Spatial Heterogeneity of the Respiratory Health Impacts of Wildfire Smoke PM2.5 in California.

Wildfire smoke fine particles (PM2.5) are a growing public health threat as wildfire events become more common and intense under climate change, especially in the Western United States. Studies assessing the association between wildfire PM2.5 exposure and health typically summarize the effects over the study area. However, health responses to wildfire PM2.5 may vary spatially. We evaluated spatially-varying respiratory acute care utilization risks associated with short-term exposure to wildfire PM2.5 and explored community characteristics possibly driving spatial heterogeneity. Using ensemble-modeled daily wildfire PM2.5, we defined a wildfire smoke day to have wildfire-specific PM2.5 concentration ≥15 µg/m3. We included daily respiratory emergency department visits and unplanned hospitalizations in 1,396 California ZIP Code Tabulation Areas (ZCTAs) and 15 census-derived community characteristics. Employing a case-crossover design and conditional logistic regression, we observed increased odds of respiratory acute care utilization on wildfire smoke days at the state level (odds ratio [OR] = 1.06, 95% confidence interval [CI]: 1.05, 1.07). Across air basins, ORs ranged from 0.88 to 1.57, with the highest effect estimate in San Diego. A within-community matching design and spatial Bayesian hierarchical model also revealed spatial heterogeneity in ZCTA-level rate differences. For example, communities with a higher percentage of Black or Pacific Islander residents had stronger wildfire PM2.5-outcome relationships, while more air conditioning and tree canopy attenuated associations. We found an important heterogeneity in wildfire smoke-related health impacts across air basins, counties, and ZCTAs, and we identified characteristics of vulnerable communities, providing evidence to guide policy development and resource allocation.

Postfire reproduction of a serotinous conifer, the giant sequoia, in the Nelder Grove, California.

The giant sequoia, a serotinous conifer naturally occurring in mixed-conifer forests of the southern and central Sierra Nevada, California, USA, is the world's largest tree species. Giant sequoia reproduction has been severely lacking over the past century, due to fire exclusion, creating a significant conservation threat. Previous research on postfire sequoia reproduction in high-severity fire areas, relative to low- and moderate-severity areas, is limited. At 6 years postfire, we investigated giant sequoia reproduction in a high-severity fire area, and nearby low-/mixed-severity fire areas, in the Nelder Grove, which burned in 2017 in the Railroad fire. Postfire giant sequoia reproduction was positively correlated with fire severity in terms of density, height (growth), and proportion (relative to other conifer species), and sequoia seedling/sapling density was positively correlated with percent shrub cover. There was no correlation between distance to live sequoia seed source and density of sequoia reproduction. More research is needed in other mixed-severity fire areas, with larger high-severity fire patches, to determine whether a similar postfire response occurs elsewhere.

Ungulates mitigate the effects of drought and shrub encroachment on the fire hazard of Mediterranean oak woodlands.

Climate change is increasing the frequency of droughts and the risk of severe wildfires, which can interact with shrub encroachment and browsing by wild ungulates. Wild ungulate populations are expanding due, among other factors, to favorable habitat changes resulting from land abandonment or land-use changes. Understanding how ungulate browsing interacts with drought to affect woody plant mortality, plant flammability, and fire hazard is especially relevant in the context of climate change and increasing frequency of wildfires. The aim of this study is to explore the combined effects of cumulative drought, shrub encroachment, and ungulate browsing on the fire hazard of Mediterranean oak woodlands in Portugal. In a long-term (18 years) ungulate fencing exclusion experiment that simulated land abandonment and management neglect, we investigated the population dynamics of the native shrub Cistus ladanifer, which naturally dominates the understory of woodlands and is browsed by ungulates, comparing areas with (no fencing) and without (fencing) wild ungulate browsing. We also modeled fire behavior in browsed and unbrowsed plots considering drought and nondrought scenarios. Specifically, we estimated C. ladanifer population density, biomass, and fuel load characteristics, which were used to model fire behavior in drought and nondrought scenarios. Overall, drought increased the proportion of dead C. ladanifer shrub individuals, which was higher in the browsed plots. Drought decreased the ratio of live to dead shrub plant material, increased total fuel loading, shrub stand flammability, and the modeled fire parameters, that is, rate of surface fire spread, fireline intensity, and flame length. However, total fuel load and fire hazard were lower in browsed than unbrowsed plots, both in drought and nondrought scenarios. Browsing also decreased the population density of living shrubs, halting shrub encroachment. Our study provides long-term experimental evidence showing the role of wild ungulates in mitigating drought effects on fire hazard in shrub-encroached Mediterranean oak woodlands. Our results also emphasize that the long-term effects of land abandonment can interact with climate change drivers, affecting wildfire hazard. This is particularly relevant given the increasing incidence of land abandonment.

Seasonal extreme temperatures and short-term fine particulate matter increases pediatric respiratory healthcare encounters in a sparsely populated region of the intermountain western United States.

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.

Trends in Rescue and Rehabilitation of Marsupials Surviving the Australian 2019-2020 Bushfires.

The 2019-2020 Australian bushfire season had a devastating impact on native wildlife. It was estimated that 3 billion native animals were impacted by the fires, yet there are few estimates of the number of animals that were rescued and rehabilitated post-fire. Focusing on the state of New South Wales (NSW) and Kangaroo Island, South Australia, we used a case study approach to determine the number of marsupials that were reported rescued due to the 2019-2020 bushfires in these areas and analysed species-specific trends in rescue and release success. In NSW, we found 889 reports of fire-affected marsupials in 2019-2020, mostly comprising kangaroos and wallabies (macropods; n = 458), koalas (n = 204), and possums (n = 162), with a smaller number of wombats (n = 43) and other marsupial species. Most reports of fire-affected marsupials occurred 6-8 weeks after fire ignition, and there was no difference in temporal frequency of rescues between marsupial groups. For the three main groups, the probability of survival and subsequent release differed, with macropods having the lowest probability of release after rescue (0.15 ± 0.04) compared to koalas (0.47 ± 0.04) and possums (0.55 ± 0.10). The type of injury was the main predictor of survival during rehabilitation for all three marsupial groups, with those malnourished/moribund or with traumatic injuries less likely to survive rehabilitation. Death or euthanasia occurred on the day of rescue for 77% of macropods, 48% of possums and 15% of koalas. Koalas most often died during rehabilitation rather than on the day of rescue, with 73% either dying or being euthanised between day 1 and 30 post-rescue, representing a potential welfare concern. On Kangaroo Island, koalas were the most frequently rescued marsupial species; most euthanasia cases and deaths occurred in a hospital, whereas other marsupials were mostly euthanised at triage. In both jurisdictions, koalas were over-represented while possums were under-represented relative to baseline population densities and wildlife rescue trends in the years before the 2019-2020 bushfires. These species differences in presentation post-fire warrant further investigation, as do the differences in triage, survival and release outcomes. It is hypothesised that the high intensity and large scale of the 2019-2020 fires impeded marsupial fire evasion tactics, as evidenced by the small number of animals found for rescue, and the differing rates of presentation relative to underlying population densities for the main marsupial groups. Based on our findings, there is a need for detailed record keeping and data sharing, development of consistent and evidence-based triage, treatment and euthanasia guidelines and deployment of trained wildlife emergency rescue teams with advanced search techniques to minimise animal suffering where safe to do so.

Exposure to Smoke From Wildfire, Prescribed, and Agricultural Burns Among At-Risk Populations Across Washington, Oregon, and California.

Wildfires, prescribed burns, and agricultural burns all impact ambient air quality across the Western U.S.; however, little is known about how communities across the region are differentially exposed to smoke from each of these fire types. To address this gap, we quantify smoke exposure stemming from wildfire, prescribed, and agricultural burns across Washington, Oregon, and California from 2014 to 2020 using a fire type-specific biomass burning emissions inventory and the GEOS-Chem chemical transport model. We examine fire type-specific PM2.5 concentration by race/ethnicity, socioeconomic status, and in relation to the Center for Disease Control's Social Vulnerability Index. Overall, population-weighted PM2.5 concentrations are greater from wildfires than from prescribed and from agricultural burns. While we found limited evidence of exposure disparities among sub-groups across the full study area, we did observe disproportionately higher exposures to wildfire-specific PM2.5 exposures among Native communities in all three states and, in California, higher agricultural burn-specific PM2.5 exposures among lower socioeconomic groups. We also identified, for all three states, areas of significant spatial clustering of smoke exposures from all fire types and increased social vulnerability. These results provide a first look at the differential contributions of smoke from wildfires, prescribed burns, and agricultural burns to PM2.5 exposures among demographic subgroups, which can be used to inform more tailored exposure reduction strategies across sources.

Shifting fire regimes cause continent-wide transformation of threatened species habitat.

Human actions are causing widespread increases in fire size, frequency, and severity in diverse ecosystems globally. This alteration of fire regimes is considered a threat to numerous animal species, but empirical evidence of how fire regimes are shifting within both threatened species' ranges and protected areas is scarce, particularly at large spatial and temporal scales. We used a big data approach to quantify multidecadal changes in fire regimes in southern Australia from 1980 to 2021, spanning 415 reserves (21.5 million ha) and 129 threatened species' ranges including birds, mammals, reptiles, invertebrates, and frogs. Most reserves and threatened species' ranges within the region have experienced declines in unburnt vegetation (≥30 y without fire), increases in recently burnt vegetation (≤5 y since fire), and increases in fire frequency. The mean percentage of unburnt vegetation within reserves declined from 61 to 36% (1980 to 2021), whereas the mean percentage of recently burnt vegetation increased from 20 to 35%, and mean fire frequency increased by 32%, with the latter two trends primarily driven by the record-breaking 2019 to 2020 fire season. The strongest changes occurred for high-elevation threatened species, and reserves of high elevation, high productivity, and strong rainfall decline, particularly in the southeast of the continent. Our results provide evidence for the widely held but poorly tested assumption that threatened species are experiencing widespread declines in unburnt habitat and increases in fire frequency. This underscores the imperative for developing management strategies that conserve fire-threatened species in an increasingly fiery future.

Niche-based approach to explore the impacts of environmental disturbances on biodiversity.

Globally, species are increasingly at risk from compounding threatening processes, an increasingly prominent driver of which is environmental disturbances. To facilitate effective conservation efforts following such events, methods that evaluate potential impacts across multiple species and provide landscape-scale information are needed to guide targeted responses. Often, the geographic overlap between a disturbance and species' distribution is calculated and then used as a proxy for potential impact. However, such methods do not account for the important influence of environmental heterogeneity throughout species' ranges. To address this shortcoming, we quantified the effects of environmental disturbances on species' environmental niche space. Using the Australian 2019 and 2020 Black Summer fires as a case study, we applied a niche-centric approach to examine the potential impacts of these fires on 387 vertebrate species. We examined the utility of established and novel niche metrics to assess the potential impacts of large-scale disturbance events on species by comparing the potential effects of the fires as determined by our various niche measures to those derived from geographic-based measures of impact. We examined the quality of environmental space affected by the disturbance by quantifying the position in niche space where the disturbance occurred (center or margin), the uniqueness of the environmental space that was burned, and the degree to which the remaining, unburned portion of the niche differed from a species' original prefire niche. There was limited congruence between the proportion of geographic and niche space affected, which showed that geographic-based approaches in isolation may have underestimated the impact of the fires for 56% of modeled species. For each species, when combined, these metrics provided a greater indication of postdisturbance recovery potential than geographic-based measures alone. Accordingly, the integration of niche-based analyses into conservation assessments following large-scale disturbance events will lead to a more nuanced understanding of potential impacts and guide more informed and effective conservation actions.

Estrategia basada en los nichos para explorar el impacto de la perturbación ambiental sobre la biodiversidad Resumen En todo el mundo, las especies corren un riesgo cada vez mayor de verse amenazadas por procesos combinados, entre los que destacan las perturbaciones ambientales. Para facilitar una labor de conservación eficaz después de estos fenómenos, se necesitan métodos que evalúen el impacto potencial en varias especies y proporcionen información a escala de paisaje para orientar las respuestas específicas. A menudo, se calcula el traslape geográfico entre una perturbación y la distribución de las especies y se utiliza como indicador del impacto potencial. Sin embargo, estos métodos no tienen en cuenta la influencia importante de la heterogeneidad ambiental en toda el área de distribución de las especies. Para abordar esta deficiencia, cuantificamos los efectos de las perturbaciones ambientales en el espacio del nicho ambiental de las especies. Usamos los incendios australianos de Black Summer de 2019 y 2020 como caso de estudio y aplicamos un enfoque centrado en el nicho para examinar los impactos potenciales de estos incendios en 387 especies de vertebrados. Analizamos la utilidad de las métricas nuevas y establecidas de nicho para evaluar los impactos potenciales de los eventos de perturbación a gran escala para las especies con la comparación de los efectos potenciales de los incendios determinados por nuestras diversas medidas de nicho con los derivados de las medidas de impacto basadas en la geografía. Examinamos la calidad del espacio ambiental afectado por la perturbación al cuantificar la posición en el espacio del nicho donde se produjo la perturbación (centro o margen), la singularidad del espacio ambiental que se quemó y el grado en que la parte restante no quemada del nicho difería del nicho original de una especie antes del incendio. Hubo una congruencia limitada entre la proporción del espacio geográfico y del nicho afectado, lo que demostró que los enfoques geográficos aislados pueden subestimar el impacto de los incendios para el 56% de las especies modeladas. Para cada especie, estas métricas combinadas proporcionaron una mayor indicación del potencial de recuperación tras las perturbaciones que las medidas geográficas por sí solas. Por lo tanto, la integración de los análisis basados en nichos en las evaluaciones de conservación tras perturbaciones a gran escala permitirá comprender mejor los impactos potenciales y orientar las acciones de conservación de manera más informada y eficaz.

Climate change and health: rethinking public health messaging for wildfire smoke and extreme heat co-exposures.

With the growing climate change crisis, public health agencies and practitioners must increasingly develop guidance documents addressing the public health risks and protective measures associated with multi-hazard events. Our Policy and Practice Review aims to assess current public health guidance and related messaging about co-exposure to wildfire smoke and extreme heat and recommend strengthened messaging to better protect people from these climate-sensitive hazards. We reviewed public health messaging published by governmental agencies between January 2013 and May 2023 in Canada and the United States. Publicly available resources were eligible if they discussed the co-occurrence of wildfire smoke and extreme heat and mentioned personal interventions (protective measures) to prevent exposure to either hazard. We reviewed local, regional, and national governmental agency messaging resources, such as online fact sheets and guidance documents. We assessed these resources according to four public health messaging themes, including (1) discussions around vulnerable groups and risk factors, (2) symptoms associated with these exposures, (3) health risks of each exposure individually, and (4) health risks from combined exposure. Additionally, we conducted a detailed assessment of current messaging about measures to mitigate exposure. We found 15 online public-facing resources that provided health messaging about co-exposure; however, only one discussed all four themes. We identified 21 distinct protective measures mentioned across the 15 resources. There is considerable variability and inconsistency regarding the types and level of detail across described protective measures. Of the identified 21 protective measures, nine may protect against both hazards simultaneously, suggesting opportunities to emphasize these particular messages to address both hazards together. More precise, complete, and coordinated public health messaging would protect against climate-sensitive health outcomes attributable to wildfire smoke and extreme heat co-exposures.

Establishing the relationship between wildfire smoke and performance metrics on finished beef cattle in Western Rangelands.

Identifying causal relationships is complicated. Researchers usually overlook causality behind relationships which can generate misleading associations. Herein, we carefully examine the parametric relationship and causality between wildfire smoke exposure and animal performance and behavior metrics over a period of 2 yr in Reno, Nevada. The animals in the 2020 smoke season were grain-finished (n = 12) and grass-finished (n = 12), whereas the animals during the 2021 season were fed under the same diet but finished with either a hormonal implant (n = 9), or without (n = 9). The dataset included daily records of feed intake (FI), body weight (BW), water intake (WI), average daily gain (ADG), and WI behavior (time spent drinking [TSD]; water intake events [WIE]; no-WIE [NWIE]). Variable tree length Bayesian additive regression trees (BART) were utilized to investigate the relationships between air quality index (AQI), particulate matter 2.5 µm (PM2.5) and 10 µm (PM10), NO2, SO2, Ozone, and CO levels in the air (sensors < 1.6 km from animals) with the animal data. Additionally, linear mixed models with a 7-d lag were used to evaluate parametric relationships among the same variables. All statistical analyses were performed on R Statistical Software (R Core Team 2023). Under the linear mixed model with a 7-d lag, significant positive and negative associations were found for all parameters examined (P < 0.05). Negative associations were found between FI, WI, ADG, BW, WIE, NWIE, TSD, and PM2.5 (P < 0.05) for at least one animal group. Positive linear associations between wildfire smoke parameters and the metrics evaluated were more variable and dependent on year, treatment, and smoke parameters. When examining the credible intervals and the variable importance in the BART, relationships were more difficult to identify. However, some associations were found for Ozone, AQI, NO2, CO, and PM10 (P < 0.05). Overall, our results carefully examine the relationship between smoke parameters and cattle performance and present interesting pathways previously unexplored that could guide early culling/finishing of animals to avoid economic losses associated with performance decrease in response to wildfire smoke exposure. Though interesting associations are found under linear mixed models, causality is difficult to establish, which highlights the need for controlled exposure experiments.

Phyllosphere bacterial community dynamics in response to bacterial wildfire disease: succession and interaction patterns.

Plants interact with complex microbial communities in which microorganisms play different roles in plant development and health. While certain microorganisms may cause disease, others promote nutrient uptake and resistance to stresses through a variety of mechanisms. Developing plant protection measures requires a deeper comprehension of the factors that influence multitrophic interactions and the organization of phyllospheric communities. High-throughput sequencing was used in this work to investigate the effects of climate variables and bacterial wildfire disease on the bacterial community's composition and assembly in the phyllosphere of tobacco (Nicotiana tabacum L.). The samples from June (M1), July (M2), August (M3), and September (M4) formed statistically separate clusters. The assembly of the whole bacterial population was mostly influenced by stochastic processes. PICRUSt2 predictions revealed genes enriched in the M3, a period when the plant wildfire disease index reached climax, were associated with the development of the wildfire disease (secretion of virulence factor), the enhanced metabolic capacity and environmental adaption. The M3 and M4 microbial communities have more intricate molecular ecological networks (MENs), bursting with interconnections within a densely networked bacterial population. The relative abundances of plant-beneficial and antagonistic microbes Clostridiales, Bacillales, Lactobacillales, and Sphingobacteriales, showed significant decrease in severally diseased sample (M3) compared to the pre-diseased samples (M1/M2). Following the results of MENs, we further test if the correlating bacterial pairs within the MEN have the possibility to share functional genes and we have unraveled 139 entries of such horizontal gene transfer (HGT) events, highlighting the significance of HGT in shaping the adaptive traits of plant-associated bacteria across the MENs, particularly in relation to host colonization and pathogenicity.

Assessing wildfire exposure and social vulnerability at the local scale using a GIS-based approach.

Exposure and vulnerability analysis are valuable tools for wildfire management, especially important for local communities that suffer from very destructive events and that require mitigation approaches adjusted to their abilities and needs. We present a methodological procedure to analyze wildfire exposure levels, social vulnerability conditions and coping capacity at the local scale, for villages or small human settlements. The procedure was developed using GIS (Geographic Information Systems) and programming tools in R and Python, which can be adapted and updated depending on the data available. The development of accessible procedures and easily replicable methodologies facilitates knowledge transfer and supports the application of mitigation and adaptation strategies, tailored to the conditions of the exposed areas.•A step-by-step procedure for the assessment of Exposure, Vulnerability, and Coping Capacity, using Python and R programming language.•Automated processes, easily replicable and adjustable to other areas.•Indications for adapting the methodology using European/international databases.

Dynamically bonded cellulose nanocrystal hydrogels: Structure, rheology and fire prevention performance.

Flame retardant composite hydrogels offer many advantages over conventional flame retardants, such as high water-retention capacity, enhanced fire resistance, and mechanical tunability. Herein, we developed flame-retardant dynamic covalent hydrogels using wood-derived cellulose nanocrystals (CNCs) crosslinked with boronate ester bonds, addressing environmental and health issues associated with the presence of non-biodegradable synthetic polymer and/or inorganic nanoparticle components in the existing systems. Our rheological investigation shows a liquid-to-soft-solid transition of CNC dispersions with tunable network elasticity ranging between ≈ 0.2 kPa to 3.5 kPa and an immediate self-healing ability. Coating pine wood with these hydrogels delayed ignition by about 30 s compared to native wood, and achieved a remarkable limiting oxygen index of 64.5 %. Also, the increased borax content of the gels was found to decrease and delay the first peak of the heat release rate up to 40 s, causing an increase in the fire retardancy index by 277 %. We correlate the microstructure and rheological behavior with the fire prevention mechanisms for the rational design of sustainable fire-retardant materials, and the results showcased a circular use of plant-based dynamic gels to prevent wood fires, even after drying- a feature lacking in conventional hydrogels.

Devastating Wildfires and Mental Health: Major Depressive Disorder Prevalence and Associated Factors among Residents in Alberta and Nova Scotia, Canada.

Background: Since March 2023, hundreds of fires have burned from coast to coast throughout the country, placing Canada on track to have the worst wildfire season ever recorded. From East to West, provinces such as Quebec, Ontario, Nova Scotia, Alberta, and British Columbia have been particularly affected by large and uncontrollable wildfires. Objectives: The objective of this study was to determine the prevalence of depression symptoms and predictors among residents living in extreme climate conditions during the Canadian wildfires of 2023 in Alberta and Nova Scotia and to update the literature with data related to those wildfires. Methods: A cross-sectional quantitative survey was conducted in this study. REDCap was used to administer an online survey between 14 May and 23 June 2023. Through the Text4Hope program, participants subscribe to receive supportive SMS messages daily. As part of the initial welcome message, participants were invited to complete an online questionnaire, containing demographic information, wildfire-related information, and responses to the Patient Health Questionnaire-9 (PHQ-9) for depression assessment. SPSS version 25 was used to analyze the data. Descriptive, univariate, and multivariate regression analyses were employed. Results: A total of 298 respondents completed the survey out of 1802 who self-subscribed to the Text4Hope program in Alberta and Nova Scotia and received a link to the online survey, producing a response rate of 16.54%. Most of the respondents were females (85.2%, 253), below 40 years of age (28.3%, 84), employed (63.6%, 189), and in a relationship (56.4%, 167). A historical depression diagnosis (OR = 3.15; 95% CI: 1.39-7.14) was a significant predictor of moderate to severe MDD in our study. The unemployed individuals were two times more likely to report moderate to severe symptoms of MDD than employed individuals (OR = 2.46; 95% CI: 1.06-5.67). Among the total sample population, the moderate to severe MDD prevalence was 50.4%, whereas it was 56.1% among those living in areas affected by wildfires. Conclusion: Based on our study findings, unemployment and a history of depression diagnosis were independently significant risk factors associated with the developing moderate to severe MDD symptoms during wildfire disasters. Further research is required to identify robust predictors of mental health disorders in disaster survivors and provide appropriate interventions to the most vulnerable communities and individuals.

Spatial analysis and machine learning prediction of forest fire susceptibility: a comprehensive approach for effective management and mitigation.

Forest fires (FF) in tropical seasonal forests impact ecosystem. Addressing FF in tropical ecosystems has become a priority to mitigate impacts on biodiversity loss and climate change. The escalating frequency and intensity of FF globally have become a mounting concern. Understanding their tendencies, patterns, and vulnerabilities is imperative for conserving ecosystems and facilitating the development of effective prevention and management strategies. This study investigates the trends, patterns, and spatiotemporal distribution of FF for the period of 2001-2022, and delineates the forest fire susceptibility zones in Odisha State, India. The study utilized: (a) MODIS imagery to examine active fire point data; (b) Kernel density tools; (c) FF risk prediction using two machine learning algorithms, namely Support Vector Machine (SVM) and Random Forest (RF); (d) Receiver Operating Characteristic and Area Under the Curve, along with various evaluation metrics; and (e) a total of 19 factors, including three topographical, seven climatic, four biophysical, and five anthropogenic, to create a map indicating areas vulnerable to FF. The validation results revealed that the RF model achieved a precision exceeding 94 % on the validation datasets, while the SVM model reached 89 %. The estimated forest fire susceptibility zones using RF and SVM techniques indicated that 20.14 % and 16.72 % of the area, respectively, fall under the "Very High Forest Fire" susceptibility class. Trend analysis reveals a general upward trend in forest fire occurrences (R2 = 0.59), with a notable increase after 2015, peaking in 2021. Notably, Angul district was identified as the most affected area, documenting the highest number of forest fire incidents over the past 22 years. Additionally, forest fire mitigation plans have been developed by drawing insights from forest fire management strategies implemented in various countries worldwide. Overall, this analysis provides valuable insights for policymakers and forest management authorities to develop effective strategies for forest fire prevention and mitigation.

Wildfire particulate exposure and risks of preterm birth and low birth weight in the Southwestern United States.

OBJECTIVES: Wildfire air pollution is a growing concern on human health. The study aims to assess the associations between wildfire air pollution and pregnancy outcomes in the Southwestern United States. STUDY DESIGN: This was a retrospective cohort study. METHODS: Birth records of 627,404 singleton deliveries in 2018 were obtained in eight states of the Southwestern United States and were linked to wildfire-sourced fine particulate matter (PM2.5) and their constituents (black carbon [BC] and organic carbon [OC]) during the entire gestational period. A double-robust logistic regression model was used to assess the associations of wildfire-sourced PM2.5 exposures and preterm birth and term low birth weight, adjusting for non-fire-sourced PM2.5 exposure and individual- and area-level confounder variables. RESULTS: Wildfire-sourced PM2.5 contributed on average 15% of the ambient total PM2.5 concentrations. For preterm birth, the strongest association was observed in the second trimester (odds ratio [OR]: 1.06, 95% confidence interval [CI]: 1.05-1.07 for PM2.5; 1.06, 95% CI: 1.05-1.07 for BC; 1.04, 95% CI: 1.03-1.05 for OC, per interquartile range increment of exposure), with higher risks identified among non-smokers or those with low socio-economic status. For term low birth weight, the associations with wildfire-sourced PM2.5 exposures were consistently elevated for all trimesters except for the exposure averaged over the entire gestational period. Overall, the associations between wildfire-sourced PM2.5 and pregnancy outcomes were stronger than those with total PM2.5. CONCLUSIONS: Wildfire-sourced PM2.5 and its constituents are linked to higher risks of preterm birth and term low birth weight among a significant US population than the effects of ambient total PM2.5.

Biomonitoring of polycyclic aromatic hydrocarbons exposure and short-time health effects in wildland firefighters during real-life fire events.

Human biomonitoring data retrieved from real-life wildland firefighting in Europe and, also, worldwide are scarce. Thus, in this study, 176 Portuguese firefighters were biomonitored pre- and post- unsimulated wildfire combating (average:12-13 h; maximum: 55 h) to evaluate the impact on the levels of urinary polycyclic aromatic hydrocarbons hydroxylated metabolites (OHPAH; quantified by high-performance liquid chromatography with fluorescence detection) and the associated short-term health effects (symptoms, and total and differentiated white blood cells). Correlations between these variables and data retrieved from the self-reported questionnaires were also investigated. Firefighters were organized into four groups according to their exposure to wildfire emissions and their smoking habits: non-smoking non-exposed (NSNExp), non-smoking exposed (NSExp), smoking non-exposed (SNExp), and smoking and exposed (SExp). The most abundant metabolites were 1-hydroxynaphthalene and 1-hydroxyacenaphthene (1OHNaph + 1OHAce) (98-99 %), followed by 2-hydroxyfluorene (2OHFlu) (0.2-1.1 %), 1-hydroxyphenanthrene (1OHPhen) (0.2-0.4 %), and 1-hydroxypyrene (1OHPy) (0.1-0.2 %); urinary 3-hydroxybenzo(a)pyrene was not detected. The exposure to wildfire emissions significantly elevated the median concentrations of each individual and total OHPAH compounds in all groups, but this effect was more pronounced in non-smoking (1.7-4.2 times; p ≤ 0.006) than in smoking firefighters (1.3-1.6 times; p ≤ 0.03). The greatest discriminant of exposure to wildfire emissions was 1OHNaph + 1OHAce (increase of 4.2 times), while for tobacco smoke it was 2OHFlu (increase of 10 times). Post-exposure, white blood cells count significantly increased ranging from 1.4 (smokers, p = 0.025) to 3.7-fold (non-smokers, p < 0.001), which was accompanied by stronger significant correlations (0.480 < r < 0.882; p < 0.04) between individual and total OHPAH and total white blood cells (and lymphocytes > monocytes > neutrophils in non-smokers), evidencing the impact of PAH released from wildfire on immune cells. This study identifies Portuguese firefighters with high levels of biomarkers of exposure to PAH and points out the importance of adopting biomonitoring schemes, that include multiple biomarkers of exposure and biomarkers of effect, and implementing mitigations strategies.

Assessing the 2023 Canadian wildfire smoke impact in Northeastern US: Air quality, exposure and environmental justice.

The Canadian wildfires in June 2023 significantly impacted the northeastern United States, particularly in terms of worsened air pollution and environmental justice concerns. While advancements have been made in low-cost sensor deployments and satellite observations of atmospheric composition, integrating dynamic human mobility with wildfire PM2.5 exposure to fully understand the environmental justice implications remains underinvestigated. This study aims to enhance the accuracy of estimating ground-level fine particulate matter (PM2.5) concentrations by fusing chemical transport model outputs with empirical observations, estimating exposures using human mobility data, and evaluating the impact of environmental justice. Employing a novel data fusion technique, the study combines the Weather Research and Forecasting model with Chemistry (WRF-Chem) outputs and surface PM2.5 measurements, providing a more accurate estimation of PM2.5 distribution. The study addresses the gap in traditional exposure assessments by incorporating human mobility data and further investigates the spatial correlation of PM2.5 levels with various environmental and demographic factors from the US Environmental Protection Agency (EPA) Environmental Justice Screening and Mapping Tool (EJScreen). Results reveal that despite reduced mobility during high PM2.5 levels from wildfire smoke, exposure for both residents and individuals on the move remains high. Regions already burdened with high environmental pollution levels face amplified PM2.5 effects from wildfire smoke. Furthermore, we observed mixed correlations between PM2.5 concentrations and various demographic and socioeconomic factors, indicating complex exposure patterns across communities. Urban areas, in particular, experience persistent high exposure, while significant correlations in rural areas with EJScreen factors highlight the unique vulnerabilities of these populations to smoke exposure. These results advocate for a comprehensive approach to environmental health that leverages advanced models, integrates human mobility data, and addresses socio-demographic disparities, contributing to the development of equitable strategies against the growing threat of wildfires.

Respiratory Diseases Associated With Wildfire Exposure in Outdoor Workers.

Wildfires, including forest fires, bushfires, and landscape fires, have become increasingly prevalent, fueled by climate change and environmental factors and posing significant challenges to both ecosystems and public health. This review article examines the relationship between wildfires and respiratory diseases in outdoor workers, with a main focus on airway disease. In addition to the expected effects of direct thermal respiratory injuries and possible carbon monoxide poisoning, there are associations between wildfires and upper and lower respiratory effects, including infections as well as exacerbations of asthma and chronic obstructive pulmonary disease. A few studies have also shown an increased risk of new-onset asthma among wildfire firefighters. Outdoor workers are likely to have greater exposure to wildfire smoke with associated increased risks of adverse effects. As wildfires become increasingly prevalent globally, it is crucial to understand the various dimensions of this association. Furthermore, this review addresses preventive measures and potential interventions to alleviate the airway burden on individuals during and after work with wildfires events.