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This work is a contribution to the understanding of wildfire smoke emissions. It focuses on the characterization of aerosols emitted by the combustion of dead shrub leaves and twigs with different thickness (range of 0.75–20 mm). The experiments were carried out at bench scale with a cone calorimeter for the burning of Cistus monspeliensis leaves and twigs. Auto-ignition of the samples was obtained by heating their surface with a radiant heat flux of 50 kW/m 2 . The smoke and aerosols emitted before ignition during pre-heating were analysed separately from the smoke and aerosols emitted during the flaming phase. Heat release rate (HRR) was also measured and we observed two different behaviours depending on the diameter of the twigs. Fuel samples with diameter smaller than 4 mm exhibit a single peak HRR whereas two peaks were observed for the twigs with larger diameters. The smoke production rate (SPR) was also measured and it showed that smoke was mainly emitted during the pre-heating phase. We also obtained a strong correlation between HRR and SPR during the flaming phase but no smoke was emitted during the glowing phase. Emission factors of aerosols were calculated depending on these combustion phases (pre-ignition and flaming) and for the range of thickness of the samples. The observations of the aerosols were performed by scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The chemical composition of organic carbon (OC) aerosols, emitted during the pre-ignition phase, were analysed using gas chromatography (GC) coupled with mass spectrometry (MS). Some carcinogenic compounds were identified. The sizes of OC and black carbon (BC) aerosols emitted were measured with an optical device. Most of the BC were PM 0.3 , which corresponds to the alveolar fraction of particles. [ABSTRACT FROM AUTHOR]

In 2020, the American West faced two competing challenges: the COVID-19 pandemic and the worst wildfire season on record. Several studies have investigated the impact of wildfire smoke (WFS) on COVID-19 morbidity and mortality, but little is known about how these two public health challenges impact mortality risk for other causes. Using a time-series design, we evaluated how daily risk of mortality due to WFS exposure differed for periods before and during the COVID-19 pandemic. Our study included daily data for 11 counties in the Front Range region of Colorado (2010–2020). We assessed WFS exposure using data from the National Oceanic and Atmospheric Administration and used mortality counts from the Colorado Department of Public Health and Environment. We estimated the interaction between WFS and the pandemic (an indicator variable) on mortality risk using generalized additive models adjusted for year, day of week, fine particulate matter, ozone, temperature, and a smoothed term for day of year. WFS impacted the study area on 10% of county-days. We observed a positive association between the presence of WFS and all-cause mortality risk (incidence rate ratio (IRR) = 1.03, 95%CI: 1.01–1.04 for same-day exposures) during the period before the pandemic; however, WFS exposure during the pandemic resulted in decreased risk of all-cause mortality (IRR = 0.90, 95%CI: 0.87–0.93 for same-day exposures). We hypothesize that mitigation efforts during the first year of the pandemic, e.g., mask mandates, along with high ambient WFS levels encouraged health behaviors that reduced exposure to WFS and reduced risk of all-cause mortality. Our results suggest a need to examine how associations between WFS and mortality are impacted by pandemic-related factors and that there may be lessons from the pandemic that could be translated into health-protective policies during future wildfire events. • We assessed the interaction of COVID-19 and wildfire smoke on non-COVID mortality. • Smoke was associated with increased all-cause mortality risk before the pandemic. • During the pandemic, smoke exposure was protective for all-cause mortality risk. • Mitigation efforts during the pandemic may have reduced population smoke exposure. [ABSTRACT FROM AUTHOR]

Competing Interests: AV has received consultancy fees from Amgen and Novartis. PK has received consultancy fees, lecture honoraria, and/or travel fees from Amarin, Amgen, Novartis, Raisio Group, and Sanofi. BB none. FR has received research grants, honoraria, or consulting fees for professional input and/or lectures from Sanofi, Regeneron, Amgen, Novartis, and LIB Therapeutics. AV declared that he is an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Human health risk assessments for complex mixtures can address real-world exposures and protect public health. While risk assessors typically prefer whole mixture approaches over component-based approaches, data from the precise exposure of interest are often unavailable and surrogate data from a sufficiently similar mixture(s) are required. This review describes recent advances in determining sufficient similarity of whole, complex mixtures spanning the comparison of chemical features, bioactivity profiles, and statistical evaluation to determine "thresholds of similarity". Case studies, including water disinfection byproducts, botanical ingredients, and wildfire emissions, are used to highlight tools and methods. Limitations to application of sufficient similarity in risk-based decision making are reviewed and recommendations presented for developing best practice guidelines., Competing Interests: Competing interests The authors declare that they have no competing interests. Declaration of interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

To understand the health effects of wildfire smoke, it is important to accurately assess smoke exposure over space and time. Particulate matter (PM) is a predominant pollutant in wildfire smoke. In this study, we develop land-use regression (LUR) models to investigate the impact that a cluster of wildfires in the northwest USA had on the level of PM in southern Alberta (Canada), in the summer of 2015. Univariate aerosol optical depth (AOD) and multivariate AOD-LUR models were used to estimate the level of PM2.5 in urban and rural areas. For epidemiological studies, it is also important to distinguish between wildfire-related PM2.5 and PM2.5 originating from other sources. We therefore subdivided the study period into three sub-periods: (1) Pre-fire, (2) during-fire, and (3) post-fire. We then developed separate models for each sub-period. With this approach, we were able to identify different predictors significantly associated with smoke-related PM2.5 verses PM2.5 of different origin. Leave-one-out cross-validation (LOOCV) was used to evaluate the models’ performance. Our results indicate that model predictors and model performance are highly related to the level of PM2.5, and the pollution source. The predictive ability of both uni- and multi-variate models were higher in the during-fire period than in the pre- and post-fire periods.

Wildfires are increasing in magnitude, frequency, and severity. Populations in the wildland-urban interface and in downwind communities are at increased risk of exposure to elevated concentrations of fine particulate matter (PM 2.5) and other harmful components of wildfire smoke. We conducted this analysis to evaluate the use of modeled predictions of wildfire smoke to create county-level measures of smoke exposure for public health research and surveillance. We evaluated four years (2015–2018) of grid-based North American Mesoscale (NAM)-derived PM 2.5 forecasts from the U.S. Forest Service BlueSky modeling framework with monitoring data from the Environmental Protection Agency Air Quality System (AQS), the Interagency Monitoring of Protected Visual Environments (IMPROVE), the Western Regional Climate Center (WRCC), and the Interagency Real Time Smoke Monitoring (AIRSIS) programs. To assess relationships between model-derived estimates and monitor-based observations, we assessed Spearman's correlations by spatial (i.e., county, level of urbanization, states in the western United States impacted by major wildfires, and climate regions) and temporal (i.e., month and wildfire activity periods) characteristics. We then generated county-level smoke estimates and examined spatial and temporal patterns in total and person-days of smoke exposure. Across all counties in the coterminous United States and for all days, the correlation between county-level model- and monitor-derived PM 2.5 estimates was 0.14 (p < 0.001). Correlations were stronger using data from temporary monitors and for areas and days impacted by high wildfire smoke, especially in the western United States. Correlations between county-level model- and monitor-derived estimates in non-metropolitan counties, and at higher concentrations ranged from 0.25 to 0.54 (p < 0.001). In general, public health practitioners and health researchers need to consider the pros and cons associated with modeled data products for conducting health analyses. Our results support the use of model-derived smoke estimates to identify communities impacted by heavy smoke events, especially during emergency response and for communities located near wildfire episodes. • Spatial and temporal gaps in monitoring network data may be reduced by using archived gridded model predictions. • Correlations between BlueSky- and monitor-derived estimates were stronger using data from temporary monitors. • Model-derived smoke estimates can be used to identify communities impacted by heavy smoke events or near wildfire episodes. [ABSTRACT FROM AUTHOR]

[Display omitted] • Wildfire PM 2.5 was associated with DNA methylation of many human genome loci. • Those loci were mapped to 47 genes related to many human diseases. • The genes were enriched in inflammatory regulation and platelet activation pathways. • DNA methylation signatures of wildfire and non-wildfire PM 2.5 were quite different. Wildfire-related fine particulate matter (PM 2.5) has many adverse health impacts, but its impacts on human epigenome are unknown. We aimed to evaluate the associations between long-term exposure to wildfire-related PM 2.5 and blood DNA methylation, and whether the associations differ from those with non-wildfire-related PM 2.5. We studied 479 Australian women comprising 132 twin pairs and 215 of their sisters. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on 3-year (year of blood collection and previous two years) average wildfire-related and non-wildfire-related PM 2.5 at 0.01°×0.01° spatial resolution were created by combining information from satellite observations, chemical transport models, and ground-based observations. Exposure data were linked to each participant's home address, assuming the address did not change during the exposure window. For DNA methylation of each cytosine-guanine dinucleotide (CpG), and for global DNA methylation represented by the average of all measured CpGs or CpGs in repetitive elements, we evaluated their associations with wildfire- or non-wildfire-related PM 2.5 using a within-sibship analysis controlling for factors shared between siblings and other important covariates. Differentially methylated regions (DMRs) were defined by comb-p and DMRcate. The 3-year average wildfire-related PM 2.5 (range: 0.3 to 7.6 µg/m3 , mean: 1.6 µg/m3) was negatively, but not significantly (p -values greater than 0.05) associated with all seven global DNA methylation measures. There were 26 CpGs and 33 DMRs associated with wildfire-related PM 2.5 (Bonferroni adjusted p -value < 0.05) mapped to 47 genes enriched for pathways related to inflammatory regulation and platelet activation. These genes have been related to many human diseases or phenotypes e.g., cancer, mental disorders, diabetes, obesity, asthma, blood pressure. These CpGs, DMRs and enriched pathways did not overlap with the 1 CpG and 7 DMRs associated with non-wildfire-related PM 2.5. Long-term exposure to wildfire-related PM 2.5 was associated with various blood DNA methylation signatures in Australian women, and these were distinct from those associated with non-wildfire-related PM 2.5. [ABSTRACT FROM AUTHOR]

Wildfires are increasing in prevalence in western North America due to changing climate conditions. A growing number of studies examine the impact of wildfire smoke on morbidity; however, few evaluate these impacts using syndromic surveillance data that cover many emergency departments (EDs). We used syndromic surveillance data to explore the effect of wildfire smoke exposure on all-cause respiratory and cardiovascular ED visits in Washington state. Using a time-stratified case crossover design, we observed an increased odds of asthma visits immediately after and in all five days following initial exposure (lag 0 OR: 1.13; 95% CI: 1.10, 1.17; lag 1-5 ORs all 1.05 or greater with a lower CI of 1.02 or higher), and an increased odds of respiratory visits in all five days following initial exposure (lag 1 OR: 1.02; 95% CI: 1.00, 1.03; lag 2-5 ORs and lower CIs were all at least as large) comparing wildfire smoke to non-wildfire smoke days. We observed mixed results for cardiovascular visits, with evidence of increased odds emerging only several days following initial exposure. We also found increased odds across all visit categories for a 10 μ g m -3 increase in smoke-impacted PM 2.5 . In stratified analyses, we observed elevated odds for respiratory visits among ages 19-64, for asthma visits among ages 5-64, and mixed risk estimates for cardiovascular visits by age group. This study provides evidence of an increased risk of respiratory ED visits immediately following initial wildfire smoke exposure, and increased risk of cardiovascular ED visits several days following initial exposure. These increased risks are seen particularly among children and younger to middle-aged adults., (© 2023 The Author(s). Published by IOP Publishing Ltd.)

Little is known about how low-income residents of urban communities engage their knowledge, attitudes, behaviors, and resources to mitigate the health impacts of wildfire smoke and other forms of air pollution. We interviewed 40 adults in Los Angeles, California, to explore their threat assessments of days of poor air quality, adaptation resources and behaviors, and the impacts of air pollution and wildfire smoke on physical and mental health. Participants resided in census tracts that were disproportionately burdened by air pollution and socioeconomic vulnerability. All participants reported experiencing days of poor air quality due primarily to wildfire smoke. Sixty percent received advanced warnings of days of poor air quality or routinely monitored air quality via cell phone apps or news broadcasts. Adaptation behaviors included remaining indoors, circulating indoor air, and wearing face masks when outdoors. Most (82.5%) of the participants reported some physical or mental health problem or symptom during days of poor air quality, but several indicated that symptom severity was mitigated by their adaptive behaviors. Although low-income residents perceive themselves to be at risk for the physical and mental health impacts of air pollution, they have also adapted to that risk with limited resources.

Landscape fires can produce large quantities of smoke that degrade air quality in both remote and urban communities. Smoke from these fires is a complex mixture of fine particulate matter and gases, exposure to which is associated with increased respiratory and cardiovascular morbidity and mortality. The public health response to short-lived smoke events typically advises people to remain indoors with windows and doors closed, but does not emphasize the use of portable air cleaners (PAC) to create private or public clean air shelters. High efficiency particulate air filters and electrostatic precipitators can lower indoor concentrations of fine particulate matter and improve respiratory and cardiovascular outcomes. We argue that PACs should be at the forefront of the public health response to landscape fire smoke events. [ABSTRACT FROM AUTHOR]

Background: Cardiovascular health effects of fine particulate matter (PM2.5) exposure from wildfire smoke are neither definitive nor consistent with PM2.5 from other air pollution sources. Non-comparability among wildfire health studies limits research conclusions.Methods: We examined cardiovascular and respiratory health outcomes related to peat wildfire smoke exposure in a population where strong associations were previously reported for the 2008 Evans Road peat wildfire. We conducted a population-based epidemiologic investigation of associations between daily county-level modeled wildfire PM2.5 and cardiopulmonary emergency department (ED) visits during the 2011 Pains Bay wildfire in eastern North Carolina. We estimated changes in the relative risk cumulative over 0-2 lagged days of wildfire PM2.5 exposure using a quasi-Poisson regression model adjusted for weather, weekends, and poverty.Results: Relative risk associated with a 10 μg/m(3) increase in 24-h PM2.5 was significantly elevated in adults for respiratory/other chest symptoms 1.06 (1.00-1.13), upper respiratory infections 1.13 (1.05-1.22), hypertension 1.05 (1.00-1.09) and 'all-cause' cardiac outcomes 1.06 (1.00-1.13) and in youth for respiratory/other chest symptoms 1.18 (1.06-1.33), upper respiratory infections 1.14 (1.04-1.24) and 'all-cause' respiratory conditions 1.09 (1.01-1.17).Conclusions: Our results replicate evidence for increased risk of cardiovascular outcomes from wildfire PM2.5 and suggest that cardiovascular health should be considered when evaluating the public health burden of wildfire smoke. [ABSTRACT FROM AUTHOR]

FireWork is an on-line, one-way coupled meteorology–chemistry model based on near-real-time wildfire emissions. It was developed by Environment and Climate Change Canada to deliver operational real-time forecasts of biomass-burning pollutants, in particular fine particulate matter (PM2.5), over North America. Such forecasts provide guidance for early air quality alerts that could reduce air pollution exposure and protect human health. A multi-year (2013–2016) analysis of FireWork forecasts over a five-month period (May to September) was conducted. This work used an archive of FireWork outputs to quantify wildfire contributions to total PM2.5 surface concentrations across North America. Different concentration thresholds (0.2 to 28 µg/m3) and averaging periods (24 h to five months) were considered. Analysis suggested that, on average over the fire season, 76% of Canadians and 69% of Americans were affected by seasonal wildfire-related PM2.5 concentrations above 0.2 µg/m3. These effects were particularly pronounced in July and August. Futhermore, the analysis showed that fire emissions contributed more than 1 µg/m3 of daily average PM2.5 concentrations on more than 30% of days in the western USA and northwestern Canada during the fire season.

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., Competing Interests: The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Lasley.)

ABSTRACT Previous research highlights the dominant role of Pacific sea surface temperatures ( SSTs) and their associated large-scale teleconnections in modulating the North American monsoon (NAM). At the regional scale, feedbacks associated with land-surface boundary conditions have been shown to provide 'memory' in the system. Here, a previously unexplored second-order linkage between aerosol generated by late-spring wildfires and subsequent summer precipitation delivered by the NAM in the Arizona-New Mexico ( AZNM) region is proposed. Correlations between June/July organic carbon and elemental carbon ( OC/ EC) in Inter-agency Monitoring of Protected Visual Environments ( IMPROVE) aerosol data (Gila Wilderness and Bandelier) and NAM precipitation in southern AZNM over the period 1994-2012 are shown to be negative ( r = -0.4), suggesting that active antecedent wildfire seasons tend to be immediately followed by a weak late summer monsoon. This result is consistent with a previous study linking precipitation and area burned in wildfires in AZNM. A survey of extant literature suggests a sound basis for potential mechanisms related to convective processes and cloud microphysics, and furthermore suggests that this forcing could be of similar magnitude to well-documented land-based second-order NAM forcings (antecedent snowpack and soil moisture, vegetation, and mineral dust). Based on these results, we believe that the role of aerosols in modulating summer precipitation deserves further investigation both observationally and in modeling studies. If indeed wildfire smoke does contribute to the modulation of NAM intensity, by virtue of its close temporal association with NAM season, it may well represent a factor that could contribute effectively to improved seasonal prediction of summer precipitation in the NAM region. [ABSTRACT FROM AUTHOR]

On August 8, 2010, a severe derecho type thunderstorm in the Baltic Sea region coincided with smoke from wildfires in Russia. Remarkable smoke aerosol concentrations, with a maximum aerosol optical depth of more than 2 at 550 nm, were observed near the thunderstorm. The impact of the wildfire smoke on the thunderstorm through direct radiative effects was investigated using the Hirlam Aladin Research for Mesoscale Operational Numerical Weather Prediction in Euromed (HARMONIE) model. HARMONIE was successfully able to resolve the dynamics of the thunderstorm, and simulations that considered the influence of the smoke-related aerosols were compared to simulation without aerosols. As simulated by the HARMONIE model, the smoke reduced the shortwave radiation flux at the surface by as much as 300 W/m 2 and decreased the near-surface temperature by as much as 3 °C in the vicinity of the thunderstorm and respectively 100 W/m 2 and 1 °C in the thunderstorm region. Atmospheric instability decreased through the direct radiative effect of aerosols, and several dynamic features of the simulated thunderstorm appeared slightly weaker. [ABSTRACT FROM AUTHOR]

PurpleAir particulate matter (PM) sensors are increasingly used in the United States and other countries for real-time air quality information, particularly during wildfire smoke episodes. Uncorrected PurpleAir data can be biased and may exhibit a nonlinear response at extreme smoke concentrations (>300 µg/m3). This bias and nonlinearity result in a disagreement with the traditional ambient monitoring network, leading to the public’s confusion during smoke episodes. These sensors must be evaluated during smoke-impacted times and then corrected for bias, to ensure that accurate data are reported. The nearby public PurpleAir sensor and monitor pairs were identified during the summer of 2020 and were used to supplement the data from collocated pairs to develop an extended U.S.-wide correction for high concentrations. We evaluated several correction schemes to identify an optimal correction, using the previously developed U.S.-wide correction, up to 300 µg/m3, transitioning to a quadradic fit above 400 µg/m3. The correction reduces the bias at each air quality index (AQI) breakpoint; most ambient collocations that were studied met the Environmental Protection Agency’s (EPA) performance targets (twelve of the thirteen ambient sensors met the EPA’s targets) and some smoke-impacted sites (5 out of 15 met the EPA’s performance targets in terms of the 1-h averages). This correction can also be used to improve the comparability of PurpleAir sensor data with regulatory-grade monitors when they are collectively analyzed or shown together on public information websites; the methods developed in this paper can also be used to correct future air-sensor types. The PurpleAir network is already filling in spatial and temporal gaps in the regulatory monitoring network and providing valuable air-quality information during smoke episodes.

Background: Smoke from wildfires is a growing public health risk due to the enormous amount of smoke-related pollution that is produced and can travel thousands of kilometers from its source. While many studies have documented the physical health harms of wildfire smoke, less is known about the effects on mental health and well-being. Understanding the effects of wildfire smoke on mental health and well-being is crucial as the world enters a time in which wildfire smoke events become more frequent and severe. We conducted a scoping review of the existing information on wildfire smoke's impact on mental health and well-being and developed a model for understanding the pathways in which wildfire smoke may contribute to mental health distress., Methods: We conducted searches using PubMed, Medline, Embase, Google, Scopus, and ProQuest for 1990-2022. These searches yielded 200 articles. Sixteen publications met inclusion criteria following screening and eligibility assessment. Three more publications from the bibliographies of these articles were included for a total of 19 publications., Results: Our review suggests that exposure to wildfire smoke may have mental health impacts, particularly in episodes of chronic and persistent smoke events, but the evidence is inconsistent and limited. Qualitative studies disclose a wider range of impacts across multiple mental health and well-being domains. The potential pathways connecting wildfire smoke with mental health and well-being operate at multiple interacting levels including individual, social and community networks, living and working conditions, and ecological levels., Conclusions: Priorities for future research include: 1) applying more rigorous methods; 2) differentiating between mental illness and emotional well-being; 3) studying chronic, persistent or repeated smoke events; 4) identifying the contextual factors that set the stage for mental health and well-being effects, and 5) identifying the causal processes that link wildfire smoke to mental health and well-being effects. The pathways model can serve as a basis for further research and knowledge synthesis on this topic. Also, it helps public health, community mental health, and emergency management practitioners mitigate the mental health and well-being harms of wildfire smoke., (© 2022. The Author(s).)

During wildfire smoke events public health agencies release advisories to stay indoors, close doors and windows, and operate a portable air cleaner (PAC). The do-it-yourself (DIY) air cleaner consisting of a box fan and a furnace filter is a widely used low-cost alternative to commercial PACs because of its increased accessibility. In this study, we evaluate the clean air delivery rate (CADR) of different DIY air cleaner designs for reducing simulated wildfire smoke and identify operating parameters that may impact their performance and use. The simplest formulation of a DIY air cleaner (box fan with taped on minimum effectiveness reporting value - [MERV] 13 furnace filter) had a CADR of 111.2 ± 1.3 ft 3 /min (CFM). Increasing the fan flow by changing the fan type, increasing the fan setting, or reducing the pressure drop across the filtering surface increased the CADR. Large increases in CADR could be obtained by using a shroud (40%), using a 4″ thick filter (123%) using two filters in a wedge shape (137%), or using four filters in a Corsi-Rosenthal (CR) box design (261%). The CADR was greatly reduced with filters heavily loaded with smoke, pointing to the need for frequent filter changes during smoke events., (Published 2022. This article is a U.S. Government work and is in the public domain in the USA. Indoor Air published by John Wiley & Sons Ltd.)

Keywords: air pollution; COVID-19; environmental and occupational health and epidemiology; health disparities; wildfire smoke EN air pollution COVID-19 environmental and occupational health and epidemiology health disparities wildfire smoke 127 128 2 12/21/20 20210101 NES 210101 B See b cover image GLO:FS9/01jan21:resp13980-toc-0001.jpg PHOTO (COLOR): . gl On the morning of 9 September 2020, residents of the San Francisco Bay Area awoke to an eerie orange light filtering through the windows (Fig. Available from URL: https://www.cdc.gov/coronavirus/2019-ncov/community/health-equity/race-ethnicity.html 4 Wu X, Nethery RC, Sabath BM, Braun D, Dominici F. Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis. Air pollution, COVID-19, environmental and occupational health and epidemiology, health disparities, wildfire smoke. [Extracted from the article]

(1) Background: The developmental origins of health and disease (DOHaD) hypothesis links adverse fetal exposures with developmental mal-adaptations and morbidity later in life. Short- and long-term exposures to air pollutants are known contributors to health outcomes; however, the potential for developmental health effects of air pollution exposures during gestation or early-childhood have yet to be reviewed and synthesized from a DOHaD lens. The objective of this study is to summarize the literature on cardiovascular and metabolic, respiratory, allergic, and neuropsychological health outcomes, from prenatal development through early childhood, associated with early-life exposures to outdoor air pollutants, including traffic-related and wildfire-generated air pollutants. (2) Methods: We conducted a search using PubMed and the references of articles previously known to the authors. We selected papers that investigated health outcomes during fetal or childhood development in association with early-life ambient or source-specific air pollution exposure. (3) Results: The current literature reports that prenatal and early-childhood exposures to ambient and traffic-related air pollutants are associated with a range of adverse outcomes in early life, including cardiovascular and metabolic, respiratory and allergic, and neurodevelopmental outcomes. Very few studies have investigated associations between wildfire-related air pollution exposure and health outcomes during prenatal, postnatal, or childhood development. (4) Conclusion: Evidence from January 2000 to January 2022 supports a role for prenatal and early-childhood air pollution exposures adversely affecting health outcomes during development. Future studies are needed to identify both detrimental air pollutants from the exposure mixture and critical exposure time periods, investigate emerging exposure sources such as wildfire, and develop feasible interventional tools.

Wildfire events are increasing across the globe. The smoke generated as a result of this changing fire landscape is potentially more toxic than air pollution from other ambient sources, according to recent studies. This is especially concerning for populations of humans or animals that live downwind of areas that burn frequently, given that ambient exposure to wildfire smoke cannot be easily eliminated. We hypothesized that a significant indoor air pollution risk existed for laboratory animal facilities located proximal to fire-prone areas. Here, we measured real time continuous outdoor and indoor air quality for 28 days at a laboratory animal facility located in the Rocky Mountain region. We demonstrated that during a wildfire event, the indoor air quality of this animal facility is influenced by ambient smoke events. The daily average indoor fine particulate matter value in an animal room exceeded the Environmental Protection Agency's ambient annual standard 14% of the time and exceeded the World Health Organization's ambient annual guideline 71% of the time. We further show that specialized cage filtration systems are capable of mitigating air pollution penetrance and could improve an animal's microenvironment. The potential effects for laboratory animal physiology that occur in response to the exposure levels and durations measured in this study remain to be determined; yet, even acute wildfire exposure events have been previously correlated with significant differences in gene regulatory and metabolic processes in vivo. We believe these findings warrant consideration for indoor laboratory animal facility air quality monitoring and development of smoke exposure prevention and response protocols, especially among facilities located downwind of fire-prone landscapes.

One of the world's biggest disasters are wildfires. The firefighting environment involves physical and respiratory risks, due the inhalation of fire smoke. This study aims to determine the respiratory function of firefighters exposed to wildfire smoke and explore the potential risk factors associated with poor respiratory function. The sample involved 53 firefighters, aged between 23 and 60 years (39.28 ± 8.71), 41 (77.40%) male and 12 (22.60%) female, who fought in wildfires. The measurement instruments used were as follows: a scale, a stadiometer, a questionnaire, a Fagerstrom test and a spirometer. Thirty-six (67.9%) firefighters showed a restrictive pattern. Firefighters fought between 1 and 9 (3.64 ± 1.97) fires and in total between 5 and 212 (62.34 ± 46.89) h. Nineteen (52.8%) firefighters, who showed a restrictive pattern, did not perform any physical exercise ( p = 0.045). Twelve (70.6%) firefighters who practiced exercise and revealed a restrictive pattern trained at least 3 or less hours weekly, whilst five (29.4%) practiced more than 3 h ( p = 0.030) of weekly exercise. Twenty (55.6%) firefighters with a restrictive pattern spent more than 48 h in combat ( p = 0.029) and twenty-two (61.1%) did not use any respiratory protection ( p = 0.011). The study data showed that occupational exposure to wildfire smoke was associated with the development of a restrictive pattern and associated factors included a sedentary lifestyle, limited duration of physical exercise, longer exposure to fire smoke and non-use of respiratory protection.

Abstract: We report high concentrations of black carbon aerosols (BC), present at two rural sites in New York during the last week in May 2010, that are linked to wildfire activity. At Mayville BC from wood smoke was recorded for a total of 20 h from three separate episodes, mean concentration was 1400 ng m−3. These three short events contributed 13% of the BC burden during the month of May. At Whiteface Mountain high concentrations of BC, carbon monoxide gas (CO), and fine particulate matter mass (PM2.5) are reported from a heavy smoke event that impacted the Adirondack region of the State on May 31, 2010. PM2.5 mass recorded at the Lodge site (600 m above mean sea level) was 150 μg m−3 at 8:30 am EST and the 24-h mean was almost twice the USEPA limits while CO concentration exceeded 1000 ppb and BC concentration reached 9600 ng m−3. The event was delayed several hours at the Summit site (1500 m above mean sea level) but at 5:45 pm BC concentration reached 1600 ng m−3 and CO was 317 ppbv. Detailed temporal profiles and correlations are presented. [Copyright &y& Elsevier]

Wildland fires produce smoke plumes that impact air quality and human health. To understand the effects of wildland fire smoke on humans, the amount and composition of the smoke plume must be quantified. Using a fire emissions inventory is one way to determine the emissions rate and composition of smoke plumes from individual fires. There are multiple fire emissions inventories, and each uses a different method to estimate emissions. This paper presents a comparison of four emissions inventories and their products: Fire INventory from NCAR (FINN version 1.5), Global Fire Emissions Database (GFED version 4s), Missoula Fire Labs Emissions Inventory (MFLEI (250 m) and MFLEI (10 km) products), and Wildland Fire Emissions Inventory System (WFEIS (MODIS) and WFEIS (MTBS) products). The outputs from these inventories are compared directly. Because there are no validation datasets for fire emissions, the outlying points from the Bayesian models developed for each inventory were compared with visible images and fire radiative power (FRP) data from satellite remote sensing. This comparison provides a framework to check fire emissions inventory data against additional data by providing a set of days to investigate closely. Results indicate that FINN and GFED likely underestimate emissions, while the MFLEI products likely overestimate emissions. No fire emissions inventory matched the temporal distribution of emissions from an external FRP dataset. A discussion of the differences impacting the emissions estimates from the four fire emissions inventories is provided, including a qualitative comparison of the methods and inputs used by each inventory and the associated strengths and limitations. [ABSTRACT FROM AUTHOR]