the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 03 Feb 2026
Global atmospheric methanol emissions inferred from IASI satellite measurements and aircraft data
Abstract. We employ an updated retrieval of space-based methanol (CH3OH) column measurements from the Infrared Atmospheric Sounding Interferometer (IASI) and an emission optimisation framework built on the MAGRITTE chemical transport model to assess terrestrial emissions of methanol to the atmosphere between 2008 and 2019. We first carry out a IASI CH3OH validation study based on concentration measurements from three airborne campaigns, using the model and the IASI averaging kernels to compute aircraft-based columns directly comparable to IASI data. IASI is found to underestimate high columns in the considered region. A linear regression gives ΩIASI = 0.46 Ωairc + 10.6·1015 molec.cm-2, with ΩIASI and Ωairc the IASI and aircraft-derived columns, respectively. Inverse modelling of terrestrial methanol emissions using MAGRITTE and bias-corrected IASI columns leads to much-improved overall agreement against in situ measurement campaigns and column data at eight FTIR stations. The optimised global biogenic methanol emissions (~160 Tg yr-1) are 22–60 % higher than previous top-down estimates, due to (1) column enhancements caused by the IASI bias-correction and (2) higher dry deposition velocities over land, compared to previous model studies, based on a parametrisation constrained by extensive campaign data. The inversion results are less reliable over boreal forests due to shortcomings of both the bias-correction and the dry deposition scheme over these regions. The optimisation suggests large changes in the seasonality of emissions. Over tropical ecosystems, radiation and temperature appear to exert a stronger control on biogenic emissions than is currently accounted for in the MEGAN model.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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Supplement
(5170 KB) - BibTeX
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2026-253', Anonymous Referee #1, 03 Mar 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-253/egusphere-2026-253-RC1-supplement.pdfCitation: https://doi.org/
10.5194/egusphere-2026-253-RC1 -
AC1: 'Reply on RC1', Jean-François Muller, 10 Apr 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-253/egusphere-2026-253-AC1-supplement.pdf
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AC1: 'Reply on RC1', Jean-François Muller, 10 Apr 2026
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RC2: 'Comment on egusphere-2026-253', Anonymous Referee #2, 07 Apr 2026
The manuscript egusphere-2026-253 by Müller and colleagues presents a very nice work on the global methanol budget.
They have used IASI satellite data to invert the a-priori emissions with the support of the MAGRITTE model.
Importantly, they have bias-corrected the IASI data, which appear to be largely underestimated. Using the corrected data for inverse modelling gives an updated methanol budget, which is however mostly in line with recent literature (e.g. Bates et al., 2021), but with some significant changes (e.g. larger biogenic emissions).I very much appreciate the completeness of the work, as well as the writing style, which helps the reader through this nice study. I have only a few comments on the manuscript, and I hope these may help the authors to improve an already excellent manuscript.
Section 2.5.2: While secondary production accounts for ~15--30% of the total emissions, I wonder how accurate this estimate may be. Nicely, a brief discussion is presented in lines 554--556, showing that changing the overall yield of CH3O2+OH (from 11.4% to 13%) does not change the results. However, it is stated (line 240) that many other uncertainties are present in the chemical production.
Would the consideration of these uncertainties considerably change any of the results obtained in the inversion? Additionally, I wonder how well RO2 is represented in the MAGRITTE model. I assume that most of it is coming from the oxidation of CH4, and therefore I would appreciate some additional discussion on the simulation of the OH fields in the model.Section 3: It is very interesting to note that the MAGRITTE model inversion is able to reproduce the observations in an exceptional way. Furthermore, I appreciate the investigation of the possible bias present in the IASIv4 data, which I consider the real main strength of this manuscript. However, I wonder if the authors could elaborate on the risk of using only an observational dataset over North America. Is this region really representative of the IASI bias? Based on the work of Bates et al. (2021), North America is mostly influenced by biogenic emissions, while biomass burning as well as chemical formation are comparatively much lower. Could the IASI bias be different in other areas of the globe, for example in regions strongly influenced by biomass burning or over the tropics, due to the much stronger influence of methanol chemical production?
Figure 9: Based on what is presented (see, for example, line 385), the focus of the inversion is on terrestrial emissions, and therefore the IASI data over oceans were excluded. I would very much appreciate it if all figures including IASI data could be masked over the ocean, to avoid confusion during reading.
Line 600: It would be great if the Spearman correlation could also be listed, to provide a more complete overview of the comparison.
Citation: https://doi.org/10.5194/egusphere-2026-253-RC2 -
AC2: 'Reply on RC2', Jean-François Muller, 10 Apr 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-253/egusphere-2026-253-AC2-supplement.pdf
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AC2: 'Reply on RC2', Jean-François Muller, 10 Apr 2026
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2026-253', Anonymous Referee #1, 03 Mar 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-253/egusphere-2026-253-RC1-supplement.pdf
-
AC1: 'Reply on RC1', Jean-François Muller, 10 Apr 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-253/egusphere-2026-253-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Jean-François Muller, 10 Apr 2026
-
RC2: 'Comment on egusphere-2026-253', Anonymous Referee #2, 07 Apr 2026
The manuscript egusphere-2026-253 by Müller and colleagues presents a very nice work on the global methanol budget.
They have used IASI satellite data to invert the a-priori emissions with the support of the MAGRITTE model.
Importantly, they have bias-corrected the IASI data, which appear to be largely underestimated. Using the corrected data for inverse modelling gives an updated methanol budget, which is however mostly in line with recent literature (e.g. Bates et al., 2021), but with some significant changes (e.g. larger biogenic emissions).I very much appreciate the completeness of the work, as well as the writing style, which helps the reader through this nice study. I have only a few comments on the manuscript, and I hope these may help the authors to improve an already excellent manuscript.
Section 2.5.2: While secondary production accounts for ~15--30% of the total emissions, I wonder how accurate this estimate may be. Nicely, a brief discussion is presented in lines 554--556, showing that changing the overall yield of CH3O2+OH (from 11.4% to 13%) does not change the results. However, it is stated (line 240) that many other uncertainties are present in the chemical production.
Would the consideration of these uncertainties considerably change any of the results obtained in the inversion? Additionally, I wonder how well RO2 is represented in the MAGRITTE model. I assume that most of it is coming from the oxidation of CH4, and therefore I would appreciate some additional discussion on the simulation of the OH fields in the model.Section 3: It is very interesting to note that the MAGRITTE model inversion is able to reproduce the observations in an exceptional way. Furthermore, I appreciate the investigation of the possible bias present in the IASIv4 data, which I consider the real main strength of this manuscript. However, I wonder if the authors could elaborate on the risk of using only an observational dataset over North America. Is this region really representative of the IASI bias? Based on the work of Bates et al. (2021), North America is mostly influenced by biogenic emissions, while biomass burning as well as chemical formation are comparatively much lower. Could the IASI bias be different in other areas of the globe, for example in regions strongly influenced by biomass burning or over the tropics, due to the much stronger influence of methanol chemical production?
Figure 9: Based on what is presented (see, for example, line 385), the focus of the inversion is on terrestrial emissions, and therefore the IASI data over oceans were excluded. I would very much appreciate it if all figures including IASI data could be masked over the ocean, to avoid confusion during reading.
Line 600: It would be great if the Spearman correlation could also be listed, to provide a more complete overview of the comparison.
Citation: https://doi.org/10.5194/egusphere-2026-253-RC2 -
AC2: 'Reply on RC2', Jean-François Muller, 10 Apr 2026
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2026/egusphere-2026-253/egusphere-2026-253-AC2-supplement.pdf
-
AC2: 'Reply on RC2', Jean-François Muller, 10 Apr 2026
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Bruno Franco
Lieven Clarisse
Crist Amelynck
Niels Schoon
Bert Verreyken
Beata Opacka
Corinne Vigouroux
Emmanuel Mahieu
Maria Makarova
Kimberly Strong
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Supplement
(5170 KB) - BibTeX
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- Final revised paper