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Wildfires pose a direct threat to the property, life, and well-being of the population of Montana, USA, and indirectly to their health through hazardous smoke and gases emitted into the atmosphere. Studies have shown that elevated levels of particulate matter cause impacts to human health ranging from early death, to neurological and immune diseases, to cancer. Although there is currently a network of ground-based air quality sensors (n = 20) in Montana, the geographically sparse network has large gaps and lacks the ability to make accurate predictions for air quality in many areas of the state. Using the random forest method, a predictive model was developed in the Google Earth Engine (GEE) environment to estimate PM2.5 concentrations using satellite-based aerosol optical depth (AOD), dewpoint temperature (DPT), relative humidity (RH), wind speed (WIND), wind direction (WDIR), pressure (PRES), and planetary-boundary-layer height (PBLH). The validity of the prediction model was evaluated using 10-fold cross validation with a R2 value of 0.572 and RMSE of 9.98 µg/m3. The corresponding R2 and RMSE values for 'held-out data' were 0.487 and 10.53 µg/m3. Using the validated prediction model, daily PM2.5 concentration maps (1 km-resolution) were estimated from 2012 to 2023 for the state of Montana. These concentration maps are accessible via an application developed using GEE. The product provides valuable insights into spatiotemporal trends of PM2.5 concentrations, which will be useful for communities to take appropriate mitigation strategies and minimize hazardous PM2.5 exposure. [ABSTRACT FROM AUTHOR]

Small unmanned aerial systems (sUAS) are becoming increasingly popular due to their affordability and logistical ease for repeated surveys. While sUAS-based remote sensing has many applications in water resource management, their applicability and limitations in fluvial settings is not well defined. This study uses a combined thermal-optic sUAS to monitor the seasonal geothermal influence of a 1-km-long reach of the Yellowstone River, paired with in-situ streambed temperature profiles to evaluate geothermal seep interactions with Yellowstone River in Montana, USA. Accurate river water surface elevation along the shoreline was estimated using structure from motion (SfM) photogrammetry digital surface models (DSMs); however, water surface elevations were unreliable in the main river channel. Water temperature in thermal infrared (TIR) orthomosaics was accurate in temperature ranges of tens of degrees (>≈30 °C), but not as accurate in temperature ranges of several degrees (>≈15 °C) as compared to in-situ water temperature measurements. This allowed for identification of geothermal features but limited the ability to identify small-scale temperature changes due to river features, such as pools and riffles. The study concludes that rivers with an average width greater than or equal to 123% of the ground area covered by a TIR image will be difficult to study using structure from motion photogrammetry, given Federal Aviation Administration (FAA) altitude restrictions and sensor field of view. This study demonstrates the potential of combined thermal-optic sUAS systems to collect data over large river systems, and when combined with in-situ measurements, can further increase the sUAS utility in identifying river characteristics. [ABSTRACT FROM AUTHOR]

A disconnect between community perceptions and officially documented Superfund remedial actions and health outcomes may hinder the essential community engagement at Superfund sites. This study evaluates the extent of one such potential disconnect in Butte, Montana, which is part of the largest U.S. Superfund site in the U.S. Since the 1860s, when mining began in Butte, mine waste disposal practices in Butte and surrounding areas have left behind massive deposits that have contaminated the area's soil, sediment, groundwater and surface water with arsenic and heavy metals. Over the last four decades, a substantial amount of remediation work has been completed along with requisite community engagement and health studies at this Superfund site. The potential disconnect was evaluated using a new survey instrument that covered: (a) general environmental health perceptions, (b) mine-waste specific environmental health perceptions, (c) effectiveness of community engagement, (d) knowledge of health outcomes, and (e) demographics. The survey results demonstrated a disconnect in many instances where objective remedial improvements may not have resulted in improved environmental health perceptions in the community. The disconnect was most pronounced in the case of drinking water protection from mine waste and knowledge of health outcomes (cancer incidence rates and children's blood levels). The use of similar environmental health perception measurements may aid responsible agencies in monitoring for and addressing environmental health perception disconnects through better community engagement for the benefit of the impacted communities. • Environmental health perceptions at a Superfund site in the U.S., were evaluated. • A disconnect between perceptions and actual improvements was quantified. • The disconnect was most pronounced in drinking water and health outcomes. • Fundamental redesign of communication processes is required to address the disconnect. [ABSTRACT FROM AUTHOR]