The contribution of wildfire to PM2.5 trends in the USA

Responses of fine particulate matter (PM2.5) air quality to future climate, land use, and emission changes: Insights from modeling across shared socioeconomic pathways

Air pollution induced by fine particulate matter with diameter ≤ 2.5 μm (PM2.5) poses a significant challenge for global air quality management. Understanding how factors such as climate change, land use and land cover change (LULCC), and changing emissions interact to impact PM2.5 remains limited. To address this gap, we employed the Community Earth System Model and examined both the individual and combined effects of these factors on global surface PM2.5 in 2010 and projected scenarios for 2050 under different Shared Socioeconomic Pathways (SSPs). Our results reveal biomass-burning and anthropogenic emissions as the primary drivers of surface PM2.5 across all SSPs. Less polluted regions like the US and Europe are expected to experience substantial PM2.5 reduction in all future scenarios, reaching up to ~5 μg m-3 (70 %) in SSP1. However, heavily polluted regions like India and China may experience varied outcomes, with a potential decrease in SSP1 and increase under SSP3. Eastern China witness ~20 % rise in PM2.5 under SSP3, while northern India may experience ~70 % increase under same scenario. Depending on the region, climate change alone is expected to change PM2.5 up to ±5 μg m-3, while the influence of LULCC appears even weaker. The modest changes in PM2.5 attributable to LULCC and climate change are associated with aerosol chemistry and meteorological effects, including biogenic volatile organic compound emissions, SO2 oxidation, and NH4NO3 formation. Despite their comparatively minor role, LULCC and climate change can still significantly shape future air quality in specific regions, potentially counteracting the benefits of emission control initiatives. This study underscores the pivotal role of changes in anthropogenic emissions in shaping future PM2.5 across all SSP scenarios. Thus, addressing all contributing factors, with a primary focus on reducing anthropogenic emissions, is crucial for achieving sustainable reduction in surface PM2.5 levels and meeting sustainable pollution mitigation goals.

PM2.5 anomaly detection for exceptional event demonstrations: A Texas case study

The shifting frontiers of air pollution emission sources contribute to stagnation or reversal of air quality gains across the United States (US). The frequency and possibly duration of Exceptional Events - driven primarily by wildfires and dust storms - have significantly increased in the US over the past decade. Combined with the US Environmental Protection Agency (EPA) final rule strengthening primary annual National Ambient Air Quality Standards (NAAQS) for PM2.5 by 25%, communities will need to reevaluate domestic and international sources of PM2.5.This study applies the Isolation Forest methodology to Exceptional Event demonstrations to flag and evaluate sources of anomalies in large PM2.5 measurement datasets. Focusing on a decade of hourly PM2.5 data measured in seven regions across Texas from 2012-2021 (>3 million data points), we present methods to efficiently flag hourly PM2.5 anomalies with compute times of ~minutes and characterize their spatial impacts as local or (multi-) regional; subsequent evaluation of potential sources of the increase can then be conducted more efficiently in a targeted manner. For a subset of anomalies, we incorporate air mass back trajectories, surface influences, and positive matrix factorization to evaluate potential sources.Our anomaly characterization method separated statistically normal PM2.5 data and enabled differentiation of localized versus larger-scale PM2.5 sources. In addition, our method successfully characterized the Summer 2020 severe Saharan dust intrusions into Texas, as well as the influence of international smoke from Mexico on El Paso's regional air quality.This anomaly flagging and characterization method is promising for assessing the relative importance of sources to anomalies in PM2.5 and other criteria air pollutants for multiple purposes; while this work focuses on its capacity for exceptional event demonstrations, the applicability includes long-term trend analyses from environmental justice analyses of air pollutant exposure to air quality attainment demonstrations.

Substantial Underestimation of Fine-Mode Aerosol Loading from Wildfires and Its Radiative Effects in Current Satellite-Based Retrievals over the United States

Wildfires generate abundant smoke primarily composed of fine-mode aerosols. However, accurately measuring the fine-mode aerosol optical depth (fAOD) is highly uncertain in most existing satellite-based aerosol products. Deep learning offers promise for inferring fAOD, but little has been done using multiangle satellite data. We developed an innovative angle-dependent deep-learning model (ADLM) that accounts for angular diversity in dual-angle observations. The model captures aerosol properties observed from dual angles in the contiguous United States and explores the potential of Greenhouse gases Observing Satellite-2's (GOSAT-2) measurements to retrieve fAOD at a 460 m spatial resolution. The ADLM demonstrates a strong performance through rigorous validation against ground-based data, revealing small biases. By comparison, the official fAOD product from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and the Multiangle Imaging Spectroradiometer (MISR) during wildfire events is underestimated by more than 40% over western USA. This leads to significant differences in estimates of aerosol radiative forcing (ARF) from wildfires. The ADLM shows more than 20% stronger ARF than the MODIS, VIIRS, and MISR estimates, highlighting a greater impact of wildfire fAOD on Earth's energy balance.

Behavioral Responses to Wildfire Smoke: A Case Study in Western Montana

Although climate change is increasing wildfire and smoke events globally, public health messaging and individual access to resources for protection are limited. Individual interventions can be highly effective at reducing wildfire smoke exposure. However, studies related to individual responses to wildfire smoke are limited and demonstrate mixed protective behaviors and risk perception. Our research helps fill this gap by assessing the self-reported behavior of 20 participants during wildfire season in Western Montana from 28 June through 1 November, 2022. We also measured continuous outdoor and indoor fine particulate matter (PM2.5) concentrations at participant residencies during this time period using PurpleAir sensors (PAII-SD, PurpleAir, Inc, USA) while participants took up to 16 self-reported online weekly activity surveys. Mixed-effect Poisson regression models were used to assess associations between exposure variables and participant reported behaviors. These results were compared with end-of-study interview findings. Wildfire smoke impacted days and increased concentrations of PM2.5 were associated with decreased outdoor exercise and opening of windows for ventilation. Interview themes were congruent with the regression analysis, with the additional finding of high portable air cleaner (PAC) use among participants. Additionally, these interviews gave context to both the tradeoffs participants face when making protective decisions and the importance of personal air quality data in increasing awareness about wildfire smoke risks. Future wildfire smoke studies can build off this research by providing personally relevant air quality data and PACs to participants and by improving public health messaging to address the compounding risks of wildfire smoke exposure and heat.

Physicochemical Characterization of the Particulate Matter in New Jersey/New York City Area, Resulting from the Canadian Quebec Wildfires in June 2023

The global increase in wildfires, primarily driven by climate change, significantly affects air quality and health. Wildfire-emitted particulate matter (WFPM) is linked to adverse health effects, yet the toxicological mechanisms are not fully understood given its physicochemical complexity and the lack of spatiotemporal exposure data. This study focuses on the physicochemical characterization of WFPM from a Canadian wildfire in June 2023, which affected over 100 million people in the US Northeast, particularly around New Jersey/New York. Aerosol systems were deployed to characterize WFPM during the 3 day event, revealing unprecedented mass concentrations mainly in the WFPM0.1 and WFPM0.1-2.5 size fractions. Peak WFPM2.5 concentrations reached 317 μg/m3, nearly 10 times the National Ambient Air Quality Standard (NAAQS) 24 h average limit. Chemical analysis showed a high organic-to-total carbon ratio (96%), consistent with brown carbon wildfires nanoparticles. Large concentrations of high-molecular-weight PAHs were found predominantly bound to WFPM0.1, with retene, a molecular marker of biomass burning and a known teratogen, being the most abundant (>70%). Computational modeling estimated a total lung deposition of 9.15 mg over 72 h, highlighting the health risks of WFPM, particularly due to its long-distance travel capability and impact on densely populated areas.

Wildfire Impacts on O3 in the Continental United States Using PM2.5 and a Generalized Additive Model (2018-2023)

We examined PM2.5 and Hazard Mapping System smoke plume satellite data at ∼600 United States (US) air monitoring stations to identify surface smoke on 14.0% of all May-September days for 2018-2023, with large influences in 2020 and 2021, due to California fires, and 2023, due to Canadian fires. Days with smoke have an average of 11 μg m-3 more PM2.5 and 8 ppb higher maximum daily 8 h average (MDA8) O3 concentrations than nonsmoke days, and they also account for 94% of all days that exceed the daily PM2.5 health standard (35 μg m-3) and 36% of all days that exceed the O3 health standard (70 ppb). To estimate the smoke contributions to the O3 MDA8, Generalized Additive Models (GAMs) were built for each site using the nonsmoke day data and up to 8 predictors. The mean and standard deviation of the residuals from the GAMs were 0 ± 6.1 ppb for the nonsmoke day data and 4.3 ± 7.9 ppb for the smoke day data, indicating a significant enhancement in the MDA8 O3 on smoke days. We found positive residuals on 72% of the smoke days and for these days, we calculate an average smoke contribution to the O3 MDA8 of 7.8 ± 6.0 ppb. Over the 6 year period, the percentage of exceedance days due to smoke in the continental US was 25% of all exceedance days, and the highest was in 2023 (38%). In 2023, the Central US experienced an unusually high number of exceedance days, 1522, with 52% of these impacted by smoke, while the Eastern US had fewer exceedance days, 288, with 78% of these impacted by smoke. Our results demonstrate the importance of wildland fires as contributors to exceedances of the health-based national air quality standards for PM2.5 and O3.

Preoperative Exposure to Fine Particulate Matter and Risk of Postoperative Complications: A Single Center Observational Cohort Bayesian Analysis

Background & Objectives

While exposure to fine particulate matter air pollution (PM 2.5 ) is known to cause adverse health effects, its impact on postoperative outcomes in US adults remains understudied. Perioperative exposure to PM 2.5 may induce inflammation that insidiously interacts with the systemic inflammatory response after surgery, leading to higher postoperative complications.

Methods

We conducted a single center, retrospective cohort study using data from 64,313 surgical patients living along Utah's Wasatch Front and undergoing elective surgical procedures at a single academic medical center from 2016-2018. Patients' addresses were geocoded and linked to daily Census-tract level PM 2.5 estimates preoperatively. We hypothesized that elevated PM 2.5 concentrations in the seven days prior to surgery would be associated with an increase in a bundle of major postoperative complications. A hierarchical Bayesians regression model was fit adjusting for age, sex, season, neighborhood disadvantage, and the Elixhauser index of comorbidities.

Results

Postoperative complications increased in a dose-dependent manner with higher concentrations of PM 2.5 exposure, with a relative increase of 7% in the odds of complications for every 10ug/m3 increase in the highest single-day 24-hr PM 2.5 exposure during the 7 days prior to surgery. The association persisted after controlling for comorbidities and potential confounders; our inferences were robust to modeling choices and sensitivity analysis.

Discussion & Conclusion

In this large Utah cohort, exposure to elevated PM 2.5 concentrations in the week before surgery was associated with increased postoperative complications in a dose-dependent manner, suggesting a potential impact of air pollution on surgical outcomes. These findings merit replication in larger datasets to identify populations at risk and to define the interaction and impact of different pollutants. PM 2.5 exposure is a potential perioperative risk factor and, given the unmitigated air pollution in urban areas, a global health concern.

Application of quasi-empirical orthogonal functions to estimate wildfire impacts in northwestern Spain

Galicia (NW Spain) is one of the most fire-prone regions in Southern Europe. In the summer of 2022, a total of thirteen wildfires each exceeding 500 ha were reported in this area, with ten of these large fires occurring in the Ourense region. To study the impacts of wildfire smoke plumes on ambient air PM2.5 concentrations, a network of 18 PurpleAir monitors was deployed across the Galicia region during July and August 2022. The PM2.5 concentration data were then used as input to test the applicability of quasi-empirical orthogonal functions (QEOFs obtained with Positive Matrix Factorization (PMF)) to characterize the spatial variability of wildfire smoke impacts on air quality. HYSPLIT back-trajectory analysis and Concentration-Weighted Trajectory (CWT) models were implemented, and the results from these tools were combined with source contributions. As a result, 19 wildfires were identified and linked with peak ambient PM2.5 concentrations (>300 μg/m3 of PM2.5; 1-h mean). Specifically, the Folgoso do Courel fire emerged as a significant contributor to these high concentrations and played an important role in influencing a significant number of the identified factors. Moreover, the results also suggested that emissions from fires in Portugal reached the study area, contributing additional impacts on air quality. These results demonstrated that this approach was useful in identifying the emission source areas contributing to observed PM2.5 concentrations during wildfire events. The PM2.5 concentration maps resulting from the CWT analysis were also valuable in understanding the short- and long-term exposures to PM2.5 from wildfire smoke.

Motivating parents to protect their children from wildfire smoke: the impact of air quality index infographics

Background. Wildfire smoke events are increasing in frequency and intensity due to climate change. Children are especially vulnerable to health effects even at moderate smoke levels. However, it is unclear how parents respond to Air Quality Indices (AQIs) frequently used by agencies to communicate air pollution health risks. Methods. In an experiment (3 × 2 × 2 factorial design), 2,100 parents were randomly assigned to view one of twelve adapted AQI infographics that varied by visual (table, line, gauge), index type (AQI [0-500], AQHI [1-11+]), and risk level (moderate, high). Participants were told to imagine encountering the infographic in a short-term exposure scenario. They reported worry about wildfire smoke, intentions to take risk-mitigating actions (e.g., air purifier use), and support for various exposure reduction policies. Subsequently, participants were told to imagine encountering the same infographic daily during a school week in a long-term exposure scenario and again reported worry, action intentions, and policy support. Results. Parents' responses significantly differentiated between risk levels that both pose a threat to children's health; worry and action intentions were much higher in the high-risk group than the moderate-risk group in both short-exposure (F = 748.68 p<.001; F = 411.59, p<.001) and long-exposure scenarios (F = 470.51, p<.001; F = 212.01, p<.001). However, in the short-exposure scenario, when shown the AQHI [1-11+] with either the line or gauge visuals, parents' action intentions were more similar between moderate- and high-risk level groups (3-way interaction, F = 6.03, p = .002). Conclusions. These results suggest some index formats such as the AQHI-rather than the AQI-may better attune parents to moderate levels of wildfire smoke being dangerous to children's health. Our research offers insights for agencies and officials seeking to improve current public education efforts during wildfire smoke events and speaks to the critical need to educate parents and help them act short-term and long-term to protect children's health.

Quantifying the impacts of Canadian wildfires on regional air pollution networks

Wildfire smoke greatly impacts regional atmospheric systems, causing changes in the behavior of pollution. However, the impacts of wildfire smoke on pollution behavior are not easily quantifiable due to the complex nature of atmospheric systems. Air pollution correlation networks have been used to quantify air pollution behavior during ambient conditions. However, it is unknown how extreme pollution events impact these networks. Therefore, we propose a multidimensional air pollution correlation network framework to quantify the impacts of wildfires on air pollution behavior. The impacts are quantified by comparing two time periods, one during the 2023 Canadian wildfires and one during normal conditions with two complex network types for each period. In this study, the value network represents PM2.5 concentrations and the rate network represents the rate of change of PM2.5 concentrations. Wildfires' impacts on air pollution behavior are captured by structural changes in the networks. The wildfires caused a discontinuous phase transition during percolation in both network types which represents non-random organization of the most significant spatiotemporal correlations. Additionally, wildfires caused changes to the connectivity of stations leading to more interconnected networks with different influential stations. During the wildfire period, highly polluted areas are more likely to form connections in the network, quantified by an 86 % and 19 % increase in the connectivity of the value and rate networks respectively compared to the normal period. In this study, we create novel understandings of the impacts of wildfires on air pollution correlation networks, show how our method can create important insights into air pollution patterns, and discuss potential applications of our methodologies. This study aims to enhance capabilities for wildfire smoke exposure mitigation and response strategies.

Mortality attributable to PM2.5 from wildland fires in California from 2008 to 2018

In California, wildfire risk and severity have grown substantially in the last several decades. Research has characterized extensive adverse health impacts from exposure to wildfire-attributable fine particulate matter (PM2.5), but few studies have quantified long-term outcomes, and none have used a wildfire-specific chronic dose-response mortality coefficient. Here, we quantified the mortality burden for PM2.5 exposure from California fires from 2008 to 2018 using Community Multiscale Air Quality modeling system wildland fire PM2.5 estimates. We used a concentration-response function for PM2.5, applying ZIP code-level mortality data and an estimated wildfire-specific dose-response coefficient accounting for the likely toxicity of wildfire smoke. We estimate a total of 52,480 to 55,710 premature deaths are attributable to wildland fire PM2.5 over the 11-year period with respect to two exposure scenarios, equating to an economic impact of $432 to $456 billion. These findings extend evidence on climate-related health impacts, suggesting that wildfires account for a greater mortality and economic burden than indicated by earlier studies.

Intricate synergistic effects between air pollution and carbon emission: An emerging evidence from China

Due to global climate change and intensifying anthropogenic pollution, China confronts the dual challenge of controlling particulate matter 2.5 μm (PM2.5) pollution and reducing carbon emissions. Quantifying the characteristics of PM2.5 concentrations and CO2 emissions, as well as identifying the driving factors and synergistic effects of PM2.5 reduction and CO2 mitigation, are crucial steps in promoting sustainable urban development and achieving the Sustainable Development Goals (SDGs) in China. In this study, we selected 168 cities as our case-study, and quantified spatial characteristics of PM2.5 concentrations and CO2 emissions from 2015 to 2020 in China. Then we analyzed driving factors affecting the spatial heterogeneity of PM2.5 reduction and CO2 mitigation applying Multi-scale Geographically Weighted Regression (MGWR) model. By employing coupling coordination degree (CCD) model, we further detected the spatiotemporal evolution patterns of the synergistic effects between PM2.5 reduction and CO2 mitigation in key Chinese cities. The result showed that: (a) From 2015 to 2020, PM2.5 concentrations experienced a significant reduction from 59.78 μg/m3 to 49.83 μg/m3, while CO2 emissions increased from 44.88 × 106 t in 2015 to 45.77 × 106 t in 2020; (b) Green economy efficiency (gee), government attention (gover), and environmental regulation (envir) demonstrate the most pronounced synergistic effect on pollution reduction and carbon mitigation, with the drivers exhibiting obvious spatial heterogeneity; (c) The overall coupling coordination level of PM2.5 pollution and CO2 emissions in China dropped from 0.49 in 2015 to 0.46 in 2020, and the coupling coordination grade in northern cities was notably higher than that in southern cities. The result enhances our understanding of spatiotemporal patterns of synergistic effects between PM2.5 reduction and CO2 mitigation, and provides the theoretical basis for policy decision-making to realize pollution decrease and carbon neutral and regional environment governance.

Air pollution from biomass burning disrupts early adolescent cortical microarchitecture development

Exposure to outdoor particulate matter (PM 2.5 ) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM 2.5 from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM 2.5 and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM 2.5 using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM 2.5 from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.

Climate Change, Landscape Fires, and Human Health: A Global Perspective

Landscape fires are an integral component of the Earth system and a feature of prehistoric, subsistence, and industrial economies. Specific spatiotemporal patterns of landscape fire occur in different locations around the world, shaped by the interactions between environmental and human drivers of fire activity. Seven distinct types of landscape fire emerge from these interactions: remote area fires, wildfire disasters, savanna fires, Indigenous burning, prescribed burning, agricultural burning, and deforestation fires. All can have substantial impacts on human health and well-being directly and indirectly through (a) exposure to heat flux (e.g., injuries and destructive impacts), (b) emissions (e.g., smoke-related health impacts), and (c) altered ecosystem functioning (e.g., biodiversity, amenity, water quality, and climate impacts). Minimizing the adverse effects of landscape fires on population health requires understanding how human and environmental influences on fire impacts can be modified through interventions targeted at individual, community, and regional levels.

Personal Strategies to Reduce the Cardiovascular Impacts of Environmental Exposures

Ubiquitous environmental exposures increase cardiovascular disease risk via diverse mechanisms. This review examines personal strategies to minimize this risk. With regard to fine particulate air pollution exposure, evidence exists to recommend the use of portable air cleaners and avoidance of outdoor activity during periods of poor air quality. Other evidence may support physical activity, dietary modification, omega-3 fatty acid supplementation, and indoor and in-vehicle air conditioning as viable strategies to minimize adverse health effects. There is currently insufficient data to recommend specific personal approaches to reduce the adverse cardiovascular effects of noise pollution. Public health advisories for periods of extreme heat or cold should be observed, with limited evidence supporting a warm ambient home temperature and physical activity as strategies to limit the cardiovascular harms of temperature extremes. Perfluoroalkyl and polyfluoroalkyl substance exposure can be reduced by avoiding contact with perfluoroalkyl and polyfluoroalkyl substance-containing materials; blood or plasma donation and cholestyramine may reduce total body stores of perfluoroalkyl and polyfluoroalkyl substances. However, the cardiovascular impact of these interventions has not been examined. Limited utilization of pesticides and safe handling during use should be encouraged. Finally, vasculotoxic metal exposure can be decreased by using portable air cleaners, home water filtration, and awareness of potential contaminants in ground spices. Chelation therapy reduces physiological stores of vasculotoxic metals and may be effective for the secondary prevention of cardiovascular disease.

Air Pollution Drives Macrophage Senescence through a Phagolysosome-15-Lipoxygenase Pathway

Urban particulate matter (PM; uPM) poses significant health risks, particularly to the respiratory system. Fine particles, such as PM2.5, can penetrate deep into the lungs and exacerbate a range of health problems, including emphysema, asthma, and lung cancer. PM exposure is also linked to extrapulmonary disorders such as heart and neurodegenerative diseases. Moreover, prolonged exposure to elevated PM levels can reduce overall life expectancy. Senescence is a dysfunctional cell state typically associated with age but can also be precipitated by environmental stressors. This study aimed to determine whether uPM could drive senescence in macrophages, an essential cell type involved in particulate phagocytosis-mediated clearance. Although it is known that uPM exposure impairs immune function, this deficit is multifaceted and incompletely understood, partly because of the use of particulates such as diesel exhaust particles as a surrogate for true uPM. uPM was collected from several locations in the United States, including Baltimore, Houston, and Phoenix. Bone marrow-derived macrophages were stimulated with uPM or reference particulates (e.g., diesel exhaust particles) to assess senescence-related parameters. We report that uPM-exposed bone marrow-derived macrophages adopt a senescent phenotype characterized by increased IL-1α secretion, senescence-associated β-galactosidase activity, and diminished proliferation. Exposure to allergens failed to elicit such a response, supporting a distinction between different types of environmental exposure. uPM-induced senescence was independent of key macrophage activation pathways, specifically inflammasome and scavenger receptors. However, inhibition of the phagolysosome pathway abrogated senescence markers, supporting this phenotype's attribution to uPM phagocytosis. These data suggest that uPM exposure leads to macrophage senescence, which may contribute to immunopathology.

Pregnancy exposure to PM2.5 from wildland fire smoke and preterm birth in California

BACKGROUND

Wildfires in the Western United States are a growing and significant source of air pollution that is eroding decades of progress in air pollution reduction. The effects on preterm birth during critical periods of pregnancy are unknown.

METHODS

We assessed associations between prenatal exposure to wildland fire smoke and risk of preterm birth (gestational age < 37 weeks). We assigned smoke exposure to geocoded residence at birth for all live singleton births in California conceived 2007-2018, using weekly average concentrations of particulate matter ≤ 2.5 µm (PM2.5) attributable to wildland fires from United States Environmental Protection Agency's Community Multiscale Air Quality Model. Logistic regression yielded odds ratio (OR) for preterm birth in relation to increases in average exposure across the whole pregnancy, each trimester, and each week of pregnancy. Models adjusted for season, age, education, race/ethnicity, medical insurance, and smoking of the birthing parent.

RESULTS

For the 5,155,026 births, higher wildland fire PM2.5 exposure averaged across pregnancy, or any trimester, was associated with higher odds of preterm birth. The OR for an increase of 1 µg/m3 of average wildland fire PM2.5 during pregnancy was 1.013 (95 % CI:1.008,1.017). Wildland fire PM2.5 during most weeks of pregnancy was associated with higher odds. Strongest estimates were observed in weeks in the second and third trimesters. A 10 µg/m3 increase in average wildland fire PM2·5 in gestational week 23 was associated with OR = 1.034; 95 % CI: 1.019, 1.049 for preterm birth.

CONCLUSIONS

Preterm birth is sensitive to wildland fire PM2.5; therefore, we must reduce exposure during pregnancy.

Air pollutants contribute to epithelial barrier dysfunction and allergic diseases

Air pollution is a global problem associated with various health conditions, causing elevated rates of morbidity and mortality. Major sources of air pollutants include industrial emissions, traffic-related pollutants, and household biomass combustion, in addition to indoor pollutants from chemicals and tobacco. Various types of air pollutants originate from both human activities and natural sources. These include particulate matter, pollen, greenhouse gases, and other harmful gases. Air pollution is linked to allergic diseases, including atopic dermatitis, allergic rhinitis, allergic conjunctivitis, food allergy, and bronchial asthma. These pollutants lead to epithelial barrier dysfunction, dysbiosis, and immune dysregulation. In addition, climate change and global warming may contribute to the exacerbation and the development of allergic diseases related to air pollutants. Epigenetic changes associated with air pollutants have also been connected to the onset of allergic diseases. Furthermore, these changes can be passed down through subsequent generations, causing a higher prevalence of allergic diseases in offspring. Modulation of the aryl hydrocarbon receptor could be a valuable strategy for alleviating air pollutant-induced epidermal barrier dysfunction and atopic dermatitis. A more effective approach to preventing allergic diseases triggered by air pollutants is to reduce exposure to them. Implementing public policies aimed at safeguarding individuals from air pollutant exposure may prove to be the most efficient solution. A pressing need exists for global policy initiatives that prioritize efforts to reduce the production of air pollutants.

Dispersion and Dosimetric Challenges of Hydrophobic Carbon-Based Nanoparticles in In Vitro Cellular Studies

Methodologies across the dispersion preparation, characterization, and cellular dosimetry of hydrophilic nanoparticles (NPs) have been developed and used extensively in the field of nanotoxicology. However, hydrophobic NPs pose a challenge for dispersion in aqueous culture media using conventional methods that include sonication followed by mixing in the culture medium of interest and cellular dosimetry. In this study, a robust methodology for the preparation of stable dispersions of hydrophobic NPs for cellular studies is developed by introducing continuous energy over time via stirring in the culture medium followed by dispersion characterization and cellular dosimetry. The stirring energy and the presence of proteins in the culture medium result in the formation of a protein corona around the NPs, stabilizing their dispersion, which can be used for in vitro cellular studies. The identification of the optimal stirring time is crucial for achieving dispersion and stability. This is assessed through a comprehensive stability testing protocol employing dynamic light scattering to evaluate the particle size distribution stability and polydispersity. Additionally, the effective density of the NPs is obtained for the stable NP dispersions using the volumetric centrifugation method, while cellular dosimetry calculations are done using available cellular computational modeling, mirroring approaches used for hydrophilic NPs. The robustness of the proposed dispersion approach is showcased using a highly hydrophobic NP model (black carbon NPs) and two culture media, RPMI medium and SABM, that are widely used in cellular studies. The proposed approach for the dispersion of hydrophobic NPs results in stable dispersions in both culture media used here. The NP effective density of 1.03-1.07 g/cm3 measured here for black carbon NPs is close to the culture media density, resulting in slow deposition on the cells over time. So, the present methodology for dispersion and dosimetry of hydrophobic NPs is essential for the design of dose-response studies and overcoming the challenges imposed by slow particle deposition.

Large Decreases in Tailpipe Criteria Pollutant Emissions from the U.S. Light-Duty Vehicle Fleet Expected in 2020-2040

The U.S. EPA MOVES3 model was used to assess the impact of the large-scale introduction of electric vehicles on emissions of criteria pollutants (CO, hydrocarbons [HC], NOx, and particulate matter [PM]) and CO2 from the U.S. light-duty vehicle fleet. Large reductions in emissions of these criteria pollutants occurred in 2000-2020. These trends are expected to continue through 2040 driven by turnover of the conventional fleet with old vehicles being replaced by battery electric vehicles (BEVs) and by new internal combustion engine vehicles (ICEVs) with modern emission control systems. Without the introduction of BEVs, the absolute emissions of CO, NOx, HC, and PM2.5 from the U.S. light-duty vehicle fleet are expected to decrease by approximately 61, 88, 55, and 20% from 2020 to 2040. Introduction of BEVs with market share increasing linearly to 100% in 2040 provides additional benefits, which, combined with ICEV fleet turnover, would lead to decreases of absolute emissions of CO, NOx, HC, and PM2.5 of approximately 77, 94, 71, and 37% from 2020 to 2040. Reductions in CO2 emissions follow a similar pattern. Large decreases in criteria pollutant and CO2 emissions from light duty vehicles lie ahead.

Clearing the air: evaluating institutions' social media health messaging on wildfire and smoke risks in the US Pacific Northwest

BACKGROUND

Wildfire smoke contributes substantially to the global disease burden and is a major cause of air pollution in the US states of Oregon and Washington. Climate change is expected to bring more wildfires to this region. Social media is a popular platform for health promotion and a need exists for effective communication about smoke risks and mitigation measures to educate citizens and safeguard public health.

METHODS

Using a sample of 1,287 Tweets from 2022, we aimed to analyze temporal Tweeting patterns in relation to potential smoke exposure and evaluate and compare institutions' use of social media communication best practices which include (i) encouraging adoption of smoke-protective actions; (ii) leveraging numeric, verbal, and Air Quality Index risk information; and (iii) promoting community-building. Tweets were characterized using keyword searches and the Linguistic Inquiry and Word Count (LIWC) software. Descriptive and inferential statistics were carried out.

RESULTS

44% of Tweets in our sample were authored between January-August 2022, prior to peak wildfire smoke levels, whereas 54% of Tweets were authored during the two-month peak in smoke (September-October). Institutional accounts used Twitter (or X) to encourage the adoption of smoke-related protective actions (82% of Tweets), more than they used it to disseminate wildfire smoke risk information (25%) or promote community-building (47%). Only 10% of Tweets discussed populations vulnerable to wildfire smoke health effects, and 14% mentioned smoke mitigation measures. Tweets from Washington-based accounts used significantly more verbal and numeric risk information to discuss wildfire smoke than Oregon-based accounts (p = 0.042 and p = 0.003, respectively); however, Tweets from Oregon-based accounts on average contained a higher percentage of words associated with community-building language (p < 0.001).

CONCLUSIONS

This research provides practical recommendations for public health practitioners and researchers communicating wildfire smoke risks on social media. As exposures to wildfire smoke rise due to climate change, reducing the environmental disease burden requires health officials to leverage popular communication platforms, distribute necessary health-related messaging rapidly, and get the message right. Timely, evidence-based, and theory-driven messaging is critical for educating and empowering individuals to make informed decisions about protecting themselves from harmful exposures. Thus, proactive and sustained communications about wildfire smoke should be prioritized even during wildfire "off-seasons."

Air pollution drives macrophage senescence through a phagolysosome-15-lipoxygenase pathway

Urban particulate matter (uPM) poses significant health risks, particularly to the respiratory system. Fine particles, such as PM2.5, can penetrate deep into the lungs and exacerbate a range of health problems, including emphysema, asthma, and lung cancer. PM exposure is also linked to extra-pulmonary disorders like heart and neurodegenerative diseases. Moreover, prolonged exposure to elevated PM levels can reduce overall life expectancy. Senescence is a dysfunctional cell state typically associated with age but can also be precipitated by environmental stressors. This study aimed to determine whether uPM could drive senescence in macrophages, an essential cell type involved in particulate phagocytosis-mediated clearance. While it is known that uPM exposure impairs immune function, this deficit is multi-faceted and incompletely understood, partly due to the use of particulates such as diesel exhaust particle (DEP) as a surrogate for true uPM. uPM was collected from several locations in the USA, including Baltimore, Houston, and Phoenix. Bone marrow-derived macrophages (BMDMs) were stimulated with uPM or reference particulates (e.g., DEP) to assess senescence-related parameters. We report that uPM-exposed BMDMs adopt a senescent phenotype characterized by increased IL-1α secretion, senescence-associated β-galactosidase activity, and diminished proliferation. Exposure to allergens failed to elicit such a response, supporting a distinction between different types of environmental exposures. uPM-induced senescence was independent of key macrophage activation pathways, specifically inflammasome and scavenger receptor. However, inhibition of the phagolysosome pathway abrogated senescence markers, supporting this phenotype's attribution to uPM phagocytosis. These data suggest uPM exposure leads to macrophage senescence, which may contribute to immunopathology.

Quantifying fire-specific smoke exposure and health impacts

Rapidly changing wildfire regimes across the Western United States have driven more frequent and severe wildfires, resulting in wide-ranging societal threats from wildfires and wildfire-generated smoke. However, common measures of fire severity focus on what is burned, disregarding the societal impacts of smoke generated from each fire. We combine satellite-derived fire scars, air parcel trajectories from individual fires, and predicted smoke PM2.5 to link source fires to resulting smoke PM2.5 and health impacts experienced by populations in the contiguous United States from April 2006 to 2020. We quantify fire-specific accumulated smoke exposure based on the cumulative population exposed to smoke PM2.5 over the duration of a fire and estimate excess asthma-related emergency department (ED) visits as a result of this exposure. We find that excess asthma visits attributable to each fire are only moderately correlated with common measures of wildfire severity, including burned area, structures destroyed, and suppression cost. Additionally, while recent California fires contributed nearly half of the country's smoke-related excess asthma ED visits during our study period, the most severe individual fire was the 2007 Bugaboo fire in the Southeast. We estimate that a majority of smoke PM2.5 comes from sources outside the local jurisdictions where the smoke is experienced, with 87% coming from fires in other counties and 60% from fires in other states. Our approach could enable broad-scale assessment of whether specific fire characteristics affect smoke toxicity or impact, inform cost-effectiveness assessments for allocation of suppression resources, and help clarify the growing transboundary nature of local air quality.

Wildland Fires Worsened Population Exposure to PM2.5 Pollution in the Contiguous United States

As wildland fires become more frequent and intense, fire smoke has significantly worsened the ambient air quality, posing greater health risks. To better understand the impact of wildfire smoke on air quality, we developed a modeling system to estimate daily PM2.5 concentrations attributed to both fire smoke and nonsmoke sources across the contiguous U.S. We found that wildfire smoke has the most significant impact on air quality in the West Coast, followed by the Southeastern U.S. Between 2007 and 2018, fire smoke contributed over 25% of daily PM2.5 concentrations at ∼40% of all regulatory air monitors in the EPA's air quality system (AQS) for more than one month per year. People residing outside the vicinity of an EPA AQS monitor (defined by a 5 km radius) were subject to 36% more smoke impact days compared with those residing nearby. Lowering the national ambient air quality standard (NAAQS) for annual mean PM2.5 concentrations to between 9 and 10 μg/m3 would result in approximately 35-49% of the AQS monitors falling in nonattainment areas, taking into account the impact of fire smoke. If fire smoke contribution is excluded, this percentage would be reduced by 6 and 9%, demonstrating the significant negative impact of wildland fires on air quality.

Low-intensity fires mitigate the risk of high-intensity wildfires in California's forests

The increasing frequency of severe wildfires demands a shift in landscape management to mitigate their consequences. The role of managed, low-intensity fire as a driver of beneficial fuel treatment in fire-adapted ecosystems has drawn interest in both scientific and policy venues. Using a synthetic control approach to analyze 20 years of satellite-based fire activity data across 124,186 square kilometers of forests in California, we provide evidence that low-intensity fires substantially reduce the risk of future high-intensity fires. In conifer forests, the risk of high-intensity fire is reduced by 64.0% [95% confidence interval (CI): 41.2 to 77.9%] in areas recently burned at low intensity relative to comparable unburned areas, and protective effects last for at least 6 years (lower bound of one-sided 95% CI: 6 years). These findings support a policy transition from fire suppression to restoration, through increased use of prescribed fire, cultural burning, and managed wildfire, of a presuppression and precolonial fire regime in California.