Articles | Volume 16, issue 16
https://doi.org/10.5194/amt-16-3959-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/amt-16-3959-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Aug 2023
Research article |
| 30 Aug 2023
| 30 Aug 2023
First-time comparison between NO2 vertical columns from Geostationary Environmental Monitoring Spectrometer (GEMS) and Pandora measurements
Serin Kim
Division of Earth Environmental System Science, Major of Spatial Information Engineering, Pukyong National University, Busan, Republic of Korea
Daewon Kim
CORRESPONDING AUTHOR
Division of Earth Environmental System Science, Major of Spatial Information Engineering, Pukyong National University, Busan, Republic of Korea
Hyunkee Hong
Environmental Satellite Center, National Institute of Environmental
Research, Incheon, Republic of Korea
Lim-Seok Chang
Environmental Satellite Center, National Institute of Environmental
Research, Incheon, Republic of Korea
Hanlim Lee
Division of Earth Environmental System Science, Major of Spatial Information Engineering, Pukyong National University, Busan, Republic of Korea
Deok-Rae Kim
Environmental Satellite Center, National Institute of Environmental
Research, Incheon, Republic of Korea
Donghee Kim
Environmental Satellite Center, National Institute of Environmental
Research, Incheon, Republic of Korea
Jeong-Ah Yu
Environmental Satellite Center, National Institute of Environmental
Research, Incheon, Republic of Korea
Dongwon Lee
Environmental Satellite Center, National Institute of Environmental
Research, Incheon, Republic of Korea
Ukkyo Jeong
Division of Earth Environmental System Science, Major of Spatial Information Engineering, Pukyong National University, Busan, Republic of Korea
Chang-Kuen Song
Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
Sang-Woo Kim
School of Earth and Environmental Sciences, Seoul National University, Seoul, Republic of Korea
Sang Seo Park
Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea
Jhoon Kim
Department of Atmospheric Sciences, Yonsei University, Seoul, Republic of Korea
Thomas F. Hanisco
Atmospheric Chemistry and Dynamics Lab, NASA Goddard Space Flight
Center, Greenbelt, MD, USA
Junsung Park
Division of Earth Environmental System Science, Major of Spatial Information Engineering, Pukyong National University, Busan, Republic of Korea
Wonei Choi
Division of Earth Environmental System Science, Major of Spatial Information Engineering, Pukyong National University, Busan, Republic of Korea
Kwangyul Lee
Air Quality Research Division, Climate and Air Quality Research
Department, National Institute of Environmental Research, Incheon, Republic
of Korea
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Christopher R. Oxford, Haihui Zhu, Maya Mehrotra, Xuan Liu, Yuxuan Ren, Maya Arnott, Isaac Abionum Adimula, Taiye Benjamin Ajibolataiye, Clement Akoshile, Omar Amador-Munoz, Araya Asfaw, Rachel Ying-Wen Chang, Sagnik Dey, Ann M. Dillner, David J. Diner, Connor J. Flynn, Diana Francis, Paterne Gahungu, Rebecca M. Garland, Michel Grutter, Sina Hasheminassab, Fahad Imam, Jhoon Kim, Kristy Langerman, Pei-Chen Lee, Puji Lestari, Po-Hsiung Lin, S. Marcela Loria-Salazar, Tesfaye Mamo, Olga L. Mayol-Bracero, Mogesh Naidoo, Narendra Nelli, Sang Seo Park, Abdus Salam, Bighnaraj Sarangi, Trailokya Saud, Robyn Schofield, Yoav Schechner, Sachchida N. Tripathi, Emily K. West, Eli Windwer, Ming-Tsang Wu, Qiang Zhang, Michael Brauer, Yinon Rudich, Jay R. Turner, and Randall V. Martin
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Jiajun Xiong, Yi Wang, Jun Wang, Yanyu Wang, Meng Zhou, Minghui Tao, Wenhui Dong, Jhoon Kim, and Lunche Wang
Atmos. Chem. Phys., 26, 8225–8253, https://doi.org/10.5194/acp-26-8225-2026, https://doi.org/10.5194/acp-26-8225-2026, 2026
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Julianna A. Christopoulos, Pablo E. Saide, Manas R. Mohanty, Nattamon Maneenoi, Jhoon Kim, Laura Judd, Katherine R. Travis, Savitri Garivait, Agapol Junpen, Kazuyuki Miyazaki, Jinkyul Choi, Takashi Sekiya, David Peterson, Theodore M. McHardy, Nicholas Gapp, Jason M. St. Clair, Erin Delaria, Glenn M. Wolfe, Abby Sebol, Alessandro Franchin, Changmin Cho, Morgan L. Silverman, and James H. Crawford
Atmos. Chem. Phys., 26, 8021–8050, https://doi.org/10.5194/acp-26-8021-2026, https://doi.org/10.5194/acp-26-8021-2026, 2026
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Juseon Bak, Arno Keppens, Daesung Choi, Sungjae Hong, Jae-Hwan Kim, Cheol-Hee Kim, Hyo-Jung Lee, Wonbae Jeon, Jhoon Kim, Ja-Ho Koo, Joowan Kim, Kanghyun Baek, Kai Yang, Xiong Liu, Gonzalo González Abad, Klaus-Peter Heue, Jean-Christopher Lambert, Yeonjin Jung, Hyunkee Hong, and Won-Jin Lee
Atmos. Meas. Tech., 19, 119–134, https://doi.org/10.5194/amt-19-119-2026, https://doi.org/10.5194/amt-19-119-2026, 2026
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This study presents the first complete description of the operational version 3 ozone profile retrieval algorithm for the Geostationary Environment Monitoring Spectrometer (GEMS) and its performance characteristics. Improvements in radiometric and wavelength calibration reduce spectral fitting uncertainties and enhance agreement with ozonesonde profiles and Pandora total ozone measurements.
Richard Ferrare, Johnathan Hair, Taylor Shingler, Chris Hostetler, Amin Nehrir, Marta Fenn, Amy Jo Scarino, Sharon Burton, Marian Clayton, James Collins, Laura Judd, James Crawford, Katherine Travis, Travis Toth, Pablo Saide, Jose Luis Jimenez, Pedro Campuzano-Jost, Guy Symonds, Richard Moore, Luke Ziemba, Michael Shook, Glenn Diskin, Joshua P. DiGangi, Ryan Bennett, Chia-Hsiang Ho, Lim-Seok Chang, Adisak Aiampisanuvong, and Ittipol Pawarmart
Atmos. Meas. Tech., 18, 7735–7766, https://doi.org/10.5194/amt-18-7735-2025, https://doi.org/10.5194/amt-18-7735-2025, 2025
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Huanxin Zhang, Jun Wang, Nathan Janechek, Cui Ge, Meng Zhou, Lorena Castro García, Tong Sha, Yanyu Wang, Weizhi Deng, Zhixin Xue, Chengzhe Li, Lakhima Chutia, Yi Wang, Sebastian Val, James L. McDuffie, Sina Hasheminassab, Scott E. Gluck, David J. Diner, Peter R. Colarco, Arlindo M. da Silva, and Jhoon Kim
Geosci. Model Dev., 18, 9061–9099, https://doi.org/10.5194/gmd-18-9061-2025, https://doi.org/10.5194/gmd-18-9061-2025, 2025
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We present the development of the Unified Inputs (of initial and boundary conditions) for WRF (Weather Research and Forecasting)-Chem (UI-WRF-Chem) framework to support the Multi-Angle Imager for Aerosols (MAIA) satellite mission. Major updates include improving dust size distribution in the chemical boundary conditions, updating land surface properties using recent available satellite data and enhancing the representation of soil NOx emissions. We demonstrate subsequent model improvements over several of the MAIA target areas.
Jeewoo Lee, Jhoon Kim, Seoyoung Lee, Myungje Choi, Jaehwa Lee, Daniel J. Jacob, Su Keun Kuk, and Young-Je Park
Earth Syst. Sci. Data, 17, 5761–5782, https://doi.org/10.5194/essd-17-5761-2025, https://doi.org/10.5194/essd-17-5761-2025, 2025
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Atmospheric aerosols adversely affect human health, with East Asia recognized as one of the most impacted regions. This study presents a long-term (2011–2021), high spatiotemporal resolution aerosol optical depth dataset retrieved from a geostationary satellite over East Asia. The high-resolution data capture subtle aerosol gradients and land-ocean boundaries, providing valuable input for various fields such as aerosol-cloud interaction, climate change, ocean optics, and air quality studies.
Janek Gödeke, Andreas Richter, Kezia Lange, Peter Maaß, Hyunkee Hong, Hanlim Lee, and Junsung Park
Atmos. Meas. Tech., 18, 3747–3779, https://doi.org/10.5194/amt-18-3747-2025, https://doi.org/10.5194/amt-18-3747-2025, 2025
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The Korean Geostationary Environmental Monitoring Spectrometer (GEMS) monitors trace gases over Asia, e.g., NO2. GEMS provides hourly data, improving the time resolution compared to the daily overpasses by other satellites. For the prediction of hourly surface NO2 over South Korea from GEMS observations and meteorological data, this study shows that machine learning models benefit from this higher time resolution. This is achieved by using observations from previous hours as additional inputs.
Prajjwal Rawat, James H. Crawford, Katherine R. Travis, Laura M. Judd, Mary Angelique G. Demetillo, Lukas C. Valin, James J. Szykman, Andrew Whitehill, Eric Baumann, and Thomas F. Hanisco
Atmos. Meas. Tech., 18, 2899–2917, https://doi.org/10.5194/amt-18-2899-2025, https://doi.org/10.5194/amt-18-2899-2025, 2025
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The Pandonia Global Network (PGN) consists of Pandora spectrometers that observe trace gases at a high time resolution to validate satellite observations and understand local air quality. To aid users, PGN assigns quality flags that assure scientifically valid data but eliminate large amounts of data appropriate for scientific applications. A new method based on contemporaneous data in two independent observation modes is proven using complementary ground-based and airborne observations.
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
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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.
Zhenyu Zhang, Jing Li, Huizheng Che, Yueming Dong, Oleg Dubovik, Thomas Eck, Pawan Gupta, Brent Holben, Jhoon Kim, Elena Lind, Trailokya Saud, Sachchida Nand Tripathi, and Tong Ying
Atmos. Chem. Phys., 25, 4617–4637, https://doi.org/10.5194/acp-25-4617-2025, https://doi.org/10.5194/acp-25-4617-2025, 2025
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We used ground-based remote sensing data from the Aerosol Robotic Network to examine long-term trends in aerosol characteristics. We found aerosol loadings generally decreased globally, and aerosols became more scattering. These changes are closely related to variations in aerosol compositions, such as decreased anthropogenic emissions over East Asia, Europe, and North America; increased anthropogenic sources over northern India; and increased dust activity over the Arabian Peninsula.
Yujin J. Oak, Daniel J. Jacob, Drew C. Pendergrass, Ruijun Dang, Nadia K. Colombi, Heesung Chong, Seoyoung Lee, Su Keun Kuk, and Jhoon Kim
Atmos. Chem. Phys., 25, 3233–3252, https://doi.org/10.5194/acp-25-3233-2025, https://doi.org/10.5194/acp-25-3233-2025, 2025
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We analyze 2015–2023 air quality trends in South Korea using surface and satellite observations. Primary pollutants have decreased, consistent with emissions reductions. Surface O3 continues to increase and PM2.5 has decreased overall, but the nitrate component has not. O3 and PM2.5 nitrate depend on nonlinear responses from precursor emissions. Satellite data indicate a recent shift to NOx-sensitive O3 and nitrate formation, where further NOx reductions will benefit both O3 and PM2.5 pollution.
Chengxin Zhang, Xinhan Niu, Hongyu Wu, Zhipeng Ding, Ka Lok Chan, Jhoon Kim, Thomas Wagner, and Cheng Liu
Atmos. Chem. Phys., 25, 759–770, https://doi.org/10.5194/acp-25-759-2025, https://doi.org/10.5194/acp-25-759-2025, 2025
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This research utilizes hourly air pollution observations from the world’s first geostationary satellite to develop a spatiotemporal neural network model for full-coverage surface NO2 pollution prediction over the next 24 hours, achieving outstanding forecasting performance and efficacy. These results highlight the profound impact of geostationary satellite observations in advancing air quality forecasting models, thereby contributing to future models for health exposure to air pollution.
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
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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.
Seunghwan Seo, Si-Wan Kim, Kyoung-Min Kim, Andreas Richter, Kezia Lange, John P. Burrows, Junsung Park, Hyunkee Hong, Hanlim Lee, Ukkyo Jeong, Jung-Hun Woo, and Jhoon Kim
Atmos. Meas. Tech., 18, 115–128, https://doi.org/10.5194/amt-18-115-2025, https://doi.org/10.5194/amt-18-115-2025, 2025
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Over the Seoul metropolitan area, tropospheric NO2 vertical column densities from the Geostationary Environment Monitoring Spectrometer show distinct seasonal features. Also, varying a priori data have substantial impacts on the observed NO2 columns. The a priori data from different chemical transport models resulted in differences of up to −18.3 %. Notably, diurnal patterns of observed NO2 columns are similar for all datasets, although their a priori data exhibit contrasting diurnal patterns.
Jin Liao, Glenn M. Wolfe, Alexander E. Kotsakis, Julie M. Nicely, Jason M. St. Clair, Thomas F. Hanisco, Gonzalo González Abad, Caroline R. Nowlan, Zolal Ayazpour, Isabelle De Smedt, Eric C. Apel, and Rebecca S. Hornbrook
Atmos. Meas. Tech., 18, 1–16, https://doi.org/10.5194/amt-18-1-2025, https://doi.org/10.5194/amt-18-1-2025, 2025
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Validation of satellite HCHO over the remote marine regions is relatively low, and modeled HCHO in these regions is usually added as a global satellite HCHO background. This paper intercompares three satellite HCHO retrievals and validates them against in situ observations from the NASA ATom mission. All retrievals are correlated with ATom-integrated columns over remote oceans, with OMI SAO (v004) showing the best agreement. A persistent low bias is found in all retrievals at high latitudes.
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
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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.
T. Nash Skipper, Emma L. D'Ambro, Forwood C. Wiser, V. Faye McNeill, Rebecca H. Schwantes, Barron H. Henderson, Ivan R. Piletic, Colleen B. Baublitz, Jesse O. Bash, Andrew R. Whitehill, Lukas C. Valin, Asher P. Mouat, Jennifer Kaiser, Glenn M. Wolfe, Jason M. St. Clair, Thomas F. Hanisco, Alan Fried, Bryan K. Place, and Havala O.T. Pye
Atmos. Chem. Phys., 24, 12903–12924, https://doi.org/10.5194/acp-24-12903-2024, https://doi.org/10.5194/acp-24-12903-2024, 2024
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We develop the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM) version 2 to improve predictions of formaldehyde in ambient air compared to satellite-, aircraft-, and ground-based observations. With the updated chemistry, we estimate the cancer risk from inhalation exposure to ambient formaldehyde across the contiguous USA and predict that 40 % of this risk is controllable through reductions in anthropogenic emissions of nitrogen oxides and reactive organic carbon.
Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, Gitaek T. Lee, Sieun D. Lee, Seunga Shin, Dong-Won Lee, Hyunkee Hong, Christophe Lerot, Isabelle De Smedt, Thomas Danckaert, Francois Hendrick, and Hitoshi Irie
Atmos. Meas. Tech., 17, 6369–6384, https://doi.org/10.5194/amt-17-6369-2024, https://doi.org/10.5194/amt-17-6369-2024, 2024
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In this study, we evaluated the GEMS glyoxal products by comparing them with TROPOMI and MAX-DOAS measurements. GEMS and TROPOMI VCDs present similar spatial distributions. Monthly variations in GEMS VCDs and TROPOMI and MAX-DOAS VCDs differ in northeastern Asia, which we attributed to a polluted reference spectrum and high NO2 concentrations. GEMS glyoxal products with unparalleled temporal resolution would enrich our understanding of VOC emissions and diurnal variation.
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
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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.
Sora Seo, Pieter Valks, Ronny Lutz, Klaus-Peter Heue, Pascal Hedelt, Víctor Molina García, Diego Loyola, Hanlim Lee, and Jhoon Kim
Atmos. Meas. Tech., 17, 6163–6191, https://doi.org/10.5194/amt-17-6163-2024, https://doi.org/10.5194/amt-17-6163-2024, 2024
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In this study, we developed an advanced retrieval algorithm for tropospheric NO2 columns from geostationary satellite spectrometers and applied it to GEMS measurements. The DLR GEMS NO2 retrieval algorithm follows the heritage from previous and existing algorithms, but improved approaches are applied to reflect the specific features of geostationary satellites. The DLR GEMS NO2 retrievals demonstrate a good capability for monitoring diurnal variability with a high spatial resolution.
Steven A. Bailey, Reem A. Hannun, Andrew K. Swanson, and Thomas F. Hanisco
Atmos. Meas. Tech., 17, 5903–5910, https://doi.org/10.5194/amt-17-5903-2024, https://doi.org/10.5194/amt-17-5903-2024, 2024
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We have developed a portable, optically based instrument that measures NO2. It consumes less than 6 W of power, so it can easily run off a small battery. This instrument has made both balloon and UAV flights. NO2 measurement results compare favorably with other known NO2 instruments. We find this instrument to be stable with repeatable results compared with calibration sources. Material cost to build a single instrument is around USD 4000. This could be lowered with economies of scale.
Suyoung Sim, Sungwon Choi, Daeseong Jung, Jongho Woo, Nayeon Kim, Sungwoo Park, Honghee Kim, Ukkyo Jeong, Hyunkee Hong, and Kyung-Soo Han
Atmos. Meas. Tech., 17, 5601–5618, https://doi.org/10.5194/amt-17-5601-2024, https://doi.org/10.5194/amt-17-5601-2024, 2024
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This study evaluates the use of background surface reflectance (BSR) derived from a semi-empirical bidirectional reflectance distribution function (BRDF) model based on GEMS satellite images. Analysis shows that BSR provides improved accuracy and stability compared to Lambertian-equivalent reflectivity (LER). These results indicate that BSR can significantly enhance climate analysis and air quality monitoring, making it a promising tool for accurate environmental satellite applications.
Myungje Choi, Alexei Lyapustin, Gregory L. Schuster, Sujung Go, Yujie Wang, Sergey Korkin, Ralph Kahn, Jeffrey S. Reid, Edward J. Hyer, Thomas F. Eck, Mian Chin, David J. Diner, Olga Kalashnikova, Oleg Dubovik, Jhoon Kim, and Hans Moosmüller
Atmos. Chem. Phys., 24, 10543–10565, https://doi.org/10.5194/acp-24-10543-2024, https://doi.org/10.5194/acp-24-10543-2024, 2024
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This paper introduces a retrieval algorithm to estimate two key absorbing components in smoke (black carbon and brown carbon) using DSCOVR EPIC measurements. Our analysis reveals distinct smoke properties, including spectral absorption, layer height, and black carbon and brown carbon, over North America and central Africa. The retrieved smoke properties offer valuable observational constraints for modeling radiative forcing and informing health-related studies.
Sooyon Kim, Yeseul Cho, Hanjeong Ki, Seyoung Park, Dagun Oh, Seungjun Lee, Yeonghye Cho, Jhoon Kim, Wonjin Lee, Jaewoo Park, Ick Hoon Jin, and Sangwook Kang
Atmos. Meas. Tech., 17, 5221–5241, https://doi.org/10.5194/amt-17-5221-2024, https://doi.org/10.5194/amt-17-5221-2024, 2024
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This paper describes new work that improves the processing of GEMS AOD data. First, we enhance the inverse-distance-weighting algorithm by incorporating quality flag information, assigning weights that are inversely proportional to the number of unreliable grids. Second, we leverage a spatiotemporal merging method to address both spatial and temporal variability. Finally, we estimate the mean field values for GEMS AOD data, enhancing our understanding of the impact of aerosols on climate change.
Yujin J. Oak, Daniel J. Jacob, Nicholas Balasus, Laura H. Yang, Heesung Chong, Junsung Park, Hanlim Lee, Gitaek T. Lee, Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, and Jhoon Kim
Atmos. Meas. Tech., 17, 5147–5159, https://doi.org/10.5194/amt-17-5147-2024, https://doi.org/10.5194/amt-17-5147-2024, 2024
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We present an improved NO2 product from GEMS by calibrating it to TROPOMI using machine learning and by reprocessing both satellite products to adopt common NO2 profiles. Our corrected GEMS product combines the high data density of GEMS with the accuracy of TROPOMI, supporting the combined use for analyses of East Asia air quality including emissions and chemistry. This method can be extended to other species and geostationary satellites including TEMPO and Sentinel-4.
Naveed Ahmad, Changqing Lin, Alexis K. H. Lau, Jhoon Kim, Tianshu Zhang, Fangqun Yu, Chengcai Li, Ying Li, Jimmy C. H. Fung, and Xiang Qian Lao
Atmos. Chem. Phys., 24, 9645–9665, https://doi.org/10.5194/acp-24-9645-2024, https://doi.org/10.5194/acp-24-9645-2024, 2024
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This study developed a nested machine learning model to convert the GEMS NO2 column measurements into ground-level concentrations across China. The model directly incorporates the NO2 mixing height (NMH) into the methodological framework. The study underscores the importance of considering NMH when estimating ground-level NO2 from satellite column measurements and highlights the significant advantages of new-generation geostationary satellites in air quality monitoring.
David P. Edwards, Sara Martínez-Alonso, Duseong S. Jo, Ivan Ortega, Louisa K. Emmons, John J. Orlando, Helen M. Worden, Jhoon Kim, Hanlim Lee, Junsung Park, and Hyunkee Hong
Atmos. Chem. Phys., 24, 8943–8961, https://doi.org/10.5194/acp-24-8943-2024, https://doi.org/10.5194/acp-24-8943-2024, 2024
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Until recently, satellite observations of atmospheric pollutants at any location could only be obtained once a day. New geostationary satellites stare at a region of the Earth to make hourly measurements, and the Geostationary Environment Monitoring Spectrometer is the first looking at Asia. These data and model simulations show how the change seen for one important pollutant that determines air quality depends on a combination of pollution emissions, atmospheric chemistry, and meteorology.
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
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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.
Minseok Kim, Jhoon Kim, Hyunkwang Lim, Seoyoung Lee, Yeseul Cho, Yun-Gon Lee, Sujung Go, and Kyunghwa Lee
Atmos. Meas. Tech., 17, 4317–4335, https://doi.org/10.5194/amt-17-4317-2024, https://doi.org/10.5194/amt-17-4317-2024, 2024
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Information about aerosol loading in the atmosphere can be collected from various satellite instruments. Aerosol products from various satellite instruments have their own error characteristics. This study statistically merged aerosol optical depth datasets from multiple instruments aboard geostationary satellites considering uncertainties. Also, a deep neural network technique is adopted for aerosol data merging.
Andrea E. Gordon, Cameron R. Homeyer, Jessica B. Smith, Rei Ueyama, Jonathan M. Dean-Day, Elliot L. Atlas, Kate Smith, Jasna V. Pittman, David S. Sayres, David M. Wilmouth, Apoorva Pandey, Jason M. St. Clair, Thomas F. Hanisco, Jennifer Hare, Reem A. Hannun, Steven Wofsy, Bruce C. Daube, and Stephen Donnelly
Atmos. Chem. Phys., 24, 7591–7608, https://doi.org/10.5194/acp-24-7591-2024, https://doi.org/10.5194/acp-24-7591-2024, 2024
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In situ airborne observations of ongoing tropopause-overshooting convection and an above-anvil cirrus plume from the 31 May 2022 flight of the Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) field campaign are examined. Upper troposphere and lower stratosphere composition changes are evaluated along with possible contributing dynamical and physical processes. Measurements reveal multiple changes in air mass composition and stratospheric hydration throughout the flight.
Laura Hyesung Yang, Daniel J. Jacob, Ruijun Dang, Yujin J. Oak, Haipeng Lin, Jhoon Kim, Shixian Zhai, Nadia K. Colombi, Drew C. Pendergrass, Ellie Beaudry, Viral Shah, Xu Feng, Robert M. Yantosca, Heesung Chong, Junsung Park, Hanlim Lee, Won-Jin Lee, Soontae Kim, Eunhye Kim, Katherine R. Travis, James H. Crawford, and Hong Liao
Atmos. Chem. Phys., 24, 7027–7039, https://doi.org/10.5194/acp-24-7027-2024, https://doi.org/10.5194/acp-24-7027-2024, 2024
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The Geostationary Environment Monitoring Spectrometer (GEMS) provides hourly measurements of NO2. We use the chemical transport model to find how emissions, chemistry, and transport drive the changes in NO2 observed by GEMS at different times of the day. In winter, the chemistry plays a minor role, and high daytime emissions dominate the diurnal variation in NO2, balanced by transport. In summer, emissions, chemistry, and transport play an important role in shaping the diurnal variation in NO2.
Drew C. Pendergrass, Daniel J. Jacob, Yujin J. Oak, Jeewoo Lee, Minseok Kim, Jhoon Kim, Seoyoung Lee, Shixian Zhai, Hitoshi Irie, and Hong Liao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-172, https://doi.org/10.5194/essd-2024-172, 2024
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Fine particles suspended in the atmosphere are a major form of air pollution and an important public health burden. However, measurements of particulate matter are sparse in space and in places like East Asia monitors are established after regulatory policies to improve pollution have changed. In this paper, we use machine learning to fill in the gaps. We train an algorithm to predict pollution at the surface from the atmosphere’s opacity, then produce high resolution maps of data without gaps.
Heesung Chong, Gonzalo González Abad, Caroline R. Nowlan, Christopher Chan Miller, Alfonso Saiz-Lopez, Rafael P. Fernandez, Hyeong-Ahn Kwon, Zolal Ayazpour, Huiqun Wang, Amir H. Souri, Xiong Liu, Kelly Chance, Ewan O'Sullivan, Jhoon Kim, Ja-Ho Koo, William R. Simpson, François Hendrick, Richard Querel, Glen Jaross, Colin Seftor, and Raid M. Suleiman
Atmos. Meas. Tech., 17, 2873–2916, https://doi.org/10.5194/amt-17-2873-2024, https://doi.org/10.5194/amt-17-2873-2024, 2024
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We present a new bromine monoxide (BrO) product derived using radiances measured from OMPS-NM on board the Suomi-NPP satellite. This product provides nearly a decade of global stratospheric and tropospheric column retrievals, a feature that is currently rare in publicly accessible datasets. Both stratospheric and tropospheric columns from OMPS-NM demonstrate robust performance, exhibiting good agreement with ground-based observations collected at three stations (Lauder, Utqiagvik, and Harestua).
Gitaek T. Lee, Rokjin J. Park, Hyeong-Ahn Kwon, Eunjo S. Ha, Sieun D. Lee, Seunga Shin, Myoung-Hwan Ahn, Mina Kang, Yong-Sang Choi, Gyuyeon Kim, Dong-Won Lee, Deok-Rae Kim, Hyunkee Hong, Bavo Langerock, Corinne Vigouroux, Christophe Lerot, Francois Hendrick, Gaia Pinardi, Isabelle De Smedt, Michel Van Roozendael, Pucai Wang, Heesung Chong, Yeseul Cho, and Jhoon Kim
Atmos. Chem. Phys., 24, 4733–4749, https://doi.org/10.5194/acp-24-4733-2024, https://doi.org/10.5194/acp-24-4733-2024, 2024
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This study evaluates the Geostationary Environment Monitoring Spectrometer (GEMS) HCHO product by comparing its vertical column densities (VCDs) with those of TROPOMI and ground-based observations. Based on some sensitivity tests, obtaining radiance references under clear-sky conditions significantly improves HCHO retrieval quality. GEMS HCHO VCDs captured seasonal and diurnal variations well during the first year of observation, showing consistency with TROPOMI and ground-based observations.
Bo-Ram Kim, Gyuyeon Kim, Minjeong Cho, Yong-Sang Choi, and Jhoon Kim
Atmos. Meas. Tech., 17, 453–470, https://doi.org/10.5194/amt-17-453-2024, https://doi.org/10.5194/amt-17-453-2024, 2024
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This study introduces the GEMS cloud algorithm and validates its results using data from GEMS and other environmental satellites. The GEMS algorithm is able to detect the lowest cloud heights among the four satellites, and its effective cloud fraction and cloud centroid pressure are well reflected in the retrieval results. The study highlights the algorithm's usefulness in correcting errors in trace gases caused by clouds in the East Asian region.
Georgios I. Gkatzelis, Matthew M. Coggon, Chelsea E. Stockwell, Rebecca S. Hornbrook, Hannah Allen, Eric C. Apel, Megan M. Bela, Donald R. Blake, Ilann Bourgeois, Steven S. Brown, Pedro Campuzano-Jost, Jason M. St. Clair, James H. Crawford, John D. Crounse, Douglas A. Day, Joshua P. DiGangi, Glenn S. Diskin, Alan Fried, Jessica B. Gilman, Hongyu Guo, Johnathan W. Hair, Hannah S. Halliday, Thomas F. Hanisco, Reem Hannun, Alan Hills, L. Gregory Huey, Jose L. Jimenez, Joseph M. Katich, Aaron Lamplugh, Young Ro Lee, Jin Liao, Jakob Lindaas, Stuart A. McKeen, Tomas Mikoviny, Benjamin A. Nault, J. Andrew Neuman, John B. Nowak, Demetrios Pagonis, Jeff Peischl, Anne E. Perring, Felix Piel, Pamela S. Rickly, Michael A. Robinson, Andrew W. Rollins, Thomas B. Ryerson, Melinda K. Schueneman, Rebecca H. Schwantes, Joshua P. Schwarz, Kanako Sekimoto, Vanessa Selimovic, Taylor Shingler, David J. Tanner, Laura Tomsche, Krystal T. Vasquez, Patrick R. Veres, Rebecca Washenfelder, Petter Weibring, Paul O. Wennberg, Armin Wisthaler, Glenn M. Wolfe, Caroline C. Womack, Lu Xu, Katherine Ball, Robert J. Yokelson, and Carsten Warneke
Atmos. Chem. Phys., 24, 929–956, https://doi.org/10.5194/acp-24-929-2024, https://doi.org/10.5194/acp-24-929-2024, 2024
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This study reports emissions of gases and particles from wildfires. These emissions are related to chemical proxies that can be measured by satellite and incorporated into models to improve predictions of wildfire impacts on air quality and climate.
Jong-Uk Park, Hyun-Jae Kim, Jin-Soo Park, Jinsoo Choi, Sang Seo Park, Kangho Bae, Jong-Jae Lee, Chang-Keun Song, Soojin Park, Kyuseok Shim, Yeonsoo Cho, and Sang-Woo Kim
Atmos. Meas. Tech., 17, 197–217, https://doi.org/10.5194/amt-17-197-2024, https://doi.org/10.5194/amt-17-197-2024, 2024
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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.
Haklim Choi, Xiong Liu, Ukkyo Jeong, Heesung Chong, Jhoon Kim, Myung Hwan Ahn, Dai Ho Ko, Dong-Won Lee, Kyung-Jung Moon, and Kwang-Mog Lee
Atmos. Meas. Tech., 17, 145–164, https://doi.org/10.5194/amt-17-145-2024, https://doi.org/10.5194/amt-17-145-2024, 2024
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GEMS is the first geostationary satellite to measure the UV--Vis region, and this paper reports the polarization characteristics of GEMS and an algorithm. We develop a polarization correction algorithm optimized for GEMS based on a look-up-table approach that simultaneously considers the polarization of incoming light and polarization sensitivity characteristics of the instrument. Pre-launch polarization error was adjusted close to zero across the spectral range after polarization correction.
Kanghyun Baek, Jae Hwan Kim, Juseon Bak, David P. Haffner, Mina Kang, and Hyunkee Hong
Atmos. Meas. Tech., 16, 5461–5478, https://doi.org/10.5194/amt-16-5461-2023, https://doi.org/10.5194/amt-16-5461-2023, 2023
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The GEMS mission was the first mission of the geostationary satellite constellation for hourly atmospheric composition monitoring. The GEMS ozone measurements were cross-compared to those of Pandora, OMPS, and TROPOMI satellite sensors and excellent agreement was found. GEMS has proven to be a powerful new instrument for monitoring and assessing the diurnal variation in atmospheric ozone. This experience can be used to advance research with future geostationary environmental satellite missions.
Yuhang Zhang, Jintai Lin, Jhoon Kim, Hanlim Lee, Junsung Park, Hyunkee Hong, Michel Van Roozendael, Francois Hendrick, Ting Wang, Pucai Wang, Qin He, Kai Qin, Yongjoo Choi, Yugo Kanaya, Jin Xu, Pinhua Xie, Xin Tian, Sanbao Zhang, Shanshan Wang, Siyang Cheng, Xinghong Cheng, Jianzhong Ma, Thomas Wagner, Robert Spurr, Lulu Chen, Hao Kong, and Mengyao Liu
Atmos. Meas. Tech., 16, 4643–4665, https://doi.org/10.5194/amt-16-4643-2023, https://doi.org/10.5194/amt-16-4643-2023, 2023
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Our tropospheric NO2 vertical column density product with high spatiotemporal resolution is based on the Geostationary Environment Monitoring Spectrometer (GEMS) and named POMINO–GEMS. Strong hotspot signals and NO2 diurnal variations are clearly seen. Validations with multiple satellite products and ground-based, mobile car and surface measurements exhibit the overall great performance of the POMINO–GEMS product, indicating its capability for application in environmental studies.
Jincheol Park, Jia Jung, Yunsoo Choi, Hyunkwang Lim, Minseok Kim, Kyunghwa Lee, Yun Gon Lee, and Jhoon Kim
Atmos. Meas. Tech., 16, 3039–3057, https://doi.org/10.5194/amt-16-3039-2023, https://doi.org/10.5194/amt-16-3039-2023, 2023
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In response to the recent release of new geostationary platform-derived observational data generated by the Geostationary Environment Monitoring Spectrometer (GEMS) and its sister instruments, this study utilized the GEMS data fusion product and its proxy data in adjusting aerosol precursor emissions over East Asia. The use of spatiotemporally more complete observation references in updating the emissions resulted in more promising model performances in estimating aerosol loadings in East Asia.
Emma L. Yates, Laura T. Iraci, Susan S. Kulawik, Ju-Mee Ryoo, Josette E. Marrero, Caroline L. Parworth, Jason M. St. Clair, Thomas F. Hanisco, Thao Paul V. Bui, Cecilia S. Chang, and Jonathan M. Dean-Day
Earth Syst. Sci. Data, 15, 2375–2389, https://doi.org/10.5194/essd-15-2375-2023, https://doi.org/10.5194/essd-15-2375-2023, 2023
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The Alpha Jet Atmospheric eXperiment (AJAX) flew scientific flights between 2011 and 2018 providing measurements of carbon dioxide, methane, ozone, formaldehyde, water vapor and meteorological parameters over California and Nevada, USA. AJAX was a multi-year, multi-objective, multi-instrument program with a variety of sampling strategies resulting in an extensive dataset of interest to a wide variety of users. AJAX measurements have been published at https://asdc.larc.nasa.gov/project/AJAX.
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
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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.
Laura Hyesung Yang, Daniel J. Jacob, Nadia K. Colombi, Shixian Zhai, Kelvin H. Bates, Viral Shah, Ellie Beaudry, Robert M. Yantosca, Haipeng Lin, Jared F. Brewer, Heesung Chong, Katherine R. Travis, James H. Crawford, Lok N. Lamsal, Ja-Ho Koo, and Jhoon Kim
Atmos. Chem. Phys., 23, 2465–2481, https://doi.org/10.5194/acp-23-2465-2023, https://doi.org/10.5194/acp-23-2465-2023, 2023
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A geostationary satellite can now provide hourly NO2 vertical columns, and obtaining the NO2 vertical columns from space relies on NO2 vertical distribution from the chemical transport model (CTM). In this work, we update the CTM to better represent the chemistry environment so that the CTM can accurately provide NO2 vertical distribution. We also find that the changes in NO2 vertical distribution driven by a change in mixing depth play an important role in the NO2 column's diurnal variation.
Gyo-Hwang Choo, Kyunghwa Lee, Hyunkee Hong, Ukkyo Jeong, Wonei Choi, and Scott J. Janz
Atmos. Meas. Tech., 16, 625–644, https://doi.org/10.5194/amt-16-625-2023, https://doi.org/10.5194/amt-16-625-2023, 2023
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This study discusses the morning and afternoon distribution of NO2 emissions in large cities and industrial areas in South Korea, one of the largest NO2 emitters around the world, using GeoTASO, an airborne remote sensing instrument developed to support geostationary satellite missions. NO2 measurements from GeoTASO were compared with those from ground-based remote sensing instruments including Pandora and in situ sensors.
Hao Guo, Clare M. Flynn, Michael J. Prather, Sarah A. Strode, Stephen D. Steenrod, Louisa Emmons, Forrest Lacey, Jean-Francois Lamarque, Arlene M. Fiore, Gus Correa, Lee T. Murray, Glenn M. Wolfe, Jason M. St. Clair, Michelle Kim, John Crounse, Glenn Diskin, Joshua DiGangi, Bruce C. Daube, Roisin Commane, Kathryn McKain, Jeff Peischl, Thomas B. Ryerson, Chelsea Thompson, Thomas F. Hanisco, Donald Blake, Nicola J. Blake, Eric C. Apel, Rebecca S. Hornbrook, James W. Elkins, Eric J. Hintsa, Fred L. Moore, and Steven C. Wofsy
Atmos. Chem. Phys., 23, 99–117, https://doi.org/10.5194/acp-23-99-2023, https://doi.org/10.5194/acp-23-99-2023, 2023
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We have prepared a unique and unusual result from the recent ATom aircraft mission: a measurement-based derivation of the production and loss rates of ozone and methane over the ocean basins. These are the key products of chemistry models used in assessments but have thus far lacked observational metrics. It also shows the scales of variability of atmospheric chemical rates and provides a major challenge to the atmospheric models.
Pamela S. Rickly, Hongyu Guo, Pedro Campuzano-Jost, Jose L. Jimenez, Glenn M. Wolfe, Ryan Bennett, Ilann Bourgeois, John D. Crounse, Jack E. Dibb, Joshua P. DiGangi, Glenn S. Diskin, Maximilian Dollner, Emily M. Gargulinski, Samuel R. Hall, Hannah S. Halliday, Thomas F. Hanisco, Reem A. Hannun, Jin Liao, Richard Moore, Benjamin A. Nault, John B. Nowak, Jeff Peischl, Claire E. Robinson, Thomas Ryerson, Kevin J. Sanchez, Manuel Schöberl, Amber J. Soja, Jason M. St. Clair, Kenneth L. Thornhill, Kirk Ullmann, Paul O. Wennberg, Bernadett Weinzierl, Elizabeth B. Wiggins, Edward L. Winstead, and Andrew W. Rollins
Atmos. Chem. Phys., 22, 15603–15620, https://doi.org/10.5194/acp-22-15603-2022, https://doi.org/10.5194/acp-22-15603-2022, 2022
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Biomass burning sulfur dioxide (SO2) emission factors range from 0.27–1.1 g kg-1 C. Biomass burning SO2 can quickly form sulfate and organosulfur, but these pathways are dependent on liquid water content and pH. Hydroxymethanesulfonate (HMS) appears to be directly emitted from some fire sources but is not the sole contributor to the organosulfur signal. It is shown that HMS and organosulfur chemistry may be an important S(IV) reservoir with the fate dependent on the surrounding conditions.
Ukkyo Jeong, Si-Chee Tsay, N. Christina Hsu, David M. Giles, John W. Cooper, Jaehwa Lee, Robert J. Swap, Brent N. Holben, James J. Butler, Sheng-Hsiang Wang, Somporn Chantara, Hyunkee Hong, Donghee Kim, and Jhoon Kim
Atmos. Chem. Phys., 22, 11957–11986, https://doi.org/10.5194/acp-22-11957-2022, https://doi.org/10.5194/acp-22-11957-2022, 2022
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Ultraviolet (UV) measurements from satellite and ground are important for deriving information on several atmospheric trace and aerosol characteristics. Simultaneous retrievals of aerosol and trace gases in this study suggest that water uptake by aerosols is one of the important phenomena affecting aerosol properties over northern Thailand, which is important for regional air quality and climate. Obtained aerosol properties covering the UV are also important for various satellite algorithms.
Samuel E. LeBlanc, Michal Segal-Rozenhaimer, Jens Redemann, Connor Flynn, Roy R. Johnson, Stephen E. Dunagan, Robert Dahlgren, Jhoon Kim, Myungje Choi, Arlindo da Silva, Patricia Castellanos, Qian Tan, Luke Ziemba, Kenneth Lee Thornhill, and Meloë Kacenelenbogen
Atmos. Chem. Phys., 22, 11275–11304, https://doi.org/10.5194/acp-22-11275-2022, https://doi.org/10.5194/acp-22-11275-2022, 2022
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Airborne observations of atmospheric particles and pollution over Korea during a field campaign in May–June 2016 showed that the smallest atmospheric particles are present in the lowest 2 km of the atmosphere. The aerosol size is more spatially variable than optical thickness. We show this with remote sensing (4STAR), in situ (LARGE) observations, satellite measurements (GOCI), and modeled properties (MERRA-2), and it is contrary to the current understanding.
Ilann Bourgeois, Jeff Peischl, J. Andrew Neuman, Steven S. Brown, Hannah M. Allen, Pedro Campuzano-Jost, Matthew M. Coggon, Joshua P. DiGangi, Glenn S. Diskin, Jessica B. Gilman, Georgios I. Gkatzelis, Hongyu Guo, Hannah A. Halliday, Thomas F. Hanisco, Christopher D. Holmes, L. Gregory Huey, Jose L. Jimenez, Aaron D. Lamplugh, Young Ro Lee, Jakob Lindaas, Richard H. Moore, Benjamin A. Nault, John B. Nowak, Demetrios Pagonis, Pamela S. Rickly, Michael A. Robinson, Andrew W. Rollins, Vanessa Selimovic, Jason M. St. Clair, David Tanner, Krystal T. Vasquez, Patrick R. Veres, Carsten Warneke, Paul O. Wennberg, Rebecca A. Washenfelder, Elizabeth B. Wiggins, Caroline C. Womack, Lu Xu, Kyle J. Zarzana, and Thomas B. Ryerson
Atmos. Meas. Tech., 15, 4901–4930, https://doi.org/10.5194/amt-15-4901-2022, https://doi.org/10.5194/amt-15-4901-2022, 2022
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Understanding fire emission impacts on the atmosphere is key to effective air quality management and requires accurate measurements. We present a comparison of airborne measurements of key atmospheric species in ambient air and in fire smoke. We show that most instruments performed within instrument uncertainties. In some cases, further work is needed to fully characterize instrument performance. Comparing independent measurements using different techniques is important to assess their accuracy.
Lim-Seok Chang, Donghee Kim, Hyunkee Hong, Deok-Rae Kim, Jeong-Ah Yu, Kwangyul Lee, Hanlim Lee, Daewon Kim, Jinkyu Hong, Hyun-Young Jo, and Cheol-Hee Kim
Atmos. Chem. Phys., 22, 10703–10720, https://doi.org/10.5194/acp-22-10703-2022, https://doi.org/10.5194/acp-22-10703-2022, 2022
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Our study explored the synergy of combined column and surface measurements during GMAP (GEMS Map of Air Pollution) campaign. It has several points to note for vertical distribution analysis. Particularly under prevailing local wind meteorological conditions, Pandora-based vertical structures sometimes showed negative correlations between column and surface measurements. Vertical analysis should be done carefully in some local meteorological conditions when employing either surface or columns.
Katherine R. Travis, James H. Crawford, Gao Chen, Carolyn E. Jordan, Benjamin A. Nault, Hwajin Kim, Jose L. Jimenez, Pedro Campuzano-Jost, Jack E. Dibb, Jung-Hun Woo, Younha Kim, Shixian Zhai, Xuan Wang, Erin E. McDuffie, Gan Luo, Fangqun Yu, Saewung Kim, Isobel J. Simpson, Donald R. Blake, Limseok Chang, and Michelle J. Kim
Atmos. Chem. Phys., 22, 7933–7958, https://doi.org/10.5194/acp-22-7933-2022, https://doi.org/10.5194/acp-22-7933-2022, 2022
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The 2016 Korea–United States Air Quality (KORUS-AQ) field campaign provided a unique set of observations to improve our understanding of PM2.5 pollution in South Korea. Models typically have errors in simulating PM2.5 in this region, which is of concern for the development of control measures. We use KORUS-AQ observations to improve our understanding of the mechanisms driving PM2.5 and the implications of model errors for determining PM2.5 that is attributable to local or foreign sources.
Tianlang Zhao, Jingqiu Mao, William R. Simpson, Isabelle De Smedt, Lei Zhu, Thomas F. Hanisco, Glenn M. Wolfe, Jason M. St. Clair, Gonzalo González Abad, Caroline R. Nowlan, Barbara Barletta, Simone Meinardi, Donald R. Blake, Eric C. Apel, and Rebecca S. Hornbrook
Atmos. Chem. Phys., 22, 7163–7178, https://doi.org/10.5194/acp-22-7163-2022, https://doi.org/10.5194/acp-22-7163-2022, 2022
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Monitoring formaldehyde (HCHO) can help us understand Arctic vegetation change. Here, we compare satellite data and model and show that Alaska summertime HCHO is largely dominated by a background from methane oxidation during mild wildfire years and is dominated by wildfire (largely from direct emission of fire) during strong fire years. Consequently, it is challenging to use satellite HCHO to study vegetation change in the Arctic region.
Glenn M. Wolfe, Thomas F. Hanisco, Heather L. Arkinson, Donald R. Blake, Armin Wisthaler, Tomas Mikoviny, Thomas B. Ryerson, Ilana Pollack, Jeff Peischl, Paul O. Wennberg, John D. Crounse, Jason M. St. Clair, Alex Teng, L. Gregory Huey, Xiaoxi Liu, Alan Fried, Petter Weibring, Dirk Richter, James Walega, Samuel R. Hall, Kirk Ullmann, Jose L. Jimenez, Pedro Campuzano-Jost, T. Paul Bui, Glenn Diskin, James R. Podolske, Glen Sachse, and Ronald C. Cohen
Atmos. Chem. Phys., 22, 4253–4275, https://doi.org/10.5194/acp-22-4253-2022, https://doi.org/10.5194/acp-22-4253-2022, 2022
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Smoke plumes are chemically complex. This work combines airborne observations of smoke plume composition with a photochemical model to probe the production of ozone and the fate of reactive gases in the outflow of a large wildfire. Model–measurement comparisons illustrate how uncertain emissions and chemical processes propagate into simulated chemical evolution. Results provide insight into how this system responds to perturbations, which can help guide future observation and modeling efforts.
Drew C. Pendergrass, Shixian Zhai, Jhoon Kim, Ja-Ho Koo, Seoyoung Lee, Minah Bae, Soontae Kim, Hong Liao, and Daniel J. Jacob
Atmos. Meas. Tech., 15, 1075–1091, https://doi.org/10.5194/amt-15-1075-2022, https://doi.org/10.5194/amt-15-1075-2022, 2022
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This paper uses a machine learning algorithm to infer high-resolution maps of particulate air quality in eastern China, Japan, and the Korean peninsula, using data from a geostationary satellite along with meteorology. We then perform an extensive evaluation of this inferred air quality and use it to diagnose trends in the region. We hope this paper and the associated data will be valuable to other scientists interested in epidemiology, air quality, remote sensing, and machine learning.
Sujung Go, Alexei Lyapustin, Gregory L. Schuster, Myungje Choi, Paul Ginoux, Mian Chin, Olga Kalashnikova, Oleg Dubovik, Jhoon Kim, Arlindo da Silva, Brent Holben, and Jeffrey S. Reid
Atmos. Chem. Phys., 22, 1395–1423, https://doi.org/10.5194/acp-22-1395-2022, https://doi.org/10.5194/acp-22-1395-2022, 2022
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This paper presents a retrieval algorithm of iron-oxide species (hematite, goethite) content in the atmosphere from DSCOVR EPIC observations. Our results display variations within the published range of hematite and goethite over the main dust-source regions but show significant seasonal and spatial variability. This implies a single-viewing satellite instrument with UV–visible channels may provide essential information on shortwave dust direct radiative effects for climate modeling.
Jin Liao, Glenn M. Wolfe, Reem A. Hannun, Jason M. St. Clair, Thomas F. Hanisco, Jessica B. Gilman, Aaron Lamplugh, Vanessa Selimovic, Glenn S. Diskin, John B. Nowak, Hannah S. Halliday, Joshua P. DiGangi, Samuel R. Hall, Kirk Ullmann, Christopher D. Holmes, Charles H. Fite, Anxhelo Agastra, Thomas B. Ryerson, Jeff Peischl, Ilann Bourgeois, Carsten Warneke, Matthew M. Coggon, Georgios I. Gkatzelis, Kanako Sekimoto, Alan Fried, Dirk Richter, Petter Weibring, Eric C. Apel, Rebecca S. Hornbrook, Steven S. Brown, Caroline C. Womack, Michael A. Robinson, Rebecca A. Washenfelder, Patrick R. Veres, and J. Andrew Neuman
Atmos. Chem. Phys., 21, 18319–18331, https://doi.org/10.5194/acp-21-18319-2021, https://doi.org/10.5194/acp-21-18319-2021, 2021
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Formaldehyde (HCHO) is an important oxidant precursor and affects the formation of O3 and other secondary pollutants in wildfire plumes. We disentangle the processes controlling HCHO evolution from wildfire plumes sampled by NASA DC-8 during FIREX-AQ. We find that OH abundance rather than normalized OH reactivity is the main driver of fire-to-fire variability in HCHO secondary production and estimate an effective HCHO yield per volatile organic compound molecule oxidized in wildfire plumes.
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
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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.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
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Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
Hao Guo, Clare M. Flynn, Michael J. Prather, Sarah A. Strode, Stephen D. Steenrod, Louisa Emmons, Forrest Lacey, Jean-Francois Lamarque, Arlene M. Fiore, Gus Correa, Lee T. Murray, Glenn M. Wolfe, Jason M. St. Clair, Michelle Kim, John Crounse, Glenn Diskin, Joshua DiGangi, Bruce C. Daube, Roisin Commane, Kathryn McKain, Jeff Peischl, Thomas B. Ryerson, Chelsea Thompson, Thomas F. Hanisco, Donald Blake, Nicola J. Blake, Eric C. Apel, Rebecca S. Hornbrook, James W. Elkins, Eric J. Hintsa, Fred L. Moore, and Steven Wofsy
Atmos. Chem. Phys., 21, 13729–13746, https://doi.org/10.5194/acp-21-13729-2021, https://doi.org/10.5194/acp-21-13729-2021, 2021
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The NASA Atmospheric Tomography (ATom) mission built a climatology of the chemical composition of tropospheric air parcels throughout the middle of the Pacific and Atlantic oceans. The level of detail allows us to reconstruct the photochemical budgets of O3 and CH4 over these vast, remote regions. We find that most of the chemical heterogeneity is captured at the resolution used in current global chemistry models and that the majority of reactivity occurs in the
hottest20 % of parcels.
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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.
A first evaluation of the Geostationary Environmental Monitoring Spectrometer (GEMS) NO2 was...
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