the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 10 Jun 2025
Emission Factors and Optical Properties of Black and Brown Carbon Emitted at a Mixed-Conifer Forest Prescribed Burn
Abstract. Prescribed burning is a fuel management practice employed globally that emits carbonaceous aerosols that affect human health and perturb the global climate system. Aerosol black and brown carbon (BC and BrC) emission factors were calculated from ground and aloft smoke during prescribed burns at a mixed-conifer, montane forest site in the Sierra Nevada in California. BC emission factors were 0.52 ± 0.42 and 1.0 ± 0.48 g kg-1 for the smoldering and flaming combustion phases. MCE is a poor predictor of BC emission factor, in this study and published literature. We discuss limitations of using BC to PM2.5 mass emission ratios to generate emissions inventories. Using BC emission factors measured in this study, we recommend BC to PM2.5 ratios of 0.7 % and 9.5 % for the smoldering and flaming combustion. We calculated absorption Ångström exponents (AAE) based on multiwavelength absorption for BrC and BC of 6.26 and 0.67. Using the Delta-C method with a BrC-specific absorption cross-section, we estimate a smoldering combustion BrC emission factor of 7.0 ± 2.7 g kg-1, nearly 14 and 7 times greater than the smoldering and flaming BC emission factors. Furthermore, we estimate that BrC would account for 23 % and 82 %, respectively, of the solar radiation absorbed by the smoldering smoke in the atmosphere integrated over the solar spectrum (300–2500 nm) and in the UV spectrum (300–400 nm), indicating that BrC affects tropospheric photochemistry in addition to atmospheric warming.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.- Preprint
(1548 KB) - Metadata XML
-
Supplement
(5473 KB) - BibTeX
- EndNote
Status: final response (author comments only)
- RC1: 'Comment on egusphere-2025-2295', Anonymous Referee #1, 25 Aug 2025
-
RC2: 'Comment on egusphere-2025-2295', Anonymous Referee #2, 27 Aug 2025
This paper reports on a limited set of measurements made near prescribed fires from both ground sites and to a lesser extent with a drone. Optical properties, mass concentrations, and emission factors are calculated for BC and BrC for smoldering vs flaming combustion conditions based on measured MCEs. The results are compared relative to what is currently used in smoke models and inventories for predictions of smoke properties and impacts. There paper is well written, but the narrative seems to succinct with insufficient details. This is a complex topic with many uncertainties, which are not considered or discussed sufficiently.
Specific comments
Describe in more detail how representative sampling with the drone was done given the issue with downwash from the props. Was the sampling isokinetic, etc?
Briefly discuss the limitations of the AE33.
Regarding the Delta-C approach discussed in the Methods. The method seems flawed, and it is not clear from this discussion why it is utilized. The instrument (AE33) used at the ground site measures light absorption coefficients. The instruments may convert this light absorption measurement and report a mass concentration with an appropriate MAC. The MACs used for this conversion are known so the bap at the 7 wavelengths is known. For the delta-C, specifically state where the numbers in Eq2 come from, how does the AAE of BC = 1 come into the calculation. Where does the assumed MACs for BrC and BC being equal come from. State why exactly this method is used, since a different approach based on Eq3 is also used. Overall, should one continue to promote a flawed analysis?
Line 203. Why is background CO = 0 (Table S2). This is not possible. What is the variability in the background CO2 (this is not given in Table S2), how does this affect the uncertainty of the MCE?
Calculation of emissions using Equation 7. This is a highly uncertain calculation, and the limitations should be discussed. For example, what is the uncertainty in the BrC concentration which depends on the MAC used, which in turn depends on the type of BrC (see Saleh et al), which can change throughout the burning process. What is the uncertainty in weight fraction of carbon in the fuel (wc). What are the assumptions on which this formula is based. Eg, does it assume that by mass most C emitted is in the form of CO and CO2 – what about other forms of carbon, eg, OA? How does ground sampling a one location (over a short period of time), provide the emission factor representative of a large area with different fuels and properties (moisture content). The implicit assumption here (see statements made in the Conclusions) is that these reported EF apply broadly to these types of forests/fuels. Discuss the many assumptions and limitations.
Fig 4, specify what the error bars represent (eg, Aeth flow uncertainty…?), and how are they determined. Or was this data variability? Why in Fig 4a does the 95% CI converge to zero at about 600 nm. Fig 4b, BC AAE was determined based on two wavelengths? Seem highly uncertain (this is noted in a different context later in the paper). Justify that based on the extrapolation from 2 data points (wavelengths), the inference of BC size is reasonable, ie lines 339-342.
Why is the term Fuel-based emission factors used? Are the fuels and its conditions known? They don’t seem to be reported in any detail, only just general forest type is given.
Line 393-394 is not clear. What does the respectively refer to?
Line 397 to 399. This is an odd statement. Anything MAY be parameterized and used in global perditions, but it doesn’t mean it is correct. It is highly speculative to suggest that the very limited data reported here can be applied for global predictions.
Line 405-407 discuss use of this data to predict adverse health impacts. This is highly speculative and not supported by this study. For one, it assumes all BrC, as determined by this method, has a similar toxicity.
Does this work consider dark BrC or tar balls. Where do they contribute, ie, to BrC or BC? How do they effect the calculations of AAEs since the method used assumes absorption at the two highest wavelengths are only from BC, but tar balls (or dark BrC ) also absorb light at these high wavelengths.
Line 415-416. Doesn’t the health impact of prescribed vs wildfires depend on location (extent of exposures), or is PM toxicity being discussed here? This is possibly too broad a statement. Essentially, don’t all the statements here come down to simply that wildfires consume much more fuel than prescribed fires so have greater emissions and hence possible impacts.
Line 418-421 regarding “Indigenous fire stewardship should be centered in this aim”. This is an opinion and not a conclusion based on this study. There may be benefits to include indigenous knowledge, but why must it be the main focus (ie, centered)?
It is not clear how one can discuss BC/PM2.5 mass emission factors since PM2.5 mass was not measured (or was it)?
Many studies have assessed the radiative importance of BrC relative to BC similar to what was done here. It would be useful to add comparisons to other studies to put these results in context.
Citation: https://doi.org/10.5194/egusphere-2025-2295-RC2
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 492 | 38 | 12 | 542 | 24 | 12 | 30 |
- HTML: 492
- PDF: 38
- XML: 12
- Total: 542
- Supplement: 24
- BibTeX: 12
- EndNote: 30
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
see attached PDF.