Performance evaluation of commercially available non-regulatory instruments and sensors in smoke for PM, CO, CO₂,...

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 PM_2.5 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 PM_2.5 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.Implications: The results presented in this paper provide federal, state, local, and tribal air monitoring and public health agencies with performance information on numerous commercially available non-regulatory instruments/sensors to address air quality monitoring data collection and interpretation challenges presented by wildland fire smoke. The presented accuracy, precision, and linearity performance metrics provide knowledge for the selection of new air quality monitors and insight on the deployment/use of existing monitors during wildland fire events to improve management oversight for professional practitioners/responders, and for communication of health messaging to the public.