Marshall Burke’s research while affiliated with Stanford University and other places

Importance A growing body of research suggests that exposure to fine particulate matter (PM 2.5 ; particle size 2.5 microns or smaller) may be associated with mental health outcomes. However, the potential impact of wildfire-specific PM 2.5 exposure on mental health remains underexplored. Objective To investigate whether wildfire-specific PM 2.5 exposure may be associated with emergency department (ED) visits for mental health conditions, including all-cause and for psychoactive substance use, nonmood psychotic disorders, anxiety, depression, and other mood-affective disorders during the extensive 2020 California wildfire season. Design, Setting, and Participants This cross-sectional study used data on ED visits from July to December 2020 obtained from the California Department of Health Care Access and Information (HCAI). Eligible participants were California residents who presented to an ED in California for mental health conditions without COVID-19. The data were analyzed between July 2020 and December 2020. Exposure Wildfire-specific PM 2.5 exposure (with up to 7-day lags) based on participants’ residential zip codes. Main Outcomes and Measures Daily ED visit counts for all-cause and disease-specific mental health conditions (F00-F99) identified using International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes at zip code tabulation areas. Results Between July and December 2020, there were 86 609 ED visits for mental health conditions (median [IQR] patient age, 38 [27-54] years; 40 272 female [46.5%]; 10 657 Black [12.3%], 30 044 Hispanic [34.7%], 35 145 White [40.6%]). Visits included psychoactive substance use (23 966 [27.6%]), nonmood psychotic disorders (16 714 [19.3%]), anxiety (26 711 [30.8%]), depression (10 422 [12.0%]), and other mood-affective disorders (5338 [6.2%]). During peak wildfire months, the median (IQR) daily concentration of wildfire-specific PM 2.5 increased to 11.9 (3.9-32.5) μg/m ³ . A 10-μg/m ³ increase in wildfire-specific PM 2.5 was associated with higher ED visits for all-cause mental conditions (cumulative relative risk [cRR] over lag 0-7 days, 1.08; 95% CI, 1.03-1.12), depression (cRR over lag 0-7 days, 1.15; 95% CI, 1.02-1.30), other mood-affective disorders (cRR over lag 0-7 days, 1.29; 95% CI, 1.09-1.54), and anxiety (cRR over lag 0-4 days, 1.06; 95% CI, 1.00-1.12). Subgroup analyses suggested that wildfire smoke was associated with disproportionately increased ED visits among female individuals (eg, depression: cRR over lag 0-4 days, 1.17; 95% CI, 1.03-1.32) and young people (other mood-affective disorders: cRR over lag 0-4 days, 1.46; 95% CI, 1.08-1.98). Effect modification by race was found, with non-Hispanic Black individuals having an increased risk of ED visits for other mood-affective disorders (cRR over lag 0-5 days, 2.35; 95% CI, 1.56-3.53) and Hispanic individuals an increased risk for visits for depression (cRR over lag 0-7 days, 1.30; 95% CI, 1.06-1.59). Conclusions and Relevance Wildfire smoke exposure was associated with significantly increased odds of subsequent ED visits for mental health conditions in this cross-sectional study, with varying lag times for different subconditions and demographic groups.

Understanding the mortality effects of the most extreme heat events is central to climate change risk analysis and adaptation decision-making. Accurate representation of these impacts requires accounting for the effects of prolonged sequences of hot days on mortality, the change in that mortality due to anthropogenic forcing, and the potential compensating effects of adaptation to heat. Here, we revisit the August 2003 heat wave in France, a canonical event in a region with rich climate and mortality data, to understand these influences. We find that standard heat mortality exposure-response functions underpredict excess deaths in August 2003 by 60%, but that accounting for the temporally compounding effects of hot days better matches observed mortality. After accounting for compounding effects and applying a machine learning approach to single-event climate attribution, we attribute 6,038 deaths in August 2003 to climate change, ten times higher than previous estimates. Finally, we show that recent adaptation to heat has reduced the projected death tolls of future 2003-like events by more than 80%.

Poor ambient air quality poses a substantial global health threat. However, accurate measurement remains challenging, particularly in countries such as India where ground monitors are scarce despite high expected exposure and health burdens. This lack of precise measurements impedes understanding of changes in pollution exposure over time and across populations. Here, we develop open-source daily fine particulate matter (PM 2.5 ) datasets at a 10-kilometer resolution for India from 2005 to 2023 using a two-stage machine learning model validated on held-out monitor data. Analyzing long-term air quality trends, we find that PM 2.5 concentrations increased across most of the country until around 2016 and then declined partly due to favorable meteorology in southern India. Recent reductions in PM 2.5 were substantially larger in wealthier areas, highlighting the urgency of air quality control policies addressing all socioeconomic communities. To advance equitable air quality monitoring, we propose additional monitor locations in India and examine the adaptability of our method to other countries with scarce monitoring data.

The potential death toll of worst-case extreme heat events is crucial for climate risk analysis and adaptation planning. We estimate this quantity for Europe using machine learning to calculate the intensity of historical heat waves if they occur at present or future global temperatures, combined with empirical exposure-response functions to quantify the resulting mortality. Each event is projected to generate tens of thousands of excess deaths. For example, if July 1994 or August 2003 meteorological conditions recur at the current global temperature anomaly of 1.5 °C, we project 14,000 or 17,300 excess deaths across Europe in a single week, respectively. At 3 °C, mortality rises to 26,800 or 31,500 per week. These death rates are comparable to peak COVID-19 mortality in Europe and are not substantially reduced by ongoing climate adaptation. Our results suggest that avoiding mass heat mortality in Europe will require significant and novel adaptation to heat.

Prescribed fire is increasingly proposed as a policy strategy to reduce wildfire risks, but evidence of its effectiveness in lowering fire severity and smoke emissions remains limited in the western US. We empirically demonstrate that areas treated with prescribed fire and subsequently burned during California’s extreme 2020 wildfire season showed a -14% net reduction in smoke emissions, though these treatments were less effective near populated areas. Our findings suggest that expanding prescribed fire use can meaningfully reduce smoke emissions, even when factoring in smoke from the prescribed fires themselves. The proposed policy of treating one million acres annually in California could reduce overall smoke emissions by 655,000 metric tons over the next five years—equivalent to 52% of the emissions from 2020 wildfires. Our results also suggest that broader application of prescribed fires can provide benefits in mitigating severe wildfire impacts and improve air quality in fire-prone regions worldwide.

Poor air quality is known to be one of the leading contributors to poor child health globally, and a wealth of evidence has linked pollution exposure during pregnancy to adverse birth and early-life outcomes. While there is some evidence pollution exposure during pregnancy is associated with slowed child growth, this evidence is largely limited to empirical settings in which it is difficult to disentangle the role of pollution from other co-varying factors. Here we rely on quasi-random variation in pollution conditions induced by thermal inversions to estimate the impact of pollution spikes during pregnancy on childhood stunting. We find that thermal inversions during pregnancy worsen air quality and increase the likelihood of childhood stunting, but only in places with poor baseline air quality and particularly for younger children and in lower-wealth communities. Our estimates imply that a 1 µg m⁻³ increase in average PM2.5 concentration during pregnancy increases the probability of stunting by an average of 4.1 percentage points (95% CI: 0.2–8.0). This translates to an 11.2% increase (95% CI: 0.6%–21.9%) in stunting risk from the sample baseline of 37% children stunted. Our results suggest that policies that limit baseline daily PM2.5 levels, particularly during seasons when thermal inversions are more frequent, have potential to generate meaningful improvements in long-run child outcomes.

Growing wildfire activity across North America produces significant smoke, undermining efforts to regulate surface air quality and protect public health. Using surface measurements, satellites, and machine learning, we provide granular, daily estimates of smoke PM2.5 concentrations in the contiguous U.S. from 2006 to 2023, and use them to assess the implications of smoke for surface air pollution and its regulation. From 2020 to 2023, population average smoke PM2.5 concentrations were 2.6–6.7 times higher than the 2006–2019 average, with exposure periods twice as long. The 5 worst exposure days in our sample period all occurred in 2023, a year with limited exposure in the western U.S. Wildfire smoke has recently driven 34% of monitoring stations above updated air quality standards, and is making the use of extreme event exemptions challenging. Without wildfire smoke, PM2.5 levels would have continued improving across the US.