the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 06 Aug 2025
Strong Primary Contribution to Brown Carbon Light Absorption in Tibet and Urban Areas: Insights based on in situ measurements
Abstract. To investigate optical properties, sources, and radiative effects of brown carbon (BrC), we conducted synchronous field campaigns in the Qinghai–Tibet Plateau (Yangbajing) and urban Guangzhou in July 2022, using multi-wavelength Aethalometer (AE33) and aerosol mass spectrometer (AMS) measurements. Total aerosol and BrC light absorption coefficients at 370 nm (Abstotal: 1.6 ± 1.6 M m⁻¹; BrC: 0.2 ± 0.3 M m⁻¹) in Tibet were an order of magnitude lower than Guangzhou, attributed to extremely low aerosol/organic aerosol (OA) mass concentrations. However, BrC fractions in Abstotal (15 % vs. 21 % at 370 nm) correlated with primary OA (POA) ratios, highlighting anthropogenic emission impacts even in this clean background. Diurnal variations (morning/evening peaks) of source-specific BrC absorption were regulated by local emissions (e.g., biomass burning, traffic) and regional secondary formation. Source apportionment (PMF/MLR) revealed primary sources (biomass burning OA, hydrocarbon-like OA) dominated BrC absorption (>75 %). Vehicle hydrocarbon-like OA (HOA) MAC (2.08 m² g⁻¹ in Tibet; 2.57 m² g⁻¹ in Guangzhou) was comparable to biomass burning OA (1.11–2.54/1.91 m² g⁻¹), indicating high fossil fuel BrC absorption. Integrated "simple forcing efficiency" (370–660 nm) showed primary emissions contributed >98 % of total radiative forcing at both sites. This study advances understanding of BrC dynamics and sources in diverse environments, underscores primary sources’ critical role in BrC absorption, and emphasizes the need for source-specific OA optical parameterization.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-2974', Anonymous Referee #2, 16 Sep 2025
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RC2: 'Comment on egusphere-2025-2974', Anonymous Referee #3, 30 Sep 2025
This manuscript presents interesting field measurements in the Qinghai–Tibet Plateau (Yangbajing) and urban Guangzhou during July 2022 with established measurement techniques including multi-wavelength Aethalometer and online aerosol mass spectrometer (AMS and ACSM) measurements to quantify black carbon (BC), brown carbon (BrC), and organic aerosols. Source apportionment (positive matrix factorization, PMF) and multilinear regression analysis were conducted to provide further insights on BrC source-specific mass absorption cross-sections (MAC), and a simple forcing efficiency (SFE) for individual OA factors. This work clearly falls within the scope of ACP, focusing on aerosol light absorption properties, radiative forcing, and aerosol composition. In addition, the manuscript provides a valuable comparison between a polluted city environment and a “pristine” environment (i.e., YBJ site), for which very few datasets have been reported so far.
However, the Method sections should include more technical details to further support the results and interpretation. And some results should be discussed further to extract more value from the dataset hence to improve the manuscript’s relevance and importance. I recommend publication after the points outlined below are addressed.
A few general comments. It would be useful to provide a broader discussion of the impact of BrC on radiative forcing in both regional and global contexts. There are some comments in the introduction and conclusion sections but they are rather scattered. This could be difficult for readers not familiar with aerosol speciation and its connection to regional BrC.
SP-AMS was referred in Section 2.3 (L154) and SI. However, insufficient operational information were provided. With the results and information provided by the SI, I would assume the instrument was operated with tungsten vaporizer. In that regard, the instrument is typically referred to as the “high-resolution aerosol mass spectrometer (HR-AMS or HR-ToF-AMS)”. If dual vaporizer mode was used, please provide the relevant details, as this would also affect the interpretation of the PMF results (e.g., refractory BC should be included in the PMF analysis).
For AMS and ACSM PMF analysis, only limited justification is provided in the SI and I have several questions:
- For the AMS PMF, In Fig. S2a, the Q/Qexp dropped below 1.0 after the 2-factor solution. Could you provide more justification for factor separation? All of your measurements peak at 0800 but not 2200 LT while the above 3 factors have similar diurnal profile, and some overlapping spectra. Could you provide more evidence?
- Following the above question, rBC and metal detected by the dual vaporization mode can help separate sources further (Bibi et al., 2021; Ma et al., 2025; Rivellini et al., 2020). It is relevant for the context since the HOA and BBOA have very similar diurnal profile. If the instrument measured with dual vaporization mode, PMF should be evaluated with refractory components.
- For Fig. S4a, it is somewhat confusing to label peaks using m/z values since they are high-resolution PMF results.
- For the ACSM PMF, please provide the rationale for constraining BBOA.
- Changes in final PMF factors will affect MLR analysis.
For the assumption of AAEBC value, could you elaborate more on the decision to use 0.8-1.2 range? To be specific, L203 stated “In this study, the value of AAE 1.4 lead to most of the BrC light absorption coefficient to be negative values…” However, some studies have shown that thermal denuded BCAAE values can be higher than 1.4 (e.g., Török et al., 2018). I may miss the justification of BrC existence at both sites.
Minor comments
A few sentences could be reorganized to improve clarity, particularly at L38-41,L87-90, and L289-292.
L289: revise to …”where BrC contributes the most”
L 445-448. Do you mean some of the HOA is transported? It is interesting the se, at YBJ site, HOA increased at night time while NO stay flat or decreased. What are the sources to the strong morning NO spike at YBJ and GIG sites?
L525: …”Singapore during winter” is misleading as Singapore do not have winter season based on temperature.
Reference
Bibi, Z., Coe, H., Brooks, J., Williams, P. I., Reyes-Villegas, E., Priestley, M., Percival, C. J., and Allan, J. D.: Technical note: A new approach to discriminate different black carbon sources by utilising fullerene and metals in positive matrix factorisation analysis of high-resolution soot particle aerosol mass spectrometer data, Atmospheric Chem. Phys., 21, 10763–10777, https://doi.org/10.5194/acp-21-10763-2021, 2021.
Ma, M., Rivellini, L.-H., Zong, Y., Kraft, M., Yu, L. E., and Lee, A. K. Y.: Advances in characterization of black carbon particles and their associated coatings using the soot-particle aerosol mass spectrometer in Singapore, a complex city environment, Atmospheric Chem. Phys., 25, 8185–8211, https://doi.org/10.5194/acp-25-8185-2025, 2025.
Rivellini, L. H., Adam, M. G., Kasthuriarachchi, N., and Lee, A. K. Y.: Characterization of carbonaceous aerosols in Singapore: insight from black carbon fragments and trace metal ions detected by a soot particle aerosol mass spectrometer, Atmospheric Chem. Phys., 20, 5977–5993, https://doi.org/10.5194/acp-20-5977-2020, 2020.
Török, S., Malmborg, V. B., Simonsson, J., Eriksson, A., Martinsson, J., Mannazhi, M., Pagels, J., and Bengtsson, P.-E.: Investigation of the absorption Ångström exponent and its relation to physicochemical properties for mini-CAST soot, Aerosol Sci. Technol., 2018.
Citation: https://doi.org/10.5194/egusphere-2025-2974-RC2
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General Comments
This manuscript presents concurrent field campaigns in the Qinghai–Tibet Plateau (Yangbajing) and urban Guangzhou during July 2022, combining multi-wavelength Aethalometer and aerosol mass spectrometer (AMS) measurements to quantify brown carbon (BrC) optical properties, identify their sources, and estimate radiative forcing. The authors apply positive matrix factorization (PMF) for source apportionment, multiple linear regression (MLR) to derive source-specific mass absorption cross-sections (MAC), and a simple forcing efficiency (SFE) approach to estimate BrC radiative effects. The study is well-motivated, addressing an important gap in quantifying BrC MAC specific for individual OA factors, in a high-altitude background environment, while providing a direct urban–background comparison under simultaneous meteorological conditions.
The dataset is valuable, especially for the Tibetan site where few high-time-resolution BrC source apportionments exist. The methodology is robust and well-documented, and the analyses are generally clear. The findings are important for both modeling and policy-relevant emission reduction strategies. The observation that fossil fuel–related BrC has comparable MAC to biomass burning–related BrC in these environments is noteworthy.
However, several aspects could be clarified or expanded to strengthen the manuscript’s contribution. I recommend publication after minor revisions addressing the points below.
Major Issues
The introduction should more clearly articulate the broader relevance of the central QTP measurements—particularly for regional climate forcing and glacier melt—and distinguish them from prior work on the QTP margins.
Line 25: the authors state that BrC contribute to 12-50% of the total positive radiative forcing. It would improve clarity if they would specify whether it is the total human-induced radiative forcing (which is generally dominated by greenhouse gases), or the positive radiative forcing related just to atmospheric particles (I suspect this is what they meant).
Line 31: Clarify “non-fossil biomass burning,” which is not a standard term. Rephrase the following sentence so it does not imply that fossil-fuel OA lacks any absorptive properties.
Editorial Suggestions