The January 2025 Los Angeles wildfires released large amounts of air pollutants and exposed millions of residents to smoke containing hazardous volatile organic compounds (VOCs). To assess exposure risks, we conducted indoor and outdoor VOCs sampling at 22 households near the Palisades and Eaton Fires across three phases: active burning with less than 50% containment (January 8-15), active burning period with more than 50% containment (January 24-31), and postfire (February 11-18). Outdoor benzene concentrations peaked during Phase 1, with a median (interquartile range) of 0.38 (0.27) ppb, decreased over time, and remained below the California Office of Environmental Health Hazard Assessment health benchmarks. Compared with the active burning period, indoor-to-outdoor ratios of m,p-xylene (p = 0.004), carbon tetrachloride (p = 0.002), and heptane (p = 0.02) were significantly higher in the postfire period. Elevated VOC levels were particularly evident in uninhabited homes within burn zones, suggesting ongoing indoor emissions from smoke-impacted materials. These findings raise concerns about indoor air quality postwildfire and the potential for prolonged exposure, underscoring the need for targeted mitigation and ongoing monitoring to protect public health during recovery.

The development of smoke fine particulate matter (PM2.5) exposure surfaces for estimating air pollution trends and associated health effects has advanced considerably. Currently available smoke exposure products rely on various data sources and modeling techniques, as there is no gold standard method for modeling wildfire smoke PM2.5. This study compares multiple daily smoke PM2.5 data sets developed using diverse methodologies spanning 2008-2018. Incorporating metrics for short- and long-term exposure, we compare four data sets at the census tract level in California: one using the U.S. Environmental Protection Agency's chemical transport model (CTM), the Community Multiscale Air Quality Modeling System (CMAQ); two using statistical methods, also referred to as machine learning (ML) techniques; and one combining these approaches to develop an ML-calibrated CTM-based exposure surface. Our analysis highlights differences between the data sets in terms of long-term exposure metrics, with the CTM data set estimating the highest concentrations overall, and considerable differences between estimates produced by the two ML models. An analysis of six case studies of large fires across the state finds that even data sets with similar inputs and methods produced estimates that varied several-fold, with additional differences by region and over time. Our findings have important implications for quantifying smoke PM2.5 exposures for use in population health impact studies, which rely on exposure estimates to accurately estimate health burden from pollution exposure.

Compound climate events capture the overlap of multiple climate hazards in space, time, or both, which can amplify adverse health outcomes. Despite a strong commitment to climate policy and action, the state of California faces a broad array of these compound climate hazards, and existing adaptation approaches do not yet consider a compound framework for exposures. California is also home to a diverse population with many underserved communities that are particularly vulnerable to the effects of climate events. This scoping review is the first to comprehensively synthesize existing evidence on compound climate exposures and health in California, analyzing exposures co-occurring in the same place at the same time. We searched the Web of Science and PubMed databases and identified 20 articles analyzing the compound effects of climate stressors including heat, air pollution, wildfire smoke, meteorology, and microclimate factors such as green space. The strongest evidence emerged for the co-occurring effects of heat and air pollution—including wildfire smoke—on various health outcomes, including mortality, hospitalizations, and birth outcomes. Several studies also demonstrated spatial variability in these compounded effects at the neighborhood scale. We found heterogeneity in both exposure assessment techniques for characterizing climate extremes, as well as methods to evaluate effects on the additive or multiplicative scale, limiting comparability across studies. Several studies analyzed equity impacts, providing limited evidence that disadvantaged populations are disproportionately vulnerable to compound health effects. Key gaps remain, however, in evaluating the full extent of environmental justice implications, as well as regional effects. Despite these limitations, current evidence underscores the urgency of preparing California populations, particularly vulnerable communities, with resilience strategies to reduce risks from increasingly frequent and severe co-exposures during compound climate events.

BACKGROUND:Maternal air pollution exposure has been associated with impaired fetal growth, yet most studies have overlooked microenvironmental and personal exposures. OBJECTIVES:To examine associations between maternal air pollution exposure in key microenvironments (home, workplace, and commuting route) and fetal growth (birth weight and small for gestational age) using three modelling approaches and personal, home-indoor, and home-outdoor monitoring. METHODS:We used data from 1024 pregnant women in the Barcelona Life Study Cohort (2018-2021). Exposure to nitrogen dioxide, black carbon, and fine particulate matter (PM2.5) and its metallic constituents (copper, iron, and zinc) in each microenvironment were estimated using land use regression models, dispersion models, and hybrid land use regression-dispersion models, and combined with time-activity data to estimate total microenvironment exposures. Personal, home-indoor, and home-outdoor nitrogen dioxide concentrations were measured using passive samplers. Associations with birth weight and small for gestational age were evaluated using linear and logistic mixed-effects models. RESULTS:Higher nitrogen dioxide and black carbon exposure at home and in total microenvironments, estimated by land use regression, dispersion, and hybrid models, were associated with lower birth weight. Increased black carbon exposure in the workplace (hybrid model) and PM2.5 exposure both at home (land use regression model) and in total microenvironments (land use regression and dispersion models) were also associated with reduced birth weight, as were higher home, workplace, and total microenvironmental exposure to metallic components of PM2.5 in land use regression models, although higher workplace PM2.5-zinc was associated with higher birth weight in hybrid models. Higher personal and home-outdoor nitrogen dioxide exposure were further associated with reduced birth weight. Similar patterns were observed for small for gestational age. CONCLUSION:Maternal air pollution exposure was associated with impaired fetal growth. Home-based exposure estimates and short-term nitrogen dioxide measurements may serve as practical exposure proxies during pregnancy.

Heatwave exposures have been linked to a variety of mental and neurological disorders. Little is known, however, about the potentially differential associations of daytime versus nighttime heatwave intensity with subtypes of mental and neurological disorders. In this time-stratified case-crossover study, we estimated and compared the associations of typically dry daytime and typically humid nighttime heatwave intensities, characterized by heatwave indices (HWIs), with acute care utilizations for various subtypes of mental and neurological disorders in 1412 ZIP Code Tabulation Areas in California from 2006 to 2019. A total of 4309 294 acute care utilizations for mental disorders and 2097 563 for neurological disorders were included in this study. Higher associations with nighttime HWI were found for most disease subtypes, including anxiety disorder, depressive disorder, schizophrenia, bipolar disorder, post-traumatic stress disorder, Alzheimer’s disease and related dementias, and Parkinson’s disease; while daytime HWI showed a higher impact on conduct disorders ( P < .001). On average, during the warm season in California, nighttime heatwaves accounted for about 70.6% and 34.0% of acute care utilizations for mental and neurological disorders that were attributable to heatwaves, respectively. Our findings highlight the detrimental impacts of humid nighttime heatwaves on mental and neurological health and call for innovative heat preparedness actions and increased awareness among public health practitioners as more nighttime heatwaves are anticipated under climate change.

BACKGROUND:We investigated associations of self-reported and job exposure matrix (JEM) assigned civilian occupational exposure to vapors, gas, dust, or fumes (VGDF) with respiratory symptoms among previously deployed US Veterans. METHODS:An interviewer-administered questionnaire ascertained self-reported civilian occupational VGDF exposure. A JEM categorized occupational VGDF based on longest-held civilian occupation and industry of employment. Models tested associations of self-reported and JEM-assigned VGDF with dyspnea, chronic bronchitis (CB), or wheeze, adjusting for smoking and other covariates. RESULTS:Among 1868 participants (mean age 37.8 ± 13.1 years); 1654 (89%) males; the median occupational duration was 6 years. The prevalence of JEM-assigned VGDF exposure or self-reported civilian occupational VGDF exposure was 31% for both, with modest agreement between them (kappa 0.48). Any JEM VGDF exposure was statistically significantly associated with increased odds of CB (odds ratio [OR]) 1.75; 95% Confidence Interval [CI] 1.05-2.20). Self-reported VGDF exposure was less strongly associated with increased CB odds (OR 1.18; 95% CI 0.85-1.86). JEM alone demonstrated a statistically significant association with CB (OR 1.77; 95% CI 1.31-2.68); combined JEM and self-reported VGDF demonstrated a similar but not statistically significant association with CB (OR 1.68; 95% CI 0.90-2.35). Self-reported VGDF alone was not positively associated with CB, dyspnea, or wheeze. CONCLUSIONS:Civilian occupational VGDF exposures (assessed by self-report and JEM) were common. Exposure to VGDF was most consistently associated with increased odds of CB, underscoring the need to consider civilian occupational factors when assessing Veterans' health.

Background:Extreme heat and high air pollution levels may co-occur and act synergistically. The synergistic health effects of extreme heat and nitrogen dioxide (NO2), and the fine-scale spatial heterogeneity in such joint effects, remain unclear. We aimed to investigate the synergistic effect of extreme heat and NO2 exposures on cardiorespiratory hospitalizations in California and explore its spatial heterogeneity.Methods:Daily ZIP Code Tabulation Area (ZCTA)-level hospitalization data, 2000-2019, were obtained from the California Department of Health Care Access and Information. Extreme heat and NO2 exposures were defined as days when the heat index and NO2 concentration exceeded a ZCTA-specific threshold, respectively. We first investigated the state-level synergistic effects with a case-crossover analysis and then estimated the ZCTA-specific synergistic effects using a within-community matched design combined with a spatial Bayesian hierarchical model. Finally, we explored how community characteristics modify these effects using meta-regressions.Results:We found mild synergistic effects of extreme heat and NO2 exposures on cardiorespiratory hospitalizations at the state level, with a relative excess risk due to interaction (RERI) of 0.005 (95% confidence interval = -0.002, 0.011). Yet, great spatial heterogeneity was observed, with ZCTA-specific RERIs ranging from -1.08 to 2.22. Higher RERIs were observed in communities with lower socioeconomic status, higher population density, reduced green space, greater proportions of racial and ethnic minority residents, and higher historical temperatures.Conclusions:Our findings underscore the need for adaptation policies that integrate compound exposures to heat and air pollution and inform the development of targeted intervention strategies to protect vulnerable communities.

Volatile organic compounds (VOCs) in wildfire smoke pose health concerns, yet limited information exists on their exposure levels and sources in postfire residential environments. We measured 24 VOCs indoors and outdoors at 50 homes across Los Angeles (LA) County from February 10 to April 1, 2025, within roughly two months following the 2025 LA wildfires. For most VOCs, indoor concentrations were up to 10 times higher than those at outdoor levels. Indoor benzene, perchloroethylene, and trichloroethylene exceeded U.S. EPA or California cancer risk screening levels in 52, 20, and 14% of homes, respectively, while outdoor benzene surpassed its screening level at 28% of sampling locations. Indoor-outdoor correlation and principal component analyses indicate that the observed indoor benzene could be primarily attributed to typical outdoor sources (e.g., vehicle emissions). Household products (particularly cleaning agents) and building material off-gassing were major sources of most other indoor VOCs. The analysis also suggests a possible association between indoor naphthalene and wildfire smoke infiltration, although this finding is limited by the low detection frequency of naphthalene and should be validated in future studies with larger sample sizes. These findings can inform the VOC exposure risk assessment and targeted interventions for communities affected by wildfires.

Climate classification enhances our understanding of regional climate patterns and enables a science-based framework for assessing environmental and public health relationships. Prior climate classification systems are limited in their ability to capture variation across dynamic subclimates, particularly in the context of complex topographical, elevation, and meteorological characteristics such as California, United States. In this study, we spatially classified climate regions in California during the warm season (May through September) in 2021 and 2022. We applied principal component analysis with k-means clustering algorithms to gridded data consisting of apparent temperature during the study period as a monthly time series. We then performed statistical and spatial analysis to delineate the geographical extent of climate regions with shared apparent temperature distributions. The results of this study include a statewide map of 30 warm season climate regions based on meteorological data characterized by homogenous temperature patterns that are distinct from one another. The climate regions demonstrate highly variable spatial patterns of heat exposures and often span across and within multiple county boundaries. The methods we present within a complex geography can be readily adapted to other regional settings and updated to other temporal periods. This study informs our understanding of regional climate patterns during the warm season and is applicable to the development of early warning systems and quantifying extreme heat impacts across statewide populations.

Individuals with Type 2 diabetes (T2D) are highly vulnerable, yet the short-term health and economic burden of air pollution remains poorly understood, especially in moderately polluted regions like California. This study evaluated statewide associations between short-term exposures to nitrogen dioxide (NO2) and fine particulate matter (PM2.5) and diabetes-related hospitalizations during 2010–2019, using a self-controlled case-crossover design and more than 6 million inpatient records from the California Department of Health Care Access and Information. High-resolution (100 m) daily air pollution estimates derived from machine-learning models were assigned to individual ZIP code–level exposure through population-weighted means. Conditional logistic regression estimated odds ratios (ORs) for hospitalization while adjusting for meteorological conditions and temporal trends. Effect modification by race and ethnicity was examined in stratified analyses. Simultaneously, generalized linear models were used to assess associations with hospitalization length of stay (LOS) across 0–3 day exposure lags. Short-term increases in NO2 and PM2.5 were significantly associated with higher hospitalization risk (ORs ≈1.02–1.06 per IQR) and longer LOS (0.5–1.0% per IQR), with the strongest effects within 24–48 hours of exposure. Both NO2 and PM2.5 showed consistent associations across exposure lags. Asians and Hispanics showed greater susceptibility to NO2, while Black patients experienced delayed but persistent PM2.5 effects. Estimated annual avoidable hospitalization costs reached approximately $86.1 million for NO2 and $69.5 million for PM2.5. These findings show that short-term air pollution peaks strain California’s healthcare system and underscore the benefits of reducing NO2 and PM2.5.

The largest natural gas disaster in the US occurred when the gas storage well at the Aliso Canyon natural gas storage facility ruptured on 10/23/2015 and released about 109,000 metric tons of airborne pollutants until 2/18/2016 when the well was capped.We used the California emergency department (ED) visit data to examine whether exposure to pollutants increased the rate of visits. We measured ED visits per 1,000 residents of the affected community living downwind of the well and a comparison group of residents with similar demographic and environmental characteristics (524,508). We further measured ED visits for the primary diagnosis for conditions and symptoms that are associated with such exposure. We examined visits during 10/2013 to 4/2014 or “before”, 10/2015 to 4/2016 or “during”, and 10/2016 to 4/2017 or “after” the blowout. We used the quasi-experimental design to examine the impact of the blowout on ED visits from before to during and after the blowout. We developed ordinary least square regression models controlling for demographics and insurance coverage.We found that the affected community had 26 (confidence interval: 18.5, 33.5) more ED visits per 1,000 from before to during the blowout than the comparison community and this rate remained elevated after the blowout. We also found more ED visits for acute respiratory infections (3.4, CI:1.4, 5.5), anxiety and stress-related disorders (1.3, CI: 0.5, 2.1), respiratory-related symptoms (2.7, CI:1.6, 3.9), and gastrointestinal-related symptoms (5.4, CI: 3.6, 7.2) and these rates also remained elevated. Our findings highlight the importance of understanding all possible public health and societal risks of continued reliance on natural gas and its contribution to climate change.

BackgroundEmerging evidence links air pollution exposure to metabolic dysfunction; however, few studies have examined diabetes-related mortality in relation to ambient air pollutants using high-resolution exposure data at the population level. In the United States, particularly in large and geographically diverse states such as California, exposure contrasts and population heterogeneity provide an important setting to evaluate these associations.MethodsWe conducted a matched case–control analysis using California Department of Public Health (CDPH) Vital Records (2010–2021). Diabetes-related mortality events (ICD-10 E11) were identified as primary or contributory causes. Decedents (cases) were geocoded to residential addresses, and one-year rolling averages of fine particulate matter (PM2.5) before death were assigned as individual exposures. Each death record was matched to its selected controls based on month and year of birth and race-ethnicity. Controls were identified from the same statewide CDPH mortality database and were eligible because they had not died by the corresponding case’s date of death. Because the number of eligible controls varied across matched strata, controls were randomly sampled within each matched stratum to achieve an overall control-to-case ratio of approximately 2:1 for the study population. The final dataset included 60,824 diabetes-related deaths and 119,053 controls. Exposures were standardized by their interquartile range (IQR) and conditional logistic regression models estimated associations between 1 year rolling average fine particulate matter (PM2.5) exposure and odds of diabetes-related mortality, adjusting for age, sex, race-ethnicity, marital status, and education. Nitrogen dioxide (NO2) was included as a co-pollutant for confounding control.ResultsPM2.5 exposure (per 2.65 μg/m3 IQR increase) was associated with a 18% higher odds of diabetes-related mortality (OR = 1.18; 95% CI: 1.15–1.22) before traffic indicator NO2 adjustment and showed a stronger association with 21% higher odds (OR = 1.21; 95% CI: 1.17–1.25) after NO2 adjustment. Health economics analysis estimated that reducing PM2.5 exposure by its IQR could avoid losses of $31.2 million per 100,000 people.ConclusionHigher ambient PM2.5 exposure was associated with increased odds of diabetes-related mortality in California even after adjustment for NO2 and other impact factors. These findings support the need for continued strengthening of ambient air quality regulations.

Air pollution is a leading environmental cause of lung cancer, yet the underlying biological pathways remain poorly understood. Identifying circulating biomarkers that capture early molecular responses may clarify how air pollutants contribute to carcinogenesis and help identify individuals at elevated risk. We conduct a prospective nested case-control study within two Cancer Prevention Study cohorts, profiling more than 1100 metabolites in pre-diagnostic plasma samples from 1357 participants. Residential concentrations of six major air pollutants are estimated at the time of blood draw. Here we show that eight circulating metabolites are associated with both air pollution exposure and subsequent lung cancer risk. Four metabolites, including γ-glutamylglutamine, phenylacetylglutamate, N-(2-furoyl)glycine, and 4-vinylguaiacol glucuronide, significantly mediate associations for particulate matter and ozone (adjusted q-value < 0.2). These findings suggest that air pollution may promote lung cancer partly through metabolic pathways related to inflammatory and oxidative processes, providing key insights into potential mechanisms and targets for prevention.

The 2025 Eaton and Palisades fires in Los Angeles (LA) exemplify destructive wildfires that increasingly threaten cities across the globe. The dangers during the post-burn cleanup phase from major urban wildfires are still being discovered. Here we report that airborne chromium bearing nanoparticles (diameter<56 nm) were found in the LA wildfire debris cleanup zones, a unique finding implicating the fires as a source of nanoparticle metals. The airborne chromium was predominantly in the carcinogenic +6 oxidation state two months post-fire with average concentrations of 13.7 ± 6.2 ng m-3, below the NIOSH workplace exposure limit of 200 ng m-3 but above the US EPA screening levels for indoor air (0.1 ng m-3 for cancer; 3 ng m-3 for non-cancer effects). Model calculations indicate that chromium containing nanoparticles traveled 10–15 km downwind from the cleanup zone. Caution and health surveillance is warranted for nearby residents given that nanoparticles can easily cross cell membranes and circulate throughout the body. Airborne hexavalent chromium nanoparticles were found at concerning levels in debris-cleanup zones after the 2025 Los Angeles wildfires and can travel several kilometers downwind, posing potential health risks to nearby communities, based on mobile air measurements and 3D chemical transport modeling.

The global shift to electric vehicles necessitates the expansion of Direct Current Fast Charging (DCFC) stations, yet the related environmental and public health impacts remain unclear. Here, we report that the power cabinet at DCFC stations emit fine particulate matter (PM2.5). We collected integrated filter samples from 50 DCFC stations across 47 cities in Los Angeles County, California. The daily PM2.5 concentrations were between 7.3 and 39.0 µg m-3, significantly higher than urban background sites (p = 0.02) and the nearest U.S. EPA monitoring stations (p < 0.0001). To understand the emission mechanism of these particles, we measured real-time PM2.5 mass concentration, particle size distribution, and other pollutants, as well as characterized particle chemical compositions on integrated filter samples. Our results indicate that these particles, primarily in the sub-micrometer range (0.5-1.0 µm), are likely due to particle resuspension from the power cabinets. PM2.5 samples from power cabinets showed higher levels of brake and tire wear tracers (Ba, Cu, Zn) and dust tracers (Ca, Al, Fe) compared to samples from nearby chargers and background sites. With no current emission standards for DCFC, managing particle resuspension is crucial for improving air quality and protecting public health as transportation electrification advances.

Smoke from the Los Angeles (LA) wildfires that started on January 7, 2025 caused severe air quality impacts across the region. Government agencies released guidance on assessing personal risk, pointing to publicly available data platforms that present information from monitoring networks and smoke plume outlines. Additional satellite-based products provide supporting information during dynamic wildfire smoke events. We evaluate the regional air quality impacts of the fires through publicly available fine particulate matter (PM2.5) and nitrogen dioxide (NO2) observations from regulatory monitoring stations, PurpleAir low-cost sensors, the TEMPO and TROPOMI satellite sensors, and Hazard Mapping System (HMS) Smoke Plumes during this multifire event. The most extreme air quality impacts were observed on January 8-9, particularly in the southern half of LA county, where daily average PM2.5 concentrations at the downtown LA regulatory monitor reached 101.7 mu g/m3 and 52.3 mu g/m3 in Compton. On January 8th, 12 PurpleAir sensors located closer to burn areas exceeded daily PM2.5 concentrations of 225 mu g/m3. While smoke impacts were largely consistent across all data sources, differences in the spatiotemporal, including vertical, resolution of each product may affect interpretability for end users. This study underscores the importance of integrating multiple air quality data sources and improving accessibility to enhance public health messaging during wildfire events.

California wildfires have grown increasingly frequent and intense over recent decades, raising serious public health concerns. In response, the California Air Resources Board (CARB) 2022 Scoping Plan outlines land management strategies to reduce wildfire risk and associated emissions under various climate change scenarios. This study evaluates the health benefits of CARB's official mitigation pathway, the S3 scenario, compared to a business-as-usual approach, using three global climate models (GCMs) and three future time slices. We apply the GEOS-Chem model to estimate fire-induced PM2.5 concentrations and use the U.S. EPA's BenMAP-CE tool, along with a wildfire-specific chronic mortality dose-response function, to assess associated morbidity and mortality. Results suggest that S3 can significantly reduce fire-related PM2.5 exposure, particularly in northern and central California where concentrations are typically highest-and where S3 treatments are most effective. In 2035 under the second generation Canadian Earth System Model GCM, for instance, S3 is associated with 1,927 fewer premature deaths and substantial reductions in asthma- and respiratory-related emergency room visits. However, health benefits vary by GCM and year, underscoring the influence of meteorological conditions on fire activity and health outcomes. These findings point to the importance of strategically timed and located land management actions and integrating climate variability into future mitigation planning.

Starting on October 23, 2015, wellhead failure at the Aliso Canyon gas storage facility led to a massive blowout near a populated area in Los Angeles County. Aircraft mass balance flights during the event estimated the methane release effectively doubled the total emissions from the Los Angeles basin by the time the leak was capped in February 2016. The plume extent and its spatiotemporal evolution, however, is less well-characterized. Here, we examine the total methane released during the event and the spatial extent of methane plumes using satellite and aircraft remote sensing observations available during the event. In particular, with the inclusion of Landsat-8 and Sentinel-2 satellite observations, we have access to multiple observations earlier during the event history than previously reported. In conjunction with the Hyperion satellite and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) instruments that were available later in the event, we quantify total methane released with more independent and publicly available measurements than previously reported. We find the atmospheric column was enhanced in methane as much as 14 km downwind of the site into February 2016. We compare AVIRIS column enhancements to nearby air quality monitoring stations and find that elevated surface concentrations from stations correlate with plume morphology from remote sensing imagery. Though further research is required to relate atmospheric column enhancement to surface exposure, we show remote sensing to be a powerful tool for estimating emissions and the potential population exposure zone from the Aliso Canyon event.