the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Nov 2023
Revising VOC emissions speciation improves global simulations of ethane and propane
Abstract. Non-Methane Volatile Organic Compounds (NMVOCs) generate ozone (O3) when they are oxidized in the presence of oxides of nitrogen, modulate the oxidative capacity of the atmosphere and can lead to the formation of aerosol. Here, we assess the capability of a chemical transport model (GEOS-Chem) to simulate NMVOC concentrations by comparing ethane, propane and higher alkane observations in remote regions from the NOAA Flask Network and the World Meteorological Organization’s Global Atmosphere Watch (GAW) network. Using the Community Emissions Data System (CEDS) inventory we find a significant underestimate in the simulated concentration of both ethane (35 %) and propane (64 %), consistent with previous studies. We run a new simulation where the total mass of anthropogenic NMVOC emitted in a grid box is the same as that used in CEDS, but with the NMVOC speciation derived from regional inventories. For US emissions we use the National Emissions Inventory (NEI), for Europe we use the UK National Atmospheric Emissions Inventory (NAEI), and for China, the Multi-resolution Emission Inventory for China (MEIC). These changes lead to a large increase in the modelled concentrations of ethane, improving the mean model bias from -35 % to -3.8 %. Simulated propane also improves (from -64 % to -48.0 % mean model bias), but there remains a substantial model underestimate. There were relatively minor changes to other NMVOCs. The low bias in simulated global ethane concentration is essentially removed, resolving one long-term issue in global simulations. Propane concentrations are improved but remain significantly underestimated, suggesting the potential for a missing global propane source. The change in the NMVOC emission speciation results in only minor changes in tropospheric O3 and OH concentrations.
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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.
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Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-2557', Anonymous Referee #1, 25 Dec 2023
General comments
In this study a chemical transport model was used to simulate NMVOC concentrations based on the CEDS inventory and compared to observational datasets. A particularly large discrepancy was found between the observed and simulated ethane and propane. By using regional NMVOC speciation to adjust the CEDS inventory (while keeping the aggregate NMVOC emissions the same), the simulation of ethane and propane concentrations were improved.
This paper is rightfully within the scope of ACP and should be published after minor revisions.
Specific comments
Line 70: Did you use CEDS gridded data as input to the model, or just the aggregate emissions files? The data reference citation (zenodo) is available on the CEDS GitHub site.
Line 116: Were measurements of hexane found in these observational datasets? In Line 81 it is mentioned that hexane was included as part of an aggregate ‘higher alkanes’ in the GEOS-Chem model. If not included in observational data, does this affect comparisons to the model output?
Line 208: To be clear, when scaling the total NMVOC in CEDS by the regional speciation, this simply disaggregates the total mass into individual species, it does not change the total mass? (I see this is specified in line 256 but may be helpful to specify earlier)
The conclusion section can be improved with some more discussion on potential future works that could close the gaps identified in the results. Should global inventories like CEDS make efforts to improve estimation of alkanes using regional NMVOC speciation data? Only a single model was tested in this study. Should a multi model analysis be conducted to determine whether sensitivity to alkane speciation is consistent across different models?
Technical corrections
Figure 4 and Figure 12 axis labels have ethane specified but should be propane.
Figure 6 and Figure 14 axis labels show ethane. Is this supposed to show higher alkanes?
Line 189: “Between” is repeated.
Line 198: …it would not be sufficient “to” extend the…
Line 328: …however, “this” (incomplete sentence?)
Citation: https://doi.org/10.5194/egusphere-2023-2557-RC1 -
RC2: 'Review of egusphere-2023-2557', Anonymous Referee #2, 04 Jan 2024
This paper presents an analysis of the impact of using different VOC speciations of emissions (i.e., relative amounts of hydrocarbons and volatile organic compounds (VOCs) for a given total amount of non-methane VOCs) in a global chemical transport model (GEOS-Chem). The majority of the analysis is evaluating the change in alkanes and aromatic hydrocarbons. The simulated mixing ratios are compared to surface observations from 2 global networks of mainly remote locations (NOAA/GML and GAW). The changes in modeled OH and ozone with the different VOC speciation of the emissions are also presented.
The topic of this paper is an important component of improving the capability to simulate tropospheric composition and air quality, as the VOC speciation of emissions inventories is a major uncertainty in atmospheric chemistry modeling. However, there are a number of deficiencies in the analysis that need to be addressed before I feel this paper would be acceptable for publication.
1. The lifetimes of the compounds that are used in this study need to be carefully taken into consideration in the discussion of the results.
Ethane has a lifetime of ~2 months (for OH = 1E6 molecules/cm3 and lower tropospheric temperature). This long lifetime makes it suitable to use observations even at remote sites for evaluating the emissions. However, all of the other species have much shorter lifetimes and should not be considered in the same manner. Propane and benzene have lifetimes of ~10 days, and higher alkanes, toluene and xylenes even shorter. Thus, the observations at remote sites are not really suitable for evaluating emissions of these compounds.2. I recommend finding observations closer to emissions source regions for the evaluation. Many aircraft campaigns have sampled urban areas and measured the hydrocarbons presented here. An analysis of the comparison of the model results to observations from air quality campaigns would provide much stronger evidence of the deficiencies of the emissions inventories and a more reliable assessment of where they are more accurate.
3. Section 3 could be incorporated in Section 4, and Figures 2-8 removed, as their contents are included in the figures in Section 4, thus significantly reducing the length of the paper and improving readability.
4. At the beginning of section 4, the discussion of MEIC speciation is very limited and does not really explain what information goes into the VOC speciation. Does it really include some local information about specific VOCs?
5. I find Sections 5.5 and 5.6 not very informative as they show annual averages of surface values of an apparently arbitrary collection of VOCs, and annual averages of surface amounts and zonal means for OH and ozone. This work would be far more valuable for readers if the discussion was a bit deeper, focusing on a few regions (close to sources, such as eastern U.S. and eastern China) and time periods (i.e., summer) that show significant change with the different speciations.
6. An evaluation of the surface ozone could be performed with air quality monitoring data, such as that available in the TOAR database. Again, discussion in greater depth of a few regions where impacts are significant would be very helpful.
While the comments above will require a signficant re-writing of the manuscript, included below are some technical corrections and minor suggestions.
l. 142 (and l.300) - It is interesting that there seems to be some correlation in the bias with observation site altitude, but some reason for this difference should be suggested. With the small number of GAW sites this could just be coincidence, or have more to do with the location in relation to sources.
Significant figures: the plot legends all have integer bias values, but the text always gives the bias in 0.1% increments. Round integers seem quite sufficient and would clean up the text.
RMSE: RMSE values are only given occasionally in the text. It would be helpful to include them in all of the plot legends. A table of all the Bias and RMSE values would also help readers.
Figures 4, 6, 12, 14: plot axes labels are wrong (or are the actual plots wrong?) - all labeled C2H6, but are supposed to be C3H8, etc.
Section 3.3: It would be informative to provide statistics and regression lines for only the higher alkanes points that are above the observed LOD. Indicating the LOD on the plots would be helpful, too.
l. 185: systemic -> systematic
l. 189: The correlation is poor for toluene and xylenes most likely because of their very short lifetimes.
l. 203: What is meant by 'large variability' in the OH rate constants for pentanes and hexanes?
Figure 11: These plots are shown with a linear scale on the y-axis while all the others use a log-scale. The linear scale works quite well, so I wonder why log-scale was used on the others (particularly Figs. 13, 15).
Citation: https://doi.org/10.5194/egusphere-2023-2557-RC2 -
AC1: 'Response to RC1 and RC2', Matthew Rowlinson, 15 Mar 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2557/egusphere-2023-2557-AC1-supplement.pdf
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AC2: 'Response to RC1 and RC2', Matthew Rowlinson, 15 Mar 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2557/egusphere-2023-2557-AC2-supplement.pdf
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2557', Anonymous Referee #1, 25 Dec 2023
General comments
In this study a chemical transport model was used to simulate NMVOC concentrations based on the CEDS inventory and compared to observational datasets. A particularly large discrepancy was found between the observed and simulated ethane and propane. By using regional NMVOC speciation to adjust the CEDS inventory (while keeping the aggregate NMVOC emissions the same), the simulation of ethane and propane concentrations were improved.
This paper is rightfully within the scope of ACP and should be published after minor revisions.
Specific comments
Line 70: Did you use CEDS gridded data as input to the model, or just the aggregate emissions files? The data reference citation (zenodo) is available on the CEDS GitHub site.
Line 116: Were measurements of hexane found in these observational datasets? In Line 81 it is mentioned that hexane was included as part of an aggregate ‘higher alkanes’ in the GEOS-Chem model. If not included in observational data, does this affect comparisons to the model output?
Line 208: To be clear, when scaling the total NMVOC in CEDS by the regional speciation, this simply disaggregates the total mass into individual species, it does not change the total mass? (I see this is specified in line 256 but may be helpful to specify earlier)
The conclusion section can be improved with some more discussion on potential future works that could close the gaps identified in the results. Should global inventories like CEDS make efforts to improve estimation of alkanes using regional NMVOC speciation data? Only a single model was tested in this study. Should a multi model analysis be conducted to determine whether sensitivity to alkane speciation is consistent across different models?
Technical corrections
Figure 4 and Figure 12 axis labels have ethane specified but should be propane.
Figure 6 and Figure 14 axis labels show ethane. Is this supposed to show higher alkanes?
Line 189: “Between” is repeated.
Line 198: …it would not be sufficient “to” extend the…
Line 328: …however, “this” (incomplete sentence?)
Citation: https://doi.org/10.5194/egusphere-2023-2557-RC1 -
RC2: 'Review of egusphere-2023-2557', Anonymous Referee #2, 04 Jan 2024
This paper presents an analysis of the impact of using different VOC speciations of emissions (i.e., relative amounts of hydrocarbons and volatile organic compounds (VOCs) for a given total amount of non-methane VOCs) in a global chemical transport model (GEOS-Chem). The majority of the analysis is evaluating the change in alkanes and aromatic hydrocarbons. The simulated mixing ratios are compared to surface observations from 2 global networks of mainly remote locations (NOAA/GML and GAW). The changes in modeled OH and ozone with the different VOC speciation of the emissions are also presented.
The topic of this paper is an important component of improving the capability to simulate tropospheric composition and air quality, as the VOC speciation of emissions inventories is a major uncertainty in atmospheric chemistry modeling. However, there are a number of deficiencies in the analysis that need to be addressed before I feel this paper would be acceptable for publication.
1. The lifetimes of the compounds that are used in this study need to be carefully taken into consideration in the discussion of the results.
Ethane has a lifetime of ~2 months (for OH = 1E6 molecules/cm3 and lower tropospheric temperature). This long lifetime makes it suitable to use observations even at remote sites for evaluating the emissions. However, all of the other species have much shorter lifetimes and should not be considered in the same manner. Propane and benzene have lifetimes of ~10 days, and higher alkanes, toluene and xylenes even shorter. Thus, the observations at remote sites are not really suitable for evaluating emissions of these compounds.2. I recommend finding observations closer to emissions source regions for the evaluation. Many aircraft campaigns have sampled urban areas and measured the hydrocarbons presented here. An analysis of the comparison of the model results to observations from air quality campaigns would provide much stronger evidence of the deficiencies of the emissions inventories and a more reliable assessment of where they are more accurate.
3. Section 3 could be incorporated in Section 4, and Figures 2-8 removed, as their contents are included in the figures in Section 4, thus significantly reducing the length of the paper and improving readability.
4. At the beginning of section 4, the discussion of MEIC speciation is very limited and does not really explain what information goes into the VOC speciation. Does it really include some local information about specific VOCs?
5. I find Sections 5.5 and 5.6 not very informative as they show annual averages of surface values of an apparently arbitrary collection of VOCs, and annual averages of surface amounts and zonal means for OH and ozone. This work would be far more valuable for readers if the discussion was a bit deeper, focusing on a few regions (close to sources, such as eastern U.S. and eastern China) and time periods (i.e., summer) that show significant change with the different speciations.
6. An evaluation of the surface ozone could be performed with air quality monitoring data, such as that available in the TOAR database. Again, discussion in greater depth of a few regions where impacts are significant would be very helpful.
While the comments above will require a signficant re-writing of the manuscript, included below are some technical corrections and minor suggestions.
l. 142 (and l.300) - It is interesting that there seems to be some correlation in the bias with observation site altitude, but some reason for this difference should be suggested. With the small number of GAW sites this could just be coincidence, or have more to do with the location in relation to sources.
Significant figures: the plot legends all have integer bias values, but the text always gives the bias in 0.1% increments. Round integers seem quite sufficient and would clean up the text.
RMSE: RMSE values are only given occasionally in the text. It would be helpful to include them in all of the plot legends. A table of all the Bias and RMSE values would also help readers.
Figures 4, 6, 12, 14: plot axes labels are wrong (or are the actual plots wrong?) - all labeled C2H6, but are supposed to be C3H8, etc.
Section 3.3: It would be informative to provide statistics and regression lines for only the higher alkanes points that are above the observed LOD. Indicating the LOD on the plots would be helpful, too.
l. 185: systemic -> systematic
l. 189: The correlation is poor for toluene and xylenes most likely because of their very short lifetimes.
l. 203: What is meant by 'large variability' in the OH rate constants for pentanes and hexanes?
Figure 11: These plots are shown with a linear scale on the y-axis while all the others use a log-scale. The linear scale works quite well, so I wonder why log-scale was used on the others (particularly Figs. 13, 15).
Citation: https://doi.org/10.5194/egusphere-2023-2557-RC2 -
AC1: 'Response to RC1 and RC2', Matthew Rowlinson, 15 Mar 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2557/egusphere-2023-2557-AC1-supplement.pdf
-
AC2: 'Response to RC1 and RC2', Matthew Rowlinson, 15 Mar 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2557/egusphere-2023-2557-AC2-supplement.pdf
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Matthew James Rowlinson
Lucy Carpenter
Katie Read
Shalini Punjabi
Adedayo Adedeji
Luke Fakes
Ally Lewis
Ben Richmond
Neil Passant
Tim Murrells
Barron Henderson
Kelvin Bates
Deltev Helmig
Mat Evans
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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