the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 Jul 2023
Parameterizations of US wildfire and prescribed fire emission ratios and emission factors based on FIREX-AQ aircraft measurements
Georgios I. Gkatzelis
Matthew M. Coggon
Chelsea E. Stockwell
Rebecca S. Hornbrook
Hannah Allen
Eric C. Apel
Katherine Ball
Megan M. Bela
Donald R. Blake
Ilann Bourgeois
Steven S. Brown
Pedro Campuzano-Jost
Jason M. St. Clair
James H. Crawford
John D. Crounse
Douglas A. Day
Joshua DiGangi
Glenn Diskin
Alan Fried
Jessica Gilman
Hongyu Guo
Johnathan W. Hair
Hannah A. Halliday
Thomas F. Hanisco
Reem Hannun
Alan Hills
Gregory Huey
Jose L. Jimenez
Joseph M. Katich
Aaron Lamplugh
Young Ro Lee
Jin Liao
Jakob Lindaas
Stuart A. McKeen
Tomas Mikoviny
Benjamin A. Nault
James A. Neuman
John B. Nowak
Demetrios Pagonis
Jeff Peischl
Anne E. Perring
Felix Piel
Pamela S. Rickly
Michael A. Robinson
Andrew W. Rollins
Thomas B. Ryerson
Melinda K. Schueneman
Rebecca H. Schwantes
Joshua P. Schwarz
Kanako Sekimoto
Vanessa Selimovic
Taylor Shingler
David J. Tanner
Laura Tomsche
Krystal Vasquez
Patrick R. Veres
Rebecca Washenfelder
Petter Weibring
Paul O. Wennberg
Armin Wisthaler
Glenn Wolfe
Caroline Womack
Robert Yokelson
Carsten Warneke
Abstract. Extensive airborne measurements of non-methane organic gases (NMOGs), methane, nitrogen oxides, reduced nitrogen-species, and aerosol emissions from US wild and prescribed fires were conducted during the 2019 NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality campaign (FIREX-AQ). Here, we report the atmospheric enhancement ratios (ERs) and inferred emission factors (EFs) for compounds measured onboard the NASA DC-8 research aircraft for nine wildfires and one prescribed fire, which encompass a range of vegetation types.
We use photochemical proxies to identify young smoke and reduce the effects of chemical degradation on our emissions calculations. ERs and EFs calculated from FIREX-AQ observations agree within a factor of 2 with values reported from previous laboratory and field studies for more than 80 % of the carbon- and nitrogen-containing species. Wildfire emissions are parameterized based on correlations of the sum of NMOGs with reactive nitrogen oxides (NOy) to modified combustion efficiency (MCE) as well as other chemical signatures indicative of flaming/smoldering combustion, including carbon monoxide (CO), nitrogen dioxide (NO2), and black carbon aerosol. The sum of primary NMOG EFs correlates to MCE with an R2 of 0.68 and a slope of -296 ± 51 g kg-1, consistent with previous studies. The sum of the NMOG mixing ratios correlates well with CO with an R2 of 0.98 and a slope of 137 ± 4 ppbv of NMOGs per ppmv of CO, demonstrating that primary NMOG emissions can be estimated from CO. Individual nitrogen-containing species correlate better with NO2, NOy, and black carbon than with CO. More than half of the NOy in fresh plumes is NO2 with an R2 of 0.95 and a ratio of NO2 to NOy of 0.55 ± 0.05 ppbv ppbv-1, highlighting that fast photochemistry had already occurred in the sampled fire plumes. The ratio of NOy to the sum of NMOGs follows trends observed in laboratory experiments and increases exponentially with MCE, due to increased emission of key nitrogen species and reduced emission of NMOGs at higher MCE during flaming combustion. These parameterizations will provide more accurate boundary conditions for modeling and satellite studies of fire plume chemistry and evolution to predict the downwind formation of secondary pollutants, including ozone and secondary organic aerosol.
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Georgios I. Gkatzelis et al.
Status: closed
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RC1: 'Comment on egusphere-2023-1439', Anonymous Referee #1, 27 Jul 2023
This paper reports enhancement ratios (ERs) and "inferred" emission factors (EFs) for gas- and particle species measured in the smoke plumes of 9 western U.S. wildfires (and one eastern prescribed fire) during the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign. The measurements were collected aboard the NASA DC-8 with what may be the most comprehensive instrument payload ever deployed for measuring atmospheric chemistry of biomass burning emissions. ERs and EFs are based on 16 cross-wind plume transects deemed to have the least photochemical aging based on measured ratios of furan, a fats-reacting primary biomass burning product, and maleic anhydride (a slow reacting secondary product). The paper focuses on emissions of non-methane organic gases (NMOG) and reactive nitrogen-containing compounds (NOy). In addition to ERs and EFs, the paper provides emission parameterizations for total NMOG and NOy which could be used with satellite observations of CO and NO2 to provide boundary conditions for atmospheric chemistry modeling.
Until very recently, detailed chemical speciation of relatively un-aged wildfire plumes in the western U.S. were unavailable. The 2013 SEAC4RS campaign provided the first such measurements, but for only a couple of wildfires. The wildfire focused 2018 Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE-CAN) provided detailed chemical speciation of emissions and ERs and EFs for multiple western wildfires.
This paper builds upon these previous studies and further expands and improves our understanding of emissions from western U.S wildfires:
1. Additional measurements of highly variable process - The relative abundance of pollutants in "fresh" wildfire smoke is highly variable as it depends on fire behavior, fuels, and environmental conditions, all of which have high natural variability. Therefore, the additional ER and EF measurements provided in this study improve our characterization of emissions for western U.S. wildfires.
2. Expanded chemical speciation - The extensive payload allows for more detailed speciation of NMOG and nitrogen-containing species than provided by previous studies.
3. Reduced measurement uncertainty - NMOG were predominantly measured using four instruments: the NOAA proton transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS), two whole air samplers (WAS) and the NOAA fast online gas chromatograph outfitted with a Time-of-Flight mass spectrometer (TOGA). Many of the NMOG species were measured by multiple instruments providing a means to reduce uncertainty.
4. Direct tie-in to extensive laboratory experiments - The NOAA PTR-ToF-MS was the same instrument used in FIREX 2016, the laboratory prequel to FIREX-AQ, provding a direct tie-in to the extensive lab measurements of biomass burning emissions form western U.S. fuels. This provides an improved interpretation of airborne measurements
5. The study uses a "photochemical clock" to select least processed emissions - ERs and EFs from measurements of smoke that is less photochemically aged than previous studies, as demonstrated by the relative yields of primary and secondary products.
6. Parameterization of NMOG and NOy emissions - provides a potential pathway for employing satellite based measurements of total column CO and NO2 to estimate fire emissions for atmospheric modeling.
Minor Comments
1. Table 1- Please described how the fuels were determined. Also, were the fuels extracted from area burned on day of flights?
2. The monoterpene ratio for FIREX-AQ/Firleab = 1.57. Did Firelab have better speciation of monoterpenes? If so, does this reflect differences in harvested vs. in-situ fuels?
3. FIREX-AQ EF vs. WE-CAN EF (Table S6): FIREX-AQ/WE-CAN is 0.16 for HCN and 3.33 for HNCO. Can the authors provide any thought on possible reason for these large differences?
4. Did the authors consider testing the ethyne/furan ratio based partitioning of NMOG emissions presented in Sekimoto et al. (2018) with the FIREX-AQ field data?
5. L489-491: "The dotted lines and shaded regions show FireLab parameterizations that describe how these ratios respond to changes in MCE (Roberts et al., 2020) for one fire burned during FireLab"
What fuel type in Firelab burn featured in Fig. 6? Are these curves indicative of typical Firelab burns?
6. L255-256: Fire plumes sampled closest to the emission source that showed significant chemical processing with a MA/F > 0.20 are excluded from this analysis.
How was the photochemical processing threshold of MA/F > 0.2 selected?
Given that maleic anhydride has multiple precursors in biomass smoke (other furans), that it is produced a couple reaction steps after the initial OH rxn, and that it has many production pathways, do the authors expect the relationship between MA/F ratio and photochemical activity be roughly the same across the 16 plumes? Could different emission rates/relative abundances of other furans and NOx or different photolysis environment significantly impact yields of MA?
7. L313: …uncertainties due to differences in calibration or canister effects are small.
Table S5. In the case of furan, the WAS/NOAA PTR and iWAS/NOAA PTR agree with one another but are less than half the TOGA/NOAA PTR. This would seem to suggest that furan loss in the canisters is significant.
8. L593-595: We suggest that these differences could be due to differences in the fuel, quantification methods applied for each study, as well as due to differences in photochemical loss of reactive species prior to detection.
Perhaps fire behavior and lofting of smoke (i.e. differential mix of flaming & smoldering) play a role as well.
Technical Comments
Figure 7 - Using fire names as labels makes it difficult to gauge location of actual measurement values on the plots. I suggest using markers instead.
Fig S4. Are the R2 for individual NMOG based on NMOG and CO medians of the 16 transects?
Citation: https://doi.org/10.5194/egusphere-2023-1439-RC1 -
RC2: 'Comment on egusphere-2023-1439', Anonymous Referee #2, 08 Aug 2023
General Comments:
This manuscript presents calculated emission ratios and emission factors from the FIREX-AQ campaign, comparing them to WECAN and the FIREX-AQ Laboratory emission factors. This work presents a detailed analysis of differences in the observed emissions between these campaigns due to instrumentation and smoke age. While not particularly exciting the manuscript is an important contribution to understanding wildfire emission factors and ratios based on the limitations of the instrumentation and field sampling design.
Specific Comments:
Line 154: “performed fast response in situ measurements” seems to include the whole air samplers which isn’t accurate since those canisters are collected on the aircraft and analyzed later. Clarifying this point and adding addition information on how many of the WAS samples met the low photochemical processing threshold for the EF and ER calculations would be useful since the number of data points per flight is limited.
Line 334: For the equation. What if there is no carbon in the compound (much of Figure 3b)?
Figure 7: It doesn’t seem like the fire name is important to the figure (the fires aren’t specifically referenced in the text) and just make the plots more difficult to read.
Table 3: In the text you discuss some compound show better a relationship with NO2. Clarify in table 3 that the ERs are to CO. And consider adding a table (in text or to the supplement) of those species that should use NO2.
Technical Corrections:
Figure 3: CO is too light and could be offset some to see the trace better. The overall quality of the figures should be improved.
Figure 5: it is very difficult to read these figure – the resolution seems poor and the size is rather small.
Line 476: instead of “On the contrary” - In contrast
Citation: https://doi.org/10.5194/egusphere-2023-1439-RC2 - AC1: 'Comment on egusphere-2023-1439', Matthew Coggon, 01 Oct 2023
Status: closed
-
RC1: 'Comment on egusphere-2023-1439', Anonymous Referee #1, 27 Jul 2023
This paper reports enhancement ratios (ERs) and "inferred" emission factors (EFs) for gas- and particle species measured in the smoke plumes of 9 western U.S. wildfires (and one eastern prescribed fire) during the 2019 Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) campaign. The measurements were collected aboard the NASA DC-8 with what may be the most comprehensive instrument payload ever deployed for measuring atmospheric chemistry of biomass burning emissions. ERs and EFs are based on 16 cross-wind plume transects deemed to have the least photochemical aging based on measured ratios of furan, a fats-reacting primary biomass burning product, and maleic anhydride (a slow reacting secondary product). The paper focuses on emissions of non-methane organic gases (NMOG) and reactive nitrogen-containing compounds (NOy). In addition to ERs and EFs, the paper provides emission parameterizations for total NMOG and NOy which could be used with satellite observations of CO and NO2 to provide boundary conditions for atmospheric chemistry modeling.
Until very recently, detailed chemical speciation of relatively un-aged wildfire plumes in the western U.S. were unavailable. The 2013 SEAC4RS campaign provided the first such measurements, but for only a couple of wildfires. The wildfire focused 2018 Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE-CAN) provided detailed chemical speciation of emissions and ERs and EFs for multiple western wildfires.
This paper builds upon these previous studies and further expands and improves our understanding of emissions from western U.S wildfires:
1. Additional measurements of highly variable process - The relative abundance of pollutants in "fresh" wildfire smoke is highly variable as it depends on fire behavior, fuels, and environmental conditions, all of which have high natural variability. Therefore, the additional ER and EF measurements provided in this study improve our characterization of emissions for western U.S. wildfires.
2. Expanded chemical speciation - The extensive payload allows for more detailed speciation of NMOG and nitrogen-containing species than provided by previous studies.
3. Reduced measurement uncertainty - NMOG were predominantly measured using four instruments: the NOAA proton transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS), two whole air samplers (WAS) and the NOAA fast online gas chromatograph outfitted with a Time-of-Flight mass spectrometer (TOGA). Many of the NMOG species were measured by multiple instruments providing a means to reduce uncertainty.
4. Direct tie-in to extensive laboratory experiments - The NOAA PTR-ToF-MS was the same instrument used in FIREX 2016, the laboratory prequel to FIREX-AQ, provding a direct tie-in to the extensive lab measurements of biomass burning emissions form western U.S. fuels. This provides an improved interpretation of airborne measurements
5. The study uses a "photochemical clock" to select least processed emissions - ERs and EFs from measurements of smoke that is less photochemically aged than previous studies, as demonstrated by the relative yields of primary and secondary products.
6. Parameterization of NMOG and NOy emissions - provides a potential pathway for employing satellite based measurements of total column CO and NO2 to estimate fire emissions for atmospheric modeling.
Minor Comments
1. Table 1- Please described how the fuels were determined. Also, were the fuels extracted from area burned on day of flights?
2. The monoterpene ratio for FIREX-AQ/Firleab = 1.57. Did Firelab have better speciation of monoterpenes? If so, does this reflect differences in harvested vs. in-situ fuels?
3. FIREX-AQ EF vs. WE-CAN EF (Table S6): FIREX-AQ/WE-CAN is 0.16 for HCN and 3.33 for HNCO. Can the authors provide any thought on possible reason for these large differences?
4. Did the authors consider testing the ethyne/furan ratio based partitioning of NMOG emissions presented in Sekimoto et al. (2018) with the FIREX-AQ field data?
5. L489-491: "The dotted lines and shaded regions show FireLab parameterizations that describe how these ratios respond to changes in MCE (Roberts et al., 2020) for one fire burned during FireLab"
What fuel type in Firelab burn featured in Fig. 6? Are these curves indicative of typical Firelab burns?
6. L255-256: Fire plumes sampled closest to the emission source that showed significant chemical processing with a MA/F > 0.20 are excluded from this analysis.
How was the photochemical processing threshold of MA/F > 0.2 selected?
Given that maleic anhydride has multiple precursors in biomass smoke (other furans), that it is produced a couple reaction steps after the initial OH rxn, and that it has many production pathways, do the authors expect the relationship between MA/F ratio and photochemical activity be roughly the same across the 16 plumes? Could different emission rates/relative abundances of other furans and NOx or different photolysis environment significantly impact yields of MA?
7. L313: …uncertainties due to differences in calibration or canister effects are small.
Table S5. In the case of furan, the WAS/NOAA PTR and iWAS/NOAA PTR agree with one another but are less than half the TOGA/NOAA PTR. This would seem to suggest that furan loss in the canisters is significant.
8. L593-595: We suggest that these differences could be due to differences in the fuel, quantification methods applied for each study, as well as due to differences in photochemical loss of reactive species prior to detection.
Perhaps fire behavior and lofting of smoke (i.e. differential mix of flaming & smoldering) play a role as well.
Technical Comments
Figure 7 - Using fire names as labels makes it difficult to gauge location of actual measurement values on the plots. I suggest using markers instead.
Fig S4. Are the R2 for individual NMOG based on NMOG and CO medians of the 16 transects?
Citation: https://doi.org/10.5194/egusphere-2023-1439-RC1 -
RC2: 'Comment on egusphere-2023-1439', Anonymous Referee #2, 08 Aug 2023
General Comments:
This manuscript presents calculated emission ratios and emission factors from the FIREX-AQ campaign, comparing them to WECAN and the FIREX-AQ Laboratory emission factors. This work presents a detailed analysis of differences in the observed emissions between these campaigns due to instrumentation and smoke age. While not particularly exciting the manuscript is an important contribution to understanding wildfire emission factors and ratios based on the limitations of the instrumentation and field sampling design.
Specific Comments:
Line 154: “performed fast response in situ measurements” seems to include the whole air samplers which isn’t accurate since those canisters are collected on the aircraft and analyzed later. Clarifying this point and adding addition information on how many of the WAS samples met the low photochemical processing threshold for the EF and ER calculations would be useful since the number of data points per flight is limited.
Line 334: For the equation. What if there is no carbon in the compound (much of Figure 3b)?
Figure 7: It doesn’t seem like the fire name is important to the figure (the fires aren’t specifically referenced in the text) and just make the plots more difficult to read.
Table 3: In the text you discuss some compound show better a relationship with NO2. Clarify in table 3 that the ERs are to CO. And consider adding a table (in text or to the supplement) of those species that should use NO2.
Technical Corrections:
Figure 3: CO is too light and could be offset some to see the trace better. The overall quality of the figures should be improved.
Figure 5: it is very difficult to read these figure – the resolution seems poor and the size is rather small.
Line 476: instead of “On the contrary” - In contrast
Citation: https://doi.org/10.5194/egusphere-2023-1439-RC2 - AC1: 'Comment on egusphere-2023-1439', Matthew Coggon, 01 Oct 2023
Georgios I. Gkatzelis et al.
Georgios I. Gkatzelis et al.
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Cited
4 citations as recorded by crossref.
- Assessing formic and acetic acid emissions and chemistry in western U.S. wildfire smoke: implications for atmospheric modeling W. Permar et al. 10.1039/D3EA00098B
- Fuel-Type Independent Parameterization of Volatile Organic Compound Emissions from Western US Wildfires K. Sekimoto et al. 10.1021/acs.est.3c00537
- Emission Factors for Crop Residue and Prescribed Fires in the Eastern US During FIREX‐AQ K. Travis et al. 10.1029/2023JD039309
- Comparison of airborne measurements of NO, NO2, HONO, NOy, and CO during FIREX-AQ I. Bourgeois et al. 10.5194/amt-15-4901-2022