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A Low-Cost Sensor Network for Wildfire Smoke Detection and Monitoring - Final Report to the Joint Fire Science Program

Author(s): John Volckens, Scott Kelleher
Year Published: 2017

Wildfires and prescribed fires produce emissions that are harmful to human health. These health effects, however, are difficult to quantify, likely in part due to sparse data on exposure. The ability to measure fire emissions as they reach sensitive areas is critical to ensuring the protection of public health. Ground level quantification of smoke from wildfires and prescribed fires has proven to be a difficult task. The state of the art for monitoring outdoor air quality has long relied upon expensive, cumbersome equipment that generally requires line power. Few ground-based measurements are typically made during fire events, which limits our ability to quantify and assess the impact of smoke from fire events.

The objective of this work was to develop and validate a new type of outdoor air quality monitor, the Outdoor Aerosol Sampler (OAS). The OAS is an active, filter-based air sampler that has been miniaturized and weatherproofed. The OAS represents and attempt to address the technical limitations of field sampling with a device that is relatively inexpensive and independently powered. Prototype development of the OAS was made possible through low-cost electronics, open-source programming platforms, and in-house fabrication methods. An online PM2.5 sensor was selected and integrated with the OAS. A Monte Carlo simulation aided in the selection of battery and solar power necessary to independently power the OAS, while keeping cost and size to a minimum. Cellular communications established via Short Message Service (SMS) technology were utilized in transmitting online sensor readings and controlling the OAS remotely.

Numerous OAS were deployed to monitor smoke concentrations downwind from a large prescribed fire. Mass concentrations sampled from the burn were interpolated to depict smoke concentration gradients downwind of the fire. Field tests found OAS solar charging efficiency (6.7%) to be slightly less than model input efficiency (7.5%). Co-located testing of the OAS demonstrated moderate agreement with equivalent federal reference method samplers for gravimetric analysis of PM2.5.

Citation: Volckens J, Kelleher S. 2017. A Low-Cost Sensor Network for Wildfire Smoke Detection and Monitoring. Joint Fire Science Project 16-2-01-3. Fort Collins, CO: Colorado State University. 42 p.
Topic(s): Smoke & Air Quality, Smoke & Populations
Ecosystem(s): None
Document Type: Technical Report or White Paper
NRFSN number: 17021
Record updated: Mar 7, 2018