the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Sep 2025
Global VOC emissions quantified from inversion of TROPOMI spaceborne formaldehyde and glyoxal data
Abstract. Volatile organic compounds (VOCs) are key precursors of tropospheric ozone and secondary organic aerosols, a major component of PM2.5, and several aromatic VOCs are toxic. Glyoxal is a short-lived oxidation product of many VOCs, yet global models consistently underestimate its abundance, indicating a substantial missing source. Here, we derive improved estimates of global biogenic, pyrogenic, and anthropogenic VOC emissions and new constraints on the atmospheric glyoxal budget, based on the first joint inversion of TROPOMI formaldehyde and glyoxal columns using the adjoint of the MAGRITTEv1.2 chemical transport model. For 2021, the global NMVOC flux is estimated at 1070 Tg/yr, 19 % above bottom-up estimates, partitioned into 749 Tg from vegetation, 102 Tg from biomass burning, and 219 Tg from anthropogenic activity. Emissions of anthropogenic glyoxal precursors are 43 % higher globally when constrained by satellite data compared with inventory-based simulations, with large underestimations in India, China, and Africa. The total glyoxal source is estimated at 100 Tg/yr, of which 41 % originates from unidentified VOCs, predominantly biogenic and concentrated in the Tropics. Likely contributors include poorly represented formation pathway in isoprene oxidation under low-NOx conditions and an underestimated contribution of monoterpenes. Validation against Pandonia Global Network, in situ, and MAX-DOAS datasets confirms improved agreement of the satellite-constrained model relative to the model based on inventory data alone.
-
Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
-
Preprint
(10692 KB)
-
Supplement
(1257 KB)
-
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(10692 KB) - Metadata XML
-
Supplement
(1257 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2025-4036', Anonymous Referee #1, 10 Dec 2025
- AC1: 'Reply on RC1', Trissevgeni Stavrakou, 16 Dec 2025
-
RC2: 'Comment on egusphere-2025-4036', Anonymous Referee #2, 12 Dec 2025
This work developed posteriori emissions of VOCs (Volatile Organic Compounds) by sectors based on the first joint inversion of TROPOMI formaldehyde and glyoxal columns using the adjoint of the MAGRITTE model. This is very important work given the high uncertainties of VOC emissions at both regional and global scales. The methodology is solid, the figures are great, and the analyses are comprehensive. I recommend authors to provide more clarifications on the chemical characteristics of the unidentified VOCs. Apart from the bias in the total VOC emissions, the speciation process is another source of uncertainty and can contribute to the bias of formaldehyde and glyoxal simulations. It would be great if this can be discussed in the paper.
My detailed comments are provided as below.
- Page 1, Line 10: for the unidentified VOCs, how does the model deal with this species in chemistry?
- Page 5, Line 130-133: it’s really nice toe see the uncertainty analyses for the HCHO and CHOCHO retrievals from TROPOMI.
- Page 9, Line 266: the uptake coefficient is really high. Is it the initial uptake coefficient or the coefficient at stable?
- Page 10, Sect. 3.2: in the inversion, how does it work to provide emission constraints for different glyoxal precursors? Does it keep the relative percentage (VOC profiles) unchanged, and only tune the total emissions, or the profiles are also tuned?
- Page 17, Fig. 3: different revision directions for Eastern US and Eastern China based on OMI and TROPOMI. Can you elaborate more on this?
- Page 19, Line 445: still curious about the chemistry of UVOC.
- Page 20, Fig. 4: can you add legends in the figure? Although you have described this in the caption, it would be better to show them directly in the figure too.
- Page 22, Line 476: this is very useful information. The simulations over Southeast US are always off, so maybe we need both HCHO and CHOCHO constraints to revise the biogenic emissions.
- Page 22, Line 497: Apart from the total VOCs, the speciation can play an important role in model simulations. I understand it’s not quantified in the inversion, but can you explain more about the potential role of VOC speciation in your analyses, especially glyoxal inversion?
- Page 24, Line 521-523: the same question as #4. I’m curious how the inversion model derives the optimized emissions for glyoxal precursors.
- Sect. 4.5 – Sect. 4.7 are all about the model evaluations. Can you re-organize these sections? It would be better move them from Results to a new session like “Model evaluations”.
Citation: https://doi.org/10.5194/egusphere-2025-4036-RC2 - AC2: 'Reply on RC2', Trissevgeni Stavrakou, 16 Dec 2025
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2025-4036', Anonymous Referee #1, 10 Dec 2025
This manuscript presents an important study that uses TROPOMI HCHO and CHOCHO data to quantify global VOC emissions from biogenic, pyrogenic and anthropogenic sources. The results indicate a large proportion of unidentified VOCs over the tropics, which is an important finding that will motivate a lot of future studies. The manuscript is very well done, and the results are interesting and convincing. I only have a few minor comments.
- The inversion framework relies on TROPOMI HCHO and CHOCHO retrievals, but these products are themselves subject to uncertainties. As the authors show, CTMs substantially underestimate CHOCHO, yet the TROPOMI retrievals use CTM a priori profiles to compute air mass factors. It is unclear how uncertainties in these a priori profiles propagate into the inversion. It would be informative to assess how the retrieved HCHO and CHOCHO column densities would change if air mass factors were recalculated using CTM fields updated with the optimized VOC emissions.
- The inversion framework appears to attribute model–satellite discrepancies in HCHO and CHOCHO solely to emission errors. However, both species are secondary products, and their yields depend on chemical mechanisms and NOx levels. It is therefore not clear how much of the discrepancy arises from uncertainties in HCHO and CHOCHO production pathways rather than emission errors. It would be helpful for the authors to comment on how the inversion accounts for, or is affected by, these chemical uncertainties.
- Because satellite retrievals are available only under clear-sky conditions, sampling biases in HCHO and CHOCHO are likely. The authors note that CHOCHO sinks may differ under cloudy conditions, but it is unclear how such sampling biases are treated within the inversion framework and how they might influence the emission estimates. A brief discussion of this issue would strengthen the manuscript.
- TROPOMI overpasses occur around 2 PM local time, when biogenic VOC emissions typically peak. It is not clear whether the inferred biogenic VOC emissions represent instantaneous emissions at overpass time or whether they are scaled to a daily mean. Clarification on this point would help interpret the emission magnitudes.
- Figure 4: Add figure legend.
Citation: https://doi.org/10.5194/egusphere-2025-4036-RC1 - AC1: 'Reply on RC1', Trissevgeni Stavrakou, 16 Dec 2025
-
RC2: 'Comment on egusphere-2025-4036', Anonymous Referee #2, 12 Dec 2025
This work developed posteriori emissions of VOCs (Volatile Organic Compounds) by sectors based on the first joint inversion of TROPOMI formaldehyde and glyoxal columns using the adjoint of the MAGRITTE model. This is very important work given the high uncertainties of VOC emissions at both regional and global scales. The methodology is solid, the figures are great, and the analyses are comprehensive. I recommend authors to provide more clarifications on the chemical characteristics of the unidentified VOCs. Apart from the bias in the total VOC emissions, the speciation process is another source of uncertainty and can contribute to the bias of formaldehyde and glyoxal simulations. It would be great if this can be discussed in the paper.
My detailed comments are provided as below.
- Page 1, Line 10: for the unidentified VOCs, how does the model deal with this species in chemistry?
- Page 5, Line 130-133: it’s really nice toe see the uncertainty analyses for the HCHO and CHOCHO retrievals from TROPOMI.
- Page 9, Line 266: the uptake coefficient is really high. Is it the initial uptake coefficient or the coefficient at stable?
- Page 10, Sect. 3.2: in the inversion, how does it work to provide emission constraints for different glyoxal precursors? Does it keep the relative percentage (VOC profiles) unchanged, and only tune the total emissions, or the profiles are also tuned?
- Page 17, Fig. 3: different revision directions for Eastern US and Eastern China based on OMI and TROPOMI. Can you elaborate more on this?
- Page 19, Line 445: still curious about the chemistry of UVOC.
- Page 20, Fig. 4: can you add legends in the figure? Although you have described this in the caption, it would be better to show them directly in the figure too.
- Page 22, Line 476: this is very useful information. The simulations over Southeast US are always off, so maybe we need both HCHO and CHOCHO constraints to revise the biogenic emissions.
- Page 22, Line 497: Apart from the total VOCs, the speciation can play an important role in model simulations. I understand it’s not quantified in the inversion, but can you explain more about the potential role of VOC speciation in your analyses, especially glyoxal inversion?
- Page 24, Line 521-523: the same question as #4. I’m curious how the inversion model derives the optimized emissions for glyoxal precursors.
- Sect. 4.5 – Sect. 4.7 are all about the model evaluations. Can you re-organize these sections? It would be better move them from Results to a new session like “Model evaluations”.
Citation: https://doi.org/10.5194/egusphere-2025-4036-RC2 - AC2: 'Reply on RC2', Trissevgeni Stavrakou, 16 Dec 2025
Peer review completion
Journal article(s) based on this preprint
Data sets
Global top-down VOC emissions based on TROPOMI formaldehyde and glyoxal data (Version 1) [Data set] Y. Sfendla et al. https://doi.org/10.18758/52E4U9EN
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 347 | 186 | 31 | 564 | 51 | 18 | 20 |
- HTML: 347
- PDF: 186
- XML: 31
- Total: 564
- Supplement: 51
- BibTeX: 18
- EndNote: 20
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
Yasmine Sfendla
Trissevgeni Stavrakou
Jean-François Müller
Glenn-Michael Oomen
Beata Opacka
Thomas Danckaert
Isabelle De Smedt
Christophe Lerot
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(10692 KB) - Metadata XML
-
Supplement
(1257 KB) - BibTeX
- EndNote
- Final revised paper
This manuscript presents an important study that uses TROPOMI HCHO and CHOCHO data to quantify global VOC emissions from biogenic, pyrogenic and anthropogenic sources. The results indicate a large proportion of unidentified VOCs over the tropics, which is an important finding that will motivate a lot of future studies. The manuscript is very well done, and the results are interesting and convincing. I only have a few minor comments.