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2. Aura Ozone Monitoring Instrument (OMI) Collection 4 Formaldehyde Product

Author

Ayazpour, Zolal, primary, Abad, Gonzalo González, additional, Nowlan, Caroline R., additional, Sun, Kang, additional, Kwon, Hyeong-Ahn, additional, Miller, Christopher Chan, additional, Chong, Heesung, additional, Wang, Huiqun, additional, Liu, Xiong, additional, Chance, Kelly V., additional, O'Sullivan, Ewan, additional, Zhu, Lei, additional, Vigouroux, Corinne, additional, Smedt, Isabelle De, additional, Stremme, Wolfgang, additional, Hannigan, James W, additional, Notholt, Justus, additional, Sun, Xiaoyu, additional, Palm, Mathias, additional, Petri, Christof, additional, Strong, Kimberly, additional, Röhling, Amelie Ninja, additional, Mahieu, Emmanuel, additional, Smale, Dan, additional, Té, Yao, additional, Morino, Isamu, additional, Murata, Isao, additional, Nagahama, Tomoo, additional, Kivi, Rigel, additional, Makarova, Maria, additional, Jones, Nicholas Brian, additional, and Sussmann, Ralf, additional

Published
2024
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3. The Post-2020 Surge in Global Atmospheric Methane Observed in Ground-based Observations

Author

Wu, Jennifer, primary, Luo, Sherry, additional, Zeng, Zhao-Cheng, additional, Turner, Alex, additional, Wunch, Debra, additional, García, Omaira, additional, Hase, Frank, additional, Kivi, Rigel, additional, Ohyama, Hirofumi, additional, Morino, Isamu, additional, Sussmann, Ralf, additional, Rettinger, Markus, additional, Té, Yao, additional, Deutscher, Nicholas Michael, additional, Griffith, David W.T, additional, Shiomi, Kei, additional, Liu, Cheng, additional, Notholt, Justus, additional, Iraci, Laura T, additional, Pollard, David Frank, additional, Warneke, Thorsten, additional, Roehl, Coleen Marie, additional, Pongetti, Thomas J, additional, Sander, Stanley, additional, and Yung, Yuk L., additional

Published
2024
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12. Emission Characteristics of Greenhouse Gases and Air Pollutants in Northern Hemisphere Cities: Comprehensive Assessment Using Ground‐Based Fourier Transform Spectrometers.

Author

Lee, Jonghyuk, Jeong, Sujong, Park, Hayoung, Hong, Jaemin, Kim, Jueun, Frey, Matthias Max, Morino, Isamu, Ohyama, Hirofumi, Hase, Frank, Mermigkas, Marios, Zhou, Minqiang, Té, Yao, and Roehl, Coleen M.

Subjects
GREENHOUSE gases, FOURIER transform spectrometers, CITIES & towns, EMISSIONS (Air pollution), AIR pollutants, CLIMATE change mitigation
Abstract

Despite the importance of understanding the urban emission characteristics of greenhouse gases (GHGs) and air pollutants, few studies have conducted integrated assessments across diverse urban environments. Herein, we conducted a comprehensive evaluation of the emission characteristics of GHGs and air pollutants in seven cities in the Northern Hemisphere using ground‐based Fourier transform spectrometers. Our analysis primarily focused on emission ratios of excess column‐averaged dry‐air mole fractions of carbon monoxide (CO) to carbon dioxide (CO2) (∆XCO:∆XCO2) and those of methane (CH4) to CO2 (∆XCH4:∆XCO2). We found that the emission ratios varied significantly across cities. Xianghe (China) and Pasadena (USA), known for severe air pollution, showed the highest emission ratios. Notably, Seoul (South Korea) showed lower ∆XCO:∆XCO2 (3.32 ± 0.10 ppb/ppm) but relatively higher ∆XCH4:∆XCO2 (4.85 ± 0.04 ppb/ppm), which was comparable to the ∆XCH4:∆XCO2 value of Xianghe (5.15 ± 0.10 ppb/ppm), suggesting that targeted CH4 reduction strategies may be required for climate change mitigation in Seoul. Plain Language Summary: Many cities experience significant greenhouse gas and air pollutant emissions. We comprehensively analyzed the characteristics of these emissions using ground‐based solar‐viewing Fourier transform spectrometers (FTSs) in Northern Hemisphere cities including Seoul (South Korea), Thessaloniki (Greece), Tsukuba (Japan), Karlsruhe (Germany), Xianghe (China), Pasadena (USA), and Paris (France). First, we focused on variations in carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO). Based on these variations, their emission ratios were estimated in terms of excess column‐averaged dry‐air mole fractions of CO to CO2 (∆XCO:∆XCO2) and CH4 to CO2 (∆XCH4:∆XCO2) in urban sites. We found that the emission ratios differed across cities. For example, Xianghe and Pasadena, which generally exhibit high levels of air pollution, had the highest emission ratios. However, Seoul had lower emission ratios of ∆XCO:∆XCO2, but higher levels of ∆XCH4:∆XCO2. This study suggests that ground‐based Fourier transform spectrometer measurements can be used as a tool for comprehensively evaluating the emission characteristics of greenhouse gases and air pollutants in urban environments. Furthermore, extending our study to longer periods and more sites could further aid in formulating effective mitigation strategies for climate change. Key Points: We comprehensively assessed the emission characteristics of greenhouse gases and air pollutants in seven cities in the Northern HemisphereGround‐based Fourier transform spectrometers offers a comprehensive analysis of the urban emission characteristics of greenhouse gases and air pollutantsOur results can further support effective strategies for mitigating climate change [ABSTRACT FROM AUTHOR]

Published
2024
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13. Weekly derived top-down volatile-organic-compound fluxes over Europe from TROPOMI HCHO data from 2018 to 2021.

Author

Oomen, Glenn-Michael, Müller, Jean-François, Stavrakou, Trissevgeni, De Smedt, Isabelle, Blumenstock, Thomas, Kivi, Rigel, Makarova, Maria, Palm, Mathias, Röhling, Amelie, Té, Yao, Vigouroux, Corinne, Friedrich, Martina M., Frieß, Udo, Hendrick, François, Merlaud, Alexis, Piters, Ankie, Richter, Andreas, Van Roozendael, Michel, and Wagner, Thomas

Subjects
SEMIVOLATILE organic compounds, TROPOSPHERIC ozone, BIOMASS burning, VOLATILE organic compounds, CLOUDINESS, CHEMICAL models, REMOTE sensing
Abstract

Volatile organic compounds (VOCs) are key precursors of particulate matter and tropospheric ozone. Although the terrestrial biosphere is by far the largest source of VOCs into the atmosphere, the emissions of biogenic VOCs remain poorly constrained at the regional scale. In this work, we derive top-down biogenic emissions over Europe using weekly averaged TROPOMI formaldehyde (HCHO) data from 2018 to 2021. The systematic bias of the TROPOMI HCHO columns is characterized and corrected for based on comparisons with FTIR data at seven European stations. The top-down fluxes of biogenic, pyrogenic, and anthropogenic VOC sources are optimized using an inversion framework based on the MAGRITTEv1.1 chemistry transport model and its adjoint. The inversion leads to strongly increased isoprene emissions with respect to the MEGAN–MOHYCAN inventory over the model domain (from 8.1 to 18.5 Tgyr-1), which is driven by the high observed TROPOMI HCHO columns in southern Europe. The impact of the inversion on biomass burning VOCs (+ 13 %) and anthropogenic VOCs (- 17 %) is moderate. An evaluation of the optimized HCHO distribution against ground-based remote sensing (FTIR and MAX-DOAS) and in situ data provides generally improved agreement at stations below about 50 ∘ N but indicates overestimated emissions in northern Scandinavia. Sensitivity inversions show that the top-down emissions are robust with respect to changes in the inversion settings and in the model chemical mechanism, leading to differences of up to 10 % in the total emissions. However, the top-down emissions are very sensitive to the bias correction of the observed columns, as the biogenic emissions are 3 times lower when the correction is not applied. Furthermore, the use of different a priori biogenic emissions has a significant impact on the inversion results due to large differences among bottom-up inventories. The sensitivity run using CAMS-GLOB-BIOv3.1 as a priori emissions in the inversion results in 30 % lower emissions with respect to the optimization using MEGAN–MOHYCAN. In regions with large temperature and cloud cover variations, there is strong week-to-week variability in the observed HCHO columns. The top-down emissions, which are optimized at weekly increments, have a much improved capability of representing these large fluctuations than an inversion using monthly increments. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Weekly-derived top-down VOC fluxes over Europe from TROPOMI HCHO data in 2018–2021

Author

Oomen, Glenn-Michael, primary, Müller, Jean-François, additional, Stavrakou, Trissevgeni, additional, De Smedt, Isabelle, additional, Blumenstock, Thomas, additional, Kivi, Rigel, additional, Makarova, Maria, additional, Palm, Mathias, additional, Röhling, Amelie, additional, Té, Yao, additional, Vigouroux, Corinne, additional, Friedrich, Martina M., additional, Frieß, Udo, additional, Hendrick, François, additional, Merlaud, Alexis, additional, Piters, Ankie, additional, Richter, Andreas, additional, Van Roozendael, Michel, additional, and Wagner, Thomas, additional

Published
2023
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15. Supplementary material to "Weekly-derived top-down VOC fluxes over Europe from TROPOMI HCHO data in 2018–2021"

Author

Oomen, Glenn-Michael, primary, Müller, Jean-François, additional, Stavrakou, Trissevgeni, additional, De Smedt, Isabelle, additional, Blumenstock, Thomas, additional, Kivi, Rigel, additional, Makarova, Maria, additional, Palm, Mathias, additional, Röhling, Amelie, additional, Té, Yao, additional, Vigouroux, Corinne, additional, Friedrich, Martina M., additional, Frieß, Udo, additional, Hendrick, François, additional, Merlaud, Alexis, additional, Piters, Ankie, additional, Richter, Andreas, additional, Van Roozendael, Michel, additional, and Wagner, Thomas, additional

Published
2023
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16. The Total Carbon Column Observing Network's GGG2020 Data Version

Author

Laughner, Joshua L., primary, Toon, Geoffrey C., additional, Mendonca, Joseph, additional, Petri, Christof, additional, Roche, Sébastien, additional, Wunch, Debra, additional, Blavier, Jean-Francois, additional, Griffith, David W. T., additional, Heikkinen, Pauli, additional, Keeling, Ralph F., additional, Kiel, Matthäus, additional, Kivi, Rigel, additional, Roehl, Coleen M., additional, Stephens, Britton B., additional, Baier, Bianca C., additional, Chen, Huilin, additional, Choi, Yonghoon, additional, Deutscher, Nicholas M., additional, DiGangi, Joshua P., additional, Gross, Jochen, additional, Herkommer, Benedikt, additional, Jeseck, Pascal, additional, Laemmel, Thomas, additional, Lan, Xin, additional, McGee, Erin, additional, McKain, Kathryn, additional, Miller, John, additional, Morino, Isamu, additional, Notholt, Justus, additional, Ohyama, Hirofumi, additional, Pollard, David F., additional, Rettinger, Markus, additional, Riris, Haris, additional, Rousogenous, Constantina, additional, Sha, Mahesh Kumar, additional, Shiomi, Kei, additional, Strong, Kimberly, additional, Sussmann, Ralf, additional, Té, Yao, additional, Velazco, Voltaire A., additional, Wofsy, Steven C., additional, Zhou, Minqiang, additional, and Wennberg, Paul O., additional

Published
2023
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18. A new method for estimating emission ratios in the urban atmosphere: examples of ratios to CO2, CO and volatile organic compounds in Paris

Author

Ammoura, Lamia, Xueref-Remy, Irène, Vogel, Felix, Gros, V., Baudic, Alexia, Bonsang, Bernard, Delmotte, Marc, Té, Yao-Veng, Chevallier, Frédéric, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres (LERMA), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-CY Cergy Paris Université (CY), ANR-09-BLAN-0356,MEGAPOLI-PARIS,MEGAPOLI - PARIS : Pollution des AéRosols: Impact sur la qualité de l'air et quantification des Sources(2009), and ANR-09-BLAN-0222,CO2-MEGAPARIS,Quantification des émissions de CO2 en Ile-de-France(2009)

Subjects
[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]
Abstract

International audience; We propose a new approach to estimate urban emission ratios that takes advantage of the enhanced local urban signal in the atmosphere at low wind speed. We apply it to estimate monthly ratios between CO$_2$, CO and some VOCs from several atmospheric concentration measurement datasets acquired in the centre of Paris between 2010 and 2014. We find that this approach is little sensitive to the regional background level definition and that, in the case of Paris, it samples all days (weekdays and weekends) and all hours of the day evenly. A large seasonal variability of the $\Delta$CO/$\Delta$CO$_ 2$ratio in Paris is shown, with a difference of around 60 % between the extreme values and a strong anti-correlation ($r^2$ = 0.75) with atmospheric temperature. The comparison of the ratios obtained for two short measurement campaigns conducted in two different districts and two different periods (fall and winter) shows differences ranging from -120 to 63 %. A comparison with a highly resolved regional emission inventory suggests some spatial variations of the ratio within the city, although most of these differences seem to be rather driven by the seasonal variability.

Published
2023

19. Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm

Author

Noël, Stefan, Reuter, Maximilian, Buchwitz, Michael, Borchardt, Jakob, Hilker, Michael, Schneising, Oliver, Bovensmann, Heinrich, Burrows, John P., Di Noia, Antonio, Parker, Robert J., Suto, Hiroshi, Yoshida, Yukio, Buschmann, Matthias, Deutscher, Nicholas M., Feist, Dietrich G., Griffith, David W. T., Hase, Frank, Kivi, Rigel, Liu, Cheng, Morino, Isamu, Notholt, Justus, Oh, Young-Suk, Ohyama, Hirofumi, Petri, Christof, Pollard, David F., Rettinger, Markus, Roehl, Coleen M., Rousogenous, Constantina, Sha, Mahesh K., Shiomi, Kei, Strong, Kimberly, Sussmann, Ralf, Té, Yao, Velazco, Voltaire A., Vrekoussis, Mihalis, and Warneke, Thorsten

Subjects
remote sensing, GOSAT-2, FOCAL, Earth sciences, Atmospheric Science, CH4, Satellite, TCCON, ddc:550, CO2, retrieval, GOSAT
Abstract

We show new results from an updated version of the Fast atmOspheric traCe gAs retrievaL (FOCAL) retrieval method applied to measurements of the Greenhouse gases Observing SATellite (GOSAT) and its successor GOSAT-2. FOCAL was originally developed for estimating the total column carbon dioxide mixing ratio (XCO2) from spectral measurements made by the Orbiting Carbon Observatory-2 (OCO-2). However, depending on the available spectral windows, FOCAL also successfully retrieves total column amounts for other atmospheric species and their uncertainties within one single retrieval. The main focus of the current paper is on methane (XCH4; full-physics and proxy product), water vapour (XH2O) and the relative ratio of semi-heavy water (HDO) to water vapour (δD). Due to the extended spectral range of GOSAT-2, it is also possible to derive information on carbon monoxide (XCO) and nitrous oxide (XN2O) for which we also show first results. We also present an update on XCO2 from both instruments. For XCO2, the new FOCAL retrieval (v3.0) significantly increases the number of valid data compared with the previous FOCAL retrieval version (v1) by 50 % for GOSAT and about a factor of 2 for GOSAT-2 due to relaxed pre-screening and improved post-processing. All v3.0 FOCAL data products show reasonable spatial distribution and temporal variations. Comparisons with the Total Carbon Column Observing Network (TCCON) result in station-to-station biases which are generally in line with the reported TCCON uncertainties. With this updated version of the GOSAT-2 FOCAL data, we provide a first total column average XN2O product. Global XN2O maps show a gradient from the tropics to higher latitudes on the order of 15 ppb, which can be explained by variations in tropopause height. The new GOSAT-2 XN2O product compares well with TCCON. Its station-to-station variability is lower than 2 ppb, which is about the magnitude of the typical N2O variations close to the surface. However, both GOSAT-2 and TCCON measurements show that the seasonal variations in the total column average XN2O are on the order of 8 ppb peak-to-peak, which can be easily resolved by the GOSAT-2 FOCAL data. Noting that only few XN2O measurements from satellites exist so far, the GOSAT-2 FOCAL product will be a valuable contribution in this context.

Published
2023

20. Characteristics of interannual variability in space-based XCO₂ global observations

Author

Guan, Yifan, Keppel-Aleks, Gretchen, Doney, Scott C., Petri, Christof, Pollard, Dave, Wunch, Debra, Hase, Frank, Ohyama, Hirofumi, Morino, Isamu, Notholt, Justus, Shiomi, Kei, Strong, Kim, Kivi, Rigel, Buschmann, Matthias, Deutscher, Nicholas, Wennberg, Paul, Sussmann, Ralf, Velazco, Voltaire A., and Té, Yao

Abstract

Atmospheric carbon dioxide (CO₂) accounts for the largest radiative forcing among anthropogenic greenhouse gases. There is, therefore, a pressing need to understand the rate at which CO₂ accumulates in the atmosphere, including the interannual variations (IAVs) in this rate. IAV in the CO₂ growth rate is a small signal relative to the long-term trend and the mean annual cycle of atmospheric CO₂, and IAV is tied to climatic variations that may provide insights into long-term carbon–climate feedbacks. Observations from the Orbiting Carbon Observatory-2 (OCO-2) mission offer a new opportunity to refine our understanding of atmospheric CO₂ IAV since the satellite can measure over remote terrestrial regions and the open ocean, where traditional in situ CO₂ monitoring is difficult, providing better spatial coverage compared to ground-based monitoring techniques. In this study, we analyze the IAV of column-averaged dry-air CO₂ mole fraction (XCO₂) from OCO-2 between September 2014 and June 2021. The amplitude of the IAV, which is calculated as the standard deviation of the time series, is up to 1.2 ppm over the continents and around 0.4 ppm over the open ocean. Across all latitudes, the OCO-2-detected XCO₂ IAV shows a clear relationship with El Niño–Southern Oscillation (ENSO)-driven variations that originate in the tropics and are transported poleward. Similar, but smoother, zonal patterns of OCO-2 XCO₂ IAV time series compared to ground-based in situ observations and with column observations from the Total Carbon Column Observing Network (TCCON) and the Greenhouse Gases Observing Satellite (GOSAT) show that OCO-2 observations can be used reliably to estimate IAV. Furthermore, the extensive spatial coverage of the OCO-2 satellite data leads to smoother IAV time series than those from other datasets, suggesting that OCO-2 provides new capabilities for revealing small IAV signals despite sources of noise and error that are inherent to remote-sensing datasets.

Published
2023

21. CH4 Fluxes Derived from Assimilation of TROPOMI XCH4 in CarbonTracker Europe-CH4: Evaluation of Seasonality and Spatial Distribution in the Northern High Latitudes

Author

Tsuruta, Aki, primary, Kivimäki, Ella, additional, Lindqvist, Hannakaisa, additional, Karppinen, Tomi, additional, Backman, Leif, additional, Hakkarainen, Janne, additional, Schneising, Oliver, additional, Buchwitz, Michael, additional, Lan, Xin, additional, Kivi, Rigel, additional, Chen, Huilin, additional, Buschmann, Matthias, additional, Herkommer, Benedikt, additional, Notholt, Justus, additional, Roehl, Coleen, additional, Té, Yao, additional, Wunch, Debra, additional, Tamminen, Johanna, additional, and Aalto, Tuula, additional

Published
2023
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22. National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the global stocktake

Author

Byrne, Brendan, primary, Baker, David F., additional, Basu, Sourish, additional, Bertolacci, Michael, additional, Bowman, Kevin W., additional, Carroll, Dustin, additional, Chatterjee, Abhishek, additional, Chevallier, Frédéric, additional, Ciais, Philippe, additional, Cressie, Noel, additional, Crisp, David, additional, Crowell, Sean, additional, Deng, Feng, additional, Deng, Zhu, additional, Deutscher, Nicholas M., additional, Dubey, Manvendra K., additional, Feng, Sha, additional, García, Omaira E., additional, Griffith, David W. T., additional, Herkommer, Benedikt, additional, Hu, Lei, additional, Jacobson, Andrew R., additional, Janardanan, Rajesh, additional, Jeong, Sujong, additional, Johnson, Matthew S., additional, Jones, Dylan B. A., additional, Kivi, Rigel, additional, Liu, Junjie, additional, Liu, Zhiqiang, additional, Maksyutov, Shamil, additional, Miller, John B., additional, Miller, Scot M., additional, Morino, Isamu, additional, Notholt, Justus, additional, Oda, Tomohiro, additional, O'Dell, Christopher W., additional, Oh, Young-Suk, additional, Ohyama, Hirofumi, additional, Patra, Prabir K., additional, Peiro, Hélène, additional, Petri, Christof, additional, Philip, Sajeev, additional, Pollard, David F., additional, Poulter, Benjamin, additional, Remaud, Marine, additional, Schuh, Andrew, additional, Sha, Mahesh K., additional, Shiomi, Kei, additional, Strong, Kimberly, additional, Sweeney, Colm, additional, Té, Yao, additional, Tian, Hanqin, additional, Velazco, Voltaire A., additional, Vrekoussis, Mihalis, additional, Warneke, Thorsten, additional, Worden, John R., additional, Wunch, Debra, additional, Yao, Yuanzhi, additional, Yun, Jeongmin, additional, Zammit-Mangion, Andrew, additional, and Zeng, Ning, additional

Published
2023
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23. Quality Evaluation of the Column-Averaged Dry Air Mole Fractions of Carbon Dioxide and Methane Observed by GOSAT and GOSAT-2

Author

Yoshida, Yukio, primary, Someya, Yu, additional, Ohyama, Hirofumi, additional, Morino, Isamu, additional, Matsunaga, Tsuneo, additional, Deutscher, Nicholas M., additional, Griffith, David W. T., additional, Hase, Frank, additional, Iraci, Laura T., additional, Kivi, Rigel, additional, Notholt, Justus, additional, Pollard, David F., additional, Té, Yao, additional, Velazco, Voltaire A., additional, and Wunch, Debra, additional

Published
2023
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24. Anomalies of O3, CO, C2H2, H2CO, and C2H6 detected with multiple ground-based Fourier-transform infrared spectrometers and assessed with model simulation in 2020: COVID-19 lockdowns versus natural variability

Author

Ortega, Ivan, primary, Gaubert, Benjamin, additional, Hannigan, James W., additional, Brasseur, Guy, additional, Worden, Helen M., additional, Blumenstock, Thomas, additional, Fu, Hao, additional, Hase, Frank, additional, Jeseck, Pascal, additional, Jones, Nicholas, additional, Liu, Cheng, additional, Mahieu, Emmanuel, additional, Morino, Isamu, additional, Murata, Isao, additional, Notholt, Justus, additional, Palm, Mathias, additional, Röhling, Amelie, additional, Té, Yao, additional, Strong, Kimberly, additional, Sun, Youwen, additional, and Yamanouchi, Shoma, additional

Published
2023
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27. CH₄ Fluxes Derived from Assimilation of TROPOMI XCH₄ in CarbonTracker Europe-CH₄: Evaluation of Seasonality and Spatial Distribution in the Northern High Latitudes

Author

Tsuruta, Aki, Kivimäki, Ella, Lindqvist, Hannakaisa, Karppinen, Tomi, Backman, Leif, Hakkarainen, Janne, Schneising, Oliver, Buchwitz, Michael, Lan, Xin, Kivi, Rigel, Chen, Huilin, Buschmann, Matthias, Herkommer, Benedikt, Notholt, Justus, Roehl, Coleen, Té, Yao, Wunch, Debra, Tamminen, Johanna, and Aalto, Tuula

Abstract

Recent advances in satellite observations of methane provide increased opportunities for inverse modeling. However, challenges exist in the satellite observation optimization and retrievals for high latitudes. In this study, we examine possibilities and challenges in the use of the total column averaged dry-air mole fractions of methane (XCH₄) data over land from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel 5 Precursor satellite in the estimation of CH₄ fluxes using the CarbonTracker Europe-CH₄ (CTE-CH₄) atmospheric inverse model. We carry out simulations assimilating two retrieval products: Netherlands Institute for Space Research’s (SRON) operational and University of Bremen’s Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS). For comparison, we also carry out a simulation assimilating the ground-based surface data. Our results show smaller regional emissions in the TROPOMI inversions compared to the prior and surface inversion, although they are roughly within the range of the previous studies. The wetland emissions in summer and anthropogenic emissions in spring are lesser. The inversion results based on the two satellite datasets show many similarities in terms of spatial distribution and time series but also clear differences, especially in Canada, where CH₄ emission maximum is later, when the SRON’s operational data are assimilated. The TROPOMI inversions show higher CH₄ emissions from oil and gas production and coal mining from Russia and Kazakhstan. The location of hotspots in the TROPOMI inversions did not change compared to the prior, but all inversions indicated spatially more homogeneous high wetland emissions in northern Fennoscandia. In addition, we find that the regional monthly wetland emissions in the TROPOMI inversions do not correlate with the anthropogenic emissions as strongly as those in the surface inversion. The uncertainty estimates in the TROPOMI inversions are more homogeneous in space, and the regional uncertainties are comparable to the surface inversion. This indicates the potential of the TROPOMI data to better separately estimate wetland and anthropogenic emissions, as well as constrain spatial distributions. This study emphasizes the importance of quantifying and taking into account the model and retrieval uncertainties in regional levels in order to improve and derive more robust emission estimates.

Published
2023

29. Weekly-derived top-down VOC fluxes over Europe from TROPOMI HCHO data in 2018–2021.

Author

Oomen, Glenn-Michael, Müller, Jean-François, Stavrakou, Trissevgeni, Smedt, Isabelle De, Blumenstock, Thomas, Kivi, Rigel, Makarova, Maria, Palm, Mathias, Röhling, Amelie, Té, Yao, Vigouroux, Corinne, Friedrich, Martina M., Frieß, Udo, Hendrick, François, Merlaud, Alexis, Piters, Ankie, Richter, Andreas, Roozendael, Michel Van, and Wagner, Thomas

Subjects
TROPOSPHERIC ozone, BIOMASS burning, CHEMICAL models, REMOTE sensing, VOLATILE organic compounds
Abstract

Volatile organic compounds (VOCs) are key precursors of particulate matter and tropospheric ozone. Although the terrestrial biosphere is by far the largest source of VOCs into the atmosphere, the emissions of biogenic VOCs remain poorly constrained at regional scale. In this work, we derive top-down biogenic emissions over Europe using weekly-averaged TROPOMI formaldehyde (HCHO) data from 2018 to 2021. The systematic bias of the TROPOMI HCHO columns is characterized and corrected for based on comparisons with FTIR data at seven European stations. The top-down fluxes of biogenic, pyrogenic, and anthropogenic VOC sources are optimized using an inversion framework based on the MAGRITTEv1.1 chemistry transport model and its adjoint. The inversion leads to strongly increased isoprene emissions with respect to the MEGAN-MOHYCAN inventory over the model domain (from 8.1 to 18.5 Tg yr-1) which is driven by the high observed TROPOMI HCHO columns in southern Europe. The impact of the inversion on biomass burning VOCs (+13 %) and anthropogenic VOCs (-17 %) is moderate. An evaluation of the optimized HCHO distribution against ground-based remote sensing (FTIR and MAX-DOAS) and in situ data provides generally improved agreement at stations below about 50° N, but indicates overestimated emissions in northern Scandinavia. Sensitivity inversions show that the top-down emissions are robust with respect to changes in the inversion settings and in the model chemical mechanism. However, the top-down emissions are very sensitive to the bias correction of the observed columns. Furthermore, the use of different a priori emissions has a significant impact on the inversion results due to large differences among bottom-up inventories. In regions with variable meteorology, there is strong week-to-week variability in the observed HCHO columns. The top-down emissions, which are optimized at weekly increments, have a much improved capability of representing these large fluctuations than an inversion using monthly increments. [ABSTRACT FROM AUTHOR]

Published
2023
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30. Characteristics of Interannual Variability in Space-based XCO2 Global Observations

Author

Guan, Yifan, primary, Keppel-Aleks, Gretchen, additional, Doney, Scott C., additional, Petri, Christof, additional, Pollard, Dave, additional, Wunch, Debra, additional, Hase, Frank, additional, Ohyama, Hirofumi, additional, Morino, Isamu, additional, Notholt, Justus, additional, Shiomi, Kei, additional, Strong, Kim, additional, Kivi, Rigel, additional, Buschmann, Matthias, additional, Deutscher, Nicholas, additional, Wennberg, Paul, additional, Sussmann, Ralf, additional, Velazco, Voltaire A., additional, and Té, Yao, additional

Published
2022
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31. Supplementary material to "Characteristics of Interannual Variability in Space-based XCO2 Global Observations"

Author

Guan, Yifan, primary, Keppel-Aleks, Gretchen, additional, Doney, Scott C., additional, Petri, Christof, additional, Pollard, Dave, additional, Wunch, Debra, additional, Hase, Frank, additional, Ohyama, Hirofumi, additional, Morino, Isamu, additional, Notholt, Justus, additional, Shiomi, Kei, additional, Strong, Kim, additional, Kivi, Rigel, additional, Buschmann, Matthias, additional, Deutscher, Nicholas, additional, Wennberg, Paul, additional, Sussmann, Ralf, additional, Velazco, Voltaire A., additional, and Té, Yao, additional

Published
2022
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32. Update on the GOSAT TANSO–FTS SWIR Level 2 retrieval algorithm

Author

Someya, Yu, primary, Yoshida, Yukio, additional, Ohyama, Hirofumi, additional, Nomura, Shohei, additional, Kamei, Akihide, additional, Morino, Isamu, additional, Mukai, Hitoshi, additional, Matsunaga, Tsuneo, additional, Laughner, Joshua L., additional, Velazco, Voltaire A., additional, Herkommer, Benedikt, additional, Té, Yao, additional, Sha, Mahesh Kumar, additional, Kivi, Rigel, additional, Zhou, Minqiang, additional, Oh, Young Suk, additional, Deutscher, Nicholas M., additional, and Griffith, David W. T., additional

Published
2022
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33. Supplementary material to "Update on the GOSAT TANSO–FTS SWIR Level 2 retrieval algorithm"

Author

Someya, Yu, primary, Yoshida, Yukio, additional, Ohyama, Hirofumi, additional, Nomura, Shohei, additional, Kamei, Akihide, additional, Morino, Isamu, additional, Mukai, Hitoshi, additional, Matsunaga, Tsuneo, additional, Laughner, Joshua L., additional, Velazco, Voltaire A., additional, Herkommer, Benedikt, additional, Té, Yao, additional, Sha, Mahesh Kumar, additional, Kivi, Rigel, additional, Zhou, Minqiang, additional, Oh, Young Suk, additional, Deutscher, Nicholas M., additional, and Griffith, David W. T., additional

Published
2022
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35. Supplementary material to "National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the Global Stocktake"

Author

Byrne, Brendan, primary, Baker, David F., additional, Basu, Sourish, additional, Bertolacci, Michael, additional, Bowman, Kevin W., additional, Carroll, Dustin, additional, Chatterjee, Abhishek, additional, Chevallier, Frédéric, additional, Ciais, Philippe, additional, Cressie, Noel, additional, Crisp, David, additional, Crowell, Sean, additional, Deng, Feng, additional, Deng, Zhu, additional, Deutscher, Nicholas M., additional, Dubey, Manvendra, additional, Feng, Sha, additional, García, Omaira, additional, Griffith, David W. T., additional, Herkommer, Benedikt, additional, Hu, Lei, additional, Jacobson, Andrew R., additional, Janardanan, Rajesh, additional, Jeong, Sujong, additional, Johnson, Matthew S., additional, Jones, Dylan B. A., additional, Kivi, Rigel, additional, Liu, Junjie, additional, Liu, Zhiqiang, additional, Maksyutov, Shamil, additional, Miller, John B., additional, Miller, Scot M., additional, Morino, Isamu, additional, Notholt, Justus, additional, Oda, Tomohiro, additional, O’Dell, Christopher W., additional, Oh, Young-Suk, additional, Ohyama, Hirofumi, additional, Patra, Prabir K., additional, Peiro, Hélène, additional, Petri, Christof, additional, Philip, Sajeev, additional, Pollard, David F., additional, Poulter, Benjamin, additional, Remaud, Marine, additional, Schuh, Andrew, additional, Sha, Mahesh K., additional, Shiomi, Kei, additional, Strong, Kimberly, additional, Sweeney, Colm, additional, Té, Yao, additional, Tian, Hanqin, additional, Velazco, Voltaire A., additional, Vrekoussis, Mihalis, additional, Warneke, Thorsten, additional, Worden, John R., additional, Wunch, Debra, additional, Yao, Yuanzhi, additional, Yun, Jeongmin, additional, Zammit-Mangion, Andrew, additional, and Zeng, Ning, additional

Published
2022
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36. National CO2 budgets (2015–2020) inferred from atmospheric CO2 observations in support of the Global Stocktake

Author

Byrne, Brendan, primary, Baker, David F., additional, Basu, Sourish, additional, Bertolacci, Michael, additional, Bowman, Kevin W., additional, Carroll, Dustin, additional, Chatterjee, Abhishek, additional, Chevallier, Frédéric, additional, Ciais, Philippe, additional, Cressie, Noel, additional, Crisp, David, additional, Crowell, Sean, additional, Deng, Feng, additional, Deng, Zhu, additional, Deutscher, Nicholas M., additional, Dubey, Manvendra, additional, Feng, Sha, additional, García, Omaira, additional, Griffith, David W. T., additional, Herkommer, Benedikt, additional, Hu, Lei, additional, Jacobson, Andrew R., additional, Janardanan, Rajesh, additional, Jeong, Sujong, additional, Johnson, Matthew S., additional, Jones, Dylan B. A., additional, Kivi, Rigel, additional, Liu, Junjie, additional, Liu, Zhiqiang, additional, Maksyutov, Shamil, additional, Miller, John B., additional, Miller, Scot M., additional, Morino, Isamu, additional, Notholt, Justus, additional, Oda, Tomohiro, additional, O’Dell, Christopher W., additional, Oh, Young-Suk, additional, Ohyama, Hirofumi, additional, Patra, Prabir K., additional, Peiro, Hélène, additional, Petri, Christof, additional, Philip, Sajeev, additional, Pollard, David F., additional, Poulter, Benjamin, additional, Remaud, Marine, additional, Schuh, Andrew, additional, Sha, Mahesh K., additional, Shiomi, Kei, additional, Strong, Kimberly, additional, Sweeney, Colm, additional, Té, Yao, additional, Tian, Hanqin, additional, Velazco, Voltaire A., additional, Vrekoussis, Mihalis, additional, Warneke, Thorsten, additional, Worden, John R., additional, Wunch, Debra, additional, Yao, Yuanzhi, additional, Yun, Jeongmin, additional, Zammit-Mangion, Andrew, additional, and Zeng, Ning, additional

Published
2022
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38. Improved calibration procedures for the EM27/SUN spectrometers of the COllaborative Carbon Column Observing Network (COCCON)

Author

Alberti, Carlos, Hase, Frank, Frey, Matthias, Dubravica, Darko, Blumenstock, Thomas, Dehn, Angelika, Castracane, Paolo, Surawicz, Gregor, Harig, Roland, Baier, Bianca, Bès, Caroline, Bi, Jianrong, Boesch, Hartmut, Butz, André, Cai, Zhaonan, Chen, Jia, Crowell, Sean, Deutscher, Nicholas, Ene, Dragos, Franklin, Jonathan, García, Omaira, Griffith, David, Grouiez, Bruno, Grutter, Michel, Hamdouni, Abdelhamid, Houweling, Sander, Humpage, Neil, Jacobs, Nicole, Jeong, Sujong, Joly, Lilian, Jones, Nicholas, Jouglet, Denis, Kivi, Rigel, Kleinschek, Ralph, Lopez, Morgan, Medeiros, Diogo, Morino, Isamu, Mostafavipak, Nasrin, Müller, Astrid, Ohyama, Hirofumi, Palmer, Paul, Pathakoti, Mahesh, Pollard, David, Raffalski, Uwe, Ramonet, Michel, Ramsay, Robbie, Sha, Mahesh Kumar, Shiomi, Kei, Simpson, William, Stremme, Wolfgang, Sun, Youwen, Tanimoto, Hiroshi, Té, Yao, Tsidu, Gizaw Mengistu, Velazco, Voltaire, Vogel, Felix, Watanabe, Masataka, Wei, Chong, Wunch, Debra, Yamasoe, Marcia, Zhang, Lu, Orphal, Johannes, Sha, Mahesh, Tsidu, Gizaw, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), ICOS-RAMCES (ICOS-RAMCES), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut Pierre-Simon-Laplace (IPSL (FR_636)), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-Centre National d'Études Spatiales [Toulouse] (CNES)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres (LERMA), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, and Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-CY Cergy Paris Université (CY)

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment
Abstract

International audience; Abstract. In this study, an extension on the previously reported status of the COllaborative Carbon Column Observing Network's (COCCON) calibration procedures incorporating refined methods is presented. COCCON is a global network of portable Bruker EM27/SUN FTIR spectrometers for deriving column-averaged atmospheric abundances of greenhouse gases. The original laboratory open-path lamp measurements for deriving the instrumental line shape (ILS) of the spectrometer from water vapour lines have been refined and extended to the secondary detector channel incorporated in the EM27/SUN spectrometer for detection of carbon monoxide (CO). The refinements encompass improved spectroscopic line lists for the relevant water lines and a revision of the laboratory pressure measurements used for the analysis of the spectra. The new results are found to be in good agreement with those reported by Frey et al. (2019) and discussed in detail. In addition, a new calibration cell for ILS measurements was designed, constructed and put into service. Spectrometers calibrated since January 2020 were tested using both methods for ILS characterization, open-path (OP) and cell measurements. We demonstrate that both methods can detect the small variations in ILS characteristics between different spectrometers, but the results of the cell method indicate a systematic bias of the OP method. Finally, a revision and extension of the COCCON network instrument-to-instrument calibration factors for XCO2, XCO and XCH4 is presented, incorporating 47 new spectrometers (of 83 in total by now). This calibration is based on the reference EM27/SUN spectrometer operated by the Karlsruhe Institute of Technology (KIT) and spectra collected by the collocated TCCON station Karlsruhe. Variations in the instrumental characteristics of the reference EM27/SUN from 2014 to 2017 were detected, probably arising from realignment and the dual-channel upgrade performed in early 2018. These variations are considered in the evaluation of the instrument-specific calibration factors in order to keep all tabulated calibration results consistent.

Published
2022

39. Nitrous Oxide Profiling from Infrared Radiances (NOPIR): Algorithm description, application to 10 years of IASI observations and quality assessment

Author

Vandenbussche, Sophie, Langerock, Bavo, Vigouroux, Corinne, Buschmann, Matthias, Deutscher, Nicholas M., Feist, Dietrich G., García, Omaira E., Hannigan, James W., Hase, Frank, Kivi, Rigel, Kumps, Nicolas, Makarova, Maria V., Millet, Dylan B., Morino, Isamu, Nagahama, Tomoo, Notholt, Justus, Ohyama, Hirofumi, Ortega, Ivan, Petri, Christof, Rettinger, Markus, Schneider, Matthias, Servais, Christian P., Sha, Mahesh K., Shiomi, Kei, Smale, Dan, Strong, Kimberly, Sussmann, Ralf, Té, Yao, Velazco, Voltaire A., Vrekoussis, Mihalis, Warneke, Thorsten, Wells, Kelley C., Wunch, Debra, Zhou, Minqiang, and De Mazière, Martine

Subjects
Nitrous oxide, IASI, Retrieval, TCCON, Greenhouse gas, nitrous oxide, greenhouse gas, retrieval, validation, Earth sciences, Satellite, Validation, ddc:550, remote sensing N2O, General Earth and Planetary Sciences, NDACC, long-term record
Abstract

Nitrous oxide (N$_{2}$O) is the third most abundant anthropogenous greenhouse gas (after carbon dioxide and methane), with a long atmospheric lifetime and a continuously increasing concentration due to human activities, making it an important gas to monitor. In this work, we present a new method to retrieve N$_{2}$O concentration profiles (with up to two degrees of freedom) from each cloud-free satellite observation by the Infrared Atmospheric Sounding Interferometer (IASI), using spectral micro-windows in the N$_{2}$O ν$_{3}$ band, the Radiative Transfer for TOVS (RTTOV) tools and the Tikhonov regularization scheme. A time series of ten years (2011–2020) of IASI N$_{2}$O profiles and integrated partial columns has been produced and validated with collocated ground-based Network for the Detection of Atmospheric Composition Change (NDACC) and Total Carbon Column Observing Network (TCCON) data. The importance of consistency in the ancillary data used for the retrieval for generating consistent time series has been demonstrated. The Nitrous Oxide Profiling from Infrared Radiances (NOPIR) N$_{2}$O partial columns are of very good quality, with a positive bias of 1.8 to 4% with respect to the ground-based data, which is less than the sum of uncertainties of the compared values. At high latitudes, the comparisons are a bit worse, due to either a known bias in the ground-based data, or to a higher uncertainty in both ground-based and satellite retrievals.

Published
2022

40. Retrieval of greenhouse gases from GOSAT and GOSAT-2 using the FOCAL algorithm

Author

Noël, Stefan, primary, Reuter, Maximilian, additional, Buchwitz, Michael, additional, Borchardt, Jakob, additional, Hilker, Michael, additional, Schneising, Oliver, additional, Bovensmann, Heinrich, additional, Burrows, John P., additional, Di Noia, Antonio, additional, Parker, Robert J., additional, Suto, Hiroshi, additional, Yoshida, Yukio, additional, Buschmann, Matthias, additional, Deutscher, Nicholas M., additional, Feist, Dietrich G., additional, Griffith, David W. T., additional, Hase, Frank, additional, Kivi, Rigel, additional, Liu, Cheng, additional, Morino, Isamu, additional, Notholt, Justus, additional, Oh, Young-Suk, additional, Ohyama, Hirofumi, additional, Petri, Christof, additional, Pollard, David F., additional, Rettinger, Markus, additional, Roehl, Coleen, additional, Rousogenous, Constantina, additional, Sha, Mahesh Kumar, additional, Shiomi, Kei, additional, Strong, Kimberly, additional, Sussmann, Ralf, additional, Té, Yao, additional, Velazco, Voltaire A., additional, Vrekoussis, Mihalis, additional, and Warneke, Thorsten, additional

Published
2022
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42. An 11-year record of XCO2 estimates derived from GOSAT measurements using the NASA ACOS version 9 retrieval algorithm

Author

Taylor, Thomas E., O'Dell, Christopher W., Crisp, David, Kuze, Akihiko, Lindqvist, Hannakaisa, Wennberg, Paul O., Chatterjee, Abhishek, Gunson, Michael, Eldering, Annmarie, Fisher, Brendan, Kiel, Matthäus, Nelson, Robert R., Merrelli, Aronne, Osterman, Greg, Chevallier, Frederic, Palmer, Paul I., Feng, Liang, Deutscher, Nicholas M., Dubey, Manvendra K., Feist, Dietrich G., García, Omaira E., Griffith, David W. T., Hase, Frank, Iraci, Laura T., Kivi, Rigel, Liu, Cheng, De Mazière, Martine, Morino, Isamu, Notholt, Justus, Oh, Young-Suk, Ohyama, Hirofumi, Pollard, David F., Rettinger, Markus, Schneider, Matthias, Roehl, Coleen M., Sha, Mahesh K., Shiomi, Kei, Strong, Kimberly, Sussmann, Ralf, Té, Yao, Velazco, Voltaire A., Vrekoussis, Mihalis, Warneke, Thorsten, Wunch, Debra, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Etude du Rayonnement et de la Matière en Astrophysique et Atmosphères = Laboratory for Studies of Radiation and Matter in Astrophysics and Atmospheres (LERMA), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de Paris, and Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-CY Cergy Paris Université (CY)

Subjects
remote sensing, Greenhouse gases, Carbon dioxide, [SDU]Sciences of the Universe [physics], Satellite, CO2, long-term record, GOSAT, ACOS, Satellite observations
Abstract

International audience; The Thermal And Near infrared Sensor for carbon Observation - Fourier Transform Spectrometer (TANSO-FTS) on the Japanese Greenhouse gases Observing SATellite (GOSAT) has been returning data since April 2009. The version 9 (v9) Atmospheric Carbon Observations from Space (ACOS) Level 2 Full Physics (L2FP) retrieval algorithm (Kiel et al., 2019) was used to derive estimates of carbon dioxide (CO2) dry air mole fraction (XCO2) from the TANSO-FTS measurements collected over its first 11 years of operation. The bias correction and quality filtering of the L2FP XCO2 product were evaluated using estimates derived from the Total Carbon Column Observing Network (TCCON) as well as values simulated from a suite of global atmospheric inversion systems (models) which do not assimilate satellite-derived CO2. In addition, the v9 ACOS GOSAT XCO2 results were compared with collocated XCO2 estimates derived from NASA's Orbiting Carbon Observatory-2 (OCO-2), using the version 10 (v10) ACOS L2FP algorithm. These tests indicate that the v9 ACOS GOSAT XCO2 product has improved throughput, scatter, and bias, when compared to the earlier v7.3 ACOS GOSAT product, which extended through mid 2016. Of the 37 million soundings collected by GOSAT through June 2020, approximately 20 % were selected for processing by the v9 L2FP algorithm after screening for clouds and other artifacts. After post-processing, 5.4 % of the soundings (2×106 out of 37×106) were assigned a "good" XCO2 quality flag, as compared to 3.9 % in v7.3 (6 out of 24×106). After quality filtering and bias correction, the differences in XCO2 between ACOS GOSAT v9 and both TCCON and models have a scatter (1σ) of approximately 1 ppm for ocean-glint observations and 1 to 1.5 ppm for land observations. Global mean biases against TCCON and models are less than approximately 0.2 ppm. Seasonal mean biases relative to the v10 OCO-2 XCO2 product are of the order of 0.1 ppm for observations over land. However, for ocean-glint observations, seasonal mean biases relative to OCO-2 range from 0.2 to 0.6 ppm, with substantial variation in time and latitude. The ACOS GOSAT v9 XCO2 data are available on the NASA Goddard Earth Science Data and Information Services Center (GES-DISC) in both the per-orbit full format (https://doi.org/10.5067/OSGTIL9OV0PN, OCO-2 Science Team et al., 2019b) and in the per-day lite format (https://doi.org/10.5067/VWSABTO7ZII4, OCO-2 Science Team et al., 2019a). In addition, a new set of monthly super-lite files, containing only the most essential variables for each satellite observation, has been generated to provide entry level users with a light-weight satellite product for initial exploration (CaltechDATA, https://doi.org/10.22002/D1.2178, Eldering, 2021). The v9 ACOS Data User's Guide (DUG) describes best-use practices for the GOSAT data (O'Dell et al., 2020). The GOSAT v9 data set should be especially useful for studies of carbon cycle phenomena that span a full decade or more and may serve as a useful complement to the shorter OCO-2 v10 data set, which begins in September 2014.

Published
2022

43. Update on the GOSAT TANSO–FTS SWIR Level 2 retrieval algorithm.

Author

Someya, Yu, Yoshida, Yukio, Ohyama, Hirofumi, Nomura, Shohei, Kamei, Akihide, Morino, Isamu, Mukai, Hitoshi, Matsunaga, Tsuneo, Laughner, Joshua L., Velazco, Voltaire A., Herkommer, Benedikt, Té, Yao, Sha, Mahesh Kumar, Kivi, Rigel, Zhou, Minqiang, Oh, Young Suk, Deutscher, Nicholas M., and Griffith, David W. T.

Subjects
SOLAR spectra, CIRRUS clouds, GAS absorption & adsorption, ALGORITHMS, ABSORPTION coefficients, SPECTRAL irradiance, MAXIMUM power point trackers
Abstract

The National Institute for Environmental Studies has provided the column-averaged dry-air mole fraction of carbon dioxide and methane (XCO 2 and XCH 4) products (L2 products) obtained from the Greenhouse gases Observing SATellite (GOSAT) for more than a decade. Recently, we updated the retrieval algorithm used to produce the new L2 product, V03.00. The main changes from the previous version (V02) of the retrieval algorithm are the treatment of cirrus clouds, the degradation model of the Thermal And Near-infrared Spectrometer for carbon Observation–Fourier Transform Spectrometer (TANSO–FTS), solar irradiance spectra, and gas absorption coefficient tables. The retrieval results from the updated algorithm showed improvements in fitting accuracies in the O 2 A, weak CO 2 , and CH 4 bands of TANSO–FTS, although the residuals increase in the strong CO 2 band over the ocean. The direct comparison of the new product obtained from the updated (V03) algorithm with the previous version V02.90/91 and the validations using the Total Carbon Column Observing Network revealed that the V03 algorithm increases the amount of data without diminishing the data qualities of XCO 2 and XCH 4 over land. However, the negative bias of XCO 2 is larger than that of the previous version over the ocean, and bias correction is still necessary. Additionally, the V03 algorithm resolves the underestimation of the XCO 2 growth rate compared with the in situ measurements over the ocean recently found using V02.90/91 and V02.95/96. [ABSTRACT FROM AUTHOR]

Published
2023
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44. CH 4 Fluxes Derived from Assimilation of TROPOMI XCH 4 in CarbonTracker Europe-CH 4 : Evaluation of Seasonality and Spatial Distribution in the Northern High Latitudes.

Author

Tsuruta, Aki, Kivimäki, Ella, Lindqvist, Hannakaisa, Karppinen, Tomi, Backman, Leif, Hakkarainen, Janne, Schneising, Oliver, Buchwitz, Michael, Lan, Xin, Kivi, Rigel, Chen, Huilin, Buschmann, Matthias, Herkommer, Benedikt, Notholt, Justus, Roehl, Coleen, Té, Yao, Wunch, Debra, Tamminen, Johanna, and Aalto, Tuula

Subjects
ATMOSPHERIC methane, LATITUDE, HOMOGENEOUS spaces, COAL mining, OPTICAL spectroscopy, MOLE fraction
Abstract

Recent advances in satellite observations of methane provide increased opportunities for inverse modeling. However, challenges exist in the satellite observation optimization and retrievals for high latitudes. In this study, we examine possibilities and challenges in the use of the total column averaged dry-air mole fractions of methane ( XCH 4 ) data over land from the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinel 5 Precursor satellite in the estimation of CH 4 fluxes using the CarbonTracker Europe- CH 4 (CTE- CH 4 ) atmospheric inverse model. We carry out simulations assimilating two retrieval products: Netherlands Institute for Space Research's (SRON) operational and University of Bremen's Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS). For comparison, we also carry out a simulation assimilating the ground-based surface data. Our results show smaller regional emissions in the TROPOMI inversions compared to the prior and surface inversion, although they are roughly within the range of the previous studies. The wetland emissions in summer and anthropogenic emissions in spring are lesser. The inversion results based on the two satellite datasets show many similarities in terms of spatial distribution and time series but also clear differences, especially in Canada, where CH 4 emission maximum is later, when the SRON's operational data are assimilated. The TROPOMI inversions show higher CH 4 emissions from oil and gas production and coal mining from Russia and Kazakhstan. The location of hotspots in the TROPOMI inversions did not change compared to the prior, but all inversions indicated spatially more homogeneous high wetland emissions in northern Fennoscandia. In addition, we find that the regional monthly wetland emissions in the TROPOMI inversions do not correlate with the anthropogenic emissions as strongly as those in the surface inversion. The uncertainty estimates in the TROPOMI inversions are more homogeneous in space, and the regional uncertainties are comparable to the surface inversion. This indicates the potential of the TROPOMI data to better separately estimate wetland and anthropogenic emissions, as well as constrain spatial distributions. This study emphasizes the importance of quantifying and taking into account the model and retrieval uncertainties in regional levels in order to improve and derive more robust emission estimates. [ABSTRACT FROM AUTHOR]

Published
2023
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45. Anomalies of O3, CO, C2H2, H2CO, and C2H6 detected with multiple ground-based Fourier-transform infrared spectrometers and assessed with model simulation in 2020: COVID-19 lockdowns versus natural variability.

Author

Ortega, Ivan, Gaubert, Benjamin, Hannigan, James W., Brasseur, Guy, Worden, Helen M., Blumenstock, Thomas, Fu, Hao, Hase, Frank, Jeseck, Pascal, Jones, Nicholas, Liu, Cheng, Mahieu, Emmanuel, Morino, Isamu, Murata, Isao, Notholt, Justus, Palm, Mathias, Röhling, Amelie, Té, Yao, Strong, Kimberly, and Sun, Youwen

Published
2023
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47. Retrieval of greenhouse gases from GOSAT and greenhouse gases and carbon monoxide from GOSAT-2 using the FOCAL algorithm

Author

Noël, Stefan, primary, Reuter, Maximilian, additional, Buchwitz, Michael, additional, Borchardt, Jakob, additional, Hilker, Michael, additional, Schneising, Oliver, additional, Bovensmann, Heinrich, additional, Burrows, John P., additional, Di Noia, Antonio, additional, Parker, Robert J., additional, Suto, Hiroshi, additional, Yoshida, Yukio, additional, Buschmann, Matthias, additional, Deutscher, Nicholas M., additional, Feist, Dietrich G., additional, Griffith, David W. T., additional, Hase, Frank, additional, Kivi, Rigel, additional, Liu, Cheng, additional, Morino, Isamu, additional, Notholt, Justus, additional, Oh, Young-Suk, additional, Ohyama, Hirofumi, additional, Petri, Christof, additional, Pollard, David F., additional, Rettinger, Markus, additional, Roehl, Coleen M., additional, Rousogenous, Constantina, additional, Sha, Mahesh Kumar, additional, Shiomi, Kei, additional, Strong, Kimberly, additional, Sussmann, Ralf, additional, Té, Yao, additional, Velazco, Voltaire A., additional, Vrekoussis, Mihalis, additional, and Warneke, Thorsten, additional

Published
2022
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49. Global Atmospheric OCS Trend Analysis from 22 NDACC Stations

Author

Hannigan, James W, primary, Ortega, Ivan, additional, Bahramvash Shams, Shima, additional, Blumenstock, Thomas, additional, Campbell, John Elliott, additional, Conway, Stephanie Araz, additional, Flood, Victoria, additional, García, Omaira, additional, Grutter, Michel, additional, Hase, Frank, additional, Jones, Nicholas Brian, additional, Jeseck, Pascal, additional, Mahieu, Emmanuel, additional, Makarova, Maria, additional, De Maziere, Martine, additional, Morino, Isamu, additional, Murata, Isao, additional, Nagahama, Tomoo, additional, Nakajima, Hideaki, additional, Notholt, Justus, additional, Palm, Mathias, additional, Poberovskii, Anatoliy, additional, Rettinger, Markus, additional, Robinson, John, additional, Schneider, Matthias, additional, Röhling, Amelie, additional, Servais, Christian, additional, Smale, Dan, additional, Stremme, Wolfgang, additional, Strong, Kimberly, additional, Sussmann, Ralf, additional, Té, Yao, additional, Vigouroux, Corinne, additional, and Wizenberg, Tyler, additional

Published
2021
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50. The reduction in C2H6 from 2015 to 2020 over Hefei, eastern China, points to air quality improvement in China

Author

Sun, Youwen, Yin, Hao, Liu, Cheng, Mahieu, Emmanuel, Notholt, Justus, Té, Yao, Lu, Xiao, Palm, Mathias, Wang, Wei, Shan, Changgong, Hu, Qihou, Qin, Min, Tian, Yuan, and Zheng, Bo

Abstract

Ethane (C2H6) is an important greenhouse gas and plays a significant role in tropospheric chemistry and climate change. This study first presents and then quantifies the variability, sources, and transport of C2H6 over densely populated and highly industrialized eastern China using ground-based high-resolution Fourier transform infrared (FTIR) remote sensing along with atmospheric modeling techniques. We obtained a retrieval error of 6.21 ± 1.2 (1σ)% and degrees of freedom (DOFS) of 1.47 ± 0.2 (1σ) in the retrieval of C2H6 tropospheric column-averaged dry-air mole fraction (troDMF) over Hefei, eastern China (32∘ N, 117∘ E; 30 ma.s.l.). The observed C2H6 troDMF reached a minimum monthly mean value of 0.36 ± 0.26 ppbv in July and a maximum monthly mean value of 1.76 ± 0.35 ppbv in December, and showed a negative change rate of −2.60 ± 1.34 % yr−1 from 2015 to 2020. The dependencies of C2H6 troDMF on meteorological and emission factors were analyzed using generalized additive models (GAMs). Generally, both meteorological and emission factors have positive influences on C2H6 troDMF in the cold season (December–January–February/March–April–May, DJF/MAM) and negative influences on C2H6 troDMF in the warm season (June–July–August/September–October–November, JJA/SON). GEOS-Chem chemical model simulation captured the observed C2H6 troDMF variability and was, thus, used for source attribution. GEOS-Chem model sensitivity simulations concluded that the anthropogenic emissions (fossil fuel plus biofuel emissions) and the natural emissions (biomass burning plus biogenic emissions) accounted for 48.1 % and 39.7 % of C2H6 troDMF variability over Hefei, respectively. The observed C2H6 troDMF variability mainly results from the emissions within China (74.1 %), where central, eastern, and northern China dominated the contribution (57.6 %). Seasonal variability in C2H6 transport inflow and outflow over the observation site is largely related to the midlatitude westerlies and the Asian monsoon system. Reduction in C2H6 abundance from 2015 to 2020 mainly results from the decrease in local and transported C2H6 emissions, which points to air quality improvement in China in recent years.

Published
2021

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