Environmental Conditions, Ignition Type, and Air Quality Impacts of Wildfires in the Southeastern and Western United States

Brey, Steven J.; Barnes, Elizabeth A.; Pierce, Jeffrey R.; Wiedinmyer, Christine; Fischer, Emily V.

doi:10.1029/2018ef000972

Cited by 51 publications

(66 citation statements)

References 64 publications

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“…Journal of Geophysical Research: Atmospheres example, within the Amazon Basin during the dry season, daily average background aerosol concentrations can reach between 50 and 600 μg/m 3 (Martin et al, 2010;Reid et al, 1998). Midlatitude regions with many nearby wild or prescribed fires may also have elevated background OA concentrations (Brey et al, 2018).…”

Section: 1029/2018jd029674mentioning

confidence: 99%

More Than Emissions and Chemistry: Fire Size, Dilution, and Background Aerosol Also Greatly Influence Near‐Field Biomass Burning Aerosol Aging

et al. 2019

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Biomass burning emits particles (black carbon and primary organic aerosol) and precursor vapors to the atmosphere that chemically and physically age in the atmosphere. This theoretical study explores the relationships between fire size (determining the initial plume width and concentration), dilution rate, and entrainment of background aerosol on particle coagulation, organic aerosol (OA) evaporation, and secondary organic aerosol (SOA) condensation in smoke plumes. We examine the impacts of these processes on aged smoke OA mass, geometric mean diameter (Dg), peak lognormal modal width (σg), particle extinction (E), and cloud condensation nuclei (CCN) concentrations. In our simulations, aging OA mass is controlled by competition between OA evaporation and SOA condensation. Large, slowly diluting plumes evaporate little in our base set of simulations, which may allow for net increases in mass, E, CCN , and Dg from SOA condensation. Smaller, quickly diluting fire plumes lead to faster evaporation, which favors decreases in mass, E, CCN, and Dg. However, the SOA fraction of the smoke OA increases more rapidly in smaller fires due to faster primary organic aerosol evaporation leading to more SOA precursors. Net mass changes for smaller fires depend on background OA concentrations; increasing background aerosol concentrations decrease evaporation rates. Although coagulation does not change mass, it can decrease the number of particles in large/slowly diluting plumes, increasing Dg and E, and decreasing σg. While our conclusions are limited by being a theoretical study, we hope they help motivate future smoke‐plume analyses to consider the effects of fire size, meteorology, and background OA concentrations.

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Section: 1029/2018jd029674mentioning

confidence: 99%

More Than Emissions and Chemistry: Fire Size, Dilution, and Background Aerosol Also Greatly Influence Near‐Field Biomass Burning Aerosol Aging

et al. 2019

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“…Brey, Barnes, et al (2018) discussed the different environmental and meteorological conditions that influence landscape fires in the western and southeastern United States, respectively. Brey, Barnes, et al (2018) discussed the different environmental and meteorological conditions that influence landscape fires in the western and southeastern United States, respectively.…”

Section: The Hazard Mapping System Fire and Smoke Product (Hms)mentioning

confidence: 99%

“…To distinguish the regional differences in smoke properties, we separate our data set into three regions. Brey, Barnes, et al (2018) discussed the different environmental and meteorological conditions that influence landscape fires in the western and southeastern United States, respectively. However, we further divide the western region into the Pacific West (PW) and the (non-California) southwest (SW) due to the different environmental conditions (primarily, whether the region is dust-prone or not, as mentioned in Hand et al,…”

Section: The Hazard Mapping System Fire and Smoke Product (Hms)mentioning

confidence: 99%

“…Most of the total burned area in the western United States is due to wildfires caused by lightning or human ignitions (Brey, Barnes, et al, 2018); while most of the total burned area in the southeastern United States (SE) is attributed to prescribed or agricultural burns (Melvin, 2015;Mitchell et al, 2014). Most of the total burned area in the western United States is due to wildfires caused by lightning or human ignitions (Brey, Barnes, et al, 2018); while most of the total burned area in the southeastern United States (SE) is attributed to prescribed or agricultural burns (Melvin, 2015;Mitchell et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

“…While uncertainties in smoke optical properties influence the performance of climate models and remote sensing techniques, there are also regional differences in landscape fire types, fuels, combustion conditions, and meteorology that may impact the smoke properties. Most of the total burned area in the western United States is due to wildfires caused by lightning or human ignitions (Brey, Barnes, et al, 2018); while most of the total burned area in the southeastern United States (SE) is attributed to prescribed or agricultural burns (Melvin, 2015;Mitchell et al, 2014). Previous laboratory experiments found that the smoke produced from fuels collected in the SE had a different chemical composition than the smoke from fuels collected in the western United States (Burling et al, 2010;Levin et al, 2010;May et al, 2014;McMeeking et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

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A Decadal Climatology of Chemical, Physical, and Optical Properties of Ambient Smoke in the Western and Southeastern United States

et al. 2020

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Biomass burning is a major source of summertime fine particulate matter in the United States, degrading air quality and affecting human health and climate. Fuels, burn conditions, and fire types vary across the United States, which may impact smoke composition and optical properties. We use the Hazard Mapping System to track smoke plumes for 10 years from 2008 to 2017, focusing on three U.S. regions: Southeast, Pacific West, and Southwest. Combining this geospatial data set with AErosol RObotic NETwork (AERONET) columnar data, and Interagency Monitoring of Protected Visual Environments (IMPROVE) network in situ observations, we define "smoke-influenced days" and derive the properties of smoke aerosol for April through September, encompassing the main fire seasons across the United States. We find in the IMPROVE surface measurement that the elemental carbon fraction of smoke in the Southeast is statistically different from and lower than that in the west, consistent with more-smoldering prescribed fires in the southeast. We find in the AERONET columnar observations that the mean single scattering albedo of smoke (at 675 nm) is lower in the two western regions (~0.94) compared to the southeast (~0.96), consistent with the differences in composition and fire types, which implies that the compositional differences at the surface may be representative of the column. Higher relative humidity in the southeast and less dust associated with smoke also appear to contribute to the higher smoke single scattering albedo relative to the west. Our results show that smoke properties vary regionally, with implications for models, data assimilation, and remote-sensing.

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Modeling wildfire activity in the western United States with machine learning

Buch

Williams

Juang

et al. 2022

Preprint

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The annual area burned due to wildfires in the western United States (WUS) increased by more than 300% between 1984 and 2020. However, accounting for the nonlinear, spatially heterogeneous interactions between climate, vegetation, and human predictors driving the trends in fire frequency and sizes at different spatial scales remains a challenging problem for statistical fire models. Here we introduce a novel stochastic machine learning (ML) framework to model observed fire frequencies and sizes in 12 km x 12 km grid cells across the WUS. This framework is implemented using Mixture Density Networks trained on a wide suite of input predictors. The modeled WUS fire frequency corresponds well with observations at both monthly (r= 0.94) and annual (r= 0.85) timescales, as do the monthly (r= 0.90) and annual (r= 0.88) area burned. Moreover, the annual time series of both fire variables exhibit strong correlations (r >= 0.6) in 16 out of 18 ecoregions. Our ML model captures the interannual variability and the distinct multidecade increases in annual area burned for both forested and non-forested ecoregions. Evaluating predictor importance with Shapley additive explanations, we find that fire month vapor pressure deficit (VPD) is the dominant driver of fire frequencies and sizes across the WUS, followed by 1000-hour dead fuel moisture (FM1000), total monthly precipitation (Prec), mean daily maximum temperature (Tmax), and fraction of grassland cover in a grid cell. Our findings serve as a promising use case of ML techniques for wildfire prediction in particular and extreme event modeling more broadly.

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Environmental Conditions, Ignition Type, and Air Quality Impacts of Wildfires in the Southeastern and Western United States

Cited by 51 publications

References 64 publications

More Than Emissions and Chemistry: Fire Size, Dilution, and Background Aerosol Also Greatly Influence Near‐Field Biomass Burning Aerosol Aging

More Than Emissions and Chemistry: Fire Size, Dilution, and Background Aerosol Also Greatly Influence Near‐Field Biomass Burning Aerosol Aging

A Decadal Climatology of Chemical, Physical, and Optical Properties of Ambient Smoke in the Western and Southeastern United States

Modeling wildfire activity in the western United States with machine learning

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