Citation:

Landis, M., R. Long, Jonathan D. Krug, M. Colon, R. Vanderpool, A. Habel, AND S. Urbanski. The U.S. EPA Wildland Fire Sensor Challenge: Performance and Evaluation of Solver Submitted Multi-Pollutant Sensor Systems. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, 247:NA, (2021). https://doi.org/10.1016/j.atmosenv.2020.118165

Impact/Purpose:

Agency Research Drivers - Wild fires often produce significant air pollution, which poses health risks to first responders, residents in nearby communities, and other downwind populations. The growing numbers of communities near areas where fires are likely to occur in the wildland-urban interface (WUI) leads to elevated risk. Air pollution measurements during wildfire events in the United States are currently limited. Existing regulatory ambient air monitoring network stations are located primarily in large population centers for long-term assessment of air quality trends and may not be optimally located to inform maximum air pollution concentrations affecting specific smaller population centers downwind of fire emissions. A limited supply of aging particulate matter (PM) monitoring equipment is available to U.S. Forest Service Air Resource Advisors (ARAs), Regional EPA Emergency Response Teams, and other agencies/organizations to understand the PM exposure of emergency responders and nearby communities. Other types of monitoring equipment, such as unmanned aerial vehicles (UAVs), satellite products, and instrumented aircraft, are sometimes employed to provide aerial information on the evolution of the fire (e.g., thermal camera imaging), however these data do not directly translate to ground-level air pollution concentrations where people may be exposed and typically to not provide actionable information for public health messaging during large wildfire events. Science Challenge - Quickly adding new air pollution measurement stations has, to date, been limited by the cost and complexity of implementation. However, emerging technologies including miniaturized direct-reading sensors, compact/powerful microprocessors, and wireless data communications are supporting the evolution of new strategies to detect air pollution. New approaches to detect and quantify emissions from wildland fires are particularly of interest, for use by ARAs, public health agencies, and researchers. Components of the desired system exist but have not been combined into an easy-to-use system and some or all component capability may need enhancement to meet the challenges of measuring the wide dynamic range of pollutant levels and potential measurement interferences experienced in smoke downwind of wildfires. Results – Ten solvers from four countries submitted sensor systems to be evaluated and considered for the challenge cash prize of up to $60,000. Evaluation reports were generated for these systems and were provided to an independent multi-Agency judging panel. The judging panel awarded first place prize and $35,000 to SenSevere/Senit Technologies (U.S.A.), second prize and $25,000 to Thingy, LLC (U.S.A.), and an Honorable Mention to Kunak Technologies (Spain). Anticipated Impact - The Wildland Fire Sensor Challenge succeeded in communicating a technological measurement and data telemetry need to the global private manufacturing sector. The need and potential market for these small form factor sensor-based products was strengthened by the partnership of so many federal agencies (CDC, EPA, NASA, NPS, NOAA, and USFS) with the Wildland Fire Sensor Challenge. The three Wildland Fire Sensor Challenge awardees have continued to refine their products based on the performance evaluation report EPA provided and have commercialized their products into the marketplace. A follow-up Small Business Innovation Research (SBIR) program Phase I wildland fire sensor solicitation using roughly the same goals/requirements as the Wildland Fire Sensor Challenge resulted in the submission of numerous proposals and the award of four grants to private companies committed to further technological development in this area in 2019. In June 2020 three of the Phase I companies were awarded Phase II grants for continued development and commercialization.

Description:

Wildland fires can emit substantial amounts of air pollution that may pose a risk to those in proximity (e.g., first responders, nearby residents) as well as downwind populations. Quickly deploying air pollution measurement capabilities in response to incidents has been limited to date by the cost, complexity of implementation, and measurement accuracy. Emerging technologies including miniaturized direct-reading sensors, compact microprocessors, and wireless data communications provide new opportunities to detect air pollution in real time. The U.S. Environmental Protection Agency (EPA) partnered with other U.S. federal agencies (CDC, NASA, NPS, NOAA, USFS) to sponsor the Wildland Fire Sensor Challenge. EPA and partnering organizations share the desire to advance wildland fire air measurement technology to be easier to deploy, suitable to use for high concentration events, durable to withstand difficult field conditions, with the ability to report high time resolution data continuously and wirelessly. The Wildland Fire Sensor Challenge encouraged innovation worldwide to develop sensor prototypes capable of measuring fine particulate matter (PM2.5), carbon monoxide (CO), carbon dioxide (CO2), and ozone (O3) during wildfire episodes. The importance of using federal reference method (FRM) versus federal equivalent method (FEM) instruments to evaluate performance in biomass smoke is discussed. Ten solvers from three countries submitted sensor systems for evaluation as part of the challenge. The sensor evaluation results including sensor accuracy, precision, linearity, and operability are presented and discussed, and three challenge winners are announced.

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