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BACKGROUND: Wildfire smoke exposure has become a growing public health concern, as megafires and fires at the wildland urban interface increase in incidence and severity. Smoke contains many pollutants that negatively impact health and is linked to a number of health complications and chronic diseases. Communicating effectively with the public, especially at-risk populations, to reduce their exposure to this environmental pollutant has become a public health priority. Although wildfire smoke risk communication research has also increased in the past decade, best practice guidance is limited, and most health communications do not adhere to health literacy principles: readability, accessibility, and actionability. This scoping review identifies peer-reviewed studies about wildfire smoke risk communications to identify gaps in research and evaluation of communications and programs that seek to educate the public. METHODS: Four hundred fifty-one articles were identified from Web of Science and PubMed databases. After screening, 21 articles were included in the final sample for the abstraction process and qualitative thematic analysis. Ten articles were based in the US, with the other half in Australia, Canada, Italy, and other countries. Fifteen articles examined communication materials and messaging recommendations. Eight papers described communication delivery strategies. Eleven articles discussed behavior change. Six articles touched on risk communications for vulnerable populations; findings were limited and called for increasing awareness and prioritizing risk communications for at-risk populations. RESULTS: This scoping review found limited studies describing behavior change to reduce wildfire smoke exposure, characteristics of effective communication materials and messaging, and communication delivery strategies. Literature on risk communications, dissemination, and behavior change for vulnerable populations was even more limited. CONCLUSIONS: Recommendations include providing risk communications that are easy-to-understand and adapted to specific needs of at-risk groups. Communications should provide a limited number of messages that include specific actions for avoiding smoke exposure. Effective communications should use mixed media formats and a wide variety of dissemination strategies. There is a pressing need for more intervention research and effectiveness evaluation of risk communications about wildfire smoke exposure, and more development and dissemination of risk communications for both the general public and vulnerable populations.

This study evaluates bushfire smoke as a workplace hazard for firefighters by characterising its chemical composition and potential health risks in Western Australia. Portable Fourier Transform Infrared (FTIR) spectrometry was used to measure airborne chemical concentrations at prescribed burns across five regions, including peat (acid sulphate) fire events. Samples were collected during both flaming and smouldering phases, as well as in perceived "clear" air resting zones. Results indicated that carbon monoxide (CO) was the dominant gas, reaching concentrations of 205 ppm at the fire front, followed by nitrogen monoxide (26 ppm) and methane (19 ppm). Peat fires produced distinct profiles, with ammonia (21.5 ppm) and sulphur dioxide (9.5 ppm) concentrations higher than those observed in typical bushfires. Smouldering phases emitted higher chemical concentrations than flaming phases 75% of the time. Even clear air zones contained measurable chemicals, with CO levels averaging 18 ppm, suggesting that firefighters are not free from exposure during rest periods. These findings highlight the need for fit-for-purpose respiratory protective equipment (RPE) and improved rest protocols to minimise exposure. The study underscores the importance of comprehensive health monitoring programs for firefighters to mitigate long-term health risks. [ABSTRACT FROM AUTHOR]

Wildfire events have increased in frequency and severity across the United States in recent decades. While a growing literature has documented the effects of wildfire smoke exposure on a wide range of health and socioeconomic outcomes, little is known about its impact on consumer behavior and household demand for adaptation in healthcare. We combine a newly developed and digitized dataset on daily wildfire smoke PM2.5 concentrations across the contiguous United States from 2006 to 2019 with weekly NielsenIQ retail scanner data to quantify how wildfire smoke exposure affects retail sales of air purifiers, bottled water, cold remedies, nasal products, cough products, and nutritional products. We find a positive and statistically significant impact of wildfire smoke exposure on the retail sales of these products. Dynamic effects are evident as wildfire smoke exposure in previous weeks also increases current sales. Nonlinear effects arising from the varying intensity of wildfire smoke exposure also reveal distinct patterns of demand for adaptation. We further explore how the effects of wildfire smoke exposure vary with socio-demographic characteristics, focusing on social vulnerability and highlighting the implications of environmental justice. Our results underscore the need for proactive policies to address the increased demand for emergency supplies and healthcare products as household adaptive measures during the wildfire season, particularly targeting socioeconomically vulnerable populations who may be prone to limited access to preventive measures against wildfire smoke. [ABSTRACT FROM AUTHOR]

Despite the increased frequency with which wildfire smoke now blankets portions of world, the effects of smoke on wildlife, and birds in particular, are largely unknown. We used 2 decades of banding data from the San Francisco Bay Bird Observatory to investigate how fine particulate matter (PM2.5)—a major component and indicator of wildfire smoke—influenced capture rates and body condition of 21 passerine or near-passerine bird species. Across all study species, we found a negative effect of acute PM2.5 exposure and a positive effect of chronic PM2.5 exposure on avian capture rates. Together, these findings are indicative of decreased bird activity or local site removal during acute periods of wildfire smoke, but increased activity or site colonization under chronic smoke conditions. Importantly, we also observed a negative relationship between chronic PM2.5 exposure and body mass change in individuals with multiple captures per season. Our results indicate that wildfire smoke likely influences the health and behavior of birds, ultimately contributing to a shift in activity and body condition, with differential short-term versus long-term impacts. Although more research is needed on the mechanisms driving these observed changes in bird health and behavior, as well as validation of these relationships in more areas, our results suggest that wildfire smoke is a potentially frequent large-scale environmental stressor to birds that deserves increasing attention and recognition. [ABSTRACT FROM AUTHOR]

Wildfires pose significant environmental and societal threats, necessitating improved early detection methods. This study investigates the effectiveness of integrating real-time object detection deep learning models (YOLOv8 and RT-DETR) with advanced data augmentation techniques, including StyleGAN2-ADA, for wildfire smoke detection. We evaluated model performance on datasets enhanced with fundamental transformations and synthetic images, focusing on detection accuracy. YOLOv8X demonstrated superior overall performance with AP@0.33 of 0.962 and AP@0.5 of 0.900, while RT-DETR-X excelled in small object detection with a 0.983 detection rate. Data augmentation, particularly StyleGAN2-ADA, significantly enhanced model performance across various metrics. Our approach reduced average detection times to 1.52 min for YOLOv8X and 2.40 min for RT-DETR-X, outperforming previous methods. The models demonstrated robust performance under challenging conditions, like fog and camera noise, providing reassurance of their effectiveness. While false positives remain a challenge, these advancements contribute significantly to early wildfire smoke detection capabilities, potentially mitigating wildfire impacts through faster response times. This research establishes a foundation for more effective wildfire management strategies and underscores the potential of deep learning applications in environmental monitoring. [ABSTRACT FROM AUTHOR]

Wildfires have become common global phenomena concurrent with warmer and drier climates and are now major contributors to ambient air pollution worldwide. Exposure to wildfire smoke has been classically associated with adverse cardiopulmonary health outcomes, especially in vulnerable populations. Recent work has expanded our understanding of wildfire smoke toxicology to include effects on the central nervous system and reproductive function; however, the neurotoxic profile of this toxicant remains ill-explored in an occupational context. Here, we sought to address this by using RNA sequencing to examine transcriptomic signatures in the prefrontal cortex of male mice modeling career wildland firefighter smoke exposure. We report robust changes in gene expression profiles between smoke-exposed samples and filtered air controls, evidenced by 2,862 differentially expressed genes (51.2% increased). We further characterized the functional relevance of these genes highlighting enriched pathways related to synaptic transmission, neuroplasticity, blood–brain barrier integrity, and neurotransmitter metabolism. Additionally, we identified possible contributors to these alterations through protein–protein interaction network mapping, which revealed a central node at ß-catenin and secondary hubs centered around mitochondrial oxidases, the Wnt signaling pathway, and gene expression machinery. The data reported here will serve as the foundation for future experiments aiming to characterize the phenotypic effects and mechanistic underpinnings of occupational wildfire smoke neurotoxicology. [ABSTRACT FROM AUTHOR]

The frequency, duration, and size of wildfires have been increasing, and the inhalation of wildfire smoke particles poses a significant risk to human health. Epidemiological studies have shown that wildfire smoke exposure is positively associated with cognitive and neurological dysfunctions. However, there is a significant gap in knowledge on how wildfire smoke exposure can affect the blood–brain barrier and cause molecular and cellular changes in the brain. Our study aims to determine the acute effect of smoldering eucalyptus wood smoke extract (WSE) on brain endothelial cells for potential neurotoxicity in vitro. Primary human brain microvascular endothelial cells (HBMEC) and immortalized human brain endothelial cell line (hCMEC/D3) were treated with different doses of WSE for 24 h. WSE treatment resulted in a dose-dependent increase in IL-8 in both HBMEC and hCMEC/D3. RNA-seq analyses showed a dose-dependent upregulation of genes involved in aryl hydrocarbon receptor (AhR) and nuclear factor erythroid 2-related factor 2 (NRF2) pathways and a decrease in tight junction markers in both HBMEC and hCMEC/D3. When comparing untreated controls, RNA-seq analyses showed that HBMEC have a higher expression of tight junction markers compared to hCMEC/D3. In summary, our study found that 24 h WSE treatment increases IL-8 production dose-dependently and decreases tight junction markers in both HBMEC and hCMEC/D3 that may be mediated through the AhR and NRF2 pathways, and HBMEC could be a better in vitro model for studying the effect of wood smoke extract or particles on brain endothelial cells. [ABSTRACT FROM AUTHOR]

Incubation of an empty nest is a rarely detected phenomenon in birds but has been documented in a diversity of species. The causes of this breeding anomaly are unclear, but previous accounts have occurred in regions with elevated air pollution. We provide a detailed account of a female Black-throated Blue Warbler (Setophaga caerulescens) incubating an empty nest for 8 d at the Hubbard Brook Experimental Forest, New Hampshire, USA, May–June 2023, and explore possible explanations based on a literature review of this breeding anomaly. Our observation coincided with the presence of smoke from widespread wildfires in Quebec, Canada. The fires were caused by record temperatures and dry conditions. Wildfire smoke increased air particle pollution. We found 231 published accounts of 11 species incubating empty nests. Cavity-nesters in Europe comprised 45% of species (5 of 11) and 96% of accounts (225 of 231). Although many accounts lacked a clear explanation, the most common factors hypothesized to explain incubating empty nests were exposure to environmental pollution (81% of accounts, 167 of 206), calcium deficiency from environmental acidification (19% of accounts, 40 of 206), and disease and/or infertility (4% of accounts, 8 of 206). Our synthesis of published observations highlights the need for more data on individuals expressing this unusual behavior. Such data would improve our understanding of how egg laying and reproductive success respond to intrinsic and environmental factors, including wildfire emissions, which are forecasted to increase with climate change. [ABSTRACT FROM AUTHOR]

Climate change and wildfire effects have continued to receive great attention in recent times due to the impact they render on the environment and most especially to the field of agriculture. The purpose of this study was to assess the synergistic impacts of climate change and wildfires on agricultural sustainability. This study adopted a cross-sectional survey design based on the quantitative research approach. Data were collected from 340 environmental experts using an online questionnaire. The results showed that extreme weather events such as heavy rains or extreme droughts negatively influence agricultural sustainability in Europe. The results showed that disruptions in ecosystems caused by climate change have a significant positive impact on agricultural sustainability in Europe. Furthermore, forest regeneration after wildfires showed statistically significant positive influence on agricultural sustainability in Europe. The economic impact of fire on crops, cattle, and farms can be estimated. This information can be used to develop and plan agricultural regions near fire-prone areas; choose the best, most cost-effective, and longest-lasting cultivar; and limit fire risk. It is also clear that increased wildfire smoke negatively affects agricultural sustainability. [ABSTRACT FROM AUTHOR]

Increasing impacts of wildfires on Western US air quality highlights the need for forecasts of smoke emissions based on dynamic modeled wildfires. This work utilizes knowledge of weather, fuels, topography, and firefighting, combined with machine learning and other statistical methods, to generate 1‐ and 2‐day forecasts of fire radiative energy (FRE). The models are trained on data covering 2019 and 2021 and evaluated on data for 2020. For the 1‐day (2‐day) forecasts, the random forest model shows the most skill, explaining 48% (25%) of the variance in observed daily FRE when trained on all available predictors compared to the 2% (<0%) of variance explained by persistence for the extreme fire year of 2020. The random forest model also shows improved skill in forecasting day‐to‐day increases and decreases in FRE, with 28% (39%) of observed increase (decrease) days predicted, and increase (decrease) days are identified with 62% (60%) accuracy. Error in the random forest increases with FRE, and the random forest tends toward persistence under severe fire weather. Sensitivity analysis shows that near‐surface weather and the latest observed FRE contribute the most to the skill of the model. When the random forest model was trained on subsets of the training data produced by agencies (e.g., the Canadian or US Forest Services), comparable if not better performance was achieved (1‐day R2 = 0.39–0.48, 2‐day R2 = 0.13–0.34). FRE is used to compute emissions, so these results demonstrate potential for improved fire emissions forecasts for air quality models. Plain Language Summary: Increasing wildfire smoke is undoing decades of air quality progress, yet air quality forecasts often miss the most intense smoke events. This is because forecasted smoke is released at constant rates whereas the rate of smoke release from real wildfires varies in time. In this work we teach a machine learning algorithm to predict the daily change in fire heat output, a quantity that is used to calculate wildfire emissions. The machine learning algorithm uses information regarding weather, fuel moisture and amount, and firefighting efforts to make its predictions. We also tried to predict the daily change in fire heat output using only weather information but found the machine learning method to be more successful. Many federal agencies have their own ways of tracking fire weather and fuel moisture, and in this paper, we show that we can apply machine learning to the data from any of several agencies and get the same level of forecasting skill. Key Points: Random forest models trained on weather, fuel, and firefighting data surpass persistence and weather‐based methods to predict fire energyRandom forest models beat persistence across states, for most days in the 2020 fire season, and across levels of fire severityFire weather and latest fire energy predictors add most skill to the random forest; models using agency weather data perform similarly [ABSTRACT FROM AUTHOR]

Quantifying the variable impacts of wildfire smoke on ozone air quality is challenging. Here we use airborne measurements from the 2018 Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE‐CAN) to parameterize emissions of reactive nitrogen (NOy) from wildfires into peroxyacetyl nitrate (PAN; 37%), NO3− (27%), and NO (36%) in a global chemistry‐climate model with 13 km spatial resolution over the contiguous US. The NOy partitioning, compared with emitting all NOy as NO, reduces model ozone bias in near‐fire smoke plumes sampled by the aircraft and enhances ozone downwind by 5–10 ppbv when Canadian smoke plumes travel to Washington, Utah, Colorado, and Texas. Using multi‐platform observations, we identify the smoke‐influenced days with daily maximum 8‐hr average (MDA8) ozone of 70–88 ppbv in Kennewick, Salt Lake City, Denver and Dallas. On these days, wildfire smoke enhanced MDA8 ozone by 5–25 ppbv, through ozone produced remotely during plume transport and locally via interactions of smoke plume with urban emissions. Plain Language Summary: Wildfires have torn across western North America over the last decade. Smoke from wildland fires in Canada can travel thousands of kilometers to US cities and reacts with urban pollution to create harmful ozone, a criteria pollutant regulated by the US Environmental Protection Agency. Accurately quantifying this impact is needed to inform US air quality policy, but is challenging due to complex physical and chemical processes. In this study, we analyze surface and airborne measurements, alongside a new variable‐resolution global chemistry‐climate model, to better understand these processes. We show that the near‐field conversion of nitrogen oxide (NOx) emissions from wildfires to peroxyacetyl nitrate (PAN) and other more oxidized forms reduces their localized impacts on ozone. PAN is the principal tropospheric reservoir for NOx radicals. When aged smoke plumes descend southward from Canada toward US cities, higher temperatures cause PAN to decompose and thus help production of ozone during smoke transport. On days when the observed ozone levels exceed the air quality limit (70 ppbv for 8‐hr average), wildfire smoke can contribute 5–25 ppbv. Key Points: Sequestration of wildfire NOx emissions in Canada as peroxyacetyl nitrate (PAN) enhances the downwind impacts on US O3 air qualityPyrogenic volatile organic compounds and PAN decomposition increase the contribution of aged Canadian smoke plumes to O3 in US citiesAccounting for these effects in a high‐resolution chemistry‐climate model improves simulation of smoke‐impacted high‐O3 events in US cities [ABSTRACT FROM AUTHOR]

Living conditions are an important modifier of individual health outcomes and may lead to higher allostatic load (AL). However, housing-induced cardiovascular and immune effects contributing to altered environmental responsiveness remain understudied. This investigation was conducted to examine the influence of enriched (EH) versus depleted housing (DH) conditions on cardiopulmonary functions, systemic immune responses, and allostatic load in response to a single wildfire smoke (WS) exposure in mice. Male and female C57BL/6J mice were divided into EH or DH for 22 weeks, and cardiopulmonary assessments measured before and after exposures to either one-hr filtered air (FA) or flaming eucalyptus WS exposure. Male and female DH mice exhibited increased heart rate (HR) and left ventricular mass (LVM), as well as reduced stroke volume and end diastolic volume (EDV) one week following exposure to WS. Female DH mice displayed significantly elevated levels of IL-2, IL-17, corticosterone and hemoglobin A1c (HbA1c) following WS, while female in EH mice higher epinephrine levels were detected. Female mice exhibited higher AL than males with DH, which was potentiated post-WS exposure. Thus, DH increased susceptibility to extreme air pollution in a gender-dependent manner suggesting that living conditions need to be evaluated as a modifier of toxicological responses. [ABSTRACT FROM AUTHOR]

The purpose of this study was to understand the experiences of agricultural workers during periods of heat and wildfire smoke exposure and to support the development and implementation of protective workplace interventions. Using community-engaged research and the Center for Disease Control (CDC) framework for policy evaluation, a qualitative descriptive study was conducted with current and former agricultural workers in Central Washington (WA). Twelve participants answered semi-structured questions via interviews or by attending a focus group. Interviews and focus groups were conducted in Spanish, recorded, transcribed, and translated into English; one interview was conducted in English. Using Braun and Clarke's Reflexive Thematic Analysis, five themes were identified among workers from various worksites: 1) Extreme weather and working conditions are becoming increasingly hazardous to worker health, 2) Employers and supervisors lack training and education on current labor laws, and health and safety rules, 3) Employers and supervisors use intimidation and retaliation to ensure productivity and to evoke feelings of replaceability among workers, 4) Workers do not trust regulatory agencies to enforce rules or hold employers accountable, 5) Solutions to climate-driven problems in the agricultural industry need to value worker health and safety, not just productivity. Participants reported experiencing adverse health symptoms related to heat and smoke exposure at work. Workers proposed solutions including improving education, training, and communication, and increased enforcement of existing and forthcoming occupational health and safety rules. The agricultural workforce is essential for ensuring a robust food supply and is facing extreme weather events due to climate change. Western states impacted by wildfires and heat are working to develop and implement occupational health and safety rules. Developing effective policies and interventions inclusive of worker perspectives is critical to adapt to a changing climate, retain a stable workforce and promote optimal health. [ABSTRACT FROM AUTHOR]

Black carbon (BC) is a critical environmental pollutant with significant implications for human health. This study aims to quantify personal exposure to BC by focusing on the influence of microenvironments and time-activity patterns in the Rio Grande Valley (RGV) region of South Texas, USA. Over eight days in March and April 2023, a portable aethalometer and GPS tracking instruments were used to measure BC exposure among a study participant, alongside recording the time spent in various microenvironments. The BC measurements were correlated to the time activity patterns to calculate BC inhaled dosage values thereby elucidating its impact on human health. The mean values for different hours ranged from the lowest,0.26 µg/m³ ± 0.29 at 02:00, to the highest, 1.07 µg/m³ ± 1.40 at 17:00. The study also identified peak BC levels in areas near major roadways and airports. Outdoor activities accounted for 31% - 33% of the BC inhaled dosage on weekends, which was much higher than the 0.10% - 1.42% contribution observed on weekdays. The results also reflect a negative impact of Mexican wildfire activities on black carbon in this border region. This research provides insights into one of the first black carbon measurement studies conducted in the South Texas, U.S.– Tamaulipas State, Mexico border region.

The results of two previously published reports of the events and impacts of the Campfire wildfire smoke exposure that occurred in California in 2018 are amplified from the point of view of the potential toxic mechanism involved. The Campfire wildfire led to the exposure of a breeding colony of macaque monkeys (Macaca mulatta) during the peak of their breeding season in 2018-2019. Considering the timing, adverse effects, and endocrine implications reported, the cumulative evidence points to an early toxic sensitive period that can lead to birth defects in higher primates and human pregnancies. This deeper inspection of the published observations provides important caveats and useful guidance for future investigators. The unique higher primate placental-adrenal-brain axis may limit the use of many traditional toxicologic approaches. Retrospective neurological evaluations of human fetuses exposed to air pollutants during organogenesis and subsequent retrospective characterization of air samples using in vitro and animal models may be the best procedures to follow.

Worsening wildfire seasons in recent years are reversing decadal progress on the reduction of harmful air pollutants in the US, particularly in Western states. Measurements of the contributions of wildfire smoke to ambient air pollutants, such as fine particulate matter (PM2.5), at fine resolution scales would be valuable to public health research on climate vulnerable populations and compound climate risks. We estimate the influence of wildfire smoke emissions on daily PM2.5 at fine-resolution, 3 km, for California 2011–2020, using a geostatistical modeled ambient PM2.5 estimate and wildfire smoke plume data from NOAA Hazard Mapping System. Additionally, we compare this product with the US Environmental Protection Agency (EPA) daily and annual standards for PM2.5 exposure. Our results show wildfires significantly influence PM2.5 in California and nearly all exceedances of the daily US EPA PM2.5 standard were influenced by wildfire smoke, while annual exceedances were increasingly attributed to wildfire smoke influence in recent years. This wildfire-influenced PM2.5 product can be applied to public health research to better understand source-specific air pollution impacts and assess the combination of multiple climate hazard risks. [ABSTRACT FROM AUTHOR]

Background: Wildfires are a global concern due to their wide-ranging environmental, economic, and public health impacts. Climate change contributes to an increase in the frequency and intensity of wildfires making smoke exposure a more significant and recurring health concern for individuals with airway diseases. Some of the most prominent effects of wildfire smoke exposure are asthma exacerbations and allergic airway sensitization. Likely due to the delayed recognition of its health impacts in comparison with cigarette smoke and industrial or traffic-related air pollution, research on the composition, the mechanisms of toxicity, and the cellular/molecular pathways involved is poor or non-existent. Summary: This review discusses potential underlying pathological mechanisms of wildfire-smoke-related allergic airway disease and asthma. We focused on major gaps in understanding the role of wildfire smoke composition in the development of airway disease and the known and potential mechanisms involving cellular and molecular players of oxidative injury at the epithelial barrier in airway inflammation. We examine how PM2.5, VOCs, O3, endotoxin, microbes, and toxic gases may affect oxidative stress and inflammation in the respiratory mucosal barrier. We discuss the role of AhR in mediating smoke's effects in alarmin release and IL-17A production and how glucocorticoid responsiveness may be impaired by IL-17A-induced signaling and epigenetic changes leading to steroid-resistant severe airway inflammation. Key Message: Effective mitigation of wildfire-smoke-related respiratory health effects would require comprehensive research efforts aimed at a better understanding of the immune regulatory effects of wildfire smoke in respiratory health and disease. [ABSTRACT FROM AUTHOR]

Background: Population growth and climate change have led to more frequent and larger wildfires, increasing the exposure of individuals to wildfire smoke. Notably, asthma exacerbations and allergic airway sensitization are prominent outcomes of such exposure. Summary: Key research questions relate to determining the precise impact on individuals with asthma, including the severity, duration, and long-term consequences of exacerbations. Identifying specific risk factors contributing to vulnerability, such as age, genetics, comorbidities, or environmental factors, is crucial. Additionally, reliable biomarkers for predicting severe exacerbations need exploration. Understanding the long-term health effects of repeated wildfire smoke exposures in individuals with asthma and addressing healthcare disparities are important research areas. Key Messages: This review discusses the need for comprehensive research efforts to better grasp wildfire smoke-induced respiratory health, particularly in vulnerable populations such as farmworkers, firefighters, pregnant women, children, the elderly, and marginalized communities. Effective mitigation would require addressing the current limitations we face by supporting research aimed at a better understanding of wildfire smoke-induced airway disease. [ABSTRACT FROM AUTHOR]

Wildfire activity is increasing globally. The resulting smoke plumes can travel hundreds to thousands of kilometers, reflecting or scattering sunlight and depositing particles within ecosystems. Several key physical, chemical, and biological processes in lakes are controlled by factors affected by smoke. The spatial and temporal scales of lake exposure to smoke are extensive and under‐recognized. We introduce the concept of the lake smoke‐day, or the number of days any given lake is exposed to smoke in any given fire season, and quantify the total lake smoke‐day exposure in North America from 2019 to 2021. Because smoke can be transported at continental to intercontinental scales, even regions that may not typically experience direct burning of landscapes by wildfire are at risk of smoke exposure. We found that 99.3% of North America was covered by smoke, affecting a total of 1,333,687 lakes ≥10 ha. An incredible 98.9% of lakes experienced at least 10 smoke‐days a year, with 89.6% of lakes receiving over 30 lake smoke‐days, and lakes in some regions experiencing up to 4 months of cumulative smoke‐days. Herein we review the mechanisms through which smoke and ash can affect lakes by altering the amount and spectral composition of incoming solar radiation and depositing carbon, nutrients, or toxic compounds that could alter chemical conditions and impact biota. We develop a conceptual framework that synthesizes known and theoretical impacts of smoke on lakes to guide future research. Finally, we identify emerging research priorities that can help us better understand how lakes will be affected by smoke as wildfire activity increases due to climate change and other anthropogenic activities. [ABSTRACT FROM AUTHOR]

In the summer and fall of 2018 and 2020, major wildfires in Northern California (USA) impacted the San Francisco Bay Area. The remote 2018 and 2020 wildfires produced the highest PM2.5 concentrations experienced in the Tri-Valley of the East Bay Area during those two years. The Tri-Valley is composed of the San Ramon, Amador, and Livermore Valleys, surrounded by local terrain that creates a small airshed. In 1967, the California Air Resources Board created 15 Air Basins defined by regional geography, topographic and meteorological conditions. Airshed is sometimes synonymous with an urban-scale component of an Air Basin. We use airshed as a Tri-Valley component of the Bay Area Air Basin. This airshed spans across two counties (Contra Costa and Alameda) and encompasses four cities: San Ramon, Dublin, Pleasanton, and Livermore. PurpleAir (PA) sensors provided good geographic coverage of variation in PM2.5 in the Tri-Valley airshed. Several studies have established significant health effects from wildfire plumes by associating daily hospital visits with PM2.5 air quality data at local and regional scales. We hypothesize that during the wildfire smoke periods of 2018 and 2020 in the Tri-Valley area, there was an increase in hospitalizations and ED visits for respiratory (asthma and COPD-related) health effects, as compared to the same time periods during years with less fire activity. The primary goal of this study was to confirm health effects from wildfire plumes on a community scale using 5 years of publicly-available health data. However, with only monthly hospitalization data available, directly linking respiratory hospital and emergency department (ED) visits with PM2.5 concentrations was unsuccessful. Also, because COVID-19 masked all other causes of hospital visits in 2020, that year was ultimately eliminated from this study. However, visits during November 2018 being much higher than any other November in 2016, 2017, and 2019 implied a potential cause and effect. Daily hospitalization and air quality data are required to quantify any relationship by regression analysis. These findings help inform future studies on the health effects of air quality at community scales. [ABSTRACT FROM AUTHOR]

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An oxidizing and harmful pollutant gas, tropospheric ozone is a product of a complex set of photochemical reactions that can make it difficult to enact effective control measures. A better understanding of its precursors including volatile organic compounds (VOCs) and nitrogen oxides (NOx) and their spatial distribution can enable policymakers to focus their control efforts. In this study we used low-cost sensors (LCSs) to increase the spatial resolution of an existing NO2 monitoring network in addition to VOC sampling to better understand summer ozone formation in Maricopa County, Arizona, and observed that afternoon O3 values at the downwind sites were significantly correlated, ~0.27, to the morning NO2 × rate values at the urban sites. Additionally, we looked at the impact of wildfire smoke on ozone exceedances and compared non-smoke days to smoke days. The average O3 on smoke days was approximately 20% higher than on non-smoke days, however, the average NO2 concentration multiplied by estimated photolysis rate (NO2 × rate) values were only 2% higher on smoke days. Finally, we evaluated the ozone sensitivity of the region by calculating HCHO/NO2 ratios using three different datasets: ground, satellite, and model. Although the satellite dataset produced higher HCHO/NO2 ratios than the other datasets, when the proper regime thresholds are applied the three datasets consistently show transition and VOC-limited O3 production regimes over the Phoenix metro area. This suggests a need to implement more VOC emission controls in order to reach O3 attainment in the county. [ABSTRACT FROM AUTHOR]

Background: Western Montana, USA, experiences complex air pollution patterns with predominant exposure sources from summer wildfire smoke and winter wood smoke. In addition, climate change related temperatures events are becoming more extreme and expected to contribute to increases in hospital admissions for a range of health outcomes. Evaluating while accounting for these exposures (air pollution and temperature) that often occur simultaneously and may act synergistically on health is becoming more important. Methods: We explored short-term exposure to air pollution on children's respiratory health outcomes and how extreme temperature or seasonal period modify the risk of air pollution-associated healthcare events. The main outcome measure included individual-based address located respiratory-related healthcare visits for three categories: asthma, lower respiratory tract infections (LRTI), and upper respiratory tract infections (URTI) across western Montana for ages 0–17 from 2017–2020. We used a time-stratified, case-crossover analysis with distributed lag models to identify sensitive exposure windows of fine particulate matter (PM2.5) lagged from 0 (same-day) to 14 prior-days modified by temperature or season. Results: For asthma, increases of 1 µg/m3 in PM2.5 exposure 7–13 days prior a healthcare visit date was associated with increased odds that were magnified during median to colder temperatures and winter periods. For LRTIs, 1 µg/m3 increases during 12 days of cumulative PM2.5 with peak exposure periods between 6–12 days before healthcare visit date was associated with elevated LRTI events, also heightened in median to colder temperatures but no seasonal effect was observed. For URTIs, 1 unit increases during 13 days of cumulative PM2.5 with peak exposure periods between 4–10 days prior event date was associated with greater risk for URTIs visits that were intensified during median to hotter temperatures and spring to summer periods. Conclusions: Delayed, short-term exposure increases of PM2.5 were associated with elevated odds of all three pediatric respiratory healthcare visit categories in a sparsely population area of the inter-Rocky Mountains, USA. PM2.5 in colder temperatures tended to increase instances of asthma and LRTIs, while PM2.5 during hotter periods increased URTIs. [ABSTRACT FROM AUTHOR]

Wildfire activity is increasing around the world, concurrent with climate change, and mitigation strategies for protecting vulnerable populations are desperately needed. Because inhaled particles are deleterious to respiratory health, particularly among older adults with co-morbidities, we engaged maintenance personnel working in long term care facilities located in the Western US. Our objective was to identify opportunities to build resilience during wildfire smoke events. We implemented a virtual workshop that addressed wildfire smoke health impacts as well as strategies to assess and maintain indoor air quality. A total of 24 maintenance personnel attended the virtual workshop and 14 participated in a quantitative survey. Workshop attendees found value in the material and there was enthusiasm for educational resources and enhancing indoor air quality. Four months later, four maintenance staff participated in a follow-up interview. Our qualitative assessment revealed the following themes: awareness and prioritization, application of knowledge, barriers, and educational resources. Access to real-time actionable air quality data was a consistent feature across these themes. Maintenance personnel could play a key role in a facility's ability to prepare for and respond to wildfire smoke events, and this study highlights potential challenges and opportunities to involving them in resilience building strategies. [ABSTRACT FROM AUTHOR]

IntroductionExposure to harmful aerosols is of increasing public health concern due to the SARS-CoV-2 pandemic and wildland fires. These events have prompted risk reduction behaviors, notably the use of disposable respiratory protection. This project investigated whether craniofacial morphology impacts the efficiency of disposable masks (N95, KN95, surgical masks, KF94) most often worn by the public to protect against toxic and infectious aerosols. This project was registered with ClinicaltTrials.gov (NCT05388201; registration May 18, 2022).MethodsOne-hundred participants (50 men, 50 women) visited the Environmental Protection Agency’s Human Studies Facility in Chapel Hill, NC between 2022-2023. Craniometrics and 3D scans were used to separate participants into four clusters. Boosting and elastic net regression yielded five measurements (bizygomatic breadth, nose length, bizygomatic nasal arc, neck circumference, ear breadth) that were the best predictors of filtration efficiency based on overall model fit. Fitted filtration efficiency was quantified for each mask at baseline and when tightened using an ear-loop clip.ResultsThe mean unmodified mask performance ranged from 55.3% (15.7%) in the large KF94 to 69.5% (12.3%) in the KN95. Modified performance ranged from 66.3% (9.4%) in the surgical to 80.7% (12.0%) in the KN95. Clusters with larger face width and neck circumference had higher unmodified mask efficiency. Larger nose gap area and nose length decreased modified mask performance.DiscussionWe identify face width, nose size, nose shape, neck circumference, and ear breadth as specific features that modulate disposable mask fit in both unmodified and modified conditions. This information can optimize guidance on respiratory protection afforded by disposable ear-loop masks.

Abstract Quantifying the variable impacts of wildfire smoke on ozone air quality is challenging. Here we use airborne measurements from the 2018 Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE‐CAN) to parameterize emissions of reactive nitrogen (NOy) from wildfires into peroxyacetyl nitrate (PAN; 37%), NO3− (27%), and NO (36%) in a global chemistry‐climate model with 13 km spatial resolution over the contiguous US. The NOy partitioning, compared with emitting all NOy as NO, reduces model ozone bias in near‐fire smoke plumes sampled by the aircraft and enhances ozone downwind by 5–10 ppbv when Canadian smoke plumes travel to Washington, Utah, Colorado, and Texas. Using multi‐platform observations, we identify the smoke‐influenced days with daily maximum 8‐hr average (MDA8) ozone of 70–88 ppbv in Kennewick, Salt Lake City, Denver and Dallas. On these days, wildfire smoke enhanced MDA8 ozone by 5–25 ppbv, through ozone produced remotely during plume transport and locally via interactions of smoke plume with urban emissions.

Abstract Background Wildfire smoke contributes substantially to the global disease burden and is a major cause of air pollution in the US states of Oregon and Washington. Climate change is expected to bring more wildfires to this region. Social media is a popular platform for health promotion and a need exists for effective communication about smoke risks and mitigation measures to educate citizens and safeguard public health. Methods Using a sample of 1,287 Tweets from 2022, we aimed to analyze temporal Tweeting patterns in relation to potential smoke exposure and evaluate and compare institutions’ use of social media communication best practices which include (i) encouraging adoption of smoke-protective actions; (ii) leveraging numeric, verbal, and Air Quality Index risk information; and (iii) promoting community-building. Tweets were characterized using keyword searches and the Linguistic Inquiry and Word Count (LIWC) software. Descriptive and inferential statistics were carried out. Results 44% of Tweets in our sample were authored between January-August 2022, prior to peak wildfire smoke levels, whereas 54% of Tweets were authored during the two-month peak in smoke (September-October). Institutional accounts used Twitter (or X) to encourage the adoption of smoke-related protective actions (82% of Tweets), more than they used it to disseminate wildfire smoke risk information (25%) or promote community-building (47%). Only 10% of Tweets discussed populations vulnerable to wildfire smoke health effects, and 14% mentioned smoke mitigation measures. Tweets from Washington-based accounts used significantly more verbal and numeric risk information to discuss wildfire smoke than Oregon-based accounts (p = 0.042 and p = 0.003, respectively); however, Tweets from Oregon-based accounts on average contained a higher percentage of words associated with community-building language (p

Abstract Background Wildfire smoke exposure has become a growing public health concern, as megafires and fires at the wildland urban interface increase in incidence and severity. Smoke contains many pollutants that negatively impact health and is linked to a number of health complications and chronic diseases. Communicating effectively with the public, especially at-risk populations, to reduce their exposure to this environmental pollutant has become a public health priority. Although wildfire smoke risk communication research has also increased in the past decade, best practice guidance is limited, and most health communications do not adhere to health literacy principles: readability, accessibility, and actionability. This scoping review identifies peer-reviewed studies about wildfire smoke risk communications to identify gaps in research and evaluation of communications and programs that seek to educate the public. Methods Four hundred fifty-one articles were identified from Web of Science and PubMed databases. After screening, 21 articles were included in the final sample for the abstraction process and qualitative thematic analysis. Ten articles were based in the US, with the other half in Australia, Canada, Italy, and other countries. Fifteen articles examined communication materials and messaging recommendations. Eight papers described communication delivery strategies. Eleven articles discussed behavior change. Six articles touched on risk communications for vulnerable populations; findings were limited and called for increasing awareness and prioritizing risk communications for at-risk populations. Results This scoping review found limited studies describing behavior change to reduce wildfire smoke exposure, characteristics of effective communication materials and messaging, and communication delivery strategies. Literature on risk communications, dissemination, and behavior change for vulnerable populations was even more limited. Conclusions Recommendations include providing risk communications that are easy-to-understand and adapted to specific needs of at-risk groups. Communications should provide a limited number of messages that include specific actions for avoiding smoke exposure. Effective communications should use mixed media formats and a wide variety of dissemination strategies. There is a pressing need for more intervention research and effectiveness evaluation of risk communications about wildfire smoke exposure, and more development and dissemination of risk communications for both the general public and vulnerable populations.

This study evaluates bushfire smoke as a workplace hazard for firefighters by characterising its chemical composition and potential health risks in Western Australia. Portable Fourier Transform Infrared (FTIR) spectrometry was used to measure airborne chemical concentrations at prescribed burns across five regions, including peat (acid sulphate) fire events. Samples were collected during both flaming and smouldering phases, as well as in perceived “clear” air resting zones. Results indicated that carbon monoxide (CO) was the dominant gas, reaching concentrations of 205 ppm at the fire front, followed by nitrogen monoxide (26 ppm) and methane (19 ppm). Peat fires produced distinct profiles, with ammonia (21.5 ppm) and sulphur dioxide (9.5 ppm) concentrations higher than those observed in typical bushfires. Smouldering phases emitted higher chemical concentrations than flaming phases 75% of the time. Even clear air zones contained measurable chemicals, with CO levels averaging 18 ppm, suggesting that firefighters are not free from exposure during rest periods. These findings highlight the need for fit-for-purpose respiratory protective equipment (RPE) and improved rest protocols to minimise exposure. The study underscores the importance of comprehensive health monitoring programs for firefighters to mitigate long-term health risks.

Wildfires pose significant environmental and societal threats, necessitating improved early detection methods. This study investigates the effectiveness of integrating real-time object detection deep learning models (YOLOv8 and RT-DETR) with advanced data augmentation techniques, including StyleGAN2-ADA, for wildfire smoke detection. We evaluated model performance on datasets enhanced with fundamental transformations and synthetic images, focusing on detection accuracy. YOLOv8X demonstrated superior overall performance with AP@0.33 of 0.962 and AP@0.5 of 0.900, while RT-DETR-X excelled in small object detection with a 0.983 detection rate. Data augmentation, particularly StyleGAN2-ADA, significantly enhanced model performance across various metrics. Our approach reduced average detection times to 1.52 min for YOLOv8X and 2.40 min for RT-DETR-X, outperforming previous methods. The models demonstrated robust performance under challenging conditions, like fog and camera noise, providing reassurance of their effectiveness. While false positives remain a challenge, these advancements contribute significantly to early wildfire smoke detection capabilities, potentially mitigating wildfire impacts through faster response times. This research establishes a foundation for more effective wildfire management strategies and underscores the potential of deep learning applications in environmental monitoring.

Wildfires are increasing across the USA. While smoke events affect human exposure and air quality, wildfire smoke effects on ecosystem‐atmosphere interactions are poorly understood. We investigate smoke effects on biogenic volatile organic compound (VOC) emissions and photosynthesis for ponderosa pines. During several wildfire smoke events, we observed photosynthetic reduction with evidence for stomatal plugging and changes in leaf‐level uptake and emission of both biogenic and wildfire VOCs. During intense smoke events, photosynthesis and VOC emissions were almost entirely suppressed, but increased dramatically upon stomatal opening. We propose four types of VOC responses to this burst in stomatal opening: post‐burst emissions, pulsed emissions, surge emissions, and post‐burst uptake. Our observations suggest that wildfire smoke can affect plant physiology and leaf‐atmosphere gas exchange. Plain Language Summary: Wildfires are becoming more prevalent in the United States. Wildfire smoke affects human health and air quality, but we know little about how smoke interacts with plants, or the subsequent feedback with the atmosphere. We present results from a field experiment during which smoke repeatedly spread across a pine forest. We measured smoke‐induced changes in plant physiology (namely photosynthesis) and a suite of chemical emissions. During prolonged periods of intense smoke, we found that both photosynthesis and leaf emissions of chemical compounds decreased. When we induced photosynthesis, we observed a burst of different chemicals and identified several different pathways for these chemical releases. Further analyses suggest that smoke intensity and exposure may change the known relationship between emissions and temperature. Key Points: Wildfire smoke interacts with stomates and leaf surfaces, suppressing photosynthesis and stomatal conductanceIntense smoke can alter emissions and uptake of biogenic and other volatile organic compounds through three mechanismsThe effects of wildfires on photosynthetic capacity and leaf emissions appear proportional to the intensity and duration of smoke events [ABSTRACT FROM AUTHOR]

Unhealthy air quality conditions can strongly affect long-term human health and wellbeing, yet many air quality data products focus on near real-time alerts or short-term forecasts. Understanding the full state of air quality also requires examining the longer term frequency and intensity of poor air quality at ground level, and how it might change over time. We present a new modeling framework to compute climate-adjusted estimates of air quality hazards for the contiguous United States (CONUS) at 10 km horizontal resolution. The framework blends results from statistical, machine-learning, and climate- chemistry models -- including a bias-adjusted version of the EPA Community Multiscale Air Quality Model (CMAQ) time series as described in (Wilson et al., 2022) -- for ground-level ozone, anthropogenic fine particulate matter (PM2.5), and wildfire smoke PM2.5 into consistent estimates of days exceeding the "unhealthy for sensitive groups" (orange colored) classification on the EPA Air Quality Index for 2023 and 2053. We find that joint PM2.5 and ozone orange+ days range from 1 day to 41 days across CONUS, with a median value of 2 days, across all years. Considering all properties across CONUS, we find that 63.5% percent are exposed to at least one orange or greater day in 2023, growing to 72.1% in 2053. For a 7-day threshold, 3.8% and 5.7% of properties are exposed in 2023 and 2053, respectively. Our results also support the identification of which parts of the country are most likely to be impacted by additional climate-related air quality risks. With growing evidence that even low levels of air pollution are harmful, these results are an important step forward in empowering individuals to understand their air quality risks both now and into the future. [ABSTRACT FROM AUTHOR]

In response to increasing wildfire risks, California plans to expand the use of prescribed fire. We characterized the anticipated change in health impacts from exposure to smoke under a future fire‐management scenario relative to a historical period (2008–2016). Using dispersion models, we estimated daily fine particulate matter (PM2.5) emissions from hypothetical future prescribed fires on 500,000‐acres classified as high priority. To evaluate health impacts, we calculated excess daily cardiorespiratory emergency department visit rates attributed to all‐source PM2.5, distinguishing the portion of the burden attributed to prescribed fire. The total burden was differentiated by fire type and by smoke strata‐specific days to calculate strata‐specific burden rates, which were then applied to estimate the burden in the future scenario. This analysis suggests that the exposure to prescribed fire smoke, measured as the number of persons exposed per year, would be 15 times greater in the future. However, these exposures were associated with lower concentrations compared to the historical period. The increased number of exposure days led to an overall increase in the future health burden. Specifically, the northern, central, and southern regions experienced the largest burden increase. This study introduces an approach that integrates spatiotemporal exposure differences, baseline morbidity, and population size to assess the impacts of prescribed fire under a future scenario. The findings highlight the need to consider both the level and frequency of exposure to guide strategies to safeguard public health as well as aid forest management agencies in making informed decisions to protect communities while mitigating wildfire risks. Plain Language Summary: Prescribed fire is a forest management strategy for reducing the risks of wildfires. While some fires are ecologically beneficial, smoke from fires is a major source of airborne particle pollution, which is harmful to human health. This study examined the change in health impacts resulting from an expected increase in the use of prescribed fire within California's high‐priority wildfire risk areas. We used daily counts of cardiorespiratory emergency department visits attributed to air quality combined with model‐generated measures of smoke pollution to estimate health impacts. We compared exposures and the associated health burden on days impacted by wildfire or prescribed fire smoke in the past to the impacts in the hypothetical future scenario with increased prescribed fire. Projections of future prescribed burning in high priority areas suggest that more people would experience smoke more often, although exposures would occur at lower concentrations. With more frequent lower‐level exposure days near populated areas, the health burden would increase relative to past prescribed fire. Understanding the potential impact of prescribed fire may simultaneously help protect public health and increase safety from wildfires. Key Points: A California‐based model of future prescribed burning in high‐priority wildfire risk areas suggested more people will experience smokeAn increased number of exposure days in the future scenario led to an overall increase in the future health burdenThe excess future health burden was due to the cumulative impact of lower exposure days and high population density in high‐priority areas [ABSTRACT FROM AUTHOR]

To understand how chemical exposure can impact health, researchers need tools that capture the complexities of personal chemical exposure. In practice, fine particulate matter (PM2.5) air quality index (AQI) data from outdoor stationary monitors and Hazard Mapping System (HMS) smoke density data from satellites are often used as proxies for personal chemical exposure, but do not capture total chemical exposure. Silicone wristbands can quantify more individualized exposure data than stationary air monitors or smoke satellites. However, it is not understood how these proxy measurements compare to chemical data measured from wristbands. In this study, participants wore daily wristbands, carried a phone that recorded locations, and answered daily questionnaires for a 7‐day period in multiple seasons. We gathered publicly available daily PM2.5 AQI data and HMS data. We analyzed wristbands for 94 organic chemicals, including 53 polycyclic aromatic hydrocarbons. Wristband chemical detections and concentrations, behavioral variables (e.g., time spent indoors), and environmental conditions (e.g., PM2.5 AQI) significantly differed between seasons. Machine learning models were fit to predict personal chemical exposure using PM2.5 AQI only, HMS only, and a multivariate feature set including PM2.5 AQI, HMS, and other environmental and behavioral information. On average, the multivariate models increased predictive accuracy by approximately 70% compared to either the AQI model or the HMS model for all chemicals modeled. This study provides evidence that PM2.5 AQI data alone or HMS data alone is insufficient to explain personal chemical exposures. Our results identify additional key predictors of personal chemical exposure. Plain Language Summary: Tools are needed to determine how chemical exposures may affect people's health. It is not understood how air quality data from stationary air monitors and smoke density data from satellites align with personal chemical exposure data from silicone wristbands; we present the first study to evaluate this. In this study, people wore wristbands, carried phones to track their locations, and answered questions for a week in different seasons. We also collected fine particulate matter data from outdoor monitors and satellites and tested the wristbands for 94 different chemicals. The results showed that the wristband data, along with other information like where people spent time and the air quality, varied between seasons. We used machine learning models to predict personal chemical exposure using only the data from monitors or satellites, and then using a mix of data from both, along with additional data about the environment and people's behaviors. Models that used a mix of data were much better at predicting exposure compared to using just one type of data. This study tells us that using fine particulate data from monitors or satellites is not enough to understand personal chemical exposure. Key Points: Explaining personal chemical exposures required more than fine particulate matter air quality index (AQI) or hazard mapping system dataModels with variables in addition to fine particulate matter AQI increased predictive accuracy of exposureHeavy wildfire smoke was measured during the study [ABSTRACT FROM AUTHOR]

Climate-related health hazards pose grave risks to human health and well-being. Individual-level behavioral response is critical given increasingly severe climate-related health hazards, such as wildfire smoke, co-occurring with other health hazards, such as COVID-19. Existing models of behavior traditionally focus on the role of threat and efficacy appraisals; however, social factors, such as social norms and social support, are also of interest to scholars and policymakers. We examine how threat and efficacy appraisal, along with descriptive social norms and social support, are related to behavioral intentions in response to wildfire smoke and COVID-19. Using survey data from a nationally representative sample (n = 502), when wildfire smoke and COVID-19 were active health threats – we found threat and efficacy appraisal were positively associated with behavioral intentions. We also found that descriptive social norms were correlated with intended response, and cognitive appraisals may mediate the effect of such norms on behavioral intentions. Social support negatively moderated the relationship between response efficacy and threat appraisal, respectively, on behavioral intentions; however, we found no evidence of social support moderating the relationship between self-efficacy and behavioral intentions. Thus social factors should be considered with cognitive appraisals when examining factors motivating behavioral response to climate-related health hazards. Behavioral interventions and public health communications leveraging descriptive social norms may promote adaptation to various threat types, directly and through perceptions of threat and efficacy. [ABSTRACT FROM AUTHOR]

Abstract Background During wildfire smoke episodes, school and childcare facility staff and those who support them rely upon air quality data to inform activity decisions. Where ambient regulatory monitor data is sparse, low-cost sensors can help inform local outdoor activity decisions, and provide indoor air quality data. However, there is no established protocol for air quality decision-makers to use sensor data for schools and childcare facilities. To develop practical, effective toolkits to guide the use of sensors in school and childcare settings, it is essential to understand the perspectives of the potential end-users of such toolkit materials. Methods We conducted 15 semi-structured interviews with school, childcare, local health jurisdiction, air quality, and school district personnel regarding sensor use for wildfire smoke response. Interviews included sharing PM2.5 data collected at schools during wildfire smoke. Interviews were transcribed and transcripts were coded using a codebook developed both a priori and amended as additional themes emerged. Results Three major themes were identified by organizing complementary codes together: (1) Low-cost sensors are useful despite data quality limitations, (2) Low-cost sensor data can inform decision-making to protect children in school and childcare settings, and (3) There are feasibility and public perception-related barriers to using low-cost sensors. Conclusions Interview responses provided practical implications for toolkit development, including demonstrating a need for toolkits that allow a variety of sensor preferences. In addition, participants expected to have a wide range of available time for monitoring, budget for sensors, and decision-making types. Finally, interview responses revealed a need for toolkits to address sensor uses outside of activity decisions, especially assessment of ventilation and filtration.

BackgroundWildfire smoke is responsible for around 20% of all particulate emissions in the U.S. and affects millions of people worldwide. Children are especially vulnerable, as ambient air pollution exposure during early childhood is associated with reduced lung function. Most studies, however, have focused on the short-term impacts of wildfire smoke exposures. We aimed to identify long-term baseline epigenetic changes associated with early-life exposure to wildfire smoke. We collected nasal epithelium samples for whole genome bisulfite sequencing (WGBS) from two groups of adult female rhesus macaques: one group born just before the 2008 California wildfire season and exposed to wildfire smoke during early-life (n = 8), and the other group born in 2009 with no wildfire smoke exposure during early-life (n = 14). RNA-sequencing was also performed on a subset of these samples.ResultsWe identified 3370 differentially methylated regions (DMRs) (difference in methylation ≥ 5%, empirical p

IntroductionWildfire smoke (WFS) exposure is a growing threat to human health, and lower socioeconomic position (SEP) has been shown to increase pollution susceptibility. Studies of SEP-related susceptibility, however, are often compromised due to spatial confounding between lower-SEP and pollution. Here we examine outdoor-housed nonhuman primates, living in natural social hierarchy in a common location, born during years of high vs. low WFS, to examine the separate and combined effects of WFS and social rank, an analog to SEP, on lung and immune function.MethodsTwenty-one females were born during extreme WFS events in summer 2008; 22 were born in summer 2009, during low WFS. Pulmonary function and circulating cytokines were measured three years later, in adolescence. We estimated fine particulate (PM2.5) and ozone exposures during each animal's first 90 days and three years of age using regulatory data. Early-life social status was estimated using maternal rank at birth, as rank in females is relatively stable throughout life, and closely approximates mother's rank. We tested associations among WFS exposure, rank, and endpoints using linear regression and ANOVA.ResultsHigher WFS exposure in infancy was, on average, associated with lower functional residual capacity (FRC), residual volume (RV), tissue compliance (Ct), and IL-8 secretion in adolescence. Higher social rank conferred significantly higher expiratory reserve volume (ERV) and functional residual capacity (FRC) solely among those born in the high-WFS year (2008). Differences in effects of rank between years were not significant after adjustment for multiple comparisons.ConclusionsExposure to WFS in infancy generally conferred lower adolescent respiratory volumes and inflammatory cytokines. Higher rank conferred higher respiratory volumes only among females born during WFS, suggesting the possibility that the health benefits of rank may be more apparent under environmental challenge.

Abstract Smoke from wildland fires has been shown to produce neuroinflammation in preclinical models, characterized by neural infiltrations of neutrophils and monocytes, as well as altered neurovascular endothelial phenotypes. To address the longevity of such outcomes, the present study examined the temporal dynamics of neuroinflammation and metabolomics after inhalation exposures from biomass-derived smoke. 2-month-old female C57BL/6 J mice were exposed to wood smoke every other day for 2 weeks at an average exposure concentration of 0.5 mg/m3. Subsequent serial euthanasia occurred at 1-, 3-, 7-, 14-, and 28-day post-exposure. Flow cytometry of right hemispheres revealed two endothelial populations of CD31Hi and CD31Med expressors, with wood smoke inhalation causing an increased proportion of CD31Hi. These populations of CD31Hi and CD31Med were associated with an anti-inflammatory and pro-inflammatory response, respectively, and their inflammatory profiles were largely resolved by the 28-day mark. However, activated microglial populations (CD11b+/CD45low) remained higher in wood smoke-exposed mice than controls at day 28. Infiltrating neutrophil populations decreased to levels below controls by day 28. However, the MHC-II expression of the peripheral immune infiltrate remained high, and the population of neutrophils retained an increased expression of CD45, Ly6C, and MHC-II. Utilizing an unbiased approach examining the metabolomic alterations, we observed notable hippocampal perturbations in neurotransmitter and signaling molecules, such as glutamate, quinolinic acid, and 5-α-dihydroprogesterone. Utilizing a targeted panel designed to explore the aging-associated NAD+ metabolic pathway, wood smoke exposure drove fluctuations and compensations across the 28-day time course, ending with decreased hippocampal NAD+ abundance on day 28. Summarily, these results indicate a highly dynamic neuroinflammatory environment, with potential resolution extending past 28 days, the implications of which may include long-term behavioral changes, systemic and neurological sequalae directly associated with wildfire smoke exposure.

Abstract Wildfires are increasing across the USA. While smoke events affect human exposure and air quality, wildfire smoke effects on ecosystem‐atmosphere interactions are poorly understood. We investigate smoke effects on biogenic volatile organic compound (VOC) emissions and photosynthesis for ponderosa pines. During several wildfire smoke events, we observed photosynthetic reduction with evidence for stomatal plugging and changes in leaf‐level uptake and emission of both biogenic and wildfire VOCs. During intense smoke events, photosynthesis and VOC emissions were almost entirely suppressed, but increased dramatically upon stomatal opening. We propose four types of VOC responses to this burst in stomatal opening: post‐burst emissions, pulsed emissions, surge emissions, and post‐burst uptake. Our observations suggest that wildfire smoke can affect plant physiology and leaf‐atmosphere gas exchange.

Unhealthy air quality conditions can strongly affect long-term human health and wellbeing, yet many air quality data products focus on near real-time alerts or short-term forecasts. Understanding the full state of air quality also requires examining the longer term frequency and intensity of poor air quality at ground level, and how it might change over time. We present a new modeling framework to compute climate-adjusted estimates of air quality hazards for the contiguous United States (CONUS) at 10 km horizontal resolution. The framework blends results from statistical, machine-learning, and climate-chemistry models—including a bias-adjusted version of the EPA Community Multiscale Air Quality Model (CMAQ) time series as described in (Wilson et al., 2022)—for ground-level ozone, anthropogenic fine particulate matter (PM2.5), and wildfire smoke PM2.5 into consistent estimates of days exceeding the “unhealthy for sensitive groups” (orange colored) classification on the EPA Air Quality Index for 2023 and 2053. We find that joint PM2.5 and ozone orange+ days range from 1 day to 41 days across CONUS, with a median value of 2 days, across all years. Considering all properties across CONUS, we find that 63.5% percent are exposed to at least one orange or greater day in 2023, growing to 72.1% in 2053. For a 7-day threshold, 3.8% and 5.7% of properties are exposed in 2023 and 2053, respectively. Our results also support the identification of which parts of the country are most likely to be impacted by additional climate-related air quality risks. With growing evidence that even low levels of air pollution are harmful, these results are an important step forward in empowering individuals to understand their air quality risks both now and into the future.

Introduction: Farmworkers are one of the populations most vulnerable to climate change. In addition to disproportionate exposure to climate-intensified hazards such as extreme heat and wildfire smoke, many farmworkers face situational and psychosocial stressors that also impact their health. Methods: We conducted open-ended interviews with 16 farmworkers in Southcentral Idaho during June-August 2023 as part of a digital storytelling project in partnership with the Idaho Organization of Resource Councils (IORC). Interviews assessed participants’ experiences with climate change, perceived impacts on their health, and strategies and barriers to protecting themselves. Bilingual (English/Spanish) study staff translated and transcribed all video recordings verbatim, and we abstracted representative quotes from interviews. Results: Participants primarily discussed the health impacts of heat, recounting personal experiences and stories of other farmworkers feeling dizzy, wanting to vomit, or passing out from occupational heat stress. Despite these experiences, they reported feeling like they needed to keep working regardless of the conditions in order to get paid and support their family. Experiences with climate change were underscored by participants’ discussions of co-exposure to situational and psychosocial stressors such as lack of access to healthcare, poor housing without air conditioning, and racism, discrimination, and fear of family separation. Discussion: This project highlights farmworkers’ first-hand experiences regarding climate change and underscores the interconnected impacts of occupational, environmental, and psychosocial stressors on their health and wellbeing. These findings emphasize the importance of shifting the burden of climate resiliency from individual farmworkers to systemic workplace, residential, and community interventions.

Abstract In response to increasing wildfire risks, California plans to expand the use of prescribed fire. We characterized the anticipated change in health impacts from exposure to smoke under a future fire‐management scenario relative to a historical period (2008–2016). Using dispersion models, we estimated daily fine particulate matter (PM2.5) emissions from hypothetical future prescribed fires on 500,000‐acres classified as high priority. To evaluate health impacts, we calculated excess daily cardiorespiratory emergency department visit rates attributed to all‐source PM2.5, distinguishing the portion of the burden attributed to prescribed fire. The total burden was differentiated by fire type and by smoke strata‐specific days to calculate strata‐specific burden rates, which were then applied to estimate the burden in the future scenario. This analysis suggests that the exposure to prescribed fire smoke, measured as the number of persons exposed per year, would be 15 times greater in the future. However, these exposures were associated with lower concentrations compared to the historical period. The increased number of exposure days led to an overall increase in the future health burden. Specifically, the northern, central, and southern regions experienced the largest burden increase. This study introduces an approach that integrates spatiotemporal exposure differences, baseline morbidity, and population size to assess the impacts of prescribed fire under a future scenario. The findings highlight the need to consider both the level and frequency of exposure to guide strategies to safeguard public health as well as aid forest management agencies in making informed decisions to protect communities while mitigating wildfire risks.

Abstract To understand how chemical exposure can impact health, researchers need tools that capture the complexities of personal chemical exposure. In practice, fine particulate matter (PM2.5) air quality index (AQI) data from outdoor stationary monitors and Hazard Mapping System (HMS) smoke density data from satellites are often used as proxies for personal chemical exposure, but do not capture total chemical exposure. Silicone wristbands can quantify more individualized exposure data than stationary air monitors or smoke satellites. However, it is not understood how these proxy measurements compare to chemical data measured from wristbands. In this study, participants wore daily wristbands, carried a phone that recorded locations, and answered daily questionnaires for a 7‐day period in multiple seasons. We gathered publicly available daily PM2.5 AQI data and HMS data. We analyzed wristbands for 94 organic chemicals, including 53 polycyclic aromatic hydrocarbons. Wristband chemical detections and concentrations, behavioral variables (e.g., time spent indoors), and environmental conditions (e.g., PM2.5 AQI) significantly differed between seasons. Machine learning models were fit to predict personal chemical exposure using PM2.5 AQI only, HMS only, and a multivariate feature set including PM2.5 AQI, HMS, and other environmental and behavioral information. On average, the multivariate models increased predictive accuracy by approximately 70% compared to either the AQI model or the HMS model for all chemicals modeled. This study provides evidence that PM2.5 AQI data alone or HMS data alone is insufficient to explain personal chemical exposures. Our results identify additional key predictors of personal chemical exposure.

Background: Smoke exposure from wildfires or residential wood burning for heat is a public health problem for many communities. Do-It-Yourself (DIY) portable air cleaners (PACs) are promoted as affordable alternatives to commercial PACs, but evidence of their effect on health outcomes is limited. Objective: Pilot test an evaluation of the effect of DIY PAC usage on self-reported symptoms, and investigate barriers and facilitators of PAC use, among members of a tribal community that routinely experiences elevated concentrations of fine particulate matter (PM2.5) from smoke. Methods: We conducted studies in Fall 2021 (“wildfire study”; N = 10) and Winter 2022 (“wood stove study”; N = 17). Each study included four sequential one-to-two-week phases: 1) initial, 2) DIY PAC usage ≥8 h/day, 3) commercial PAC usage ≥8 h/day, and 4) air sensor with visual display and optional PAC use. We continuously monitored PAC usage and indoor/outdoor PM2.5 concentrations in homes. Concluding each phase, we conducted phone surveys about participants’ symptoms, perceptions, and behaviors. We analyzed symptoms associated with PAC usage and conducted an analysis of indoor PM2.5 concentrations as a mediating pathway using mixed effects multivariate linear regression. We categorized perceptions related to PACs into barriers and facilitators of use. Results: No association was observed between PAC usage and symptoms, and the mediation analysis did not indicate that small observed trends were attributable to changes in indoor PM2.5 concentrations. Small sample sizes hindered the ability to draw conclusions regarding the presence or absence of causal associations. DIY PAC usage was low; loud operating noise was a barrier to use. Discussion: This research is novel in studying health effects of DIY PACs during wildfire and wood smoke exposures. Such research is needed to inform public health guidance. Recommendations for future studies on PAC use during smoke exposure include building flexibility of intervention timing into the study design.

Sub-micron particles are ubiquitous in the indoor environment, especially during wildfire smoke episodes, and have a higher impact on human health than larger particles. Conventional fibrous air filters installed in heating, ventilation, and air conditioning (HVAC) systems play an important role in controlling indoor air quality by removing various air pollutants, including particulate matter (PM). However, it is evident that the removal efficiency of wildfire smoke PM and its effect on filter performance is significantly under-studied. This study delves into the size-specific removal efficiency of pine needle smoke, a representative of wildfire smoke and emissions. We test an array of filter media with minimum efficiency reporting values (MERV) spanning 11–15. Both size-resolved particle number concentrations and mass concentrations were measured using an Optical Particle Sizer (OPS, TSI, Inc.) and a Scanning Mobility Particle Sizer (SMPS, TSI, Inc.). Furthermore, we characterize the filter media morphology and smoke particles deposited on filter fibers using Scanning Electron Microscopy (SEM) to gain insights into the interaction dynamics of these particles. Our findings add to the comprehension of the relationship between MERV designations and smoke removal efficiency. Such insight can inform standards and guidelines and equip decision-makers with the knowledge needed to initiate measures for mitigating the impact of air pollution, specifically on the indoor environment. [ABSTRACT FROM AUTHOR]

There have been few empirical studies of the sensitivity of birds to the effect of air pollutants. In late 2019 and early 2020 the Australian Capital Territory (ACT) and much of south-eastern Australia were affected by extreme wildfire events and smoke extended to surrounding areas. Prior to this event, GPS transmitters had been fitted to a sample of Little Eagles Hieraaetus morphnoides in the ACT as part of a study of their movement behaviour. Three of these birds carried transmitters in the breeding season during the fires and in the previous breeding season. This offered opportunistic analysis of data from both periods to test for effects of smoke on the birds' flight behaviour. The effects of particulate matter in the air of ≤2.5 microns in diameter (PM2.5) and covariates on flight status were investigated with a binomial generalised linear model with logistic link. The birds were more likely to fly when there were low levels of PM2.5 and the odds of flying decreased as density of PM2.5 increased at a rate of 0.202% per ug/m3. None of the sample birds died during or after smoke exposure, although their respiratory system might have been affected. [ABSTRACT FROM AUTHOR]