Wildfire Smoke Exposure Control
Daniel Autenrieth | Montana Technological University
This proposed follow-up study to our Pilot Planning Project seeks to establish the efficacy of low-cost do-it-yourself portable air cleaners (DIY PACs) to control wildfire smoke-sourced particulate matter exposures in office environments, which is our first Aim. These DIY PACs are constructed using a basic box fan and a furnace filter. The rationale is that public health agencies are increasingly recommending that individuals stay indoors and utilize PACs during wildfire smoke events, but a dearth of published data exists regarding their efficacy, particularly in office buildings where occupants have very little control over other factors that influence wildfire smoke infiltration and concentration (such as ventilation). Further, the low cost of these DIY PACs may be a particular benefit to underserved populations, and their accessibility and ease of design may provide increased agency to control exposures for people from these populations. Efficacy at controlling smoke concentrations will be determined using offices paired by volume and configuration and providing one office within each pair the DIY PAC. The occupants of both offices will be equipped with personal air monitoring devices to measure their exposure to wildfire smoke-sourced particulate matter during the 2021 wildfire season. Additional DIY PAC testing will occur in a controlled laboratory environment, using generated sodium chloride aerosol and smoke to characterize the performance of the devices under a variety of different conditions, including different filters, fan speeds, and fan orientations, which is our second Aim. Indoor office concentrations of wild-fire smoke-sourced particulate matter have been strongly correlated with ambient concentrations in previous research. However, our study takes place on the Flathead Reservation where no EPA air quality monitoring station is present. Our third Aim seeks to create a network of low-cost particulate matter monitors on the reservation and compare the ambient particulate matter concentrations to EPA monitors in the broader region. This preliminary research will determine if data from these existing monitors can be used to accurately predict concentrations on the reservation, or if not, where the optimal location would be for a new air quality monitoring station.
The first goal of this study is to evaluate the effectiveness of low-cost PACs at controlling wildfire smoke PM 2.5 exposures in different workplace environments and configurations. Another goal is to characterize the influence of design parameters such as fan speed and filtration efficiencies on low-cost PAC performance in a laboratory setting. The final goal is to explore the spatial and temporal variability of PM 2.5 in the Mission Valley and determine if local PM 2.5 concentrations can be accurately predicted using regional data. Achievement of these goals will inform environmental health recommendations for controlling wildfire smoke exposures in office environments and will provide evidence for self-protective behaviors individuals can take to control exposures using affordable and widely available technology. These goals will be accomplished through the following specific aims:
- Assess the efficacy of low-cost DIY PACs at controlling personal exposures to wildfire smoke in individual office and cubical settings on the Flathead Reservation. Working hypotheses: Exposures to PM 2.5 will be lower in individual offices and cubicles with a DIY PAC as compared to matched controls. We also hypothesize that exposures will be controlled below environmental PM 2.5 health guidelines more often when using a DIY PAC as compared to not using one.
- Characterize the performance characteristics of numerous DIY PAC configurations in a Montana Tech laboratory setting. The anecdotal information available regarding DIY PAC construction is quite variable and we anticipate that these design parameters may be a significant factor when assessing the efficacy of DIY PACs. For example, fan speed is anticipated to influence the airflow capacity of the fan, and PM 2.5 filtration efficiency of the selected filter is anticipated to be a substantial variable. Filtration ratings are commonly expressed as minimum efficiency reporting values (MERV). In general terms, the higher the MERV rating, the greater filtration efficiency for sub-micron particles. However, this increased efficiency may also result in greater fan resistance and energy consumption. In addition, higher MERV rated filtration mechanisms are typically relatively more expensive. Working hypothesis: We hypothesize that there will be no difference in key PAC performance factors (air flow, noise, percent reductions in PM, and energy usage) associated with DIY PACs constructed and operated under numerous design parameters including filter type, fan speed, and PAC orientation to the room occupant. This Aim will begin prior to and occur simultaneously with Aim 1.
- Explore the spatial and temporal variation in ambient PM 2.5 concentrations associated with uncontrolled wildfire events and Tribally-controlled fire management practices on the Flathead Reservation. The current aim proposes to establish a low-cost, community-based air sensor network for real-time assessment of PM 2.5 concentrations on the Flathead Reservation. The proposed sensor network and outdoor air quality data obtained will be immediately relevant to the indoor air quality quantified in Aims 1 and 2. In addition, the spatial and temporal data obtained will be highly informative for future work to establish a more accurate and robust air quality monitoring method on the Flathead Reservation. Working hypotheses: Ambient PM 2.5 concentrations will be markedly elevated during the larger and more uncontrolled wildfire events, which will significantly impact ambient PM 2.5 concentrations (and by extension indoor concentrations); while, controlled fire management practices will have minimal influence on ambient PM 2.5 concentrations. In addition, we hypothesize that regional air monitoring data may be an accurate predictor of local PM 2.5 concentrations.