Air pollution changes due to COVID-19 lockdowns and attributable mortality changes in four countries.

COVID-19 lockdowns reduced nitrogen dioxide (NO2) and fine particulate matter (PM2.5) emissions in many countries. We aim to quantify the changes in these pollutants and to assess the attributable changes in mortality in Jiangsu, China; California, U.S.; Central-southern Italy; and Germany during COVID-19 lockdowns in early 2020. Accounting for meteorological impacts and air pollution time trends, we use a machine learning-based meteorological normalization technique and the difference-in-differences approach to quantify the changes in NO2 and PM2.5 concentrations due to lockdowns. Using region-specific estimates of the association between air pollution and mortality derived from a causal modeling approach using data from 2015 to 2019, we assess the changes in mortality attributable to the air pollution changes caused by the lockdowns in early 2020. During the lockdowns, NO2 reductions avoided 1.41 (95% empirical confidence interval [eCI]: 0.94, 1.88), 0.44 (95% eCI: 0.17, 0.71), and 4.66 (95% eCI: 2.03, 7.44) deaths per 100,000 people in Jiangsu, China; California, U.S.; and Central-southern Italy, respectively. Mortality benefits attributable to PM2.5 reductions were also significant, albeit of a smaller magnitude. For Germany, the mortality benefits attributable to NO2 changes were not significant (0.11; 95% eCI: -0.03, 0.25), and an increase in PM2.5 concentrations was associated with an increase in mortality of 0.35 (95% eCI: 0.22, 0.48) deaths per 100,000 people during the lockdown. COVID-19 lockdowns overall improved air quality and brought attributable health benefits, especially associated with NO2 improvements, with notable heterogeneity across regions. This study underscores the importance of accounting for local characteristics when policymakers adapt successful emission control strategies from other regions.

Comprehensive evaluation framework for intervention on health effects of ambient temperature.

Despite the existence of many interventions to mitigate or adapt to the health effects of climate change, their effectiveness remains unclear. Here, we introduce the Comprehensive Evaluation Framework for Intervention on Health Effects of Ambient Temperature to evaluate study designs and effects of intervention studies. The framework comprises three types of interventions: proactive, indirect, and direct, and four categories of indicators: classification, methods, scope, and effects. We trialed the framework by an evaluation of existing intervention studies. The evaluation revealed that each intervention has its own applicable characteristics in terms of effectiveness, feasibility, and generalizability scores. We expanded the framework's potential by offering a list of intervention recommendations in different scenarios. Future applications are then explored to establish models of the relationship between study designs and intervention effects, facilitating effective interventions to address the health effects of ambient temperature under climate change.

Short-Term Exposure to Fine Particulate Matter and Nitrogen Dioxide and Mortality in 4 Countries.

Importance: The association between short-term exposure to air pollution and mortality has been widely documented worldwide; however, few studies have applied causal modeling approaches to account for unmeasured confounders that vary across time and space. Objective: To estimate the association between short-term changes in fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations and changes in daily all-cause mortality rates using a causal modeling approach. Design, Setting, and Participants: This cross-sectional study used air pollution and mortality data from Jiangsu, China; California; central-southern Italy; and Germany with interactive fixed-effects models to control for both measured and unmeasured spatiotemporal confounders. A total of 8 963 352 deaths in these 4 regions from January 1, 2015, to December 31, 2019, were included in the study. Data were analyzed from June 1, 2021, to October 30, 2023. Exposure: Day-to-day changes in county- or municipality-level mean PM2.5 and NO2 concentrations. Main Outcomes and Measures: Day-to-day changes in county- or municipality-level all-cause mortality rates. Results: Among the 8 963 352 deaths in the 4 study regions, a 10-µg/m3 increase in daily PM2.5 concentration was associated with an increase in daily all-cause deaths per 100 000 people of 0.01 (95% CI, 0.001-0.01) in Jiangsu, 0.03 (95% CI, 0.004-0.05) in California, 0.10 (95% CI, 0.07-0.14) in central-southern Italy, and 0.04 (95% CI, 0.02- 0.05) in Germany. The corresponding increases in mortality rates for a 10-µg/m3 increase in NO2 concentration were 0.04 (95% CI, 0.03-0.05) in Jiangsu, 0.03 (95% CI, 0.01-0.04) in California, 0.10 (95% CI, 0.05-0.15) in central-southern Italy, and 0.05 (95% CI, 0.04-0.06) in Germany. Significant effect modifications by age were observed in all regions, by sex in Germany (eg, 0.05 [95% CI, 0.03-0.06] for females in the single-pollutant model of PM2.5), and by urbanicity in Jiangsu (0.07 [95% CI, 0.04-0.10] for rural counties in the 2-pollutant model of NO2). Conclusions and Relevance: The findings of this cross-sectional study contribute to the growing body of evidence that increases in short-term exposures to PM2.5 and NO2 may be associated with increases in all-cause mortality rates. The interactive fixed-effects model, which controls for unmeasured spatial and temporal confounders, including unmeasured time-varying confounders in different spatial units, can be used to estimate associations between changes in short-term exposure to air pollution and changes in health outcomes.

Ozone-related acute excess mortality projected to increase in the absence of climate and air quality controls consistent with the Paris Agreement.

Short-term exposure to ground-level ozone in cities is associated with increased mortality and is expected to worsen with climate and emission changes. However, no study has yet comprehensively assessed future ozone-related acute mortality across diverse geographic areas, various climate scenarios, and using CMIP6 multi-model ensembles, limiting our knowledge on future changes in global ozone-related acute mortality and our ability to design targeted health policies. Here, we combine CMIP6 simulations and epidemiological data from 406 cities in 20 countries or regions. We find that ozone-related deaths in 406 cities will increase by 45 to 6,200 deaths/year between 2010 and 2014 and between 2050 and 2054, with attributable fractions increasing in all climate scenarios (from 0.17% to 0.22% total deaths), except the single scenario consistent with the Paris Climate Agreement (declines from 0.17% to 0.15% total deaths). These findings stress the need for more stringent air quality regulations, as current standards in many countries are inadequate.

Evaluating the sensitivity of mortality attributable to pollution to modeling Choices: A case study for Colorado.

We evaluated the sensitivity of estimated PM2.5 and NO2 health impacts to varying key input parameters and assumptions including: 1) the spatial scale at which impacts are estimated, 2) using either a single concentration-response function (CRF) or using racial/ethnic group specific CRFs from the same epidemiologic study, 3) assigning exposure to residents based on home, instead of home and work locations for the state of Colorado. We found that the spatial scale of the analysis influences the magnitude of NO2, but not PM2.5, attributable deaths. Using county-level predictions instead of 1 km2 predictions of NO2 resulted in a lower estimate of mortality attributable to NO2 by âˆ¼ 50 % for all of Colorado for each year between 2000 and 2020. Using an all-population CRF instead of racial/ethnic group specific CRFs results in a 130 % higher estimate of annual mortality attributable for the white population and a 40 % and 80 % lower estimate of mortality attributable to PM2.5 for Black and Hispanic residents, respectively. Using racial/ethnic group specific CRFs did not result in a different estimation of NO2 attributable mortality for white residents, but led to âˆ¼ 50 % lower estimates of mortality for Black residents, and 290 % lower estimate for Hispanic residents. Using NO2 based on home instead of home and workplace locations results in a smaller estimate of annual mortality attributable to NO2 for all of Colorado by 2 % each year and 0.3 % for PM2.5. Our results should be interpreted as an exercise to make methodological recommendations for future health impact assessments of pollution.

Unpacking the factors contributing to changes in PM2.5-associated mortality in China from 2013 to 2019.

From 2013 to 2019, a series of air pollution control actions significantly reduced PM2.5 pollution in China. Control actions included changes in activity levels, structural adjustment (SA) policy, energy and material saving (EMS) policy, and end-of-pipe (EOP) control in several sources, which have not been systematically studied in previous studies. Here, we integrate an emission inventory, a chemical transport model, a health impact assessment model, and a scenario analysis to quantify the contribution of each control action across a range of major emission sources to the changes in PM2.5 concentrations and associated mortality in China from 2013 to 2019. Assuming equal toxicity of PM2.5 from all the sources, we estimate that PM2.5-related mortality decreased from 2.52 (95 % confidence interval, 2.13-2.88) to 1.94 (1.62-2.24) million deaths. Anthropogenic emission reductions and declining baseline incidence rates significantly contributed to health benefits, but population aging partially offset their impact. Among the major sources, controls on power plants and industrial boilers were responsible for the highest reduction in PM2.5-related mortality (∼80 %), followed by industrial processes (∼40 %), residential combustion (∼40 %), and transportation (∼30 %). However, considering the potentially higher relative risks of power plant PM2.5, the adverse effects avoided by their control could be ∼2.4 times the current estimation. Our power plant sensitivity analyses indicate that future estimates of source-specific PM2.5 health effects should incorporate variations in individual source PM2.5 effect coefficients when available. As for the control actions, while activity levels increased for most sources, SA policy significantly reduced the emissions in residential combustion and industrial boilers, and EOP control dominated the contribution in health benefits in most sources except residential combustion. Considering the emission reduction potential by source and control actions in 2019, our results suggest that promoting clean energy in residential combustion and enforcing more stringent EOP control in the iron and steel industry should be prioritized in the future.

Tracking Progress Toward Urban Nature Targets Using Landcover and Vegetation Indices: A Global Study for the 96 C40 Cities.

Access to urban natural space, including blue and greenspace, is associated with improved health. In 2021, the C40 Cities Climate Leadership Group set 2030 Urban Nature Declaration (UND) targets: "Quality Total Cover" (30% green area within each city) and "Equitable Spatial Distribution" (70% of the population living close to natural space). We evaluate progress toward these targets in the 96 C40 cities using globally available, high-resolution data sets for landcover and normalized difference vegetation index (NDVI). We use the European Space Agency (ESA)'s WorldCover data set to define greenspace with discrete landcover categories and ESA's Sentinel-2A to calculate NDVI, adding the "open water" landcover category to characterize total natural space. We compare 2020 levels of urban green and natural space to the two UND targets and predict the city-specific NDVI level consistent with the UND targets using linear regressions. The 96-city mean NDVI was 0.538 (range: 0.148, 0.739). Most (80%) cities meet the Quality Total Cover target, and nearly half (47%) meet the Equitable Spatial Distribution target. Landcover-measured greenspace and total natural space were strong (mean R 2 = 0.826) and moderate (mean R 2 = 0.597) predictors of NDVI and our NDVI-based natural space proximity measure, respectively. The 96-city mean predicted NDVI value of meeting the UND targets was 0.478 (range: 0.352-0.565) for Quality Total Cover and 0.660 (range: 0.498-0.767) for Equitable Spatial Distribution. Our translation of the area- and access-based metrics common in urban natural space targets into the NDVI metric used in epidemiology allows for quantifying the health benefits of achieving such targets.

Quantifying Disparities in Air Pollution Exposures across the United States Using Home and Work Addresses.

While human mobility plays a crucial role in determining ambient air pollution exposures and health risks, research to date has assessed risks on the basis of almost solely residential location. Here, we leveraged a database of ∼128-144 million workers in the United States and published ambient PM2.5 data between 2011 and 2018 to explore how incorporating information on both workplace and residential location changes our understanding of disparities in air pollution exposure. In general, we observed higher workplace exposures relative to home exposures, as well as increased exposures for nonwhite and less educated workers relative to the national average. Workplace exposure disparities were higher among racial and ethnic groups and job types than by income, education, age, and sex. Not considering workplace exposures can lead to systematic underestimations in disparities in exposure among these subpopulations. We also quantified the error in assigning workers home instead of a weighted home-and-work exposure. We observed that biases in associations between PM2.5 and health impacts by using home instead of home-and-work exposure were the highest among urban, younger populations.

Household Air Pollution and Child Lung Function: The Ghana Randomized Air Pollution and Health Study.

RATIONALE: The impact of a household air pollution (HAP) stove intervention on child lung function is poorly described. OBJECTIVES: To assess the effect of a prenatal to age one HAP stove intervention on, and exposure-response associations with, age four lung function. METHODS: The Ghana Randomized Air Pollution and Health Study (GRAPHS) randomized pregnant women to a liquefied petroleum gas (LPG), improved biomass, or open fire (control) stove through child age one. We quantified HAP exposure by repeated maternal and child personal carbon monoxide (CO) exposure measurements. Children performed oscillometry, an effort-independent lung function measurement, at age four. We examined associations between GRAPHS stove assignment and prenatal and infant CO measurements and oscillometry via generalized linear regression models. We used reverse distributed lag models (rDLMs) to examine time-varying associations between prenatal CO and oscillometry. MEASUREMENTS AND MAIN RESULTS: The primary oscillometry measure was reactance at 5 Hertz, X5, a measure of elastic and inertial lung properties. Secondary measures included total, large and small airway resistance (R5, R20, R5-20), area of reactance (AX) and resonant frequency (Fres). Of the 683 children who attended the lung function visit, 567 (83%) performed acceptable oscillometry. Two hundred and twenty-one, 106, and 240 children were from the LPG, improved biomass and control arms, respectively. Compared to control, the improved biomass stove was associated with lower reactance at 5 Hertz (X5 z-score, beta=-0.25, 95% CI -0.39, -0.11), higher large airway resistance (R20 z-score, beta=0.34, 95% CI 0.23, 0.44) and higher area of reactance (AX z-score, beta=0.16, 95% CI 0.06, 0.26) suggestive of overall worse lung function. The LPG stove was associated with higher X5 (beta=0.16, 95% CI 0.01, 0.31) and lower small airway resistance (R5-20 z-score, beta=-0.15, 95% CI -0.30, 0.0) suggestive of better small airway function. Higher average prenatal CO exposure was associated with higher R5 and R20 and DLMs identified sensitive windows of exposure between CO and X5, R5, R20 and R5-20. CONCLUSIONS: These data support the importance of prenatal HAP exposure on child lung function. Clinical trial registration available at www. CLINICALTRIALS: gov, ID: NCT01335490.

Acute exposure to total and source-specific ambient fine particulate matter and risk of respiratory disease hospitalization in Kuwait.

Many epidemiologic studies concerned with acute exposure to ambient PM2.5 have reported positive associations for respiratory disease hospitalization. However, few studies have investigated this relationship in Kuwait and extrapolating results from other regions may involve considerable uncertainty due to variations in concentration levels, particle sources and composition, and population characteristics. Local studies can provide evidence for strategies to reduce risks from episodic exposures to high levels of ambient PM2.5 and generating hypotheses for evaluating health risks from chronic exposures. Therefore, using speciated PM2.5 data from local samplers, we analyzed the impact of daily total and source-specific PM2.5 exposure on respiratory hospitalizations in Kuwait using a case-crossover design with conditional quasi-Poisson regression. Total and source-specific ambient PM2.5 were modeled using 0-5-day cumulative distributed lags. For total PM2.5, we observed a 0.16% (95% confidence interval [CI] = 0.05, 0.27%) increase in risk for respiratory hospitalization per 1 µg/m3 increase in concentration. Of the source factors assessed, dust demonstrated a statistically significant increase in risk (0.16%, 95% CI = 0.04, 0.29%), and the central estimate for regional PM2.5 was positive (0.11%) but not statistically significant (95% CI = -0.11, 0.33%). No effect was observed from traffic emissions and 'other' source factors. When hospitalizations were stratified by sex, nationality, and age, we found that female, Kuwaiti national, and adult groups had higher effect estimates. These results suggest that exposure to ambient PM2.5 is harmful in Kuwait and provide some evidence of differential toxicity and effect modification depending on the PM2.5 source and population affected.

Health-based strategies for overcoming barriers to climate change adaptation and mitigation.

Climate change poses an unequivocal threat to the respiratory health of current and future generations. Human activities-largely through the release of greenhouse gases-are driving rising global temperatures. Without a concerted effort to mitigate greenhouse gas emissions or adapt to the effects of a changing climate, each increment of warming increases the risk of climate hazards (eg, heat waves, floods, and droughts) that that can adversely affect allergy and immunologic diseases. For instance, wildfires, which release large quantities of particulate matter with a diameter of less than 2.5 µm (an air pollutant), occur with greater intensity, frequency, and duration in a hotter climate. This increases the risk of associated respiratory outcomes such as allergy and asthma. Fortunately, many mitigation and adaptation strategies can be applied to limit the impacts of global warming. Adaptation strategies, ranging from promotions of behavioral changes to infrastructural improvements, have been effectively deployed to increase resilience and alleviate adverse health effects. Mitigation strategies aimed at reducing greenhouse gas emissions can not only address the problem at the source but also provide numerous direct health cobenefits. Although it is possible to limit the impacts of climate change, urgent and sustained action must be taken now. The health and scientific community can play a key role in promoting and implementing climate action to ensure a more sustainable and healthy future.

Identifying sensitive windows of prenatal household air pollution on birth weight and infant pneumonia risk to inform future interventions.

BACKGROUND: Prenatal household air pollution impairs birth weight and increases pneumonia risk however time-varying associations have not been elucidated and may have implications for the timing of public health interventions. METHODS: The Ghana Randomized Air Pollution and Health Study (GRAPHS) enrolled 1,414 pregnant women from Kintampo, Ghana and measured personal carbon monoxide (CO) exposure four times over pregnancy. Birth weight was measured within 72-hours of birth. Fieldworkers performed weekly pneumonia surveillance and referred sick children to study physicians. The primary pneumonia outcome was one or more physician-diagnosed severe pneumonia episode in the first year of life. We employed reverse distributed lag models to examine time-varying associations between prenatal CO exposure and birth weight and infant pneumonia risk. RESULTS: Analyses included n = 1,196 mother-infant pairs. In models adjusting for child sex; maternal age, body mass index (BMI), ethnicity and parity at enrollment; household wealth index; number of antenatal visits; and evidence of placental malaria, prenatal CO exposures from 15 to 20 weeks gestation were inversely associated with birth weight. Sex-stratified models identified a similar sensitive window in males and a window at 10-weeks gestation in females. In models adjusting for child sex, maternal age, BMI and ethnicity, household wealth index, gestational age at delivery and average postnatal child CO exposure, CO exposure during 34-39 weeks gestation were positively associated with severe pneumonia risk, especially in females. CONCLUSIONS: Household air pollution exposures in mid- and late- gestation are associated with lower birth weight and higher pneumonia risk, respectively. These findings support the urgent need for deployment of clean fuel stove interventions beginning in early pregnancy.

Solidarity for the Anthropocene.

Social solidarity is essential to large-scale collective action, but the need for solidarity has received little attention from scholars of Earth Systems, sustainability and public health. Now, the need for solidarity requires recognition. We have entered a new planetary epoch - the Anthropocene - in which human-induced global changes are occurring at an unprecedented scale. There are multiple health crises facing humanity - widening inequity, climate change, biodiversity loss, diminishing resources, persistent poverty, armed conflict, large-scale migration, and others. These global challenges are so far-reaching, and call for such extensive, large-scale action, that solidarity is a sine qua non for tackling these challenges. However, the heightened need for solidarity has received little attention in the context of the Anthropocene and, in particular, how it can be created and nurtured has been overlooked. In this commentary, we explore the concept of solidarity from inter-species, intra-generational and inter-generational perspectives. We also propose strategies to enhance solidarity in the Anthropocene.

Development of a global urban greenness indicator dataset for 1,000+ cities.

Global climate change has sparked efforts to adapt to increasing temperatures, especially in urban areas that experience increased day and nighttime temperatures due to the urban heat island effect. The addition of greenspace has been suggested as a possible means for urban centers to respond to increasing urban temperatures. Thus, it is important for urban planning and policymakers to have access to data on greenspace specific at a fine spatial resolution. This dataset consists of information on peak and annual average 1 × 1 km Normalized Difference Vegetation Index (NDVI) for over 1,000 global urban centers, which is an objective satellite-based measure of vegetation. Population-weighted values for both peak and annual average NDVI and include an indicator of greenness, with seven levels ranging from extremely low to extremely high are provided. Additional information regarding the climate zone (using the Köppen-Geiger climate classification) and level of development (using the Human Development Index or HDI) for each city is included. Analyses were repeated in 2010, 2015, and 2020 to provide the ability to track urban greenness over time. Data are provided in tabular format with summaries presented in both tables and graphics. These data can be used to inform policy and planning and can be used as an indicator for a variety of climate and health investigations.

Association between malaria and household air pollution interventions in a predominantly rural area of Ghana.

BACKGROUND: Though anecdotal evidence suggests that smoke from HAP has a repellent effect on mosquitoes, very little work has been done to assess the effect of biomass smoke on malaria infection. The study, therefore, sought to investigate the hypothesis that interventions to reduce household biomass smoke may have an unintended consequence of increasing placental malaria or increase malaria infection in the first year of life. METHODS: This provides evidence from a randomized controlled trial among 1414 maternal-infant pairs in the Kintampo North and Kintampo South administrative areas of Ghana. Logistic regression was used to assess the association between study intervention assignment (LPG, Biolite or control) and placental malaria. Finally, an extended Cox model was used to assess the association between study interventions and all episodes of malaria parasitaemia in the first year of infant's life. RESULTS: The prevalence of placental malaria was 24.6%. Out of this, 20.8% were acute infections, 18.7% chronic infections and 60.5% past infections. The study found no statistical significant association between the study interventions and all types of placental malaria (OR = 0.88; 95% CI 0.59-1.30). Of the 1165 infants, 44.6% experienced at least one episode of malaria parasitaemia in the first year of life. The incidence of first and/or only episode of malaria parasitaemia was however found to be similar among the study arms. CONCLUSION: The findings suggest that cookstove interventions for pregnant women and infants, when combined with additional malaria prevention strategies, do not lead to an increased risk of malaria among pregnant women and infants.

Trends of source apportioned PM2.5 in Tianjin over 2013-2019: Impacts of Clean Air Actions.

A long-term (2013-2019) PM2.5 speciation dataset measured in Tianjin, the largest industrial city in northern China, was analyzed with dispersion normalized positive matrix factorization (DN-PMF). The trends of source apportioned PM2.5 were used to assess the effectiveness of source-specific control policies and measures in support of the two China's Clean Air Actions implemented nationwide in 2013-2017 and 2018-2020, respectively. Eight sources were resolved from the DN-PMF analysis: coal combustion (CC), biomass burning (BB), vehicular emissions, dust, steelmaking and galvanizing emissions, a mixed sulfate-rich factor and secondary nitrate. After adjustment for meteorological fluctuations, a substantial improvement in PM2.5 air quality was observed in Tianjin with decreases in PM2.5 at an annual rate of 6.6%/y. PM2.5 from CC decreased by 4.1%/y. The reductions in SO2 concentration, PM2.5 contributed by CC, and sulfate demonstrated the improved control of CC-related emissions and fuel quality. Policies aimed at eliminating winter-heating pollution have had substantial success as shown by reduced heating-related SO2, CC, and sulfate from 2013 to 2019. The two industrial source types showed sharp drops after the 2013 mandated controls went into effect to phaseout outdated iron/steel production and enforce tighter emission standards for these industries. BB reduced significantly by 2016 and remained low due to the no open field burning policy. Vehicular emissions and road/soil dust declined over the Action's first phase followed by positive upward trends, showing that further emission controls are needed. Nitrate concentrations remained constant although NOX emissions dropped significantly. The lack of a decrease in nitrate may result from increased ammonia emissions from enhanced vehicular NOX controls. The port and shipping emissions were evident implying their impacts on coastal air quality. These results affirm the effectiveness of the Clean Air Actions in reducing primary anthropogenic emissions. However, further emission reductions are needed to meet global health-based air quality standards.

Using time-resolved monitor wearing data to study the effect of clean cooking interventions on personal air pollution exposures.

BACKGROUND: Personal monitoring can estimate individuals' exposures to environmental pollutants; however, accuracy depends on consistent monitor wearing, which is under evaluated. OBJECTIVE: To study the association between device wearing and personal air pollution exposure. METHODS: Using personal device accelerometry data collected in the context of a randomized cooking intervention in Ghana with three study arms (control, improved biomass, and liquified petroleum gas (LPG) arms; N = 1414), we account for device wearing to infer parameters of PM2.5 and CO exposure. RESULTS: Device wearing was positively associated with exposure in the control and improved biomass arms, but weakly in the LPG arm. Inferred community-level air pollution was similar across study arms (~45 µg/m3). The estimated direct contribution of individuals' cooking to PM2.5 exposure was 64 µg/m3 for the control arm, 74 µg/m3 for improved biomass, and 6 µg/m3 for LPG. Arm-specific average PM2.5 exposure at near-maximum wearing was significantly lower in the LPG arm as compared to the improved biomass and control arms. Analysis of personal CO exposure mirrored PM2.5 results. CONCLUSIONS: Personal monitor wearing was positively associated with average air pollution exposure, emphasizing the importance of high device wearing during monitoring periods and directly assessing device wearing for each deployment. SIGNIFICANCE: We demonstrate that personal monitor wearing data can be used to refine exposure estimates and infer unobserved parameters related to the timing and source of environmental exposures. IMPACT STATEMENTS: In a cookstove trial among pregnant women, time-resolved personal air pollution device wearing data were used to refine exposure estimates and infer unobserved exposure parameters, including community-level air pollution, the direct contribution of cooking to personal exposure, and the effect of clean cooking interventions on personal exposure. For example, in the control arm, while average 48 h personal PM2.5 exposure was 77 µg/m3, average predicted exposure at near-maximum daytime device wearing was 108 µg/m3 and 48 µg/m3 at zero daytime device wearing. Wearing-corrected average 48 h personal PM2.5 exposures were 50% lower in the LPG arm than the control and improved biomass and inferred direct cooking contributions to personal PM2.5 from LPG were 90% lower than the other arms. Our recommendation is that studies assessing personal exposures should examine the direct association between device wearing and estimated mean personal exposure.