z","timestamp":1633392000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100010700","name":"National Institute of Environmental Research","doi-asserted-by":"publisher","award":["NIER-2021-01-01-052"],"award-info":[{"award-number":["NIER-2021-01-01-052"]}],"id":[{"id":"10.13039\/501100010700","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Atmospheric carbon monoxide (CO) significantly impacts climate change and human health, and has become the focus of increased air quality and climate research. Since 2018, the Troposphere Monitoring Instrument (TROPOMI) has provided total column amounts of CO (CTROPOMI) with a high spatial resolution to monitor atmospheric CO. This study compared and assessed the accuracy of CTROPOMI measurements using surface in-situ measurements (SKME) obtained from an extensive ground-based network over South Korea, where CO level is persistently affected by both local emissions and trans-boundary transport. Our analysis reveals that the TROPOMI effectively detected major emission sources of CO over South Korea and efficiently complemented the spatial coverage of the ground-based network. In general, the correlations between CTROPOMI and SKME were lower than those for NO2 reported in a previous study, and this discrepancy was partly attributed to the lower spatiotemporal variability. Moreover, vertical CO profiles were sampled from the ECMWF CAMS reanalysis data (EAC4) to convert CTROPOMI to surface mixing ratios (STROPOMI). STROPOMI showed a significant underestimation compared with SKME by approximately 40%, with a moderate correlation of approximately 0.51. The low biases of STROPOMI were more significant during the winter season, which was mainly attributed to the underestimation of the EAC4 CO at the surface. This study can contribute to the assessment of satellite and model data for monitoring surface air quality and greenhouse gas emissions.<\/jats:p>","DOI":"10.3390\/rs13193987","type":"journal-article","created":{"date-parts":[[2021,10,8]],"date-time":"2021-10-08T21:26:20Z","timestamp":1633728380000},"page":"3987","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Comparison of Total Column and Surface Mixing Ratio of Carbon Monoxide Derived from the TROPOMI\/Sentinel-5 Precursor with In-Situ Measurements from Extensive Ground-Based Network over South Korea"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8124-1495","authenticated-orcid":false,"given":"Ukkyo","family":"Jeong","sequence":"first","affiliation":[{"name":"Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD 20740, USA"},{"name":"NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA"}]},{"given":"Hyunkee","family":"Hong","sequence":"additional","affiliation":[{"name":"National Institute of Environmental Research, Seogu Hwangyong-ro 42, Incheon 22689, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"8931","DOI":"10.1029\/1999JD901006","article-title":"Three-dimensional climatological distribution of tropospheric OH: Update and evaluation","volume":"105","author":"Spivakovsky","year":"2000","journal-title":"J. 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