the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 06 Nov 2023
Bias characterization of OMI HCHO columns based on FTIR and aircraft measurements and impact on top-down emission estimates
Abstract. Spaceborne formaldehyde (HCHO) measurements constitute an excellent proxy for the sources of non-methane volatile organic compounds (NMVOCs). Past studies suggested substantial overestimation of NMVOC emissions in state-of-the-art inventories over major source regions. Here, the QA4ECV (Quality Assurance for Essential Climate Variables) retrieval of HCHO columns from OMI (Ozone Monitoring Instrument) are evaluated against (1) FTIR (Fourier-transform infrared) column observations at 26 stations worldwide, and (2) aircraft in situ HCHO measurements from campaigns conducted over the U.S. in 2012–2013. Both validation exercises show that OMI underestimates high columns and overestimates low columns. The linear regression of OMI and aircraft-based columns gives ΩOMI = 0.651 Ωairc + 2.95×1015 molec.cm-2, with ΩOMI and Ωairc the OMI and aircraft-derived vertical columns, whereas the regression of OMI and FTIR data givesΩOMI = 0.659 ΩFTIR + 2.02×1015 molec.cm-2. Inverse modelling of NMVOC emissions with a global model based on OMI columns corrected for biases based on those relationships leads to much-improved agreement against FTIR data and HCHO concentrations from 11 aircraft campaigns. The optimized global isoprene emissions (~445 Tg yr-1) are 25 % higher than those obtained without bias correction. The optimized isoprene emissions bear both striking similarities and differences with recently published emissions based on spaceborne isoprene columns from the CrIS (Cross-track Infrared Sounder) sensor. Although the interannual variability of OMI HCHO columns is well understood over regions where biogenic emissions are dominant, and the HCHO trends over China and India clearly reflect anthropogenic emission changes, the observed HCHO decline over Southeastern U.S. remains imperfectly elucidated.
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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.
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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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Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-2456', Anonymous Referee #1, 05 Dec 2023
The authors present a comprehensive and detailed assessment of satellite-based HCHO column measurements from OMI. They perform an evaluation of the columns against ground-based FTIR observations and against aircraft measurements, including both direct column:column comparisons (in the case of the FTIR data) and indirect assessments whereby they use a CTM as intercomparison platform. They find based on both approaches that the QA4ECV OMI HCHO product is biased low for high column amounts and biased high for low column amounts, and derive highly consistent bias corrections based on both the direct and indirect comparison approaches. They then proceed to assess the impact of this bias correction on the VOC emissions that are inferred from the OMI data, interpreting their global results in terms of biogenic/anthropogenic/pyrogenic source contributions and trends, and exploring the consistency of their results with other available constraints including direct isoprene measurements from CrIS.
The paper is extremely well written and thorough and addresses a topic of scientific importance. I appreciate the authors' careful analysis and forthright discussion of uncertainties. I strongly recommend publication and have only minor comments and suggestions.
1) The authors discuss inconsistency and uncertainty in the aircraft HCHO measurements used for satellite evaluation, and come up with a defensible approach for dealing with this. It would be helpful somewhere later on to include a brief discussion of the degree to which these uncertainties could impact (or not) their conclusions about OMI and the resulting emissions.
2) There is a sensitivity inversion (OPT3) included to assess impacts of the prior error assumptions on the inversion results, which I agree is an important test to include. However, the results and conclusions from this test do not seem to be discussed anywhere.
3) 281-290, I am confused here b/c the text first says that E is diagonal but then later the text describes a decorrelation length scale which seems to imply the presence of off-diagonal elements. Please clarify.
4) 543-544, "and comparatively slower increases (< 1%yr−1) in biogenic VOC emissions over many areas due to global warming (e.g. over Amazonia, Southern Africa and Australia) (Fig. 14)."
The phrasing here implies that warming is unequivocally driving a statistically significant, detectable increase in emissions over these regions. Looking at the figure, however, the trend for Amazonia is 0.0%/y and I have a hard time believing that the trends for Southern Africa and Australia are statistically distinguishable from zero. I wonder if what the authors mean to say is that any warming driven isoprene increase is small or undetectable over this period; that is the conclusion I draw from Fig. 14.5) Sections 3.3-3.4, I get the impression that emissions are being optimized on a monthly basis but I don't believe this is explicitly stated. Please specify.
6) In lines 515-520 the authors discuss the difficulty in separating biogenic versus pyrogenic emissions in some regions. I feel that the paper would benefit from a more general discussion of this issue, perhaps earlier on when introducing the inversion methodology. That is, we are solving for 3 separate variables (anthropogenic, biogenic, and pyrogenic VOC emissions) for every grid cell based on a single observed variable (HCHO). To what degree are these terms actually resolved through the inversion, and to what degree does that separation merely rely on the prior and/or only work where (again according to the prior) one source is dominant?
7) The VOC source optimization is by nature indirect and based on the resulting HCHO abundance. The authors should include some assessment or discussion of the extent to which the VOC emission magnitude updates could in fact be compensating for other factors or model errors that affect HCHO (for example, incorrect VOC speciation, uncertainty in the diel cycle of VOC emissions, errors in NOx emissions or in the HCHO lifetime, uncertainties in the chemistry leading to HCHO, etc.).
Citation: https://doi.org/10.5194/egusphere-2023-2456-RC1 - AC1: 'Reply on RC1', J.-F. Müller, 21 Dec 2023
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RC2: 'Comment on egusphere-2023-2456', Anonymous Referee #2, 11 Dec 2023
- AC2: 'Reply on RC2', J.-F. Müller, 21 Dec 2023
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2456', Anonymous Referee #1, 05 Dec 2023
The authors present a comprehensive and detailed assessment of satellite-based HCHO column measurements from OMI. They perform an evaluation of the columns against ground-based FTIR observations and against aircraft measurements, including both direct column:column comparisons (in the case of the FTIR data) and indirect assessments whereby they use a CTM as intercomparison platform. They find based on both approaches that the QA4ECV OMI HCHO product is biased low for high column amounts and biased high for low column amounts, and derive highly consistent bias corrections based on both the direct and indirect comparison approaches. They then proceed to assess the impact of this bias correction on the VOC emissions that are inferred from the OMI data, interpreting their global results in terms of biogenic/anthropogenic/pyrogenic source contributions and trends, and exploring the consistency of their results with other available constraints including direct isoprene measurements from CrIS.
The paper is extremely well written and thorough and addresses a topic of scientific importance. I appreciate the authors' careful analysis and forthright discussion of uncertainties. I strongly recommend publication and have only minor comments and suggestions.
1) The authors discuss inconsistency and uncertainty in the aircraft HCHO measurements used for satellite evaluation, and come up with a defensible approach for dealing with this. It would be helpful somewhere later on to include a brief discussion of the degree to which these uncertainties could impact (or not) their conclusions about OMI and the resulting emissions.
2) There is a sensitivity inversion (OPT3) included to assess impacts of the prior error assumptions on the inversion results, which I agree is an important test to include. However, the results and conclusions from this test do not seem to be discussed anywhere.
3) 281-290, I am confused here b/c the text first says that E is diagonal but then later the text describes a decorrelation length scale which seems to imply the presence of off-diagonal elements. Please clarify.
4) 543-544, "and comparatively slower increases (< 1%yr−1) in biogenic VOC emissions over many areas due to global warming (e.g. over Amazonia, Southern Africa and Australia) (Fig. 14)."
The phrasing here implies that warming is unequivocally driving a statistically significant, detectable increase in emissions over these regions. Looking at the figure, however, the trend for Amazonia is 0.0%/y and I have a hard time believing that the trends for Southern Africa and Australia are statistically distinguishable from zero. I wonder if what the authors mean to say is that any warming driven isoprene increase is small or undetectable over this period; that is the conclusion I draw from Fig. 14.5) Sections 3.3-3.4, I get the impression that emissions are being optimized on a monthly basis but I don't believe this is explicitly stated. Please specify.
6) In lines 515-520 the authors discuss the difficulty in separating biogenic versus pyrogenic emissions in some regions. I feel that the paper would benefit from a more general discussion of this issue, perhaps earlier on when introducing the inversion methodology. That is, we are solving for 3 separate variables (anthropogenic, biogenic, and pyrogenic VOC emissions) for every grid cell based on a single observed variable (HCHO). To what degree are these terms actually resolved through the inversion, and to what degree does that separation merely rely on the prior and/or only work where (again according to the prior) one source is dominant?
7) The VOC source optimization is by nature indirect and based on the resulting HCHO abundance. The authors should include some assessment or discussion of the extent to which the VOC emission magnitude updates could in fact be compensating for other factors or model errors that affect HCHO (for example, incorrect VOC speciation, uncertainty in the diel cycle of VOC emissions, errors in NOx emissions or in the HCHO lifetime, uncertainties in the chemistry leading to HCHO, etc.).
Citation: https://doi.org/10.5194/egusphere-2023-2456-RC1 - AC1: 'Reply on RC1', J.-F. Müller, 21 Dec 2023
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RC2: 'Comment on egusphere-2023-2456', Anonymous Referee #2, 11 Dec 2023
- AC2: 'Reply on RC2', J.-F. Müller, 21 Dec 2023
Peer review completion
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Jean-François Müller
Trissevgeni Stavrakou
Glenn-Michael Oomen
Beata Opacka
Isabelle De Smedt
Alex Guenther
Corinne Vigouroux
Bavo Langerock
Carlos Augusto Bauer Aquino
Michel Grutter
James Hannigan
Frank Hase
Rigel Kivi
Erik Lutsch
Emmanuel Mahieu
Maria Makarova
Jean-Marc Metzger
Isamu Morino
Isao Murata
Tomoo Nagahama
Justus Notholt
Ivan Ortega
Mathias Palm
Amelie Röhling
Wolfgang Stremme
Kimberly Strong
Ralf Sussmann
Alan Fried
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(5823 KB) - Metadata XML
-
Supplement
(3515 KB) - BibTeX
- EndNote
- Final revised paper