Articles | Volume 18, issue 15
https://doi.org/10.5194/amt-18-3747-2025
© Author(s) 2025. 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-18-3747-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Aug 2025
Research article |
| 11 Aug 2025
| 11 Aug 2025
Hourly surface nitrogen dioxide retrieval from GEMS tropospheric vertical column densities: benefit of using time-contiguous input features for machine learning models
Center for Industrial Mathematics, University of Bremen, Bremen, Germany
Andreas Richter
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Kezia Lange
Institute of Environmental Physics, University of Bremen, Bremen, Germany
Peter Maaß
Center for Industrial Mathematics, University of Bremen, Bremen, Germany
Hyunkee Hong
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
Junsung Park
Division of Earth Environmental System Science, Major of Spatial Information Engineering, Pukyong National University, Busan, Republic of Korea
Related authors
No articles found.
Miriam Latsch, Andreas Richter, John P. Burrows, and Hartmut Bösch
Atmos. Meas. Tech., 18, 4373–4395, https://doi.org/10.5194/amt-18-4373-2025, https://doi.org/10.5194/amt-18-4373-2025, 2025
Short summary
Short summary
This study presents our advanced methods to qualitatively detect ship-related nitrogen dioxide (NO2) signals in TROPOMI satellite data. By applying filtering techniques, we identify numerous global shipping routes, including previously undetected ones, as well as emissions from offshore platforms. Additionally, we compare the filtered satellite data with high-pass-filtered CAMS global model data to estimate the differences between observed and modeled NO2 emissions.
Stefanie Falk, Luca Reißig, Bianca Zilker, Andreas Richter, and Björn-Martin Sinnhuber
EGUsphere, https://doi.org/10.5194/egusphere-2025-3181, https://doi.org/10.5194/egusphere-2025-3181, 2025
Short summary
Short summary
We investigate ozone depletion events (ODEs) and bromine explosions in 2019/20. Model results evaluated against surface ozone measurements, satellite-derived tropospheric BrO vertical column densities, and in situ data from the MOSAiC expedition suggest that increased Br2 emissions do not resolve model discrepancies, Br2 emissions from first-year sea ice may not fully account for observed ODE variability, and additional climate-sensitive mechanisms may modulate Arctic ozone chemistry.
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 Beak, Kai Yang, Xiong Liu, Gonzalo Gonzalez Abad, Klaus-Peter Heue, Jean-Christopher Lambert, Yeonjin Jung, Hyunkee Hong, and Won-Jin Lee
EGUsphere, https://doi.org/10.5194/egusphere-2025-2276, https://doi.org/10.5194/egusphere-2025-2276, 2025
Short summary
Short summary
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.
Huanhuan Yan, Andreas Richter, Xingying Zhang, Anja Schönhardt, and Thomas Visarius
EGUsphere, https://doi.org/10.5194/egusphere-2025-2177, https://doi.org/10.5194/egusphere-2025-2177, 2025
Short summary
Short summary
The Ozone Monitoring Suite (OMS) launched in August 2023 is a new Chinese hyperspectral UV-VIS instrument. This study used the OMS measurements and Differential Optical Absorption Spectroscopy (DOAS) inversion to for the first time retrieve global SO2 columns from OMS. The results show that the OMS SO2 retrievals exhibit good stability over clean oceanic regions, successfully capture volcanic SO2 plumes, and effectively detect the elevated SO2 columns from anthropogenic emissions.
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.
Yuhang Zhang, Huan Yu, Isabelle De Smedt, Jintai Lin, Nicolas Theys, Michel Van Roozendael, Gaia Pinardi, Steven Compernolle, Ruijing Ni, Fangxuan Ren, Sijie Wang, Lulu Chen, Jos Van Geffen, Mengyao Liu, Alexander M. Cede, Martin Tiefengraber, Alexis Merlaud, Martina M. Friedrich, Andreas Richter, Ankie Piters, Vinod Kumar, Vinayak Sinha, Thomas Wagner, Yongjoo Choi, Hisahiro Takashima, Yugo Kanaya, Hitoshi Irie, Robert Spurr, Wenfu Sun, and Lorenzo Fabris
Atmos. Meas. Tech., 18, 1561–1589, https://doi.org/10.5194/amt-18-1561-2025, https://doi.org/10.5194/amt-18-1561-2025, 2025
Short summary
Short summary
We developed an advanced algorithm for global retrieval of TROPOspheric Monitoring Instrument (TROPOMI) HCHO and NO2 vertical column densities with much improved consistency. Sensitivity tests demonstrate the complexity and nonlinear interactions of auxiliary parameters in the air mass factor calculation. An improved agreement is found with measurements from a global ground-based instrument network. The scientific retrieval provides a useful source of information for studies combining HCHO and NO2.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Henk Eskes, Athanasios Tsikerdekis, Melanie Ades, Mihai Alexe, Anna Carlin Benedictow, Yasmine Bennouna, Lewis Blake, Idir Bouarar, Simon Chabrillat, Richard Engelen, Quentin Errera, Johannes Flemming, Sebastien Garrigues, Jan Griesfeller, Vincent Huijnen, Luka Ilić, Antje Inness, John Kapsomenakis, Zak Kipling, Bavo Langerock, Augustin Mortier, Mark Parrington, Isabelle Pison, Mikko Pitkänen, Samuel Remy, Andreas Richter, Anja Schoenhardt, Michael Schulz, Valerie Thouret, Thorsten Warneke, Christos Zerefos, and Vincent-Henri Peuch
Atmos. Chem. Phys., 24, 9475–9514, https://doi.org/10.5194/acp-24-9475-2024, https://doi.org/10.5194/acp-24-9475-2024, 2024
Short summary
Short summary
The Copernicus Atmosphere Monitoring Service (CAMS) provides global analyses and forecasts of aerosols and trace gases in the atmosphere. On 27 June 2023 a major upgrade, Cy48R1, became operational. Comparisons with in situ, surface remote sensing, aircraft, and balloon and satellite observations show that the new CAMS system is a significant improvement. The results quantify the skill of CAMS to forecast impactful events, such as wildfires, dust storms and air pollution peaks.
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
Short summary
Short summary
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.
Matías Osorio, Alejandro Agesta, Tim Bösch, Nicolás Casaballe, Andreas Richter, Leonardo M. A. Alvarado, and Erna Frins
Atmos. Chem. Phys., 24, 7447–7465, https://doi.org/10.5194/acp-24-7447-2024, https://doi.org/10.5194/acp-24-7447-2024, 2024
Short summary
Short summary
This study concerns the detection and quantification of long-transport emissions of a biomass burning event, which represents a major source of air pollutants, due to the release of large amounts of aerosols and chemical species into the atmosphere. The quantification was done using ground-based observations (which play an important role in assessing the abundance of trace gases and aerosols) over Montevideo (Uruguay) and using satellite observations.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Blanca Fuentes Andrade, Michael Buchwitz, Maximilian Reuter, Heinrich Bovensmann, Andreas Richter, Hartmut Boesch, and John P. Burrows
Atmos. Meas. Tech., 17, 1145–1173, https://doi.org/10.5194/amt-17-1145-2024, https://doi.org/10.5194/amt-17-1145-2024, 2024
Short summary
Short summary
We developed a method to estimate CO2 emissions from localized sources, such as power plants, using satellite data and applied it to estimate CO2 emissions from the Bełchatów Power Station (Poland). As the detection of CO2 emission plumes from satellite data is difficult, we used observations of co-emitted NO2 to constrain the emission plume region. Our results agree with CO2 emission estimations based on the power-plant-generated power and emission factors.
Glenn-Michael Oomen, Jean-François Müller, Trissevgeni Stavrakou, Isabelle De Smedt, Thomas Blumenstock, Rigel Kivi, Maria Makarova, Mathias Palm, Amelie Röhling, Yao Té, Corinne Vigouroux, Martina M. Friedrich, Udo Frieß, François Hendrick, Alexis Merlaud, Ankie Piters, Andreas Richter, Michel Van Roozendael, and Thomas Wagner
Atmos. Chem. Phys., 24, 449–474, https://doi.org/10.5194/acp-24-449-2024, https://doi.org/10.5194/acp-24-449-2024, 2024
Short summary
Short summary
Natural emissions from vegetation have a profound impact on air quality for their role in the formation of harmful tropospheric ozone and organic aerosols, yet these emissions are highly uncertain. In this study, we quantify emissions of organic gases over Europe using high-quality satellite measurements of formaldehyde. These satellite observations suggest that emissions from vegetation are much higher than predicted by models, especially in southern Europe.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Bianca Zilker, Andreas Richter, Anne-Marlene Blechschmidt, Peter von der Gathen, Ilias Bougoudis, Sora Seo, Tim Bösch, and John Philip Burrows
Atmos. Chem. Phys., 23, 9787–9814, https://doi.org/10.5194/acp-23-9787-2023, https://doi.org/10.5194/acp-23-9787-2023, 2023
Short summary
Short summary
During Arctic spring, near-surface ozone is depleted by bromine released from salty sea ice and/or snow-covered areas under certain meteorological conditions. To study this ozone depletion and the prevailing meteorological conditions, two ozone data sets from Ny-Ålesund, Svalbard, have been evaluated. We found that during ozone depletion events lower pressure over the Barents Sea and higher pressure in the Icelandic Low area led to a transport of cold polar air from the north to Ny-Ålesund.
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.
Ka Lok Chan, Pieter Valks, Klaus-Peter Heue, Ronny Lutz, Pascal Hedelt, Diego Loyola, Gaia Pinardi, Michel Van Roozendael, François Hendrick, Thomas Wagner, Vinod Kumar, Alkis Bais, Ankie Piters, Hitoshi Irie, Hisahiro Takashima, Yugo Kanaya, Yongjoo Choi, Kihong Park, Jihyo Chong, Alexander Cede, Udo Frieß, Andreas Richter, Jianzhong Ma, Nuria Benavent, Robert Holla, Oleg Postylyakov, Claudia Rivera Cárdenas, and Mark Wenig
Earth Syst. Sci. Data, 15, 1831–1870, https://doi.org/10.5194/essd-15-1831-2023, https://doi.org/10.5194/essd-15-1831-2023, 2023
Short summary
Short summary
This paper presents the theoretical basis as well as verification and validation of the Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 products.
Kai Krause, Folkard Wittrock, Andreas Richter, Dieter Busch, Anton Bergen, John P. Burrows, Steffen Freitag, and Olesia Halbherr
Atmos. Meas. Tech., 16, 1767–1787, https://doi.org/10.5194/amt-16-1767-2023, https://doi.org/10.5194/amt-16-1767-2023, 2023
Short summary
Short summary
Inland shipping is an important source of nitrogen oxides (NOx). The amount of emitted NOx depends on the characteristics of the individual vessels and the traffic density. Ship emissions are often characterised by the amount of emitted NOx per unit of burnt fuel, and further knowledge about fuel consumption is needed to quantify the total emissions caused by ship traffic. In this study, a new approach to derive absolute emission rates (in g s−1) from onshore measurements is presented.
Kezia Lange, Andreas Richter, Anja Schönhardt, Andreas C. Meier, Tim Bösch, André Seyler, Kai Krause, Lisa K. Behrens, Folkard Wittrock, Alexis Merlaud, Frederik Tack, Caroline Fayt, Martina M. Friedrich, Ermioni Dimitropoulou, Michel Van Roozendael, Vinod Kumar, Sebastian Donner, Steffen Dörner, Bianca Lauster, Maria Razi, Christian Borger, Katharina Uhlmannsiek, Thomas Wagner, Thomas Ruhtz, Henk Eskes, Birger Bohn, Daniel Santana Diaz, Nader Abuhassan, Dirk Schüttemeyer, and John P. Burrows
Atmos. Meas. Tech., 16, 1357–1389, https://doi.org/10.5194/amt-16-1357-2023, https://doi.org/10.5194/amt-16-1357-2023, 2023
Short summary
Short summary
We present airborne imaging DOAS and ground-based stationary and car DOAS measurements conducted during the S5P-VAL-DE-Ruhr campaign in the Rhine-Ruhr region. The measurements are used to validate spaceborne NO2 data products from the Sentinel-5 Precursor TROPOspheric Monitoring Instrument (TROPOMI). Auxiliary data of the TROPOMI NO2 retrieval, such as spatially higher resolved a priori NO2 vertical profiles, surface reflectivity, and cloud treatment are investigated to evaluate their impact.
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
Short summary
Short summary
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.
Miriam Latsch, Andreas Richter, Henk Eskes, Maarten Sneep, Ping Wang, Pepijn Veefkind, Ronny Lutz, Diego Loyola, Athina Argyrouli, Pieter Valks, Thomas Wagner, Holger Sihler, Michel van Roozendael, Nicolas Theys, Huan Yu, Richard Siddans, and John P. Burrows
Atmos. Meas. Tech., 15, 6257–6283, https://doi.org/10.5194/amt-15-6257-2022, https://doi.org/10.5194/amt-15-6257-2022, 2022
Short summary
Short summary
The article investigates different S5P TROPOMI cloud retrieval algorithms for tropospheric trace gas retrievals. The cloud products show differences primarily over snow and ice and for scenes under sun glint. Some issues regarding across-track dependence are found for the cloud fractions as well as for the cloud heights.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Gaia Pinardi, Michel Van Roozendael, François Hendrick, Andreas Richter, Pieter Valks, Ramina Alwarda, Kristof Bognar, Udo Frieß, José Granville, Myojeong Gu, Paul Johnston, Cristina Prados-Roman, Richard Querel, Kimberly Strong, Thomas Wagner, Folkard Wittrock, and Margarita Yela Gonzalez
Atmos. Meas. Tech., 15, 3439–3463, https://doi.org/10.5194/amt-15-3439-2022, https://doi.org/10.5194/amt-15-3439-2022, 2022
Short summary
Short summary
We report on the GOME-2A and GOME-2B OClO dataset (2007 to 2016, from the EUMETSAT's AC SAF) validation using data from nine NDACC zenith-scattered-light DOAS (ZSL-DOAS) instruments distributed in both the Arctic and Antarctic. Specific sensitivity tests are performed on the ground-based data to estimate the impact of the different OClO DOAS analysis settings and their typical errors. Good agreement is found for both the inter-annual variability and the overall OClO seasonal behavior.
M. Dolores Andrés Hernández, Andreas Hilboll, Helmut Ziereis, Eric Förster, Ovid O. Krüger, Katharina Kaiser, Johannes Schneider, Francesca Barnaba, Mihalis Vrekoussis, Jörg Schmidt, Heidi Huntrieser, Anne-Marlene Blechschmidt, Midhun George, Vladyslav Nenakhov, Theresa Harlass, Bruna A. Holanda, Jennifer Wolf, Lisa Eirenschmalz, Marc Krebsbach, Mira L. Pöhlker, Anna B. Kalisz Hedegaard, Linlu Mei, Klaus Pfeilsticker, Yangzhuoran Liu, Ralf Koppmann, Hans Schlager, Birger Bohn, Ulrich Schumann, Andreas Richter, Benjamin Schreiner, Daniel Sauer, Robert Baumann, Mariano Mertens, Patrick Jöckel, Markus Kilian, Greta Stratmann, Christopher Pöhlker, Monica Campanelli, Marco Pandolfi, Michael Sicard, José L. Gómez-Amo, Manuel Pujadas, Katja Bigge, Flora Kluge, Anja Schwarz, Nikos Daskalakis, David Walter, Andreas Zahn, Ulrich Pöschl, Harald Bönisch, Stephan Borrmann, Ulrich Platt, and John P. Burrows
Atmos. Chem. Phys., 22, 5877–5924, https://doi.org/10.5194/acp-22-5877-2022, https://doi.org/10.5194/acp-22-5877-2022, 2022
Short summary
Short summary
EMeRGe provides a unique set of in situ and remote sensing airborne measurements of trace gases and aerosol particles along selected flight routes in the lower troposphere over Europe. The interpretation uses also complementary collocated ground-based and satellite measurements. The collected data help to improve the current understanding of the complex spatial distribution of trace gases and aerosol particles resulting from mixing, transport, and transformation of pollution plumes over Europe.
Kezia Lange, Andreas Richter, and John P. Burrows
Atmos. Chem. Phys., 22, 2745–2767, https://doi.org/10.5194/acp-22-2745-2022, https://doi.org/10.5194/acp-22-2745-2022, 2022
Short summary
Short summary
In this study, we investigated short time variability of NOx emissions and lifetimes on a global scale. We combined 2 years of satellite Sentinel-5P TROPOMI tropospheric NO2 column data with wind data. Fifty NOx sources distributed around the world are analyzed. The retrieved emissions show a clear seasonal dependence. NOx lifetime shows a latitudinal dependence but only a week seasonal dependence. NOx emissions show a clear weekly pattern which in contrast is not visible for NOx lifetimes.
Christophe Lerot, François Hendrick, Michel Van Roozendael, Leonardo M. A. Alvarado, Andreas Richter, Isabelle De Smedt, Nicolas Theys, Jonas Vlietinck, Huan Yu, Jeroen Van Gent, Trissevgeni Stavrakou, Jean-François Müller, Pieter Valks, Diego Loyola, Hitoshi Irie, Vinod Kumar, Thomas Wagner, Stefan F. Schreier, Vinayak Sinha, Ting Wang, Pucai Wang, and Christian Retscher
Atmos. Meas. Tech., 14, 7775–7807, https://doi.org/10.5194/amt-14-7775-2021, https://doi.org/10.5194/amt-14-7775-2021, 2021
Short summary
Short summary
Global measurements of glyoxal tropospheric columns from the satellite instrument TROPOMI are presented. Such measurements can contribute to the estimation of atmospheric emissions of volatile organic compounds. This new glyoxal product has been fully characterized with a comprehensive error budget, with comparison with other satellite data sets as well as with validation based on independent ground-based remote sensing glyoxal observations.
Jānis Puķīte, Christian Borger, Steffen Dörner, Myojeong Gu, Udo Frieß, Andreas Carlos Meier, Carl-Fredrik Enell, Uwe Raffalski, Andreas Richter, and Thomas Wagner
Atmos. Meas. Tech., 14, 7595–7625, https://doi.org/10.5194/amt-14-7595-2021, https://doi.org/10.5194/amt-14-7595-2021, 2021
Short summary
Short summary
Chlorine dioxide (OClO) is used as an indicator for chlorine activation. We present a new differential optical absorption spectroscopy retrieval algorithm for OClO from measurements of TROPOMI on the Sentinel-5P satellite. To achieve a substantially improved accuracy for the weak absorber OClO, we consider several additional fit parameters accounting for various higher-order spectral effects. The retrieved OClO slant column densities are compared with ground-based zenith sky measurements.
Song Liu, Pieter Valks, Gaia Pinardi, Jian Xu, Ka Lok Chan, Athina Argyrouli, Ronny Lutz, Steffen Beirle, Ehsan Khorsandi, Frank Baier, Vincent Huijnen, Alkiviadis Bais, Sebastian Donner, Steffen Dörner, Myrto Gratsea, François Hendrick, Dimitris Karagkiozidis, Kezia Lange, Ankie J. M. Piters, Julia Remmers, Andreas Richter, Michel Van Roozendael, Thomas Wagner, Mark Wenig, and Diego G. Loyola
Atmos. Meas. Tech., 14, 7297–7327, https://doi.org/10.5194/amt-14-7297-2021, https://doi.org/10.5194/amt-14-7297-2021, 2021
Short summary
Short summary
In this work, an improved tropospheric NO2 retrieval algorithm from TROPOMI measurements over Europe is presented. The stratospheric estimation is implemented with correction for the dependency of the stratospheric NO2 on the viewing geometry. The AMF calculation is implemented using improved surface albedo, a priori NO2 profiles, and cloud correction. The improved tropospheric NO2 data show good correlations with ground-based MAX-DOAS measurements.
Kai Krause, Folkard Wittrock, Andreas Richter, Stefan Schmitt, Denis Pöhler, Andreas Weigelt, and John P. Burrows
Atmos. Meas. Tech., 14, 5791–5807, https://doi.org/10.5194/amt-14-5791-2021, https://doi.org/10.5194/amt-14-5791-2021, 2021
Short summary
Short summary
Ships are an important source of key pollutants. Usually, these are measured aboard the ship or on the coast using in situ instruments. This study shows how active optical remote sensing can be used to measure ship emissions and how to determine emission rates of individual ships out of those measurements. These emission rates are valuable input for the assessment of the influence of shipping emissions in regions close to the shipping lanes.
Isabelle De Smedt, Gaia Pinardi, Corinne Vigouroux, Steven Compernolle, Alkis Bais, Nuria Benavent, Folkert Boersma, Ka-Lok Chan, Sebastian Donner, Kai-Uwe Eichmann, Pascal Hedelt, François Hendrick, Hitoshi Irie, Vinod Kumar, Jean-Christopher Lambert, Bavo Langerock, Christophe Lerot, Cheng Liu, Diego Loyola, Ankie Piters, Andreas Richter, Claudia Rivera Cárdenas, Fabian Romahn, Robert George Ryan, Vinayak Sinha, Nicolas Theys, Jonas Vlietinck, Thomas Wagner, Ting Wang, Huan Yu, and Michel Van Roozendael
Atmos. Chem. Phys., 21, 12561–12593, https://doi.org/10.5194/acp-21-12561-2021, https://doi.org/10.5194/acp-21-12561-2021, 2021
Short summary
Short summary
This paper assess the performances of the TROPOMI formaldehyde observations compared to its predecessor OMI at different spatial and temporal scales. We also use a global network of MAX-DOAS instruments to validate both satellite datasets for a large range of HCHO columns. The precision obtained with daily TROPOMI observations is comparable to monthly OMI observations. We present clear detection of weak HCHO column enhancements related to shipping emissions in the Indian Ocean.
Stefan F. Schreier, Tim Bösch, Andreas Richter, Kezia Lange, Michael Revesz, Philipp Weihs, Mihalis Vrekoussis, and Christoph Lotteraner
Atmos. Meas. Tech., 14, 5299–5318, https://doi.org/10.5194/amt-14-5299-2021, https://doi.org/10.5194/amt-14-5299-2021, 2021
Short summary
Short summary
This paper reports on the evaluation of aerosol profiling products retrieved from ground-based MAX-DOAS instruments using the BOREAS algorithm. Aerosol extinction profiles, near-surface aerosol extinction, and aerosol optical depth are compared to measurements collected with ceilometer, sun photometer, and in situ instruments. We show that these MAX-DOAS aerosol profiling products provide useful information to study spatial and temporal variations above the urban area of Vienna.
Ioanna Skoulidou, Maria-Elissavet Koukouli, Astrid Manders, Arjo Segers, Dimitris Karagkiozidis, Myrto Gratsea, Dimitris Balis, Alkiviadis Bais, Evangelos Gerasopoulos, Trisevgeni Stavrakou, Jos van Geffen, Henk Eskes, and Andreas Richter
Atmos. Chem. Phys., 21, 5269–5288, https://doi.org/10.5194/acp-21-5269-2021, https://doi.org/10.5194/acp-21-5269-2021, 2021
Short summary
Short summary
The performance of LOTOS-EUROS v2.2.001 regional chemical transport model NO2 simulations is investigated over Greece from June to December 2018. Comparison with in situ NO2 measurements shows a spatial correlation coefficient of 0.86, while the model underestimates the concentrations mostly during daytime (12 to 15:00 local time). Further, the simulated tropospheric NO2 columns are evaluated against ground-based MAX-DOAS NO2 measurements and S5P/TROPOMI observations for July and December 2018.
Myrto Gratsea, Tim Bösch, Panagiotis Kokkalis, Andreas Richter, Mihalis Vrekoussis, Stelios Kazadzis, Alexandra Tsekeri, Alexandros Papayannis, Maria Mylonaki, Vassilis Amiridis, Nikos Mihalopoulos, and Evangelos Gerasopoulos
Atmos. Meas. Tech., 14, 749–767, https://doi.org/10.5194/amt-14-749-2021, https://doi.org/10.5194/amt-14-749-2021, 2021
Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Jean-Christopher Lambert, Henk J. Eskes, Kai-Uwe Eichmann, Ann Mari Fjæraa, José Granville, Sander Niemeijer, Alexander Cede, Martin Tiefengraber, François Hendrick, Andrea Pazmiño, Alkiviadis Bais, Ariane Bazureau, K. Folkert Boersma, Kristof Bognar, Angelika Dehn, Sebastian Donner, Aleksandr Elokhov, Manuel Gebetsberger, Florence Goutail, Michel Grutter de la Mora, Aleksandr Gruzdev, Myrto Gratsea, Georg H. Hansen, Hitoshi Irie, Nis Jepsen, Yugo Kanaya, Dimitris Karagkiozidis, Rigel Kivi, Karin Kreher, Pieternel F. Levelt, Cheng Liu, Moritz Müller, Monica Navarro Comas, Ankie J. M. Piters, Jean-Pierre Pommereau, Thierry Portafaix, Cristina Prados-Roman, Olga Puentedura, Richard Querel, Julia Remmers, Andreas Richter, John Rimmer, Claudia Rivera Cárdenas, Lidia Saavedra de Miguel, Valery P. Sinyakov, Wolfgang Stremme, Kimberly Strong, Michel Van Roozendael, J. Pepijn Veefkind, Thomas Wagner, Folkard Wittrock, Margarita Yela González, and Claus Zehner
Atmos. Meas. Tech., 14, 481–510, https://doi.org/10.5194/amt-14-481-2021, https://doi.org/10.5194/amt-14-481-2021, 2021
Short summary
Short summary
This paper reports on the ground-based validation of the NO2 data produced operationally by the TROPOMI instrument on board the Sentinel-5 Precursor satellite. Tropospheric, stratospheric, and total NO2 columns are compared to measurements collected from MAX-DOAS, ZSL-DOAS, and PGN/Pandora instruments respectively. The products are found to satisfy mission requirements in general, though negative mean differences are found at sites with high pollution levels. Potential causes are discussed.
Jan-Lukas Tirpitz, Udo Frieß, François Hendrick, Carlos Alberti, Marc Allaart, Arnoud Apituley, Alkis Bais, Steffen Beirle, Stijn Berkhout, Kristof Bognar, Tim Bösch, Ilya Bruchkouski, Alexander Cede, Ka Lok Chan, Mirjam den Hoed, Sebastian Donner, Theano Drosoglou, Caroline Fayt, Martina M. Friedrich, Arnoud Frumau, Lou Gast, Clio Gielen, Laura Gomez-Martín, Nan Hao, Arjan Hensen, Bas Henzing, Christian Hermans, Junli Jin, Karin Kreher, Jonas Kuhn, Johannes Lampel, Ang Li, Cheng Liu, Haoran Liu, Jianzhong Ma, Alexis Merlaud, Enno Peters, Gaia Pinardi, Ankie Piters, Ulrich Platt, Olga Puentedura, Andreas Richter, Stefan Schmitt, Elena Spinei, Deborah Stein Zweers, Kimberly Strong, Daan Swart, Frederik Tack, Martin Tiefengraber, René van der Hoff, Michel van Roozendael, Tim Vlemmix, Jan Vonk, Thomas Wagner, Yang Wang, Zhuoru Wang, Mark Wenig, Matthias Wiegner, Folkard Wittrock, Pinhua Xie, Chengzhi Xing, Jin Xu, Margarita Yela, Chengxin Zhang, and Xiaoyi Zhao
Atmos. Meas. Tech., 14, 1–35, https://doi.org/10.5194/amt-14-1-2021, https://doi.org/10.5194/amt-14-1-2021, 2021
Short summary
Short summary
Multi-axis differential optical absorption spectroscopy (MAX-DOAS) is a ground-based remote sensing measurement technique that derives atmospheric aerosol and trace gas vertical profiles from skylight spectra. In this study, consistency and reliability of MAX-DOAS profiles are assessed by applying nine different evaluation algorithms to spectral data recorded during an intercomparison campaign in the Netherlands and by comparing the results to colocated supporting observations.
Xin Yang, Anne-M. Blechschmidt, Kristof Bognar, Audra McClure-Begley, Sara Morris, Irina Petropavlovskikh, Andreas Richter, Henrik Skov, Kimberly Strong, David W. Tarasick, Taneil Uttal, Mika Vestenius, and Xiaoyi Zhao
Atmos. Chem. Phys., 20, 15937–15967, https://doi.org/10.5194/acp-20-15937-2020, https://doi.org/10.5194/acp-20-15937-2020, 2020
Short summary
Short summary
This is a modelling-based study on Arctic surface ozone, with a particular focus on spring ozone depletion events (i.e. with concentrations < 10 ppbv). Model experiments show that model runs with blowing-snow-sourced sea salt aerosols implemented as a source of reactive bromine can reproduce well large-scale ozone depletion events observed in the Arctic. This study supplies modelling evidence of the proposed mechanism of reactive-bromine release from blowing snow on sea ice (Yang et al., 2008).
Gaia Pinardi, Michel Van Roozendael, François Hendrick, Nicolas Theys, Nader Abuhassan, Alkiviadis Bais, Folkert Boersma, Alexander Cede, Jihyo Chong, Sebastian Donner, Theano Drosoglou, Anatoly Dzhola, Henk Eskes, Udo Frieß, José Granville, Jay R. Herman, Robert Holla, Jari Hovila, Hitoshi Irie, Yugo Kanaya, Dimitris Karagkiozidis, Natalia Kouremeti, Jean-Christopher Lambert, Jianzhong Ma, Enno Peters, Ankie Piters, Oleg Postylyakov, Andreas Richter, Julia Remmers, Hisahiro Takashima, Martin Tiefengraber, Pieter Valks, Tim Vlemmix, Thomas Wagner, and Folkard Wittrock
Atmos. Meas. Tech., 13, 6141–6174, https://doi.org/10.5194/amt-13-6141-2020, https://doi.org/10.5194/amt-13-6141-2020, 2020
Short summary
Short summary
We validate several GOME-2 and OMI tropospheric NO2 products with 23 MAX-DOAS and 16 direct sun instruments distributed worldwide, highlighting large horizontal inhomogeneities at several sites affecting the validation results. We propose a method for quantification and correction. We show the application of such correction reduces the satellite underestimation in almost all heterogeneous cases, but a negative bias remains over the MAX-DOAS and direct sun network ensemble for both satellites.
Sora Seo, Andreas Richter, Anne-Marlene Blechschmidt, Ilias Bougoudis, and John Philip Burrows
Atmos. Chem. Phys., 20, 12285–12312, https://doi.org/10.5194/acp-20-12285-2020, https://doi.org/10.5194/acp-20-12285-2020, 2020
Short summary
Short summary
In this study, we present spatial distributions of occurrence frequency of enhanced total BrO column and various meteorological parameters affecting it in the Arctic and Antarctic sea ice regions by using 10 years of GOME-2 measurements and meteorological model data. Statistical analysis using the long-term dataset shows clear differences in the meteorological conditions between the mean field and the situation of enhanced total BrO columns in both polar sea ice regions.
Ilias Bougoudis, Anne-Marlene Blechschmidt, Andreas Richter, Sora Seo, John Philip Burrows, Nicolas Theys, and Annette Rinke
Atmos. Chem. Phys., 20, 11869–11892, https://doi.org/10.5194/acp-20-11869-2020, https://doi.org/10.5194/acp-20-11869-2020, 2020
Short summary
Short summary
A 22-year (1996 to 2017) consistent Arctic tropospheric BrO dataset derived from four satellite remote sensing instruments is presented. An increase in tropospheric BrO VCDs over this period, and especially during polar springs, can be seen. Comparisons of tropospheric BrO VCDs with first-year sea ice reveal a moderate spatial and temporal correlation between the two, suggesting that the increase in first-year sea ice in the Arctic has an impact on tropospheric BrO abundancies.
Alexis Merlaud, Livio Belegante, Daniel-Eduard Constantin, Mirjam Den Hoed, Andreas Carlos Meier, Marc Allaart, Magdalena Ardelean, Maxim Arseni, Tim Bösch, Hugues Brenot, Andreea Calcan, Emmanuel Dekemper, Sebastian Donner, Steffen Dörner, Mariana Carmelia Balanica Dragomir, Lucian Georgescu, Anca Nemuc, Doina Nicolae, Gaia Pinardi, Andreas Richter, Adrian Rosu, Thomas Ruhtz, Anja Schönhardt, Dirk Schuettemeyer, Reza Shaiganfar, Kerstin Stebel, Frederik Tack, Sorin Nicolae Vâjâiac, Jeni Vasilescu, Jurgen Vanhamel, Thomas Wagner, and Michel Van Roozendael
Atmos. Meas. Tech., 13, 5513–5535, https://doi.org/10.5194/amt-13-5513-2020, https://doi.org/10.5194/amt-13-5513-2020, 2020
Short summary
Short summary
The AROMAT campaigns took place in Romania in 2014 and 2015. They aimed to test airborne observation systems dedicated to air quality studies and to verify the concept of such campaigns in support of the validation of space-borne atmospheric missions. We show that airborne measurements of NO2 can be valuable for the validation of air quality satellites. For H2CO and SO2, the validation should involve ground-based measurement systems at key locations that the AROMAT measurements help identify.
Cited articles
Ahmad, N., Lin, C., Lau, A. K. H., Kim, J., Zhang, T., Yu, F., Li, C., Li, Y., Fung, J. C. H., and Lao, X. Q.: Estimation of ground-level NO2 and its spatiotemporal variations in China using GEMS measurements and a nested machine learning model, Atmos. Chem. Phys., 24, 9645–9665, https://doi.org/10.5194/acp-24-9645-2024, 2024. a, b
Bechle, M. J., Millet, D. B., and Marshall, J. D.: Remote sensing of exposure to NO2: Satellite versus ground-based measurement in a large urban area, Atmos. Environ., 69, 345–353, https://doi.org/10.1016/j.atmosenv.2012.11.046, 2013. a
Beirle, S., Hörmann, C., Jöckel, P., Liu, S., Penning de Vries, M., Pozzer, A., Sihler, H., Valks, P., and Wagner, T.: The STRatospheric Estimation Algorithm from Mainz (STREAM): estimating stratospheric NO2 from nadir-viewing satellites by weighted convolution, Atmos. Meas. Tech., 9, 2753–2779, https://doi.org/10.5194/amt-9-2753-2016, 2016. a
Bovensmann, H., Burrows, J., Buchwitz, M., Frerick, J., Noel, S., Rozanov, V., Chance, Kelly, and Goede, A.: SCIAMACHY: mission objectives and measurement modes, J. Atmos. Sci., 56, 127–150 https://doi.org/10.1175/1520-0469(1999)056<0127:SMOAMM>2.0.CO;2, 1999. a
Breiman, L.: Random Forests, Machine Learning, 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001. a
Burrows, J. P., Weber, M., Buchwitz, M., Rozanov, V., Ladstätter-Weißenmayer, A., Richter, A., DeBeek, R., Hoogen, R., Bramstedt, K., Eichmann, K.-U., Eisinger, M., and Perner, D.: The Global Ozone Monitoring Experiment (GOME): Mission Concept and First Scientific Results, J. Atmos. Sci., 56, 151–175, https://doi.org/10.1175/1520-0469(1999)056<0151:TGOMEG>2.0.CO;2, 1999. a
Chan, K. L., Khorsandi, E., Liu, S., Baier, F., and Valks, P.: Estimation of Surface NO2 Concentrations over Germany from TROPOMI Satellite Observations Using a Machine Learning Method, Remote Sensing, 13, 969, https://doi.org/10.3390/rs13050969, 2021. a, b, c, d
Chen, Z.-Y., Zhang, R., Zhang, T.-H., Ou, C.-Q., and Guo, Y.: A kriging-calibrated machine learning method for estimating daily ground-level NO2 in mainland China, Sci. Total Environ., 690, 556–564, https://doi.org/10.1016/j.scitotenv.2019.06.349, 2019. a
Cooper, M., Martin, R., Hammer, M., Levelt, P. F., Veefkind, P., Lamsal, L. N., Krotkov, N. A., Brook, J. R., and McLinden, C. A.: Global fine-scale changes in ambient NO2 during COVID-19 lockdowns, Nature, 601, 380–387, https://doi.org/10.1038/s41586-021-04229-0, 2022. a
Cooper, M. J., Martin, R. V., McLinden, C. A., and Brook, J. R.: Inferring ground-level nitrogen dioxide concentrations at fine spatial resolution applied to the TROPOMI satellite instrument, Environ. Res. Lett., 15, 104013, https://doi.org/10.1088/1748-9326/aba3a5, 2020. a
Copernicus Climate Change Service: 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, 2023. a
de Hoogh, K., Saucy, A., Shtein, A., Schwartz, J., West, E. A., Strassmann, A., Puhan, M., Röösli, M., Stafoggia, M., and Kloog, I.: Predicting Fine-Scale Daily NO2 for 2005–2016 Incorporating OMI Satellite Data Across Switzerland, Environ. Sci. Technol., 53, 10279–10287, https://doi.org/10.1021/acs.est.9b03107, 2019. a, b
Di, Q., Amini, H., Shi, L., Kloog, I., Silvern, R., Kelly, J., Sabath, M. B., Choirat, C., Koutrakis, P., Lyapustin, A., Wang, Y., Mickley, L. J., and Schwartz, J.: Assessing NO2 Concentration and Model Uncertainty with High Spatiotemporal Resolution across the Contiguous United States Using Ensemble Model Averaging, Environ. Sci. Technol., 54, 1372–1384, https://doi.org/10.1021/acs.est.9b03358, 2020. a, b, c, d
Dou, X., Liao, C., Wang, H., Huang, Y., Tu, Y., Huang, X., Peng, Y., Zhu, B., Tan, J., Deng, Z., Wu, N., Sun, T., Ke, P., and Liu, Z.: Estimates of daily ground-level NO2 concentrations in China based on Random Forest model integrated K-means, Advances in Applied Energy, 2, 100017, https://doi.org/10.1016/j.adapen.2021.100017, 2021. a
Geddes, J. A., Martin, R. V., Boys, B. L., and van Donkelaar, A.: Long-Term Trends Worldwide in Ambient NO2 Concentrations Inferred from Satellite Observations, Environ. Health Persp., 124, 281–289, https://doi.org/10.1289/ehp.1409567, 2016. a
Genuer, R., Poggi, J.-M., and Tuleau, C.: Random Forests: some methodological insights, arXiv [preprint], https://doi.org/10.48550/arXiv.0811.3619, 21 November 2008. a, b
Gu, J., Chen, L., Yu, C., Li, S., Tao, J., Fan, M., Xiong, X., Wang, Z., Shang, H., and Su, L.: Ground-Level NO2 Concentrations over China Inferred from the Satellite OMI and CMAQ Model Simulations, Remote Sensing, 9, 519, https://doi.org/10.3390/rs9060519, 2017. a
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, 2023. a, b, c, d, e
Huang, K., Zhu, Q., Lu, X., Gu, D., and Liu, Y.: Satellite-Based Long-Term Spatiotemporal Trends in Ambient NO2 Concentrations and Attributable Health Burdens in China From 2005 to 2020, GeoHealth, 7, e2023GH000798, https://doi.org/10.1029/2023GH000798, 2023. a, b
Jacob, D. J.: Introduction to Atmospheric Chemistry, Princeton University Press, Princeton, https://doi.org/10.1515/9781400841547, ISBN 9781400841547, 2000. a
Jiang, Q. and Christakos, G.: Space-time mapping of ground-level PM2.5 and NO2 concentrations in heavily polluted northern China during winter using the Bayesian maximum entropy technique with satellite data, Air Qual. Atmos. Hlth., 11, 23–33, https://doi.org/10.1007/s11869-017-0514-8, 2018. a
Kharol, S., Martin, R., Philip, S., Boys, B., Lamsal, L., Jerrett, M., Brauer, M., Crouse, D., McLinden, C., and Burnett, R.: Assessment of the magnitude and recent trends in satellite-derived ground-level nitrogen dioxide over North America, Atmos. Environ., 118, 236–245, https://doi.org/10.1016/j.atmosenv.2015.08.011, 2015. a
Kim, D., Lee, H., Hong, H., Choi, W., Lee, Y. G., and Park, J.: Estimation of Surface NO2 Volume Mixing Ratio in Four Metropolitan Cities in Korea Using Multiple Regression Models with OMI and AIRS Data, Remote Sensing, 9, 627, https://doi.org/10.3390/rs9060627, 2017. a, b
Kim, J., Jeong, U., Ahn, M.-H., Kim, J. H., Park, R. J., Lee, H., Song, C. H., Choi, Y.-S., Lee, K.-H., Yoo, J.-M., Jeong, M.-J., Park, S. K., Lee, K.-M., Song, C.-K., Kim, S.-W., Kim, Y. J., Kim, S.-W., Kim, M., Go, S., Liu, X., Chance, K., Miller, C. C., Al-Saadi, J., Veihelmann, B., Bhartia, P. K., Torres, O., Abad, G. G., Haffner, D. P., Ko, D. H., Lee, S. H., Woo, J.-H., Chong, H., Park, S. S., Nicks, D., Choi, W. J., Moon, K.-J., Cho, A., Yoon, J., Kim, S.-k., Hong, H., Lee, K., Lee, H., Lee, S., Choi, M., Veefkind, P., Levelt, P. F., Edwards, D. P., Kang, M., Eo, M., Bak, J., Baek, K., Kwon, H.-A., Yang, J., Park, J., Han, K. M., Kim, B.-R., Shin, H.-W., Choi, H., Lee, E., Chong, J., Cha, Y., Koo, J.-H., Irie, H., Hayashida, S., Kasai, Y., Kanaya, Y., Liu, C., Lin, J., Crawford, J. H., Carmichael, G. R., Newchurch, M. J., Lefer, B. L., Herman, J. R., Swap, R. J., Lau, A. K. H., Kurosu, T. P., Jaross, G., Ahlers, B., Dobber, M., McElroy, C. T., and Choi, Y.: New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS), B. Am. Meteorol. Soc., 101, E1–E22, https://doi.org/10.1175/BAMS-D-18-0013.1, 2020. a, b
Kim, M., Brunner, D., and Kuhlmann, G.: Importance of satellite observations for high-resolution mapping of near-surface NO2 by machine learning, Remote Sens. Environ., 264, 112573, https://doi.org/10.1016/j.rse.2021.112573, 2021. a, b
Kley, D. and McFarland, M.: Chemiluminescence detector for NO and NO/sub 2/, Atmos. Technol. (United States), 12, https://www.osti.gov/biblio/6457230, 1980. a
Lamsal, L. N., Martin, R. V., van Donkelaar, A., Steinbacher, M., Celarier, E. A., Bucsela, E., Dunlea, E. J., and Pinto, J. P.: Ground-level nitrogen dioxide concentrations inferred from the satellite-borne Ozone Monitoring Instrument, J. Geophys. Res.-Atmos., 113, D16308, https://doi.org/10.1029/2007JD009235, 2008. a
Lamsal, L. N., Martin, R. V., van Donkelaar, A., Celarier, E. A., Bucsela, E. J., Boersma, K. F., Dirksen, R., Luo, C., and Wang, Y.: Indirect validation of tropospheric nitrogen dioxide retrieved from the OMI satellite instrument: Insight into the seasonal variation of nitrogen oxides at northern midlatitudes, J. Geophys. Res.-Atmos., 115, D05302, https://doi.org/10.1029/2009JD013351, 2010. a
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. a
Lange, K., Richter, A., Bösch, T., Zilker, B., Latsch, M., Behrens, L. K., Okafor, C. M., Bösch, H., Burrows, J. P., Merlaud, A., Pinardi, G., Fayt, C., Friedrich, M. M., Dimitropoulou, E., Van Roozendael, M., Ziegler, S., Ripperger-Lukosiunaite, S., Kuhn, L., Lauster, B., Wagner, T., Hong, H., Kim, D., Chang, L.-S., Bae, K., Song, C.-K., Park, J.-U., and Lee, H.: Validation of GEMS tropospheric NO2 columns and their diurnal variation with ground-based DOAS measurements, Atmos. Meas. Tech., 17, 6315–6344, https://doi.org/10.5194/amt-17-6315-2024, 2024. a, b
Lee, H. J., Kim, N. R., and Shin, M. Y.: Capabilities of satellite Geostationary Environment Monitoring Spectrometer (GEMS) NO2 data for hourly ambient NO2 exposure modeling, Environ. Res., 261, 119633, https://doi.org/10.1016/j.envres.2024.119633, 2024. a
Levelt, P., van den Oord, G., Dobber, M., Malkki, A., Visser, H., de Vries, J., Stammes, P., Lundell, J., and Saari, H.: The ozone monitoring instrument, IEEE T. Geosci. Remote, 44, 1093–1101, https://doi.org/10.1109/TGRS.2006.872333, 2006. a
Li, M., Wu, Y., Bao, Y., Liu, B., and Petropoulos, G. P.: Near-Surface NO2 Concentration Estimation by Random Forest Modeling and Sentinel-5P and Ancillary Data, Remote Sensing, 14, 3612, https://doi.org/10.3390/rs14153612, 2022. a, b, c, d
Oak, Y. J., Jacob, D. J., Balasus, N., Yang, L. H., Chong, H., Park, J., Lee, H., Lee, G. T., Ha, E. S., Park, R. J., Kwon, H.-A., and Kim, J.: A bias-corrected GEMS geostationary satellite product for nitrogen dioxide using machine learning to enforce consistency with the TROPOMI satellite instrument, Atmos. Meas. Tech., 17, 5147–5159, https://doi.org/10.5194/amt-17-5147-2024, 2024. a
Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E.: Scikit-learn: Machine Learning in Python, J. Mach. Learn. Res., 12, 2825–2830, 2011. a, b
Probst, P., Bischl, B., and Boulesteix, A.-L.: Tunability: Importance of Hyperparameters of Machine Learning Algorithms, arXiv [preprint], https://doi.org/10.48550/arXiv.1802.09596, 22 October 2018. a, b, c
Probst, P., Wright, M. N., and Boulesteix, A.-L.: Hyperparameters and tuning strategies for random forest, WIREs Data Mining and Knowledge Discovery, 9, e1301, https://doi.org/10.1002/widm.1301, 2019. a
Qin, K., Han, X., Li, D., Xu, J., Loyola, D., Xue, Y., Zhou, X., Li, D., Zhang, K., and Yuan, L.: Satellite-based estimation of surface NO2 concentrations over east-central China: A comparison of POMINO and OMNO2d data, Atmos. Environ., 224, 117322, https://doi.org/10.1016/j.atmosenv.2020.117322, 2020. a, b, c
Scornet, E.: Tuning parameters in random forests, ESAIM: Procs., 60, 144–162, https://doi.org/10.1051/proc/201760144, 2017. a
Shetty, S., Schneider, P., Stebel, K., David Hamer, P., Kylling, A., and Koren Berntsen, T.: Estimating surface NO2 concentrations over Europe using Sentinel-5P TROPOMI observations and Machine Learning, Remote Sens. Environ., 312, 114321, https://doi.org/10.1016/j.rse.2024.114321, 2024. a
Siddique, M. A., Naseer, E., Usama, M., and Basit, A.: Estimation of Surface-Level NO2 Using Satellite Remote Sensing and Machine Learning: A review, IEEE Geoscience and Remote Sensing Magazine, 12, 2–28, https://doi.org/10.1109/MGRS.2024.3398434, 2024. a
Tang, B., Stanier, C. O., Carmichael, G. R., and Gao, M.: Ozone, nitrogen dioxide, and PM2.5 estimation from observation-model machine learning fusion over S. Korea: Influence of observation density, chemical transport model resolution, and geostationary remotely sensed AOD, Atmos. Environ., 331, 120603, https://doi.org/10.1016/j.atmosenv.2024.120603, 2024. a, b
Veefkind, J., Aben, I., McMullan, K., Förster, H., de Vries, J., Otter, G., Claas, J., Eskes, H., de Haan, J., 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.: 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. a
Wang, B. and Chen, Z.: An intercomparison of satellite-derived ground-level NO2 concentrations with GMSMB modeling results and in-situ measurements – A North American study, Environ. Pollut., 181, 172–181, https://doi.org/10.1016/j.envpol.2013.06.037, 2013. a
Wei, J., Liu, S., Li, Z., Liu, C., Qin, K., Liu, X., Pinker, R. T., Dickerson, R. R., Lin, J., Boersma, K. F., Sun, L., Li, R., Xue, W., Cui, Y., Zhang, C., and Wang, J.: Ground-Level NO2 Surveillance from Space Across China for High Resolution Using Interpretable Spatiotemporally Weighted Artificial Intelligence, Environ. Sci. Technol., 56, 9988–9998, https://doi.org/10.1021/acs.est.2c03834, 2022. a
Williams, J. E., Boersma, K. F., Le Sager, P., and Verstraeten, W. W.: The high-resolution version of TM5-MP for optimized satellite retrievals: description and validation, Geosci. Model Dev., 10, 721–750, https://doi.org/10.5194/gmd-10-721-2017, 2017. a
Yang, L. H., Jacob, D. J., Colombi, N. K., Zhai, S., Bates, K. H., Shah, V., Beaudry, E., Yantosca, R. M., Lin, H., Brewer, J. F., Chong, H., Travis, K. R., Crawford, J. H., Lamsal, L. N., Koo, J.-H., and Kim, J.: Tropospheric NO2 vertical profiles over South Korea and their relation to oxidant chemistry: implications for geostationary satellite retrievals and the observation of NO2 diurnal variation from space, Atmos. Chem. Phys., 23, 2465–2481, https://doi.org/10.5194/acp-23-2465-2023, 2023a. a
Yang, Q., Kim, J., Cho, Y., Lee, W.-J., Lee, D.-W., Yuan, Q., Wang, F., Zhou, C., Zhang, X., Xiao, X., Guo, M., Guo, Y., Carmichael, G. R., and Gao, M.: A synchronized estimation of hourly surface concentrations of six criteria air pollutants with GEMS data, npj Clim. Atmos. Sci., 6, 94, https://doi.org/10.1038/s41612-023-00407-1, 2023b. a, b, c, d, e
Zhang, Y., Lin, J., Kim, J., Lee, H., Park, J., Hong, H., Van Roozendael, M., Hendrick, F., Wang, T., Wang, P., He, Q., Qin, K., Choi, Y., Kanaya, Y., Xu, J., Xie, P., Tian, X., Zhang, S., Wang, S., Cheng, S., Cheng, X., Ma, J., Wagner, T., Spurr, R., Chen, L., Kong, H., and Liu, M.: A research product for tropospheric NO2 columns from Geostationary Environment Monitoring Spectrometer based on Peking University OMI NO2 algorithm, Atmos. Meas. Tech., 16, 4643–4665, https://doi.org/10.5194/amt-16-4643-2023, 2023. a
Short summary
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.
The Korean Geostationary Environmental Monitoring Spectrometer (GEMS) monitors trace gases over...
