the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 03 Jan 2022
Non-reversible aging can increase solar absorption in African biomass burning aerosol plumes of intermediate age
Abstract. Recent studies highlight that biomass-burning aerosol over the remote southeast Atlantic is some of the most sunlight-absorbing aerosol on the planet. In-situ measurements of single-scattering albedo at the 530 nm wavelength (SSA530nm) range from 0.83 to 0.89 within six flights (five in September, 2016 and one in late August, 2017) of the ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) aircraft campaign, increasing with the organic aerosol to black carbon (OA : BC) mass ratio. OA : BC mass ratios of 10 to 14 are lower than some model values and consistent with BC-enriched source emissions, based on indirect inferences of fuel type (savannah grasslands) and dry, flame-efficient combustion conditions. These primarily explain the low single-scattering albedos. We investigate whether continued chemical aging of aerosol plumes of intermediate age (4–7 days after emission, as determined from model tracers) within the free troposphere can further lower the SSA530nm. A mean OA to organic carbon mass ratio of 2.2 indicates highly oxygenated aerosol with the chemical marker f44 indicating the free-tropospheric aerosol continues to oxidize after advecting offshore of continental Africa. Two flights, for which BC to carbon monoxide (CO) ratios remain constant with increasing chemical age, are analyzed further. In both flights, the OA : BC mass ratio decreases over the same time span, indicating continuing net aerosol loss. One flight sampled younger (∼ 4 days) aerosol within the strong zonal outflow of the 4–6 km altitude African Easterly Jet-South. This possessed the highest OA : BC mass ratio of the 2016 campaign and overlaid slightly older aerosol with proportionately less OA, although the age difference of one day is not enough to attribute to a large-scale recirculation and subsidence pattern. The other flight sampled aerosol constrained closer to the coast by a mid-latitude disturbance and found older aerosol aloft overlying younger aerosol. Its vertical increase in OA : BC and nitrate to BC was less pronounced than when younger aerosol overlaid older aerosol, consistent with compensation between a net aerosol loss through aging and a thermodynamical partitioning. Organic nitrate provided 68 % on average of the total nitrate for the 6 flights, in contrast to measurements made at Ascension Island that only found inorganic nitrate. Some evidence for the thermodynamical partitioning to the particle phase at higher altitudes with higher relative humidities for nitrate is still found. The 470–660 nm absorption Angstrom exponent is slightly higher near the African coast than further offshore (approximately 1.2 versus 1.0–1.1), indicating some brown carbon may be present near the coast. The data support the following parameterization: SSA530nm = 0.80+0056*(OA : BC). This indicates a 20 % decrease in SSA can be attributed to chemical aging, or the net 25 % reduction in OA : BC documented for constant BC : CO ratios.
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Interactive discussion
Status: closed
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RC1: 'Comment on acp-2021-1081', Anonymous Referee #1, 19 Jan 2022
The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2021-1081/acp-2021-1081-RC1-supplement.pdf
-
RC2: 'Comment on acp-2021-1081', Anonymous Referee #2, 28 Jan 2022
Review of Dobracki et al.
The authors present an analysis of aerosol optical properties during a selection of flights from the ORACLES field program that indicate that during aging of biomass burning aerosols the organic aerosol is reduced relative to black carbon which results in a decrease in the single-scattering albedo of the aerosol at a mid-visible wavelength. The authors offer a “parameterization” of this dependency between the optical properties and chemical composition. The authors also find that the organic aerosol has a higher ratio of organic mass to organic carbon than is often considered leading to potential for modelling biases/underestimates. They further argue that it is chemical oxidation that is responsible for the loss of organic aerosol as the plume ages.
In my opinion, the manuscript is unsuitable for publication. The authors make quite forceful interpretations from the data, but the claims are not backed by sufficient evidence and so counter-narratives are easily plausible. The flaws in the analysis are not helped by challenging readability (and some errors). Please consider the points made below as grounds for this assessment.
- The title is misleading. The main finding appears to be that OA is lost with age and SSA is found to decrease. But it is the change of the scattering that is seemingly changing the SSA, not a substantial change to the absorption. Even though the authors find the brown carbon contribution to be small, they do note that it decreases with age. Loss of brown carbon absorption, combined with potential reduction in absorption enhancing effects such as lensing, may instead imply that the absorption is actually decreasing across the ages of the plumes discussed as a result of OA loss – the opposite of claimed in the title.
- The conclusions touch on some climate impacts of the findings (e.g. L476-480) and I had hoped that in “Section 7: Radiative implications and inferences” the authors would have actually provided some analysis of the radiative implications of a reduction of scattering aerosol in an absorbing layer. Instead the authors just reported the optical properties of the aerosol, namely SSA and AAE, in relation to chemical properties. Therefore the climate/ratiative implication of the findings is not really part of the study at all. The “parameterization” just seems to be the coefficients of a simple linear regression. It is not clear that the specifics of this relationship (namely the fit coefficients) would hold for any other location/scenario. In general, the discussion around nitrate was quite a large part of the manuscript. I could not understand why the discussion of organic versus inorganic nitrate deserved such a focus given the objectives of the paper. Also, if nitrate (inorganic and organic) was so relevant, why then was it not part of the “parameterization”?
- Thermodynamic partitioning: Section 6 aims to prove that the loss of OA cannot be a consequence of repartitioning of semi-volatiles into the gas phase. The authors use NO3 to make this case but the thermodynamic arguments are superficial and only related to temperature (or altitude) and humidity but ignore major controlling factors such as the nitric acid vapor pressure or the abundance of other acidic or basic species such as sulfate and ammonium. While it is understood and accepted that the flights may not have the full suite of measurements to support thermodynamic modelling, the authors could have at least offered some discussion and/or calculations to at least constrain their assumptions. The use of NO3 partitioning to constrain the OA partitioning is further flawed by the fact that OA volatility is variable tending to become lower with age (at least along a functionalization pathway suggested by the VK analysis). Hence the use of the vertical profile of nitrate is not conclusive in anchoring the expected altitude dependence of OA (e.g. all else equal) due to partitioning.
- The argument for chemical oxidation being the driver for OA loss is weak. It appears that it is centered around the fact that for roughly constant BC:CO, an increase in f44 coexists with a decrease in OA:BC somehow implying that increased oxidation causes evaporation. The problem with the reasoning is that if oxidation causes loss of OA, then the signature of oxidation would surely be lost along with the OA. Upon functionalization, a decrease in volatility might be expected (e.g. shift from SV-OOA to LV-OOA with associated increase in f44). Although small carboxylic acids could be volatilized and/or eventually react to CO2, the authors do not make clear what pathway they are actually describing in relation to further oxidation that leads to OA loss - it is left vague. Also, consider the following: if semi-volatiles – with lower f44 – were liberated from a mixture containing low-volatiles – with higher f44 – as a result of gas vapor pressure dilution, then the f44 of the mixture would go up as the OA went down – i.e. the same as observed, but no chemical mechanism required.
- Transport and meteorology: a brief review of visible satellite imagery on the days of the detailed cases (09/24 and 08/31) and the days prior, suggests that terrestrial convective clouds were exerting an influence on the environment over land in the vicinity of the BBA sources and their near-source transport. The authors do not provide any context and discussion of the potential for prior processing of BBA by clouds. There are a wide variety of BBA sources active at the time of the case flights spanning a very large geographical extent but little depth of analysis is placed on constraining sources. Significant variability in emissions is known to exist for different fuel types and burn conditions and this could explain the variability in OA even for relatively similar BC:CO. The authors use a forecast product but it is not clear why a forecast product is the correct tool to analyze the meteorology/transport of an event in the past – especially since the purpose of the paper is not to analyze the skill of the forecast. The authors discuss transport age and f44 as two methods to describe the age of the BBA and use transport age as a filter for selecting the flights (while also documenting some of the shortfalls/limitations of the age estimate) yet the f44 data presented in Fig 6 indicates that all the ORACLES data is bounded by the f44 of the six hand-picked cases – therefore if f44 is a worthy metric of identifying candidate cases, why then the authors restrict themselves just to the six cases? In the two detailed cases, the vertical structure of the plume is linked to the transport age but the authors do not show what that transport pathway looks like. Given that the vertical structure is important for the mechanistic arguments made by the authors, more evidence is needed supporting how that vertical structure connects back to the described meteorology (e.g. AEJ-S, recirculation, subsidence etc). A reader would benefit from seeing this transport pathway in the form of a trajectory (or some other means), at minimum.
- General structure and readability: Many of the sections describing results of the study contain introductory material. This is particularly notable in the Conclusions section where it becomes challenging to actually summarize/assess the work carried out by this study. Conversely, the last part of the Introduction includes some description of the flights and some preliminary discussion. There are some concepts that are given quite a bit of weight (e.g. recirculation and subsidence of aging plumes) but then discounted elsewhere. Some concepts are only introduced in the Conclusions section (e.g. the “Kalahari heat low” makes an initial appearance with no other description of what this is or why it is relevant). Similar on Fig 7 these elemental ratios are captioned as mass ratios while their magnitude (and convention) would suggest they are molar ratios. Some definitions (e.g. OC, AEJ-S) were not introduced during first instance, also some datasets are not introduced in the dataset section (e.g. temperature, RH and wind data shown in the profiles – were these in situ data during the profile or from another means e.g. dropsondes?). Some of the figures have errors (e.g. Fig. 11 IN:BC is listed in the caption but not in the plots) and readability issue (e.g. Figure 4 has scale bars and axes that overlap and the top-left panel is unreadable). In line references to figures do not match the content of the figure (e.g. L137-138 this is not shown in Fig 5). In Fig 6, what are the pink diamonds clustered near the ORACLES data? Fig 12 is mostly a repeat of Fig 11, just with the temperature recast as potential temperature and the RH as water vapor mixing ratio.
- Other inconsistency: Why does the distribution of BC:CO look so different for 08/31/17 all data (Fig 8d) to the same data broken out by f44 shown in Fig 9? Even if only the box containing the vast majority of data is considered (f44: 0.21-0.24) it looks quite different to the distribution of the overall. Based on the argument of using cases with constant BC:CO, from Fig 8 this flight would seem to be a perfect choice.
Citation: https://doi.org/10.5194/acp-2021-1081-RC2 -
EC1: 'Comment on acp-2021-1081', Joshua Schwarz, 17 Feb 2022
Dear Authors -
We have received two considered reviews of this manuscript from topical experts. After carefully considering those inputs, my opinion as handling editor is that the main scientific conclusions of the paper are unsupported. Hence, I discourage you from preparing a response and revised manuscript addressing these reviews. Instead, I encourage you to reconsider your work, with these reviews as valuable resources. In anticipation that you will find valuable conclusions that you can support, I recommend that you report them in a manuscript submitted for peer-review as a new and independent work.
Sincerely,
Joshua Schwarz
Citation: https://doi.org/10.5194/acp-2021-1081-EC1 -
AC1: 'Comment on acp-2021-1081', Paquita Zuidema, 07 Mar 2022
Dear reviewers and editor: Thank you for the useful feedback you have provided. We will keep working on this analysis until we have it figured out with a deeper understanding, and will resubmit as a new manuscript at that point in time. Thank you again, Paquita Zuidema
Citation: https://doi.org/10.5194/acp-2021-1081-AC1
Interactive discussion
Status: closed
-
RC1: 'Comment on acp-2021-1081', Anonymous Referee #1, 19 Jan 2022
The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2021-1081/acp-2021-1081-RC1-supplement.pdf
-
RC2: 'Comment on acp-2021-1081', Anonymous Referee #2, 28 Jan 2022
Review of Dobracki et al.
The authors present an analysis of aerosol optical properties during a selection of flights from the ORACLES field program that indicate that during aging of biomass burning aerosols the organic aerosol is reduced relative to black carbon which results in a decrease in the single-scattering albedo of the aerosol at a mid-visible wavelength. The authors offer a “parameterization” of this dependency between the optical properties and chemical composition. The authors also find that the organic aerosol has a higher ratio of organic mass to organic carbon than is often considered leading to potential for modelling biases/underestimates. They further argue that it is chemical oxidation that is responsible for the loss of organic aerosol as the plume ages.
In my opinion, the manuscript is unsuitable for publication. The authors make quite forceful interpretations from the data, but the claims are not backed by sufficient evidence and so counter-narratives are easily plausible. The flaws in the analysis are not helped by challenging readability (and some errors). Please consider the points made below as grounds for this assessment.
- The title is misleading. The main finding appears to be that OA is lost with age and SSA is found to decrease. But it is the change of the scattering that is seemingly changing the SSA, not a substantial change to the absorption. Even though the authors find the brown carbon contribution to be small, they do note that it decreases with age. Loss of brown carbon absorption, combined with potential reduction in absorption enhancing effects such as lensing, may instead imply that the absorption is actually decreasing across the ages of the plumes discussed as a result of OA loss – the opposite of claimed in the title.
- The conclusions touch on some climate impacts of the findings (e.g. L476-480) and I had hoped that in “Section 7: Radiative implications and inferences” the authors would have actually provided some analysis of the radiative implications of a reduction of scattering aerosol in an absorbing layer. Instead the authors just reported the optical properties of the aerosol, namely SSA and AAE, in relation to chemical properties. Therefore the climate/ratiative implication of the findings is not really part of the study at all. The “parameterization” just seems to be the coefficients of a simple linear regression. It is not clear that the specifics of this relationship (namely the fit coefficients) would hold for any other location/scenario. In general, the discussion around nitrate was quite a large part of the manuscript. I could not understand why the discussion of organic versus inorganic nitrate deserved such a focus given the objectives of the paper. Also, if nitrate (inorganic and organic) was so relevant, why then was it not part of the “parameterization”?
- Thermodynamic partitioning: Section 6 aims to prove that the loss of OA cannot be a consequence of repartitioning of semi-volatiles into the gas phase. The authors use NO3 to make this case but the thermodynamic arguments are superficial and only related to temperature (or altitude) and humidity but ignore major controlling factors such as the nitric acid vapor pressure or the abundance of other acidic or basic species such as sulfate and ammonium. While it is understood and accepted that the flights may not have the full suite of measurements to support thermodynamic modelling, the authors could have at least offered some discussion and/or calculations to at least constrain their assumptions. The use of NO3 partitioning to constrain the OA partitioning is further flawed by the fact that OA volatility is variable tending to become lower with age (at least along a functionalization pathway suggested by the VK analysis). Hence the use of the vertical profile of nitrate is not conclusive in anchoring the expected altitude dependence of OA (e.g. all else equal) due to partitioning.
- The argument for chemical oxidation being the driver for OA loss is weak. It appears that it is centered around the fact that for roughly constant BC:CO, an increase in f44 coexists with a decrease in OA:BC somehow implying that increased oxidation causes evaporation. The problem with the reasoning is that if oxidation causes loss of OA, then the signature of oxidation would surely be lost along with the OA. Upon functionalization, a decrease in volatility might be expected (e.g. shift from SV-OOA to LV-OOA with associated increase in f44). Although small carboxylic acids could be volatilized and/or eventually react to CO2, the authors do not make clear what pathway they are actually describing in relation to further oxidation that leads to OA loss - it is left vague. Also, consider the following: if semi-volatiles – with lower f44 – were liberated from a mixture containing low-volatiles – with higher f44 – as a result of gas vapor pressure dilution, then the f44 of the mixture would go up as the OA went down – i.e. the same as observed, but no chemical mechanism required.
- Transport and meteorology: a brief review of visible satellite imagery on the days of the detailed cases (09/24 and 08/31) and the days prior, suggests that terrestrial convective clouds were exerting an influence on the environment over land in the vicinity of the BBA sources and their near-source transport. The authors do not provide any context and discussion of the potential for prior processing of BBA by clouds. There are a wide variety of BBA sources active at the time of the case flights spanning a very large geographical extent but little depth of analysis is placed on constraining sources. Significant variability in emissions is known to exist for different fuel types and burn conditions and this could explain the variability in OA even for relatively similar BC:CO. The authors use a forecast product but it is not clear why a forecast product is the correct tool to analyze the meteorology/transport of an event in the past – especially since the purpose of the paper is not to analyze the skill of the forecast. The authors discuss transport age and f44 as two methods to describe the age of the BBA and use transport age as a filter for selecting the flights (while also documenting some of the shortfalls/limitations of the age estimate) yet the f44 data presented in Fig 6 indicates that all the ORACLES data is bounded by the f44 of the six hand-picked cases – therefore if f44 is a worthy metric of identifying candidate cases, why then the authors restrict themselves just to the six cases? In the two detailed cases, the vertical structure of the plume is linked to the transport age but the authors do not show what that transport pathway looks like. Given that the vertical structure is important for the mechanistic arguments made by the authors, more evidence is needed supporting how that vertical structure connects back to the described meteorology (e.g. AEJ-S, recirculation, subsidence etc). A reader would benefit from seeing this transport pathway in the form of a trajectory (or some other means), at minimum.
- General structure and readability: Many of the sections describing results of the study contain introductory material. This is particularly notable in the Conclusions section where it becomes challenging to actually summarize/assess the work carried out by this study. Conversely, the last part of the Introduction includes some description of the flights and some preliminary discussion. There are some concepts that are given quite a bit of weight (e.g. recirculation and subsidence of aging plumes) but then discounted elsewhere. Some concepts are only introduced in the Conclusions section (e.g. the “Kalahari heat low” makes an initial appearance with no other description of what this is or why it is relevant). Similar on Fig 7 these elemental ratios are captioned as mass ratios while their magnitude (and convention) would suggest they are molar ratios. Some definitions (e.g. OC, AEJ-S) were not introduced during first instance, also some datasets are not introduced in the dataset section (e.g. temperature, RH and wind data shown in the profiles – were these in situ data during the profile or from another means e.g. dropsondes?). Some of the figures have errors (e.g. Fig. 11 IN:BC is listed in the caption but not in the plots) and readability issue (e.g. Figure 4 has scale bars and axes that overlap and the top-left panel is unreadable). In line references to figures do not match the content of the figure (e.g. L137-138 this is not shown in Fig 5). In Fig 6, what are the pink diamonds clustered near the ORACLES data? Fig 12 is mostly a repeat of Fig 11, just with the temperature recast as potential temperature and the RH as water vapor mixing ratio.
- Other inconsistency: Why does the distribution of BC:CO look so different for 08/31/17 all data (Fig 8d) to the same data broken out by f44 shown in Fig 9? Even if only the box containing the vast majority of data is considered (f44: 0.21-0.24) it looks quite different to the distribution of the overall. Based on the argument of using cases with constant BC:CO, from Fig 8 this flight would seem to be a perfect choice.
Citation: https://doi.org/10.5194/acp-2021-1081-RC2 -
EC1: 'Comment on acp-2021-1081', Joshua Schwarz, 17 Feb 2022
Dear Authors -
We have received two considered reviews of this manuscript from topical experts. After carefully considering those inputs, my opinion as handling editor is that the main scientific conclusions of the paper are unsupported. Hence, I discourage you from preparing a response and revised manuscript addressing these reviews. Instead, I encourage you to reconsider your work, with these reviews as valuable resources. In anticipation that you will find valuable conclusions that you can support, I recommend that you report them in a manuscript submitted for peer-review as a new and independent work.
Sincerely,
Joshua Schwarz
Citation: https://doi.org/10.5194/acp-2021-1081-EC1 -
AC1: 'Comment on acp-2021-1081', Paquita Zuidema, 07 Mar 2022
Dear reviewers and editor: Thank you for the useful feedback you have provided. We will keep working on this analysis until we have it figured out with a deeper understanding, and will resubmit as a new manuscript at that point in time. Thank you again, Paquita Zuidema
Citation: https://doi.org/10.5194/acp-2021-1081-AC1
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Amie Dobracki
Steve Howell
Pablo Saide
Steffen Freitag
Allison C. Aiken
Sharon P. Burton
Arthur J. Sedlacek III
Jens Redemann
Robert Wood
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