Improving consistency in estimating future health burdens from environmental risk factors: Case study for ambient air pollution.

Future changes in exposure to risk factors should impact mortality rates and population. However, studies commonly use mortality rates and population projections developed exogenously to the health impact assessment model used to quantify future health burdens attributable to environmental risks that are therefore invariant to projected exposure levels. This impacts the robustness of many future health burden estimates for environmental risk factors. This work describes an alternative methodology that more consistently represents the interaction between risk factor exposure, population and mortality rates, using ambient particulate air pollution (PM2.5) as a case study. A demographic model is described that estimates future population based on projected births, mortality and migration. Mortality rates are disaggregated between the fraction due to PM2.5 exposure and other factors for a historic year, and projected independently. Accounting for feedbacks between future risk factor exposure and population and mortality rates can greatly affect estimated future attributable health burdens. The demographic model estimates much larger PM2.5-attributable health burdens with constant 2019 PM2.5 (∼10.8 million deaths in 2050) compared to a model using exogenous population and mortality rate projections (∼7.3 million), largely due to differences in mortality rate projection methods. Demographic model-projected PM2.5-attributable mortality can accumulate substantially over time. For example, ∼71 million more people are estimated to be alive in 2050 when WHO guidelines (5 µg m-3) are achieved compared to constant 2019 PM2.5 concentrations. Accounting for feedbacks is more important in applications with relatively high future PM2.5 concentrations, and relatively large changes in non-PM2.5 mortality rates.

Increasing Racial and Ethnic Disparities in Ambient Air Pollution-Attributable Morbidity and Mortality in the United States.

BACKGROUND: Ambient nitrogen dioxide (NO2) and fine particulate matter with aerodynamic diameter ≤2.5µm (PM2.5) threaten public health in the US, and systemic racism has led to modern-day disparities in the distribution and associated health impacts of these pollutants. OBJECTIVES: Many studies on environmental injustices related to ambient air pollution focus only on disparities in pollutant concentrations or provide only an assessment of pollution or health disparities at a snapshot in time. In this study, we compare injustices in NO2- and PM2.5-attributable health burdens, considering NO2-attributable health impacts across the entire US; document changing disparities in these health burdens over time (2010-2019); and evaluate how more stringent air quality standards would reduce disparities in health impacts associated with these pollutants. METHODS: Through a health impact assessment, we quantified census tract-level variations in health outcomes attributable to NO2 and PM2.5 using health impact functions that combine demographic data from the US Census Bureau; two spatially resolved pollutant datasets, which fuse satellite data with physical and statistical models; and epidemiologically derived relative risk estimates and incidence rates from the Global Burden of Disease study. RESULTS: Despite overall decreases in the public health damages associated with NO2 and PM2.5, racial and ethnic relative disparities in NO2-attributable pediatric asthma and PM2.5-attributable premature mortality have widened in the US during the last decade. Racial relative disparities in PM2.5-attributable premature mortality and NO2-attributable pediatric asthma have increased by 16% and 19%, respectively, between 2010 and 2019. Similarly, ethnic relative disparities in PM2.5-attributable premature mortality have increased by 40% and NO2-attributable pediatric asthma by 10%. DISCUSSION: Enacting and attaining more stringent air quality standards for both pollutants could preferentially benefit the most marginalized and minoritized communities by greatly reducing racial and ethnic relative disparities in pollution-attributable health burdens in the US. Our methods provide a semi-observational approach to track changes in disparities in air pollution and associated health burdens across the US. https://doi.org/10.1289/EHP11900.

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.

Public Health Benefits From Improved Identification of Severe Air Pollution Events With Geostationary Satellite Data.

Despite improvements in ambient air quality in the US in recent decades, many people still experience unhealthy levels of pollution. At present, national-level alert-day identification relies predominately on surface monitor networks and forecasters. Satellite-based estimates of surface air quality have rapidly advanced and have the capability to inform exposure-reducing actions to protect public health. At present, we lack a robust framework to quantify public health benefits of these advances in applications of satellite-based atmospheric composition data. Here, we assess possible health benefits of using geostationary satellite data, over polar orbiting satellite data, for identifying particulate air quality alert days (24hr PM2.5 > 35 µg m-3) in 2020. We find the more extensive spatiotemporal coverage of geostationary satellite data leads to a 60% increase in identification of person-alerts (alert days × population) in 2020 over polar-orbiting satellite data. We apply pre-existing estimates of PM2.5 exposure reduction by individual behavior modification and find these additional person-alerts may lead to 1,200 (800-1,500) or 54% more averted PM2.5-attributable premature deaths per year, if geostationary, instead of polar orbiting, satellite data alone are used to identify alert days. These health benefits have an associated economic value of 13 (8.8-17) billion dollars ($2019) per year. Our results highlight one of many potential applications of atmospheric composition data from geostationary satellites for improving public health. Identifying these applications has important implications for guiding use of current satellite data and planning future geostationary satellite missions.

All-Cause NO2-Attributable Mortality Burden and Associated Racial and Ethnic Disparities in the United States.

Nitrogen dioxide (NO2) is a regulated pollutant that is associated with numerous health impacts. Recent advances in epidemiology indicate high confidence linking NO2 exposure with increased mortality, an association that recent studies suggest persists even at concentrations below regulatory thresholds. While large disparities in NO2 exposure among population subgroups have been reported, U.S. NO2-attributable mortality rates and their disparities remain unquantified. Here we provide the first estimate of NO2-attributable all-cause mortality across the contiguous U.S. (CONUS) at the census tract-level. We leverage fine-scale, satellite-informed, land use regression model NO2 concentrations and census tract-level baseline mortality data to characterize the associated disparities among different racial/ethnic subgroups. Across CONUS, we estimate that the NO2-attributable all-cause mortality is ∼170,850 (95% confidence interval: 43,970, 251,330) premature deaths yr-1 with large variability across census tracts and within individual cities. Additionally, we find that higher NO2 concentrations and underlying susceptibilities for predominately Black communities lead to NO2-attributable mortality rates that are ∼47% higher compared to CONUS-wide average rates. Our results highlight the substantial U.S. NO2 mortality burden, particularly in marginalized communities, and motivate adoption of more stringent standards to protect public health.

State-of-the-Science Data and Methods Need to Guide Place-Based Efforts to Reduce Air Pollution Inequity.

BACKGROUND: Recently enacted environmental justice policies in the United States at the state and federal level emphasize addressing place-based inequities, including persistent disparities in air pollution exposure and associated health impacts. Advances in air quality measurement, models, and analytic methods have demonstrated the importance of finer-scale data and analysis in accurately quantifying the extent of inequity in intraurban pollution exposure, although the necessary degree of spatial resolution remains a complex and context-dependent question. OBJECTIVE: The objectives of this commentary were to a) discuss ways to maximize and evaluate the effectiveness of efforts to reduce air pollution disparities, and b) argue that environmental regulators must employ improved methods to project, measure, and track the distributional impacts of new policies at finer geographic and temporal scales. DISCUSSION: The historic federal investments from the Inflation Reduction Act, the Infrastructure Investment and Jobs Act, and the Biden Administration's commitment to Justice40 present an unprecedented opportunity to advance climate and energy policies that deliver real reductions in pollution-related health inequities. In our opinion, scientists, advocates, policymakers, and implementing agencies must work together to harness critical advances in air quality measurements, models, and analytic methods to ensure success. https://doi.org/10.1289/EHP13063.

Ethnoracial Disparities in Nitrogen Dioxide Pollution in the United States: Comparing Data Sets from Satellites, Models, and Monitors.

In the United States (U.S.), studies on nitrogen dioxide (NO2) trends and pollution-attributable health effects have historically used measurements from in situ monitors, which have limited geographical coverage and leave 66% of urban areas unmonitored. Novel tools, including remotely sensed NO2 measurements and estimates of NO2 estimates from land-use regression and photochemical models, can aid in assessing NO2 exposure gradients, leveraging their complete spatial coverage. Using these data sets, we find that Black, Hispanic, Asian, and multiracial populations experience NO2 levels 15-50% higher than the national average in 2019, whereas the non-Hispanic White population is consistently exposed to levels that are 5-15% lower than the national average. By contrast, the in situ monitoring network indicates more moderate ethnoracial NO2 disparities and different rankings of the least- to most-exposed ethnoracial population subgroup. Validating these spatially complete data sets against in situ observations reveals similar performance, indicating that all these data sets can be used to understand spatial variations in NO2. Integrating in situ monitoring, satellite data, statistical models, and photochemical models can provide a semiobservational record, complete geospatial coverage, and increasingly high spatial resolution, enhancing future efforts to characterize, map, and track exposure and inequality for highly spatially heterogeneous pollutants like NO2.

Reversal of trends in global fine particulate matter air pollution.

Ambient fine particulate matter (PM2.5) is the world's leading environmental health risk factor. Quantification is needed of regional contributions to changes in global PM2.5 exposure. Here we interpret satellite-derived PM2.5 estimates over 1998-2019 and find a reversal of previous growth in global PM2.5 air pollution, which is quantitatively attributed to contributions from 13 regions. Global population-weighted (PW) PM2.5 exposure, related to both pollution levels and population size, increased from 1998 (28.3 µg/m3) to a peak in 2011 (38.9 µg/m3) and decreased steadily afterwards (34.7 µg/m3 in 2019). Post-2011 change was related to exposure reduction in China and slowed exposure growth in other regions (especially South Asia, the Middle East and Africa). The post-2011 exposure reduction contributes to stagnation of growth in global PM2.5-attributable mortality and increasing health benefits per µg/m3 marginal reduction in exposure, implying increasing urgency and benefits of PM2.5 mitigation with aging population and cleaner air.

Unified real-time environmental-epidemiological data for multiscale modeling of the COVID-19 pandemic.

An impressive number of COVID-19 data catalogs exist. However, none are fully optimized for data science applications. Inconsistent naming and data conventions, uneven quality control, and lack of alignment between disease data and potential predictors pose barriers to robust modeling and analysis. To address this gap, we generated a unified dataset that integrates and implements quality checks of the data from numerous leading sources of COVID-19 epidemiological and environmental data. We use a globally consistent hierarchy of administrative units to facilitate analysis within and across countries. The dataset applies this unified hierarchy to align COVID-19 epidemiological data with a number of other data types relevant to understanding and predicting COVID-19 risk, including hydrometeorological data, air quality, information on COVID-19 control policies, vaccine data, and key demographic characteristics.

Inequitable Exposures to U.S. Coal Power Plant-Related PM2.5: 22 Years and Counting.

BACKGROUND: Emissions from coal power plants have decreased over recent decades due to regulations and economics affecting costs of providing electricity generated by coal vis-à-vis its alternatives. These changes have improved regional air quality, but questions remain about whether benefits have accrued equitably across population groups. OBJECTIVES: We aimed to quantify nationwide long-term changes in exposure to particulate matter (PM) with an aerodynamic diameter ≤2.5µm (PM2.5) associated with coal power plant SO2 emissions. We linked exposure reductions with three specific actions taken at individual power plants: scrubber installations, reduced operations, and retirements. We assessed how emissions changes in different locations have influenced exposure inequities, extending previous source-specific environmental justice analyses by accounting for location-specific differences in racial/ethnic population distributions. METHODS: We developed a data set of annual PM2.5 source impacts ("coal PM2.5") associated with SO2 emissions at each of 1,237 U.S. coal-fired power plants across 1999-2020. We linked population-weighted exposure with information about each coal unit's operational and emissions-control status. We calculate changes in both relative and absolute exposure differences across demographic groups. RESULTS: Nationwide population-weighted coal PM2.5 declined from 1.96µg/m3 in 1999 to 0.06 µg/m3 in 2020. Between 2007 and 2010, most of the exposure reduction is attributable to SO2 scrubber installations, and after 2010 most of the decrease is attributable to retirements. Black populations in the South and North Central United States and Native American populations in the western United States were inequitably exposed early in the study period. Although inequities decreased with falling emissions, facilities in states across the North Central United States continue to inequitably expose Black populations, and Native populations are inequitably exposed to emissions from facilities in the West. DISCUSSION: We show that air quality controls, operational adjustments, and retirements since 1999 led to reduced exposure to coal power plant related PM2.5. Reduced exposure improved equity overall, but some populations continue to be inequitably exposed to PM2.5 associated with facilities in the North Central and western United States. https://doi.org/10.1289/EHP11605.

A Source Apportionment and Emission Scenario Assessment of PM2.5- and O3-Related Health Impacts in G20 Countries.

Exposure to air pollution is a leading risk factor for premature death globally; however, the complexity of its formation and the diversity of its sources can make it difficult to address. The Group of Twenty (G20) countries are a collection of the world's largest and most influential economies and are uniquely poised to take action to reduce the global health burden associated with air pollution. We present a framework capable of simultaneously identifying regional and sectoral sources of the health impacts associated with two air pollutants, fine particulate matter (PM2.5) and ozone (O3) in G20 countries; this framework is also used to assess the health impacts associated with emission reductions. This approach combines GEOS-Chem adjoint sensitivities, satellite-derived data, and a new framework designed to better characterize the non-linear relationship between O3 exposures and nitrogen oxides emissions. From this approach, we estimate that a 50% reduction of land transportation emissions by 2040 would result in 251 thousand premature deaths avoided in G20 countries. These premature deaths would be attributable equally to reductions in PM2.5 and O3 exposure which make up 51% and 49% of the potential benefits, respectively. In our second application, we estimate that the energy generation related co-benefits associated with G20 countries staying on pace with their net-zero carbon dioxide targets would be 290 thousand premature deaths avoided in 2040; action by India (47%) would result in the most benefits of any country and a majority of these avoided deaths would be attributable to reductions in PM2.5 exposure (68%).

Trends in urban air pollution over the last two decades: A global perspective.

Ground-level ozone (O3), fine particles (PM2.5), and nitrogen dioxide (NO2) are the most harmful urban air pollutants regarding human health effects. Here, we aimed at assessing trends in concurrent exposure of global urban population to O3, PM2.5, and NO2 between 2000 and 2019. PM2.5, NO2, and O3 mean concentrations and summertime mean of the daily maximum 8-h values (O3 MDA8) were analyzed (Mann-Kendall test) using data from a global reanalysis, covering 13,160 urban areas, and a ground-based monitoring network (Tropospheric Ozone Assessment Report), collating surface O3 observations at nearly 10,000 stations worldwide. At global scale, PM2.5 exposures declined slightly from 2000 to 2019 (on average, - 0.2 % year-1), with 65 % of cities showing rising levels. Improvements were observed in the Eastern US, Europe, Southeast China, and Japan, while the Middle East, sub-Saharan Africa, and South Asia experienced increases. The annual NO2 mean concentrations increased globally at 71 % of cities (on average, +0.4 % year-1), with improvements in North America and Europe, and increases in exposures in sub-Saharan Africa, Middle East, and South Asia regions, in line with socioeconomic development. Global exposure of urban population to O3 increased (on average, +0.8 % year-1 at 89 % of stations), due to lower O3 titration by NO. The summertime O3 MDA8 rose at 74 % of cities worldwide (on average, +0.6 % year-1), while a decline was observed in North America, Northern Europe, and Southeast China, due to the reduction in precursor emissions. The highest O3 MDA8 increases (>3 % year-1) occurred in Equatorial Africa, South Korea, and India. To reach air quality standards and mitigate outdoor air pollution effects, actions are urgently needed at all governance levels. More air quality monitors should be installed in cities, particularly in Africa, for improving risk and exposure assessments, concurrently with implementation of effective emission control policies that will consider regional socioeconomic imbalances.

Global trends in ozone concentration and attributable mortality for urban, peri-urban, and rural areas between 2000 and 2019: a modelling study.

BACKGROUND: Data on long-term trends of ozone exposure and attributable mortality across urban-rural catchment areas worldwide are scarce, especially for low-income and middle-income countries. This study aims to estimate trends in ozone concentrations and attributable mortality for urban-rural catchment areas worldwide. METHODS: In this modelling study, we used a health impact function to estimate ozone concentrations and ozone-attributable chronic respiratory disease mortality for urban areas worldwide, and their surrounding peri-urban, peri-rural, and rural areas. We estimated ozone-attributable respiratory health outcomes using a modified Global Burden of Diseases, Injuries, and Risk Factors 2019 Study approach. We evaluate long-term trends with linear regressions of annual ozone concentrations and ozone-attributable mortality against time in years, and examined the influence of each health impact function input parameter to temporal changes in ozone-attributable disease burden estimates for 12 946 cities worldwide by region, from 2000 to 2019. FINDINGS: Ozone-attributable mortality worldwide increased by 46% from 2000 (290 400 deaths [95% CI 151 800-457 600]) to 2019 (423 100 deaths [95% CI 223 200-659 400]). The fraction of global ozone-attributable mortality occurring in peri-urban areas remained unchanged from 2000 to 2019 (56%), whereas urban areas gained in their share of global ozone-attributable burden (from 35% to 37%; 54 000 more deaths). Across all cities studied, average population-weighted mean ozone concentration increased by 11% (46 parts per billion [ppb] to 51 ppb). The number of cities with concentrations above the WHO peak season ozone standard (60 µg/m3) increased from 11 568 (89%) of 12 946 cities in 2000 to 12 433 (96%) cities in 2019. Percent change in ozone-attributable mortality averaged across 11 032 cities within each region from 2000 to 2019 ranged from -62% in eastern Europe to 350% in tropical Latin America. The contribution of ozone concentrations, population size, and baseline chronic respiratory disease rates to the change in ozone-attributable mortality differed regionally. INTERPRETATION: Ozone exposure is increasing worldwide, contributing to disproportionate ozone mortality in peri-urban areas and increasing ozone exposure and attributable mortality in urban areas worldwide. Reducing ozone precursor emissions in areas affecting urban and peri-urban exposure can yield substantial public health benefits. FUNDING: NASA Health and Air Quality Applied Sciences Team, the National Institute for Occupational Safety and Health, and the NOAA Co-operative Agreement with the Cooperative Institute for Research in Environmental Sciences.

Disparities in Air Pollutants Across Racial, Ethnic, and Poverty Groups at US Public Schools.

We investigate socioeconomic disparities in air quality at public schools in the contiguous US using high resolution estimates of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) concentrations. We find that schools with higher proportions of people of color (POC) and students eligible for the federal free or reduced lunch program, a proxy for poverty level, are associated with higher pollutant concentrations. For example, we find that the median annual NO2 concentration for White students, nationally, was 7.7 ppbv, compared to 9.2 ppbv for Black and African American students. Statewide and regional disparities in pollutant concentrations across racial, ethnic, and poverty groups are consistent with nationwide results, where elevated NO2 concentrations were associated with schools with higher proportions of POC and higher levels of poverty. Similar, though smaller, differences were found in PM2.5 across racial and ethnic groups in most states. Racial, ethnic, and economic segregation across the rural-urban divide is likely an important factor in pollution disparities at US public schools. We identify distinct regional patterns of disparities, highlighting differences between California, New York, and Florida. Finally, we highlight that disparities exist not only across urban and non-urban lines but also within urban environments.

Sources of ambient PM2.5 exposure in 96 global cities.

To improve air quality, knowledge of the sources and locations of air pollutant emissions is critical. However, for many global cities, no previous estimates exist of how much exposure to fine particulate matter (PM2.5), the largest environmental cause of mortality, is caused by emissions within the city vs. outside its boundaries. We use the Intervention Model for Air Pollution (InMAP) global-through-urban reduced complexity air quality model with a high-resolution, global inventory of pollutant emissions to quantify the contribution of emissions by source type and location for 96 global cities. Among these cities, we find that the fraction of PM2.5 exposure caused by within-city emissions varies widely (µ = 37%; σ = 22%) and is not well-explained by surrounding population density. The list of most-important sources also varies by city. Compared to a more mechanistically detailed model, InMAP predicts urban measured concentrations with lower bias and error but also lower correlation. Predictive accuracy in urban areas is not particularly high with either model, suggesting an opportunity for improving global urban air emission inventories. We expect the results herein can be useful as a screening tool for policy options and, in the absence of available resources for further analysis, to inform policy action to improve public health.

Global Health Impacts for Economic Models of Climate Change: A Systematic Review and Meta-Analysis.

Rationale: Avoiding excess health damages attributable to climate change is a primary motivator for policy interventions to reduce greenhouse gas emissions. However, the health benefits of climate mitigation, as included in the policy assessment process, have been estimated without much input from health experts. Objectives: In accordance with recommendations from the National Academies in a 2017 report on approaches to update the social cost of greenhouse gases (SC-GHG), an expert panel of 26 health researchers and climate economists gathered for a virtual technical workshop in May 2021 to conduct a systematic review and meta-analysis and recommend improvements to the estimation of health impacts in economic-climate models. Methods: Regionally resolved effect estimates of unit increases in temperature on net all-cause mortality risk were generated through random-effects pooling of studies identified through a systematic review. Results: Effect estimates and associated uncertainties varied by global region, but net increases in mortality risk associated with increased average annual temperatures (ranging from 0.1% to 1.1% per 1°C) were estimated for all global regions. Key recommendations for the development and utilization of health damage modules were provided by the expert panel and included the following: not relying on individual methodologies in estimating health damages; incorporating a broader range of cause-specific mortality impacts; improving the climate parameters available in economic models; accounting for socioeconomic trajectories and adaptation factors when estimating health damages; and carefully considering how air pollution impacts should be incorporated in economic-climate models. Conclusions: This work provides an example of how subject-matter experts can work alongside climate economists in making continued improvements to SC-GHG estimates.

Long-term trends in urban NO2 concentrations and associated paediatric asthma incidence: estimates from global datasets.

BACKGROUND: Combustion-related nitrogen dioxide (NO2) air pollution is associated with paediatric asthma incidence. We aimed to estimate global surface NO2 concentrations consistent with the Global Burden of Disease study for 1990-2019 at a 1 km resolution, and the concentrations and attributable paediatric asthma incidence trends in 13 189 cities from 2000 to 2019. METHODS: We scaled an existing annual average NO2 concentration dataset for 2010-12 from a land use regression model (based on 5220 NO2 monitors in 58 countries and land use variables) to other years using NO2 column densities from satellite and reanalysis datasets. We applied these concentrations in an epidemiologically derived concentration-response function with population and baseline asthma rates to estimate NO2-attributable paediatric asthma incidence. FINDINGS: We estimated that 1·85 million (95% uncertainty interval [UI] 0·93-2·80 million) new paediatric asthma cases were attributable to NO2 globally in 2019, two thirds of which occurred in urban areas (1·22 million cases; 95% UI 0·60-1·8 million). The proportion of paediatric asthma incidence that is attributable to NO2 in urban areas declined from 19·8% (1·22 million attributable cases of 6·14 million total cases) in 2000 to 16·0% (1·24 million attributable cases of 7·73 million total cases) in 2019. Urban attributable fractions dropped in high-income countries (-41%), Latin America and the Caribbean (-16%), central Europe, eastern Europe, and central Asia (-13%), and southeast Asia, east Asia, and Oceania (-6%), and rose in south Asia (+23%), sub-Saharan Africa (+11%), and north Africa and the Middle East (+5%). The contribution of NO2 concentrations, paediatric population size, and asthma incidence rates to the change in NO2-attributable paediatric asthma incidence differed regionally. INTERPRETATION: Despite improvements in some regions, combustion-related NO2 pollution continues to be an important contributor to paediatric asthma incidence globally, particularly in cities. Mitigating air pollution should be a crucial element of public health strategies for children. FUNDING: Health Effects Institute, NASA.