The Fire and Smoke Model Evaluation Experiment—A Plan for Integrated, Large Fire–Atmosphere Field Campaigns

Prichard, Susan J.; Larkin, Narasimhan; Ottmar, Roger D.; French, Nancy H. F.; Baker, Kirk R.; Brown, Tim; Clements, Craig B.; Dickinson, Matt; Hudak, Andrew T.; Kochanski, Adam K.; Linn, Rodman; Liu, Yongqiang; Potter, Brian E.; Mell, William E.; Tanzer, Danielle; Urbanski, S. P.; Watts, Adam C.

doi:10.3390/atmos10020066

Cited by 66 publications

(45 citation statements)

References 73 publications

(97 reference statements)

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“…However, given the sparse nature of routine ground measurements and assumptions required for remotely sensed data a simple approach for correcting or modulating the modeled fire predictions could introduce new errors both spatially and temporally. Current studies are underway to improve smoke modeling capability [84] and advance integration of data sources through machine learning methods.…”

Section: Strengths and Limitationsmentioning

confidence: 99%

Mapping Modeled Exposure of Wildland Fire Smoke for Human Health Studies in California

et al. 2019

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Wildland fire smoke exposure affects a broad proportion of the U.S. population and is increasing due to climate change, settlement patterns and fire seclusion. Significant public health questions surrounding its effects remain, including the impact on cardiovascular disease and maternal health. Using atmospheric chemical transport modeling, we examined general air quality with and without wildland fire smoke PM 2.5 . The 24-h average concentration of PM 2.5 from all sources in 12-km gridded output from all sources in California (2007-2013) was 4.91 µg/m 3 . The average concentration of fire-PM 2.5 in California by year was 1.22 µg/m 3 (~25% of total PM 2.5 ). The fire-PM 2.5 daily mean was estimated at 4.40 µg/m 3 in a high fire year (2008). Based on the model-derived fire-PM 2.5 data, 97.4% of California's population lived in a county that experienced at least one episode of high smoke exposure ("smokewave") from 2007-2013. Photochemical model predictions of wildfire impacts on daily average PM 2.5 carbon (organic and elemental) compared to rural monitors in California compared well for most years but tended to over-estimate wildfire impacts for 2008 (2.0 µg/m 3 bias) and 2013 (1.6 µg/m 3 bias) while underestimating for 2009 (−2.1 µg/m 3 bias). The modeling system isolated wildfire and PM 2.5 from other sources at monitored and unmonitored locations, which is important for understanding population exposure in health studies. Further work is needed to refine model predictions of wildland fire impacts on air quality in order to increase confidence in the model for future assessments. Atmospheric modeling can be a useful tool to assess broad geographic scale exposure for epidemiologic studies and to examine scenario-based health impacts.

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Section: Strengths and Limitationsmentioning

confidence: 99%

Mapping Modeled Exposure of Wildland Fire Smoke for Human Health Studies in California

et al. 2019

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“…A lightweight compact instrument package capable of collecting air samples and measuring CO, CO 2 , and PM concentrations and fire weather conditions (i.e., temperature, relative humidity) was developed to characterize smoke plumes. This instrument package is suitable for airborne deployment on sUASs and stationary ground-based monitoring, and matches the desired specifications for the Fire and Smoke Model Evaluation Experiment (FASMEE)-Smoke and Emissions priority area [12,21]. The instrument package consists of two parts: (1) A measurement device (~625 g) consisting of a sampling module that includes a solenoid valve system for collecting air samples and a sensing module for characterizing atmospheric gas concentrations and meteorological conditions in real-time, and (2) a radio-operated remote-control device (~145 g) for initiating air sample collection and displaying time-series data from the sensing module.…”

Section: Methodsmentioning

confidence: 88%

“…Emissions factors for many gases and particulate matter (PM) remain uncertain and depend greatly on combustion processes that arise from the characteristics of fuel beds and weather conditions prior to and during burning [8,10]. Accurate emissions estimates from wildland fires are needed for reducing uncertainties in atmospheric chemical transport models and for improving predictions of fire effects on air quality [11,12]. Characterization and quantification of smoke emissions is difficult and complex due to the innate hazards associated with collecting measurements and samples in and near open burning areas, and also because smoke is highly dynamic in space and time.…”

Section: Introductionmentioning

confidence: 99%

A Multipollutant Smoke Emissions Sensing and Sampling Instrument Package for Unmanned Aircraft Systems: Development and Testing

Nelson

Boehmler

Khlystov

et al. 2019

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Poor air quality arising from prescribed and wildfire smoke emissions poses threats to human health and therefore must be taken into account for the planning and implementation of prescribed burns for reducing contemporary fuel loading and other management goals. To better understand how smoke properties vary as a function of fuel beds and environmental conditions, we developed and tested a compact portable instrument package that integrates direct air sampling with air quality and meteorology sensing, suitable for in situ data collection within burn units and as a payload on multi-rotor small unmanned aircraft systems (sUASs). Co-located sensors collect carbon dioxide, carbon monoxide, and particulate matter data at a sampling rate of~0.5 Hz with a microcontroller-based system that includes independent data logging, power systems, radio telemetry, and global positioning system data. Sensor data facilitates precise remote canister collection of air samples suitable for laboratory analysis of volatile organic compounds (VOCs) and other major and trace gases. Instrument package specifications are compatible with common protocols for ground-based and airborne measurements. We present and discuss design specifications for the system and preliminary data collected in controlled burns at Tall Timbers Research Station, FL, USA and Sycan Marsh Preserve, OR, USA.

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“…A number of model predictions can be evaluated using micrometeorological data collected during fires, but large-scale field experiments such as those reported here have only recently been conducted frequently enough to provide sufficient information to evaluate detailed relationships between ignition pattern and fire behavior, fuel consumption and turbulence and energy fluxes in the fire environment. Continuation of multi-scale experiments that couple above-and within-canopy turbulence and energy flux measurements with more precise measurements of fuel combustion physics such as those conducted under the Department of Defense-sponsored Strategic Environmental Research Program (SERDP) [55] and the multi-agency Fire and Smoke Model Evaluation Experiment (FASMEE) [56] will add considerably to these efforts.…”

Section: Discussionmentioning

confidence: 99%

Fire Behavior, Fuel Consumption, and Turbulence and Energy Exchange during Prescribed Fires in Pitch Pine Forests

et al. 2020

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Prescribed fires are conducted extensively in pine-dominated forests throughout the Eastern USA to reduce the risk of wildfires and maintain fire-adapted ecosystems. We asked how fire behavior and fuel consumption during prescribed fires are associated with turbulence and energy fluxes, which affect the dispersion of smoke and transport of firebrands, potentially impacting local communities and transportation corridors. We estimated fuel consumption and measured above-canopy turbulence and energy fluxes using eddy covariance during eight prescribed fires ranging in behavior from low-intensity backing fires to high-intensity head fires in pine-dominated forests of the New Jersey Pinelands, USA. Consumption was greatest for fine litter, intermediate for understory vegetation, and least for 1 + 10 hour wood, and was significantly correlated with pre-burn loading for all fuel types. Crown torching and canopy fuel consumption occurred only during high-intensity fires. Above-canopy air temperature, vertical wind velocity, and turbulent kinetic energy (TKE) in buoyant plumes above fires were enhanced up to 20.0, 3.9 and 4.1 times, respectively, compared to values measured simultaneously on control towers in unburned areas. When all prescribed fires were considered together, differences between above-canopy measurements in burn and control areas (Δ values) for maximum Δ air temperatures were significantly correlated with maximum Δ vertical wind velocities at all (10 Hz to 1 minute) integration times, and with Δ TKE. Maximum 10 minute averaged sensible heat fluxes measured above canopy were lower during low-intensity backing fires than for high-intensity head fires, averaging 1.8 MJ m−2 vs. 10.6 MJ m−2, respectively. Summed Δ sensible heat values averaged 70 ± 17%, and 112 ± 42% of convective heat flux estimated from fuel consumption for low-intensity and high-intensity fires, respectively. Surprisingly, there were only weak relationships between the consumption of surface and understory fuels and Δ air temperature, Δ wind velocities, or Δ TKE values in buoyant plumes. Overall, low-intensity fires were effective at reducing fuels on the forest floor, but less effective at consuming understory vegetation and ladder fuels, while high-intensity head fires resulted in greater consumption of ladder and canopy fuels but were also associated with large increases in turbulence and heat flux above the canopy. Our research quantifies some of the tradeoffs involved between fire behavior and turbulent transfer of smoke and firebrands during effective fuel reduction treatments and can assist wildland fire managers when planning and conducting prescribed fires.

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The Fire and Smoke Model Evaluation Experiment—A Plan for Integrated, Large Fire–Atmosphere Field Campaigns

Cited by 66 publications

References 73 publications

Mapping Modeled Exposure of Wildland Fire Smoke for Human Health Studies in California

Mapping Modeled Exposure of Wildland Fire Smoke for Human Health Studies in California

A Multipollutant Smoke Emissions Sensing and Sampling Instrument Package for Unmanned Aircraft Systems: Development and Testing

Fire Behavior, Fuel Consumption, and Turbulence and Energy Exchange during Prescribed Fires in Pitch Pine Forests

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