Articles | Volume 17, issue 1
https://doi.org/10.5194/amt-17-197-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-17-197-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Airborne observation with a low-cost hyperspectral instrument: retrieval of NO2 vertical column densities (VCDs) and the satellite sub-grid variability over industrial point sources
Jong-Uk Park
School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea
Hyun-Jae Kim
Climate and Air Quality Research Department, National Institute of Environmental Research, Incheon, South Korea
Jin-Soo Park
Climate and Air Quality Research Department, National Institute of Environmental Research, Incheon, South Korea
Jinsoo Choi
Climate and Air Quality Research Department, National Institute of Environmental Research, Incheon, South Korea
Sang Seo Park
Department of Civil Urban Earth and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
Kangho Bae
Department of Civil Urban Earth and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
Jong-Jae Lee
Department of Civil Urban Earth and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
Chang-Keun Song
Department of Civil Urban Earth and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea
Graduate School of Carbon Neutrality, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, South Korea
Research & Management Center for Particulate Matters at the Southeast Region of Korea, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, South Korea
Soojin Park
School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea
Kyuseok Shim
School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea
Yeonsoo Cho
School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea
School of Earth and Environmental Sciences, Seoul National University, Seoul, South Korea
Related authors
Kezia Lange, Andreas Richter, Tim Bösch, Bianca Zilker, Miriam Latsch, Lisa K. Behrens, Chisom M. Okafor, Hartmut Bösch, John P. Burrows, Alexis Merlaud, Gaia Pinardi, Caroline Fayt, Martina M. Friedrich, Ermioni Dimitropoulou, Michel Van Roozendael, Steffen Ziegler, Simona Ripperger-Lukosiunaite, Leon Kuhn, Bianca Lauster, Thomas Wagner, Hyunkee Hong, Donghee Kim, Lim-Seok Chang, Kangho Bae, Chang-Keun Song, Jong-Uk Park, and Hanlim Lee
Atmos. Meas. Tech., 17, 6315–6344, https://doi.org/10.5194/amt-17-6315-2024, https://doi.org/10.5194/amt-17-6315-2024, 2024
Short summary
Short summary
Instruments for air quality observations on geostationary satellites provide multiple observations per day and allow for the analysis of the diurnal variation of important air pollutants such as nitrogen dioxide (NO2) over large areas. The South Korean instrument GEMS, launched in February 2020, is the first instrument in geostationary orbit and covers a large part of Asia. Our investigations show the observed diurnal evolution of NO2 at different measurement sites.
Sang Seo Park, Jhoon Kim, Yeseul Cho, Hanlim Lee, Junsung Park, Dong-Won Lee, Won-Jin Lee, and Deok-Rae Kim
Atmos. Meas. Tech., 18, 2241–2259, https://doi.org/10.5194/amt-18-2241-2025, https://doi.org/10.5194/amt-18-2241-2025, 2025
Short summary
Short summary
An operational aerosol effective height (AEH) retrieval algorithm for the Geostationary Environment Monitoring Spectrometer (GEMS) was developed that solely uses the O2–O2 absorption band considering aerosol and surface properties. AEH retrievals are only performed when aerosol optical depth is larger than 0.3. The retrieval results show significant estimations by comparing the aerosol height from the Cloud–Aerosol Lidar with Orthogonal Polarization and the Tropospheric Monitoring Instrument.
Hyerim Kim, Xi Chen, Jun Wang, Zhendong Lu, Meng Zhou, Gregory R. Carmichael, Sang Seo Park, and Jhoon Kim
Atmos. Meas. Tech., 18, 327–349, https://doi.org/10.5194/amt-18-327-2025, https://doi.org/10.5194/amt-18-327-2025, 2025
Short summary
Short summary
We compare passive aerosol layer height (ALH) retrievals from the Earth Polychromatic Imaging Camera (EPIC), TROPOspheric Monitoring Instrument (TROPOMI), and Geostationary Environment Monitoring Spectrometer (GEMS) with lidar. GEMS shows a lower correlation (R = 0.64) than EPIC and TROPOMI (R > 0.7) but with minimal bias (0.1 km vs. overestimated by ~0.8 km). GEMS performance is improved for an ultraviolet aerosol index ≥ 3. EPIC and GEMS ALH diurnal variation differs slightly.
Eui-Jong Kang, Byung-Ju Sohn, Sang-Woo Kim, Wonho Kim, Young-Cheol Kwon, Seung-Bum Kim, Hyoung-Wook Chun, and Chao Liu
Geosci. Model Dev., 17, 8553–8568, https://doi.org/10.5194/gmd-17-8553-2024, https://doi.org/10.5194/gmd-17-8553-2024, 2024
Short summary
Short summary
Sea surface temperature (SST) is vital in climate, weather, and ocean sciences because it influences air–sea interactions. Errors in the ECMWF model's scheme for predicting ocean skin temperature prompted a revision of the ocean mixed layer model. Validation against infrared measurements and buoys showed a good correlation with minimal deviations. The revised model accurately simulates SST variations and aligns with solar radiation distributions, showing promise for weather and climate models.
Kezia Lange, Andreas Richter, Tim Bösch, Bianca Zilker, Miriam Latsch, Lisa K. Behrens, Chisom M. Okafor, Hartmut Bösch, John P. Burrows, Alexis Merlaud, Gaia Pinardi, Caroline Fayt, Martina M. Friedrich, Ermioni Dimitropoulou, Michel Van Roozendael, Steffen Ziegler, Simona Ripperger-Lukosiunaite, Leon Kuhn, Bianca Lauster, Thomas Wagner, Hyunkee Hong, Donghee Kim, Lim-Seok Chang, Kangho Bae, Chang-Keun Song, Jong-Uk Park, and Hanlim Lee
Atmos. Meas. Tech., 17, 6315–6344, https://doi.org/10.5194/amt-17-6315-2024, https://doi.org/10.5194/amt-17-6315-2024, 2024
Short summary
Short summary
Instruments for air quality observations on geostationary satellites provide multiple observations per day and allow for the analysis of the diurnal variation of important air pollutants such as nitrogen dioxide (NO2) over large areas. The South Korean instrument GEMS, launched in February 2020, is the first instrument in geostationary orbit and covers a large part of Asia. Our investigations show the observed diurnal evolution of NO2 at different measurement sites.
Yeseul Cho, Jhoon Kim, Sujung Go, Mijin Kim, Seoyoung Lee, Minseok Kim, Heesung Chong, Won-Jin Lee, Dong-Won Lee, Omar Torres, and Sang Seo Park
Atmos. Meas. Tech., 17, 4369–4390, https://doi.org/10.5194/amt-17-4369-2024, https://doi.org/10.5194/amt-17-4369-2024, 2024
Short summary
Short summary
Aerosol optical properties have been provided by the Geostationary Environment Monitoring Spectrometer (GEMS), the world’s first geostationary-Earth-orbit (GEO) satellite instrument designed for atmospheric environmental monitoring. This study describes improvements made to the GEMS aerosol retrieval algorithm (AERAOD) and presents its validation results. These enhancements aim to provide more accurate and reliable aerosol-monitoring results for Asia.
Yujin Jo, Myoseon Jang, Sanghee Han, Azad Madhu, Bonyoung Koo, Yiqin Jia, Zechen Yu, Soontae Kim, and Jinsoo Park
Atmos. Chem. Phys., 24, 487–508, https://doi.org/10.5194/acp-24-487-2024, https://doi.org/10.5194/acp-24-487-2024, 2024
Short summary
Short summary
The CAMx–UNIPAR model simulated the SOA budget formed via multiphase reactions of hydrocarbons and the impact of emissions and climate on SOA characteristics under California’s urban environments during winter 2018. SOA growth was dominated by daytime oxidation of long-chain alkanes and nighttime terpene oxidation with O3 and NO−3 radicals. The spatial distributions of anthropogenic SOA were affected by the northwesterly wind, whereas those of biogenic SOA were insensitive to wind directions.
Serin Kim, Daewon Kim, Hyunkee Hong, Lim-Seok Chang, Hanlim Lee, Deok-Rae Kim, Donghee Kim, Jeong-Ah Yu, Dongwon Lee, Ukkyo Jeong, Chang-Kuen Song, Sang-Woo Kim, Sang Seo Park, Jhoon Kim, Thomas F. Hanisco, Junsung Park, Wonei Choi, and Kwangyul Lee
Atmos. Meas. Tech., 16, 3959–3972, https://doi.org/10.5194/amt-16-3959-2023, https://doi.org/10.5194/amt-16-3959-2023, 2023
Short summary
Short summary
A first evaluation of the Geostationary Environmental Monitoring Spectrometer (GEMS) NO2 was carried out via comparison with the NO2 data obtained from the ground-based Pandora direct-sun measurements at four sites in Seosan, Republic of Korea. Comparisons between GEMS NO2 and Pandora NO2 were performed according to GEMS cloud fraction. GEMS NO2 showed good agreement with that of Pandora NO2 under less cloudy conditions.
Minseok Kim, Jhoon Kim, Hyunkwang Lim, Seoyoung Lee, Yeseul Cho, Huidong Yeo, and Sang-Woo Kim
Atmos. Meas. Tech., 16, 2673–2690, https://doi.org/10.5194/amt-16-2673-2023, https://doi.org/10.5194/amt-16-2673-2023, 2023
Short summary
Short summary
Aerosol height information is important when seeking an understanding of the vertical structure of the aerosol layer and long-range transport. In this study, a geometrical aerosol top height (ATH) retrieval using a parallax of two geostationary satellites is investigated. With sufficient longitudinal separation between the two satellites, a decent ATH product could be retrieved.
Shixian Zhai, Daniel J. Jacob, Drew C. Pendergrass, Nadia K. Colombi, Viral Shah, Laura Hyesung Yang, Qiang Zhang, Shuxiao Wang, Hwajin Kim, Yele Sun, Jin-Soo Choi, Jin-Soo Park, Gan Luo, Fangqun Yu, Jung-Hun Woo, Younha Kim, Jack E. Dibb, Taehyoung Lee, Jin-Seok Han, Bruce E. Anderson, Ke Li, and Hong Liao
Atmos. Chem. Phys., 23, 4271–4281, https://doi.org/10.5194/acp-23-4271-2023, https://doi.org/10.5194/acp-23-4271-2023, 2023
Short summary
Short summary
Anthropogenic fugitive dust in East Asia not only causes severe coarse particulate matter air pollution problems, but also affects fine particulate nitrate. Due to emission control efforts, coarse PM decreased steadily. We find that the decrease of coarse PM is a major driver for a lack of decrease of fine particulate nitrate, as it allows more nitric acid to form fine particulate nitrate. The continuing decrease of coarse PM requires more stringent ammonia and nitrogen oxides emission controls.
Zechen Yu, Myoseon Jang, Soontae Kim, Kyuwon Son, Sanghee Han, Azad Madhu, and Jinsoo Park
Atmos. Chem. Phys., 22, 9083–9098, https://doi.org/10.5194/acp-22-9083-2022, https://doi.org/10.5194/acp-22-9083-2022, 2022
Short summary
Short summary
The UNIPAR model was incorporated into CAMx to predict the ambient concentration of organic matter in urban atmospheres during the KORUS-AQ campaign. CAMx–UNIPAR significantly improved the simulation of SOA formation under the wet aerosol condition through the consideration of aqueous reactions of reactive organic species and gas–aqueous partitioning into the wet inorganic aerosol.
Clémence Rose, Martine Collaud Coen, Elisabeth Andrews, Yong Lin, Isaline Bossert, Cathrine Lund Myhre, Thomas Tuch, Alfred Wiedensohler, Markus Fiebig, Pasi Aalto, Andrés Alastuey, Elisabeth Alonso-Blanco, Marcos Andrade, Begoña Artíñano, Todor Arsov, Urs Baltensperger, Susanne Bastian, Olaf Bath, Johan Paul Beukes, Benjamin T. Brem, Nicolas Bukowiecki, Juan Andrés Casquero-Vera, Sébastien Conil, Konstantinos Eleftheriadis, Olivier Favez, Harald Flentje, Maria I. Gini, Francisco Javier Gómez-Moreno, Martin Gysel-Beer, Anna Gannet Hallar, Ivo Kalapov, Nikos Kalivitis, Anne Kasper-Giebl, Melita Keywood, Jeong Eun Kim, Sang-Woo Kim, Adam Kristensson, Markku Kulmala, Heikki Lihavainen, Neng-Huei Lin, Hassan Lyamani, Angela Marinoni, Sebastiao Martins Dos Santos, Olga L. Mayol-Bracero, Frank Meinhardt, Maik Merkel, Jean-Marc Metzger, Nikolaos Mihalopoulos, Jakub Ondracek, Marco Pandolfi, Noemi Pérez, Tuukka Petäjä, Jean-Eudes Petit, David Picard, Jean-Marc Pichon, Veronique Pont, Jean-Philippe Putaud, Fabienne Reisen, Karine Sellegri, Sangeeta Sharma, Gerhard Schauer, Patrick Sheridan, James Patrick Sherman, Andreas Schwerin, Ralf Sohmer, Mar Sorribas, Junying Sun, Pierre Tulet, Ville Vakkari, Pieter Gideon van Zyl, Fernando Velarde, Paolo Villani, Stergios Vratolis, Zdenek Wagner, Sheng-Hsiang Wang, Kay Weinhold, Rolf Weller, Margarita Yela, Vladimir Zdimal, and Paolo Laj
Atmos. Chem. Phys., 21, 17185–17223, https://doi.org/10.5194/acp-21-17185-2021, https://doi.org/10.5194/acp-21-17185-2021, 2021
Short summary
Short summary
Aerosol particles are a complex component of the atmospheric system the effects of which are among the most uncertain in climate change projections. Using data collected at 62 stations, this study provides the most up-to-date picture of the spatial distribution of particle number concentration and size distribution worldwide, with the aim of contributing to better representation of aerosols and their interactions with clouds in models and, therefore, better evaluation of their impact on climate.
Chinmoy Sarkar, Gracie Wong, Anne Mielnik, Sanjeevi Nagalingam, Nicole Jenna Gross, Alex B. Guenther, Taehyoung Lee, Taehyun Park, Jihee Ban, Seokwon Kang, Jin-Soo Park, Joonyoung Ahn, Danbi Kim, Hyunjae Kim, Jinsoo Choi, Beom-Keun Seo, Jong-Ho Kim, Jeong-Ho Kim, Soo Bog Park, and Saewung Kim
Atmos. Chem. Phys., 21, 11505–11518, https://doi.org/10.5194/acp-21-11505-2021, https://doi.org/10.5194/acp-21-11505-2021, 2021
Short summary
Short summary
We present experimental proofs illustrating the emission of an unexplored volatile organic compound, tentatively assigned as ketene, in an industrial facility in South Korea. The emission of such a compound has rarely been reported, but our experimental data show that the emission rate is substantial. It potentially has tremendous implications for regional air quality and public health, as it is highly reactive and toxic at the same time.
Hyunkwang Lim, Sujung Go, Jhoon Kim, Myungje Choi, Seoyoung Lee, Chang-Keun Song, and Yasuko Kasai
Atmos. Meas. Tech., 14, 4575–4592, https://doi.org/10.5194/amt-14-4575-2021, https://doi.org/10.5194/amt-14-4575-2021, 2021
Short summary
Short summary
Aerosol property observations by satellites from geostationary Earth orbit (GEO) in particular have advantages of frequent sampling better than 1 h in addition to broader spatial coverage. This study provides data fusion products of aerosol optical properties from four different algorithms for two different GEO satellites: GOCI and AHI. The fused aerosol products adopted ensemble-mean and maximum-likelihood estimation methods. The data fusion provides improved results with better accuracy.
Saehee Lim, Meehye Lee, Paolo Laj, Sang-Woo Kim, Kang-Ho Ahn, Junsoo Gil, Xiaona Shang, Marco Zanatta, and Kyeong-Sik Kang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-1247, https://doi.org/10.5194/acp-2020-1247, 2021
Preprint withdrawn
Short summary
Short summary
This study identifies the main drivers of the formation and transformation processes of submicron particles and highlights that the thick coating of rBC was a result of active conversion of hygroscopic inorganic salts leading to fine aerosol pollution. Consequently, we suggest BC particles as a key contributor to PM2.5 mass increase, which implies that BC reduction is an effective mitigation against haze pollution as well as climate change in Northeast Asia.
Cited articles
Appel, W., Napelenok, S., Hogrefe, C., Pouliot, G., Foley, K., Roselle, S., Pleim, J., Bash, J., Pye, H., Heath, N., Murphy, B., and Mathur, R.: Overview and Evaluation of the Community Multiscale Air Quality (CMAQ) Modeling System Version 5.2, Chapter 11, Air Pollution Modeling and its Application XXV, Springer International Publishing AG, Cham (ZG), Switzerland, 69–73, https://doi.org/10.1007/978-3-319-57645-9_11, 2017.
Bak, J., Coddington, O., Liu, X., Chance, K., Lee, H. J., Jeon, W., Kim, J. H., and Kim, C. H.: Impact of using a new high-resolution solar reference spectrum on OMI ozone profile retrievals, Remote Sens.-Basel, 14, 1–12, https://doi.org/10.3390/rs14010037, 2021.
Beirle, S., Boersma, K. F., Platt, U., Lawrence, M. G., and Wagner, T.: Megacity emissions and lifetimes of nitrogen oxides probed from space, Science, 333, 1737–1739, https://doi.org/10.1126/science.1207824, 2011.
Boersma, K. F., Eskes, H. J., Richter, A., De Smedt, I., Lorente, A., Beirle, S., van Geffen, J. H. G. M., Zara, M., Peters, E., Van Roozendael, M., Wagner, T., Maasakkers, J. D., van der A, R. J., Nightingale, J., De Rudder, A., Irie, H., Pinardi, G., Lambert, J.-C., and Compernolle, S. C.: Improving algorithms and uncertainty estimates for satellite NO2 retrievals: results from the quality assurance for the essential climate variables (QA4ECV) project, Atmos. Meas. Tech., 11, 6651–6678, https://doi.org/10.5194/amt-11-6651-2018, 2018.
Brewer, A. W. and Kerr, J. B.: Total Ozone Measurements in Cloudy Weather, Pure Appl. Geophys., 106, 928–937, 1973.
Brewer, A. W., McElroy, C. T., and Kerr, J. B.: Nitrogen Dioxide Concentrations in the Atmosphere, Nature, 246, 129–133, 1973.
Burrows, J. P., Buchwitz, M., Rozanov, V., Weber, M., Richter, A., Ladstätter-Weißenmayer, A., and Eisinger, M.: The Global Ozone Monitoring Experiment (GOME): Mission, instrument concept, and first scientific results, European Space Agency Special Publication, 414 PART 2, 585–590, 1997.
Chan, A. W. H., Chan, M. N., Surratt, J. D., Chhabra, P. S., Loza, C. L., Crounse, J. D., Yee, L. D., Flagan, R. C., Wennberg, P. O., and Seinfeld, J. H.: Role of aldehyde chemistry and NOx concentrations in secondary organic aerosol formation, Atmos. Chem. Phys., 10, 7169–7188, https://doi.org/10.5194/acp-10-7169-2010, 2010.
CleanSYS: Continuous Emission Monitoring System, Ministry of Environment, Republic of Korea government, https://www.stacknsky.or.kr/eng/index.html, last access: 30 June 2023.
Choo, G.-H., Lee, K., Hong, H., Jeong, U., Choi, W., and Janz, S. J.: Highly resolved mapping of NO2 vertical column densities from GeoTASO measurements over a megacity and industrial area during the KORUS-AQ campaign, Atmos. Meas. Tech., 16, 625–644, https://doi.org/10.5194/amt-16-625-2023, 2023.
Coddington, O. M., Richard, E. C., Harber, D., Pilewskie, P., Woods, T. N., Chance, K., Liu, X., and Sun, K.: The TSIS-1 Hybrid Solar Reference Spectrum, Geophys. Res. Lett., 48, e2020GL091709, https://doi.org/10.1029/2020GL091709, 2021.
Colombi, N. K., Jacob, D. J., Yang, L. H., Zhai, S., Shah, V., Grange, S. K., Yantosca, R. M., Kim, S., and Liao, H.: Why is ozone in South Korea and the Seoul metropolitan area so high and increasing?, Atmos. Chem. Phys., 23, 4031–4044, https://doi.org/10.5194/acp-23-4031-2023, 2023.
Dobson, G. M. B.: Observers' handbook for the ozone spectrophotometer, in: Annals of the International Geophysical Year, Pergamon Press, V, Part 1, 46–89, 1957a.
Dobson, G. M. B.: Adjustment and calibration of the ozone spectrophotometer, Pergamon Press, ibid. V, Part I, 90–113, 1957b.
Emde, C., Buras-Schnell, R., Kylling, A., Mayer, B., Gasteiger, J., Hamann, U., Kylling, J., Richter, B., Pause, C., Dowling, T., and Bugliaro, L.: The libRadtran software package for radiative transfer calculations (version 2.0.1), Geosci. Model Dev., 9, 1647–1672, https://doi.org/10.5194/gmd-9-1647-2016, 2016.
ESA and KNMI (Koninklijk Nederlands Meteorologisch Instituut): Sentinel-5P TROPOMI Tropospheric NO2 1-Orbit L2 5.5km x 3.5km, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], Greenbelt, MD, USA, https://doi.org/10.5270/S5P-9bnp8q8, 2021.
Hersbach, H., Bell, B., Berrisford, P., et al.: The ERA5 Global Reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on pressure levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.bd0915c6, 2023a.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47 2023b.
Holben B. N., Eck, T. F., Slutsker, I., Tanre, D., Buis, J. P., Setzer, A., Vermote, E., Reagan, J. A., Kaufman, Y., Nakajima, T., Lavenu, F., Jankowiak, I., and Smirnov, A.: AERONET – A federated instrument network and data archive for aerosol characterization, Remote Sens. Environ., 66, 1–16, https://doi.org/10.1016/S0034-4257(98)00031-5, 1998.
Itten, K. I., Dell'Endice, F., Hueni, A., Kneubühler, M., Schläpfer, D., Odermatt, D., Seidel, F., Huber, S., Schopfer, J., Kellenberger, T., Bühler, Y., D'Odorico, P., Nieke, J., Alberti, E., and Meuleman, K.: APEX – The hyperspectral ESA airborne prism experiment, Sensors-Basel, 8, 6235–6259, https://doi.org/10.3390/s8106235, 2008.
Jaffe, D. A. and Wigder, N. L.: Ozone production from wildfires: A critical review, Atmos. Environ., 51, 1–10, https://doi.org/10.1016/j.atmosenv.2011.11.063, 2012.
Jo, S., Kim, Y.-J., Park, K. W., Hwang, Y. S., Lee, S. H., Kim, B. J., and Chung, S. J.: Association of NO2 and Other Air Pollution Exposures With the Risk of Parkinson Disease, JAMA Neurol., 78, 800–808, https://doi.org/10.1001/jamaneurol.2021.1335, 2021.
Judd, L. M., Al-Saadi, J. A., Janz, S. J., Kowalewski, M. G., Pierce, R. B., Szykman, J. J., Valin, L. C., Swap, R., Cede, A., Mueller, M., Tiefengraber, M., Abuhassan, N., and Williams, D.: Evaluating the impact of spatial resolution on tropospheric NO2 column comparisons within urban areas using high-resolution airborne data, Atmos. Meas. Tech., 12, 6091–6111, https://doi.org/10.5194/amt-12-6091-2019, 2019.
Kampa, M. and Castanas, E.: Human health effects of air pollution, Environ. Pollut., 151, 362–367, https://doi.org/10.1016/j.envpol.2007.06.012, 2008.
Kang, M., Ahn, M. H., Liu, X., Jeong, U., and Kim, J.: Spectral calibration algorithm for the geostationary environment monitoring spectrometer (GEMS), Remote Sens.-Basel, 12, 1–17, https://doi.org/10.3390/rs12172846, 2020.
Kim, H. C., Bae, C., Bae, M., Kim, O., Kim, B. U., Yoo, C., Park, J., Choi, J., Lee, J.-bum, Lefer, B., Stein, A., and Kim, S.: Space-borne monitoring of NOx emissions from cement kilns in South Korea, Atmosphere, 11, 1–14, https://doi.org/10.3390/ATMOS11080881, 2020.
Kim, N. K., Kim, Y. P., Morino, Y., Kurokawa, J., and Ohara, T.: Verification of NOx emission inventory over South Korea using sectoral activity data and satellite observation of NO2 vertical column densities, Atmos. Environ., 77, 496–508, https://doi.org/10.1016/j.atmosenv.2013.05.042, 2013.
Kim, S.-W., Yoon, S.-C., Kim, J., and Kim, S.-Y.: Seasonal and monthly variations of columnar aerosol optical properties over east Asia determined from multi-year MODIS, LIDAR, and AERONET Sun/sky radiometer measuerements, Atmos. Environ., 41, 1634–1651, https://doi.org/10.1016/j.atmosenv.2006.10.044, 2007.
Kowalewski, M. G. and Janz, S. J.: Remote Sensing Capabilities of the Airborne Compact Atmospheric Mapper, Proc. SPIE, San Diego, California, USA, 2–6 August 2009, Earth Observing Systems XIV, 74520Q, https://doi.org/10.1117/12.827035, 2009.
Kowalewski, M. G. and Janz, S. J.: Remote sensing capabilities of the GEO-CAPE airborne simulator, Proc. SPIE, 9218, Earth Observing Systems XIX, San Diego, California, United States, 26 September 2014, SPIE, 92181I, https://doi.org/10.1117/12.2062058, 2014.
Lamsal, L. N., Martin, R. V., Parrish, D. D., and Krotkov, N. A.: Scaling relationship for NO2 pollution and urban population size: A satellite perspective, Environ. Sci. Technol., 47, 7855–7861, https://doi.org/10.1021/es400744g, 2013.
Lamsal, L. N., Janz, S. J., Krotkov, N. A., Pickering, K. E., Spurr, R. J. D., Kowalewski, M. G., Loughner, C. P., Crawford, J. H., Swartz, W. H., and Herman, J. R.: High-resolution NO2 observations from the airborne compact atmospheric mapper: Retrieval and validation, J. Geophys. Res., 122, 1953–1970, https://doi.org/10.1002/2016JD025483, 2017.
Leitch, J. W., Delker, T., Good, W., Ruppert, L., Murcray, F., Chance, K., Liu, X., Nowlan, C., Janz, S. J., Krotkov, N. A., Pickering, K. E., Kowalewski, M., and Wang, J.: The GeoTASO airborne spectrometer project, Proc. SPIE, 9218, Earth Observing Systems XIX, San Diego, California, United States, 2 October 2014, SPIE, 92181H, https://doi.org/10.1117/12.2063763, 2014.
Levelt, P. F., Van Den Oord, G. H. J., Dobber, M. R., Mälkki, A., Visser, H., De Vries, J., Stammes, P., Lundell, J. O. V., and Saari, H.: The ozone monitoring instrument, IEEE T. Geosci. Remote, 44, 1093–1100, https://doi.org/10.1109/TGRS.2006.872333, 2006.
Li, K., Jacob, D. J., Shen, L., Lu, X., De Smedt, I., and Liao, H.: Increases in surface ozone pollution in China from 2013 to 2019: anthropogenic and meteorological influences, Atmos. Chem. Phys., 20, 11423–11433, https://doi.org/10.5194/acp-20-11423-2020, 2020.
Liu, C., Liu, X., Kowalewski, M. G., Janz, S. J., González Abad, G., Pickering, K. E., Chance, K., and Lamsal, L. N.: Characterization and verification of ACAM slit functions for trace-gas retrievals during the 2011 DISCOVER-AQ flight campaign, Atmos. Meas. Tech., 8, 751–759, https://doi.org/10.5194/amt-8-751-2015, 2015.
Liu, F., Beirle, S., Zhang, Q., Dörner, S., He, K., and Wagner, T.: NOx lifetimes and emissions of cities and power plants in polluted background estimated by satellite observations, Atmos. Chem. Phys., 16, 5283–5298, https://doi.org/10.5194/acp-16-5283-2016, 2016.
Mayer, B. and Kylling, A.: Technical note: The libRadtran software package for radiative transfer calculations - description and examples of use, Atmos. Chem. Phys., 5, 1855–1877, https://doi.org/10.5194/acp-5-1855-2005, 2005.
Munro, R., Lang, R., Klaes, D., Poli, G., Retscher, C., Lindstrot, R., Huckle, R., Lacan, A., Grzegorski, M., Holdak, A., Kokhanovsky, A., Livschitz, J., and Eisinger, M.: The GOME-2 instrument on the Metop series of satellites: instrument design, calibration, and level 1 data processing – an overview, Atmos. Meas. Tech., 9, 1279–1301, https://doi.org/10.5194/amt-9-1279-2016, 2016.
Nehir, M., Frank, C., Aßmann, S., and Achterberg, E. P.: Improving Optical Measurements: Non-Linearity Compensation of Compact Charge-Coupled Device (CCD) Spectrometers, Sensors-Basel, 19, 2833, https://doi.org/10.3390/s19122833, 2019.
Nowlan, C. R., Liu, X., Leitch, J. W., Chance, K., González Abad, G., Liu, C., Zoogman, P., Cole, J., Delker, T., Good, W., Murcray, F., Ruppert, L., Soo, D., Follette-Cook, M. B., Janz, S. J., Kowalewski, M. G., Loughner, C. P., Pickering, K. E., Herman, J. R., Beaver, M. R., Long, R. W., Szykman, J. J., Judd, L. M., Kelley, P., Luke, W. T., Ren, X., and Al-Saadi, J. A.: Nitrogen dioxide observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument: Retrieval algorithm and measurements during DISCOVER-AQ Texas 2013, Atmos. Meas. Tech., 9, 2647–2668, https://doi.org/10.5194/amt-9-2647-2016, 2016.
Park, H. J., Park, J. S., Kim, S. W., Chong, H., Lee, H., Kim, H., Ahn, J. Y., Kim, D. G., Kim, J., and Park, S. S.: Retrieval of NO2 column amounts from ground-based hyperspectral imaging sensor measurements, Remote Sens.-Basel, 11, 3005, https://doi.org/10.3390/rs11243005, 2019.
Park, J.-U.: Nitrogen Dioxide vertical column densities from the Hyperspectral Imaging Sensor (HIS), V3, Harvard Dataverse [data set], https://doi.org/10.7910/DVN/YCZ9JU, 2023.
Park, J. U., Park, J. S., Diaz, D. S., Gebetsberger, M., Müller, M., Shalaby, L., Tiefengraber, M., Kim, H. J., Park, S. S., Song, C. K., and Kim, S. W.: Spatiotemporal inhomogeneity of total column NO2 in a polluted urban area inferred from TROPOMI and Pandora intercomparisons, GIScience Remote Sens., 59, 354–373, https://doi.org/10.1080/15481603.2022.2026640, 2022.
Platt, U. and Stutz, J.: Differential Optical Absorption Spectroscopy: Principles and Applications, Springer-Verlag, Berlin, Germany, https://doi.org/10.1007/978-3-540-75776-4, 2008.
Popp, C., Brunner, D., Damm, A., Van Roozendael, M., Fayt, C., and Buchmann, B.: High-resolution NO2 remote sensing from the Airborne Prism EXperiment (APEX) imaging spectrometer, Atmos. Meas. Tech., 5, 2211–2225, https://doi.org/10.5194/amt-5-2211-2012, 2012.
Pulli, T., Nevas, S., El Gawhary, O., van den Berg, S., Askola, J., Kärhä, P., Manoocheri, F., and Ikonen, E.: Nonlinearity characterization of array spectroradiometers for the solar UV measurements, Appl. Optices, 56, 3077–3086, https://doi.org/10.1364/AO.56.003077, 2017.
Schaaf, C., Wang, Z., Zhang, X., and Strahler, A.: VIIRS/NPP BRDF/Albedo Albedo Model Parameters Daily L3 Global 0.05Deg CMG V001, NASA EOSDIS Land Processes DAAC [data set], https://doi.org/10.5067/VIIRS/VNP43C1.001, 2019.
Schönhardt, A., Altube, P., Gerilowski, K., Krautwurst, S., Hartmann, J., Meier, A. C., Richter, A., and Burrows, J. P.: A wide field-of-view imaging DOAS instrument for two-dimensional trace gas mapping from aircraft, Atmos. Meas. Tech., 8, 5113–5131, https://doi.org/10.5194/amt-8-5113-2015, 2015.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, Wiley, 3rd edn., ISBN: 978-1-118-94740-1, 2016
Sillman, S.: The relation between ozone, NOx and hydrocarbons in urban and polluted rural environments, Atmos. Environ., 33, 1821–1845, https://doi.org/10.1016/S1474-8177(02)80015-8, 1999.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D. M., Duda, M. G., Huang, X.-Y., Wang, W., and Powers, J. G.: A Description of the Advanced Research WRF Version 3, NCAR Technical Note NCAR/TN-475+STR, 113 pp., https://doi.org/10.5065/D68S4MVH, 2008.
Song, J., Qu, R., Sun, B., Wang, Y., Chen, R., Kan, H., An, Z., Wu, H., Li, J., Jiang, J., Zhang, Y., and Wu, W.: Acute effects of ambient nitrogen dioxide exposure on serum biomarkers of nervous system damage in healthy older adults, Ecotoxicol. Environ. Saf., 249, 114423, https://doi.org/10.1016/j.ecoenv.2022.114423, 2023.
Spinei, E., Cede, A., Swartz, W. H., Herman, J., and Mount, G. H.: The use of NO2 absorption cross section temperature sensitivity to derive NO2 profile temperature and stratospheric–tropospheric column partitioning from visible direct-sun DOAS measurements, Atmos. Meas. Tech., 7, 4299–4316, https://doi.org/10.5194/amt-7-4299-2014, 2014.
Stark, M. S., Harrison, J. T. H., and Anastasi, C.: Formation of nitrogen oxides by electrical discharges and implications for atmospheric lightning, J. Geophys. Res.-Atmos., 101, 6963–6969, https://doi.org/10.1029/95JD03008, 1996.
Tack, F., Merlaud, A., Iordache, M.-D., Danckaert, T., Yu, H., Fayt, C., Meuleman, K., Deutsch, F., Fierens, F., and Van Roozendael, M.: High-resolution mapping of the NO2 spatial distribution over Belgian urban areas based on airborne APEX remote sensing, Atmos. Meas. Tech., 10, 1665–1688, https://doi.org/10.5194/amt-10-1665-2017, 2017.
Tack, F., Merlaud, A., Meier, A. C., Vlemmix, T., Ruhtz, T., Iordache, M.-D., Ge, X., van der Wal, L., Schuettemeyer, D., Ardelean, M., Calcan, A., Constantin, D., Schönhardt, A., Meuleman, K., Richter, A., and Van Roozendael, M.: Intercomparison of four airborne imaging DOAS systems for tropospheric NO2 mapping – the AROMAPEX campaign, Atmos. Meas. Tech., 12, 211–236, https://doi.org/10.5194/amt-12-211-2019, 2019.
Tack, F., Merlaud, A., Iordache, M.-D., Pinardi, G., Dimitropoulou, E., Eskes, H., Bomans, B., Veefkind, P., and Van Roozendael, M.: Assessment of the TROPOMI tropospheric NO2 product based on airborne APEX observations, Atmos. Meas. Tech., 14, 615–646, https://doi.org/10.5194/amt-14-615-2021, 2021.
Tang, W., Edwards, D. P., Emmons, L. K., Worden, H. M., Judd, L. M., Lamsal, L. N., Al-Saadi, J. A., Janz, S. J., Crawford, J. H., Deeter, M. N., Pfister, G., Buchholz, R. R., Gaubert, B., and Nowlan, C. R.: Assessing sub-grid variability within satellite pixels over urban regions using airborne mapping spectrometer measurements, Atmos. Meas. Tech., 14, 4639–4655, https://doi.org/10.5194/amt-14-4639-2021, 2021.
US EPA (United States Environmental Protection Agency): CMAQ, Version 5.2, Zenodo [software], https://doi.org/10.5281/zenodo.1167892, 2017.
Valin, L. C., Russell, A. R., and Cohen, R. C.: Variations of OH radical in an urban plume inferred from NO2 column measurements, Geophys. Res. Lett., 40, 1856–1860, https://doi.org/10.1002/grl.50267, 2013.
Vandaele, A. C., Hermans, C., Fally, S., Carleer, M., Mérienne, M.-F., Jenouvrier, A., Coquart, B., and Colin, R.: Absorption crosssections of NO2: simulation of temperature and pressure effects, J. Quant. Spectrosc. Ra., 76, 373–391, https://doi.org/10.1016/S0022-4073(02)00064-X, 2003.
Veefkind, J. P., Aben, I., McMullan, K., Förster, H., de Vries, J., Otter, G., Claas, J., Eskes, H. J., de Haan, J. F., Kleipool, Q., van Weele, M., Hasekamp, O., Hoogeveen, R., Landgraf, J., Snel, R., Tol, P., Ingmann, P., Voors, R., Kruizinga, B., Vink, R., Visser, H., and Levelt, P. F.: TROPOMI on the ESA Sentinel-5 Precursor: A GMES mission for global observations of the atmospheric composition for climate, air quality and ozone layer applications, Remote Sens. Environ., 120, 70–83, https://doi.org/10.1016/j.rse.2011.09.027, 2012.
Verhoelst, T., Compernolle, S., Pinardi, G., Lambert, J.-C., Eskes, H. J., Eichmann, K.-U., Fjæraa, A. M., Granville, J., Niemeijer, S., Cede, A., Tiefengraber, M., Hendrick, F., Pazmiño, A., Bais, A., Bazureau, A., Boersma, K. F., Bognar, K., Dehn, A., Donner, S., Elokhov, A., Gebetsberger, M., Goutail, F., Grutter de la Mora, M., Gruzdev, A., Gratsea, M., Hansen, G. H., Irie, H., Jepsen, N., Kanaya, Y., Karagkiozidis, D., Kivi, R., Kreher, K., Levelt, P. F., Liu, C., Müller, M., Navarro Comas, M., Piters, A. J. M., Pommereau, J.-P., Portafaix, T., Prados-Roman, C., Puentedura, O., Querel, R., Remmers, J., Richter, A., Rimmer, J., Rivera Cárdenas, C., Saavedra de Miguel, L., Sinyakov, V. P., Stremme, W., Strong, K., Van Roozendael, M., Veefkind, J. P., Wagner, T., Wittrock, F., Yela González, M., and Zehner, C.: Ground-based validation of the Copernicus Sentinel-5P TROPOMI NO2 measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks, Atmos. Meas. Tech., 14, 481–510, https://doi.org/10.5194/amt-14-481-2021, 2021.
Wang, S., Carpenter, D. A., DeJager, A., DiBella, J. A., Doran, J. E., Fabinski, R. P., Garland, A., Johnson, J. A., and Yaniga, R.: A 47 million pixel high-performance interline CCD image sensor, IEEE T. Electron Dev., 63, 174–181, https://doi.org/10.1109/TED.2015.2447214, 2016.
Woo, J.-H., Choi, K.-C., Kim, H. K., Baek, B. H., Jang, M. D., Eum, J.-H., Song, C.-H., Ma, Y.-I., Sunwoo, Y., Chang, L.-S., and Yoo, S.H.: Development of an anthropogenic emission processing system for Asia using SMOKE, Atmos. Environ., 58, 5–13, https://doi.org/10.1016/j.atmosenv.2011.10.042, 2012.
Woo, J.-H., Kim, Y. H., Kim, H.-K., Choi, K.-C., Eum, J.-H., Lee, J.-B., Lim, J.-H., Kim, J. Y., and Seong, M. A.: Development of the CREATE Inventory in Support of Integrated Climate and Air Quality Modeling for Asia, Sustainability, 12, 7930, https://doi.org/10.3390/su12197930, 2020.
Xie, S. X., Liao, D., and Chinchilli, V. M.: Measurement error reduction using weighted average method for repeated measurements from heterogeneous instruments, Environmetrics, 12, 785–790, https://doi.org/10.1002/env.511, 2001.
Short summary
The high-spatial-resolution NO2 vertical column densities (VCDs) were measured from airborne observations using the low-cost hyperspectral imaging sensor (HIS) at three industrial areas in South Korea with the newly developed versatile NO2 VCD retrieval algorithm apt to be applied to the instruments with volatile optical and radiometric properties. The airborne HIS observations emphasized the intensifying satellite sub-grid variability in NO2 VCDs near the emission sources.
The high-spatial-resolution NO2 vertical column densities (VCDs) were measured from airborne...