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. 2023 Mar 29;23(7):3561.
doi: 10.3390/s23073561.

UAV-Based Wildland Fire Air Toxics Data Collection and Analysis

Prabhash Ragbir  1 , Ajith Kaduwela  2 , David Passovoy  3 , Preet Amin  1 , Shuchen Ye  1 , Christopher Wallis  2 , Christopher Alaimo  4 , Thomas Young  4 , Zhaodan Kong  1
Affiliations

UAV-Based Wildland Fire Air Toxics Data Collection and Analysis

Prabhash Ragbir et al. Sensors (Basel). .

Abstract

Smoke plumes emitted from wildland-urban interface (WUI) wildfires contain toxic chemical substances that are harmful to human health, mainly due to the burning of synthetic components. Accurate measurement of these air toxics is necessary for understanding their impacts on human health. However, air pollution is typically measured using ground-based sensors, manned airplanes, or satellites, which all provide low-resolution data. Unmanned Aerial Vehicles (UAVs) have the potential to provide high-resolution spatial and temporal data due to their ability to hover in specific locations and maneuver with precise trajectories in 3-D space. This study investigates the use of an octocopter UAV, equipped with a customized air quality sensor package and a volatile organic compound (VOC) air sampler, for the purposes of collecting and analyzing air toxics data from wildfire plumes. The UAV prototype developed has been successfully tested during several prescribed fires conducted by the California Department of Forestry and Fire Protection (CAL FIRE). Data from these experiments were analyzed with emphasis on the relationship between the air toxics measured and the different types of vegetation/fuel burnt. BTEX compounds were found to be more abundant for hardwood burning compared to grassland burning, as expected.

Keywords: Unmanned Aerial Vehicles; air quality monitoring; low-cost sensors; smoke plumes; volatile organic compounds; wildfire.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Figures

Figure 1
Figure 1
(a) Front view and (b) top view of octocopter UAV platform equipped with air quality sensor package and VOC air sampler.
Figure 2
Figure 2
The main board (left) and extension board (right) of the Sony Spresense microcontroller used for the air quality sensor package and VOC air sampler.
Figure 3
Figure 3
(a) Front view and (b) back view of the air quality sensor package.
Figure 4
Figure 4
VOC sorbent tube air sampler.
Figure 5
Figure 5
Equipment used for Thermal Desorption-Gas Chromatography-Mass Spectrometry analysis.
Figure 6
Figure 6
(a) Smoke plume emitted from a prescribed fire at Jack London State Park. (b) UAV-based data collection during a prescribed fire at Jack London State Park.
Figure 7
Figure 7
(a) 2D GPS data and (b) 3D GPS data for UAV data collection during a prescribed burn at Pilot Hill.
Figure 8
Figure 8
3D GPS data for (a) Angels Camp and (b) Jack London Prescribed Fire Experiments.
Figure 9
Figure 9
2D Heat Maps for (a) CO2 and (b) PM2.5 from the Pilot Hill Prescribed Fire Experiment.
Figure 10
Figure 10
3D Scatter Plot for (a) CO2 and (b) PM2.5 from the Pilot Hill Prescribed Fire Experiment.
Figure 10
Figure 10
3D Scatter Plot for (a) CO2 and (b) PM2.5 from the Pilot Hill Prescribed Fire Experiment.
Figure 11
Figure 11
3D Scatter Plot for (a) CO2 and (b) PM2.5 from the Angels Camp Prescribed Fire Experiment.
Figure 12
Figure 12
3D Scatter Plot for (a) CO2 and (b) PM2.5 from the Jack London Prescribed Fire Experiment.
Figure 13
Figure 13
VOC Data for the (a) Pilot Hill, (b) Angels Camp, and (c) Jack London Prescribed Fire Experiments.
See this image and copyright information in PMC

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