# Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ)

Carten Warneke, Joshua P. Schwarz, Jack Dibb, Olga Kalashnikova, Gregory Frost, Jassim Al-Saad, Steven S. Brown, Wm. Alan Brewer, Amber Soja, Felix C. Seidel, et al.

<figure><img src="image_1.png" /></figure>

## To cite this version:

Carten Warneke, Joshua P. Schwarz, Jack Dibb, Olga Kalashnikova, Gregory Frost, et al. Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ). Journal of Geophysical Research: Atmospheres, 2023, Journal of Geophysical Research: Atmospheres, 128, 10.1029/2022JD037758. [hal-04465865](https://hal-univ-lille.fr/hal-04465865)

HAL Id: hal-04465865

https://hal.univ-lille.fr/hal-04465865

Submitted on 19 Feb 2024

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

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<figure><img src="image_2.png" /></figure>
# Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ)

Carten Warneke, Joshua P. Schwarz, Jack Dibb, Olga Kalashnikova, Gregory Frost, Jassim Al-Saad, Steven S. Brown, Wm. Alan Brewer, Amber Soja, Felix C. Seidel, et al.

<figure><img src="image_1.png" /></figure>

## To cite this version:

Carten Warneke, Joshua P. Schwarz, Jack Dibb, Olga Kalashnikova, Gregory Frost, et al. Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ). Journal of Geophysical Research: Atmospheres, 2023, Journal of Geophysical Research: Atmospheres, 128, 10.1029/2022JD037758. [https://lilloa.hal.science/hal-04465865v1](https://lilloa.hal.science/hal-04465865v1)

HAL Id: hal-04465865

[https://lilloa.hal.science/hal-04465865v1](https://lilloa.hal.science/hal-04465865v1)

Submitted on 19 Feb 2024

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

<figure><img src="image_2.png" /></figure>
# JGR Atmospheres

## RESEARCH ARTICLE

10.1029/2022JD037758

**Key Points:**

* This work is an overview of the NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field experiment

* FIREX-AQ investigated biomass burning emissions and chemistry and smoke transport

* FIREX-AQ was a multi-platform mission that also utilized fire modeling and satellite detections and validation

**Supporting Information:**

Supporting Information may be found in the online version of this article.

**Correspondence to:**

C. Warneke,
carsten.warneke@noaa.gov

**Citation:**

Warneke, C., Schwarz, J. P., Dibb, J., Kalashnikova, O., Frost, G., Al-Saad, J., et al. (2023). Fire influence on regional to global environments and air quality (FIREX-AQ). *Journal of Geophysical Research: Atmospheres*, 128, e2022JD037758. https://doi.org/10.1029/2022JD037758

Received 29 AUG 2022

Accepted 2 DEC 2022

<figure><img src="image_3.png" /></figure>

## Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ)

Carsten Warneke¹ ID, Joshua P. Schwarz¹ ID, Jack Dibb² ID, Olga Kalashnikova³ ID, Gregory Frost¹ ID, Jassim Al-Saad⁴, Steven S. Brown¹ ID, Wm. Alan Brewer¹, Amber Soja⁴,⁵ ID, Felix C. Seidel³,⁶, Rebecca A. Washenfelder¹ ID, Elizabeth B. Wiggins⁴ ID, Richard H. Moore⁴ ID, Bruce E. Anderson⁴, Carolyn Jordan⁴,⁵ ID, Tara I. Yacovitch⁷ ID, Scott C. Herndon⁷ ID, Shang Liu⁸, Toshihiro Kuwayama⁸, Daniel Jaffe⁹ ID, Nancy Johnston¹⁰ ID, Vanessa Selimovic¹¹ ID, Robert Yokelson¹¹ ID, David M. Giles¹²,¹³ ID, Brent N. Holben¹², Philippe Goloub¹⁴, Ioana Popovici¹⁴,¹⁵, Michael Trainer¹,¹⁶ ID, Aditya Kumar¹⁷, R. Bradley Pierce¹⁷, David Fahey¹ ID, James Roberts¹ ID, Emily M. Gargulinski⁵ ID, David A. Peterson¹⁸, Xinxin Ye¹⁹ ID, Laura H. Thapa¹⁹ ID, Pablo E. Saide¹⁹,²⁰, Charles H. Fite²¹ ID, Christopher D. Holmes²¹ ID, Siyuan Wang¹,¹⁶ ID, Matthew M. Coggon¹,¹⁶ ID, Zachary C. J. Decker¹,¹⁶,²²,²³ ID, Chelsea E. Stockwell¹,¹⁶ ID, Lu Xu¹,¹⁶, Georgios Gkatzelis¹,¹⁶,²⁴, Kenneth Aikin¹,¹⁶ ID, Barry Lefer⁶ ID, Jackson Kaspari²⁵ ID, Debora Griffin²⁶ ID, Linghan Zeng²⁷ ID, Rodney Weber²⁷ ID, Meredith Hastings²⁸ ID, Jiajue Chai²⁸, Glenn M. Wolfe¹² ID, Thomas F. Hanisco¹² ID, Jin Liao¹²,²⁹, Pedro Campuzano Jost¹⁶ ID, Hongyu Guo¹⁶, Jose L. Jimenez¹⁶ ID, James Crawford⁴ ID, and The FIREX-AQ Science Team³⁰

¹Chemical Sciences Laboratory, National Oceanic and Atmospheric Administration NOAA, Boulder, CO, USA, ²Earth Systems Research Center, University of New Hampshire, Durham, NH, USA, ³NASA, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA, ⁴NASA Langley Research Center, Hampton, VA, USA, ⁵National Institute of Aerospace, Hampton, VA, USA, ⁶Earth Sciences Division, NASA Headquarters, Washington, DC, USA, ⁷Aerodyne Research Inc., Billerica, MA, USA, ⁸Research Division, California Air Resource Board, Sacramento, CA, USA, ⁹Physical Sciences Division, University of Washington, Seattle, WA, USA, ¹⁰Lewis-Clark State College, Lewiston, ID, USA, ¹¹Department of Chemistry and Biochemistry, University of Montana, Missoula, MT, USA, ¹²NASA Goddard Space Flight Center, Greenbelt, MD, USA, ¹³Science Systems and Applications, Inc. (SSAI), Lanham, MD, USA, ¹⁴Laboratoire d'Optique Atmosphérique, Lille University, Villeneuve d'Ascq Cedex, France, ¹⁵Research & Development Department, Cimel Electronique, Paris, France, ¹⁶Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA, ¹⁷Space Science and Engineering Center, Madison, WI, USA, ¹⁸Naval Research Laboratory, Monterey, CA, USA, ¹⁹Department of Atmospheric and Oceanic Sciences, University of California Los Angeles, Los Angeles, CA, USA, ²⁰Institute of the Environment and Sustainability, University of California Los Angeles, Los Angeles, CA, USA, ²¹Earth, Ocean, and Atmospheric Science, Florida State University, Tallahassee, FL, USA, ²²Now at Paul Scherrer Institute (PSI), Villigen, Switzerland, ²³Department of Chemistry, University of Colorado Boulder, Boulder, CO, USA, ²⁴Now at: Forschungszentrum Jülich, IEK 8: Troposphäre, Jülich, Germany, ²⁵Department of Chemistry, University of New Hampshire, Durham, NH, USA, ²⁶Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON, Canada, ²⁷School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA, ²⁸Department of Earth, Environment and Planetary Science, Brown University, Providence, RI, USA, ²⁹Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, College Park, MD, USA, ³⁰See Appendix A

**Abstract** The NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) experiment was a multi-agency, inter-disciplinary research effort to: (a) obtain detailed measurements of trace gas and aerosol emissions from wildfires and prescribed fires using aircraft, satellites and ground-based instruments, (b) make extensive suborbital remote sensing measurements of fire dynamics, (c) assess local, regional, and global modeling of fires, and (d) strengthen connections to observables on the ground such as fuels and fuel consumption and satellite products such as burned area and fire radiative power. From Boise, ID western wildfires were studied with the NASA DC-8 and two NOAA Twin Otter aircraft. The high-altitude NASA ER-2 was deployed from Palmdale, CA to observe some of these fires in conjunction with satellite overpasses and the other aircraft. Further research was conducted on three mobile laboratories and ground sites, and 17 different modeling forecast and analyses products for fire, fuels and air quality and climate implications. From Salina, KS the DC-8 investigated 87 smaller fires in the Southeast with remote and in-situ data collection. Sampling by all platforms was designed to measure emissions of trace gases and aerosols with multiple transects to capture the chemical transformation of these emissions and perform remote sensing observations of fire and smoke plumes under day and night conditions. The emissions were linked to fuels

© 2022 The Authors. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
# JGR Atmospheres

## RESEARCH ARTICLE

10.1029/2022JD037758

**Key Points:**

* This work is an overview of the NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field experiment

* FIREX-AQ investigated biomass burning emissions and chemistry and smoke transport

* FIREX-AQ was a multi-platform mission that also utilized fire modeling and satellite detections and validation

**Supporting Information:**

Supporting Information may be found in the online version of this article.

**Correspondence to:**

C. Warneke,
carsten.warneke@noaa.gov

**Citation:**

Warneke, C., Schwarz, J. P., Dibb, J., Kalashnikova, O., Frost, G., Al-Saad, J., et al. (2023). Fire influence on regional to global environments and air quality (FIREX-AQ). *Journal of Geophysical Research: Atmospheres*, 128, e2022JD037758. https://doi.org/10.1029/2022JD037758

Received 29 AUG 2022

Accepted 2 DEC 2022

<figure><img src="image_3.png" /></figure>

## Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ)

Carsten Warneke¹ ID, Joshua P. Schwarz¹ ID, Jack Dibb² ID, Olga Kalashnikova³ ID, Gregory Frost¹ ID, Jassim Al-Saad⁴, Steven S. Brown¹ ID, Wm. Alan Brewer¹, Amber Soja⁴,⁵ ID, Felix C. Seidel³,⁶, Rebecca A. Washenfelder¹ ID, Elizabeth B. Wiggins⁴ ID, Richard H. Moore⁴ ID, Bruce E. Anderson⁴, Carolyn Jordan⁴,⁵ ID, Tara I. Yacovitch⁷ ID, Scott C. Herndon⁷ ID, Shang Liu⁸, Toshihiro Kuwayama⁸, Daniel Jaffe⁹ ID, Nancy Johnston¹⁰ ID, Vanessa Selimovic¹¹ ID, Robert Yokelson¹¹ ID, David M. Giles¹²,¹³ ID, Brent N. Holben¹², Philippe Goloub¹⁴, Ioana Popovici¹⁴,¹⁵, Michael Trainer¹,¹⁶ ID, Aditya Kumar¹⁷, R. Bradley Pierce¹⁷, David Fahey¹ ID, James Roberts¹ ID, Emily M. Gargulinski⁵ ID, David A. Peterson¹⁸, Xinxin Ye¹⁹ ID, Laura H. Thapa¹⁹ ID, Pablo E. Saide¹⁹,²⁰, Charles H. Fite²¹ ID, Christopher D. Holmes²¹ ID, Siyuan Wang¹,¹⁶ ID, Matthew M. Coggon¹,¹⁶ ID, Zachary C. J. Decker¹,¹⁶,²²,²³ ID, Chelsea E. Stockwell¹,¹⁶ ID, Lu Xu¹,¹⁶, Georgios Gkatzelis¹,¹⁶,²⁴, Kenneth Aikin¹,¹⁶ ID, Barry Lefer⁶ ID, Jackson Kaspari²⁵ ID, Debora Griffin²⁶ ID, Linghan Zeng²⁷ ID, Rodney Weber²⁷ ID, Meredith Hastings²⁸ ID, Jiajue Chai²⁸, Glenn M. Wolfe¹² ID, Thomas F. Hanisco¹² ID, Jin Liao¹²,²⁹, Pedro Campuzano Jost¹⁶ ID, Hongyu Guo¹⁶, Jose L. Jimenez¹⁶ ID, James Crawford⁴ ID, and The FIREX-AQ Science Team³⁰

¹Chemical Sciences Laboratory, National Oceanic and Atmospheric Administration NOAA, Boulder, CO, USA, ²Earth Systems Research Center, University of New Hampshire, Durham, NH, USA, ³NASA, Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA, ⁴NASA Langley Research Center, Hampton, VA, USA, ⁵National Institute of Aerospace, Hampton, VA, USA, ⁶Earth Sciences Division, NASA Headquarters, Washington, DC, USA, ⁷Aerodyne Research Inc., Billerica, MA, USA, ⁸Research Division, California Air Resource Board, Sacramento, CA, USA, ⁹Physical Sciences Division, University of Washington, Seattle, WA, USA, ¹⁰Lewis-Clark State College, Lewiston, ID, USA, ¹¹Department of Chemistry and Biochemistry, University of Montana, Missoula, MT, USA, ¹²NASA Goddard Space Flight Center, Greenbelt, MD, USA, ¹³Science Systems and Applications, Inc. (SSAI), Lanham, MD, USA, ¹⁴Laboratoire d'Optique Atmosphérique, Lille University, Villeneuve d'Ascq Cedex, France, ¹⁵Research & Development Department, Cimel Electronique, Paris, France, ¹⁶Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA, ¹⁷Space Science and Engineering Center, Madison, WI, USA, ¹⁸Naval Research Laboratory, Monterey, CA, USA, ¹⁹Department of Atmospheric and Oceanic Sciences, University of California Los Angeles, Los Angeles, CA, USA, ²⁰Institute of the Environment and Sustainability, University of California Los Angeles, Los Angeles, CA, USA, ²¹Earth, Ocean, and Atmospheric Science, Florida State University, Tallahassee, FL, USA, ²²Now at Paul Scherrer Institute (PSI), Villigen, Switzerland, ²³Department of Chemistry, University of Colorado Boulder, Boulder, CO, USA, ²⁴Now at: Forschungszentrum Jülich, IEK 8: Troposphäre, Jülich, Germany, ²⁵Department of Chemistry, University of New Hampshire, Durham, NH, USA, ²⁶Air Quality Research Division, Environment and Climate Change Canada, Toronto, ON, Canada, ²⁷School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA, USA, ²⁸Department of Earth, Environment and Planetary Science, Brown University, Providence, RI, USA, ²⁹Goddard Earth Sciences Technology and Research (GESTAR) II, University of Maryland, College Park, MD, USA, ³⁰See Appendix A

**Abstract** The NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) experiment was a multi-agency, inter-disciplinary research effort to: (a) obtain detailed measurements of trace gas and aerosol emissions from wildfires and prescribed fires using aircraft, satellites and ground-based instruments, (b) make extensive suborbital remote sensing measurements of fire dynamics, (c) assess local, regional, and global modeling of fires, and (d) strengthen connections to observables on the ground such as fuels and fuel consumption and satellite products such as burned area and fire radiative power. From Boise, ID western wildfires were studied with the NASA DC-8 and two NOAA Twin Otter aircraft. The high-altitude NASA ER-2 was deployed from Palmdale, CA to observe some of these fires in conjunction with satellite overpasses and the other aircraft. Further research was conducted on three mobile laboratories and ground sites, and 17 different modeling forecast and analyses products for fire, fuels and air quality and climate implications. From Salina, KS the DC-8 investigated 87 smaller fires in the Southeast with remote and in-situ data collection. Sampling by all platforms was designed to measure emissions of trace gases and aerosols with multiple transects to capture the chemical transformation of these emissions and perform remote sensing observations of fire and smoke plumes under day and night conditions. The emissions were linked to fuels

© 2022 The Authors. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
consumed and fire radiative power using orbital and suborbital remote sensing observations collected during overflights of the fires and smoke plumes and ground sampling of fuels.

**Plain Language Summary** The NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) experiment was aimed at understanding how fuel and fire conditions at the point of emission influence the chemistry of smoke, what conditions and processes control the rise of smoke plumes, what happens to smoke as it is distributed in the atmosphere, and how chemical transformation of smoke impacts air quality, weather, and climate downwind. Lessons learned from FIREX-AQ will also be used to assess and improve the effectiveness of satellites for estimating the emissions from wildfires and prescribed burns and to reduce uncertainties associated with modeling and forecasting of smoke. Here we present an overview of the FIREX-AQ effort, its motivation and design, with detailed descriptions of the measurements and analyses carried out, their connections to FIREX-AQ science goals, and the early findings of this exceptionally broad effort to understand fire and its many impacts on the atmosphere.

# 1. Rationale and Motivation

The combination of a warmer, drier climate with fire-control practices applied over the last century has led to more intense fires, larger burned areas, and longer fire seasons in the U.S., Canada, and around the world. The 20th century saw fire suppression become the standard response to wildfires, especially in the western U.S. and southwest Canada; this has led to a buildup of fuels in forested areas, a breakdown in the natural ecology of forests. In addition, risks to life and property associated with the expansion of the Wildland Urban Interface (WUI) have increased (Radeloff et al., 2018). Climate change causes increased temperatures, drought, higher fuel aridity and tree death further increasing the fire intensity (Abatzoglou, Battisti, et al., 2021; Kitzberger et al., 2007; Westerling, 2016). Prescribed fires and allowing some naturally occurring fires to burn are some of the management practices that address the above problem (Mutch, 1994; Schoennagel et al., 2017).

Fire is important for many ecosystems (Mutch, 1994), but it also poses costly risks to human health and property. These risks have increased in recent decades due in part to population growth in the WUI (Westerling et al., 2006). Extreme fire seasons attract mounting attention due to the increasing number of costly extreme wildfires that include: the 2018 Camp Fire, which was the deadliest and most destructive wildfire in California's history and burned 62,053 ha and cost 16.65 billion dollars. The 2016 fires that burned across eight states in the southeast (48,158 ha); the 2016 Anderson Creek prairie fire that was the largest in Kansas history (161,874 ha); the 2016 Fort McMurray fire, which is the costliest fire in Canadian history ($2.7 B, 589,552 ha, 2400 structures destroyed); the 2004 Alaskan fire season (2.74 M ha), the largest in almost 80 years of Alaskan fire history and the extreme 2015 unusually-early-season Alaskan fires (2.07 M ha) (Abatzoglou, Rupp, et al., 2021; Wentworth et al., 2018) and the extreme fires in North America in 2020 and 2021 (https://www.nifc.gov/fire-information/statistics). Coupled with the direct threats to life and property, wildland fires have demonstrable detrimental air quality related health impacts including aggravated asthma, chronic bronchitis, decreased lung function, congestive heart failure, and premature death (Adetona et al., 2016; Doubleday et al., 2020; Rappold et al., 2011; Reid et al., 2016; Thelen et al., 2013).

Prescribed fires in the United States have ranged from 3.3 to 4.8 million ha (M ha) annually over the last decade, well above the typical wildfire area (Melvin, 2020). The majority of this area (80%) is in forests and rangeland (wildland) and agricultural use makes up about 20% of prescribed fire area (Melvin, 2018). Prescribed fires can reduce the risk of dangerous wildfires and usually have low direct risk to people and property, but they still generate smoke and air quality impacts (Addington et al., 2015; Fernandes & Botelho, 2003; Nowell et al., 2018; Stephens et al., 2012).

Fire impacts occur over wide time and distance scales, from local to global (Ansmann et al., 2018; Schill et al., 2020), via complex, interdependent, and poorly understood processes. For example, primary fire emissions are affected by a wide variety of factors including fuel conditions (type, structure, quantity, and moisture content), fire intensity, and fire weather (cumulative temperature, relative humidity (RH), wind speed, and precipitation), which in turn can be rapidly and heterogeneously modified by fires as they burn. Wildfire initiation can be natural (by lightning) or human caused, and prescribed fires are a frequent tool for land management (e.g., reducing fuels, land clearing and agriculture). Human ignition is currently the dominant ignition source in the United States (Balch et al., 2017). Over the life cycle of a fire, combinations of flaming and smoldering combustion
consumed and fire radiative power using orbital and suborbital remote sensing observations collected during overflights of the fires and smoke plumes and ground sampling of fuels.

**Plain Language Summary** The NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) experiment was aimed at understanding how fuel and fire conditions at the point of emission influence the chemistry of smoke, what conditions and processes control the rise of smoke plumes, what happens to smoke as it is distributed in the atmosphere, and how chemical transformation of smoke impacts air quality, weather, and climate downwind. Lessons learned from FIREX-AQ will also be used to assess and improve the effectiveness of satellites for estimating the emissions from wildfires and prescribed burns and to reduce uncertainties associated with modeling and forecasting of smoke. Here we present an overview of the FIREX-AQ effort, its motivation and design, with detailed descriptions of the measurements and analyses carried out, their connections to FIREX-AQ science goals, and the early findings of this exceptionally broad effort to understand fire and its many impacts on the atmosphere.

# 1. Rationale and Motivation

The combination of a warmer, drier climate with fire-control practices applied over the last century has led to more intense fires, larger burned areas, and longer fire seasons in the U.S., Canada, and around the world. The 20th century saw fire suppression become the standard response to wildfires, especially in the western U.S. and southwest Canada; this has led to a buildup of fuels in forested areas, a breakdown in the natural ecology of forests. In addition, risks to life and property associated with the expansion of the Wildland Urban Interface (WUI) have increased (Radeloff et al., 2018). Climate change causes increased temperatures, drought, higher fuel aridity and tree death further increasing the fire intensity (Abatzoglou, Battisti, et al., 2021; Kitzberger et al., 2007; Westerling, 2016). Prescribed fires and allowing some naturally occurring fires to burn are some of the management practices that address the above problem (Mutch, 1994; Schoennagel et al., 2017).

Fire is important for many ecosystems (Mutch, 1994), but it also poses costly risks to human health and property. These risks have increased in recent decades due in part to population growth in the WUI (Westerling et al., 2006). Extreme fire seasons attract mounting attention due to the increasing number of costly extreme wildfires that include: the 2018 Camp Fire, which was the deadliest and most destructive wildfire in California's history and burned 62,053 ha and cost 16.65 billion dollars. The 2016 fires that burned across eight states in the southeast (48,158 ha); the 2016 Anderson Creek prairie fire that was the largest in Kansas history (161,874 ha); the 2016 Fort McMurray fire, which is the costliest fire in Canadian history ($2.7 B, 589,552 ha, 2400 structures destroyed); the 2004 Alaskan fire season (2.74 M ha), the largest in almost 80 years of Alaskan fire history and the extreme 2015 unusually-early-season Alaskan fires (2.07 M ha) (Abatzoglou, Rupp, et al., 2021; Wentworth et al., 2018) and the extreme fires in North America in 2020 and 2021 (https://www.nifc.gov/fire-information/statistics). Coupled with the direct threats to life and property, wildland fires have demonstrable detrimental air quality related health impacts including aggravated asthma, chronic bronchitis, decreased lung function, congestive heart failure, and premature death (Adetona et al., 2016; Doubleday et al., 2020; Rappold et al., 2011; Reid et al., 2016; Thelen et al., 2013).

Prescribed fires in the United States have ranged from 3.3 to 4.8 million ha (M ha) annually over the last decade, well above the typical wildfire area (Melvin, 2020). The majority of this area (80%) is in forests and rangeland (wildland) and agricultural use makes up about 20% of prescribed fire area (Melvin, 2018). Prescribed fires can reduce the risk of dangerous wildfires and usually have low direct risk to people and property, but they still generate smoke and air quality impacts (Addington et al., 2015; Fernandes & Botelho, 2003; Nowell et al., 2018; Stephens et al., 2012).

Fire impacts occur over wide time and distance scales, from local to global (Ansmann et al., 2018; Schill et al., 2020), via complex, interdependent, and poorly understood processes. For example, primary fire emissions are affected by a wide variety of factors including fuel conditions (type, structure, quantity, and moisture content), fire intensity, and fire weather (cumulative temperature, relative humidity (RH), wind speed, and precipitation), which in turn can be rapidly and heterogeneously modified by fires as they burn. Wildfire initiation can be natural (by lightning) or human caused, and prescribed fires are a frequent tool for land management (e.g., reducing fuels, land clearing and agriculture). Human ignition is currently the dominant ignition source in the United States (Balch et al., 2017). Over the life cycle of a fire, combinations of flaming and smoldering combustion
lead to different emissions at different times and at different locations within a fire (Bertschi et al., 2003; Saide et al., 2015; Yates et al., 2016). These variables also influence plume rise and the subsequent transport and chemical evolution of fire emissions (Herron-Thorpe et al., 2014), which determines secondary products (e.g., evolved gases and aerosol species) (Akagi et al., 2012). Fire growth is driven by weather conditions, and forecasts are subject to the limitations of weather-based prediction (Potter, 2020). Fire activity varies on a broad seasonal scale, but climatology is inadequate to provide the detailed information needed to understand and predict fire impacts. This is especially true for impacts related to air quality, which depend on the intersection of fire emissions with populations and are sensitive to chemical transformations that can result when emissions from fires and anthropogenic sources combine (Selimovic et al., 2020).

The importance of biomass burning (BB) on a global scale is well-known (Akagi et al., 2011; Bond et al., 2004, 2013; Crutzen & Andreae, 1990; Crutzen et al., 1979; Schill et al., 2020). Previous BB studies have focused on: the tropics, documenting both the near field environment (Andreae et al., 1994; Kaufman et al., 1998; Swap et al., 2002; Ward et al., 1992; Yokelson et al., 2011) and the widespread impacts across remote oceanic regions (Fishman et al., 1996; Hoell et al., 1999), boreal/Arctic regions (Goode et al., 2000; Jacob et al., 2010; Lefer et al., 1994; Nance et al., 1993; Palmer et al., 2013; Soja et al., 2004) where the relative importance of BB to fossil fuel and other air pollution sources is great, and temperate BB field measurements, which can also target prescribed fires (Akagi et al., 2013; Baker et al., 2018; Burling et al., 2011; May et al., 2014; Yokelson et al., 1999, 2013).

The ubiquity of fire emissions is also evident from previous airborne field studies in North America that were not focused solely on BB but sampled smoke frequently. Following are examples from some of the more recent missions that observed BB atmospheric impacts. The international ICARTT study 2004 (International Consortium for Atmospheric Research on Transport and Transformation) found a strong BB influence from Canadian and Alaskan fires in the northeast U.S. (Clarke et al., 2007; Warneke et al., 2006), and NOAA's TEXAQS 2006 (Texas Air Quality Study) identified systematic differences in particle morphology between urban and BB sources (Schwarz et al., 2008). The international POLARCAT study 2008 (Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols, and Transport) focused on Arctic measurements, where arctic haze over Alaska was attributed to spring fires burning in Asia (Warneke et al., 2009, 2010). While sampling local Canadian fire emissions during the summer was intentional, sampling fires in California in the spring during ARCTAS-CARB 2008 (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) was unexpected (Sahu et al., 2012), but these campaigns provided a broad cross section of fire emissions and impacts (Hecobian et al., 2011; Singh et al., 2012). Canadian fire emissions and their downwind impacts were the focus of the BORTAS (quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites) (Palmer et al., 2013) campaigns in 2011. NOAA's SENEX 2013 (Southeast Nexus) acquired data on the relative contribution of BB to organic aerosols and gases in the southeast U.S. in summertime and provided the first airborne measurements of nighttime smoke (Zarzana et al., 2017), while the NASA/NSF DC3 (2012) campaign fortuitously encountered a smoke plume interacting with a deep convective cloud (Apel et al., 2015) and evidence for the broad influence of convection on the ventilation of fire emissions (Huntrieser et al., 2016). Most recently, the NASA Atmospheric Tomography (ATom) project revisited the widespread BB products that are transported across the remote ocean atmosphere (Bourgeois et al., 2021; Schill et al., 2020).

Large scale atmospheric campaigns in temperate regions began specifying wildfires as targets during NASA's ARCTAS 2008 and SEAC⁴RS 2013 (Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys) (Toon et al., 2016). The latter included detailed evaluation of the plume from the Rim Fire, which was one of the largest known wildfires in California at the time (Forrister et al., 2015; Peterson et al., 2015; Saide et al., 2015; Yates et al., 2016; Yu et al., 2016). SEAC⁴RS also measured emissions and smoke evolution from 15 small agricultural fires in the Mississippi River Valley (MRV) (Liu et al., 2016).

The DOE BBOP 2013 (Department of Energy BB Observation Project) mission was the first airborne campaign to focus primarily on western US wildfires and detailed smoke optical properties. BBOP identified evidence for evolving brown carbon (BrC) materials in fire plumes (Kleinman et al., 2020; Sedlacek et al., 2018; Zhou et al., 2017). By combining all the wildfire data from BBOP and SEAC⁴RS, Liu et al. (2017) calculated wildfire emission factors (EFs) for about 80 species based on three fires. Parallel to the above field measurements, the University of Montana and others led laboratory studies including FLAME-3 and 4 that produced numerous
lead to different emissions at different times and at different locations within a fire (Bertschi et al., 2003; Saide et al., 2015; Yates et al., 2016). These variables also influence plume rise and the subsequent transport and chemical evolution of fire emissions (Herron-Thorpe et al., 2014), which determines secondary products (e.g., evolved gases and aerosol species) (Akagi et al., 2012). Fire growth is driven by weather conditions, and forecasts are subject to the limitations of weather-based prediction (Potter, 2020). Fire activity varies on a broad seasonal scale, but climatology is inadequate to provide the detailed information needed to understand and predict fire impacts. This is especially true for impacts related to air quality, which depend on the intersection of fire emissions with populations and are sensitive to chemical transformations that can result when emissions from fires and anthropogenic sources combine (Selimovic et al., 2020).

The importance of biomass burning (BB) on a global scale is well-known (Akagi et al., 2011; Bond et al., 2004, 2013; Crutzen & Andreae, 1990; Crutzen et al., 1979; Schill et al., 2020). Previous BB studies have focused on: the tropics, documenting both the near field environment (Andreae et al., 1994; Kaufman et al., 1998; Swap et al., 2002; Ward et al., 1992; Yokelson et al., 2011) and the widespread impacts across remote oceanic regions (Fishman et al., 1996; Hoell et al., 1999), boreal/Arctic regions (Goode et al., 2000; Jacob et al., 2010; Lefer et al., 1994; Nance et al., 1993; Palmer et al., 2013; Soja et al., 2004) where the relative importance of BB to fossil fuel and other air pollution sources is great, and temperate BB field measurements, which can also target prescribed fires (Akagi et al., 2013; Baker et al., 2018; Burling et al., 2011; May et al., 2014; Yokelson et al., 1999, 2013).

The ubiquity of fire emissions is also evident from previous airborne field studies in North America that were not focused solely on BB but sampled smoke frequently. Following are examples from some of the more recent missions that observed BB atmospheric impacts. The international ICARTT study 2004 (International Consortium for Atmospheric Research on Transport and Transformation) found a strong BB influence from Canadian and Alaskan fires in the northeast U.S. (Clarke et al., 2007; Warneke et al., 2006), and NOAA's TEXAQS 2006 (Texas Air Quality Study) identified systematic differences in particle morphology between urban and BB sources (Schwarz et al., 2008). The international POLARCAT study 2008 (Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols, and Transport) focused on Arctic measurements, where arctic haze over Alaska was attributed to spring fires burning in Asia (Warneke et al., 2009, 2010). While sampling local Canadian fire emissions during the summer was intentional, sampling fires in California in the spring during ARCTAS-CARB 2008 (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) was unexpected (Sahu et al., 2012), but these campaigns provided a broad cross section of fire emissions and impacts (Hecobian et al., 2011; Singh et al., 2012). Canadian fire emissions and their downwind impacts were the focus of the BORTAS (quantifying the impact of BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites) (Palmer et al., 2013) campaigns in 2011. NOAA's SENEX 2013 (Southeast Nexus) acquired data on the relative contribution of BB to organic aerosols and gases in the southeast U.S. in summertime and provided the first airborne measurements of nighttime smoke (Zarzana et al., 2017), while the NASA/NSF DC3 (2012) campaign fortuitously encountered a smoke plume interacting with a deep convective cloud (Apel et al., 2015) and evidence for the broad influence of convection on the ventilation of fire emissions (Huntrieser et al., 2016). Most recently, the NASA Atmospheric Tomography (ATom) project revisited the widespread BB products that are transported across the remote ocean atmosphere (Bourgeois et al., 2021; Schill et al., 2020).

Large scale atmospheric campaigns in temperate regions began specifying wildfires as targets during NASA's ARCTAS 2008 and SEAC⁴RS 2013 (Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys) (Toon et al., 2016). The latter included detailed evaluation of the plume from the Rim Fire, which was one of the largest known wildfires in California at the time (Forrister et al., 2015; Peterson et al., 2015; Saide et al., 2015; Yates et al., 2016; Yu et al., 2016). SEAC⁴RS also measured emissions and smoke evolution from 15 small agricultural fires in the Mississippi River Valley (MRV) (Liu et al., 2016).

The DOE BBOP 2013 (Department of Energy BB Observation Project) mission was the first airborne campaign to focus primarily on western US wildfires and detailed smoke optical properties. BBOP identified evidence for evolving brown carbon (BrC) materials in fire plumes (Kleinman et al., 2020; Sedlacek et al., 2018; Zhou et al., 2017). By combining all the wildfire data from BBOP and SEAC⁴RS, Liu et al. (2017) calculated wildfire emission factors (EFs) for about 80 species based on three fires. Parallel to the above field measurements, the University of Montana and others led laboratory studies including FLAME-3 and 4 that produced numerous
fuel-specific EFs and smoke aging simulations for laboratory fires (Ahern et al., 2019; Hatch et al., 2015, 2017; May et al., 2013; McMeeking et al., 2009; Stockwell et al., 2014, 2015).

The Western wildfire Experiment for Cloud chemistry, Aerosol absorption and Nitrogen 2018 (WE-CAN 2018) (https://www.eol.ucar.edu/fieldProjects/we-can) was originally planned to coincide with the NASA/NOAA 2019 field campaign as a complement to FIREX-AQ, but aircraft schedules could not be aligned. WE-CAN systematically characterized the emissions and early evolution of western U.S. wildfire plumes and focused on three sets of scientific questions related to fixed nitrogen, absorbing aerosols, cloud activation, and chemistry in wildfire plumes (Lindaas et al., 2021; Palm et al., 2020; Permar et al., 2021). The data were collected from the NCAR/NSF C-130 research aircraft stationed in Boise, ID in the summer of 2018. The main focus was on the first day of processing, which is a major driver of the eventual air quality and climate significance of wildfire smoke, because the chemistry and micro-physics occurring during this time determine the partitioning of reactive nitrogen, alters cloud chemistry and nucleation, and determines aerosol scattering and absorption (Hodshire et al., 2019). Several WE-CAN results have been published (https://www.eol.ucar.edu/node/12743/publications).

Due in large part to the variability and complexity of wildfires and agricultural burning, and due to their evolving emission trends, there remains a need to enhance the understanding of emissions, smoke evolution, and AQ impacts across a greater range of conditions, while taking advantage of the most recent advances in atmospheric chemistry instrumentation. FIREX-AQ was planned to advance these critical research needs to better characterize BB impacts on air quality and climate impacts.

## 1.1. FIREX-AQ Science Objectives

The overarching objective of FIREX-AQ was to provide an unprecedented combination of fire science covering: (a) measurements of trace gas and aerosol emissions for not only wildfires but also prescribed fires in great detail, (b) relate them to fuel and fire conditions at the point of emission, (c) characterize the conditions relating to plume rise, (d) follow plumes downwind to understand chemical transformation and air quality impacts, (e) assess the efficacy of satellite detections for estimating the emissions from sampled fires, (f) connecting remote sensing and in-situ with satellite data, and (g) improve air quality and climate models.

The NOAA FIREX research effort was designed as a five-year research project and later merged into the comprehensive NOAA/NASA FIREX-AQ research effort to target critical unknowns about BB with state-of-the-art technologies and collaborative laboratory and field studies, culminating in the 2019 field campaign that deployed multiple aircraft, mobile laboratories and fixed ground sites coupled with satellite measurements and intensive modeling studies. The diverse activities included in FIREX-AQ 2019 range from scientists collecting fuels on the ground to multiple aircraft measurements of smoke plumes from wildfires and prescribed burning to global 3D fire and health impacts modeling.

Wildfires tend to be seasonal and generally result in large pollution concentrations over wide areas and can cause both local and regional air quality impacts. Their emissions are often transported thousands of kilometers and can impact large regions of the U.S. at a time (Park et al., 2007; Rogers et al., 2020; Selimovic et al., 2019; Warneke et al., 2006). Prescribed fires are usually smaller and less intense than wildfires but are much greater in number and occur throughout the whole year. They may be ignited during periods that minimize population exposure and air quality impacts, but can cause regional backgrounds to increase, are generally in closer proximity to populations, and are responsible for a large fraction of the U.S. PM₂.₅ emissions (Washenfelder et al., 2015). Prescribed burning associated with agricultural fire outputs is still poorly represented in emission inventories (McCarty et al., 2009; Nowell et al., 2018; Pouliot et al., 2017; Ramo et al., 2021). The field experiments in FIREX-AQ investigated both wild and prescribed fires, but did not include residential or trash burning. Subsequent sections discuss the coordination of prescribed and wildfire sampling, including the resulting benefits to stakeholders.

## 1.2. FIREX-AQ Science Questions

A summary of the FIREX-AQ science questions is provided here and the topics include questions about emissions, chemical transformations, local air quality effects, regional and long-term impacts, climate relevant properties, and satellite measurements of wildfires and prescribed fires in North America.
fuel-specific EFs and smoke aging simulations for laboratory fires (Ahern et al., 2019; Hatch et al., 2015, 2017; May et al., 2013; McMeeking et al., 2009; Stockwell et al., 2014, 2015).

The Western wildfire Experiment for Cloud chemistry, Aerosol absorption and Nitrogen 2018 (WE-CAN 2018) (https://www.eol.ucar.edu/fieldProjects/we-can) was originally planned to coincide with the NASA/NOAA 2019 field campaign as a complement to FIREX-AQ, but aircraft schedules could not be aligned. WE-CAN systematically characterized the emissions and early evolution of western U.S. wildfire plumes and focused on three sets of scientific questions related to fixed nitrogen, absorbing aerosols, cloud activation, and chemistry in wildfire plumes (Lindaas et al., 2021; Palm et al., 2020; Permar et al., 2021). The data were collected from the NCAR/NSF C-130 research aircraft stationed in Boise, ID in the summer of 2018. The main focus was on the first day of processing, which is a major driver of the eventual air quality and climate significance of wildfire smoke, because the chemistry and micro-physics occurring during this time determine the partitioning of reactive nitrogen, alters cloud chemistry and nucleation, and determines aerosol scattering and absorption (Hodshire et al., 2019). Several WE-CAN results have been published (https://www.eol.ucar.edu/node/12743/publications).

Due in large part to the variability and complexity of wildfires and agricultural burning, and due to their evolving emission trends, there remains a need to enhance the understanding of emissions, smoke evolution, and AQ impacts across a greater range of conditions, while taking advantage of the most recent advances in atmospheric chemistry instrumentation. FIREX-AQ was planned to advance these critical research needs to better characterize BB impacts on air quality and climate impacts.

## 1.1. FIREX-AQ Science Objectives

The overarching objective of FIREX-AQ was to provide an unprecedented combination of fire science covering: (a) measurements of trace gas and aerosol emissions for not only wildfires but also prescribed fires in great detail, (b) relate them to fuel and fire conditions at the point of emission, (c) characterize the conditions relating to plume rise, (d) follow plumes downwind to understand chemical transformation and air quality impacts, (e) assess the efficacy of satellite detections for estimating the emissions from sampled fires, (f) connecting remote sensing and in-situ with satellite data, and (g) improve air quality and climate models.

The NOAA FIREX research effort was designed as a five-year research project and later merged into the comprehensive NOAA/NASA FIREX-AQ research effort to target critical unknowns about BB with state-of-the-art technologies and collaborative laboratory and field studies, culminating in the 2019 field campaign that deployed multiple aircraft, mobile laboratories and fixed ground sites coupled with satellite measurements and intensive modeling studies. The diverse activities included in FIREX-AQ 2019 range from scientists collecting fuels on the ground to multiple aircraft measurements of smoke plumes from wildfires and prescribed burning to global 3D fire and health impacts modeling.

Wildfires tend to be seasonal and generally result in large pollution concentrations over wide areas and can cause both local and regional air quality impacts. Their emissions are often transported thousands of kilometers and can impact large regions of the U.S. at a time (Park et al., 2007; Rogers et al., 2020; Selimovic et al., 2019; Warneke et al., 2006). Prescribed fires are usually smaller and less intense than wildfires but are much greater in number and occur throughout the whole year. They may be ignited during periods that minimize population exposure and air quality impacts, but can cause regional backgrounds to increase, are generally in closer proximity to populations, and are responsible for a large fraction of the U.S. PM<sub>2.5</sub> emissions (Washenfelder et al., 2015). Prescribed burning associated with agricultural fire outputs is still poorly represented in emission inventories (McCarty et al., 2009; Nowell et al., 2018; Pouliot et al., 2017; Ramo et al., 2021). The field experiments in FIREX-AQ investigated both wild and prescribed fires, but did not include residential or trash burning. Subsequent sections discuss the coordination of prescribed and wildfire sampling, including the resulting benefits to stakeholders.

## 1.2. FIREX-AQ Science Questions

A summary of the FIREX-AQ science questions is provided here and the topics include questions about emissions, chemical transformations, local air quality effects, regional and long-term impacts, climate relevant properties, and satellite measurements of wildfires and prescribed fires in North America.
1. What are the emissions of gases and aerosols from North American fires?

2. What chemical transformations affect those emissions?

3. What are the local air quality impacts of North American fires?

4. What are the regional and long-term impacts of North American fires?

5. What are the climate-relevant properties of BB aerosols?

6. How can satellite measurements help with #1–5?

### 1.3. FIREX FireLab 2016 Campaign

The NOAA FIREX FireLab Experiment was conducted at the USDA Fire Sciences Laboratory in Missoula, Montana in 2016, in preparation for FIREX-AQ. The goal of these experiments was to apply the most technically up-to-date methods to measure emissions, optical properties, and aging of smoke from laboratory fires. The focus was to burn fuels under combustion conditions that are characteristic of the western U.S. and other fuels that are under-sampled by the fire research community. Three main areas of research were conducted: quantifying the emissions of gases and particles, understanding chemical and physical processing of smoke emissions, and measuring optical properties of smoke. A very comprehensive set of EFs for various fire conditions was measured and is available for trace gases and aerosol from fuels typical in the Western and some limited fuels from the Southeastern U.S. The Fire Lab Experiment also provided a better understanding of the mechanisms of trace gas emissions for different fire conditions, such as high and low temperature combustion (Sekimoto et al., 2018). In addition, a large number of photochemical products of smoke aging were determined and used to update chemical mechanisms in various models (Coggon et al., 2019). Several new methods were applied to the measurement of optical properties of smoke particles, and new results were obtained on the relationships between particle chemistry and optical properties. There have been a substantial number of publications from the 2016 FireLab study that describe a variety of research products (Table S1 in Supporting Information S1).

The Missoula FireLab facility has been featured in a number of previous publications (Burling et al., 2010; Christian et al., 2003) so is not described here. A website with substantial detail can be found here (https://csl.noaa.gov/projects/firex/firelab/). The details of the fuels burned, quantities, and elemental compositions can be found in Selimovic et al. (2018). For the most part, the fuels burned during the study were characteristic of western North America, since one main goal of FIREX-AQ was a better understanding of how wildfires impact air quality in this region. The fuels were often burned as realistic mixtures of canopy, litter, and duff material from a particular species, for example, Engelmann Spruce, and some fires were conducted with only one of those classes of materials, for example, duff (the partially decayed material right above the soil surface). It should be recognized that there are limitations inherent in the simulation of fires in the laboratory: fuel moisture is often lower than in the natural setting: the soil boundary and its associated moisture and heat capacity is absent. Nevertheless, laboratory studies have provided essential information with which to begin analyzing and interpreting measurements of actual wildfires.

Considerable progress was made during the FireLab experiment on understanding emissions from North American fuels. This has resulted in more detailed ways to categorize volatile organic compounds (VOC), reactive N, and POC (particulate organic carbon) emissions according to fire regime (Koss et al., 2018; Roberts et al., 2020). In addition, the application of new analytical techniques has led to refinements in the identification of VOC species responsible for oxidant and SOA (secondary organic aerosol) formation, and the absorption properties of primary and secondary organic aerosol particles (BrC). The FireLab study also provided an opportunity to compare multiple measurement methods for gas phase species, and for black carbon (BC) particles in particular. Many of these features of primary wildfire emissions are being examined and refined using the results of the FIREX-AQ measurements.

A number of experiments at the FireLab involved capturing the emissions from the Stack Burns and subjecting them to short-term (hours to a few days) simulated atmospheric processing, either under photochemical (e.g., OH reaction) or nighttime (e.g., NO<sub>3</sub> and O<sub>3</sub> reaction) conditions. These efforts yielded valuable information of which compounds were important in oxidant, SOA, and BrC formation, and what product species could be expected from these processes. Several experiments also encompassed liquid and particle condensed phase photochemical processing to examine the potential of that chemistry to produce and destroy BrC chromophores (Adler et al., 2019; Fleming et al., 2020).
1. What are the emissions of gases and aerosols from North American fires?

2. What chemical transformations affect those emissions?

3. What are the local air quality impacts of North American fires?

4. What are the regional and long-term impacts of North American fires?

5. What are the climate-relevant properties of BB aerosols?

6. How can satellite measurements help with #1–5?

### 1.3. FIREX FireLab 2016 Campaign

The NOAA FIREX FireLab Experiment was conducted at the USDA Fire Sciences Laboratory in Missoula, Montana in 2016, in preparation for FIREX-AQ. The goal of these experiments was to apply the most technically up-to-date methods to measure emissions, optical properties, and aging of smoke from laboratory fires. The focus was to burn fuels under combustion conditions that are characteristic of the western U.S. and other fuels that are under-sampled by the fire research community. Three main areas of research were conducted: quantifying the emissions of gases and particles, understanding chemical and physical processing of smoke emissions, and measuring optical properties of smoke. A very comprehensive set of EFs for various fire conditions was measured and is available for trace gases and aerosol from fuels typical in the Western and some limited fuels from the Southeastern U.S. The Fire Lab Experiment also provided a better understanding of the mechanisms of trace gas emissions for different fire conditions, such as high and low temperature combustion (Sekimoto et al., 2018). In addition, a large number of photochemical products of smoke aging were determined and used to update chemical mechanisms in various models (Coggon et al., 2019). Several new methods were applied to the measurement of optical properties of smoke particles, and new results were obtained on the relationships between particle chemistry and optical properties. There have been a substantial number of publications from the 2016 FireLab study that describe a variety of research products (Table S1 in Supporting Information S1).

The Missoula FireLab facility has been featured in a number of previous publications (Burling et al., 2010; Christian et al., 2003) so is not described here. A website with substantial detail can be found here (https://csl.noaa.gov/projects/firex/firelab/). The details of the fuels burned, quantities, and elemental compositions can be found in Selimovic et al. (2018). For the most part, the fuels burned during the study were characteristic of western North America, since one main goal of FIREX-AQ was a better understanding of how wildfires impact air quality in this region. The fuels were often burned as realistic mixtures of canopy, litter, and duff material from a particular species, for example, Engelmann Spruce, and some fires were conducted with only one of those classes of materials, for example, duff (the partially decayed material right above the soil surface). It should be recognized that there are limitations inherent in the simulation of fires in the laboratory: fuel moisture is often lower than in the natural setting: the soil boundary and its associated moisture and heat capacity is absent. Nevertheless, laboratory studies have provided essential information with which to begin analyzing and interpreting measurements of actual wildfires.

Considerable progress was made during the FireLab experiment on understanding emissions from North American fuels. This has resulted in more detailed ways to categorize volatile organic compounds (VOC), reactive N, and POC (particulate organic carbon) emissions according to fire regime (Koss et al., 2018; Roberts et al., 2020). In addition, the application of new analytical techniques has led to refinements in the identification of VOC species responsible for oxidant and SOA (secondary organic aerosol) formation, and the absorption properties of primary and secondary organic aerosol particles (BrC). The FireLab study also provided an opportunity to compare multiple measurement methods for gas phase species, and for black carbon (BC) particles in particular. Many of these features of primary wildfire emissions are being examined and refined using the results of the FIREX-AQ measurements.

A number of experiments at the FireLab involved capturing the emissions from the Stack Burns and subjecting them to short-term (hours to a few days) simulated atmospheric processing, either under photochemical (e.g., OH reaction) or nighttime (e.g., NO₃ and O₃ reaction) conditions. These efforts yielded valuable information of which compounds were important in oxidant, SOA, and BrC formation, and what product species could be expected from these processes. Several experiments also encompassed liquid and particle condensed phase photochemical processing to examine the potential of that chemistry to produce and destroy BrC chromophores (Adler et al., 2019; Fleming et al., 2020).
<caption>**Table 1**</caption>

List of the Platforms and Their Location and Timing During FIREX-AQ

<table><thead><tr><th>Platform/Site</th><th>Location</th><th>Deployment date</th><th>Number of flights/drives</th></tr></thead><tbody><tr><td><strong>Aircraft</strong></td><td></td><td></td><td></td></tr><tr><td>NASA DC-8</td><td>Boise, ID</td><td>24 July–16 August 2019</td><td>13</td></tr><tr><td></td><td>Salina, KS</td><td>19 August–03 September 2019</td><td>7</td></tr><tr><td>NOAA Chem Twin Otter</td><td>Boise, ID</td><td>03 August–05 September 2019</td><td>33</td></tr><tr><td></td><td>Cedar City, UT</td><td></td><td>6</td></tr><tr><td>NOAA Met Twin Otter</td><td>Boise, ID</td><td>21 July–13 August 2019</td><td>23</td></tr><tr><td>NASA ER-2</td><td>Palmdale, CA</td><td>01–21 August 2019</td><td>12</td></tr><tr><td><strong>Mobile Laboratories</strong></td><td></td><td></td><td></td></tr><tr><td>AML</td><td>McCall, ID</td><td>05–30 August 2019</td><td>12</td></tr><tr><td>MACH-2</td><td>McCall, ID</td><td>21 July–27 August 2019</td><td>8</td></tr><tr><td></td><td>Boise, ID</td><td></td><td></td></tr><tr><td>CARB</td><td>CA</td><td>15–30 August, 1–4 November 2019</td><td>4</td></tr><tr><td>DRAGON-Mobile 1 and 2</td><td>McCall, ID</td><td>29 July–28 August 2019</td><td>11</td></tr><tr><td></td><td>Boise, ID</td><td></td><td></td></tr><tr><td></td><td>Missoula, MT</td><td></td><td></td></tr><tr><td><strong>Ground sites</strong></td><td></td><td></td><td></td></tr><tr><td>DRAGON</td><td>Multiple sites</td><td>23 July–3 September 2019</td><td></td></tr><tr><td>McCall, ID</td><td>44.871 N, 116.115 W</td><td>25–30 June 2019</td><td></td></tr><tr><td>Missoula, MT</td><td>46.86 N, 113.985 W</td><td>2017–2021</td><td></td></tr><tr><td>Lewiston, ID</td><td>46.413 N, 117.027 W</td><td>18 June–08 September 2019</td><td></td></tr><tr><td>Boise, ID</td><td>43.60 N, 116.351 W</td><td>25 June–10 September 2019</td><td></td></tr><tr><td>Mt. Bachelor, WA</td><td>43.979 N, 121.687 W</td><td>05 August–15 September 2019</td><td></td></tr></tbody></table>

The final goal of the FireLab experiment can be broadly categorized as the application of new and improved analytical methods to measure the optical properties of smoke. Much of this work was performed during the Room Burns, as many of these methods needed a consistent smoke source that lasted for a sufficient time (10 min to over an hour). The instrumentation used in this work measured both the light scattering and absorption properties of smoke, as well as BC and BrC properties. Several of the optical experiments have direct application to refining the detection and characterization of smoke plumes by satellites (Manfred et al., 2018).

## 2. Assets Deployed During FIREX-AQ 2019

### 2.1. Platform Summary

The FIREX-AQ campaign was a large-scale coordinated effort in summer 2019. The deployment dates and locations of the various platforms for FIREX-AQ science are listed in Table 1, a schematic of the deployed platforms is shown in Figure 1, and each platform is then discussed in detail. The FIREX-AQ field campaign was conducted in two phases, focusing first on western wildfires and then targeting smaller fires in the south east. All of the platforms and the forecasting team described below deployed to the western region in late July 2019. Boise, ID was the main operations base. When the DC-8 relocated to Salina, KS on 19 August to conduct the small fire sampling, several of the other platforms and ground sites continued to sample smoke from western wildfires until early September. The forecasting team moved to Salina with the DC-8 but continued to provide daily briefings for the team members that remained in the west.
<caption>**Table 1**</caption>

List of the Platforms and Their Location and Timing During FIREX-AQ

<table><thead><tr><th>Platform/Site</th><th>Location</th><th>Deployment date</th><th>Number of flights/drives</th></tr></thead><tbody><tr><td><strong>Aircraft</strong></td><td></td><td></td><td></td></tr><tr><td>NASA DC-8</td><td>Boise, ID</td><td>24 July–16 August 2019</td><td>13</td></tr><tr><td></td><td>Salina, KS</td><td>19 August–03 September 2019</td><td>7</td></tr><tr><td>NOAA Chem Twin Otter</td><td>Boise, ID</td><td>03 August–05 September 2019</td><td>33</td></tr><tr><td></td><td>Cedar City, UT</td><td></td><td>6</td></tr><tr><td>NOAA Met Twin Otter</td><td>Boise, ID</td><td>21 July–13 August 2019</td><td>23</td></tr><tr><td>NASA ER-2</td><td>Palmdale, CA</td><td>01–21 August 2019</td><td>12</td></tr><tr><td><strong>Mobile Laboratories</strong></td><td></td><td></td><td></td></tr><tr><td>AML</td><td>McCall, ID</td><td>05–30 August 2019</td><td>12</td></tr><tr><td>MACH-2</td><td>McCall, ID</td><td>21 July–27 August 2019</td><td>8</td></tr><tr><td></td><td>Boise, ID</td><td></td><td></td></tr><tr><td>CARB</td><td>CA</td><td>15–30 August, 1–4 November 2019</td><td>4</td></tr><tr><td>DRAGON-Mobile 1 and 2</td><td>McCall, ID</td><td>29 July–28 August 2019</td><td>11</td></tr><tr><td></td><td>Boise, ID</td><td></td><td></td></tr><tr><td></td><td>Missoula, MT</td><td></td><td></td></tr><tr><td><strong>Ground sites</strong></td><td></td><td></td><td></td></tr><tr><td>DRAGON</td><td>Multiple sites</td><td>23 July–3 September 2019</td><td></td></tr><tr><td>McCall, ID</td><td>44.871 N, 116.115 W</td><td>25–30 June 2019</td><td></td></tr><tr><td>Missoula, MT</td><td>46.86 N, 113.985 W</td><td>2017–2021</td><td></td></tr><tr><td>Lewiston, ID</td><td>46.413 N, 117.027 W</td><td>18 June–08 September 2019</td><td></td></tr><tr><td>Boise, ID</td><td>43.60 N, 116.351 W</td><td>25 June–10 September 2019</td><td></td></tr><tr><td>Mt. Bachelor, WA</td><td>43.979 N, 121.687 W</td><td>05 August–15 September 2019</td><td></td></tr></tbody></table>

The final goal of the FireLab experiment can be broadly categorized as the application of new and improved analytical methods to measure the optical properties of smoke. Much of this work was performed during the Room Burns, as many of these methods needed a consistent smoke source that lasted for a sufficient time (10 min to over an hour). The instrumentation used in this work measured both the light scattering and absorption properties of smoke, as well as BC and BrC properties. Several of the optical experiments have direct application to refining the detection and characterization of smoke plumes by satellites (Manfred et al., 2018).

## 2. Assets Deployed During FIREX-AQ 2019

### 2.1. Platform Summary

The FIREX-AQ campaign was a large-scale coordinated effort in summer 2019. The deployment dates and locations of the various platforms for FIREX-AQ science are listed in Table 1, a schematic of the deployed platforms is shown in Figure 1, and each platform is then discussed in detail. The FIREX-AQ field campaign was conducted in two phases, focusing first on western wildfires and then targeting smaller fires in the south east. All of the platforms and the forecasting team described below deployed to the western region in late July 2019. Boise, ID was the main operations base. When the DC-8 relocated to Salina, KS on 19 August to conduct the small fire sampling, several of the other platforms and ground sites continued to sample smoke from western wildfires until early September. The forecasting team moved to Salina with the DC-8 but continued to provide daily briefings for the team members that remained in the west.
<figure><img src="image_4.png" /><figcaption>**Figure 1.** The platforms used for the coordinated sampling of the western wildfires during FIREX-AQ.</figcaption></figure>

## 2.2. Fires Investigated

All the western wildfires that were investigated during the FIREX-AQ campaign are listed in Table 2 and locations are shown in Figure 2. Table 2 also includes information of the platforms and dates that each fire was sampled and total burned area and fuels burned.

## 2.3. Aircraft Platforms

### 2.3.1. NASA DC-8

The NASA DC-8 instrument payload for FIREX-AQ 2019 is described in Table 3 and was designed to provide the most detailed characterization of fire plumes from any aircraft platform to date. The DC-8 had a very complete package of gas- and aerosol-phase measurements as well as extensive remote sensing capabilities. Several of the in-situ measurements had a time resolution of up to 10 Hz, which was essential when sampling small fires with plume penetrations shorter than 5 s (Liu et al., 2016). The value of sampling with a sub-second time resolution has been demonstrated by Müller et al. (2016). The NASA DC-8 flights are shown in Figure 3 and the intercepted fires are included in Table 2. The specific flight tracks of the NASA DC-8 for the western wildfires are shown in Figure S1 in Supporting Information S1 color coded with CO.

### 2.3.2. NOAA Chem Twin Otter

The NOAA Chem Twin Otter completed 39 science flights during 3 August 2019–5 September 2019 and sampled 10 regional wildfires near Boise, ID and Cedar City, UT. The payload weight limited the aircraft to flight durations of 2.5–3.0 hr. The aircraft typically completed two or three individual flights per day, for a total daily flight time of 5–9 hr. The NOAA Chem Twin Otter was stationed in Boise, ID and Cedar City, UT, but regularly refueled at small regional airports to access fires throughout Idaho, Oregon, Montana, Nevada, and Utah. The flight duration allowed the NOAA Chem Twin Otter to follow wildfire plumes approximately 200 km downwind, corresponding to plume ages near 10 hr.

The NOAA Chem Twin Otter payload during FIREX-AQ 2019 was selected for detailed measurements of emissions, BrC evolution, and fast chemistry during both day and night. The payload is listed in Table 4. The NOAA Chem Twin Otter flights are shown in Figure 2 and the 10 intercepted fires are included in Table 2. The specific
<figure><img src="image_4.png" /><figcaption>**Figure 1.** The platforms used for the coordinated sampling of the western wildfires during FIREX-AQ.</figcaption></figure>

## 2.2. Fires Investigated

All the western wildfires that were investigated during the FIREX-AQ campaign are listed in Table 2 and locations are shown in Figure 2. Table 2 also includes information of the platforms and dates that each fire was sampled and total burned area and fuels burned.

## 2.3. Aircraft Platforms

### 2.3.1. NASA DC-8

The NASA DC-8 instrument payload for FIREX-AQ 2019 is described in Table 3 and was designed to provide the most detailed characterization of fire plumes from any aircraft platform to date. The DC-8 had a very complete package of gas- and aerosol-phase measurements as well as extensive remote sensing capabilities. Several of the in-situ measurements had a time resolution of up to 10 Hz, which was essential when sampling small fires with plume penetrations shorter than 5 s (Liu et al., 2016). The value of sampling with a sub-second time resolution has been demonstrated by Müller et al. (2016). The NASA DC-8 flights are shown in Figure 3 and the intercepted fires are included in Table 2. The specific flight tracks of the NASA DC-8 for the western wildfires are shown in Figure S1 in Supporting Information S1 color coded with CO.

### 2.3.2. NOAA Chem Twin Otter

The NOAA Chem Twin Otter completed 39 science flights during 3 August 2019–5 September 2019 and sampled 10 regional wildfires near Boise, ID and Cedar City, UT. The payload weight limited the aircraft to flight durations of 2.5–3.0 hr. The aircraft typically completed two or three individual flights per day, for a total daily flight time of 5–9 hr. The NOAA Chem Twin Otter was stationed in Boise, ID and Cedar City, UT, but regularly refueled at small regional airports to access fires throughout Idaho, Oregon, Montana, Nevada, and Utah. The flight duration allowed the NOAA Chem Twin Otter to follow wildfire plumes approximately 200 km downwind, corresponding to plume ages near 10 hr.

The NOAA Chem Twin Otter payload during FIREX-AQ 2019 was selected for detailed measurements of emissions, BrC evolution, and fast chemistry during both day and night. The payload is listed in Table 4. The NOAA Chem Twin Otter flights are shown in Figure 2 and the 10 intercepted fires are included in Table 2. The specific
<table><caption>**Table 2**
List of Western US Fires Investigated During FIREX-AQ</caption><thead><tr><th>Fire name</th><th>State</th><th>Ignition<br>lat</th><th>Ignition<br>lon</th><th>Date</th><th>DC-8</th><th>Chem-<br>otter</th><th>ER-2</th><th>Met-otter</th><th>LARGE</th><th>DRAGON</th><th>AML</th><th>MMP</th><th>Final<br>burned<br>area<br>(acres)</th><th>Fuels (FCCS 2014) 30 m</th></tr></thead><tbody><tr><td rowspan="10">204 Cow</td><td rowspan="10">OR</td><td rowspan="10">44.29</td><td rowspan="10">-118.46</td><td>8/23/19</td><td></td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td>9,602</td><td>Douglas-fir-Pacific ponderosa pine/oceanspray forest</td></tr><tr><td>8/24/19</td><td></td><td>X</td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td></td></tr><tr><td>8/25/19</td><td></td><td>X</td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td></td></tr><tr><td>8/26/19</td><td></td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td></tr><tr><td>8/27/19</td><td></td><td>X</td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td></tr><tr><td>8/28/19</td><td></td><td>X</td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td></tr><tr><td>9/3/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>9/4/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>7/29/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>1,306</td><td>Grand fir-Douglas fir forest</td></tr><tr><td>7/30/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>8/1/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="2">Barren Hills</td><td rowspan="2">ID</td><td rowspan="2">46.24</td><td rowspan="2">-114.98</td><td>7/30/19</td><td></td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td>7/29/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Beeskove</td><td>MT</td><td>46.96</td><td>-113.87</td><td>7/30/19</td><td></td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td>430</td><td>Douglas-fir-Pacific ponderosa pine/oceanspray forest</td></tr><tr><td>Black<br>Diamond</td><td>MT</td><td>46.95</td><td>-112.43</td><td>8/2/19</td><td></td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td>31</td><td>Subalpine fir-lodgepole pine-whitebark pine-Engelmann spruce forest</td></tr><tr><td>Boulin</td><td>AZ</td><td>35.39</td><td>-112.01</td><td>8/15/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td></td><td>4,095</td><td>Ponderosa pine-two-needle pinyon-Utah juniper forest</td></tr><tr><td>Canyon 66</td><td>OR</td><td>44.42</td><td>-120.39</td><td>9/4/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td></td><td>4,451</td><td>Douglas-fir-Pacific ponderosa pine/oceanspray forest</td></tr><tr><td>Castle</td><td>AZ</td><td>36.53</td><td>-112.23</td><td>8/12/19</td><td>X</td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td></td><td>19,378</td><td>Ponderosa pine-two-needle pinyon-Utah juniper forest</td></tr><tr><td rowspan="10">CCC Fire</td><td rowspan="10">ID</td><td rowspan="10">47.57</td><td rowspan="10">-116.32</td><td>8/13/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>8/15/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>8/16/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>8/20/19</td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td>8/21/19</td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td>8/22/19</td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td>8/23/19</td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td>8/8/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>7/29/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>7/30/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>8/2/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>8/5/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Crab</td><td>ID</td><td>46.5</td><td>-114.57</td><td>7/29/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td></td><td>450</td><td>Douglas-fir-Pacific ponderosa pine/oceanspray forest</td></tr><tr><td>Dixon</td><td>CA</td><td>38.57</td><td>-119.74</td><td>8/2/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td></td><td>214</td><td>Subalpine fir-lodgepole pine-whitebark pine-Engelmann spruce forest</td></tr><tr><td>Goose</td><td>NV</td><td>41.87</td><td>-114.2</td><td>8/5/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td></td><td>9</td><td>Red fir forest</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>6,857</td><td>Sagebrush shrubland - post prescribed burn</td></tr></tbody></table>
<table><caption>**Table 2**
List of Western US Fires Investigated During FIREX-AQ</caption><thead><tr><th>Fire name</th><th>State</th><th>Ignition<br>lat</th><th>Ignition<br>lon</th><th>Date</th><th>DC-8</th><th>Chem-<br>otter</th><th>ER-2</th><th>Met-otter</th><th>LARGE</th><th>DRAGON</th><th>AML</th><th>MMP</th><th>Final<br>burned<br>area<br>(acres)</th><th>Fuels (FCCS 2014) 30 m</th></tr></thead><tbody><tr><td rowspan="10">204 Cow</td><td rowspan="10">OR</td><td rowspan="10">44.29</td><td rowspan="10">-118.46</td><td>8/23/19</td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td>9,602</td><td>Douglas-fir-Pacific ponderosa pine/oceanspray forest</td></tr><tr><td>8/24/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td>8/25/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td></tr><tr><td>8/26/19</td><td></td><td></td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td></tr><tr><td>8/27/19</td><td></td><td>X</td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td><td></td></tr><tr><td>8/28/19</td><td></td><td>X</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td>9/3/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>9/4/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>7/29/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>1,306</td><td>Grand fir-Douglas fir forest</td></tr><tr><td>7/30/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>8/1/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="2">Barren Hills</td><td rowspan="2">ID</td><td rowspan="2">46.24</td><td rowspan="2">-114.98</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td rowspan="2">Beeskove</td><td rowspan="2">MT</td><td rowspan="2">46.96</td><td rowspan="2">-113.87</td><td>7/30/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>430</td><td>Douglas-fir-Pacific ponderosa pine/oceanspray forest</td></tr><tr><td>8/2/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Black<br>Diamond</td><td>MT</td><td>46.95</td><td>-112.43</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td>31</td><td>Subalpine fir-lodgepole pine-whitebark pine-Engelmann spruce forest</td></tr><tr><td>Boulin</td><td>AZ</td><td>35.39</td><td>-112.01</td><td>8/15/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td>4,095</td><td>Ponderosa pine-two-needle pinyon-Utah juniper forest</td></tr><tr><td>Canyon 66</td><td>OR</td><td>44.42</td><td>-120.39</td><td>9/4/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td>4,451</td><td>Douglas-fir-Pacific ponderosa pine/oceanspray forest</td></tr><tr><td rowspan="10">Castle</td><td rowspan="10">AZ</td><td rowspan="10">36.53</td><td rowspan="10">-112.23</td><td>8/12/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>19,378</td><td>Ponderosa pine-two-needle pinyon-Utah juniper forest</td></tr><tr><td>8/13/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>8/15/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>8/16/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>8/20/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td></tr><tr><td>8/21/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td></tr><tr><td>8/22/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td></tr><tr><td>8/23/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td>8/23/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td>8/8/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>450</td><td>Douglas-fir-Pacific ponderosa pine/oceanspray forest</td></tr><tr><td>7/29/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>7/30/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>214</td><td>Subalpine fir-lodgepole pine-whitebark pine-Engelmann spruce forest</td></tr><tr><td rowspan="2">Dixon</td><td rowspan="2">CA</td><td rowspan="2">38.57</td><td rowspan="2">-119.74</td><td>8/2/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>9</td><td>Red fir forest</td></tr><tr><td>8/5/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Goose</td><td>NV</td><td>41.87</td><td>-114.2</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>6,857</td><td>Sagebrush shrubland - post prescribed burn</td></tr></tbody></table>
<table><caption>**Table 2**
*Continued*</caption><thead><tr><th>Fire name</th><th>State</th><th>Ignition<br>lat</th><th>Ignition<br>lon</th><th>Date</th><th>DC-8</th><th>Chem-<br>otter</th><th>ER-2</th><th>Met-otter</th><th>LARGE</th><th>DRAGON</th><th>AML</th><th>MMP</th><th>Final<br>burned<br>area<br>(acres)</th><th>Fuels (FCCS 2014) 30 m</th></tr></thead><tbody><tr><td>Granite<br>Gulch</td><td>OR</td><td>45.18</td><td>-117.43</td><td>8/7/19</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td>5,559</td><td>Whitebark pine/subalpine fir forest and Douglas-fir-<br>Pacific ponderosa pine/oceanspray forest</td></tr><tr><td></td><td></td><td></td><td></td><td>8/9/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/16/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/17/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/20/19</td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/21/19</td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td>HK163</td><td>OR</td><td>45.05</td><td>-119.46</td><td>8/9/19</td><td></td><td>X</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td>2,666</td><td>Douglas-fir-Pacific ponderosa pine/oceanspray forest<br>and Ponderosa pine savanna</td></tr><tr><td>Horsefly</td><td>MT</td><td>46.96</td><td>-112.44</td><td>8/6/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>1,352</td><td>Subalpine fir-lodgepole pine-whitebark pine-<br>Engelmann spruce forest</td></tr><tr><td>Ikes</td><td>AZ</td><td>36.35</td><td>-112.29</td><td>8/16/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td>16,424</td><td>Ponderosa pine-two-needle pinyon-Utah juniper forest</td></tr><tr><td></td><td></td><td></td><td></td><td>8/20/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/21/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/22/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td>Left Hand<br>Fire</td><td>WA</td><td>46.93</td><td>-120.99</td><td>7/30/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>3,463</td><td>Grand fir-Douglas-fir forest and ponderosa pine/<br>oceanspray forest</td></tr><tr><td>Lick Creek</td><td>ID</td><td>47.16</td><td>-115.91</td><td>8/2/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>178</td><td>Grand fir-Douglas-fir forest</td></tr><tr><td>Little Bear</td><td>UT</td><td>37.59</td><td>-112.32</td><td>8/20/19</td><td></td><td></td><td>X</td><td>X</td><td>X</td><td>X</td><td></td><td></td><td>2,651</td><td>White fir-gamble oak forest and Ponderosa pine<br>savanna</td></tr><tr><td>UT</td><td></td><td></td><td></td><td>8/21/19</td><td></td><td>X</td><td>X</td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td>Lizzy</td><td>ID</td><td>44.26</td><td>-115.17</td><td>8/3/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>13</td><td>Pasture/Barren</td></tr><tr><td>Mica Creek</td><td>ID</td><td>47.23</td><td>-116.17</td><td>8/2/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>40</td><td>Grand fir-Douglas-fir forest</td></tr><tr><td>Milepost 97</td><td>OR</td><td>42.91</td><td>-123.27</td><td>7/27/19</td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td>13,097</td><td>Douglas-fir-madrone-tanoak forest</td></tr><tr><td>Mill</td><td>CA</td><td>36.01</td><td>-121.47</td><td>8/2/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td>322</td><td>Scrub oak chaparral shrubland and California black<br>oak woodland</td></tr></tbody></table>
<table><caption>**Table 2**
*Continued*</caption><thead><tr><th>Fire name</th><th>State</th><th>Ignition<br>lat</th><th>Ignition<br>lon</th><th>Date</th><th>DC-8</th><th>Chem-<br>otter</th><th>ER-2</th><th>Met-otter</th><th>LARGE</th><th>DRAGON</th><th>AML</th><th>MMP</th><th>Final<br>burned<br>area<br>(acres)</th><th>Fuels (FCCS 2014) 30 m</th></tr></thead><tbody><tr><td>Granite<br>Gulch</td><td>OR</td><td>45.18</td><td>-117.43</td><td>8/7/19</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td>5,559</td><td>Whitebark pine/subalpine fir forest and Douglas-fir-<br>Pacific ponderosa pine/oceanspray forest</td></tr><tr><td></td><td></td><td></td><td></td><td>8/9/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/16/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/17/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/20/19</td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/21/19</td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td>HK163</td><td>OR</td><td>45.05</td><td>-119.46</td><td>8/9/19</td><td></td><td>X</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td>2,666</td><td>Douglas-fir-Pacific ponderosa pine/oceanspray forest<br>and Ponderosa pine savanna</td></tr><tr><td>Horsefly</td><td>MT</td><td>46.96</td><td>-112.44</td><td>8/6/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>1,352</td><td>Subalpine fir-lodgepole pine-whitebark pine-<br>Engelmann spruce forest</td></tr><tr><td>Ikes</td><td>AZ</td><td>36.35</td><td>-112.29</td><td>8/16/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td>16,424</td><td>Ponderosa pine-two-needle pinyon-Utah juniper forest</td></tr><tr><td></td><td></td><td></td><td></td><td>8/20/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/21/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/22/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td>Left Hand<br>Fire</td><td>WA</td><td>46.93</td><td>-120.99</td><td>7/30/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>3,463</td><td>Grand fir-Douglas-fir forest and ponderosa pine/<br>oceanspray forest</td></tr><tr><td>Lick Creek</td><td>ID</td><td>47.16</td><td>-115.91</td><td>8/2/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>178</td><td>Grand fir-Douglas-fir forest</td></tr><tr><td>Little Bear</td><td>UT</td><td>37.59</td><td>-112.32</td><td>8/20/19</td><td></td><td></td><td>X</td><td>X</td><td>X</td><td>X</td><td></td><td></td><td>2,651</td><td>White fir-gamble oak forest and Ponderosa pine<br>savanna</td></tr><tr><td>UT</td><td></td><td></td><td></td><td>8/21/19</td><td></td><td>X</td><td>X</td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td>Lizzy</td><td>ID</td><td>44.26</td><td>-115.17</td><td>8/3/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>13</td><td>Pasture/Barren</td></tr><tr><td>Mica Creek</td><td>ID</td><td>47.23</td><td>-116.17</td><td>8/2/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>40</td><td>Grand fir-Douglas-fir forest</td></tr><tr><td>Milepost 97</td><td>OR</td><td>42.91</td><td>-123.27</td><td>7/27/19</td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td>13,097</td><td>Douglas-fir-madrone-tanoak forest</td></tr><tr><td>Mill</td><td>CA</td><td>36.01</td><td>-121.47</td><td>8/2/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td>322</td><td>Scrub oak chaparral shrubland and California black<br>oak woodland</td></tr></tbody></table>
<table><caption>**Table 2**
*Continued*</caption><thead><tr><th>Fire name</th><th>State</th><th>Ignition<br>lat</th><th>Ignition<br>lon</th><th>Date</th><th>DC-8</th><th>Chem-<br>otter</th><th>ER-2</th><th>Met-otter</th><th>LARGE</th><th>DRAGON</th><th>AML</th><th>MMP</th><th>Final<br>burned<br>area<br>(acres)</th><th>Fuels (FCCS 2014) 30 m</th></tr></thead><tbody><tr><td>Nethiker</td><td>ID</td><td>45.25</td><td>-115.93</td><td>8/9/19</td><td></td><td>X</td><td></td><td>X</td><td>X</td><td></td><td>X</td><td></td><td>2,369</td><td>Douglas-fir-Pacific ponderosa pine/oceanspray forest and Subalpine fir-lodgepole pine-whitebark pine-Engelmann spruce forest</td></tr><tr><td></td><td></td><td></td><td></td><td>8/10/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/11/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/12/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/13/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/14/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/15/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/16/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/17/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/19/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/22/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/23/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/24/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/28/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td>Nevada<br>Mountain</td><td>MT</td><td>46.83</td><td>-112.57</td><td>8/1/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td>57</td></tr><tr><td></td><td></td><td></td><td></td><td>8/2/19</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>North Hills</td><td>MT</td><td>46.75</td><td>-111.96</td><td>7/29/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>5,009</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Pipeline</td><td>WA</td><td>46.83</td><td>-120.52</td><td>7/25/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td>6,516</td></tr><tr><td></td><td></td><td></td><td></td><td>7/26/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>7/27/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td>Prescribed</td><td>ID</td><td>44.956</td><td>-116.18</td><td>8/27/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td>151</td></tr><tr><td></td><td></td><td></td><td></td><td>8/28/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td></tr><tr><td>Ridgetop</td><td>MT</td><td>47.5</td><td>-108.23</td><td>8/2/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>11,128</td></tr><tr><td>Saber</td><td>AZ</td><td>35.01</td><td>-112.90</td><td>8/15/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>3,280</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><caption>**Table 2**
*Continued*</caption><thead><tr><th>Fire name</th><th>State</th><th>Ignition<br>lat</th><th>Ignition<br>lon</th><th>Date</th><th>DC-8</th><th>Chem-<br>otter</th><th>ER-2</th><th>Met-otter</th><th>LARGE</th><th>DRAGON</th><th>AML</th><th>MMP</th><th>Final<br>burned<br>area<br>(acres)</th><th>Fuels (FCCS 2014) 30 m</th></tr></thead><tbody><tr><td>Nethiker</td><td>ID</td><td>45.25</td><td>-115.93</td><td>8/9/19</td><td></td><td>X</td><td></td><td>X</td><td>X</td><td></td><td>X</td><td></td><td>2,369</td><td>Douglas-fir-Pacific ponderosa pine/oceanspray forest and Subalpine fir-lodgepole pine-whitebark pine-Engelmann spruce forest</td></tr><tr><td></td><td></td><td></td><td></td><td>8/10/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/11/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/12/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/13/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/14/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/15/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/16/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/17/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/19/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/22/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/23/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/24/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/28/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td>Nevada<br>Mountain</td><td>MT</td><td>46.83</td><td>-112.57</td><td>8/1/19</td><td></td><td>X</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td>57</td><td>Douglas-fir-Pacific ponderosa pine/oceanspray forest</td></tr><tr><td></td><td></td><td></td><td></td><td>8/2/19</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>North Hills</td><td>MT</td><td>46.75</td><td>-111.96</td><td>7/29/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>5,009</td><td>Idaho fescue-bluebunch wheatgrass grassland, Ponderosa pine savanna, and Douglas-fir-Pacific ponderosa pine/oceanspray forest</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>6,516</td><td>Sagebrush shrubland - exotic species</td></tr><tr><td>Pipeline</td><td>WA</td><td>46.83</td><td>-120.52</td><td>7/25/19</td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>7/26/19</td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>7/27/19</td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td>Prescribed</td><td>ID</td><td>44.956</td><td>-116.18</td><td>8/27/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td>151</td><td>Prescribed understory burn, Litter primarily from Douglas-fir-Pacific ponderosa pine/oceanspray forest</td></tr><tr><td></td><td></td><td></td><td></td><td>8/28/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td>Ridgetop</td><td>MT</td><td>47.5</td><td>-108.23</td><td>8/2/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>11,128</td><td>Bluebunch wheatgrass-bluegrass grassland</td></tr><tr><td>Saber</td><td>AZ</td><td>35.01</td><td>-112.90</td><td>8/15/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>3,280</td><td>Understory grass and litter primarily from Ponderosa pine-two-needle pinyon-Utah juniper forest</td></tr></tbody></table>
<table><caption>**Table 2**
*Continued*</caption><thead><tr><th>Fire name</th><th>State</th><th>Ignition<br>lat</th><th>Ignition<br>lon</th><th>Date</th><th>DC-8</th><th>Chem-<br>otter</th><th>ER-2</th><th>Met-otter</th><th>LARGE</th><th>DRAGON</th><th>AML</th><th>MMP</th><th>Final<br>burned<br>area<br>(acres)</th><th>Fuels (FCCS 2014) 30 m</th></tr></thead><tbody><tr><td>Shady</td><td>ID</td><td>44.52</td><td>-115.02</td><td>7/24/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>6,091</td><td>Timber litter and shrubs under Douglas-fir, Pacific<br>ponderosa-lodgepole pine/oceanspray forest</td></tr><tr><td></td><td></td><td></td><td></td><td>7/25/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>7/26/19</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>7/28/19</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>7/29/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/1/19</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/2/19</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/3/19</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sheep</td><td>ID</td><td>43.56</td><td>-112.88</td><td>7/24/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>112,168</td><td>Sagebrush shrubland with grasses</td></tr><tr><td>Sheridan</td><td>AZ</td><td>34.68</td><td>-112.89</td><td>8/15/19</td><td>X</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td>21,483</td><td>Pinyon-Utah juniper forest</td></tr><tr><td></td><td></td><td></td><td></td><td>8/16/19</td><td>X</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/21/19</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Smith Knob</td><td>ID</td><td>45.3</td><td>-115.54</td><td>9/5/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td>874</td><td>Showy sedge-black alpine sedge grassland and<br>Douglas-fir-Pacific ponderosa pine/oceanspray<br>forest</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>4,841</td><td>Ponderosa pine-Jeffrey pine forest</td></tr><tr><td>Springs</td><td>CA</td><td>37.83</td><td>-118.87</td><td>8/12/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/13/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/15/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/30/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td></tr><tr><td>Trumbull</td><td>AZ</td><td>36.41</td><td>-113.14</td><td>8/15/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>3,027</td><td>Pinyon-Utah juniper and Ponderosa pine forest with<br>timber and grass understory</td></tr><tr><td>Tucker</td><td>CA</td><td>41.73</td><td>-121.24</td><td>7/30/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>14,154</td><td>Sagebrush-greasewood shrubland with open grasses</td></tr><tr><td>Vader</td><td>ID</td><td>44.36</td><td>-115.14</td><td>7/21/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td>443</td><td>Timber litter from primarily Mature lodgepole pine<br>forest</td></tr><tr><td></td><td></td><td></td><td></td><td>7/22/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>7/25/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td>Williams<br>Flats</td><td>WA</td><td>47.94</td><td>-118.62</td><td>8/3/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td>44,360</td><td>Ignited in primarily Idaho fescue-bluebunch<br>wheatgrass grassland and expanded to primarily<br>Douglas-fir-Pacific ponderosa pine/oceanspray<br>forest</td></tr><tr><td></td><td></td><td></td><td></td><td>8/4/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/5/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/6/19</td><td>X</td><td></td><td></td><td>X</td><td></td><td></td><td>X</td><td>X</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/7/19</td><td>X</td><td></td><td></td><td>X</td><td></td><td></td><td>X</td><td>X</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/8/19</td><td>X</td><td></td><td></td><td>X</td><td></td><td></td><td>X</td><td>X</td><td></td><td></td></tr></tbody></table>
<table><caption>**Table 2**
*Continued*</caption><thead><tr><th>Fire name</th><th>State</th><th>Ignition<br>lat</th><th>Ignition<br>lon</th><th>Date</th><th>DC-8</th><th>Chem-<br>otter</th><th>ER-2</th><th>Met-otter</th><th>LARGE</th><th>DRAGON</th><th>AML</th><th>MMP</th><th>Final<br>burned<br>area<br>(acres)</th><th>Fuels (FCCS 2014) 30 m</th></tr></thead><tbody><tr><td>Shady</td><td>ID</td><td>44.52</td><td>-115.02</td><td>7/24/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>6,091</td><td>Timber litter and shrubs under Douglas-fir, Pacific<br>ponderosa-lodgepole pine/oceanspray forest</td></tr><tr><td></td><td></td><td></td><td></td><td>7/25/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>7/26/19</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>7/28/19</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>7/29/19</td><td></td><td></td><td></td><td>X</td><td>X</td><td>X</td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/1/19</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/2/19</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/3/19</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Sheep</td><td>ID</td><td>43.56</td><td>-112.88</td><td>7/24/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>112,168</td><td>Sagebrush shrubland with grasses</td></tr><tr><td>Sheridan</td><td>AZ</td><td>34.68</td><td>-112.89</td><td>8/15/19</td><td>X</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td>21,483</td><td>Pinyon-Utah juniper forest</td></tr><tr><td></td><td></td><td></td><td></td><td>8/16/19</td><td>X</td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/21/19</td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Smith Knob</td><td>ID</td><td>45.3</td><td>-115.54</td><td>9/5/19</td><td></td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td>874</td><td>Showy sedge-black alpine sedge grassland and<br>Douglas-fir-Pacific ponderosa pine/oceanspray<br>forest</td></tr><tr><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>4,841</td><td>Ponderosa pine-Jeffrey pine forest</td></tr><tr><td>Springs</td><td>CA</td><td>37.83</td><td>-118.87</td><td>8/12/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/13/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/15/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/30/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td></tr><tr><td>Trumbull</td><td>AZ</td><td>36.41</td><td>-113.14</td><td>8/15/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>3,027</td><td>Pinyon-Utah juniper and Ponderosa pine forest with<br>timber and grass understory</td></tr><tr><td>Tucker</td><td>CA</td><td>41.73</td><td>-121.24</td><td>7/30/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>14,154</td><td>Sagebrush-greasewood shrubland with open grasses</td></tr><tr><td>Vader</td><td>ID</td><td>44.36</td><td>-115.14</td><td>7/21/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td>443</td><td>Timber litter from primarily Mature lodgepole pine<br>forest</td></tr><tr><td></td><td></td><td></td><td></td><td>7/22/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>7/25/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td></td><td></td><td></td></tr><tr><td>Williams<br>Flats</td><td>WA</td><td>47.94</td><td>-118.62</td><td>8/3/19</td><td>X</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>44,360</td><td>Ignited in primarily Idaho fescue-bluebunch<br>wheatgrass grassland and expanded to primarily<br>Douglas-fir-Pacific ponderosa pine/oceanspray<br>forest</td></tr><tr><td></td><td></td><td></td><td></td><td>8/4/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/5/19</td><td></td><td></td><td></td><td></td><td></td><td></td><td>X</td><td>X</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/6/19</td><td>X</td><td></td><td></td><td>X</td><td></td><td></td><td>X</td><td>X</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/7/19</td><td>X</td><td></td><td></td><td>X</td><td></td><td></td><td>X</td><td>X</td><td></td><td></td></tr><tr><td></td><td></td><td></td><td></td><td>8/8/19</td><td>X</td><td></td><td></td><td>X</td><td></td><td></td><td>X</td><td>X</td><td></td><td></td></tr></tbody></table>
<figure><img src="image_5.png" /><figcaption>**Figure 2.** Maps showing the western portion of the campaign. (left) The flight tracks of the FIREX-AQ aircraft, the drive tracks of the mobile laboratories, the locations of the ground sites, and the locations of the investigated fires. (right) The investigated fires on top of a land cover map.</figcaption></figure>

flight tracks color coded with CO of the NOAA Chem Twin Otter for the western wildfires are shown in Figure S2 in Supporting Information S1.

The NOAA Chem Twin Otter was the only aircraft to observe significant nighttime processing of a smoke plume and an example is described in Figure 3 for the 204 Cow Fire.

The NOAA Chem Twin Otter was the only platform where a main science goal was to focus on nighttime smoke. Several flights targeted the transition between photochemistry and dark chemistry and intercepted nighttime smoke, which was usually aged daytime smoke. Figure 3 shows results from smoke sampled after sunset on 28 August 2019 from the 204 Cow fire. Plume age estimates suggest the youngest smoke was emitted between 0 and 2.25 hr before sunset with a best estimate of 1.0 hr before sunset. The time series shows that the production rate of NO<sub>3</sub>, P(NO<sub>3</sub>), is significant due to enhanced NO<sub>2</sub> within the plume and the smoke sampled contained <100 pptv of NO. The left panel shows a positive correlation of O<sub>3</sub> with CO from O<sub>3</sub> production for smoke emitted >5 hr before sunset, but a negative correlation with CO for smoke emitted <5 hr before sunset suggesting a strong potential for NO<sub>3</sub> chemistry.

### 2.3.3. NASA ER-2

NASA's high-altitude ER-2 research aircraft flew seven satellite simulator instruments with the goal to serve as a bridge between in-situ and satellite datasets. An airborne remote sensing instrument suite was used to help characterize fire development, emission processes, plume evolution, and downwind impacts on air quality. The primary objective for addressing broad FIREX-AQ science goals was to provide large-scale high-resolution observational constraints for fire behavior, plume rise, and smoke emission models, while the specific objectives of this platform were to: (a) Establish observational links between atmospheric conditions, fire temperature, smoke plume heights, and downwind smoke dispersion; (b) Characterize regional aerosol properties and trace gases profiles/amounts downwind from fires; (c) Evaluate multi-instrument synergy for fire process characterization. The payload of the NASA ER-2 was designed to achieve those goals and is listed in Table 5. The NASA ER-2 flights are shown in Figure 2 and the 10 observed fires are included in Table 2. The specific flight tracks of the NASA ER-2 for the western wildfires are shown in Figure S3 in Supporting Information S1.

All NASA ER-2 flights were coordinated with satellites in a variety of smoke conditions to evaluate how well satellite retrievals can handle small-scale sub-pixel variabilities. The satellite coordination included NASA ER-2 flight legs on and parallel to satellite tracks to evaluate viewing angle uncertainties in satellite retrievals. Ground monitors (including mobile AERONET, and California Air Resources Board (CARB) mobile platforms) were routinely targeted during the campaign primarily for NASA ER-2 instrument algorithm validation purposes.

An example of how the ER-2 connects to satellite data is shown in Figure 4. The NASA ER-2 investigated the Williams Flats fire in coordination with the NASA DC-8 aircraft on 06 August 2019, where the eMAS instrument measured high aerosol optical depth (AOD) with a very high spatial resolution at center of the MODIS-Aqua swath, where the collocation of MODIS and eMAS aligned nicely. The comparison shows that eMAS and MODIS 10 km data are in good agreement. The NASA DC-8 aircraft sampled the plume in-situ at roughly the same time.
<figure><img src="image_5.png" /><figcaption>**Figure 2.** Maps showing the western portion of the campaign. (left) The flight tracks of the FIREX-AQ aircraft, the drive tracks of the mobile laboratories, the locations of the ground sites, and the locations of the investigated fires. (right) The investigated fires on top of a land cover map.</figcaption></figure>

flight tracks color coded with CO of the NOAA Chem Twin Otter for the western wildfires are shown in Figure S2 in Supporting Information S1.

The NOAA Chem Twin Otter was the only aircraft to observe significant nighttime processing of a smoke plume and an example is described in Figure 3 for the 204 Cow Fire.

The NOAA Chem Twin Otter was the only platform where a main science goal was to focus on nighttime smoke. Several flights targeted the transition between photochemistry and dark chemistry and intercepted nighttime smoke, which was usually aged daytime smoke. Figure 3 shows results from smoke sampled after sunset on 28 August 2019 from the 204 Cow fire. Plume age estimates suggest the youngest smoke was emitted between 0 and 2.25 hr before sunset with a best estimate of 1.0 hr before sunset. The time series shows that the production rate of NO<sub>3</sub>, P(NO<sub>3</sub>), is significant due to enhanced NO<sub>2</sub> within the plume and the smoke sampled contained <100 pptv of NO. The left panel shows a positive correlation of O<sub>3</sub> with CO from O<sub>3</sub> production for smoke emitted >5 hr before sunset, but a negative correlation with CO for smoke emitted <5 hr before sunset suggesting a strong potential for NO<sub>3</sub> chemistry.

### 2.3.3. NASA ER-2

NASA's high-altitude ER-2 research aircraft flew seven satellite simulator instruments with the goal to serve as a bridge between in-situ and satellite datasets. An airborne remote sensing instrument suite was used to help characterize fire development, emission processes, plume evolution, and downwind impacts on air quality. The primary objective for addressing broad FIREX-AQ science goals was to provide large-scale high-resolution observational constraints for fire behavior, plume rise, and smoke emission models, while the specific objectives of this platform were to: (a) Establish observational links between atmospheric conditions, fire temperature, smoke plume heights, and downwind smoke dispersion; (b) Characterize regional aerosol properties and trace gases profiles/amounts downwind from fires; (c) Evaluate multi-instrument synergy for fire process characterization. The payload of the NASA ER-2 was designed to achieve those goals and is listed in Table 5. The NASA ER-2 flights are shown in Figure 2 and the 10 observed fires are included in Table 2. The specific flight tracks of the NASA ER-2 for the western wildfires are shown in Figure S3 in Supporting Information S1.

All NASA ER-2 flights were coordinated with satellites in a variety of smoke conditions to evaluate how well satellite retrievals can handle small-scale sub-pixel variabilities. The satellite coordination included NASA ER-2 flight legs on and parallel to satellite tracks to evaluate viewing angle uncertainties in satellite retrievals. Ground monitors (including mobile AERONET, and California Air Resources Board (CARB) mobile platforms) were routinely targeted during the campaign primarily for NASA ER-2 instrument algorithm validation purposes.

An example of how the ER-2 connects to satellite data is shown in Figure 4. The NASA ER-2 investigated the Williams Flats fire in coordination with the NASA DC-8 aircraft on 06 August 2019, where the eMAS instrument measured high aerosol optical depth (AOD) with a very high spatial resolution at center of the MODIS-Aqua swath, where the collocation of MODIS and eMAS aligned nicely. The comparison shows that eMAS and MODIS 10 km data are in good agreement. The NASA DC-8 aircraft sampled the plume in-situ at roughly the same time.
<table><caption>**Table 3**
Payload of the NASA DC-8 for FIREX-AQ</caption><thead><tr><th>Species measured</th><th>Technique</th><th>Frequency (Hz)</th><th>Investigator</th><th>Institution</th><th>References</th></tr></thead><tbody><tr><td colspan="6">Gas phase measurements (tracers and reactive nitrogen)</td></tr><tr><td>O<sub>3</sub>, NO, NO<sub>2</sub>, NO<sub>Y</sub></td><td>Chemiluminescence</td><td>1</td><td>Tom Ryerson</td><td>NOAA CSL</td><td>Ryerson et al. (2000)</td></tr><tr><td>CO<sub>2</sub>, CO, CH<sub>4</sub>, H<sub>2</sub>O</td><td>Laser absorption spectroscopy</td><td>1–5</td><td>Glenn Diskin</td><td>NASA LaRC</td><td>Sachse et al. (1991)</td></tr><tr><td>NH<sub>3</sub>, Speciated hydrocarbons, and OVOCs<sup>a</sup></td><td>PTR-ToF-MS</td><td>1–5</td><td>Armin Wisthaler</td><td>U Innsbruck and U Oslo</td><td>Müller et al. (2014), Tomsche et al. (2022)</td></tr><tr><td>PAN, PPN, other PANs</td><td>Chemical ionization mass spectrometry (CIMS)</td><td>1–10</td><td>Greg Huey</td><td>Georgia Tech</td><td>Zheng et al. (2011)</td></tr><tr><td>HONO, HCN, HNCO, HCOOH, N<sub>2</sub>O<sub>5</sub>, hydroperoxymethyl thioformate (HPMTF), halogenated compounds</td><td>Iodide ToF-CIMS</td><td>1</td><td>Patrick Veres</td><td>NOAA CSL</td><td>Veres et al. (2020)</td></tr><tr><td>CH<sub>3</sub>CN</td><td>H3O+ ToF-CIMS</td><td>1–5</td><td>Carsten Warneke</td><td>NOAA CSL</td><td>Yuan et al. (2017)</td></tr><tr><td>CO, N<sub>2</sub>O, H<sub>2</sub>O</td><td>Cavity enhanced absorption</td><td>1</td><td>Jeff Peischl</td><td>NOAA CSL</td><td>Eilerman et al. (2016)</td></tr><tr><td>SO<sub>2</sub></td><td>Laser induced fluorescence</td><td>1</td><td>Andrew Rollins</td><td>NOAA CSL</td><td>Rollins et al. (2016)</td></tr><tr><td>NO</td><td>Laser induced fluorescence</td><td>1</td><td>Andrew Rollins</td><td>NOAA CSL</td><td>Rollins et al. (2020)</td></tr><tr><td>HCN</td><td>CIMS</td><td>1–10</td><td>Paul Wennberg</td><td>CalTech</td><td>Crounse et al. (2006)</td></tr><tr><td>NO<sub>2</sub></td><td>CANOE, nonresonant laser-induced fluorescence</td><td>1</td><td>Jason St. Clair</td><td>NASA GSFC</td><td>St. Clair et al. (2019)</td></tr><tr><td>NO<sub>2</sub>, HONO</td><td>Airborne cavity enhanced spectrometer</td><td>1</td><td>Caroline Womack</td><td>NOAA CSL</td><td>Min et al. (2016)</td></tr><tr><td>HNO<sub>3</sub></td><td>Mist chamber</td><td>0.0066</td><td>Jack Dibb</td><td>UNH</td><td>Scheuer et al. (2010)</td></tr><tr><td>O<sub>3</sub></td><td>ROZE, cavity enhanced absorption</td><td>1–10</td><td>Tom Hanisco</td><td>NASA GSFC</td><td>Hannun et al. (2020)</td></tr><tr><td colspan="6">Gas phase measurements (Hydrocarbons and Oxidation Products)</td></tr><tr><td>CH<sub>2</sub>O, C<sub>2</sub>H<sub>6</sub></td><td>Laser absorption spectroscopy</td><td>1</td><td>Alan Fried</td><td>CU Boulder</td><td>Weibring et al. (2007)</td></tr><tr><td>C<sub>2</sub>-C<sub>11</sub> Alkanes, C<sub>2-10</sub> Alkenes, C<sub>6</sub>-C<sub>9</sub> Aromatics, C<sub>1</sub>-C<sub>5</sub> Alkylnitrates, etc.</td><td>Whole air sampling</td><td>Up to 168/flight</td><td>Don Blake</td><td>UC Irvine</td><td>Simpson et al. (2020)</td></tr><tr><td>Speciated hydrocarbons and OVOCs</td><td>H3O+ ToF-CIMS</td><td>1–5</td><td>Carsten Warneke</td><td>NOAA CSL</td><td>Yuan et al. (2017)</td></tr><tr><td>C<sub>2</sub>-C<sub>10</sub> Alkanes, C<sub>2</sub>-C<sub>4</sub> Alkenes, C<sub>6</sub>-C<sub>9</sub> Aromatics, C<sub>1</sub>-C<sub>5</sub> Alkylnitrates, etc.</td><td>Whole air sampling</td><td>Up to 72/flight</td><td>Jessica Gilman</td><td>NOAA CSL</td><td>Lerner et al. (2017)</td></tr><tr><td>C<sub>3</sub>-C<sub>10</sub> hydrocarbons, C<sub>1</sub>-C<sub>7</sub> OVOCs, HCN, CH<sub>3</sub>CN, C<sub>1</sub>-C<sub>2</sub> halocarbons, etc.</td><td>HR-ToF-GC/MS</td><td>0.0095</td><td>Eric Apel</td><td>NCAR ACOM</td><td>Apel et al. (2010)</td></tr><tr><td>CH<sub>2</sub>O</td><td>Laser induced fluorescence</td><td>1–10</td><td>Tom Hanisco</td><td>NASA GSFC</td><td>Cazorla et al. (2015)</td></tr><tr><td>H<sub>2</sub>O<sub>2</sub>, organic peroxides, organic acids, isoprene oxidations products, etc.</td><td>CIMS</td><td>1</td><td>Paul Wennberg</td><td>CalTech</td><td>Crounse et al. (2006)</td></tr><tr><td>glyoxal, methylglyoxal</td><td>Airborne cavity enhanced spectrometer</td><td>1</td><td>Caroline Womack</td><td>NOAA CSL</td><td>Min et al. (2016)</td></tr><tr><td colspan="6">Aerosol measurements (physical/optical/chemical)</td></tr><tr><td>bulk aerosol composition</td><td>Filter sampling (FS) and mist chamber (MC)</td><td>0.0066</td><td>Jack Dibb</td><td>UNH</td><td>Heim et al. (2020)</td></tr></tbody></table>
<table><caption>**Table 3**
Payload of the NASA DC-8 for FIREX-AQ</caption><thead><tr><th>Species measured</th><th>Technique</th><th>Frequency (Hz)</th><th>Investigator</th><th>Institution</th><th>References</th></tr></thead><tbody><tr><td colspan="6">Gas phase measurements (tracers and reactive nitrogen)</td></tr><tr><td>O<sub>3</sub>, NO, NO<sub>2</sub>, NO<sub>Y</sub></td><td>Chemiluminescence</td><td>1</td><td>Tom Ryerson</td><td>NOAA CSL</td><td>Ryerson et al. (2000)</td></tr><tr><td>CO<sub>2</sub>, CO, CH<sub>4</sub>, H<sub>2</sub>O</td><td>Laser absorption spectroscopy</td><td>1–5</td><td>Glenn Diskin</td><td>NASA LaRC</td><td>Sachse et al. (1991)</td></tr><tr><td>NH<sub>3</sub>, Speciated hydrocarbons, and OVOCs<sup>a</sup></td><td>PTR-ToF-MS</td><td>1–5</td><td>Armin Wisthaler</td><td>U Innsbruck and U Oslo</td><td>Müller et al. (2014), Tomsche et al. (2022)</td></tr><tr><td>PAN, PPN, other PANs</td><td>Chemical ionization mass spectrometry (CIMS)</td><td>1–10</td><td>Greg Huey</td><td>Georgia Tech</td><td>Zheng et al. (2011)</td></tr><tr><td>HONO, HCN, HNCO, HCOOH, N<sub>2</sub>O<sub>5</sub>, hydroperoxymethyl thioformate (HPMTF), halogenated compounds</td><td>Iodide ToF-CIMS</td><td>1</td><td>Patrick Veres</td><td>NOAA CSL</td><td>Veres et al. (2020)</td></tr><tr><td>CH<sub>3</sub>CN</td><td>H3O+ ToF-CIMS</td><td>1–5</td><td>Carsten Warneke</td><td>NOAA CSL</td><td>Yuan et al. (2017)</td></tr><tr><td>CO, N<sub>2</sub>O, H<sub>2</sub>O</td><td>Cavity enhanced absorption</td><td>1</td><td>Jeff Peischl</td><td>NOAA CSL</td><td>Eilerman et al. (2016)</td></tr><tr><td>SO<sub>2</sub></td><td>Laser induced fluorescence</td><td>1</td><td>Andrew Rollins</td><td>NOAA CSL</td><td>Rollins et al. (2016)</td></tr><tr><td>NO</td><td>Laser induced fluorescence</td><td>1</td><td>Andrew Rollins</td><td>NOAA CSL</td><td>Rollins et al. (2020)</td></tr><tr><td>HCN</td><td>CIMS</td><td>1–10</td><td>Paul Wennberg</td><td>CalTech</td><td>Crounse et al. (2006)</td></tr><tr><td>NO<sub>2</sub></td><td>CANOE, nonresonant laser-induced fluorescence</td><td>1</td><td>Jason St. Clair</td><td>NASA GSFC</td><td>St. Clair et al. (2019)</td></tr><tr><td>NO<sub>2</sub>, HONO</td><td>Airborne cavity enhanced spectrometer</td><td>1</td><td>Caroline Womack</td><td>NOAA CSL</td><td>Min et al. (2016)</td></tr><tr><td>HNO<sub>3</sub></td><td>Mist chamber</td><td>0.0066</td><td>Jack Dibb</td><td>UNH</td><td>Scheuer et al. (2010)</td></tr><tr><td>O<sub>3</sub></td><td>ROZE, cavity enhanced absorption</td><td>1–10</td><td>Tom Hanisco</td><td>NASA GSFC</td><td>Hannun et al. (2020)</td></tr><tr><td colspan="6">Gas phase measurements (Hydrocarbons and Oxidation Products)</td></tr><tr><td>CH<sub>2</sub>O, C<sub>2</sub>H<sub>6</sub></td><td>Laser absorption spectroscopy</td><td>1</td><td>Alan Fried</td><td>CU Boulder</td><td>Weibring et al. (2007)</td></tr><tr><td>C<sub>2</sub>-C<sub>11</sub> Alkanes, C<sub>2-10</sub> Alkenes, C<sub>6</sub>-C<sub>9</sub> Aromatics, C<sub>1</sub>-C<sub>5</sub> Alkylnitrates, etc.</td><td>Whole air sampling</td><td>Up to 168/flight</td><td>Don Blake</td><td>UC Irvine</td><td>Simpson et al. (2020)</td></tr><tr><td>Speciated hydrocarbons and OVOCs</td><td>H3O+ ToF-CIMS</td><td>1–5</td><td>Carsten Warneke</td><td>NOAA CSL</td><td>Yuan et al. (2017)</td></tr><tr><td>C<sub>2</sub>-C<sub>10</sub> Alkanes, C<sub>2</sub>-C<sub>4</sub> Alkenes, C<sub>6</sub>-C<sub>9</sub> Aromatics, C<sub>1</sub>-C<sub>5</sub> Alkylnitrates, etc.</td><td>Whole air sampling</td><td>Up to 72/flight</td><td>Jessica Gilman</td><td>NOAA CSL</td><td>Lerner et al. (2017)</td></tr><tr><td>C<sub>3</sub>-C<sub>10</sub> hydrocarbons, C<sub>1</sub>-C<sub>7</sub> OVOCs, HCN, CH<sub>3</sub>CN, C<sub>1</sub>-C<sub>2</sub> halocarbons, etc.</td><td>HR-ToF-GC/MS</td><td>0.0095</td><td>Eric Apel</td><td>NCAR ACOM</td><td>Apel et al. (2010)</td></tr><tr><td>CH<sub>2</sub>O</td><td>Laser induced fluorescence</td><td>1–10</td><td>Tom Hanisco</td><td>NASA GSFC</td><td>Cazorla et al. (2015)</td></tr><tr><td>H<sub>2</sub>O<sub>2</sub>, organic peroxides, organic acids, isoprene oxidations products, etc.</td><td>CIMS</td><td>1</td><td>Paul Wennberg</td><td>CalTech</td><td>Crounse et al. (2006)</td></tr><tr><td>glyoxal, methylglyoxal</td><td>Airborne cavity enhanced spectrometer</td><td>1</td><td>Caroline Womack</td><td>NOAA CSL</td><td>Min et al. (2016)</td></tr><tr><td colspan="6">Aerosol measurements (physical/optical/chemical)</td></tr><tr><td>bulk aerosol composition</td><td>Filter sampling (FS) and mist chamber (MC)</td><td>0.0066</td><td>Jack Dibb</td><td>UNH</td><td>Heim et al. (2020)</td></tr></tbody></table>
<caption>**Table 3**</caption>

Continued

<table><thead><tr><th>Species measured</th><th>Technique</th><th>Frequency (Hz)</th><th>Investigator</th><th>Institution</th><th>References</th></tr></thead><tbody><tr><td>BrC absorption</td><td>FS and MC with spectro-photometer</td><td>0.0066</td><td>Rodney Weber</td><td>Georgia Tech</td><td>Forrister et al. (2015), Zeng et al. (2021)</td></tr><tr><td>Aerosol absorption and extinction at multiple wavelengths and RH</td><td>Cavity ringdown extinction and photoacoustic absorption spectrometers</td><td>1</td><td>Nick Wagner</td><td>NOAA CSL</td><td>Lack et al. (2012)</td></tr><tr><td>Aerosol scattering phase function at UV and visible (blue) wavelengths</td><td>Laser imaging nephelometer</td><td>1</td><td>Adam Ahern</td><td>NOAA CSL</td><td>Manfred et al. (2018)</td></tr><tr><td>Aerosol number concentration</td><td>TSI CPC</td><td>1</td><td>Richard Moore</td><td>NASA LaRC</td><td>Sinclair & Hoopes (1975)</td></tr><tr><td></td><td>BMI mCPC</td><td>~5–10</td><td></td><td></td><td>Agarwal & Sem (1980)</td></tr><tr><td>Cloud and supermicron aerosol size distribution</td><td>DMT CDP<br>DMT CPSPD</td><td>1</td><td>Richard Moore</td><td>NASA LaRC</td><td>Baumgardner et al. (2014), Lance et al. (2010)</td></tr><tr><td>Aerosol number size distribution</td><td>TSI SMPS (mobility), TSI LAS (optical)</td><td>0.016<br>1</td><td>Richard Moore</td><td>NASA LaRC</td><td>Moore et al. (2021)</td></tr><tr><td>Non-volatile aerosol number concentration and size distribution (350°C)</td><td>Thermally-denuded CPC and LAS</td><td>1</td><td>Richard Moore</td><td>NASA LaRC</td><td></td></tr><tr><td>Cloud condensation nuclei (0.34%SS)</td><td>DMT CCN Counter</td><td>1</td><td>Richard Moore</td><td>NASA LaRC</td><td>Roberts & Nenes (2005)</td></tr><tr><td>Aerosol absorption and scattering at multiple wavelengths and RH</td><td>TSI nephelometer, radiance research PSAP<br>BMI TAP</td><td>1</td><td>Richard Moore</td><td>NASA LaRC</td><td>Bodhaine et al. (1991), Bond et al. (1999), Lin et al. (1973), and Ogren (2010)</td></tr><tr><td>BC concentration, size, mixing state</td><td>SP2</td><td>1</td><td>Joshua Schwarz</td><td>NOAA CSL</td><td>Schwarz et al. (2008)</td></tr><tr><td>Submicron aerosol bulk and size segregated composition</td><td>HR-ToF-AMS</td><td>1–10</td><td>Jose Jimenez</td><td>CU Boulder</td><td>Canagaratna et al. (2007), Guo et al. (2021)</td></tr><tr><td>Molecular aerosol composition</td><td>EESI-MS (ESI offline filters)</td><td>1 (2e–4)</td><td>Jose Jimenez (Alexander Laskin)</td><td>CU Boulder (Purdue U)</td><td>Pagonis et al. (2021)</td></tr><tr><td>Cloud and coarse mode size distribution</td><td>Optical wing probe detectors</td><td>1</td><td>Bernadett Weinzierl</td><td>U Vienna</td><td>Baumgardner et al. (2001)</td></tr><tr><td>mixing state, shape, composition of single particles</td><td>transmission electron microscopy</td><td>24/flight</td><td>Adachi Kouji</td><td>Meteorological Research Institute, Japan</td><td>Adachi et al. (2020)</td></tr><tr><td>Remote sensing measurements (active and passive)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Zenith/nadir solar actinic flux and photolysis frequencies</td><td>4π-sr spectroradiometry</td><td>1</td><td>Sam Hall</td><td>NCAR ACOM</td><td>Hall et al. (2018)</td></tr><tr><td>Active fires (T ≤ 850 K) and burn scars at 10–20 m resolution</td><td>MODIS/ASTER airborne simulator (MASTER) scanning spectrometer</td><td></td><td>Jeff Myers</td><td>NASA ARC</td><td>Hook et al. (2001)</td></tr><tr><td>Zenith/nadir profiles of O<sub>3</sub>, aerosol backscatter, extinction, depolarization, etc.</td><td>Differential absorption lidar-high spectral resolution lidar (DIAL-HSRL)</td><td>0.1</td><td>John Hair</td><td>NASA LaRC</td><td>Hair et al. (2008)</td></tr><tr><td>Meteorological measurements</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<caption>**Table 3**</caption>

Continued

<table><thead><tr><th>Species measured</th><th>Technique</th><th>Frequency (Hz)</th><th>Investigator</th><th>Institution</th><th>References</th></tr></thead><tbody><tr><td>BrC absorption</td><td>FS and MC with spectro-photometer</td><td>0.0066</td><td>Rodney Weber</td><td>Georgia Tech</td><td>Forrister et al. (2015), Zeng et al. (2021)</td></tr><tr><td>Aerosol absorption and extinction at multiple wavelengths and RH</td><td>Cavity ringdown extinction and photoacoustic absorption spectrometers</td><td>1</td><td>Nick Wagner</td><td>NOAA CSL</td><td>Lack et al. (2012)</td></tr><tr><td>Aerosol scattering phase function at UV and visible (blue) wavelengths</td><td>Laser imaging nephelometer</td><td>1</td><td>Adam Ahern</td><td>NOAA CSL</td><td>Manfred et al. (2018)</td></tr><tr><td>Aerosol number concentration</td><td>TSI CPC</td><td>1</td><td>Richard Moore</td><td>NASA LaRC</td><td>Sinclair & Hoopes (1975)</td></tr><tr><td></td><td>BMI mCPC</td><td>~5–10</td><td></td><td></td><td>Agarwal & Sem (1980)</td></tr><tr><td>Cloud and supermicron aerosol size distribution</td><td>DMT CDP<br>DMT CPSPD</td><td>1</td><td>Richard Moore</td><td>NASA LaRC</td><td>Baumgardner et al. (2014), Lance et al. (2010)</td></tr><tr><td>Aerosol number size distribution</td><td>TSI SMPS (mobility), TSI LAS (optical)</td><td>0.016<br>1</td><td>Richard Moore</td><td>NASA LaRC</td><td>Moore et al. (2021)</td></tr><tr><td>Non-volatile aerosol number concentration and size distribution (350°C)</td><td>Thermally-denuded CPC and LAS</td><td>1</td><td>Richard Moore</td><td>NASA LaRC</td><td></td></tr><tr><td>Cloud condensation nuclei (0.34%SS)</td><td>DMT CCN Counter</td><td>1</td><td>Richard Moore</td><td>NASA LaRC</td><td>Roberts & Nenes (2005)</td></tr><tr><td>Aerosol absorption and scattering at multiple wavelengths and RH</td><td>TSI nephelometer, radiance research PSAP<br>BMI TAP</td><td>1</td><td>Richard Moore</td><td>NASA LaRC</td><td>Bodhaine et al. (1991), Bond et al. (1999), Lin et al. (1973), and Ogren (2010)</td></tr><tr><td>BC concentration, size, mixing state</td><td>SP2</td><td>1</td><td>Joshua Schwarz</td><td>NOAA CSL</td><td>Schwarz et al. (2008)</td></tr><tr><td>Submicron aerosol bulk and size segregated composition</td><td>HR-ToF-AMS</td><td>1–10</td><td>Jose Jimenez</td><td>CU Boulder</td><td>Canagaratna et al. (2007), Guo et al. (2021)</td></tr><tr><td>Molecular aerosol composition</td><td>EESI-MS (ESI offline filters)</td><td>1 (2e–4)</td><td>Jose Jimenez (Alexander Laskin)</td><td>CU Boulder (Purdue U)</td><td>Pagonis et al. (2021)</td></tr><tr><td>Cloud and coarse mode size distribution</td><td>Optical wing probe detectors</td><td>1</td><td>Bernadett Weinzierl</td><td>U Vienna</td><td>Baumgardner et al. (2001)</td></tr><tr><td>mixing state, shape, composition of single particles</td><td>transmission electron microscopy</td><td>24/flight</td><td>Adachi Kouji</td><td>Meteorological Research Institute, Japan</td><td>Adachi et al. (2020)</td></tr><tr><td>Remote sensing measurements (active and passive)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Zenith/nadir solar actinic flux and photolysis frequencies</td><td>4π-sr spectroradiometry</td><td>1</td><td>Sam Hall</td><td>NCAR ACOM</td><td>Hall et al. (2018)</td></tr><tr><td>Active fires (T ≤ 850 K) and burn scars at 10–20 m resolution</td><td>MODIS/ASTER airborne simulator (MASTER) scanning spectrometer</td><td></td><td>Jeff Myers</td><td>NASA ARC</td><td>Hook et al. (2001)</td></tr><tr><td>Zenith/nadir profiles of O<sub>3</sub>, aerosol backscatter, extinction, depolarization, etc.</td><td>Differential absorption lidar-high spectral resolution lidar (DIAL-HSRL)</td><td>0.1</td><td>John Hair</td><td>NASA LaRC</td><td>Hair et al. (2008)</td></tr><tr><td>Meteorological measurements</td><td></td><td></td><td></td><td></td><td></td></tr></tbody></table>
<table><caption>**Table 3**
*Continued*</caption><thead><tr><th>Species measured</th><th>Technique</th><th>Frequency (Hz)</th><th>Investigator</th><th>Institution</th><th>References</th></tr></thead><tbody><tr><td>3D winds, turbulence, Reynolds number</td><td>Meteorological measurement system</td><td>1–20</td><td>Paul Bui</td><td>NASA ARC</td><td></td></tr><tr><td>Meteorological and navigation parameters</td><td>Various</td><td>1–5</td><td>Melissa Yang</td><td>NASA NSRC</td><td></td></tr></tbody></table>

### 2.3.4. NOAA Met Twin Otter

The NOAA Met Twin Otter (MET-TO), based in Boise, ID, completed 14 science flights (57 hr) and sampled 12 different fires. The MET-TO had a typical endurance of 4 hr and, for more distant fires, would land and refuel at nearby airfields to extend its sampling time on station. Four of the flights were coordinated with the NOAA Chem Twin Otter.

The MET-TO was deployed to characterize the spatial structure of the horizontal wind fields surrounding the fire, the fire strength and progression, and to investigate the vertical motions over the fire and the transport and geometry of the downwind plume. This was accomplished using remote sensing instrumentation (a scanning Doppler lidar, optical imager, and infrared radiometer) and a meteorological package to profile thermodynamic variables when the aircraft was changing altitudes and measuring conditions at flight altitude. The payload listed in Table 6 for this platform was purposely kept light in order to maximize the endurance of the aircraft. The NOAA Met Twin Otter flights are shown in Figure 2 and the intercepted fires are included in Table 2. The specific flight tracks of the NOAA Met Twin Otter for the western wildfires are shown in Figure S4 in Supporting Information S1.

The NOAA MET Twin Otter aircraft flew above the plume, when possible, in order to provide complete vertical coverage of dynamics and aerosol concentration throughout the plume. The aerosol backscatter measured with the Micro-pulse Doppler Lidar of the NOAA MET-TO is shown in Figure 5. The backscatter data together with the measured wind field structure can be used to determine fire weather dynamics. For example, the plume rise and the injection height can be measured as a function of the fire strength and boundary layer conditions.

### 2.4. Mobile Laboratories

#### 2.4.1. NASA MACH-2

The NASA Langley Aerosol Research Group (LARGE; https://science-data.larc.nasa.gov/large/) deployed the NASA Mobile Aerosol Characterization laboratory (MACH-2) with Boise, ID as a home base. The MACH-2 was driven to the fires as listed in Table 1 to investigate smoke for up to 5 days like in the case of the Williams Flats fire. The MACH-2 coordinated with other research platforms, including the NOAA Twin Otters, the Aerodyne Mobile Laboratory (AML), the Mobile Dragons, and the NASA DC-8. The MACH-2 traveled 13,300 miles in 51 days, sampled eight fires in six different states, and recorded 10.5 days of 1-s data.

The payload of the MACH-2 is listed in Table 7 and was focused on characterizing aerosol optical, microphysical and compositional properties. Most instruments sampled during the drive, but filter samples were only collected during stationary measurements. The MACH-2 conducted detailed measurements of gaseous and particulate nitrogen species including the isotopic composition of NOₓ, HONO, HNO₃ and aerosol nitrate to examine reactive nitrogen budgets in fresh and aged smoke plumes. In addition, quartz-fiber and Teflon filter samples were collected and analyzed for EC/OC, BrC, toxicity, organic functional groups, and isotopes. Samples were drawn from a common inlet on the top rear of the vehicle to minimize generator exhaust contamination and enable temporal correlation between measured species. Ancillary measurements of CO, CO₂, NO₂, NOₓ, H₂O, temperature, pressure, vertical aerosol backscattering and navigational parameters were made to establish plume characteristics and vehicle location relative to emission sources. The MACH-2 drives are shown in Figure 2 and the intercepted fires are included in Table 2. The specific drive tracks color coded with CO of the MACH-2 for the western wildfires are shown in Figure S5 in Supporting Information S1.

<footnote>ªThe VOCs from this instrument were only archived for one flight to cover unavailable data from the primary H₃O⁺-ToF CIMS.</footnote>
<table><caption>**Table 3**
*Continued*</caption><thead><tr><th>Species measured</th><th>Technique</th><th>Frequency (Hz)</th><th>Investigator</th><th>Institution</th><th>References</th></tr></thead><tbody><tr><td>3D winds, turbulence, Reynolds number</td><td>Meteorological measurement system</td><td>1–20</td><td>Paul Bui</td><td>NASA ARC</td><td></td></tr><tr><td>Meteorological and navigation parameters</td><td>Various</td><td>1–5</td><td>Melissa Yang</td><td>NASA NSRC</td><td></td></tr></tbody></table>

### 2.3.4. NOAA Met Twin Otter

The NOAA Met Twin Otter (MET-TO), based in Boise, ID, completed 14 science flights (57 hr) and sampled 12 different fires. The MET-TO had a typical endurance of 4 hr and, for more distant fires, would land and refuel at nearby airfields to extend its sampling time on station. Four of the flights were coordinated with the NOAA Chem Twin Otter.

The MET-TO was deployed to characterize the spatial structure of the horizontal wind fields surrounding the fire, the fire strength and progression, and to investigate the vertical motions over the fire and the transport and geometry of the downwind plume. This was accomplished using remote sensing instrumentation (a scanning Doppler lidar, optical imager, and infrared radiometer) and a meteorological package to profile thermodynamic variables when the aircraft was changing altitudes and measuring conditions at flight altitude. The payload listed in Table 6 for this platform was purposely kept light in order to maximize the endurance of the aircraft. The NOAA Met Twin Otter flights are shown in Figure 2 and the intercepted fires are included in Table 2. The specific flight tracks of the NOAA Met Twin Otter for the western wildfires are shown in Figure S4 in Supporting Information S1.

The NOAA MET Twin Otter aircraft flew above the plume, when possible, in order to provide complete vertical coverage of dynamics and aerosol concentration throughout the plume. The aerosol backscatter measured with the Micro-pulse Doppler Lidar of the NOAA MET-TO is shown in Figure 5. The backscatter data together with the measured wind field structure can be used to determine fire weather dynamics. For example, the plume rise and the injection height can be measured as a function of the fire strength and boundary layer conditions.

## 2.4. Mobile Laboratories

### 2.4.1. NASA MACH-2

The NASA Langley Aerosol Research Group (LARGE; https://science-data.larc.nasa.gov/large/) deployed the NASA Mobile Aerosol Characterization laboratory (MACH-2) with Boise, ID as a home base. The MACH-2 was driven to the fires as listed in Table 1 to investigate smoke for up to 5 days like in the case of the Williams Flats fire. The MACH-2 coordinated with other research platforms, including the NOAA Twin Otters, the Aerodyne Mobile Laboratory (AML), the Mobile Dragons, and the NASA DC-8. The MACH-2 traveled 13,300 miles in 51 days, sampled eight fires in six different states, and recorded 10.5 days of 1-s data.

The payload of the MACH-2 is listed in Table 7 and was focused on characterizing aerosol optical, microphysical and compositional properties. Most instruments sampled during the drive, but filter samples were only collected during stationary measurements. The MACH-2 conducted detailed measurements of gaseous and particulate nitrogen species including the isotopic composition of NOₓ, HONO, HNO₃ and aerosol nitrate to examine reactive nitrogen budgets in fresh and aged smoke plumes. In addition, quartz-fiber and Teflon filter samples were collected and analyzed for EC/OC, BrC, toxicity, organic functional groups, and isotopes. Samples were drawn from a common inlet on the top rear of the vehicle to minimize generator exhaust contamination and enable temporal correlation between measured species. Ancillary measurements of CO, CO₂, NO₂, NOₓ, H₂O, temperature, pressure, vertical aerosol backscattering and navigational parameters were made to establish plume characteristics and vehicle location relative to emission sources. The MACH-2 drives are shown in Figure 2 and the intercepted fires are included in Table 2. The specific drive tracks color coded with CO of the MACH-2 for the western wildfires are shown in Figure S5 in Supporting Information S1.

<footnote>ªThe VOCs from this instrument were only archived for one flight to cover unavailable data from the primary H₃O⁺-ToF CIMS.</footnote>
<figure><img src="image_6.png" /><figcaption>**Figure 3.** Nighttime processing of a smoke plume from the 204 Cow Fire on 28 August 2019 observed by the NOAA Chem Twin Otter during FIREX-AQ. (top) The flight track color coded by CO. (bottom) CO correlation with $O_3$. (right) Time series of the $NO_3$ production rate, $NO_2$, and $O_3$.</figcaption></figure>

### 2.4.2. Aerodyne Mobile Laboratory

The AML operated out of McCall, ID (the location of a ground site as described below), during FIREX-AQ from 9 to 28 August 2019 and during WE-CAN from 11 to 28 August 2018. The AML was well-equipped for detailed gas- and aerosol-phase characterization as listed in Table 8 and included, among other instruments, highly speciated VOC measurements with a Vocus PTR-MS instrument and aerosol composition with an aerosol mass spectrometer (AMS) operated with or without soot-particle mode. Aerodyne Research, Inc. trace gas monitors (using tunable infrared laser differential absorption spectroscopy, TILDAS) measured select trace gases including the fire tracer hydrogen cyanide (HCN) and ethane ($C_2H_6$). The AML also hosted a number of guest instruments run by external collaborators, also listed in the table below. The goal of the AML was to link the aircraft measurements to the ground by comparing EFs, understanding smoldering versus flaming emissions in close range of the fires, measure the air quality and the nighttime exposure in smoke-filled valleys, and look at plume aging. The AML drives are shown in Figure 2 and the intercepted fires are included in Table 2. The specific drive tracks of the AML for the western wildfires are shown in Figure S6 in Supporting Information S1.

The AML had the opportunity to measure smoke filled valleys, measured very close to the 204 Cow Fire, and intercepted smoke from a prescribed fire close to McCall, ID (Figures 6–10).

In 2019, the Nethker fire, which burned throughout the deployment, provided numerous close and longer-range mobile sampling opportunities, an investigation of VOC EFs with the Vocus PTR-MS and an investigation of smoke photochemistry with an onboard reaction chamber (potential aerosol mass). Excursions to the 204 Cow and Castle/Ikes fires measured smoke accumulation and ventilation in smoke-filled valleys. A small, prescribed burn near McCall, ID provided an opportunity to measure plume aging by intercepting the plume at three different distances from the fire with a clear change in aerosol oxidation state observed. The ground site also observed this prescribed burn.
<figure><img src="image_6.png" /><figcaption>**Figure 3.** Nighttime processing of a smoke plume from the 204 Cow Fire on 28 August 2019 observed by the NOAA Chem Twin Otter during FIREX-AQ. (top) The flight track color coded by CO. (bottom) CO correlation with $O_3$. (right) Time series of the $NO_3$ production rate, $NO_2$, and $O_3$.</figcaption></figure>

### 2.4.2. Aerodyne Mobile Laboratory

The AML operated out of McCall, ID (the location of a ground site as described below), during FIREX-AQ from 9 to 28 August 2019 and during WE-CAN from 11 to 28 August 2018. The AML was well-equipped for detailed gas- and aerosol-phase characterization as listed in Table 8 and included, among other instruments, highly speciated VOC measurements with a Vocus PTR-MS instrument and aerosol composition with an aerosol mass spectrometer (AMS) operated with or without soot-particle mode. Aerodyne Research, Inc. trace gas monitors (using tunable infrared laser differential absorption spectroscopy, TILDAS) measured select trace gases including the fire tracer hydrogen cyanide (HCN) and ethane ($C_2H_6$). The AML also hosted a number of guest instruments run by external collaborators, also listed in the table below. The goal of the AML was to link the aircraft measurements to the ground by comparing EFs, understanding smoldering versus flaming emissions in close range of the fires, measure the air quality and the nighttime exposure in smoke-filled valleys, and look at plume aging. The AML drives are shown in Figure 2 and the intercepted fires are included in Table 2. The specific drive tracks of the AML for the western wildfires are shown in Figure S6 in Supporting Information S1.

The AML had the opportunity to measure smoke filled valleys, measured very close to the 204 Cow Fire, and intercepted smoke from a prescribed fire close to McCall, ID (Figures 6–10).

In 2019, the Nethker fire, which burned throughout the deployment, provided numerous close and longer-range mobile sampling opportunities, an investigation of VOC EFs with the Vocus PTR-MS and an investigation of smoke photochemistry with an onboard reaction chamber (potential aerosol mass). Excursions to the 204 Cow and Castle/Ikes fires measured smoke accumulation and ventilation in smoke-filled valleys. A small, prescribed burn near McCall, ID provided an opportunity to measure plume aging by intercepting the plume at three different distances from the fire with a clear change in aerosol oxidation state observed. The ground site also observed this prescribed burn.
<table><caption>**Table 4**
Payload of the NOAA Chem Twin Otter for FIREX-AQ</caption><thead><tr><th>Parameters measured</th><th>Technique</th><th>Frequency (Hz)</th><th>Investigator</th><th>Institution</th><th>References</th></tr></thead><tbody><tr><td colspan="6"><strong>Gas phase measurements</strong></td></tr><tr><td>O<sub>3</sub>, NO, NO<sub>2</sub></td><td>Chemiluminescence</td><td>1</td><td>Andrew Weinheimer</td><td>NCAR ACOM</td><td>Ridley et al. (1992)</td></tr><tr><td>CO, CO<sub>2</sub>, CH<sub>4</sub>, H<sub>2</sub>O</td><td>Cavity ring-down spectroscopy</td><td>1</td><td>Michael Robinson</td><td>NOAA CSL</td><td>Crosson (2008), Karion et al. (2013)</td></tr><tr><td>Selected acids (HNO<sub>3</sub>, HONO, organics), acid gases (N<sub>2</sub>O<sub>5</sub>, CINO<sub>2</sub>), oxygenated organics, organic nitrates, and halogens</td><td>Iodide TOF-CIMS</td><td>1</td><td>Joel Thornton</td><td>University of Washington</td><td>Lee et al. (2014)</td></tr><tr><td>Speciated VOCs</td><td>GC × GC TOF-MS</td><td>Variable; discrete samples</td><td>Kelley Barsanti</td><td>UC Riverside</td><td>Pankow et al. (2012)</td></tr><tr><td colspan="6"><strong>Aerosol measurements</strong></td></tr><tr><td>Submicron aerosol composition</td><td>HR-TOF-AMS</td><td>1</td><td>Ann Middlebrook</td><td>NOAA CSL</td><td>DeCarlo et al. (2006)</td></tr><tr><td>Water-soluble organic carbon concentration and BrC absorption</td><td>BrC-PILS</td><td>0.25</td><td>Rebecca Washenfelder</td><td>NOAA CSL</td><td>Zeng et al. (2021)</td></tr><tr><td>Aerosol absorption</td><td>Continuous light absorption photometer</td><td>1</td><td>Ale Franchin</td><td>NOAA CSL</td><td>Ogren et al. (2017)</td></tr><tr><td>Submicron particle size distribution</td><td>UHSAS optical particle counter</td><td>1</td><td>Ale Franchin</td><td>NOAA CSL</td><td>Kupc et al. (2018)</td></tr><tr><td>Soluble ions, absorption</td><td>Ion chromatography, size-exclusion chromatography with UV/visible spectroscopy</td><td>Variable; discrete samples</td><td>Cora Young</td><td>York University</td><td>Di Lorenzo et al. (2017)</td></tr><tr><td>Elemental analysis</td><td>XRF, others</td><td>1 sample/4 min</td><td>Alex Laskin</td><td>Purdue University</td><td>Laskin et al. (2003)</td></tr><tr><td colspan="6"><strong>Radiation and Meteorological measurements</strong></td></tr><tr><td>NO<sub>2</sub> photolysis frequency</td><td>Filter radiometers</td><td>1</td><td>Michael Robinson</td><td>NOAA CSL</td><td>Junkermann et al. (1989)</td></tr><tr><td>Meteorological and navigation parameters</td><td>ARIM200</td><td>1</td><td>Michael Robinson</td><td>NOAA CSL</td><td>(Aventech Research Inc.)</td></tr></tbody></table>

The emission ratios of more than 150 species measured by the Vocus PTR, consisting of a range of VOCs and OVOCs, were calculated for all of the different fires sampled in 2019 (and during earlier work in 2018) and compared with literature values. For the Nethker fire, positive matrix factorization (PMF) was used to identify and apportion low- and high-temperature burning mass-spectral signatures. In addition, the reactivity with daytime and nighttime oxidants of several BB species measured with the Vocus PTR was investigated. Details and discussion of all of these Vocus PTR observations can be found in Majluf et al. (2022).

AML sampling of the 204 Cow fire demonstrated how mobile ground measurements can capture smoke pooling and ventilation in mountain valleys, a phenomenon the aircraft could not sample in 2019 and is even sometimes missed by ground networks. In this example, measurements are done throughout the night, close to the fire, and access mountain valleys and plateaus experiencing differing smoke impacts at different times. The 204 Cow fire occurred in the mountainous Malheur National Forest in eastern Oregon. The AML deployment started in the afternoon (local time) of 26 August 2019 and continued through the night until around 11 a.m. (local time) the next morning. Sampling was possible on a limited number of roads to the east of the fire (Figure 6). Fire fighters were actively working on containing the fire at the time of deployment.

Ground measurements help investigate the impact of boundary layer dynamics on ground-level smoke, something of particular importance for air quality and exposures in mountain valley communities. Figure 7 shows hydrogen
<table><caption>**Table 4**
Payload of the NOAA Chem Twin Otter for FIREX-AQ</caption><thead><tr><th>Parameters measured</th><th>Technique</th><th>Frequency (Hz)</th><th>Investigator</th><th>Institution</th><th>References</th></tr></thead><tbody><tr><td>Gas phase measurements</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>O<sub>3</sub>, NO, NO<sub>2</sub></td><td>Chemiluminescence</td><td>1</td><td>Andrew Weinheimer</td><td>NCAR ACOM</td><td>Ridley et al. (1992)</td></tr><tr><td>CO, CO<sub>2</sub>, CH<sub>4</sub>, H<sub>2</sub>O</td><td>Cavity ring-down spectroscopy</td><td>1</td><td>Michael Robinson</td><td>NOAA CSL</td><td>Crosson (2008), Karion et al. (2013)</td></tr><tr><td>Selected acids (HNO<sub>3</sub>, HONO, organics), acid gases (N<sub>2</sub>O<sub>5</sub>, CINO<sub>2</sub>), oxygenated organics, organic nitrates, and halogens</td><td>Iodide TOF-CIMS</td><td>1</td><td>Joel Thornton</td><td>University of Washington</td><td>Lee et al. (2014)</td></tr><tr><td>Speciated VOCs</td><td>GC × GC TOF-MS</td><td>Variable; discrete samples</td><td>Kelley Barsanti</td><td>UC Riverside</td><td>Pankow et al. (2012)</td></tr><tr><td>Aerosol measurements</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Submicron aerosol composition</td><td>HR-TOF-AMS</td><td>1</td><td>Ann Middlebrook</td><td>NOAA CSL</td><td>DeCarlo et al. (2006)</td></tr><tr><td>Water-soluble organic carbon concentration and BrC absorption</td><td>BrC-PILS</td><td>0.25</td><td>Rebecca Washenfelder</td><td>NOAA CSL</td><td>Zeng et al. (2021)</td></tr><tr><td>Aerosol absorption</td><td>Continuous light absorption photometer</td><td>1</td><td>Ale Franchin</td><td>NOAA CSL</td><td>Ogren et al. (2017)</td></tr><tr><td>Submicron particle size distribution</td><td>UHSAS optical particle counter</td><td>1</td><td>Ale Franchin</td><td>NOAA CSL</td><td>Kupc et al. (2018)</td></tr><tr><td>Soluble ions, absorption</td><td>Ion chromatography, size-exclusion chromatography with UV/visible spectroscopy</td><td>Variable; discrete samples</td><td>Cora Young</td><td>York University</td><td>Di Lorenzo et al. (2017)</td></tr><tr><td>Elemental analysis</td><td>XRF, others</td><td>1 sample/4 min</td><td>Alex Laskin</td><td>Purdue University</td><td>Laskin et al. (2003)</td></tr><tr><td>Radiation and Meteorological measurements</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>NO<sub>2</sub> photolysis frequency</td><td>Filter radiometers</td><td>1</td><td>Michael Robinson</td><td>NOAA CSL</td><td>Junkermann et al. (1989)</td></tr><tr><td>Meteorological and navigation parameters</td><td>ARIM200</td><td>1</td><td>Michael Robinson</td><td>NOAA CSL</td><td>(Aventech Research Inc.)</td></tr></tbody></table>

The emission ratios of more than 150 species measured by the Vocus PTR, consisting of a range of VOCs and OVOCs, were calculated for all of the different fires sampled in 2019 (and during earlier work in 2018) and compared with literature values. For the Nethker fire, positive matrix factorization (PMF) was used to identify and apportion low- and high-temperature burning mass-spectral signatures. In addition, the reactivity with daytime and nighttime oxidants of several BB species measured with the Vocus PTR was investigated. Details and discussion of all of these Vocus PTR observations can be found in Majluf et al. (2022).

AML sampling of the 204 Cow fire demonstrated how mobile ground measurements can capture smoke pooling and ventilation in mountain valleys, a phenomenon the aircraft could not sample in 2019 and is even sometimes missed by ground networks. In this example, measurements are done throughout the night, close to the fire, and access mountain valleys and plateaus experiencing differing smoke impacts at different times. The 204 Cow fire occurred in the mountainous Malheur National Forest in eastern Oregon. The AML deployment started in the afternoon (local time) of 26 August 2019 and continued through the night until around 11 a.m. (local time) the next morning. Sampling was possible on a limited number of roads to the east of the fire (Figure 6). Fire fighters were actively working on containing the fire at the time of deployment.

Ground measurements help investigate the impact of boundary layer dynamics on ground-level smoke, something of particular importance for air quality and exposures in mountain valley communities. Figure 7 shows hydrogen
<table><caption>**Table 5**
Payload of the NASA ER-2 Aircraft for FIREX-AQ in 2019</caption><thead><tr><th>Parameters measured</th><th>Technique</th><th>Nominal resolution</th><th>PI-name</th><th>Institution</th><th>References</th></tr></thead><tbody><tr><td>Aerosol and cloud properties, (research: aerosol plume height)</td><td>AirMSPI-1 (Multiangle Spectro-Polarimetric Imager)</td><td>10 m and 10 km swath</td><td>David Diner</td><td>NASA JPL</td><td>Diner et al. (2013), van Harten et al. (2018)</td></tr><tr><td>Vegetation types, effective fire temperature, H<sub>2</sub>O (research, AOD)</td><td>AVIRIS-C (Vis-SWIR spectrometer)</td><td>18 m and 20km swath</td><td>Rob Green</td><td>NASA JPL</td><td>Green et al. (1998)</td></tr><tr><td>Backscatter profile, depolarization ration, aerosol extinction profiles, aerosol layer type</td><td>CPL (channel backscatter lidar with polarization)</td><td>30 m vertical, 20 m horizontal</td><td>Matt McGill</td><td>NASA GSFC</td><td>McGill et al. (2002)</td></tr><tr><td>Cloud and aerosol properties</td><td>eMAS (Vis-IR scanning spectrometer)</td><td>50 m and 37 km swath</td><td>Rob Levy</td><td>NASA GSFC</td><td>King et al. (1996)</td></tr><tr><td>NO<sub>2</sub>, HCHO, SO<sub>2</sub>, CHOCHO, O<sub>3</sub></td><td>GCAS (UV-Vis-NIR spectrometer)</td><td>500 m and 16 km swath</td><td>Scott Janz</td><td>NASA GSFC</td><td>Kowalewski &amp; Janz (2014)</td></tr><tr><td>Atmospheric thermodynamic profiles; CO, O<sub>3</sub> profiles</td><td>NAST-I (IR scanning interferometer)</td><td>2,600 m and 40 km swath</td><td>Allen Larar</td><td>NASA LaRC</td><td>Zhou et al. (2002, 2005)</td></tr><tr><td>Atmospheric thermodynamic profiles; Research (CO<sub>2</sub>, O<sub>3</sub>, CO, N<sub>2</sub>O, CH<sub>4</sub>, SO<sub>2</sub> profiles)</td><td>S-HIS (IR scanning interferometer)</td><td>2,000 m and 40 km swath</td><td>Joe Taylor</td><td>U. Wisconsin-SSEC</td><td>McCourt et al. (2004), Taylor et al. (2005)</td></tr></tbody></table>

cyanide (HCN) measurements as a function of time along with AML elevation. Acetonitrile (formally C<sub>3</sub>H<sub>4</sub>N<sup>+</sup>, as quantified by the Vocus PTR-ToF) and BC (quantified by the SP-AMS) are also shown. These measurements were conducted along repeated transects and stationary locations on the set of roads shown in Figure 6. Fire tracers were generally at low concentrations during the first two thirds of the deployment. During the last one third of the deployment, HCN and other fire tracers increased rapidly. Then about 2 hr after sunrise, all fire tracers decreased to almost background levels. We attribute this to the dynamics of the atmosphere. At night, the boundary layer height decreases; with a strong inversion layer, all fire tracers are “trapped” in a shallow layer above ground. About 2 hr after sunrise, all fire tracer concentrations decreased rapidly. This was the case even when the AML drove through the eastern part of the fire-impacted area (roads closed during the night). We attribute this to rapid airmass lofting with convection during the day.

<figure><img src="image_7.png" /><figcaption>**Figure 4.** Overlay of the eMAS AOD data on top of the MODIS AOD retrieval for the flight of the NASA ER-2 over the Williams Flats fire on 06 August 2019.</figcaption></figure>
<table><caption>**Table 5**
Payload of the NASA ER-2 Aircraft for FIREX-AQ in 2019</caption><thead><tr><th>Parameters measured</th><th>Technique</th><th>Nominal resolution</th><th>PI-name</th><th>Institution</th><th>References</th></tr></thead><tbody><tr><td>Aerosol and cloud properties, (research: aerosol plume height)</td><td>AirMSPI-1 (Multiangle Spectro-Polarimetric Imager)</td><td>10 m and 10 km swath</td><td>David Diner</td><td>NASA JPL</td><td>Diner et al. (2013), van Harten et al. (2018)</td></tr><tr><td>Vegetation types, effective fire temperature, H<sub>2</sub>O (research, AOD)</td><td>AVIRIS-C (Vis-SWIR spectrometer)</td><td>18 m and 20km swath</td><td>Rob Green</td><td>NASA JPL</td><td>Green et al. (1998)</td></tr><tr><td>Backscatter profile, depolarization ration, aerosol extinction profiles, aerosol layer type</td><td>CPL (channel backscatter lidar with polarization)</td><td>30 m vertical, 20 m horizontal</td><td>Matt McGill</td><td>NASA GSFC</td><td>McGill et al. (2002)</td></tr><tr><td>Cloud and aerosol properties</td><td>eMAS (Vis-IR scanning spectrometer)</td><td>50 m and 37 km swath</td><td>Rob Levy</td><td>NASA GSFC</td><td>King et al. (1996)</td></tr><tr><td>NO<sub>2</sub>, HCHO, SO<sub>2</sub>, CHOCHO, O<sub>3</sub></td><td>GCAS (UV-Vis-NIR spectrometer)</td><td>500 m and 16 km swath</td><td>Scott Janz</td><td>NASA GSFC</td><td>Kowalewski &amp; Janz (2014)</td></tr><tr><td>Atmospheric thermodynamic profiles; CO, O<sub>3</sub> profiles</td><td>NAST-I (IR scanning interferometer)</td><td>2,600 m and 40 km swath</td><td>Allen Larar</td><td>NASA LaRC</td><td>Zhou et al. (2002, 2005)</td></tr><tr><td>Atmospheric thermodynamic profiles; Research (CO<sub>2</sub>, O<sub>3</sub>, CO, N<sub>2</sub>O, CH<sub>4</sub>, SO<sub>2</sub> profiles)</td><td>S-HIS (IR scanning interferometer)</td><td>2,000 m and 40 km swath</td><td>Joe Taylor</td><td>U. Wisconsin-SSEC</td><td>McCourt et al. (2004), Taylor et al. (2005)</td></tr></tbody></table>

cyanide (HCN) measurements as a function of time along with AML elevation. Acetonitrile (formally C<sub>3</sub>H<sub>4</sub>N<sup>+</sup>, as quantified by the Vocus PTR-ToF) and BC (quantified by the SP-AMS) are also shown. These measurements were conducted along repeated transects and stationary locations on the set of roads shown in Figure 6. Fire tracers were generally at low concentrations during the first two thirds of the deployment. During the last one third of the deployment, HCN and other fire tracers increased rapidly. Then about 2 hr after sunrise, all fire tracers decreased to almost background levels. We attribute this to the dynamics of the atmosphere. At night, the boundary layer height decreases; with a strong inversion layer, all fire tracers are “trapped” in a shallow layer above ground. About 2 hr after sunrise, all fire tracer concentrations decreased rapidly. This was the case even when the AML drove through the eastern part of the fire-impacted area (roads closed during the night). We attribute this to rapid airmass lofting with convection during the day.

<figure><img src="image_7.png" /><figcaption>**Figure 4.** Overlay of the eMAS AOD data on top of the MODIS AOD retrieval for the flight of the NASA ER-2 over the Williams Flats fire on 06 August 2019.</figcaption></figure>
<table><caption>**Table 6**
Payload of the MET-TO for FIREX-AQ</caption><thead><tr><td>Parameters measured</td><td>Technique</td><td>Frequency (Hz)</td><td>PI-name</td><td>Institution</td><td>References</td></tr></thead><tbody><tr><td>Line-of-sight wind speed and aerosol backscatter intensity (ABI)</td><td>Micropulse Doppler lidar</td><td>0.15–1</td><td>Alan Brewer</td><td>NOAA CSL</td><td>Schroeder et al. (2020)</td></tr><tr><td>Fire radiative power</td><td>Scanning Radiometers Imager FLIR Duo R</td><td></td><td>Ru-Shan Gao</td><td>NOAA CSL</td><td></td></tr></tbody></table>

These measurements also show the effects of topography and smoke pooling. At the 204 Cow fire, strong down-hill outflow of fire tracers was observed through relatively narrow valley structures, as indicated by the blue arrows in Figure 6. The AML drove through the area where the outflow joined the main valley, and high fire tracer concentrations were measured. The AML could not access the road that followed the main valley floor, but above the valley floor, fire tracer concentrations were low to moderate. This suggests that the main outflow happened only along the lowest altitudes of the valley. Conversely, in northern Arizona, the AML observed very little smoke outflow on the lee side of the plateau where the Castle and Ikes fires burned, and into the deep valley structures of the upper Colorado River. A major difference between the 204 Cow and Castle/Ikes fires is in the topographical scales: shallow valleys funneling smoke, versus a much larger downwind elevation drop in Arizona.

On 27 August 2019, a prescribed burn was conducted east of New Meadows, Idaho. With wind flow out of the WSW, the prescribed fire plume was sampled at various points by the AML. The plume was sampled initially on Idaho State Highway 55 approximately three miles west of McCall and then later sampled at two additional locations on the west and east sides of Payette Lake. Figure 8 depicts HCN associated with this BB plume. The

<figure><img src="image_8.png" /><figcaption>**Figure 5.** Range corrected aerosol backscatter intensity curtain and horizontal wind profile in the foreground from the Goose Fire measured on 5 August 2019 by the NOAA Met-TO with the Doppler Lidar. The active fire location is shown in orange on the surface map and the vertical ticks on the Y axes are every 500 m. The view in this image is from the ENE and the curtain data runs roughly SW to NE (going from left to right).</figcaption></figure>
<table><caption>**Table 6**
Payload of the MET-TO for FIREX-AQ</caption><thead><tr><td>Parameters measured</td><td>Technique</td><td>Frequency (Hz)</td><td>PI-name</td><td>Institution</td><td>References</td></tr></thead><tbody><tr><td>Line-of-sight wind speed and aerosol backscatter intensity (ABI)</td><td>Micropulse Doppler lidar</td><td>0.15–1</td><td>Alan Brewer</td><td>NOAA CSL</td><td>Schroeder et al. (2020)</td></tr><tr><td>Fire radiative power</td><td>Scanning Radiometers Imager FLIR Duo R</td><td></td><td>Ru-Shan Gao</td><td>NOAA CSL</td><td></td></tr></tbody></table>

These measurements also show the effects of topography and smoke pooling. At the 204 Cow fire, strong downhill outflow of fire tracers was observed through relatively narrow valley structures, as indicated by the blue arrows in Figure 6. The AML drove through the area where the outflow joined the main valley, and high fire tracer concentrations were measured. The AML could not access the road that followed the main valley floor, but above the valley floor, fire tracer concentrations were low to moderate. This suggests that the main outflow happened only along the lowest altitudes of the valley. Conversely, in northern Arizona, the AML observed very little smoke outflow on the lee side of the plateau where the Castle and Ikes fires burned, and into the deep valley structures of the upper Colorado River. A major difference between the 204 Cow and Castle/Ikes fires is in the topographical scales: shallow valleys funneling smoke, versus a much larger downwind elevation drop in Arizona.

On 27 August 2019, a prescribed burn was conducted east of New Meadows, Idaho. With wind flow out of the WSW, the prescribed fire plume was sampled at various points by the AML. The plume was sampled initially on Idaho State Highway 55 approximately three miles west of McCall and then later sampled at two additional locations on the west and east sides of Payette Lake. Figure 8 depicts HCN associated with this BB plume. The

<figure><img src="image_8.png" /><figcaption>**Figure 5.** Range corrected aerosol backscatter intensity curtain and horizontal wind profile in the foreground from the Goose Fire measured on 5 August 2019 by the NOAA Met-TO with the Doppler Lidar. The active fire location is shown in orange on the surface map and the vertical ticks on the Y axes are every 500 m. The view in this image is from the ENE and the curtain data runs roughly SW to NE (going from left to right).</figcaption></figure>
<table><caption>**Table 7**
Payload of the NASA MACH-2 for FIREX-AQ</caption><thead><tr><th>Parameter measured</th><th>Technique</th><th>Frequency (s)</th><th>Investigator</th><th>Institution</th><th>References</th></tr></thead><tbody><tr><td colspan="6"><strong>Aerosol measurements</strong></td></tr><tr><td>Particle number density</td><td>TSI 3775</td><td>1</td><td>Bruce<br>Anderson</td><td>NASA LaRC</td><td>TSI_3775</td></tr><tr><td rowspan="3">Aerosol size distribution</td><td>TSI SMPS w/3772 CPC</td><td>60</td><td>Bruce<br>Anderson</td><td>NASA LaRC</td><td>TSI_SMPS</td></tr><tr><td>Teledyne T640</td><td>10</td><td></td><td></td><td>Teledyne_T640</td></tr><tr><td>TSI APS</td><td>1</td><td></td><td></td><td>TSI_3321</td></tr><tr><td>TSI Optical Particle Spectrometer</td><td></td><td>1</td><td></td><td></td><td>TSI_3330</td></tr><tr><td>3-λ scattering</td><td>Air Photon</td><td>5</td><td>Bruce<br>Anderson</td><td></td><td>Air_Photon_IN101</td></tr><tr><td>3-λ extinction</td><td>3-wavelength CAPS</td><td>5</td><td>Bruce<br>Anderson</td><td></td><td>Aerodyne_CAPS</td></tr><tr><td>Hyperspectral aerosol absorption<br>photometer</td><td>Custom</td><td>Variable</td><td>Bruce<br>Anderson</td><td></td><td>Jordan<br>et al. (2022)</td></tr><tr><td>Spectral aerosol extinction,<br>absorption, BrC absorption</td><td>Hyperspectral Extinctiometer (SpEX)</td><td>240</td><td>Carolyn<br>Jordan</td><td>NIA/LaRC</td><td>Jordan<br>et al. (2015,<br>2021)</td></tr><tr><td>3-λ absorption photometer</td><td>TAP, PSAP</td><td>5</td><td>Bruce<br>Anderson</td><td></td><td>Brechtel_TAP</td></tr><tr><td>Aerosol ionic composition</td><td>PTFE filters + IC</td><td>Intermittent</td><td>Bruce<br>Anderson</td><td></td><td>—</td></tr><tr><td>Aerosol organics</td><td>PTFE filters + Spectroscopy</td><td>Intermittent</td><td>Bruce<br>Anderson</td><td></td><td>—</td></tr><tr><td>EC/OC, metals</td><td>quartz filters; sunset labs, ICP</td><td>Intermittent</td><td>Bruce<br>Anderson</td><td></td><td>OC/<br>EC_Analyzer</td></tr><tr><td>PM<sub>2.5</sub></td><td>MetOneE-BAM</td><td>3,600</td><td>Bruce<br>Anderson</td><td></td><td>MetOne_E-BAM</td></tr><tr><td>PM<sub>2.5</sub>, PM<sub>10</sub></td><td>Teledyne T640</td><td>60</td><td>Bruce<br>Anderson</td><td></td><td>Teledyne_T640</td></tr><tr><td>Cloud/aerosol profiles</td><td>Vaisala CL5100 Ceiliometer</td><td>60</td><td>Rich Moore</td><td></td><td>Vaisala_CL51</td></tr><tr><td colspan="6"><strong>Gas phase measurements</strong></td></tr><tr><td>CO, CO<sub>2</sub>, H<sub>2</sub>O</td><td>LGR iCOSSpectrometer</td><td>1</td><td>Bruce<br>Anderson</td><td>NASA LaRC</td><td>LGR_CO/CO2</td></tr><tr><td>CO<sub>2</sub>, H<sub>2</sub>O</td><td>Licor 840 NDIR</td><td>1</td><td></td><td></td><td>LI-840</td></tr><tr><td>NO<sub>x</sub>, NO<sub>2</sub></td><td>LGR NO<sub>2</sub> Spectrometer</td><td>1</td><td></td><td></td><td>LGR_NO2</td></tr><tr><td>O<sub>3</sub></td><td>Thermo scientific</td><td>1</td><td></td><td></td><td>Thermo_<br>Scientific</td></tr><tr><td>HONO, HNO<sub>3</sub></td><td>Mist Chamber/IC</td><td>300</td><td>Jack Dibb</td><td>UNH</td><td>Scheuer<br>et al. (2010)</td></tr><tr><td>N and O isotopes in NO<sub>x</sub>, NO<sub>2</sub>,<br>HONO, nitrate and ammonium</td><td>Impinger for NO<sub>x</sub>, denuders for NO<sub>2</sub> and HONO,<br>and filters for nitrate and ammonium</td><td>variable (hours)</td><td>Meredith<br>Hastings</td><td>Brown<br>University</td><td>Chai et al. (2021)</td></tr><tr><td colspan="6"><strong>Meteorological measurements</strong></td></tr><tr><td>Winds, T, RH, and navigation<br>parameters</td><td>AirMar 200WX</td><td>1</td><td>Bruce<br>Anderson</td><td></td><td>AirMar_200WX</td></tr></tbody></table>

orientation of this road network perpendicular to the transport of the plume allows for investigation of plume aging with transport.

The SP-AMS instrument showed increases in organic and BC loading associated with this plume. As a BB plume ages, we expect oxidation to occur. Figure 9 depicts the H:C and O:C ratios of fit organic species measured with the SP-AMS. As transects move further downwind relative to the source, the O:C state of the organic aerosol on average increases. Each dot in Figure 10 represents one 20-s sampling point.
<table><caption>**Table 7**
Payload of the NASA MACH-2 for FIREX-AQ</caption><thead><tr><th>Parameter measured</th><th>Technique</th><th>Frequency (s)</th><th>Investigator</th><th>Institution</th><th>References</th></tr></thead><tbody><tr><td colspan="6"><strong>Aerosol measurements</strong></td></tr><tr><td>Particle number density</td><td>TSI 3775</td><td>1</td><td>Bruce<br>Anderson</td><td>NASA LaRC</td><td>TSI_3775</td></tr><tr><td rowspan="3">Aerosol size distribution</td><td>TSI SMPS w/3772 CPC</td><td>60</td><td>Bruce<br>Anderson</td><td>NASA LaRC</td><td>TSI_SMPS</td></tr><tr><td>Teledyne T640</td><td>10</td><td></td><td></td><td>Teledyne_T640</td></tr><tr><td>TSI APS</td><td>1</td><td></td><td></td><td>TSI_3321</td></tr><tr><td>TSI Optical Particle Spectrometer</td><td></td><td>1</td><td></td><td></td><td>TSI_3330</td></tr><tr><td>3-λ scattering</td><td>Air Photon</td><td>5</td><td>Bruce<br>Anderson</td><td></td><td>Air_Photon_IN101</td></tr><tr><td>3-λ extinction</td><td>3-wavelength CAPS</td><td>5</td><td>Bruce<br>Anderson</td><td></td><td>Aerodyne_CAPS</td></tr><tr><td>Hyperspectral aerosol absorption<br>photometer</td><td>Custom</td><td>Variable</td><td>Bruce<br>Anderson</td><td></td><td>Jordan<br>et al. (2022)</td></tr><tr><td>Spectral aerosol extinction,<br>absorption, BrC absorption</td><td>Hyperspectral Extinctiometer (SpEX)</td><td>240</td><td>Carolyn<br>Jordan</td><td>NIA/LaRC</td><td>Jordan<br>et al. (2015,<br>2021)</td></tr><tr><td>3-λ absorption photometer</td><td>TAP, PSAP</td><td>5</td><td>Bruce<br>Anderson</td><td></td><td>Brechtel_TAP</td></tr><tr><td>Aerosol ionic composition</td><td>PTFE filters + IC</td><td>Intermittent</td><td>Bruce<br>Anderson</td><td></td><td>—</td></tr><tr><td>Aerosol organics</td><td>PTFE filters + Spectroscopy</td><td>Intermittent</td><td>Bruce<br>Anderson</td><td></td><td>—</td></tr><tr><td>EC/OC, metals</td><td>quartz filters; sunset labs, ICP</td><td>Intermittent</td><td>Bruce<br>Anderson</td><td></td><td>OC/<br>EC_Analyzer</td></tr><tr><td>PM<sub>2.5</sub></td><td>MetOneE-BAM</td><td>3,600</td><td>Bruce<br>Anderson</td><td></td><td>MetOne_E-BAM</td></tr><tr><td>PM<sub>2.5</sub>, PM<sub>10</sub></td><td>Teledyne T640</td><td>60</td><td>Bruce<br>Anderson</td><td></td><td>Teledyne_T640</td></tr><tr><td>Cloud/aerosol profiles</td><td>Vaisala CL5100 Ceiliometer</td><td>60</td><td>Rich Moore</td><td></td><td>Vaisala_CL51</td></tr><tr><td colspan="6"><strong>Gas phase measurements</strong></td></tr><tr><td>CO, CO<sub>2</sub>, H<sub>2</sub>O</td><td>LGR iCOSSpectrometer</td><td>1</td><td>Bruce<br>Anderson</td><td>NASA LaRC</td><td>LGR_CO/CO2</td></tr><tr><td>CO<sub>2</sub>, H<sub>2</sub>O</td><td>Licor 840 NDIR</td><td>1</td><td></td><td></td><td>LI-840</td></tr><tr><td>NO<sub>x</sub>, NO<sub>2</sub></td><td>LGR NO<sub>2</sub> Spectrometer</td><td>1</td><td></td><td></td><td>LGR_NO2</td></tr><tr><td>O<sub>3</sub></td><td>Thermo scientific</td><td>1</td><td></td><td></td><td>Thermo_<br>Scientific</td></tr><tr><td>HONO, HNO<sub>3</sub></td><td>Mist Chamber/IC</td><td>300</td><td>Jack Dibb</td><td>UNH</td><td>Scheuer<br>et al. (2010)</td></tr><tr><td>N and O isotopes in NO<sub>x</sub>, NO<sub>2</sub>,<br>HONO, nitrate and ammonium</td><td>Impinger for NO<sub>x</sub>, denuders for NO<sub>2</sub> and HONO,<br>and filters for nitrate and ammonium</td><td>variable (hours)</td><td>Meredith<br>Hastings</td><td>Brown<br>University</td><td>Chai et al. (2021)</td></tr><tr><td colspan="6"><strong>Meteorological measurements</strong></td></tr><tr><td>Winds, T, RH, and navigation<br>parameters</td><td>AirMar 200WX</td><td>1</td><td>Bruce<br>Anderson</td><td></td><td>AirMar_200WX</td></tr></tbody></table>

orientation of this road network perpendicular to the transport of the plume allows for investigation of plume aging with transport.

The SP-AMS instrument showed increases in organic and BC loading associated with this plume. As a BB plume ages, we expect oxidation to occur. Figure 9 depicts the H:C and O:C ratios of fit organic species measured with the SP-AMS. As transects move further downwind relative to the source, the O:C state of the organic aerosol on average increases. Each dot in Figure 10 represents one 20-s sampling point.
<table><caption>**Table 8**
Payload of the Aerodyne Mobile Laboratory (AML) for FIREX-AQ in 2019</caption><thead><tr><th>Species measured</th><th>Technique</th><th>Freq. (Hz)</th><th>Investigator</th><th>Institution</th><th>References</th></tr></thead><tbody><tr><td>CO, N<sub>2</sub>O, H<sub>2</sub>O; C<sub>2</sub>H<sub>6</sub>, CH<sub>4</sub>; HCN, C<sub>2</sub>H<sub>2</sub>, HCHO, HCOOH, NO, NO<sub>2</sub>, NH<sub>3</sub></td><td>multiple Tunable Infrared Laser Direct Absorption Spectroscopy (TILDAS)</td><td>1</td><td>Tara Yacovitch, Christoph Dyroff; Scott Herndon; J. Rob Roscioli</td><td>Aerodyne research Inc. (ARI)</td><td>McManus et al. (2015), Yacovitch et al. (2014)</td></tr><tr><td>CO<sub>2</sub>, H<sub>2</sub>O</td><td>Non-dispersive infrared</td><td>1</td><td>Tara Yacovitch</td><td>ARI</td><td>LiCOR</td></tr><tr><td>O<sub>3</sub></td><td>UV absorption</td><td>1</td><td>Tara Yacovitch</td><td>ARI</td><td>2B Tech</td></tr><tr><td>oxygenated and nitrogen-containing VOCs</td><td>Vocus-PTR-MS</td><td>1</td><td>Francesca Majluf</td><td>ARI</td><td>Krechmer et al. (2018)</td></tr><tr><td>particulate matter size and composition</td><td>High-resolution aerosol mass spectrometer (AMS, SP-AMS)</td><td>1</td><td>Ed Fortner</td><td>ARI</td><td>Jayne et al. (2000), Onasch et al. (2012)</td></tr><tr><td>BC size distribution</td><td>Single Particle Soot Photometer (SP2)</td><td>1–10</td><td>Tim Onasch</td><td>ARI</td><td>Sedlacek et al. (2018)</td></tr><tr><td>particle count</td><td>Condensation Particle Counter (CPC)</td><td>1</td><td>Ed Fortner</td><td>ARI</td><td></td></tr><tr><td>GPS and meteorology</td><td>GPS compass, RMYoung and Airmar anemometers</td><td>1–10</td><td>Tara Yacovitch</td><td>ARI</td><td></td></tr><tr><td>NO<sub>2</sub> photolysis frequency</td><td>Filter radiometer</td><td>1</td><td>Samuel Hall</td><td>NCAR ACOM</td><td>Metcon Inc.</td></tr><tr><td>OC, EC, Levoglucosan, dehydroabietic acid</td><td>Filter samples with GCxGC-ToF-MS and Sunset OC/EC analyzer</td><td>30–60 min</td><td>Allen Goldstein</td><td>UC Berkeley</td><td>Jen et al. (2019), Liang et al. (2022)</td></tr><tr><td>Aerosol absorption and extinction at 488 and 561 nm</td><td>Multiwavelength Integrated Photoacoustic spectrometer and Nepehelometer (MIPN)</td><td>2</td><td>Rajan Chakrabarty</td><td>Washington Uni. in St. Louis</td><td>Sumlin et al. (2021)</td></tr><tr><td>Single-particle optical properties and composition</td><td>Electron Energy-Loss Spectroscopy (EELS)</td><td>10/fire</td><td>Rohan Mishra, Rajan Chakrabarty</td><td>Washington Uni. in St. Louis</td><td>Zhu et al. (2014)</td></tr></tbody></table>

<figure><img src="image_9.png" /><figcaption>**Figure 6.** AML deployment at the 204 Cow fire on 26 August 2019. The HCN data are color (and size) coded in bins of 10 ppb from 0–10 ppb (green) to 60–70 ppb (red). The red area indicates the boundary of the fire during the month of August (VIIRS data (University of Maryland, 2020)). The red shaded heatmap shows fire observations as detected from satellite for the same time period. The blue arrows indicate outflow paths of fire tracers downhill through narrow valleys during the second half of the night. Topographical maps from Google.com.</figcaption></figure>

### 2.4.3. AERONET and DRAGON

In the northwestern U.S. and southwestern Canada, 14 regional AErosol RObotic NETwork (AERONET) sites were located in the FIREX-AQ region and sun/moon/sky photometers performed measurements for aerosol assessment. These permanent AERONET sites were augmented with three Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) located in Missoula, Taylor Ranch, and McCall (locations shown in Figure 3) and two mobile deployed units (Holben et al., 2018). Each DRAGON provided enhanced coverage with temporarily deployed sunphotometers. The goals were to capture aerosol variability, specifically smoke aerosol at varying distances from source regions in complex mountainous terrain and to develop a geo-referenced database that will facilitate comparison and validation investigations with in-situ and remote sensing platforms from FIREX-AQ. The regional DRAGON and AERONET sites operated 22 July–6 September with a nighttime focus 7–21 August for FIREX-AQ.

The payload of the DRAGONs is listed in Table 9 with a Sun-tracking CIMEL CE318T to measure AOD and volume size distribution, where the retrieval algorithms had to be adjusted for mobile instrument data (Giles et al., 2019; Sinyuk et al., 2020). Further the PLASMA (for Photomètre Léger Aéroporté pour la Surveillance des Masses d'Air) sun photometer provided rapid observations of the Sun to provide AOD every 10 s (Karol et al., 2013). Less frequent measurements using Microtops II and Calitoo hand-held sun
<table><caption>**Table 8**
Payload of the Aerodyne Mobile Laboratory (AML) for FIREX-AQ in 2019</caption><thead><tr><th>Species measured</th><th>Technique</th><th>Freq. (Hz)</th><th>Investigator</th><th>Institution</th><th>References</th></tr></thead><tbody><tr><td>CO, N<sub>2</sub>O, H<sub>2</sub>O; C<sub>2</sub>H<sub>6</sub>, CH<sub>4</sub>; HCN, C<sub>2</sub>H<sub>2</sub>, HCHO, HCOOH, NO, NO<sub>2</sub>, NH<sub>3</sub></td><td>multiple Tunable Infrared Laser Direct Absorption Spectroscopy (TILDAS)</td><td>1</td><td>Tara Yacovitch, Christoph Dyroff; Scott Herndon; J. Rob Roscioli</td><td>Aerodyne research Inc. (ARI)</td><td>McManus et al. (2015), Yacovitch et al. (2014)</td></tr><tr><td>CO<sub>2</sub>, H<sub>2</sub>O</td><td>Non-dispersive infrared</td><td>1</td><td>Tara Yacovitch</td><td>ARI</td><td>LiCOR</td></tr><tr><td>O<sub>3</sub></td><td>UV absorption</td><td>1</td><td>Tara Yacovitch</td><td>ARI</td><td>2B Tech</td></tr><tr><td>oxygenated and nitrogen-containing VOCs</td><td>Vocus-PTR-MS</td><td>1</td><td>Francesca Majluf</td><td>ARI</td><td>Krechmer et al. (2018)</td></tr><tr><td>particulate matter size and composition</td><td>High-resolution aerosol mass spectrometer (AMS, SP-AMS)</td><td>1</td><td>Ed Fortner</td><td>ARI</td><td>Jayne et al. (2000), Onasch et al. (2012)</td></tr><tr><td>BC size distribution</td><td>Single Particle Soot Photometer (SP2)</td><td>1–10</td><td>Tim Onasch</td><td>ARI</td><td>Sedlacek et al. (2018)</td></tr><tr><td>particle count</td><td>Condensation Particle Counter (CPC)</td><td>1</td><td>Ed Fortner</td><td>ARI</td><td></td></tr><tr><td>GPS and meteorology</td><td>GPS compass, RMYoung and Airmar anemometers</td><td>1–10</td><td>Tara Yacovitch</td><td>ARI</td><td></td></tr><tr><td>NO<sub>2</sub> photolysis frequency</td><td>Filter radiometer</td><td>1</td><td>Samuel Hall</td><td>NCAR ACOM</td><td>Metcon Inc.</td></tr><tr><td>OC, EC, Levoglucosan, dehydroabietic acid</td><td>Filter samples with GCxGC-ToF-MS and Sunset OC/EC analyzer</td><td>30–60 min</td><td>Allen Goldstein</td><td>UC Berkeley</td><td>Jen et al. (2019), Liang et al. (2022)</td></tr><tr><td>Aerosol absorption and extinction at 488 and 561 nm</td><td>Multiwavelength Integrated Photoacoustic spectrometer and Nepehelometer (MIPN)</td><td>2</td><td>Rajan Chakrabarty</td><td>Washington Uni. in St. Louis</td><td>Sumlin et al. (2021)</td></tr><tr><td>Single-particle optical properties and composition</td><td>Electron Energy-Loss Spectroscopy (EELS)</td><td>10/fire</td><td>Rohan Mishra, Rajan Chakrabarty</td><td>Washington Uni. in St. Louis</td><td>Zhu et al. (2014)</td></tr></tbody></table>

<figure><img src="image_9.png" /><figcaption>**Figure 6.** AML deployment at the 204 Cow fire on 26 August 2019. The HCN data are color (and size) coded in bins of 10 ppb from 0–10 ppb (green) to 60–70 ppb (red). The red area indicates the boundary of the fire during the month of August (VIIRS data (University of Maryland, 2020)). The red shaded heatmap shows fire observations as detected from satellite for the same time period. The blue arrows indicate outflow paths of fire tracers downhill through narrow valleys during the second half of the night. Topographical maps from Google.com.</figcaption></figure>

### 2.4.3. AERONET and DRAGON

In the northwestern U.S. and southwestern Canada, 14 regional AErosol RObotic NETwork (AERONET) sites were located in the FIREX-AQ region and sun/moon/sky photometers performed measurements for aerosol assessment. These permanent AERONET sites were augmented with three Distributed Regional Aerosol Gridded Observation Networks (DRAGONs) located in Missoula, Taylor Ranch, and McCall (locations shown in Figure 3) and two mobile deployed units (Holben et al., 2018). Each DRAGON provided enhanced coverage with temporarily deployed sunphotometers. The goals were to capture aerosol variability, specifically smoke aerosol at varying distances from source regions in complex mountainous terrain and to develop a geo-referenced database that will facilitate comparison and validation investigations with in-situ and remote sensing platforms from FIREX-AQ. The regional DRAGON and AERONET sites operated 22 July–6 September with a nighttime focus 7–21 August for FIREX-AQ.

The payload of the DRAGONs is listed in Table 9 with a Sun-tracking CIMEL CE318T to measure AOD and volume size distribution, where the retrieval algorithms had to be adjusted for mobile instrument data (Giles et al., 2019; Sinyuk et al., 2020). Further the PLASMA (for Photomètre Léger Aéroporté pour la Surveillance des Masses d'Air) sun photometer provided rapid observations of the Sun to provide AOD every 10 s (Karol et al., 2013). Less frequent measurements using Microtops II and Calitoo hand-held sun
<figure><img src="image_10.png" /><figcaption>**Figure 7.** Time series of HCN, BC (from SP-AMS), and C<sub>3</sub>H<sub>4</sub>N<sup>+</sup> (quantified as acetonitrile) during the cow fire deployment. Note the strong increase in fire tracers in the early morning hours (Analysis and figures by Christoph Dyroff).</figcaption></figure>

photometer data were available when the CIMEL CE318T photometer was performing sky scanning measurements (Smirnov et al., 2009). Two CIMEL Lidars (CE370 and CE376 models) were available in each mobile unit to provide aerosol and cloud vertical distribution.

The fires investigated by the DRAGONs are listed in Table 2 and measurements were coordinated with other platforms for example, the DC-8 and ER-2 during Williams Flats fire observations. The DRAGON drives are shown in Figure S7 in Supporting Information S1.

As examples of the aerosol variability observed by AERONET and the DRAGONs, the decrease of AOD with distance from the Williams Flats fire and vertical variation downwind of the 204 Cow Fire are shown in Figures 10 and 11. The goal of examining aerosol variability can be viewed in Figure 10 as AOD changes with the distance to the fire source for the Williams Flats Fire from 5 to 8 August 2019, where several plume crossings were attempted up to 250 km downwind of the fire. The AOD magnitude is highly variable in the vicinity of the fire due to the significant changes in aerosol loading as the vehicles moved in and out of the smoke plume. Peaks in AOD near

120 and 185 km are due to the DRAGON Mobile Unit 2 passing through the downwind smoke plume. The Angstrom Exponent (AE) (440–870 nm) varied between 1.4 and 2.4 indicating aerosol particle sizes vary significantly in the fine mode smoke. The variation in AE stabilized around 1.8 at 100 km from the fire suggesting aging and aggregation of the smoke particles farther away from the fire source.

Figure 11 shows the Cimel CE370 micro-pulse lidar range corrected signal (RCS) measured during the 204 Cow Fire in Oregon on 26 August 2019 by DRAGON Mobile Unit 2. Vertical variation of the aerosols shows the smoke plume rising to about 3 km on the first transect while other transects farther to the east indicate smoke may have subsided near the ground into the nearby valleys (top panels). Coincident measurements from the PLASMA instrument AOD (bottom left) are interpolated to lidar wavelength at 532 nm and AE from 440 to 870 nm. Aqua MODIS true color imagery (bottom right) indicate the extent of the smoke plume at 20:15 UTC.

### 2.4.4. CARB

The CARB deployed a Mobile Measurement Platform (MMP) equipped with advanced technologies to measure gas- and particle-phase pollutants emitted from wildfires. Over the past decade, CARB's MMPs have been used to

<figure><img src="image_11.png" /><figcaption>**Figure 8.** The drive track of the AML on 27 August 2019 color and size coded by HCN.</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>**Figure 7.** Time series of HCN, BC (from SP-AMS), and C<sub>3</sub>H<sub>4</sub>N<sup>+</sup> (quantified as acetonitrile) during the cow fire deployment. Note the strong increase in fire tracers in the early morning hours (Analysis and figures by Christoph Dyroff).</figcaption></figure>

photometer data were available when the CIMEL CE318T photometer was performing sky scanning measurements (Smirnov et al., 2009). Two CIMEL Lidars (CE370 and CE376 models) were available in each mobile unit to provide aerosol and cloud vertical distribution.

The fires investigated by the DRAGONs are listed in Table 2 and measurements were coordinated with other platforms for example, the DC-8 and ER-2 during Williams Flats fire observations. The DRAGON drives are shown in Figure S7 in Supporting Information S1.

As examples of the aerosol variability observed by AERONET and the DRAGONs, the decrease of AOD with distance from the Williams Flats fire and vertical variation downwind of the 204 Cow Fire are shown in Figures 10 and 11. The goal of examining aerosol variability can be viewed in Figure 10 as AOD changes with the distance to the fire source for the Williams Flats Fire from 5 to 8 August 2019, where several plume crossings were attempted up to 250 km downwind of the fire. The AOD magnitude is highly variable in the vicinity of the fire due to the significant changes in aerosol loading as the vehicles moved in and out of the smoke plume. Peaks in AOD near

120 and 185 km are due to the DRAGON Mobile Unit 2 passing through the downwind smoke plume. The Angstrom Exponent (AE) (440–870 nm) varied between 1.4 and 2.4 indicating aerosol particle sizes vary significantly in the fine mode smoke. The variation in AE stabilized around 1.8 at 100 km from the fire suggesting aging and aggregation of the smoke particles farther away from the fire source.

Figure 11 shows the Cimel CE370 micro-pulse lidar range corrected signal (RCS) measured during the 204 Cow Fire in Oregon on 26 August 2019 by DRAGON Mobile Unit 2. Vertical variation of the aerosols shows the smoke plume rising to about 3 km on the first transect while other transects farther to the east indicate smoke may have subsided near the ground into the nearby valleys (top panels). Coincident measurements from the PLASMA instrument AOD (bottom left) are interpolated to lidar wavelength at 532 nm and AE from 440 to 870 nm. Aqua MODIS true color imagery (bottom right) indicate the extent of the smoke plume at 20:15 UTC.

### 2.4.4. CARB

The CARB deployed a Mobile Measurement Platform (MMP) equipped with advanced technologies to measure gas- and particle-phase pollutants emitted from wildfires. Over the past decade, CARB's MMPs have been used to

<figure><img src="image_11.png" /><figcaption>**Figure 8.** The drive track of the AML on 27 August 2019 color and size coded by HCN.</figcaption></figure>
<figure><img src="image_12.png" /><figcaption>**Figure 9.** Organic aerosol O:C and H:C ratios are depicted and colored by location of plume intercept by the AML (Analysis and figures by Ed Fortner).</figcaption></figure>

<figure><img src="image_13.png" /><figcaption>**Figure 10.** Mobile DRAGON showed a decrease of the AOD with increasing distance from the Williams Flats Fire from 5 to 8 August 2019. The peak at 120 km represents Mobile DRAGON Units 1 and 2 crossing the Williams Flats Fire plume near Spokane, Washington. The lower peak at 185 km represents the plume crossing of Mobile DRAGON 2 at Cour d'Alene.</figcaption></figure>

measure a variety of source emissions, study air pollution impacts on communities, and identify fugitive methane leaks throughout California. The measured EFs are used to inform the fire emission model, the First Order Fire Effects Model, used by CARB. The research advances the modeling of wildfire impacts on air quality to safeguard human health.

The payload of the MMP during FIREX-AQ is listed in Table 10, including the guest instruments from UC Berkeley and UC Riverside. CARB deployed the MMP during FIREX-AQ on 15 and 30 August 2019 to the Springs Fire and after FIREX-AQ on 1 and 4 November 2019 to the Kincade Fire in California. During each deployment, CARB staff drove the MMP in the vicinity of the wildfire to detect the wildfire smoke. Once the smoke was identified (i.e., (CO) > 500 ppb), the MMP acted as a stationary site to monitor the fire plumes. The MMP drives are shown in Figure S8 in Supporting Information S1.

The lack of fire activity in California during FIREX-AQ limited the interaction of the MMP with the rest of the FIREX-AQ platforms, but an example of the MMP measurements of the Springs Fire is shown in Figure 12, which shows an example of the evolution of the Springs Fire on 30 August 2019. During the deployment, the MMP was parked ~3 km north of the Springs Fire. The measurement can be categorized into three periods. Period 1 is characterized by fast-changing pollutant concentrations. The smoke evolved quickly as the planetary boundary layer developed during 07:00–09:00, causing the pollutant concentration to decline. The modified combustion efficiency (MCE) also decreased from ~0.95 to ~0.85. Period 2 lasted from 09:00 to 10:30. The measurement was under northwesterly wind conditions. Clean background air entrainment diluted the sampled fire plume, resulting in low pollutant concentrations. The southerly winds dominated during Period 3 (similar to Period 1). The pollutant concentrations showed multiple spikes. The MCE values were around 0.9.
<figure><img src="image_12.png" /><figcaption>**Figure 9.** Organic aerosol O:C and H:C ratios are depicted and colored by location of plume intercept by the AML (Analysis and figures by Ed Fortner).</figcaption></figure>

<figure><img src="image_13.png" /><figcaption>**Figure 10.** Mobile DRAGON showed a decrease of the AOD with increasing distance from the Williams Flats Fire from 5 to 8 August 2019. The peak at 120 km represents Mobile DRAGON Units 1 and 2 crossing the Williams Flats Fire plume near Spokane, Washington. The lower peak at 185 km represents the plume crossing of Mobile DRAGON 2 at Cour d'Alene.</figcaption></figure>

measure a variety of source emissions, study air pollution impacts on communities, and identify fugitive methane leaks throughout California. The measured EFs are used to inform the fire emission model, the First Order Fire Effects Model, used by CARB. The research advances the modeling of wildfire impacts on air quality to safeguard human health.

The payload of the MMP during FIREX-AQ is listed in Table 10, including the guest instruments from UC Berkeley and UC Riverside. CARB deployed the MMP during FIREX-AQ on 15 and 30 August 2019 to the Springs Fire and after FIREX-AQ on 1 and 4 November 2019 to the Kincade Fire in California. During each deployment, CARB staff drove the MMP in the vicinity of the wildfire to detect the wildfire smoke. Once the smoke was identified (i.e., (CO) > 500 ppb), the MMP acted as a stationary site to monitor the fire plumes. The MMP drives are shown in Figure S8 in Supporting Information S1.

The lack of fire activity in California during FIREX-AQ limited the interaction of the MMP with the rest of the FIREX-AQ platforms, but an example of the MMP measurements of the Springs Fire is shown in Figure 12, which shows an example of the evolution of the Springs Fire on 30 August 2019. During the deployment, the MMP was parked ~3 km north of the Springs Fire. The measurement can be categorized into three periods. Period 1 is characterized by fast-changing pollutant concentrations. The smoke evolved quickly as the planetary boundary layer developed during 07:00–09:00, causing the pollutant concentration to decline. The modified combustion efficiency (MCE) also decreased from ~0.95 to ~0.85. Period 2 lasted from 09:00 to 10:30. The measurement was under northwesterly wind conditions. Clean background air entrainment diluted the sampled fire plume, resulting in low pollutant concentrations. The southerly winds dominated during Period 3 (similar to Period 1). The pollutant concentrations showed multiple spikes. The MCE values were around 0.9.