Performance evaluation of commercially available non-regulatory instruments and sensors in smoke for PM, CO, CO 2 , NO 2, and SO 2
| Authors: | Matthew S. Landis, Russell W. Long, Jonathan D. Krug, Maribel Colón, Jenny Perth, Shawn P. Urbanski |
| Year: | 2026 |
| Type: | Scientific Journal |
| Station: | Rocky Mountain Research Station |
| DOI: | https://doi.org/10.1080/10962247.2026.2629562 |
| Source: | Journal of the Air & Waste Management Association |
Abstract
Wildland fire smoke can severely degrade downwind air quality and impact responding firefighters and the public. Accurate and timely monitoring of particulate matter (PM) and gaseous pollutants around wildland fires are needed to support management activities like protecting responders and the public from the health and safety hazards of wildland fire smoke. This study systematically evaluates the performance of commercially available, non-regulatory PM and gas instruments/ sensors under controlled wildland fire smoke conditions. We assessed accuracy, precision, and linearity by comparing instrument/sensor outputs to reference-grade samplers/instruments across a wide range of smoke concentrations. Results indicate that most non-regulatory PM instruments/ sensors, particularly those utilizing optical particle sensing technology, often exhibit a high positive raw PM2.5 measurement bias. However, applying smoke-specific calibration models substantially improved accuracy, with several models achieving post-calibration accuracy greater than 85%. Carbon monoxide (CO) and carbon dioxide (CO2) gas instruments/sensors generally performed well after calibration, while the performance of electrochemical nitrogen dioxide (NO2) and sulfur dioxide (SO2) sensors was relatively poor. Non-regulatory PM2.5 instrument/sensor response was primarily influenced by aerosol optical properties, particle size distribution, and effective density. We found that smoke-specific calibration and data quality assurance are key for reliable non-regulatory measurements during wildland fire events, especially for incident responder force protection and nearby communities. Integrating calibrated non-regulatory measurement data with regulatory networks can improve smoke exposure assessment and public health messaging. While non-regulatory instruments/sensors cannot fully replace reference instruments, their proper selection and calibration can provide valuable, actionable data for air quality management during wildfires.