Articles | Volume 13, issue 4
https://doi.org/10.5194/amt-13-1735-2020
© Author(s) 2020. 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-13-1735-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Apr 2020
Research article |
| 07 Apr 2020
| 07 Apr 2020
Discrete-wavelength DOAS NO2 slant column retrievals from OMI and TROPOMI
Cristina Ruiz Villena
CORRESPONDING AUTHOR
Department of Physics and Astronomy, Earth Observation Science Group, University of Leicester, Leicester, UK
Jasdeep S. Anand
Department of Physics and Astronomy, Earth Observation Science Group, University of Leicester, Leicester, UK
Roland J. Leigh
Department of Physics and Astronomy, Earth Observation Science Group, University of Leicester, Leicester, UK
now at: EarthSense Systems Ltd, Leicester, UK
Paul S. Monks
Department of Chemistry, University of Leicester, Leicester, UK
Claire E. Parfitt
formerly at: Thales Alenia Space UK Ltd, Bristol, UK
Joshua D. Vande Hey
CORRESPONDING AUTHOR
Department of Physics and Astronomy, Earth Observation Science Group, University of Leicester, Leicester, UK
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Measurement errors in satellite observations of CO2 attributed to co-estimated atmospheric variables are corrected using a linear regression on quality-filtered data. We propose a nonlinear method that improves correction against a set of ground truth proxies and allows for high throughput of well-corrected data.
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Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-220, https://doi.org/10.5194/amt-2023-220, 2023
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Comparison of total ozone column (TOC) measurements from ground-based Dobson and Brewer spectrophotometers generally reveals seasonally varying differences of a few percent. This study recommends a new TOC retrieval approach, which effectively eliminate these seasonally varying differences by applying new ozone absorption cross-sections, appropriate slit functions for the Dobson instrument, and climatological values for the effective ozone temperature.
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Revised manuscript accepted for AMT
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Manuel López-Puertas, Maya García-Comas, Bernd Funke, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, and Gabriele P. Stiller
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Atmospheric N2O and CH4 columns are successfully retrieved from low-resolution FTIR spectra recorded by a Bruker VERTEX 70. The 1-year measurements at Sodankylä show that the N2O total columns retrieved from 125HR and VERTEX 70 spectra are −0.3 ± 0.7 % with an R value of 0.93. The relative differences between the CH4 total columns retrieved from the 125HR and VERTEX spectra are 0.0 ± 0.8 % with an R value of 0.87. Such a technique can help to fill the gap in NDACC N2O and CH4 measurements.
Simon Warnach, Holger Sihler, Christian Borger, Nicole Bobrowski, Steffen Beirle, Ulrich Platt, and Thomas Wagner
Atmos. Meas. Tech., 16, 5537–5573, https://doi.org/10.5194/amt-16-5537-2023, https://doi.org/10.5194/amt-16-5537-2023, 2023
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BrO inside volcanic gas plumes but can be used in combination with SO2 to characterize the volcanic property and its activity state. High-quality satellite observations can provide a global inventory of this important quantity. This paper investigates how to accurately detect BrO inside volcanic plumes from the satellite UV spectrum. A sophisticated novel non-volcanic background correction scheme is presented, and systematic errors including cross-interference with formaldehyde are minimized.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Nickolay A. Krotkov, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Atmos. Meas. Tech., 16, 5575–5592, https://doi.org/10.5194/amt-16-5575-2023, https://doi.org/10.5194/amt-16-5575-2023, 2023
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Snow-covered terrain, with its high reflectance in the UV, typically enhances satellite sensitivity to boundary layer pollution. However, a significant fraction of high-quality cloud-free measurements over snow is currently excluded from analyses. In this study, we investigated how satellite SO2 measurements over snow-covered surfaces can be used to improve estimations of annual SO2 emissions.
Lieven Clarisse, Bruno Franco, Martin Van Damme, Tommaso Di Gioacchino, Juliette Hadji-Lazaro, Simon Whitburn, Lara Noppen, Daniel Hurtmans, Cathy Clerbaux, and Pierre Coheur
Atmos. Meas. Tech., 16, 5009–5028, https://doi.org/10.5194/amt-16-5009-2023, https://doi.org/10.5194/amt-16-5009-2023, 2023
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Ammonia is an important atmospheric pollutant. This article presents version 4 of the algorithm which retrieves ammonia abundances from the infrared measurements of the satellite sounder IASI. A measurement operator is introduced that can emulate the measurements (so-called averaging kernels) and measurement uncertainty is better characterized. Several other changes to the product itself are also documented, most of which improve the temporal consistency of the 2007–2022 IASI NH3 dataset.
Vladimir Savastiouk, Henri Diémoz, and C. Thomas McElroy
Atmos. Meas. Tech., 16, 4785–4806, https://doi.org/10.5194/amt-16-4785-2023, https://doi.org/10.5194/amt-16-4785-2023, 2023
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This paper describes a way to significantly improve ozone measurements at low sun elevations and large ozone amounts when using the Brewer ozone spectrophotometer. The proposed algorithm will allow more uniform ozone measurements across the monitoring network. This will contribute to more reliable trend analysis and support the satellite validation. This research contributes to better understanding the physics of the instrument, and the new algorithm is based on this new knowledge.
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.
Marvin Knapp, Ralph Kleinschek, Sanam N. Vardag, Felix Külheim, Helge Haveresch, Moritz Sindram, Tim Siegel, Bruno Burger, and Andre Butz
EGUsphere, https://doi.org/10.5194/egusphere-2023-1857, https://doi.org/10.5194/egusphere-2023-1857, 2023
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Imaging carbon dioxide (CO2) plumes of anthropogenic sources from planes and satellites has proven valuable for detecting emitters and monitoring climate mitigation efforts. We present the first images of CO2 plumes taken with a ground-based spectral camera, observing a coal-fired power plant as a validation target. We develop a technique to find the source emission strength with an hourly resolution, which reasonably agrees with the expected emissions under favorable conditions.
Matthieu Dogniaux, Joannes D. Maasakkers, Daniel J. Varon, and Ilse Aben
EGUsphere, https://doi.org/10.31223/X53M42, https://doi.org/10.31223/X53M42, 2023
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We analyze Landsat 8 (L8) and Sentinel-2B (S-2B) observations of the 2022 Nord Stream 2 methane leak, and show how challenging this case is for usual data analysis methods. We provide customized calibrations for this Nord Stream 2 case and assess that no firm conclusion can be drawn from L8 or S-2B single overpasses. However, if we opportunistically assume that L8 and S-2B results are independent, we find an averaged L8 and S-2B combined methane leak rate of 415 +/- 321 t/hr.
Stefan Noël, Michael Buchwitz, Michael Hilker, Maximilian Reuter, Michael Weimer, Heinrich Bovensmann, John P. Burrows, Hartmut Bösch, and Ruediger Lang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-194, https://doi.org/10.5194/amt-2023-194, 2023
Revised manuscript accepted for AMT
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FOCAL-CO2M is one of the three operational retrieval algorithms which will be used to derive XCO2 and XCH4 from measurements of the forthcoming European CO2M mission. We present results of applications of FOCAL-CO2M to simulated spectra, from which confidence is gained that the algorithm is able to fulfil the challenging requirements on systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4).
Philipp Hochstaffl, Franz Schreier, Claas Henning Köhler, Andreas Baumgartner, and Daniele Cerra
Atmos. Meas. Tech., 16, 4195–4214, https://doi.org/10.5194/amt-16-4195-2023, https://doi.org/10.5194/amt-16-4195-2023, 2023
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The study examines methane enhancements inferred from hyperspectral imaging observations using different retrieval schemes. One of the core challenges is the high spatial and moderate spectral resolution as it makes separation of spectral variations caused by molecular absorption and surface reflectivity challenging. It was found that localized methane enhancements can be detected and quantified from HySpex airborne observations using various retrieval schemes.
Wenyu Wang, Jian Xu, and Zhenzhan Wang
Atmos. Meas. Tech., 16, 4137–4153, https://doi.org/10.5194/amt-16-4137-2023, https://doi.org/10.5194/amt-16-4137-2023, 2023
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This article presents a study for feasibility analysis of atmospheric wind measurement using a terahertz (THz) passive limb radiometer with high spectral resolution. The simulations show that line-of-sight wind from 40 to 120 km can be obtained better than 10 m s−1 (at most altitudes it is better than 5 m s−1) using the O3, O2, H2O, and OI bands. This study will provide reference for future payload design.
Wei Huang, Lei Liu, Bin Yang, Shuai Hu, Wanying Yang, Zhenfeng Li, Wantong Li, and Xiaofan Yang
Atmos. Meas. Tech., 16, 4101–4114, https://doi.org/10.5194/amt-16-4101-2023, https://doi.org/10.5194/amt-16-4101-2023, 2023
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To improve the retrieval speed of the AERI optimal estimation (AERIoe) method, a fast-retrieval algorithm named Fast AERIoe is proposed on the basis of the findings that the change in Jacobians during the retrieval process had little effect on the performance of AERIoe. The results of the experiment show that the retrieved profiles from Fast AERIoe are comparable to those of AERIoe and that the retrieval speed is significantly improved, with the average retrieval time reduced by 59 %.
Rafaella Chiarella, Matthias Buschmann, Joshua Laughner, Isamu Morino, Justus Notholt, Christof Petri, Geoffrey Toon, Voltaire A. Velazco, and Thorsten Warneke
Atmos. Meas. Tech., 16, 3987–4007, https://doi.org/10.5194/amt-16-3987-2023, https://doi.org/10.5194/amt-16-3987-2023, 2023
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The goal is to establish a window and strategy for xCO2 retrieval from ground-based Fourier transform spectrometers for NDACC. In the study we describe the spectroscopy of the region, the locations and instruments used, and the methods of calculating the retrieved xCO2. We performed tests to assess the sensitivity to diverse factors and sources of errors while comparing the retrieval to a well-established xCO2 retrieval from TCCON.
Jack Bruno, Dylan Jervis, Daniel Varon, and Daniel Jacob
EGUsphere, https://doi.org/10.5194/egusphere-2023-1343, https://doi.org/10.5194/egusphere-2023-1343, 2023
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Methane is a potent greenhouse gas and a current high priority target for short/mid term climate change mitigation. Detection of individual methane emitters from space has become possible in recent years, and the volume of data for this task has been rapidly growing and the data volume is outpacing processing capabilities. We introduce an automated approach, U-Plume, which can detect and quantify emissions from individual methane sources in high spatial resolution satellite data.
Gabriele P. Stiller, Thomas von Clarmann, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Bernd Funke, Maya Garcia-Comas, and Manuel Lopez-Puertas
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-172, https://doi.org/10.5194/amt-2023-172, 2023
Revised manuscript accepted for AMT
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CFC-11, CFC-12, and HCFC-22 contribute to the depletion of ozone and are potent greenhouse gases. They have been banned by the Montreal protocol. With MIPAS on Envisat the atmospheric composition could be observed between 2002 and 2012. We present here the retrieval of their atmospheric distributions for the final data version 8. We characterise the derived data by their error budget and their spatial resolution. An additional representation for direct comparison to models is also provided.
Zhao-Cheng Zeng, Lu Lee, Chengli Qi, Lieven Clarisse, and Martin Van Damme
Atmos. Meas. Tech., 16, 3693–3713, https://doi.org/10.5194/amt-16-3693-2023, https://doi.org/10.5194/amt-16-3693-2023, 2023
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This study presents an NH3 retrieval algorithm based on the optimal estimation method for the Geostationary Interferometric Infrared Sounder (GIIRS) on board China’s FengYun-4B satellite (FY-4B/GIIRS). Retrieval results demonstrate the capability of FY-4B/GIIRS in capturing the diurnal NH3 changes in East Asia. This operational geostationary observation by FY-4B/GIIRS represents an important advancement over the twice-per-day observations provided by current low-Earth-orbit (LEO) instruments.
Juseon Bak, Xiong Liu, Kai Yang, Gonzalo Gonzalez Abad, Ewan O'Sullivan, Kelly Chance, and Cheol-Hee Kim
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-154, https://doi.org/10.5194/amt-2023-154, 2023
Revised manuscript accepted for AMT
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The new version (V2) of the OMI ozone profile product is introduced to improve retrieval quality and long-term consistency of tropospheric ozone, by incorporating the recent collection 4 OMI L1b spectral products and refining radiometric correction, forward model calculation and a priori ozone data.
Ethan Runge, Jeff Langille, Daniel Zawada, Adam Bourassa, and Doug Degenstein
Atmos. Meas. Tech., 16, 3123–3139, https://doi.org/10.5194/amt-16-3123-2023, https://doi.org/10.5194/amt-16-3123-2023, 2023
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The Limb Imaging Fourier Transform Spectrometer Experiment (LIFE) instrument takes vertical images of limb radiance across a wide mid-infrared spectral band from a stratospheric balloon. Measurements are used to infer vertical-trace-gas-profile retrievals of H2O, O3, HNO3, CH4, and N2O. Nearly time-/space-coincident observations from the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS) and Microwave Limb Sounder (MLS) instruments are compared to the LIFE results.
Zhao-Cheng Zeng, Lu Lee, and Chengli Qi
Atmos. Meas. Tech., 16, 3059–3083, https://doi.org/10.5194/amt-16-3059-2023, https://doi.org/10.5194/amt-16-3059-2023, 2023
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Observations from geostationary orbit provide contiguous coverage with a high temporal resolution, representing an important advancement over current low-Earth-orbit instruments. Using measurements from GIIRS on board China's FengYun satellite, the world’s first geostationary hyperspectral infrared sounder, we showed the first results of diurnal CO in eastern Asia from a geostationary orbit, which will have great potential in improving local and global air quality and climate research.
Norbert Glatthor, Thomas von Clarmann, Bernd Funke, Maya Garcia-Comas, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Michael Kiefer, Alexandra Laeng, Andrea Linden, Manuel Lopez-Puertas, and Gabriele P. Stiller
EGUsphere, https://doi.org/10.5194/egusphere-2023-919, https://doi.org/10.5194/egusphere-2023-919, 2023
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We present global atmospheric methane (CH4) and nitrous oxide (N2O) distributions retrieved from measurements of the MIPAS instrument onboard the ENVIronmental SATellite (ENVISAT) during 2002 to 2012. Monitoring of these gases is of scientific interest, because both of them are strong greenhouse gases. We analyse the latest, improved version of calibrated MIPAS measurements. Further, we apply a new retrieval scheme leading to an improved CH4 and N2O data product .
Tobias Borsdorff, Teresa Campos, Natalie Kille, Kyle J. Zarzana, Rainer Volkamer, and Jochen Landgraf
Atmos. Meas. Tech., 16, 3027–3038, https://doi.org/10.5194/amt-16-3027-2023, https://doi.org/10.5194/amt-16-3027-2023, 2023
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ECMWF plans to assimilate TROPOMI CO with their CAMS-IFS model. This will constrain the total column and the vertical CO distribution of the model. To show this, we combine individual TROPOMI CO column retrievals with different vertical sensitivities and obtain a vertical CO concentration profile. We test the approach on three CO pollution events in comparison with CAMS-IFS simulations that do not assimilate TROPOMI CO data and in situ airborne measurements of the BB-FLUX campaign.
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
EGUsphere, https://doi.org/10.5194/egusphere-2023-1163, https://doi.org/10.5194/egusphere-2023-1163, 2023
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We describe a new bromine monoxide (BrO) product from the OMPS-NM instrument onboard the Suomi-NPP satellite. This product provides global stratospheric and tropospheric columns separately for nearly a decade, a feature that is currently rare in publicly available datasets. Both stratospheric and the tropospheric BrO vertical columns from OMPS-NM demonstrate good agreement with ground-based observations from three stations (Lauder, Utqiag ̇vik, and Harestua).
Peter Joyce, Cristina Ruiz Villena, Yahui Huang, Alex Webb, Manuel Gloor, Fabien H. Wagner, Martyn P. Chipperfield, Rocío Barrio Guilló, Chris Wilson, and Hartmut Boesch
Atmos. Meas. Tech., 16, 2627–2640, https://doi.org/10.5194/amt-16-2627-2023, https://doi.org/10.5194/amt-16-2627-2023, 2023
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Methane emissions are responsible for a lot of the warming caused by the greenhouse effect, much of which comes from a small number of point sources. We can identify methane point sources by analysing satellite data, but it requires a lot of time invested by experts and is prone to very high errors. Here, we produce a neural network that can automatically identify methane point sources and estimate the mass of methane that is being released per hour and are able to do so with far smaller errors.
Harrison A. Parker, Joshua L. Laughner, Geoffrey C. Toon, Debra Wunch, Coleen M. Roehl, Laura T. Iraci, James R. Podolske, Kathryn McKain, Bianca C. Baier, and Paul O. Wennberg
Atmos. Meas. Tech., 16, 2601–2625, https://doi.org/10.5194/amt-16-2601-2023, https://doi.org/10.5194/amt-16-2601-2023, 2023
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We describe a retrieval algorithm for determining limited information about the vertical distribution of carbon monoxide (CO) and carbon dioxide (CO2) from total column observations from ground-based observations. Our retrieved partial column values compare well with integrated in situ data. The average error for our retrieval is 1.51 ppb (~ 2 %) for CO and 5.09 ppm (~ 1.25 %) for CO2. We anticipate that this approach will find broad application for use in carbon cycle science.
Andrea Orfanoz-Cheuquelaf, Carlo Arosio, Alexei Rozanov, Mark Weber, Annette Ladstätter-Weißenmayer, John P. Burrows, Anne M. Thompson, Ryan M. Stauffer, and Debra E. Kollonige
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2023-87, https://doi.org/10.5194/amt-2023-87, 2023
Revised manuscript accepted for AMT
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Valuable information on the tropospheric ozone column (TrOC) can be obtained globally by combining space-borne limb and nadir measurements (limb-nadir matching, LNM). This study describes the retrieval of TrOC from the OMPS instrument (since 2012) using the LNM technique. The OMPS-LNM TrOC was compared with ozonesondes and other satellite measurements, showing a good agreement with a negative bias within 1 to 4 DU. This new dataset is suitable for pollution studies.
Anna Vaughan, Gonzalo Mateo-García, Luis Gómez-Chova, Vít Růžička, Luis Guanter, and Itziar Irakulis-Loitxate
EGUsphere, https://doi.org/10.5194/egusphere-2023-563, https://doi.org/10.5194/egusphere-2023-563, 2023
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Methane is a potent greenhouse gas responsible for around 25 % of global warming since the industrial revolution. Consequently identifying and mitigating methane emissions is an important step in combating the climate crisis. We develop a new deep learning model to automatically detect methane plumes from satellite images, and demonstrate that this can be applied to monitor large methane emissions resulting from the oil and gas industry.
Qiansi Tu, Frank Hase, Zihan Chen, Matthias Schneider, Omaira García, Farahnaz Khosrawi, Shuo Chen, Thomas Blumenstock, Fang Liu, Kai Qin, Jason Cohen, Qin He, Song Lin, Hongyan Jiang, and Dianjun Fang
Atmos. Meas. Tech., 16, 2237–2262, https://doi.org/10.5194/amt-16-2237-2023, https://doi.org/10.5194/amt-16-2237-2023, 2023
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Four-year TROPOMI observations are used to derive tropospheric NO2 emissions in two mega(cities) with high anthropogenic activity. Wind-assigned anomalies are calculated, and the emission rates and spatial patterns are estimated based on a machine learning algorithm. The results are in reasonable agreement with previous studies and the inventory. Our method is quite robust and can be used as a simple method to estimate the emissions of NO2 as well as other gases in other regions.
Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Sylvia Kellmann, Michael Kiefer, Andrea Linden, Manuel López-Puertas, Gabriele P. Stiller, and Thomas von Clarmann
Atmos. Meas. Tech., 16, 2167–2196, https://doi.org/10.5194/amt-16-2167-2023, https://doi.org/10.5194/amt-16-2167-2023, 2023
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New global nitric oxide (NO) volume-mixing-ratio and lower-thermospheric temperature data products, retrieved from Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) spectra with the IMK-IAA MIPAS data processor, have been released. The dataset covers the entire Envisat mission lifetime and includes retrieval results from all MIPAS observation modes. The data are based on ESA version 8 calibration and were processed using an improved retrieval approach.
Adrien Vu Van, Anne Boynard, Pascal Prunet, Dominique Jolivet, Olivier Lezeaux, Patrice Henry, Claude Camy-Peyret, Lieven Clarisse, Bruno Franco, Pierre-François Coheur, and Cathy Clerbaux
Atmos. Meas. Tech., 16, 2107–2127, https://doi.org/10.5194/amt-16-2107-2023, https://doi.org/10.5194/amt-16-2107-2023, 2023
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With its near-real-time observations and good horizontal coverage, the Infrared Atmospheric Sounding Interferometer (IASI) instrument can contribute to the monitoring systems for a systematic and continuous detection of exceptional atmospheric events such as fires, anthropogenic pollution episodes, volcanic eruptions, or industrial releases. In this paper, a new approach is described for the detection and characterization of unexpected events in terms of trace gases using IASI radiance spectra.
Ian Ashpole and Aldona Wiacek
Atmos. Meas. Tech., 16, 1923–1949, https://doi.org/10.5194/amt-16-1923-2023, https://doi.org/10.5194/amt-16-1923-2023, 2023
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The MOPITT instrument has been measuring atmospheric carbon monoxide (CO) from space since 2000. Its data products are valuable for CO trend analysis. This paper compares products with different spatial resolutions to identify discrepancies in mean CO amounts and detectable trends for coastal grid boxes. It is found that CO amounts and trends differ significantly between data products for a large number of these grid boxes, essentially due to how the coarser-resolution products are created.
Viktoria F. Sofieva, Monika Szelag, Johanna Tamminen, Carlo Arosio, Alexei Rozanov, Mark Weber, Doug Degenstein, Adam Bourassa, Daniel Zawada, Michael Kiefer, Alexandra Laeng, Kaley A. Walker, Patrick Sheese, Daan Hubert, Michel van Roozendael, Christian Retscher, Robert Damadeo, and Jerry D. Lumpe
Atmos. Meas. Tech., 16, 1881–1899, https://doi.org/10.5194/amt-16-1881-2023, https://doi.org/10.5194/amt-16-1881-2023, 2023
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The paper presents the updated SAGE-CCI-OMPS+ climate data record of monthly zonal mean ozone profiles. This dataset covers the stratosphere and combines measurements by nine limb and occultation satellite instruments (SAGE II, OSIRIS, MIPAS, SCIAMACHY, GOMOS, ACE-FTS, OMPS-LP, POAM III, and SAGE III/ISS). The update includes new versions of MIPAS, ACE-FTS, and OSIRIS datasets and introduces data from additional sensors (POAM III and SAGE III/ISS) and retrieval processors (OMPS-LP).
Pierre J. Vanderbecken, Joffrey Dumont Le Brazidec, Alban Farchi, Marc Bocquet, Yelva Roustan, Élise Potier, and Grégoire Broquet
Atmos. Meas. Tech., 16, 1745–1766, https://doi.org/10.5194/amt-16-1745-2023, https://doi.org/10.5194/amt-16-1745-2023, 2023
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Instruments dedicated to monitoring atmospheric gaseous compounds from space will provide images of urban-scale plumes. We discuss here the use of new metrics to compare observed plumes with model predictions that will be less sensitive to meteorology uncertainties. We have evaluated our metrics on diverse plumes and shown that by eliminating some aspects of the discrepancies, they are indeed less sensitive to meteorological variations.
Alba Lorente, Tobias Borsdorff, Mari C. Martinez-Velarte, and Jochen Landgraf
Atmos. Meas. Tech., 16, 1597–1608, https://doi.org/10.5194/amt-16-1597-2023, https://doi.org/10.5194/amt-16-1597-2023, 2023
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In the TROPOMI methane data, there are few false methane anomalies that can be misinterpreted as enhancements caused by strong emission sources. These artefacts are caused by features of the underlying surfaces that are not well characterized in the retrieval algorithm. Here we improve the representation of the surface reflectance dependency with wavelength in the forward model, removing the artificial localized CH4 enhancements found in several locations like Siberia, Australia and Algeria.
Thomas Wagner, Simon Warnach, Steffen Beirle, Nicole Bobrowski, Adrian Jost, Janis Puķīte, and Nicolas Theys
Atmos. Meas. Tech., 16, 1609–1662, https://doi.org/10.5194/amt-16-1609-2023, https://doi.org/10.5194/amt-16-1609-2023, 2023
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We investigate 3D effects of volcanic plumes on the retrieval results of satellite and ground-based UV–Vis observations. With its small ground pixels of 3.5 x 5.5 km², the TROPOMI instrument can detect much smaller volcanic plumes than previous instruments. At the same time, 3D effects become important. The effect of horizontal photon paths especially can lead to a strong underestimation of the derived plume contents of up to > 50 %, which can be further increased for strong absorbers like SO2.
Congcong Qiao, Song Liu, Juan Huo, Xihan Mu, Ping Wang, Shengjie Jia, Xuehua Fan, and Minzheng Duan
Atmos. Meas. Tech., 16, 1539–1549, https://doi.org/10.5194/amt-16-1539-2023, https://doi.org/10.5194/amt-16-1539-2023, 2023
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We established a spectral-fitting method to derive precipitable water vapor (PWV) and aerosol optical depth based on a strict radiative transfer theory by the spectral measurements of direct sun from EKO MS711 and MS712 spectroradiometers. The retrievals were compared with that of the colocated CE-318 photometer; the results showed a high degree of consistency. In the PWV inversion, a strong water vapor absorption band around 1370 nm is introduced to retrieve PWV in a relatively dry atmosphere.
Yu Someya, Yukio Yoshida, Hirofumi Ohyama, Shohei Nomura, Akihide Kamei, Isamu Morino, Hitoshi Mukai, Tsuneo Matsunaga, Joshua L. Laughner, Voltaire A. Velazco, Benedikt Herkommer, Yao Té, Mahesh Kumar Sha, Rigel Kivi, Minqiang Zhou, Young Suk Oh, Nicholas M. Deutscher, and David W. T. Griffith
Atmos. Meas. Tech., 16, 1477–1501, https://doi.org/10.5194/amt-16-1477-2023, https://doi.org/10.5194/amt-16-1477-2023, 2023
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The updated retrieval algorithm for the Greenhouse gases Observing SATellite level 2 product is presented. The main changes in the algorithm from the previous one are the treatment of cirrus clouds, the degradation model of the sensor, solar irradiance, and gas absorption coefficient tables. The retrieval results showed improvements in fitting accuracy and an increase in the data amount over land. On the other hand, there are still large biases of XCO2 which should be corrected over the ocean.
Steffen Mauceri, Steven Massie, and Sebastian Schmidt
Atmos. Meas. Tech., 16, 1461–1476, https://doi.org/10.5194/amt-16-1461-2023, https://doi.org/10.5194/amt-16-1461-2023, 2023
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The Orbiting Carbon Observatory-2 makes space-based measurements of reflected sunlight. Using a retrieval algorithm these measurements are converted to CO2 concentrations in the atmosphere. However, the converted CO2 concentrations contain errors for observations close to clouds. Using a simple machine learning approach, we developed a model to correct these remaining errors. The model is able to reduce errors over land and ocean by 20 % and 40 %, respectively.
Michael Kiefer, Thomas von Clarmann, Bernd Funke, Maya García-Comas, Norbert Glatthor, Udo Grabowski, Michael Höpfner, Sylvia Kellmann, Alexandra Laeng, Andrea Linden, Manuel López-Puertas, and Gabriele P. Stiller
Atmos. Meas. Tech., 16, 1443–1460, https://doi.org/10.5194/amt-16-1443-2023, https://doi.org/10.5194/amt-16-1443-2023, 2023
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A new ozone data set, derived from radiation measurements of the space-borne instrument MIPAS, is presented. It consists of more than 2 million single ozone profiles from 2002–2012, covering virtually all latitudes and altitudes between 5 and 70 km. Progress in data calibration and processing methods allowed for significant improvement of the data quality, compared to previous data versions. Hence, the data set will help to better understand e.g. the time evolution of ozone in the stratosphere.
Nasrin Mostafavi Pak, Jacob K. Hedelius, Sébastien Roche, Liz Cunningham, Bianca Baier, Colm Sweeney, Coleen Roehl, Joshua Laughner, Geoffrey Toon, Paul Wennberg, Harrison Parker, Colin Arrowsmith, Joseph Mendonca, Pierre Fogal, Tyler Wizenberg, Beatriz Herrera, Kimberly Strong, Kaley A. Walker, Felix Vogel, and Debra Wunch
Atmos. Meas. Tech., 16, 1239–1261, https://doi.org/10.5194/amt-16-1239-2023, https://doi.org/10.5194/amt-16-1239-2023, 2023
Short summary
Short summary
Ground-based remote sensing instruments in the Total Carbon Column Observing Network (TCCON) measure greenhouse gases in the atmosphere. Consistency between TCCON measurements is crucial to accurately infer changes in atmospheric composition. We use portable remote sensing instruments (EM27/SUN) to evaluate biases between TCCON stations in North America. We also improve the retrievals of EM27/SUN instruments and evaluate the previous (GGG2014) and newest (GGG2020) retrieval algorithms.
Cited articles
Alvarado, L. M. A., Richter, A., Vrekoussis, M., Wittrock, F., Hilboll, A., Schreier, S. F., and Burrows, J. P.: An improved glyoxal retrieval from OMI measurements, Atmos. Meas. Tech., 7, 4133–4150, https://doi.org/10.5194/amt-7-4133-2014, 2014. a
Anand, J. S., Monks, P. S., and Leigh, R. J.: An improved retrieval of tropospheric NO2 from space over polluted regions using an Earth radiance reference, Atmos. Meas. Tech., 8, 1519–1535, https://doi.org/10.5194/amt-8-1519-2015, 2015. a
Boersma, K. F., Eskes, H. J., Veefkind, J. P., Brinksma, E. J., van der A, R. J., Sneep, M., van den Oord, G. H. J., Levelt, P. F., Stammes, P., Gleason, J. F., and Bucsela, E. J.: Near-real time retrieval of tropospheric NO2 from OMI, Atmos. Chem. Phys., 7, 2103–2118, https://doi.org/10.5194/acp-7-2103-2007, 2007. a
Boersma, K. F., Eskes, H. J., Dirksen, R. J., van der A, R. J., Veefkind, J. P., Stammes, P., Huijnen, V., Kleipool, Q. L., Sneep, M., Claas, J., Leitão, J., Richter, A., Zhou, Y., and Brunner, D.: An improved tropospheric NO2 column retrieval algorithm for the Ozone Monitoring Instrument, Atmos. Meas. Tech., 4, 1905–1928, https://doi.org/10.5194/amt-4-1905-2011, 2011. a, b
Boersma, K. F., Eskes, H., Richter, A., Smedt, I. D., Lorente, A., Beirle, S.,
van Geffen, J., Peters, E., Roozendael, M. V., and Wagner, T.: QA4ECV NO2
tropospheric and stratospheric column data from OMI [Dataset],
https://doi.org/10.21944/qa4ecv-no2-omi-v1.1, 2017. a
Boersma, K. F., Eskes, H. J., Richter, A., De Smedt, I., Lorente, A., Beirle, S., van Geffen, J. H. G. M., Zara, M., Peters, E., Van Roozendael, M., Wagner, T., Maasakkers, J. D., van der A, R. J., Nightingale, J., De Rudder, A., Irie, H., Pinardi, G., Lambert, J.-C., and Compernolle, S. C.: Improving algorithms and uncertainty estimates for satellite NO2 retrievals: results from the quality assurance for the essential climate variables (QA4ECV) project, Atmos. Meas. Tech., 11, 6651–6678, https://doi.org/10.5194/amt-11-6651-2018, 2018. a, b, c, d, e
Bovensmann, H., Burrows, J. P., Buchwitz, M., Frerick, J., Noël, S., Rozanov,
V. V., Chance, K. V., and Goede, A. P. H.: 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, b
Bucsela, E., Celarier, E., Wenig, M., Gleason, J., Veefkind, J., Boersma, K.,
and Brinksma, E.: Algorithm for NO2 vertical column retrieval from the
ozone monitoring instrument, IEEE T. Geosci. Remote, 44, 1245, https://doi.org/10.1109/TGRS.2005.863715, 2006. a, b
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
Castellanos, P. and Boersma, K. F.: Reductions in nitrogen oxides over Europe
driven by environmental policy and economic recession, Sci. Rep., 2,
265, https://doi.org/10.1038/srep00265, 2012. a
Cede, A., Herman, J., Richter, A., Krotkov, N., and Burrows, J.: Measurements
of nitrogen dioxide total column amounts using a Brewer double
spectrophotometer in direct Sun mode, J. Geophys. Res.-Atmos., 111, D05304, https://doi.org/10.1029/2005JD006585, 2006. a
Chance, K. V. and Spurr, R. J.: Ring effect studies: Rayleigh scattering,
including molecular parameters for rotational Raman scattering, and the
Fraunhofer spectrum, Appl. Optics, 36, 5224, https://doi.org/10.1364/AO.36.005224, 1997. a
DEFRA: Air Pollution in the UK 2017 – Compliance Assessment Summary, Tech.
rep., Department for Environment, Food & Rural Affairs, available at: https://uk-air.defra.gov.uk/library/annualreport/assets/documents/annualreport/air_pollution_uk_2017_Compliance_Assessment_Summary_Issue1.pdf (last access: 2 April 2020),
2018. a
Dekemper, E., Vanhamel, J., Van Opstal, B., and Fussen, D.: The AOTF-based NO2 camera, Atmos. Meas. Tech., 9, 6025–6034, https://doi.org/10.5194/amt-9-6025-2016, 2016. a
Dobber, M., Kleipool, Q., Dirksen, R., Levelt, P., Jaross, G., Taylor, S.,
Kelly, T., Flynn, L., Leppelmeier, G., and Rozemeijer, N.: Validation of
Ozone Monitoring Instrument level 1b data products, J. Geophys. Res.-Atmos., 113, D15S06, https://doi.org/10.1029/2007JD008665, 2008. a
Dunlea, E. J., Herndon, S. C., Nelson, D. D., Volkamer, R. M., San Martini, F., Sheehy, P. M., Zahniser, M. S., Shorter, J. H., Wormhoudt, J. C., Lamb, B. K., Allwine, E. J., Gaffney, J. S., Marley, N. A., Grutter, M., Marquez, C., Blanco, S., Cardenas, B., Retama, A., Ramos Villegas, C. R., Kolb, C. E., Molina, L. T., and Molina, M. J.: Evaluation of nitrogen dioxide chemiluminescence monitors in a polluted urban environment, Atmos. Chem. Phys., 7, 2691–2704, https://doi.org/10.5194/acp-7-2691-2007, 2007. a
EEA: Air quality in Europe – 2018 Report, Tech. rep., European Enviroment
Agency, available at: https://www.eea.europa.eu/publications/air-quality-in-europe-2018 (last access: 2 April 2020),
2018. a
EPA: Technical assistance document for the chemiluminescence measurement of
nitrogen dioxide, Tech. rep., United States Environmental Protection Agency, available at: https://www3.epa.gov/ttnamti1/archive/files/ambient/criteria/reldocs/4-75-003.pdf (last access: 2 April 2020), ePA-600/4-75-003, 1975. a
European Space Agency (ESA): Sentinel-5P Pre-Operations Data Hub, available at: https://s5phub.copernicus.eu/dhus/#/home, last access: 2 April 2020. a
Hains, J. C., Boersma, K. F., Kroon, M., Dirksen, R. J., Cohen, R. C., Perring,
A. E., Bucsela, E. J., Volten, H., Swart, D., Richter, A., Wittrock, F.,
Schönhardt, A., Wagner, T., Ibrahim, O. W., van Roozendael, M., Pinardi, G., Gleason,
J. F., Veefkind, J. P., and Levelt, P. P.: Testing and improving OMI DOMINO
tropospheric NO2 using observations from the DANDELIONS and INTEX-B
validation campaigns, J. Geophys. Res.-Atmos., 115,
D05301, https://doi.org/10.1029/2009JD012399, 2010. a
Heath, D. F., Krueger, A. J., Roeder, H. A., and Henderson, B. D.: The Solar
Backscatter Ultraviolet and Total Ozone Mapping Spectrometer (SBUV/TOMS) for
NIMBUS G, Opt. Eng., 14, 323–331, https://doi.org/10.1117/12.7971839, 1975. a
Hilboll, A., Richter, A., and Burrows, J. P.: NO2 pollution over India observed from space – the impact of rapid economic growth, and a recent decline, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-101, in review, 2017. a
Huang, T., Zhu, X., Zhong, Q., Yun, X., Meng, W., Li, B., Ma, J., Zeng, E. Y.,
and Tao, S.: Spatial and Temporal Trends in Global Emissions of Nitrogen
Oxides from 1960 to 2014, Environ. Sci. Technol., 51,
7992–8000, https://doi.org/10.1021/acs.est.7b02235, 2017. a
Ingmann, P., Veihelmann, B., Langen, J., Lamarre, D., Stark, H., and
Courrèges-Lacoste, G. B.: Requirements for the GMES Atmosphere Service and
ESA's implementation concept: Sentinels-4/-5 and -5p, Remote Sens. Environ., 120, 58–69, https://doi.org/10.1016/j.rse.2012.01.023,
2012. a
KNMI: Tropospheric Emission Monitoring
Internet Service – Regional Tropospheric NO2 columns from OMI, available at: http://temis.nl/airpollution/no2col/no2regioomi_qa.php, last access: 2 April 2020a. a
KNMI: Tropospheric Emission Monitoring
Internet Service – Regional Tropospheric NO2 columns from TROPOMI, available at: http://temis.nl/airpollution/no2col/no2regio_tropomi.php, last access: 2 April 2020b. a
Krijger, J. M., van Weele, M., Aben, I., and Frey, R.: Technical Note: The effect of sensor resolution on the number of cloud-free observations from space, Atmos. Chem. Phys., 7, 2881–2891, https://doi.org/10.5194/acp-7-2881-2007, 2007. a
Krotkov, N. A., Lamsal, L. N., Celarier, E. A., Swartz, W. H., Marchenko, S. V., Bucsela, E. J., Chan, K. L., Wenig, M., and Zara, M.: The version 3 OMI NO2 standard product, Atmos. Meas. Tech., 10, 3133–3149, https://doi.org/10.5194/amt-10-3133-2017, 2017. a
Levelt, P. F., van den Oord, G. H. J., Dobber, M. R., Malkki, A., Visser, H.,
de Vries, J., Stammes, P., Lundell, J. O. V., and Saari, H.: The ozone
monitoring instrument, IEEE T. Geosci. Remote,
44, 1093–1101, https://doi.org/10.1109/TGRS.2006.872333, 2006. a, b
Levelt, P. F., Joiner, J., Tamminen, J., Veefkind, J. P., Bhartia, P. K., Stein Zweers, D. C., Duncan, B. N., Streets, D. G., Eskes, H., van der A, R., McLinden, C., Fioletov, V., Carn, S., de Laat, J., DeLand, M., Marchenko, S., McPeters, R., Ziemke, J., Fu, D., Liu, X., Pickering, K., Apituley, A., González Abad, G., Arola, A., Boersma, F., Chan Miller, C., Chance, K., de Graaf, M., Hakkarainen, J., Hassinen, S., Ialongo, I., Kleipool, Q., Krotkov, N., Li, C., Lamsal, L., Newman, P., Nowlan, C., Suleiman, R., Tilstra, L. G., Torres, O., Wang, H., and Wargan, K.: The Ozone Monitoring Instrument: overview of 14 years in space, Atmos. Chem. Phys., 18, 5699–5745, https://doi.org/10.5194/acp-18-5699-2018, 2018. a
Levy, I., Mihele, C., Lu, G., Narayan, J., and Brook, J. R.: Evaluating
Multipollutant Exposure and Urban Air Quality: Pollutant Interrelationships,
Neighborhood Variability, and Nitrogen Dioxide as a Proxy Pollutant,
Environ. Health Persp., 122, 65–72, https://doi.org/10.1289/ehp.1306518,
2013. a
Met Office: Cartopy: a cartographic python library with a Matplotlib
interface, Exeter, Devon, available at: http://scitools.org.uk/cartopy (last access: 2 April 2020), 2010–2015. a
Monks, P. S., Granier, C., Fuzzi, S., Stohl, A., Williams, M. L., Akimoto, H.,
Amann, M., Baklanov, A., Baltensperger, U., Bey, I., Blake, N., Blake, R. S.,
Carslaw, K., Cooper, O. R., Dentener, F., Fowler, D., Fragkou, E., Frost,
G. J., Generoso, S., Ginoux, P., Grewe, V., Guenther, A., Hansson, H. C.,
Henne, S., Hjorth, J., Hofzumahaus, A., Huntrieser, H., Isaksen, I. S. A.,
Jenkin, M. E., Kaiser, J., Kanakidou, M., Klimont, Z., Kulmala, M., Laj, P.,
Lawrence, M. G., Lee, J. D., Liousse, C., Maione, M., McFiggans, G., Metzger,
A., Mieville, A., Moussiopoulos, N., Orlando, J. J., O'Dowd, C. D., Palmer,
P. I., Parrish, D. D., Petzold, A., Platt, U., Pöschl, U., Prévôt, A.
S. H., Reeves, C. E., Reimann, S., Rudich, Y., Sellegri, K., Steinbrecher,
R., Simpson, D., ten Brink, H., Theloke, J., van der Werf, G. R., Vautard,
R., Vestreng, V., Vlachokostas, C., and von Glasow, R.: Atmospheric
composition change – global and regional air quality, Atmos. Environ., 43, 5268–5350, https://doi.org/10.1016/j.atmosenv.2009.08.021, 2009. a
Mount, G. H., Rusch, D. W., Noxon, J. F., Zawodny, J. M., and Barth, C. A.:
Measurements of stratospheric NO2 from the Solar Mesosphere Explorer
satellite: 1. An overview of the results, J. Geophys. Res.-Atmos., 89, 1327–1340, http://ntrs.nasa.gov/search.jsp?R=19840040377 (last access: 2 April 2020), 1984. a
Munro, R., Anderson, C., Callies, J., Corpaccioli, E., Eisinger, M., Lang, R.,
Lefebvre, A., Livschitz, Y., and Albiñana, A. P.: GOME-2 on MetOp, The 2006 EUMETSAT Meteorological Satellite Conference, Helsinki, Finland, available at: https://www.eumetsat.int/website/wcm/idc/idcplg?IdcService=GET_FILE&dDocName=PDF_CONF_P48_S4_01_MUNRO_V&RevisionSelectionMethod=LatestReleased&Rendition=Web (last access: 2 April 2020), 2006. a, b
National Aeronautics and Space Administration (NASA): Goddard Earth Sciences Data and Information Services Center – OMI Data, available at: https://disc.gsfc.nasa.gov/datasets?page=1&source=AURA%20OMI, last access: 2 April 2020. a
Oldeman, A.: Effect of including an intensity offset in the DOAS NO2 retrieval
of TROPOMI, Tech. rep., Eindhoven University of Technology/KNMI, Eindhoven,
available at: https://kfolkertboersma.files.wordpress.com/2018/06/report_oldeman_22052018.pdf (last access: 2 April 2020), internship report, R1944-SE, 2018. a, b
Palmer, P. I., Jacob, D. J., Chance, K., Martin, R. V., Spurr, R. J. D.,
Kurosu, T. P., Bey, I., Yantosca, R., Fiore, A., and Li, Q.: Air mass factor
formulation for spectroscopic measurements from satellites: Application to
formaldehyde retrievals from the Global Ozone Monitoring Experiment, J. Geophys. Res.-Atmos., 106, 14539–14550,
https://doi.org/10.1029/2000JD900772, 2001. a, b
Richter, A., Burrows, J. P., Nuss, H., Granier, C., and Niemeier, U.: Increase
in tropospheric nitrogen dioxide over China observed from space, Nature, 437,
129–132, https://doi.org/10.1038/nature04092, 2005. a
Richter, A., Begoin, M., Hilboll, A., and Burrows, J. P.: An improved NO2 retrieval for the GOME-2 satellite instrument, Atmos. Meas. Tech., 4, 1147–1159, https://doi.org/10.5194/amt-4-1147-2011, 2011. a, b
Russell, A. R., Valin, L. C., and Cohen, R. C.: Trends in OMI NO2 observations over the United States: effects of emission control technology and the economic recession, Atmos. Chem. Phys., 12, 12197–12209, https://doi.org/10.5194/acp-12-12197-2012, 2012. a
van Geffen, J. H. G. M., Boersma, K. F., Van Roozendael, M., Hendrick, F., Mahieu, E., De Smedt, I., Sneep, M., and Veefkind, J. P.: Improved spectral fitting of nitrogen dioxide from OMI in the 405–465 nm window, Atmos. Meas. Tech., 8, 1685–1699, https://doi.org/10.5194/amt-8-1685-2015, 2015. a, b, c, d, e
van Geffen, J. H. G. M., Eskes, H. J., Boersma, K. F., Maasakkers, J. D., and
Veefkind, J. P.: TROPOMI ATBD of the total and tropospheric NO2 data
products, Tech. rep., Koninklijk Nederlands Meteorologisch Instituut, De Bilt, the Netherlands, s5PKNMIL20005RP, available at: http://www.tropomi.eu/sites/default/files/files/publicS5P-KNMI-L2-0005-RP-ATBD_NO2_data_products-20190206_v140.pdf (last access: 2 April 2020), 2019. a, b, c
van Geffen, J., Boersma, K. F., Eskes, H., Sneep, M., ter Linden, M., Zara, M., and Veefkind, J. P.: S5P TROPOMI NO2 slant column retrieval: method, stability, uncertainties and comparisons with OMI, Atmos. Meas. Tech., 13, 1315–1335, https://doi.org/10.5194/amt-13-1315-2020, 2020. a
Vandaele, A. C., Fayt, C., Hendrick, F., Hermans, C., Humbled, F., Roozendael,
M. V., Gil, M., Navarro, M., Puentedura, O., Yela, M., Braathen, G., Stebel,
K., Tørnkvist, K., Johnston, P., Kreher, K., Goutail, F., Mieville, A.,
Pommereau, J.-P., Khaikine, S., Richter, A., Oetjen, H., Wittrock, F.,
Bugarski, S., Frieß, U., Pfeilsticker, K., Sinreich, R., Wagner, T.,
Corlett, G., and Leigh, R.: An intercomparison campaign of ground-based
UV-visible measurements of NO2, BrO, and OClO slant columns: Methods of
analysis and results for NO2, J. Geophsy. Res.-Atmos., 110, D08305, https://doi.org/10.1029/2004JD005423, 2005. a
Veefkind, J. P., Aben, I., McMullan, K., Förster, H., de Vries, J., Otter, G.,
Claas, J., Eskes, H. J., de Haan, J. F., Kleipool, Q., van Weele, M.,
Hasekamp, O., Hoogeveen, R., Landgraf, J., Snel, R., Tol, P., Ingmann, P.,
Voors, R., Kruizinga, B., Vink, R., Visser, H., and Levelt, P. F.: TROPOMI on
the ESA Sentinel-5 Precursor: A GMES mission for global observations of the
atmospheric composition for climate, air quality and ozone layer
applications, Remote Sens. Environ., 120, 70–83,
https://doi.org/10.1016/j.rse.2011.09.027, 2012. a, b, c
Veefkind, J. P., de Haan, J. F., Sneep, M., and Levelt, P. F.: Improvements to the OMI O2−O2 operational cloud algorithm and comparisons with ground-based radar–lidar observations, Atmos. Meas. Tech., 9, 6035–6049, https://doi.org/10.5194/amt-9-6035-2016, 2016. a, b
Wallace, J. M. and Hobbs, P. V.: Atmospheric science, vol. 92, 2nd edn., Elsevier Acad.
Press, Amsterdam, 2006. a
Wenig, M. O., Cede, A. M., Bucsela, E. J., Celarier, E. A., Boersma, K. F.,
Veefkind, J. P., Brinksma, E. J., Gleason, J. F., and Herman, J. R.:
Validation of OMI tropospheric NO2 column densities using direct-Sun mode
Brewer measurements at NASA Goddard Space Flight Center, J. Geophys. Res.-Atmos., 113, D16S45, https://doi.org/10.1029/2007JD008988,
2008. a
WHO: Air quality guidelines global update 2005: particulate matter, ozone,
nitrogen dioxide, and sulfur dioxide, includes bibliographical references, Ebrary eBook, World Health Organization, Copenhagen, Denmark, 2006. a
WHO Regional Office for Europe: Review of evidence on health aspects of air
pollution – REVIHAAP Project, Tech. rep., WHO Regional Office for Europe,
available at: http://www.euro.who.int/__data/assets/pdf_file/0004/193108/REVIHAAP-Final-technical-report.pdf (2 April 2020),
2013. a
WMO: World Meteorological Organization: Systematic Observation Requirements for
Satellite-Based Data Products for Climate – 2011 Update, Tech. rep., World
Meteorological Organization,
available at: https://library.wmo.int/doc_num.php?explnum_id=3710 (2 April 2020), 2011. a
Zara, M., Boersma, K. F., De Smedt, I., Richter, A., Peters, E., van Geffen, J. H. G. M., Beirle, S., Wagner, T., Van Roozendael, M., Marchenko, S., Lamsal, L. N., and Eskes, H. J.: Improved slant column density retrieval of nitrogen dioxide and formaldehyde for OMI and GOME-2A from QA4ECV: intercomparison, uncertainty characterisation, and trends, Atmos. Meas. Tech., 11, 4033–4058, https://doi.org/10.5194/amt-11-4033-2018, 2018. a, b, c
Short summary
We present a new method to derive NO2 concentrations from satellite observations that uses up to 30 times less spectral information than traditional methods. We tested the method using data from existing instruments OMI and TROPOMI and found our results agree with the reference data to 5 % and 11 %, respectively. Our method could allow for simpler instrument designs that can be used in low-cost constellations of small satellites for air quality monitoring at high spatial and temporal resolution.
We present a new method to derive NO2 concentrations from satellite observations that uses up to...
