To evaluate the recent literature on differential exposure to and health risks from wildfire smoke across subpopulations, whether wildfire-derived PM2.5 affects health differently from non-wildfire-derived PM2.5, and how wildfire smoke composition affects health. We found inconsistent evidence of differential exposure to and health risks from wildfire PM2.5 by population subgroups. This could be due to variation in wildfire PM2.5 infiltration into buildings and ability to take individual protective actions, both of which have been noted to be related to socio-economic status in the recent scientific literature. Respiratory health endpoints have been the most consistent and commonly evaluated health outcome in studies of wildfire smoke; additional research is needed to resolve conflicting findings for non-respiratory health outcomes (e.g., cardiovascular disease). Although some recent studies have documented larger health risks from wildfire-derived as compared to non-wildfire-derived PM2.5, we document how further research could evaluate whether these findings are confounded by type of fuel burned, due to methodological concerns, or are true. We also conclude that more research is necessary to elucidate potential differences in health risks of constituents of wildfire smoke other than PM2.5 or from burning of different fuels. Wildfire smoke is projected to continue to increase. We encourage future research to move away from further documentation of respiratory health impacts of wildfire smoke, which has been very well established, into studies of other health endpoints that have been less well studied to date, more exploration into health effects from wildfire smoke constituents other than PM2.5 and from different types of fires (i.e., wildland urban interface (WUI) fires versus wildland fires), and additional exploration of remaining uncertainties with a goal of further supporting public health protection from wildfire smoke.

Objective:To evaluate the association between ambient fine particulate matter (PM2.5) exposure and bovine respiratory disease (BRD) in northern Colorado dairy calves. Methods:Retrospective data were analyzed from 45 preweaned dairy calves. Calves were screened for BRD twice weekly from May 23 through August 7, 2023. Daily PM2.5 concentrations were obtained from Environmental Protection Agency monitors. Logistic mixed-effects models, including distributive-lag nonlinear models, were used to estimate associations between PM2.5 and BRD. Results:There were 27 clinical and 190 subclinical BRD occurrences over 900 screenings. Mean daily PM2.5 during the study was 4.5 μg/m3, with peaks up to 54.3 μg/m3 coincident with a wildfire smoke event preceding screening. A 5 μg/m3 increase in daily PM2.5 was associated with 66% higher odds of incident BRD (OR, 1.66; 95% CI, 1.08 to 2.53). Temperature-humidity index (OR, 1.17; 95% CI, 1.11 to 1.22) and male sex (OR, 1.65; 95% CI, 1.08 to 2.53) were also significant predictors. Lagged analyses showed variable associations across 0- to 30-day lag, with increased odds of BRD observed at PM2.5 concentrations between 4.8 and 8 μg/m3. Conclusions:PM2.5 was significantly associated with increased BRD risk in dairy calves. Even relatively low PM2.5 concentrations were linked to higher BRD odds, highlighting impacts below regulatory thresholds established for human health. Future prospective studies across multiple dairies are warranted to characterize disease progression and potential mitigation strategies. Clinical Relevance:Veterinarians should consider ambient air quality when assessing disease risk, guiding preventive strategies, and advising clients. Awareness of PM2.5 and implementation of adaptation strategies may improve respiratory health outcomes in dairy calves.

Historical redlining originated in the 1930s from the Home Owners’ Loan Corporation (HOLC), with discriminatory loans and insurance based on neighborhoods’ racial/ethnic composition and socioeconomic status. We investigated associations between historically redlined neighborhood grades and child blood lead levels (BLL), and whether these associations differed by race/ethnicity. Child BLL, demographic, and geocoded home address data were collected from the Wisconsin Systematic Tracking of Elevated Lead Levels and Remediation system in Milwaukee and Racine Counties (1996–2001, 2011–2020). We analyzed 26,381 unique BLL in adjusted linear regression models, explored interactions of HOLC grade and race/ethnicity on BLL, and assessed spatial autocorrelation. Most children were Black (70

Blood lead levels (BLL) in children in the United States have decreased in recent decades; yet, lead is toxic at any concentration, and disparities in lead poisoning persist across population groups. As a result, lead exposure continues to be a major environmental public health concern. Because the relative contributions of different lead exposure sources are rarely evaluated together, mitigation efforts may be fragmented, with limited resources not always directed toward the highest-impact interventions. The objective of this study was to investigate the combined impacts of housing characteristics, soil lead concentrations, and water service line materials on childhood BLLs using tree-based machine-learning methods. Milwaukee, Wisconsin, was selected as a case study due to its high prevalence of elevated pediatric BLLs and large population at risk from older housing stock. Using existing data, we applied extreme gradient boosting model with SHapley Additive exPlanation (SHAP) to quantify the relative contributions of multiple lead exposure sources among children aged 1-5 years and to assess whether exposure profiles interact to produce higher BLLs. Our results indicate that housing age and property values, among other housing characteristics, were more strongly associated with elevated childhood BLLs than soil lead concentrations or the presence of lead service lines. Children living in homes older than 90 years with lead service lines exhibited increased exposure risk, whereas similar homes with copper service lines showed substantially reduced risk. Overall, our findings demonstrate that interpretable machine-learning methods can provide cost-effective insights to guide more targeted and impactful pediatric lead mitigation strategies.

Wildfire-associated smoke has been increasing in frequency and severity in recent years in the western United States, posing complex health risks. In this study, we investigated the effects of smoke and fine particulate matter (PM2.5) on sperm quality in a Colorado breeding facility bull population (n = 100), leveraging the facility's sample quality assessment records as a longitudinal data source. We focused on sperm viability as an outcome, using reproductive health records (February 2021-October 2023) to identify sperm sample dates and discard status, with 11,217 samples meeting inclusion criteria. For each preceding spermatogenesis period (61 d), we calculated median air pollution exposures (PM2.5, PM10, carbon monoxide, sulfur dioxide, and ozone) using proximate EPA monitors and a derived "smoke day" index integrating NOAA Hazard Mapping System smoke plumes with PM2.5 monitor data. We used three pairs (one each with and without interaction terms) of generalized linear mixed-effects models to predict sample discard probability and assess trend stability over increasingly complex air quality characterizations. We adjusted for bull age, two aggregate breed groups (specific to this study population and based on project partner guidance), and heat index, as well as individual bulls and collection date as random effects. Our best-performing model (per Akaike Information Criterion) found each additional smoke day increased discard odds by ∼4% (odds ratio 1.04, 95% CI 1.02-1.05), with a nonsignificant primary PM2.5 effect but a significant breed interaction for ∼31% higher odds per additional 1-μg/m3 median PM2.5 (OR 1.31, 95% CI 1.15, 1.49) in Angus and Red Angus bulls. A model using only PM2.5 for air quality explained the most variance (R2) with a 1-μg/m3 increase raising sample discard odds by ∼7% (OR 1.07, 95% CI 1.01, 1.14) and a similar breed interaction effect (OR 1.31, 95% CI 1.15, 1.47). These findings help establish a baseline correlation between smoke and fine particulate matter exposure and reproductive fitness in bulls, with an apparent difference in vulnerability to PM2.5 across groups of related breeds. These results establish a baseline relationship that can begin to inform communication and risk mitigation strategies for cattlemen and veterinarians, and act as groundwork for future research into biological mechanisms and mitigation strategies.

Animal health remains largely absent from climate-health policy, despite growing evidence of climate-related health risks across species. Using Colorado as a model, we identify key climate hazards affecting animals and examine their overlap with human health risks. We synthesized national, regional, and state-specific climate and health, translating human health themes to 3 animal groups: companion animals, livestock (including horses), and wildlife. Findings were validated through interviews with subject-matter experts from state agencies, academia, and nonprofit organizations. Wildfire, air quality, extreme heat, and drought emerged as the most urgent hazards, with flooding, extreme storms, waterborne disease, and vector-borne disease also affecting animal populations across the state. Three crosscutting themes-animal welfare, food safety, and caregiver impacts-linked all hazards and highlighted the interdependence of animal and human well-being. Experts identified major gaps between human-focused resources and the limited animal-specific guidance. Transferable strategies such as air-quality advisories, heat-risk mitigation, and emergency preparedness were recognized but require adaptation across species and management settings. This work suggests 4 priority areas for climate action, emphasizing (1) animal-specific decision tools and surveillance; (2) integrated preparedness for concurrent hazards; (3) equitable access to veterinary and protective resources; and (4) cross-sector networks that harmonize animal, human, and ecosystem health. Aligning animal and public health systems offers a practical opportunity to strengthen climate resilience for animals, people, and ecosystems.

Wildfires are the largest source of primary fine particulate matter (PM2.5) in the US, and PM2.5 exposure is associated with a suite of negative health impacts. Epidemiological studies of wildfire smoke exposure typically rely on hospitalizations and Emergency Department (ED) visits to assess health outcomes. However, substantial reporting delays limit usefulness for near real-time public health response. Syndromic Surveillance (SS) is a voluntary reporting system based on chief complaints and/or discharge diagnoses from the ED that is available near-real time, but has been used in fewer epidemiological studies of wildfire smoke exposure. We conducted a time-stratified case crossover study to compare association between wildfire smoke PM2.5 exposure and ED visits versus SS in New Mexico from 2019–2022. Our results showed some consistency between ED visits and SS reports for all respiratory-related, asthma, and all-cardiovascular related ED visits versus SS reports; however, there were meaningful differences in significance and magnitudes of several odds ratios. The “Air Quality-Related Respiratory Illness” SS definition may be useful for studying the impact of wildfire smoke exposure, with significantly increased odds per 10 µg m−3 smoke PM2.5. These results were comparable to all respiratory-related SS reports. Overall, we hypothesize that SS could be a valuable tool for allocating resources during an intense, local wildfire event. Future work should be conducted to further our understanding of the use of SS in epidemiological studies of wildfire smoke exposure.

Objective:To characterize spatiotemporal patterns of criteria air pollutants surrounding Thoroughbred racetracks in the US. Methods:We identified all active Thoroughbred racetracks from 2011 through 2024, linking their location with daily air quality data from the US Environmental Protection Agency (EPA) Air Quality System. Mean daily and annual pollutant concentrations within a 50-km bounding box of each racetrack were summarized using descriptive statistics and evaluated for monthly and annual trends. Exceedances were defined as any observation in which pollutant concentration met or exceeded the National Ambient Air Quality Standards (NAAQS) and were assessed across EPA regions to characterize spatial patterns. Results:Of the 56 racetracks included in the study, all experienced an exceedance of at least 1 pollutant, most commonly ozone (96%) and particulate matter ≤ 2.5 μm in diameter (PM2.5; 95%). Lead had the most exceedances, but these declined over the study period. Median pollutant concentrations were below the NAAQS across EPA regions, though annual PM2.5 exceeded the NAAQS threshold in the Great Lakes and Southwest. While most pollutants declined over time, ozone, PM2.5, and particulate matter ≤ 10 μm in diameter increased after 2020. Among observations, 25.2% of PM2.5 measurements were ≥ 11 µg/m3, a level linked with performance declines. Conclusions:These findings indicate that air pollution near racetracks frequently reaches levels relevant to equine health and performance and is associated with human health risk. Clinical Relevance:Racetrack veterinarians and managers should be aware of air quality and have knowledge of the risks of exposure. Integration of air quality monitoring at racetracks can guide action to safeguard the health of horses, jockeys, and spectators.

As climate change intensifies, heat-related health risks are expected to increase, arising from complex interactions between environmental and social factors. Although prior research has primarily focused on the effects of extreme heat events on heat-related illnesses, the cumulative impact of prolonged summer heat on all-cause hospitalization trends, as well as its spatiotemporal interactions with key heat-risk factors, remains insufficiently understood. This study addresses this gap by examining the relationship between all-cause hospitalization rates and heat-risk factors, including Wet-Bulb Globe Temperature (WBGT), heat-related social vulnerabilities, and PM2.5, in New Mexico from 2016 to 2022. By integrating a spatiotemporal Bayesian model and Self-Organizing Maps (SOM), we identified regional variations in relative risk and analyzed how these factors influenced hospitalization patterns over time and space. Results show that WBGT only becomes positively associated with hospitalizations after considering heat-related social vulnerabilities. Despite declining hospitalization rates over the study period, the increasing relative risk of hospitalization may reflect underlying healthcare access inequalities. SOM clustering highlights distinct regional patterns, where some counties are more influenced by environmental factors while others are driven by heat-related social vulnerabilities. As a result, our findings highlight the need for geographically differentiated interventions that reflect the evolving impact of heat-risk factors, enabling more effective and equitable resource allocation based on each region's dominant drivers of risk.

Background Outdoor air quality has significant health effects for susceptible groups, such as outdoor workers. Identifying motivations for such audiences to seek information about air quality is important to inform evidence-based practices to protect health and well-being.Focus of the Article We examine the effects of an organizationally based social marketing air quality campaign targeted at outdoor workers designed using the EAST (Easy, Attractive, Social, Timely) framework. Key perceptions from the theoretical models of information seeking were analyzed after the conclusion of the campaign.Research Question Does a social marketing campaign designed with the EAST framework increase outdoor air quality risk perceptions, informational subjective norms, and routine and nonroutine information seeking behaviors?Program Design/Approach The "Air Aware" campaign was developed based on insights from employees in the organization where the campaign was implemented and a state-wide survey of outdoor workers in the state of implementation. The campaign was designed using principles from the EAST framework to make information about air quality easy to access, engaging, and relevant to the needs of the audience, for whom exposure to outdoor air is an unavoidable part of their daily life.Importance to the Social Marketing Field By integrating a campaign design informed by the EAST framework with evaluation of theoretically informed information behaviors, this study bridges behavioral insights with communication theory to inform campaign design and evaluation. The innovative theory-practice hybrid approach demonstrates how aligning behavioral nudges of the EAST framework with cognitive and social explanations of information behaviors can inform the design and evaluation of targeted public health campaigns.Methods A pre-/post-test quasi-experimental design (treatment and control group) with outdoor workers for city and county organizations in an area susceptible to poor outdoor air quality in summertime was used to evaluate the campaign.Results The campaign increased select behaviors and perceptions related to information seeking.Recommendations for Practice Practitioners can use insights from this study to design targeted campaigns that leverage behavioral nudges and audience-specific motivations to increase information seeking, an important precursor to other behavioral adoptions, among high-risk groups such as outdoor workers.

Few studies examine health effects of metals in ambient fine particulate matter (PM2.5), as measurements of elemental composition are sparse. To facilitate intraurban studies in Denver, Colorado, we developed land use regression models for seven speciescopper (Cu), iron (Fe), titanium (Ti), zinc (Zn), potassium (K), calcium (Ca), and magnesium (Mg). As part of the Healthy Start Cohort study, we collected filter-based PM2.5 using personal air samplers at 67 locations across Denver. Sample collection occurred from May 2018 through March 2019, accounting for all meteorological seasons. Exposure models were informed by 83 geospatial covariates, with traffic-related predictors as the strongest and most consistent across models. Model performance was evaluated using 10-fold cross validation and overall, varied by sampling campaign and season, with R 2 values ranging from 0 to 0.63. At best, our model predicts Cu and Fe during fall (R 2 = 0.56 and 0.63, respectively); whereas it fails to capture species unrelated to traffic year-round (R 2 < 0.40). This highlights the influence of missing predictors (e.g., wildfire smoke, atmospheric transport and other meteorological factors) on PM2.5 concentrations and spatial gradients. Despite limitations, resulting models enable estimation of intraurban metal exposures and support future analyses of long-term health impacts in Denver.

BACKGROUND:Ambient air pollution contributes substantially to human morbidity and mortality, and athletes are recognised as a particularly vulnerable group. However, little is known about the impact of air pollution on equine athletes. OBJECTIVES:To explore the relationship between air pollution exposure during the pre-competition training period and race day performance among Thoroughbred racehorses that competed on California racetracks. STUDY DESIGN:A retrospective longitudinal study. METHODS:For each winning horse, pollutant exposure during the 21-day pre-competition training period was assigned using data from the nearest EPA air quality monitoring site to the racetrack where horses trained and competed. Exposure was characterised using the threshold Air Quality Index (AQI), with additional analyses evaluating fine particulate matter (PM2.5) and ozone (O3). A distributed lag non-linear model was applied to estimate associations between pollutant exposure during the training period and winning speed. RESULTS:Horses exposed to higher pollutant levels (80th percentile AQI = 58) during the pre-competition period had slower winning speeds when compared with those exposed to lower levels (20th percentile AQI = 32), with statistically significant decreases observed approximately 2-17 days before competition. Over the 21-day pre-competition exposure window, daily exposure to an AQI of 58, compared to an AQI of 32, was associated with a decrease in winning speed of 0.044 m/s (95% CI: -0.056, -0.032). MAIN LIMITATIONS:Limitations include the use of data from regional air quality monitors, which may not accurately reflect the quality of air horses are actually breathing, and the inclusion of only California racetracks, limiting generalisability. CONCLUSIONS:Pre-competition air pollution exposure was associated with slower winning speeds in Thoroughbred racehorses, highlighting the importance of systematic air quality measurement at equine racetracks.

Residents of agricultural communities may experience higher exposures to pesticides due to their proximity to agricultural operations. We applied a novel measurement approach, using Ultrasonic Personal Air Samplers (UPAS), to quantify particulate matter and organophosphate pesticides in air in California's Central Valley. We collected 124 personal, 126 in-home, and 32 outdoor air samples with 66 adults from 37 rural households in 2023 and 2024. We detected chlorpyrifos, acephate, malathion, diazinon, and naled in air samples. We detected gas-phase chlorpyrifos in 63% of personal samples and 86% of homeseven though use of chlorpyrifos has been banned in California (with few exceptions) since January 2021at 24 h average concentrations ranging up to 13 ng m-3 (personal) and 5.8 ng m-3 (in-home). We did not detect chlorpyrifos in outdoor air samples. Using linear mixed models, we found that higher indoor air temperatures and having more carpets/rugs were associated with higher indoor chlorpyrifos concentrations. The concentrations we measured were well below the California Department of Pesticide Regulation's health screening level of 510 ng m-3 for chronic exposure to chlorpyrifos in air; nevertheless, our results suggest that persistent chlorpyrifos in home environments continues to contribute to nondietary exposure among California residents.

Background:Air pollution is a major global health threat that is expected to worsen, yet its effects on domestic animals remain poorly understood. The objective of this scoping review was to synthesize existing evidence on associations between ambient air pollutants and health outcomes in domestic animals and to identify gaps to guide future research. Methods:A scoping review was conducted following the Arksey and O'Malley framework and Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews guidelines with 2 search databases (PubMed and Web of Science) using terms related to domestic animals, air pollutants, and potential health outcomes on August 15, 2024. Eligible studies included research evaluating associations between ambient air pollutant exposures and domestic animal health outcomes. Studies assessing indoor air quality or experimental exposures were excluded. Results were synthesized descriptively and narratively. Results:29 studies were included, examining dogs, horses, cattle, sheep, and goats. Reported outcomes spanned cardiopulmonary, neurologic, ophthalmologic, immunologic, metabolic, reproductive, behavioral, performance, production, and mortality. Evidence demonstrated parallels with human health, particularly respiratory and neurologic effects, but cardiovascular and reproductive outcomes were notably underrepresented relative to human literature. Research publications related to air pollution and domestic animal health have increased in recent years, reflecting growing recognition of its contributions to animal health outcomes. Clinical Relevance:Veterinarians are increasingly confronted with questions about the health impacts of poor air quality. This review consolidates current evidence, identifies vulnerable populations, and highlights air pollution as an emerging risk to domestic animal health. Expanding research will strengthen veterinarians' ability to recognize, mitigate, and advise on pollution-related health impacts.

In 2022, New Mexico (NM) experienced a number of wildfires, including the state's largest, Calf Canyon/Hermit's Peak. This study aimed to evaluate how different exposure estimate methods and referent period selection impacted associations between wildfire smoke and health outcomes using a case-crossover study design. We investigated associations with exposure to fine particulate matter (PM2.5) from wildfire smoke and cardiorespiratory-related emergency department (ED) visits in NM during 2022. Our study compared a range of exposure methods: (a) PM2.5 from the Environmental Protection Agency (EPA) regulatory-grade monitors, (b) PM2.5 from both the EPA regulatory-grade monitors and low-cost PurpleAir observations, (c) modeled 24-hr average wildfire smoke PM2.5 from the Community Multiscale Air Quality Modeling System (CMAQ), and (d) CMAQ daily 1-hr maximum wildfire smoke PM2.5. The magnitude and statistical significance of health outcome associations varied substantially across exposure estimates and referent period selections. CMAQ-based exposure estimates produced odds ratios with wider confidence intervals (CIs), while the product that leveraged both regulatory and bias-corrected PurpleAir measurements improved the PM2.5 measurement spatial coverage and yielded epidemiological estimates with narrower CIs. This highlights the importance of low-cost sensors in rural regions. Our findings emphasize the need to critically assess the inputs used in epidemiological studies for accurate and meaningful results, emphasizing the need for careful consideration of exposure assessment methods and study design when evaluating wildfire smoke health impacts.

ABSTRACT Climate change is intensifying wildfire seasons, disproportionately affecting populations like manufactured home communities. Community‐engaged health communication requires purposeful relationship‐building and systematic exploration of community perspectives to develop campaigns centered on community needs. We conducted in‐depth interviews (n = 19) with residents in Colorado to explore perceptions of wildfire smoke risks, barriers to protective actions, and information sharing within their networks. Findings emphasize the need for community‐centered approaches to develop targeted, actionable air quality communications that build on existing community resilience.

Ambient air pollution remains a leading environmental risk factor for morbidity and mortality in the U.S, though most research is conducted in urban areas. Our study assessed how sociodemographic factors indicative of social vulnerability were associated with smoke from agricultural burns in Florida. We assessed census-level sociodemographic variables among four counties adjacent to the Everglades Agricultural Area (n = 409 census tracts, 2016-2020). Smoke day counts from local agricultural fires were based on satellite plumes identified from the National Oceanic and Atmospheric Administration Hazard Mapping System. Primary analysis fit a negative binomial model with bidirectional stepwise regression, followed by an adjusted geospatial model with a Queen-continuity adjacency matrix. Sensitivity analysis focused on rural-only census tracts. Rural areas had higher concentrations of people of color and poverty compared to coastal urban areas. Median (Q1, Q3) smoke days by census tract was 36 (31, 45), with the highest concentrations in rural central and western regions. Primary model results skewed toward mostly urban tracts, where an interquartile ranges (IQR) increase in median household income was associated with a 12% decrease (95% confidence interval (CI) -14.5%, -5.2%) in smoke days. Among rural-only census tracts, an IQR increase in percentage of residents living 200% below the poverty line and non-English speaking residents were associated with 23% (95% CI: 1.2%, 37.7%) and 120% (95% CI: 20.5%, 176.5%) increases in smoke days, respectively. Sociodemographic factors associated with health and environmental vulnerability were context dependent. Within rural regions, poverty, race and ethnicity played more important roles in exposure risk, whereas wealth mitigated risk among urban areas.

The relationship between exposure to perfluoroalkyl substances (PFAS) and birthweight remains unclear. Pooling data across multiple cohorts can increase power, leading to more representative populations and exposure distributions, but confounding by cohort can be a major source of bias. To understand this potential bias, we assessed the relationship between exposure to five PFAS and birthweight utilizing data from 5480 mother-infant dyads across 17 Environmental influences on Child Health Outcomes (ECHO) Cohort sites. The relationship was assessed in several ways: covariate-adjusted models without cohort adjustment as well as adjustment via fixed and random effects. Findings from analysis with cohort adjustment resulted in significantly inverse relationships for four of the five PFAS considered. Adjustment via fixed and random effects produced similar findings. Failure to adjust for cohort resulted in bias of varying direction and magnitude depending on the PFAS considered. Results were supported in simulated data. In this study, we saw evidence of confounding bias by cohort even after adjustment for covariates, while adjustment by both fixed and random effects for cohort resulted in comparable results.

In recent years the area of wildland fires has increased in the US and many regions have experienced extremely poor air quality due to smoke. We combine data for PM2.5 (particulate matter with diameter <2.5 μm) with a satellite product to identify smoke-influenced days and associated PM2.5 for 2019-2024 from air quality monitors covering 85% of the US population. Averaged across the US, smoke is present on 14.2% of all days and increases the daily mean PM2.5 concentration on these days by 6.9 μg m-3, with a maximum of 687 μg m-3. For each region, we estimate the contribution of smoke PM2.5 to emergency department visits (EDV) for asthma. While rural regions in the western US have the highest contributions of smoke to the PM2.5 concentrations, larger metropolitan areas have a greater number of EDV from smoke due to greater populations. We next consider the impacts of smoke on compliance with the US annual standard for PM2.5 (9.0 μg m-3). Using data for 2022-2024, out of 807 of monitors studied 174 would not meet the standard, but in the absence of smoke, only 57 of these would not meet the standard. While observed annual PM2.5 has shown no significant change over the past 6 years, we find a significant decline in PM2.5 when the smoke contributions are excluded.

Smoke from agricultural fires is a potentially important source of fine particulate matter (PM2.5) in the US. Sugarcane is burned in Florida to facilitate the harvesting process, with the majority of these fires occurring in the Everglades Agricultural Area (EAA), where there is only one regulatory air quality monitor. During the 2022-2023 sugarcane burning season (October-May), we used public low-cost PurpleAir sensors, regulatory monitors, and 29 PurpleAir sensors deployed for this study to quantify PM2.5 from agricultural fires. We found satellite imagery is of limited use for detecting smoke from agricultural fires in Florida due to the cloud cover, overnight smoke, and the fires being small and short-lived. For these reasons, surface measurements are critical for capturing increases in PM2.5 from smoke, and we used multiple smoke-identification criteria. During the study period, median 24-hour PM2.5 concentrations increased by 2.3-6.9 μg m-3 on smoke-impacted days compared to unimpacted days, with smoke observed on 4%-28% of the campaign days (ranges from the different smoke-identification criteria). Further, short-term PM2.5 increases were observed over 40 μg m-3 during smoke events. We contrast the region near the EAA with large populations of low-income and minoritized groups to the more affluent coastal region. The inland region experienced more smoke-impacted monitor days than the Florida east coast region, and there was a higher study-average smoke PM2.5 concentration in the inland area. These findings highlight the need to increase air quality monitoring near the EAA.