the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 19 Sep 2023
Weekly-derived top-down VOC fluxes over Europe from TROPOMI HCHO data in 2018–2021
Glenn-Michael Oomen
Jean-François Müller
Trissevgeni Stavrakou
Isabelle De Smedt
Thomas Blumenstock
Rigel Kivi
Maria Makarova
Mathias Palm
Amelie Röhling
Corinne Vigouroux
Martina M. Friedrich
Udo Frieß
François Hendrick
Alexis Merlaud
Ankie Piters
Andreas Richter
Michel Van Roozendael
Thomas Wagner
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.
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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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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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- Final revised paper
Journal article(s) based on this preprint
Glenn-Michael Oomen et al.
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-1972', Anonymous Referee #1, 02 Oct 2023
For the past 20 years, the BIRA group has been working on top-down inversions of VOC emissions using satellite-based formaldehyde observations. This paper was the latest installment of that effort, using the high spatiotemporal resolution observations from TROPOMI. In my view, this was a well thoughtout paper that described most of the important details that went into the inversion process. The highlights of the paper include (1) a detailed description of the error covariance matrices, (2) the use of ground-based measurements to correct for the satellite HCHO biases, and (3) a series of inversion experiments to determine the sensitivities of the inversion to the different model/data assumptions or bias correction. All of these contents added to the scientific robustness of the work and improved the community's general understanding of the use of satellite constraints in top-down emission inversions.The paper is extremely well written with clear logic and descriptions of methods and results. I have only minor editorial comments. Overall, I would recommend that the paper be published after minor revisions.Lines 55-56: "The emissions of biogenic VOCs ... one month.": Please revise this sentence to improve readability.Line 61: "those compounds":please change to "BVOCs"Lines 64-68: I personally think that saying a particular emission estimate is higher/lower than the MEGAN inventory is not very useful, since (as the authors also pointed out) BVOC emissions estimated from MEGAN can be very different depending on the input PFT data, meteorological data, year of simulation, and also model resolution. I would strongly recommend that the authors revise these statements to give numbers, which would also give the readers a feel of the uncertainty in top-down/bottom-up BVOC emission estimates over Europe.Section 2 and lines 335-340: Because a strict cloud filtering was applied, the HCHO column dataset used for the inversion may have a 'clear-sky bias', i.e., it is biased high because it only sampled days when the cloud cover was very low. Did the authors consider this when doing the bias correction using the ground-based measurements and when performing the inversion? If so, how? Was the optimization only applied to simulated days/grids with no cloud cover? Did the final weekly emission inversion accounted for the effects of cloud cover?Line 215: "The model": Please specify which model you are referring to to improve clarity.Citation: https://doi.org/
10.5194/egusphere-2023-1972-RC1 - AC1: 'Reply on RC1', Glenn-Michael Oomen, 10 Nov 2023
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RC2: 'Comment on egusphere-2023-1972', Anonymous Referee #2, 10 Oct 2023
The paper by Oomen et al presents top-down VOC emissions over Europe derived from TROPOMI over a four-year period. The authors exploit the high performance of TROPOMI to derive the first weekly top-down VOC emissions separating biogenic, biomass burning and anthropogenic emissions over Europe. They propose a dedicated validation of the HCHO columns using FTIR ground-based measurement in Europe to adjust the bias correction to the European domain and use the corrected columns for the inversion. The inversions are performed from May to September each year from 2018 to 2021 and show an increase of biogenic and biomass burning emissions and a decrease of anthropogenic emissions. The authors demonstrate the improvement given by weekly-derived emissions compared to monthly ones. They provide a tentative of evaluation of the results with independent ground-based measurements and stress the need for additional ground-based measurements of HCHO in Europe, especially in the South, to reinforce the evaluation/validation capabilities, which remain poor. They also provide an interesting sensitivity study which underlines all the difficulties to derive accurate VOC emissions from HCHO satellite observations.
The paper is well structured, written and documented. It provides a step forward in inverse modelling of VOC emissions at high temporal and spatial resolution with TROPOMI. The paper is suitable for publication in ACP after some clarifications.
Main comments:
- HCHO column validation: the authors use FTIR measurements in Europe to validate and propose a bias correction to the HCHO columns to be used in the inversion. Most of the FTIR stations are in the northern part of the domain where emissions and columns are smaller, it may introduce a bias in the bias correction for the large columns, not well represented in the north. The authors stress the lack of ground-based measurement in Southern Europe and its potential impacts in their discussion, but I wonder if they could use FTIR stations in other part of the world, where HCHO columns are higher and similar to the columns in Southern Europe to complement their validation and ensure they do not introduce a bias in the correction.
- Model evaluation: the comparison with MAX-DOAS measurements and optimized HCHO columns does not show any improvement (except in Greece). The authors state that this might be due to measurements of the MAX-DOAS instruments during cloudy days. Did they try to consider only clear-sly days in their comparison to quantify the impact? It might be interesting.
- Biogenic emissions: in the inversion setup (lines 256-257), it is written that the emission parameters are applied to both isoprene and monoterpene, but the results are only discussed in terms of isoprene emissions in the manuscript. The authors should add a discussion on the monoterpene emissions if they have effectively inversed them or explain why they do not show the results.
Specific comments:
- Lines 14-15: the authors should consider giving numbers when they mention the results of their sensitivity study.
- Line 15 and elsewhere, “variable meteorology”, this expression might be confusing. Meteorology is variable by nature. The authors should clarify what they call “variable meteorology”.
- P8, section 2.4 : the authors try to use climatological averages based on measurements in the 90s or early 2000s. They mention the difficulties and that the results should be considered with caution. I wonder if something is known or could be derived from climate simulations for example to quantify how far from now these measurements are when considering temperature increase and land-use changes.
- Line 241: I was confused by the sentence “the inversion is carried out with a time step of 24 hours” whereas the inversion provides weekly emissions. Rephrasing the sentence might be useful to avoid the confusion between the time step of the forward model calculation and the inversion.
- Inversion setup: It is not completely clear which assimilation window is used. Is it the May-September period?
- Line 259: On which basis the 1010molec.cm-2s-1 threshold has been chosen? How many pixels are concerned, and where are they located?
- Line 282: how have the spatial correlation of anthropogenic emission errors been chosen?
- Line 286 and 570-574: is the filtering out of low columns made on individual observations or after the average?
- Line 307-308: Is there a reference that compare the different sensitivity? If yes, it might be interesting to refer to or if not, to provide a plot to illustrate it.
- Line 375-376: are the oceanic data excluded with the filter mentioned line 259 or is it a new filter?
Technical corrections:
- Line 185: replace ‘wth’ by “with”
- Line 359: remove the url.
Citation: https://doi.org/10.5194/egusphere-2023-1972-RC2 - AC1: 'Reply on RC1', Glenn-Michael Oomen, 10 Nov 2023
- AC2: 'Reply on RC2', Glenn-Michael Oomen, 10 Nov 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-1972', Anonymous Referee #1, 02 Oct 2023
For the past 20 years, the BIRA group has been working on top-down inversions of VOC emissions using satellite-based formaldehyde observations. This paper was the latest installment of that effort, using the high spatiotemporal resolution observations from TROPOMI. In my view, this was a well thoughtout paper that described most of the important details that went into the inversion process. The highlights of the paper include (1) a detailed description of the error covariance matrices, (2) the use of ground-based measurements to correct for the satellite HCHO biases, and (3) a series of inversion experiments to determine the sensitivities of the inversion to the different model/data assumptions or bias correction. All of these contents added to the scientific robustness of the work and improved the community's general understanding of the use of satellite constraints in top-down emission inversions.The paper is extremely well written with clear logic and descriptions of methods and results. I have only minor editorial comments. Overall, I would recommend that the paper be published after minor revisions.Lines 55-56: "The emissions of biogenic VOCs ... one month.": Please revise this sentence to improve readability.Line 61: "those compounds":please change to "BVOCs"Lines 64-68: I personally think that saying a particular emission estimate is higher/lower than the MEGAN inventory is not very useful, since (as the authors also pointed out) BVOC emissions estimated from MEGAN can be very different depending on the input PFT data, meteorological data, year of simulation, and also model resolution. I would strongly recommend that the authors revise these statements to give numbers, which would also give the readers a feel of the uncertainty in top-down/bottom-up BVOC emission estimates over Europe.Section 2 and lines 335-340: Because a strict cloud filtering was applied, the HCHO column dataset used for the inversion may have a 'clear-sky bias', i.e., it is biased high because it only sampled days when the cloud cover was very low. Did the authors consider this when doing the bias correction using the ground-based measurements and when performing the inversion? If so, how? Was the optimization only applied to simulated days/grids with no cloud cover? Did the final weekly emission inversion accounted for the effects of cloud cover?Line 215: "The model": Please specify which model you are referring to to improve clarity.Citation: https://doi.org/
10.5194/egusphere-2023-1972-RC1 - AC1: 'Reply on RC1', Glenn-Michael Oomen, 10 Nov 2023
-
RC2: 'Comment on egusphere-2023-1972', Anonymous Referee #2, 10 Oct 2023
The paper by Oomen et al presents top-down VOC emissions over Europe derived from TROPOMI over a four-year period. The authors exploit the high performance of TROPOMI to derive the first weekly top-down VOC emissions separating biogenic, biomass burning and anthropogenic emissions over Europe. They propose a dedicated validation of the HCHO columns using FTIR ground-based measurement in Europe to adjust the bias correction to the European domain and use the corrected columns for the inversion. The inversions are performed from May to September each year from 2018 to 2021 and show an increase of biogenic and biomass burning emissions and a decrease of anthropogenic emissions. The authors demonstrate the improvement given by weekly-derived emissions compared to monthly ones. They provide a tentative of evaluation of the results with independent ground-based measurements and stress the need for additional ground-based measurements of HCHO in Europe, especially in the South, to reinforce the evaluation/validation capabilities, which remain poor. They also provide an interesting sensitivity study which underlines all the difficulties to derive accurate VOC emissions from HCHO satellite observations.
The paper is well structured, written and documented. It provides a step forward in inverse modelling of VOC emissions at high temporal and spatial resolution with TROPOMI. The paper is suitable for publication in ACP after some clarifications.
Main comments:
- HCHO column validation: the authors use FTIR measurements in Europe to validate and propose a bias correction to the HCHO columns to be used in the inversion. Most of the FTIR stations are in the northern part of the domain where emissions and columns are smaller, it may introduce a bias in the bias correction for the large columns, not well represented in the north. The authors stress the lack of ground-based measurement in Southern Europe and its potential impacts in their discussion, but I wonder if they could use FTIR stations in other part of the world, where HCHO columns are higher and similar to the columns in Southern Europe to complement their validation and ensure they do not introduce a bias in the correction.
- Model evaluation: the comparison with MAX-DOAS measurements and optimized HCHO columns does not show any improvement (except in Greece). The authors state that this might be due to measurements of the MAX-DOAS instruments during cloudy days. Did they try to consider only clear-sly days in their comparison to quantify the impact? It might be interesting.
- Biogenic emissions: in the inversion setup (lines 256-257), it is written that the emission parameters are applied to both isoprene and monoterpene, but the results are only discussed in terms of isoprene emissions in the manuscript. The authors should add a discussion on the monoterpene emissions if they have effectively inversed them or explain why they do not show the results.
Specific comments:
- Lines 14-15: the authors should consider giving numbers when they mention the results of their sensitivity study.
- Line 15 and elsewhere, “variable meteorology”, this expression might be confusing. Meteorology is variable by nature. The authors should clarify what they call “variable meteorology”.
- P8, section 2.4 : the authors try to use climatological averages based on measurements in the 90s or early 2000s. They mention the difficulties and that the results should be considered with caution. I wonder if something is known or could be derived from climate simulations for example to quantify how far from now these measurements are when considering temperature increase and land-use changes.
- Line 241: I was confused by the sentence “the inversion is carried out with a time step of 24 hours” whereas the inversion provides weekly emissions. Rephrasing the sentence might be useful to avoid the confusion between the time step of the forward model calculation and the inversion.
- Inversion setup: It is not completely clear which assimilation window is used. Is it the May-September period?
- Line 259: On which basis the 1010molec.cm-2s-1 threshold has been chosen? How many pixels are concerned, and where are they located?
- Line 282: how have the spatial correlation of anthropogenic emission errors been chosen?
- Line 286 and 570-574: is the filtering out of low columns made on individual observations or after the average?
- Line 307-308: Is there a reference that compare the different sensitivity? If yes, it might be interesting to refer to or if not, to provide a plot to illustrate it.
- Line 375-376: are the oceanic data excluded with the filter mentioned line 259 or is it a new filter?
Technical corrections:
- Line 185: replace ‘wth’ by “with”
- Line 359: remove the url.
Citation: https://doi.org/10.5194/egusphere-2023-1972-RC2 - AC1: 'Reply on RC1', Glenn-Michael Oomen, 10 Nov 2023
- AC2: 'Reply on RC2', Glenn-Michael Oomen, 10 Nov 2023
Peer review completion
Journal article(s) based on this preprint
Glenn-Michael Oomen et al.
Data sets
TROPOMI-based isoprene emissions over Europe Glenn-Michael Oomen https://emissions.aeronomie.be/index.php/tropomi-based/isoprene-eu
TROPOMI-based biomass burning emissions over Europe Glenn-Michael Oomen https://emissions.aeronomie.be/index.php/tropomi-based/fire-eu
TROPOMI-based anthropogenic VOC emissions over Europe Glenn-Michael Oomen https://emissions.aeronomie.be/index.php/tropomi-based/anthropogenic-eu
Glenn-Michael Oomen et al.
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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
(21825 KB) - Metadata XML
-
Supplement
(19529 KB) - BibTeX
- EndNote
- Final revised paper