the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 19 Jun 2024
Role of chemical production and depositional losses on formaldehyde in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM)
Abstract. Formaldehyde (HCHO) is an important air pollutant due to its direct health effects as an air toxic that contributes to elevated cancer risk, its role in ozone formation, and its role as a product from oxidation of most gas phase reactive organic carbon. We make several updates affecting secondary production of HCHO in the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM) in the Community Multiscale Air Quality (CMAQ) model. Secondary HCHO from isoprene and monoterpenes is increased, correcting an underestimate in the current version. Simulated 2019 June–August surface HCHO during peak photochemical production (11 am–3 pm) increased by 0.6 ppb (32 %) over the southeastern US and by 0.2 ppb (13 %) over the entire contiguous US. The increased HCHO compares more favorably with satellite-based observations from TROPOMI and observations from an aircraft campaign. Evaluation against hourly surface observations indicates a missing nighttime sink for HCHO which can be ameliorated by adding bidirectional exchange of HCHO and a leaf wetness dependent deposition process which increases nighttime deposition, decreasing 2019 June–August nocturnal (8 pm–4 am) surface HCHO by 1.1 ppb (36 %) over the southeastern US and 0.5 ppb (29 %) over the entire contiguous US. The ability of CRACMM to capture peak levels of HCHO at midday is improved, particularly at sites in the northeastern US, while peak levels at southeastern US sites are improved though still lower than observed. Using established risk assessment methods, lifetime exposure of the contiguous U.S. population (~320 million) to ambient HCHO levels predicted here may result in 6200 lifetime cancer cases, 40 % of which are from controllable anthropogenic emissions of nitrogen oxides and reactive organic compounds. Chemistry updates will be available in CRACMM version 2 (CRACMM2) in CMAQv5.5.
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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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Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-1680', J.-F. Müller, 23 Jul 2024
This manuscript presents a comprehensive revision of the chemical mechanism used in the CMAQ model, the CRACMM mechanism. The goal is to achieve a better representation of the chemical production of formaldehyde from its various VOC precursors in CMAQ, mainly motivated by the significance of atmospheric formaldehyde for human health. The paper also presents a detailed evaluation of CMAQ model predictions against in situ, airborne (FIREX) and satellite (TROPOMI) formaldehyde data, and shows that the mechanistic updates generally improve the model performance. A consequence of the updates is an enhancement of formaldehyde abundances, especially over the regions with high biogenic emissions like the southeast US. Next, the model is used to estimate the number of cancer cases due to airborne HCHO in the United States, as well as the controllable fraction of this number.
The paper is very well written, and generally very clear. In my opinion, the order of the sections is not logical and could be changed: the chemistry updates should be presented before the box model simulations and comparisons. The methodologies are appropriate, except for a minor reservation (see further below). I appreciate very much the detailed comparison of CMAQ with formaldehyde measurements and the discussion of discrepancies. I also appreciate the model implementation of bidirectional exchange of formaldehyde, justified on the basis of model comparisons with in situ hourly HCHO data. The overall results, including the cancer risks estimates, appear to be robust. Still, I think an acknowledgment of the remaining mechanistic uncertainties would be welcome in the implications sections, and possibly also in the Abstract.
Main comments
1. I suggest to reorganize the sections in a more logical order. Currently, the results of the box model comparisons with the different mechanism are presented before discussing the mechanistic updates, which is weird. For example AMORE is mentioned in section 2 without telling what it is and how it relates to CRACMM2.
2. CRACMM1 is evaluated against MCM v3.3.1, which is mostly fine. However, although MCM is indeed a very detailed mechanism, it has its limitations, which should be acknowledged. Isoprene oxidation experiments at Juelich have shown that the bulk rate of isomerisation of isoprene hydroxyperoxy radicals is underestimated in MCMv3.3.1, by as much as a factor of 3, with consequences for the production of HOx radicals but also, almost certainly, for HCHO production (since HCHO is produced along with MVK and MACR, which are overestimated in MCMv3.3.1) (Novelli et al., 2020). A crude but effective way to test this would be to modify the MCM mechanism following Novelli et al. (see their Table 2). Note that there might be also caveats regarding the accuracy of MCM predictions for monoterpenes and for anthropogenic NMVOCs.
3. The estimate of cancer risks (and especially the controllable part) is likely underestimated, given the underestimations of HCHO abundances e.g. in oil and gas production areas. This should be better acknowledged in the implications section of the paper.
Minor comments
l. 73 The last paragraph of the introduction should better present the structure of the paper.
l. 271 "autoxidation of PINAL and LIMAL" : I suppose you mean PINALP and LIMALP, since pinonaldehyde and limonaldehyde do not undergo autoxidation.
l. 404-405: Decreases in HOx due to heterogeneous chemistry would indeed increase the lifetime of HCHO but also increase HCHO production from many VOCs including methane.
l. 440-442: The TROPOMI HCHO VCDs are scaled up by 25% when the column exceeds 8E15 molecules cm-2 to account for the low bias at high HCHO levels (De Smedt 2021). How does that compare with the TROPOMI HCHO evaluation against FTIR data from e.g. Oomen et al. 2024 and Vigouroux et al. 2020 ? For very large columns, the discrpancy between FTIR and TROPOMI is likely much larger than 25%. The potential consequences for the comparisons presented here should be briefly discussed.
l. 597 "Biogenic isoprene emissions could be low in CMAQ": I agree. How does the annual or seasonal emissions of isoprene from CMAQ compare with determinations based on MEGAN (see e.g. Kaiser et al. 2018) or from inverse modelling of satellite data (e.g. Muller et al., 2024) ?
l. 629 and Fig. 6: I don't understand the separation of "bidirectional flux" and "leaf wetness deposition". Isn't deposition included in the representation of bidirectional flux? This should be clarified. Does the model of Shutter et al. account for the re-volatilization of formaldehyde when the leaf water evaporates (and when the Henry's law constant of HCHO decreases due to warming temperature), i.e. during daytime?
Technical comments
l. 80 "are avaluated" --> "is evaluated"References
Kaiser, J., et al., High-resolution inversion of OMI formaldehyde columns to quantify isoprene emission on ecosystem-relevant scales: application to the southeast US, Atmos. Chem. Phys., 18, https://doi.org/10.5194/acp-18-5483-2018, 2018.
Muller, J.-F., et al., Bias correction of OMI HCHO columns based on FTIR and aircraft measurements and impact on top-down emission estimates, Atmos. Chem. Phys., 24, 2207, https://doi.org/10.5194/acp-24-2207-2024, 2024.
Novelli, A., et al., Importance of isomerization reactions for OH radical regeneration from the photo-oxidation of isoprene investigated in the atmospheric simulation chamber SAPHIR, Atmos. Chem. Phys., 20, 3333-3355, https://doi.org/10.5194/acp-20-3333-2020, 2020.
Oomen, G.-M., et al., Weekly-derived top-down volatile-organic-compound fluxes over Europe from TROPOMI HCHO data from 2018 to 2021, Atmos. Chem. Phys., 24, 449-474, https://doi.org/10.5194/acp-24-449-2024, 2024.
Vigouroux, C., et al., TROPOMI/S5P formaldehyde validation using an extensive network of ground-based FTIR stations, Atmos. Meas. Tech., 13, 3751, https://doi.org/10.5194/amt-13-3751-2020, 2020.Citation: https://doi.org/10.5194/egusphere-2024-1680-RC1 -
RC2: 'Comment on egusphere-2024-1680', Narendra Ojha, 11 Aug 2024
The mechanism of secondary formaldehyde (HCHO) production has been updated in the regional air quality model – CMAQ. In addition, a night-time sink has been implemented. These updates helped model in better capturing the magnitudes in satellite and aircraft-based observations, and a diurnal change seen in field measurements.
Model results have been used to assess the health impact of HCHO on contiguous US. Manuscript presents significant advancements in chemistry and deposition of HCHO and is recommended for publication in ACP. However, following comments are offered for authors to consider during the revision.
- L.50-60: Add 1-2 statements on the uncertainty in anthropogenic and biogenic emissions of HCHO and precursors over the study region, from literature or by analyzing different emission inventories.
- L.96-100: Add more rationale behind setting NOx with 1 ppb NO2. What were the initial mixing ratios of major HCHO precursors in box model? Wouldn’t it be better to run 2-3 different cases representing urban and clean environments and then select all reactions to optimize chemistry for “regional-scale” modelling?
- L.360: “Biogenic emissions……using the BEIS module”. Since the biogenic emissions are major source for HCHO, some additional details should have been provided on this module / method. Difference with other widely used models like MEGAN and estimation on how much total biogenic emission it estimates (e.g. for isoprene) could be valuable.
- L.382-385: Discuss how the chemical updates affected the mixing ratios of isoprene and monoterpene.
- Organization of the manuscript could be improved. The observational datasets and technical details (section 5.1) could be discussed earlier, before entering the results and discussions.
- L.455-464: This is important result. The effect of emission uncertainty should be discussed in introduction section (as I have mentioned in my comment # 1). Large underestimation over California suggest that emissions / primary production may have large bias (and could have affected estimation of health effect). More discussion on this may be added.
- Figure 5 – rightmost panel: check and make uniform the use of “southeastern” or “eastern US” between text and figures.
Citation: https://doi.org/10.5194/egusphere-2024-1680-RC2 - AC1: 'Response to reviews of egusphere-2024-1680', Havala Pye, 16 Sep 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-1680', J.-F. Müller, 23 Jul 2024
This manuscript presents a comprehensive revision of the chemical mechanism used in the CMAQ model, the CRACMM mechanism. The goal is to achieve a better representation of the chemical production of formaldehyde from its various VOC precursors in CMAQ, mainly motivated by the significance of atmospheric formaldehyde for human health. The paper also presents a detailed evaluation of CMAQ model predictions against in situ, airborne (FIREX) and satellite (TROPOMI) formaldehyde data, and shows that the mechanistic updates generally improve the model performance. A consequence of the updates is an enhancement of formaldehyde abundances, especially over the regions with high biogenic emissions like the southeast US. Next, the model is used to estimate the number of cancer cases due to airborne HCHO in the United States, as well as the controllable fraction of this number.
The paper is very well written, and generally very clear. In my opinion, the order of the sections is not logical and could be changed: the chemistry updates should be presented before the box model simulations and comparisons. The methodologies are appropriate, except for a minor reservation (see further below). I appreciate very much the detailed comparison of CMAQ with formaldehyde measurements and the discussion of discrepancies. I also appreciate the model implementation of bidirectional exchange of formaldehyde, justified on the basis of model comparisons with in situ hourly HCHO data. The overall results, including the cancer risks estimates, appear to be robust. Still, I think an acknowledgment of the remaining mechanistic uncertainties would be welcome in the implications sections, and possibly also in the Abstract.
Main comments
1. I suggest to reorganize the sections in a more logical order. Currently, the results of the box model comparisons with the different mechanism are presented before discussing the mechanistic updates, which is weird. For example AMORE is mentioned in section 2 without telling what it is and how it relates to CRACMM2.
2. CRACMM1 is evaluated against MCM v3.3.1, which is mostly fine. However, although MCM is indeed a very detailed mechanism, it has its limitations, which should be acknowledged. Isoprene oxidation experiments at Juelich have shown that the bulk rate of isomerisation of isoprene hydroxyperoxy radicals is underestimated in MCMv3.3.1, by as much as a factor of 3, with consequences for the production of HOx radicals but also, almost certainly, for HCHO production (since HCHO is produced along with MVK and MACR, which are overestimated in MCMv3.3.1) (Novelli et al., 2020). A crude but effective way to test this would be to modify the MCM mechanism following Novelli et al. (see their Table 2). Note that there might be also caveats regarding the accuracy of MCM predictions for monoterpenes and for anthropogenic NMVOCs.
3. The estimate of cancer risks (and especially the controllable part) is likely underestimated, given the underestimations of HCHO abundances e.g. in oil and gas production areas. This should be better acknowledged in the implications section of the paper.
Minor comments
l. 73 The last paragraph of the introduction should better present the structure of the paper.
l. 271 "autoxidation of PINAL and LIMAL" : I suppose you mean PINALP and LIMALP, since pinonaldehyde and limonaldehyde do not undergo autoxidation.
l. 404-405: Decreases in HOx due to heterogeneous chemistry would indeed increase the lifetime of HCHO but also increase HCHO production from many VOCs including methane.
l. 440-442: The TROPOMI HCHO VCDs are scaled up by 25% when the column exceeds 8E15 molecules cm-2 to account for the low bias at high HCHO levels (De Smedt 2021). How does that compare with the TROPOMI HCHO evaluation against FTIR data from e.g. Oomen et al. 2024 and Vigouroux et al. 2020 ? For very large columns, the discrpancy between FTIR and TROPOMI is likely much larger than 25%. The potential consequences for the comparisons presented here should be briefly discussed.
l. 597 "Biogenic isoprene emissions could be low in CMAQ": I agree. How does the annual or seasonal emissions of isoprene from CMAQ compare with determinations based on MEGAN (see e.g. Kaiser et al. 2018) or from inverse modelling of satellite data (e.g. Muller et al., 2024) ?
l. 629 and Fig. 6: I don't understand the separation of "bidirectional flux" and "leaf wetness deposition". Isn't deposition included in the representation of bidirectional flux? This should be clarified. Does the model of Shutter et al. account for the re-volatilization of formaldehyde when the leaf water evaporates (and when the Henry's law constant of HCHO decreases due to warming temperature), i.e. during daytime?
Technical comments
l. 80 "are avaluated" --> "is evaluated"References
Kaiser, J., et al., High-resolution inversion of OMI formaldehyde columns to quantify isoprene emission on ecosystem-relevant scales: application to the southeast US, Atmos. Chem. Phys., 18, https://doi.org/10.5194/acp-18-5483-2018, 2018.
Muller, J.-F., et al., Bias correction of OMI HCHO columns based on FTIR and aircraft measurements and impact on top-down emission estimates, Atmos. Chem. Phys., 24, 2207, https://doi.org/10.5194/acp-24-2207-2024, 2024.
Novelli, A., et al., Importance of isomerization reactions for OH radical regeneration from the photo-oxidation of isoprene investigated in the atmospheric simulation chamber SAPHIR, Atmos. Chem. Phys., 20, 3333-3355, https://doi.org/10.5194/acp-20-3333-2020, 2020.
Oomen, G.-M., et al., Weekly-derived top-down volatile-organic-compound fluxes over Europe from TROPOMI HCHO data from 2018 to 2021, Atmos. Chem. Phys., 24, 449-474, https://doi.org/10.5194/acp-24-449-2024, 2024.
Vigouroux, C., et al., TROPOMI/S5P formaldehyde validation using an extensive network of ground-based FTIR stations, Atmos. Meas. Tech., 13, 3751, https://doi.org/10.5194/amt-13-3751-2020, 2020.Citation: https://doi.org/10.5194/egusphere-2024-1680-RC1 -
RC2: 'Comment on egusphere-2024-1680', Narendra Ojha, 11 Aug 2024
The mechanism of secondary formaldehyde (HCHO) production has been updated in the regional air quality model – CMAQ. In addition, a night-time sink has been implemented. These updates helped model in better capturing the magnitudes in satellite and aircraft-based observations, and a diurnal change seen in field measurements.
Model results have been used to assess the health impact of HCHO on contiguous US. Manuscript presents significant advancements in chemistry and deposition of HCHO and is recommended for publication in ACP. However, following comments are offered for authors to consider during the revision.
- L.50-60: Add 1-2 statements on the uncertainty in anthropogenic and biogenic emissions of HCHO and precursors over the study region, from literature or by analyzing different emission inventories.
- L.96-100: Add more rationale behind setting NOx with 1 ppb NO2. What were the initial mixing ratios of major HCHO precursors in box model? Wouldn’t it be better to run 2-3 different cases representing urban and clean environments and then select all reactions to optimize chemistry for “regional-scale” modelling?
- L.360: “Biogenic emissions……using the BEIS module”. Since the biogenic emissions are major source for HCHO, some additional details should have been provided on this module / method. Difference with other widely used models like MEGAN and estimation on how much total biogenic emission it estimates (e.g. for isoprene) could be valuable.
- L.382-385: Discuss how the chemical updates affected the mixing ratios of isoprene and monoterpene.
- Organization of the manuscript could be improved. The observational datasets and technical details (section 5.1) could be discussed earlier, before entering the results and discussions.
- L.455-464: This is important result. The effect of emission uncertainty should be discussed in introduction section (as I have mentioned in my comment # 1). Large underestimation over California suggest that emissions / primary production may have large bias (and could have affected estimation of health effect). More discussion on this may be added.
- Figure 5 – rightmost panel: check and make uniform the use of “southeastern” or “eastern US” between text and figures.
Citation: https://doi.org/10.5194/egusphere-2024-1680-RC2 - AC1: 'Response to reviews of egusphere-2024-1680', Havala Pye, 16 Sep 2024
Peer review completion
Journal article(s) based on this preprint
Data sets
NASA FIREX-AQ 2019 DC8 Aircraft Data FIREX-AQ Team https://www-air.larc.nasa.gov/cgi-bin/ArcView/firexaq
KaiserLab-GeorgiaTech/long-term-HCHO-monitoring_efforts_datasets Kaiser Lab Georgia Tech https://doi.org/10.5281/zenodo.10855090
NASA GROUND-GOETHALS-FIELD 2023 Data NASA https://www-air.larc.nasa.gov/cgi-bin/ArcView/listos.2023
UWFPS 2017 Ground Sites Data Download UWFPS Team https://csl.noaa.gov/groups/csl7/measurements/2017uwfps/Ground/DataDownload/
Model code and software
CMAQ Github Repository US Environmental Protection Agency https://github.com/USEPA/CMAQ
CMAQ Version 5.4 US EPA Office of Research and Development https://doi.org/10.5281/zenodo.7218076
CRACMM Github Repository US Environmental Protection Agency https://github.com/USEPA/CRACMM
Framework for 0-D Atmospheric Modeling (F0AM) Github Repository Glenn M. Wolfe https://github.com/AirChem/F0AM
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Cited
1 citations as recorded by crossref.
T. Nash Skipper
Emma L. D'Ambro
Forwood C. Wiser
V. Faye McNeill
Rebecca H. Schwantes
Barron H. Henderson
Ivan R. Piletic
Colleen B. Baublitz
Jesse O. Bash
Andrew R. Whitehill
Lukas C. Valin
Asher P. Mouat
Jennifer Kaiser
Glenn M. Wolfe
Jason M. St. Clair
Thomas F. Hanisco
Alan Fried
Bryan K. Place
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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