the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 18 Jan 2024
Understanding Absorption by Black Versus Brown Carbon in Biomass Burning Plumes from the WE-CAN Campaign
Abstract. Aerosol absorption of visible light has an important impact on global radiative forcing. Wildfires are one of the major sources of light-absorbing aerosol, but there remains significant uncertainty about the magnitude, wavelength dependence and bleaching of absorption from biomass burning aerosol. We collected and analyzed data from 21 Western United States wildfire smoke plumes during the 2018 WE-CAN airborne measurement campaign to determine the contribution of black carbon (BC), brown carbon (BrC), and lensing to the aerosol mass absorption cross-section (MAC). MACBC, MAC of organics (MACBrC+lensing), and the MAC of water-soluble BrC (MACws_BrC660) are calculated using Photoacoustic Absorption Spectrometer, Single Particle Soot Photometer and Particle-into-Liquid Sampler measurements. MACBC660 does not change significantly with physical age, organic aerosol (OA) concentration, oxygen to carbon ratio (O:C), gas-phase toluene:benzene ratio, modified combustion efficiency (MCE), altitude, or temperature, and has a relatively stable average value of 10.9 ± 2.1 m2 g-1. On average, 54 % of non-BC absorption (23 % total absorption) at 660 nm is from water-soluble BrC. MACws_BrC660 is 0.06 ± 0.04 m2 g-1 while MACBrC+lensing is 0.11 ± 0.06 m2 g-1 at 660 nm, increasing to 0.59 ± 0.19 m2 g-1 at 405 nm. MACBrC+lensing is constant with physical age and MCE, but increases slightly with increasing O:C or decreasing toluene:benzene, while total absorption (normalized to CO) slightly decreases with increasing O:C or decreasing toluene:benzene due to decreasing OA. No evidence of BrC bleaching is observed. Comparison to commonly used parameterizations, modeling studies, and the FIREX-AQ observations suggest model overestimation of absorption is likely due to incorrect BrC refractive indices. Quantification of significant brown carbon in the red wavelengths and the stability of MACBC, the observation of minimal bleaching, and the observation of changes in OA with O:C and toluene:benzene markers all serve as important constraints on aerosol absorption in regional and global climate models.
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RC1: 'Comment on egusphere-2023-3114', Anonymous Referee #1, 03 Mar 2024
The paper entitled 'Understanding Absorption by Black Versus Brown Carbon in Biomass Burning Plumes from the WE-CAN Campaign' seeks to elucidate the optical characteristics of black carbon (BC) and brown carbon (BrC) based on data collected from an airborne campaign. The dataset presented in the manuscript is unique and valuable, but a much deeper analysis is needed. To bolster the credibility of your findings, it is crucial to extend beyond merely presenting scattering plots that display a minimal correlation. The manuscript frequently employs the term 'unclear,' which diminishes its assertiveness. Recognizing the challenges in drawing definitive conclusions due to the variability in fuels, combustion conditions, and weather among different fires, I would suggest the authors concentrate on data from either a single transect or multiple transects within the same plume. This approach would minimize the influence of external variables. A significant issue is identified in Section 2.4, particularly with Equation 2, where the absorption by BrC is not accounted for, potentially leading to an overestimation of E_abs. Furthermore, the term 'MAC BrC+lensing' is unconventional. It would be beneficial for the clarity of the manuscript if the terminology related to BC and BrC were more thoroughly explained. In summary, the manuscript requires substantial revision to reach the publication standards of ACP.
General comments:
L62 If BC core is coated by absorbing component, I think the absorption of BC would be reduced.
L94 It is unclear in the sentence here. I am not sure if authors want to express BC absorption or BC core absorption is rare. Additionally, MAC BC is for BC core only or the overall BC particle.
L139 PM2.5 or PM1
L157 I think you should move this paragraph before L152.
L190,L199 Please specify the size range of particles you measured.
Line 358-360 From Fig 3c and 3d, it is hard to conclude the trend of the fitting line with R2 equals to 0.02 or 0.03
Line 368-370 What is the trend between t/b with O:C ratio? Do they have a nice correlation?
Line 473 I would suggest you move the part describing how you convert liquid abs to abs in air to the method section
Citation: https://doi.org/10.5194/egusphere-2023-3114-RC1 -
RC2: 'Comment on egusphere-2023-3114', Anonymous Referee #2, 03 Apr 2024
This paper investigates the vast amounts of field data gathered during WE-CAN. While I believe that the authors have made significant progress in understanding the dataset, the manuscript suffers greatly by treating all wildfires fires as a monolith and analyzing them together rather than individually. Considering Figure 1, it is unreasonable to assume that the parameters studied here would have universal trends across all these wildfires given their disparate geographic locations, which carry differences in fuel type, fire area, fire maturity, and meteorology. Indeed, even the tenuous correlations shown here all but vanish upon considering individual fires without any additional context.
I am curious as to what the motivation for analyzing the data in this manner was. I believe the authors should refocus their analysis on individual wildfires and investigate whether any novel conclusions can be drawn from the data that can be tied to a specific emission source. Unfortunately, as the manuscript stands, no novel conclusions can be drawn and I cannot recommend it for publication without significant reanalysis and revision.
Upon revision, the authors should also address the following general comments.
The fires themselves are not discussed at all. Analysis of a plume is necessarily incomplete without information on fire location, size, maturity, fuel type, and meteorology. This additional context may provide insight to the various parameters observed.
Line 152: How were the optical parameters translated to STP? Which equations were used?
Line 197: Same question: how were SP2 measurements converted to STP?
Section 2.2: Why did the authors not use a more robust method for calculating plume age, such as HYSPLIT?
Line 337: The authors state “This result indicates that the combustion conditions (flaming or smoldering) does not have an easily described relationship to MACBC660.” I believe this result is mostly indicative of how difficult it is to use MCE to describe a fire. MCE is highly variable and may have vastly different values at different locations within the fire area. The authors may want to consider using another plume marker - the PTR-ToF-MS may provide a measurement of HCN, though this will likely carry similar uncertainty.
Line 357: The statement “Even for each individual flight, the increasing trend in mean diameter is clear” is not supported by Figure S2.
Line 358: The statement “Another contributor to increasing SSA is the decrease in absorption at 660 nm (Fig. 3d) with age for most fires” is not supported by figure 3d. Perhaps overall, the linear regression shows a negative slope, but when considering individual plumes (notably RF10 and RF19), the interpretation fails.
The authors do not justify the use of linear regressions as their model fit for these data and it is unlikely that any of the several parameters would be linear in the others, save, perhaps OA/CO vs O:C Ratio, which is rather obvious. Most of the regressions in this analysis show no linear correlation whatsoever, yet the authors discuss the results as if the correlations are significant (line 408, for example). The authors may want to consider different models when fitting their reanalyzed data.
In Figure 7, there is clearly no correlation between either altitude or temperature and OA/CO, rather, these graphs taken together merely show that colder plumes are found at higher altitudes. The same can be said of Figure 9 (a) and (b).
Line 459: Are the authors trying to draw a distinction between externally and internally mixed BrC?
Line 470: please cite the Mie code used, unless it was developed by the authors. If so, please state so.
Line 561: Similar to other figures where the r2 is extremely low, there are no trends in Figure 14 and no conclusions can be drawn from the data as presented.
Citation: https://doi.org/10.5194/egusphere-2023-3114-RC2 -
AC1: 'Response to Reviewer Comments on egusphere-2023-3114', Yingjie Shen, 12 Jul 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2023-3114/egusphere-2023-3114-AC1-supplement.pdf
Status: closed
-
RC1: 'Comment on egusphere-2023-3114', Anonymous Referee #1, 03 Mar 2024
The paper entitled 'Understanding Absorption by Black Versus Brown Carbon in Biomass Burning Plumes from the WE-CAN Campaign' seeks to elucidate the optical characteristics of black carbon (BC) and brown carbon (BrC) based on data collected from an airborne campaign. The dataset presented in the manuscript is unique and valuable, but a much deeper analysis is needed. To bolster the credibility of your findings, it is crucial to extend beyond merely presenting scattering plots that display a minimal correlation. The manuscript frequently employs the term 'unclear,' which diminishes its assertiveness. Recognizing the challenges in drawing definitive conclusions due to the variability in fuels, combustion conditions, and weather among different fires, I would suggest the authors concentrate on data from either a single transect or multiple transects within the same plume. This approach would minimize the influence of external variables. A significant issue is identified in Section 2.4, particularly with Equation 2, where the absorption by BrC is not accounted for, potentially leading to an overestimation of E_abs. Furthermore, the term 'MAC BrC+lensing' is unconventional. It would be beneficial for the clarity of the manuscript if the terminology related to BC and BrC were more thoroughly explained. In summary, the manuscript requires substantial revision to reach the publication standards of ACP.
General comments:
L62 If BC core is coated by absorbing component, I think the absorption of BC would be reduced.
L94 It is unclear in the sentence here. I am not sure if authors want to express BC absorption or BC core absorption is rare. Additionally, MAC BC is for BC core only or the overall BC particle.
L139 PM2.5 or PM1
L157 I think you should move this paragraph before L152.
L190,L199 Please specify the size range of particles you measured.
Line 358-360 From Fig 3c and 3d, it is hard to conclude the trend of the fitting line with R2 equals to 0.02 or 0.03
Line 368-370 What is the trend between t/b with O:C ratio? Do they have a nice correlation?
Line 473 I would suggest you move the part describing how you convert liquid abs to abs in air to the method section
Citation: https://doi.org/10.5194/egusphere-2023-3114-RC1 -
RC2: 'Comment on egusphere-2023-3114', Anonymous Referee #2, 03 Apr 2024
This paper investigates the vast amounts of field data gathered during WE-CAN. While I believe that the authors have made significant progress in understanding the dataset, the manuscript suffers greatly by treating all wildfires fires as a monolith and analyzing them together rather than individually. Considering Figure 1, it is unreasonable to assume that the parameters studied here would have universal trends across all these wildfires given their disparate geographic locations, which carry differences in fuel type, fire area, fire maturity, and meteorology. Indeed, even the tenuous correlations shown here all but vanish upon considering individual fires without any additional context.
I am curious as to what the motivation for analyzing the data in this manner was. I believe the authors should refocus their analysis on individual wildfires and investigate whether any novel conclusions can be drawn from the data that can be tied to a specific emission source. Unfortunately, as the manuscript stands, no novel conclusions can be drawn and I cannot recommend it for publication without significant reanalysis and revision.
Upon revision, the authors should also address the following general comments.
The fires themselves are not discussed at all. Analysis of a plume is necessarily incomplete without information on fire location, size, maturity, fuel type, and meteorology. This additional context may provide insight to the various parameters observed.
Line 152: How were the optical parameters translated to STP? Which equations were used?
Line 197: Same question: how were SP2 measurements converted to STP?
Section 2.2: Why did the authors not use a more robust method for calculating plume age, such as HYSPLIT?
Line 337: The authors state “This result indicates that the combustion conditions (flaming or smoldering) does not have an easily described relationship to MACBC660.” I believe this result is mostly indicative of how difficult it is to use MCE to describe a fire. MCE is highly variable and may have vastly different values at different locations within the fire area. The authors may want to consider using another plume marker - the PTR-ToF-MS may provide a measurement of HCN, though this will likely carry similar uncertainty.
Line 357: The statement “Even for each individual flight, the increasing trend in mean diameter is clear” is not supported by Figure S2.
Line 358: The statement “Another contributor to increasing SSA is the decrease in absorption at 660 nm (Fig. 3d) with age for most fires” is not supported by figure 3d. Perhaps overall, the linear regression shows a negative slope, but when considering individual plumes (notably RF10 and RF19), the interpretation fails.
The authors do not justify the use of linear regressions as their model fit for these data and it is unlikely that any of the several parameters would be linear in the others, save, perhaps OA/CO vs O:C Ratio, which is rather obvious. Most of the regressions in this analysis show no linear correlation whatsoever, yet the authors discuss the results as if the correlations are significant (line 408, for example). The authors may want to consider different models when fitting their reanalyzed data.
In Figure 7, there is clearly no correlation between either altitude or temperature and OA/CO, rather, these graphs taken together merely show that colder plumes are found at higher altitudes. The same can be said of Figure 9 (a) and (b).
Line 459: Are the authors trying to draw a distinction between externally and internally mixed BrC?
Line 470: please cite the Mie code used, unless it was developed by the authors. If so, please state so.
Line 561: Similar to other figures where the r2 is extremely low, there are no trends in Figure 14 and no conclusions can be drawn from the data as presented.
Citation: https://doi.org/10.5194/egusphere-2023-3114-RC2 -
AC1: 'Response to Reviewer Comments on egusphere-2023-3114', Yingjie Shen, 12 Jul 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2023-3114/egusphere-2023-3114-AC1-supplement.pdf
Data sets
Aerosol Extinction, Scattering and Absorption (PAS CAPS) Data Shane M. Murphy https://doi.org/10.26023/K8P0-X4T3-TN06
Particle Into Liquid Sampler 2 (PILS2) two minute integrated cations, anions, levoglucosan, and organic acids data Amy P. Sullivan https://doi.org/10.26023/7TAN-TZMD-680Y
Single Particle Soot Photometer (SP2) Black Carbon Mass in Individual Particles Data Ezra J. T. Levin https://doi.org/10.26023/P8R2-RAB6-N814
CVI/UHSAS Data Darin W. Toohey https://doi.org/10.26023/BZ4F-EAC4-290W
PTR-ToF-MS Measurements of Selected NMVOCs Data Lu Hu and Wade Permar https://doi.org/10.26023/K9F4-2CNH-EQ0W
HR-ToF-AMS Fine-Mode Aerosol Composition Data Delphine K. Farmer and Sonia M. Kreidenweis https://doi.org/10.26023/MM2Y-ZGFQ-RB0B
Picarro G2401-m WS-CRDS CO2, CH4, CO and H2O in situ mixing ratio observations - ICARTT format Teresa Campos https://doi.org/10.26023/NNYM-Z18J-PX0Q
Aerodyne CS-108 miniQCL CO, N2O and H2O in situ mixing ratio observations - ICARTT format Teresa Campos https://doi.org/10.26023/Q888-WZRD-B70F
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