scholarly journals Accessing the Life in Smoke: A New Application of Unmanned Aircraft Systems (UAS) to Sample Wildland Fire Bioaerosol Emissions and Their Environment

Fire ◽  
2019 ◽  
Vol 2 (4) ◽  
pp. 56 ◽  
Author(s):  
Leda N. Kobziar ◽  
Melissa R. A. Pingree ◽  
Adam C. Watts ◽  
Kellen N. Nelson ◽  
Tyler J. Dreaden ◽  
...  
Keyword(s):  
Wildland Fire ◽  
Unmanned Aircraft ◽  
Biomass Combustion ◽  
Wildland Fires ◽  
Microbial Composition ◽  
Fire Smoke ◽  
Major Producer ◽  
Aircraft System ◽  
Bacteria And Fungi ◽  
Background Air

Wildland fire is a major producer of aerosols from combustion of vegetation and soils, but little is known about the abundance and composition of smoke’s biological content. Bioaerosols, or aerosols derived from biological sources, may be a significant component of the aerosol load vectored in wildland fire smoke. If bioaerosols are injected into the upper troposphere via high-intensity wildland fires and transported across continents, there may be consequences for the ecosystems they reach. Such transport would also alter the concept of a wildfire’s perimeter and the disturbance domain of its impact. Recent research has revealed that viable microorganisms are directly aerosolized during biomass combustion, but sampling systems and methodology for quantifying this phenomenon are poorly developed. Using a series of prescribed fires in frequently burned forest ecosystems, we report the results of employing a small rotary-wing unmanned aircraft system (UAS) to concurrently sample aerosolized bacteria and fungi, particulate matter, and micrometeorology in smoke plumes versus background conditions. Airborne impaction-based bioaerosol sampling indicated that microbial composition differed between background air and smoke, with seven unique organisms in smoke vs. three in background air. The air temperature was negatively correlated with the number of fungal colony-forming units detected. Our results demonstrate the utility of a UAS-based sampling platform for active sampling of viable aerosolized microbes in smoke arising from wildland fires. This methodology can be extended to sample viable microbes in a wide variety of emissions sampling pursuits, especially those in hazardous and inaccessible environments.

scholarly journals Mapping Burn Extent of Large Wildland Fires from Satellite Imagery Using Machine Learning Trained from Localized Hyperspatial Imagery

2020 ◽  
Vol 12 (24) ◽  
pp. 4097
Author(s):  
Dale Hamilton ◽  
Enoch Levandovsky ◽  
Nicholas Hamilton
Keyword(s):  
Satellite Imagery ◽  
Wildland Fire ◽  
Low Cost ◽  
Satellite Image ◽  
Temporal Stability ◽  
Fire Effects ◽  
The United States ◽  
Unmanned Aircraft ◽  
Wildlife Habitat ◽  
Wildland Fires

Wildfires burn 4–10 million acres annually across the United States and wildland fire related damages and suppression costs have exceeded $13 billion for a single year. High-intensity wildfires contribute to post-fire erosion, degraded wildlife habitat, and loss of timber resources. Accurate and temporally adequate assessment of the effects of wildland fire on the environment is critical to improving the of wildland fire as a tool for restoring ecosystem resilience. Sensor miniaturization and small unmanned aircraft systems (sUAS) provide affordable, on-demand monitoring of wildland fire effects at a much finer spatial resolution than is possible with satellite imagery. The use of sUAS would allow researchers to obtain data with more detail at a much lower initial cost. Unfortunately, current regulatory and technical constraints prohibit the acquisition of imagery using sUAS for the entire extent of large fires. This research examined the use of sUAS imagery to train and validate burn severity and extent mapping of large wildland fires from various satellite images. Despite the lower resolution of the satellite image, the research utilized the advantages of satellite imagery such as global coverage, low cost, temporal stability, and spectral extent while leveraging the higher resolution of hyperspatial sUAS imagery for training and validating the mapping analytics.

scholarly journals Wildland fire emission sampling at Fishlake National Forest, Utah using an unmanned aircraft system

2021 ◽  
Vol 247 ◽  
pp. 118193
Author(s):  
J. Aurell ◽  
B. Gullett ◽  
A. Holder ◽  
F. Kiros ◽  
W. Mitchell ◽  
...  
Keyword(s):  
Wildland Fire ◽  
Unmanned Aircraft ◽  
National Forest ◽  
Unmanned Aircraft System ◽  
Emission Sampling ◽  
Aircraft System

scholarly journals Comparison of Ozone Measurement Methods in Biomass Burning Smoke: An evaluation under field and laboratory conditions

2020 ◽  
Author(s):  
Russell W. Long ◽  
Andrew Whitehill ◽  
Andrew Habel ◽  
Shawn Urbanski ◽  
Hannah Halliday ◽  
...  
Keyword(s):  
United States ◽  
Gas Phase ◽  
Biomass Burning ◽  
Wildland Fire ◽  
The United States ◽  
Photometric Method ◽  
Wildland Fires ◽  
Fire Plumes ◽  
Fire Smoke ◽  
Field And Laboratory Conditions

Abstract. In recent years wildland fires in the United States have had significant impacts on local and regional air quality and negative human health outcomes. Although the primary health concerns from wildland fires come from fine particulate matter (PM2.5), large increases in ozone (O3) are also observed downwind of wildland fire plumes. Conditions generated in and around wildland fire plumes, including the presence of interfering chemical species, can make the accurate measurement of O3 concentrations using the ultraviolet (UV) photometric method challenging if not impossible. UV photometric method instruments are prone to interferences by volatile organic compounds (VOCs) that are present at high concentrations in wildland fire smoke. Four different O3 measurement methodologies were deployed in a mobile sampling platform downwind of active prescribed grassland fire lines in Kansas and Oregon and during controlled chamber burns at the United States Forest Service, Rocky Mountain Research Station Fire Sciences Laboratory in Missoula, Montana. We demonstrate that the Federal Reference Method (FRM) nitric oxide (NO) chemiluminescence monitors and Federal Equivalent Method (FEM) gas-phase (NO) chemical scrubber UV photometric O3 monitors are relatively interference-free, even in near-field combustion plumes. In contrast, FEM UV photometric O3 monitors using solid-phase catalytic scrubbers show positive artifacts that are positively correlated with carbon monoxide (CO) and total gas phase hydrocarbons (THC), two indicator species of biomass burning. Of the two catalytic scrubber UV photometric methods evaluated, the instruments that included a Nafion® tube dryer in the sample introduction system had artifacts an order of magnitude smaller than the instrument with no humidity correction. We hypothesize that Nafion®--permeable VOCs (such as aromatic hydrocarbons) could be a significant source of interference for catalytic scrubber UV photometric O3 monitors, and that the inclusion of a Nafion® tube dryer assists with the mitigation of these interferences. The interference-free chemiluminescence FRM method is highly recommended for accurate measurements of O3 in wildland fire plume studies and at regulatory ambient monitoring sites frequently impacted by wildland fire smoke.

scholarly journals Wildland Fire Tree Mortality Mapping from Hyperspatial Imagery Using Machine Learning

2021 ◽  
Vol 13 (2) ◽  
pp. 290
Author(s):  
Dale A. Hamilton ◽  
Kamden L. Brothers ◽  
Samuel D. Jones ◽  
Jason Colwell ◽  
Jacob Winters
Keyword(s):  
Tree Mortality ◽  
Wildland Fire ◽  
Canopy Cover ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Burn Severity ◽  
Crown Fire ◽  
Aircraft Systems ◽  
Ground Truthing ◽  
Aircraft System

The use of imagery from small unmanned aircraft systems (sUAS) has enabled the production of more accurate data about the effects of wildland fire, enabling land managers to make more informed decisions. The ability to detect trees in hyperspatial imagery enables the calculation of canopy cover. A comparison of hyperspatial post-fire canopy cover and pre-fire canopy cover from sources such as the LANDFIRE project enables the calculation of tree mortality, which is a major indicator of burn severity. A mask region-based convolutional neural network was trained to classify trees as groups of pixels from a hyperspatial orthomosaic acquired with a small unmanned aircraft system. The tree classification is summarized at 30 m, resulting in a canopy cover raster. A post-fire canopy cover is then compared to LANDFIRE canopy cover preceding the fire, calculating how much the canopy was reduced due to the fire. Canopy reduction allows the mapping of burn severity while also identifying where surface, passive crown, and active crown fire occurred within the burn perimeter. Canopy cover mapped through this effort was lower than the LANDFIRE Canopy Cover product, which literature indicated is typically over reported. Assessment of canopy reduction mapping on a wildland fire reflects observations made both from ground truthing efforts as well as observations made of the associated hyperspatial sUAS orthomosaic.

scholarly journals Comparison of ozone measurement methods in biomass burning smoke: an evaluation under field and laboratory conditions

2021 ◽  
Vol 14 (3) ◽  
pp. 1783-1800
Author(s):  
Russell W. Long ◽  
Andrew Whitehill ◽  
Andrew Habel ◽  
Shawn Urbanski ◽  
Hannah Halliday ◽  
...  
Keyword(s):  
United States ◽  
Gas Phase ◽  
Biomass Burning ◽  
Wildland Fire ◽  
The United States ◽  
Photometric Method ◽  
Wildland Fires ◽  
Fire Plumes ◽  
Fire Smoke ◽  
Field And Laboratory Conditions

Abstract. In recent years wildland fires in the United States have had significant impacts on local and regional air quality and negative human health outcomes. Although the primary health concerns from wildland fires come from fine particulate matter (PM2.5), large increases in ozone (O3) have been observed downwind of wildland fire plumes (DeBell et al., 2004; Bytnerowicz et al., 2010; Preisler et al., 2010; Jaffe et al., 2012; Bytnerowicz et al., 2013; Jaffe et al., 2013; Lu et al., 2016; Lindaas et al., 2017; McClure and Jaffe, 2018; Liu et al., 2018; Baylon et al., 2018; Buysse et al., 2019). Conditions generated in and around wildland fire plumes, including the presence of interfering chemical species, can make the accurate measurement of O3 concentrations using the ultraviolet (UV) photometric method challenging if not impossible. UV photometric method instruments are prone to interferences by volatile organic compounds (VOCs) that are present at high concentrations in wildland fire smoke. Four different O3 measurement methodologies were deployed in a mobile sampling platform downwind of active prescribed grassland fire lines in Kansas and Oregon and during controlled chamber burns at the United States Forest Service, Rocky Mountain Research Station Fire Sciences Laboratory in Missoula, Montana. We demonstrate that the Federal Reference Method (FRM) nitric oxide (NO) chemiluminescence monitors and Federal Equivalent Method (FEM) gas-phase (NO) chemical scrubber UV photometric O3 monitors are relatively interference-free, even in near-field combustion plumes. In contrast, FEM UV photometric O3 monitors using solid-phase catalytic scrubbers show positive artifacts that are positively correlated with carbon monoxide (CO) and total gas-phase hydrocarbon (THC), two indicator species of biomass burning. Of the two catalytic scrubber UV photometric methods evaluated, the instruments that included a Nafion® tube dryer in the sample introduction system had artifacts an order of magnitude smaller than the instrument with no humidity correction. We hypothesize that Nafion®-permeating VOCs (such as aromatic hydrocarbons) could be a significant source of interference for catalytic scrubber UV photometric O3 monitors and that the inclusion of a Nafion® tube dryer assists with the mitigation of these interferences. The chemiluminescence FRM method is highly recommended for accurate measurements of O3 in wildland fire plume studies and at regulatory ambient monitoring sites frequently impacted by wildland fire smoke.

scholarly journals Application of a Mini Unmanned Aircraft System for In Situ Monitoring of Fire Plume Thermodynamic Properties

2012 ◽  
Vol 29 (3) ◽  
pp. 309-315 ◽  
Author(s):  
Caroline M. Kiefer ◽  
Craig B. Clements ◽  
Brian E. Potter
Keyword(s):  
Wildland Fire ◽  
Potential Temperature ◽  
Fire Behavior ◽  
Unmanned Aircraft ◽  
In Situ Monitoring ◽  
Unmanned Aircraft System ◽  
Fire Plume ◽  
Aircraft System ◽  
Water Vapor Mixing Ratio

Abstract Direct measurements of wildland fire plume properties are rare because of difficult access to regions near the fire front and plume. Moisture released from combustion, in addition to added heat, can enhance buoyancy and convection, influencing fire behavior. In this study, a mini unmanned aircraft system (miniUAS) was used to obtain in situ measurements of temperature and relative humidity during a prescribed fire. The miniUAS was successfully maneuvered through the plume and its associated turbulence and provided observations of temperature and humidity profiles from near the centerline of the plume. Within the plume, the water vapor mixing ratio increased by 0.5–3.5 g kg−1 above ambient and was caused by the combustion of fuels. Potential temperature perturbations were on the order of 2–5 K. These results indicate that significant moisture and temperature enhancement can occur and may potentially modify convection dynamics of fire plumes.

Heavy Lift Multirotor Unmanned Aircraft System for Beyond-Visual-Line-of-Sight Operations in the National Airspace System

2021 ◽  
Author(s):  
Michael C. Hatfield ◽  
Levi Purdy ◽  
Logan Graves ◽  
William Remmert
Keyword(s):  
Unmanned Aircraft ◽  
Line Of Sight ◽  
National Airspace System ◽  
Unmanned Aircraft System ◽  
Heavy Lift ◽  
Aircraft System

The NATO Unmanned Aircraft System Human Systems Integration Guidebook

2012 ◽  
Author(s):  
Anthony P. Tvaryanas ◽  
Rebecca Singer ◽  
Barbara Palmer
Keyword(s):  
Systems Integration ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft System ◽  
Human Systems Integration ◽  
Aircraft System ◽  
Human Systems
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