the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 23 May 2024
Brownness of Organics in Anthropogenic Biomass Burning Aerosols over South Asia
Abstract. In South Asia, biomass is burned for energy and waste disposal, producing brown carbon (BrC) aerosols whose climatic impacts are highly uncertain. To assess these impacts, a real-world understanding of BrC’s physio-optical properties is essential. For this region, the order-of-magnitude variability in BrC’s spectral refractive index as a function of particle volatility distribution is poorly understood. This leads to oversimplified model parameterization and subsequent underestimation of regional radiative forcing. Here we used the field-collected aerosol samples from major anthropogenic biomass activities to examine the methanol-soluble BrC optical properties. We show a strong relation between the absorption strength, wavelength dependence, and thermo-optical fractions of carbonaceous aerosols. Our observations show strongly absorbing BrC near the Himalayan foothills that may accelerate glacier melt, further highlighting the limitations of climate models where variable BrC properties are not considered. These findings provide crucial inputs for refining climate models and developing effective regional strategies to mitigate BrC.
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Journal article(s) based on this preprint
Interactive discussion
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RC1: 'Comment on egusphere-2024-1313', Anonymous Referee #1, 23 Aug 2024
The manuscript “Brownness of organics in anthropogenic biomass burning aerosols over South Asia” by Chimurkar Navinya et al. measured the absorbance and its wavelength dependence of real-world brown carbon (BrC) from different biomass fuels and sources. It further connected this absorption (kBrC) and wavelength dependence (w) with the thermos-optically obtained volatility of OC, and applied the relationship between kBrC and w and OC/OA ratio to evaluate the spatial variations of kBrC and w over south Asia. The manuscript is well within the scope of the ACP journal. The ideas and methods are good, previous studies are well-referenced, and the structure of the manuscript is generally clear. However, in the Results and Discussion section, the narrations are not sufficient enough to support the authors’ views and there is a lack of proper connection between subsections. Therefore, the manuscript can only be accepted for publication in ACP after addressing the following questions.
Specific comments:
Line 136: it’s better to include the unit of each parameter
Line 143: “the absorption” to “the absorption coefficient”?
Line 161: solubility (Saleh, 2020).
Line 175: why do you think you can assume a 10% uncertainty in absorption coefficient?
Line 192: “study” to “studies”
Line 192: “, however,” to “. However,”
Line 221: the usage of correlation coefficient and R2 should be unified through the text
Lines 224-226: the sentence should be restructured. What do you think is the reason for the outliers? How many samples have you measured for each fuel and source type?
Lines 231-232: “Such relationships … .” any reference or explanation to this?
Line 249: . However,
Line 255: A similar relationship between kBrC,550 and BC/OA ratio has also been…
Lines 253-256: “In agricultural … and w (Figure 4).” Should this part be moved to the end of this subsection or section 3.3?
Section 3.3 I’m interested to see the measured relationship between kBrC,365 and BC/OA ratio. It’s also interesting to see a comparison of kBrC,365 between measured and indirectly inferred from the relationships between kBrC,550 and BC/OA ratio, w and BC/OA ratio, and w and kBrC,550 ratio.
Line 318: “, while most models…”? or restructure lines 314-319.
Lines 334-335: same to my comments to section 3.3, why do you have to estimate kBrC,365 from w and KBrC,550? Why can’t you estimate kBrC,365 from the relationship between measured kBrC,365 and BC/OA ratio?
Line 337: “shows very large kBrC”, could the figure have a problem? I couldn’t see very large kBrC in the northern hilly region from figure 5a or figure S6.
Lines 342-344: what I see from Figure S3 is that the absolute contribution of AGRI to kBrC in northwestern India is much lower than that of HEAT. Could you please reconsider this statement?
Line 350: Does “the extended time required for photobleaching” only apply to northern Idia?
Lines 332-350: a detailed interpretation of the distributions of source- and/or fuel-specific contributions to w, kBrC,365, and kBrC,550 could be interesting and helpful to the explanation of other views already presented in this paragraph.
Citation: https://doi.org/10.5194/egusphere-2024-1313-RC1 -
RC2: 'Comment on egusphere-2024-1313', Anonymous Referee #2, 15 Sep 2024
The manuscript provides important data and findings to assess the radiative forcing of BrC emissions in South Asia. The study fits well within the scope of ACP. The manuscript is well-written. It discusses the results in most cases properly and considers also relevant previous studies. The methods seem appropriate. However, the authors could discuss and elaborate the influence of the used methods on the obtained results and consider the methodological differences also when comparing the results of this study to those from previous studies (e.g. related to the methodologies used in sample collection and organic matter extraction from the collected filter samples). The results and conclusions are presented in a clear, concise, and well-structured way and the manuscript can be accepted after a minor revision, taking into account the following specific comments:
line 19: ”This leads to oversimplified model parameterization and subsequent underestimation of regional radiative forcing.”
- If refractive index (RF) has uncertainty, the current estimations may either underestimate or overestimate radiative forcing? Should this rather be “subsequent uncertainty” of regional radiative forcing?
Lines 112 “This study leverages samples of aerosol particle emissions collected on filter substrates during the COALESCE field campaign to propose a hypothesis regarding the BrC-BC continuum in BrC optical properties.”
- It remains unclear what is the hypothesis that is proposed. Please describe it.
Line 132: “The sampler is fully described in previous studies (Venkataraman et al., 2020; Kumari et al., 2021).
- Some basic information of the sampling system would be important. However, the link given for the reference Kumari et al. (2021) does not work and the reference Venkataraman et al., 2020 presents a project report, but the reviewer found no description for the sampling setup. Please describe how sampling was performed to acquire representative samples. Did you quantify the dilution ratio of raw exhaust gas with ambient air and the sampling temperature? Both of these influence the partitioning of organic matter and therefore the volatility fractions that are in the particulate matter during sampling. (and as the paper discusses, different volatility fractions may exhibit different BrC absorption strengths).
Line 157: “The estimated BrC absorption could be underestimated due to excluded insoluble BrC and tarball structures, which possess high absorption strength (Corbin et al., 2019; Chakrabarty et al., 2023, 2010). The underestimation may be more pronounced within the dark-BrC region but comparatively lower in other BrC categories (figure 2), considering the inverse relationship between BrC absorption strength and solubility. (Saleh, 2020). In this study only two data points, observed marginally in the dark-BrC region, might be affected”
- It is important that this methodological limitation of excluding the methanol insoluble fraction of organic matter is mentioned here. It is also a good idea to refer to the wavelength dependency (w) vs. K_550 space presented by Saleh (2020). However, if your results indicate no low solubility organic matter in this space, but on the other hand your method excludes the analysis of methanol insoluble organic matter, is this not a circular argument? (i.e. your method restricts your data to show no insoluble organic matter in the w-k550 space.).
- Tarball structures are often present in all kinds of open biomass burning emissions. Could you explain why they would not be present in your samples?
- When comparing the results of this study to those presented by Saleh (2020), could you also discuss the methodological differences in these studies?
Line 165: “Thermo-optically resolved carbon fractions (OC1, OC2, OC3, OC4, EC1, EC2, and EC3) were used after pyrolytic correction to reconstruct the total organic carbon and total elemental carbon fractions (Chow et al., 2007).
- When making the pyrolytic correction, in which fraction did you add the pyrolytic carbon (PC)? Since pyrolytic carbon is originally organic carbon that pyrolyses during the OC-phase and decomposes during EC-phase, to the reviewer’s knowledge it is normally not assigned to any specific OC fractions.
Line 179: “The imaginary refractive index of BrC (kBrC,λ) was estimated by considering the density (𝜌) of freshly emitted OC to be 1.5 kg m-3”
- I assume that the density used was 1500 kg/m3? Please correct
Line 189: “w (AAE-1) indicates the spectral dependence of the imaginary refractive index (w)”
- Should it be “imaginary refractive index (k)” ?
Line 199: “Here, OA was derived by multiplying OC by a factor of 1.8”
- Is this assumption in agreement with the assumption of using 1,5 g/cm3 as the OA density? The method by Kuwata et al. (2012) could possibly be used to evaluate this.
Line 227: “The thermo-optically resolved carbon fractions show a decline in the total OC fraction, mainly OC3 and OC4 (a relatively low volatile fractions) with increasing BrC absorption strength (Figure 3a).
- This result sounds somewhat confusing. If mainly OC3 and OC4 fractions (which are the low volatility and solubility fractions) decline, one would expect to see a decrease in BrC absorption strength based on the Figure 2.
- Can you explain why specifically OC3+OC4 decline with increasing BrC absorption strength?
Line 256: “The large variation in kBrC,550 during agricultural residue burning could be due to differences in the combustion conditions and fuel properties”
- “Combustion conditions and fuel properties” is very broadly defined. It is very likely that they explain the observed variation.
Line 262: “The combustion conditions during these three activities are comparatively different could be because of the very low fuel feed rate.”
- If you have no data of the fuel feed rate, this sounds like unnecessary speculation and could be removed. The combustion conditions and combustion efficiencies are influenced by a large number of parameters. The fuel feed rate is not a good parameter to describe the combustion process, because of the variability in the combustion systems in this work. The air-fuel equivalence ratio would be a more precise parameter to describe the ratio of stoichiometric combustion air demand to the amount of available air in the combustion process. Moreover, distinguishing between open and closed combustion systems and reporting the fuel moisture contents could help the evaluate the data. Finally, if the measurements had included defining of the modified combustion efficiencies (by measuring CO and CO2 from the sampled gas/aerosol), it could be used to assess the differences in combustion conditions. Without any of such data I believe it will not be possible to explain the observed variation in the data.
Line 271: “The values reported in our study are in the upper range of ambient MACBrC,365 (0.62-2.3) reported previously over India (Sarkar et al., 2019; Shamjad et al., 2018; Satish et al., 2020; Rastogi et al., 2021; Rana et al., 2020; Kirillova et al., 2016; Dey et al., 2021).
- Could this be because this study analysed fresh exhaust particulate matter and in ambient studies photobleaching of BrC might decrease its MAC?
References
Kuwata M., Zorn S.R., Martin S.T. (2012) Using elemental ratios to predict the density of organic material composed of carbon, hydrogen, and oxygen. Environmental Science and Technology, 46 (2), 787 – 794, DOI: 10.1021/es202525q
Citation: https://doi.org/10.5194/egusphere-2024-1313-RC2 - AC1: 'Comment on egusphere-2024-1313', Navinya Chimurkar, 09 Oct 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-1313', Anonymous Referee #1, 23 Aug 2024
The manuscript “Brownness of organics in anthropogenic biomass burning aerosols over South Asia” by Chimurkar Navinya et al. measured the absorbance and its wavelength dependence of real-world brown carbon (BrC) from different biomass fuels and sources. It further connected this absorption (kBrC) and wavelength dependence (w) with the thermos-optically obtained volatility of OC, and applied the relationship between kBrC and w and OC/OA ratio to evaluate the spatial variations of kBrC and w over south Asia. The manuscript is well within the scope of the ACP journal. The ideas and methods are good, previous studies are well-referenced, and the structure of the manuscript is generally clear. However, in the Results and Discussion section, the narrations are not sufficient enough to support the authors’ views and there is a lack of proper connection between subsections. Therefore, the manuscript can only be accepted for publication in ACP after addressing the following questions.
Specific comments:
Line 136: it’s better to include the unit of each parameter
Line 143: “the absorption” to “the absorption coefficient”?
Line 161: solubility (Saleh, 2020).
Line 175: why do you think you can assume a 10% uncertainty in absorption coefficient?
Line 192: “study” to “studies”
Line 192: “, however,” to “. However,”
Line 221: the usage of correlation coefficient and R2 should be unified through the text
Lines 224-226: the sentence should be restructured. What do you think is the reason for the outliers? How many samples have you measured for each fuel and source type?
Lines 231-232: “Such relationships … .” any reference or explanation to this?
Line 249: . However,
Line 255: A similar relationship between kBrC,550 and BC/OA ratio has also been…
Lines 253-256: “In agricultural … and w (Figure 4).” Should this part be moved to the end of this subsection or section 3.3?
Section 3.3 I’m interested to see the measured relationship between kBrC,365 and BC/OA ratio. It’s also interesting to see a comparison of kBrC,365 between measured and indirectly inferred from the relationships between kBrC,550 and BC/OA ratio, w and BC/OA ratio, and w and kBrC,550 ratio.
Line 318: “, while most models…”? or restructure lines 314-319.
Lines 334-335: same to my comments to section 3.3, why do you have to estimate kBrC,365 from w and KBrC,550? Why can’t you estimate kBrC,365 from the relationship between measured kBrC,365 and BC/OA ratio?
Line 337: “shows very large kBrC”, could the figure have a problem? I couldn’t see very large kBrC in the northern hilly region from figure 5a or figure S6.
Lines 342-344: what I see from Figure S3 is that the absolute contribution of AGRI to kBrC in northwestern India is much lower than that of HEAT. Could you please reconsider this statement?
Line 350: Does “the extended time required for photobleaching” only apply to northern Idia?
Lines 332-350: a detailed interpretation of the distributions of source- and/or fuel-specific contributions to w, kBrC,365, and kBrC,550 could be interesting and helpful to the explanation of other views already presented in this paragraph.
Citation: https://doi.org/10.5194/egusphere-2024-1313-RC1 -
RC2: 'Comment on egusphere-2024-1313', Anonymous Referee #2, 15 Sep 2024
The manuscript provides important data and findings to assess the radiative forcing of BrC emissions in South Asia. The study fits well within the scope of ACP. The manuscript is well-written. It discusses the results in most cases properly and considers also relevant previous studies. The methods seem appropriate. However, the authors could discuss and elaborate the influence of the used methods on the obtained results and consider the methodological differences also when comparing the results of this study to those from previous studies (e.g. related to the methodologies used in sample collection and organic matter extraction from the collected filter samples). The results and conclusions are presented in a clear, concise, and well-structured way and the manuscript can be accepted after a minor revision, taking into account the following specific comments:
line 19: ”This leads to oversimplified model parameterization and subsequent underestimation of regional radiative forcing.”
- If refractive index (RF) has uncertainty, the current estimations may either underestimate or overestimate radiative forcing? Should this rather be “subsequent uncertainty” of regional radiative forcing?
Lines 112 “This study leverages samples of aerosol particle emissions collected on filter substrates during the COALESCE field campaign to propose a hypothesis regarding the BrC-BC continuum in BrC optical properties.”
- It remains unclear what is the hypothesis that is proposed. Please describe it.
Line 132: “The sampler is fully described in previous studies (Venkataraman et al., 2020; Kumari et al., 2021).
- Some basic information of the sampling system would be important. However, the link given for the reference Kumari et al. (2021) does not work and the reference Venkataraman et al., 2020 presents a project report, but the reviewer found no description for the sampling setup. Please describe how sampling was performed to acquire representative samples. Did you quantify the dilution ratio of raw exhaust gas with ambient air and the sampling temperature? Both of these influence the partitioning of organic matter and therefore the volatility fractions that are in the particulate matter during sampling. (and as the paper discusses, different volatility fractions may exhibit different BrC absorption strengths).
Line 157: “The estimated BrC absorption could be underestimated due to excluded insoluble BrC and tarball structures, which possess high absorption strength (Corbin et al., 2019; Chakrabarty et al., 2023, 2010). The underestimation may be more pronounced within the dark-BrC region but comparatively lower in other BrC categories (figure 2), considering the inverse relationship between BrC absorption strength and solubility. (Saleh, 2020). In this study only two data points, observed marginally in the dark-BrC region, might be affected”
- It is important that this methodological limitation of excluding the methanol insoluble fraction of organic matter is mentioned here. It is also a good idea to refer to the wavelength dependency (w) vs. K_550 space presented by Saleh (2020). However, if your results indicate no low solubility organic matter in this space, but on the other hand your method excludes the analysis of methanol insoluble organic matter, is this not a circular argument? (i.e. your method restricts your data to show no insoluble organic matter in the w-k550 space.).
- Tarball structures are often present in all kinds of open biomass burning emissions. Could you explain why they would not be present in your samples?
- When comparing the results of this study to those presented by Saleh (2020), could you also discuss the methodological differences in these studies?
Line 165: “Thermo-optically resolved carbon fractions (OC1, OC2, OC3, OC4, EC1, EC2, and EC3) were used after pyrolytic correction to reconstruct the total organic carbon and total elemental carbon fractions (Chow et al., 2007).
- When making the pyrolytic correction, in which fraction did you add the pyrolytic carbon (PC)? Since pyrolytic carbon is originally organic carbon that pyrolyses during the OC-phase and decomposes during EC-phase, to the reviewer’s knowledge it is normally not assigned to any specific OC fractions.
Line 179: “The imaginary refractive index of BrC (kBrC,λ) was estimated by considering the density (𝜌) of freshly emitted OC to be 1.5 kg m-3”
- I assume that the density used was 1500 kg/m3? Please correct
Line 189: “w (AAE-1) indicates the spectral dependence of the imaginary refractive index (w)”
- Should it be “imaginary refractive index (k)” ?
Line 199: “Here, OA was derived by multiplying OC by a factor of 1.8”
- Is this assumption in agreement with the assumption of using 1,5 g/cm3 as the OA density? The method by Kuwata et al. (2012) could possibly be used to evaluate this.
Line 227: “The thermo-optically resolved carbon fractions show a decline in the total OC fraction, mainly OC3 and OC4 (a relatively low volatile fractions) with increasing BrC absorption strength (Figure 3a).
- This result sounds somewhat confusing. If mainly OC3 and OC4 fractions (which are the low volatility and solubility fractions) decline, one would expect to see a decrease in BrC absorption strength based on the Figure 2.
- Can you explain why specifically OC3+OC4 decline with increasing BrC absorption strength?
Line 256: “The large variation in kBrC,550 during agricultural residue burning could be due to differences in the combustion conditions and fuel properties”
- “Combustion conditions and fuel properties” is very broadly defined. It is very likely that they explain the observed variation.
Line 262: “The combustion conditions during these three activities are comparatively different could be because of the very low fuel feed rate.”
- If you have no data of the fuel feed rate, this sounds like unnecessary speculation and could be removed. The combustion conditions and combustion efficiencies are influenced by a large number of parameters. The fuel feed rate is not a good parameter to describe the combustion process, because of the variability in the combustion systems in this work. The air-fuel equivalence ratio would be a more precise parameter to describe the ratio of stoichiometric combustion air demand to the amount of available air in the combustion process. Moreover, distinguishing between open and closed combustion systems and reporting the fuel moisture contents could help the evaluate the data. Finally, if the measurements had included defining of the modified combustion efficiencies (by measuring CO and CO2 from the sampled gas/aerosol), it could be used to assess the differences in combustion conditions. Without any of such data I believe it will not be possible to explain the observed variation in the data.
Line 271: “The values reported in our study are in the upper range of ambient MACBrC,365 (0.62-2.3) reported previously over India (Sarkar et al., 2019; Shamjad et al., 2018; Satish et al., 2020; Rastogi et al., 2021; Rana et al., 2020; Kirillova et al., 2016; Dey et al., 2021).
- Could this be because this study analysed fresh exhaust particulate matter and in ambient studies photobleaching of BrC might decrease its MAC?
References
Kuwata M., Zorn S.R., Martin S.T. (2012) Using elemental ratios to predict the density of organic material composed of carbon, hydrogen, and oxygen. Environmental Science and Technology, 46 (2), 787 – 794, DOI: 10.1021/es202525q
Citation: https://doi.org/10.5194/egusphere-2024-1313-RC2 - AC1: 'Comment on egusphere-2024-1313', Navinya Chimurkar, 09 Oct 2024
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Chimurkar Navinya
Taveen Singh Kapoor
Gupta Anurag
Chandra Venkataraman
Harish C. Phuleria
Rajan K. Chakrabarty
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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(1054 KB) - Metadata XML
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(1154 KB) - BibTeX
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- Final revised paper