Ground solar absorption observations of total column CO, CO2, CH4, and aerosol optical depth from California’s Sequoia Lightning Complex Fire: Emission factors and modified combustion efficiency at large scales
Abstract. With global wildfires becoming more widespread and severe, tracking their emissions of greenhouse gases and air pollutants is becoming increasingly important. Wildfire emissions have primarily been characterized by in situ laboratory, and field observations at fine scales. While this approach captures the mechanisms relating emissions to combustion phase and fuel properties, their evaluation on large scale plumes has been limited. In this study, we report remote observations of total column trace gases and aerosols in the 2020 wildfire season of smoke plumes from the Sierra Nevada of California with an EM27/SUN solar Fourier transform infrared (FTIR) spectrometer. We derive total column aerosol optical depth (AOD), emission factors (EF) and modified combustion efficiency (MCE) for these fires, and evaluate relationships between them based on combustion phase at large scales. We demonstrate that the EM27/SUN effectively detects changes of CO, CO2 and CH4 in the atmospheric column at ~10 km scales that are attributed to wildfire emissions. These observations are used to derive total column EFCO of 120.5 ± 12.2 and EFCH4 of 4.3 ± 0.8 for a large smoke plume event in mixed combustion phases. These values are consistent with in situ relationships measured in similar temperate coniferous forest wildfires. FTIR derived AOD was compared to a nearby AERONET station and observed ratios of AOD to XCO were consistent with those previously observed from satellites. We also show that co-located XCO observations from the TROPOMI satellite-based instrument are 9.7 % higher than our EM27/SUN observations during the wildfire period. Finally, we put wildfire CH4 emissions in context of the California state CH4 budget and estimate that 213.7 ± 49.8 Gg CH4 were emitted by large wildfires in California during 2020, about 13.6 % of the total state CH4 emissions in 2019. Our novel application of an EM27/SUN solar spectrometer to quantify wildfire emission ratios at large scales follows predictive relationships that are consistent with in situ studies, offering promise for extensive monitoring from ground networks and satellite remote sensing.
Isis Frausto-Vicencio et al.
Isis Frausto-Vicencio et al.
Isis Frausto-Vicencio et al.
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In this work, the authors use FTIR (EM27/SUN) measurements of XCO, XCO2, XCH4, and AOD to estimate fire emission factors and combustion phases during the 2020 wildfire seasons in California. Focusing on two major fires, the Creek and the Sequoia Lightning fires, they report emission factors (EFCO/CO2 and EFCH4/CO2) and modified combustion efficiency (MCE) and compare them to values reported in the literature. In addition, XCO derived from the EM27/SUN is compared to TROPOMI observations in wildfires, suggesting an overestimation of about 10% of the satellite. Finally, the authors estimate emission of CH4 from wildfire and discuss this value with regards to the California CH4 state budget.
While the scientific asset of using such an instrument to study wildfire is explicit, discussion about the limitation of this study is clearly missing.
The paper is well written and easy to follow. Some parts are however very repetitive and the manuscript would need some restructuring. There are some repetitions in the paper and authors should reorganize some parts to make it more concise. For instance, some similar sentences are shown in different parts throughout the paper: lines 78-80 similar to lines 240-244, line 557-559 is quasi similar to lines 94-96, and 26-28.
The discussion section is interesting and well written. The introduction section should be more concise and emphasize the research state of art. More appropriate references are needed. I would recommend not using references in the conclusion section and focusing on summarizing the main results of this study. A paragraph in the conclusion is missing to highlight the limitations and the perspectives of this work.
Although authors are very thorough in the sensitivity tests, the main concerns are error estimations and background measurements.
The error estimations are missing in this study. There are no estimation of the measurement uncertainties of Xgas and AOD which should be incorporated and propagated in the calculation of ER, EF and MCE. The slopes of the linear fits should reflect errors propagation and be mentioned with an error bar (+-).
The background values are very important in the ER computation. How can you ensure that the 2nd percentile of the daily measured mixing ratios represent the background at this location? Why comparing the background SJV values to the very remote location of Mauna Loa? Could you find appropriate background values located at closer sites (Caltech, Mont Wilson, Dryden, other)? The ER values greatly depend on background concentrations and measurement precision. Error bars should be added to these estimates.
Some figures could be improved for clarity purpose. Ex: the time series does not display well intraday variations.
The word “large scale” is recurrent in the manuscript and does not seem to be appropriated. Is regional more appropriated? The title should be modified since “large scales” is vague.
Overall, this paper addresses relevant scientific questions within the scope of ACP journal, which is why I recommend its publication.
Please clarify the differences between Emission Ratios and Enhancement Ratios.
Abstract line 19: please define at “10km scales”. Is it vertical or horizontal scale?
Line 57: “fire conditions”, please explain what conditions.
Figure 3b: the error bars are the standard deviation. Errors on both TROPOMI and EM27/SUN measurements should be included in the linear fit.
Section 3.3: authors state that FTIR and AERONET AOD are in agreement. What is the R value? How can you prove it?
Figure 4: reduce point size or find a solution to better display intraday variations.
Figure 5: What are the measurement errors? Could you propagate the errors to obtain slopes values with all uncertainties?
Figure 9: what is the error bar on the Top 20 CA wildfires emissions?
Please verify the order of the references in the parenthesis throughout the manuscript. It should follow the ACP journal recommendations: https://www.atmospheric-chemistry-and physics.net/submission.html#references (ex: line 72; lines 110-111; …)
Title of section 3.5 should be more specific. SJV GHG’s sources are only dairy farms?
Line 34-35: Rephrase this sentence and define particulate matter 2.5.
Line 56: Is reference “CARB 2018” appropriate?
Line 51: Is IPCC 2014 correct? Can you refer to a more recent report?
Line 65-66, 69, 70, 71 and more: add references.
Figure 5, 8: Change dots color or size to clearly display all the points.
Figure 3b, 6, D1: R2 should be R2