Faculty Bibliography

Air quality management is increasingly focused not only on across-the-board reductions in ambient pollution concentrations but also on identifying and remediating elevated exposures that often occur in traditionally disadvantaged communities. Remote sensing of ambient air pollution using data derived from satellites has the potential to better inform management decisions that address environmental disparities by providing increased spatial coverage, at high-spatial resolutions, compared to air pollution exposure estimates based on ground-based monitors alone. Daily PM2.5 estimates for 2015"“2018 were estimated at a 1 km2 resolution, derived from NASA"™s Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument and the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm in order to assess the utility of highly refined spatiotemporal air pollution data in 92 California cities and in the 13 communities included in the California Community Air Protection Program. The identification of pollution hot-spots within a city is typically not possible relying solely on the regulatory monitoring networks; however, day-to-day temporal variability was shown to be generally well represented by nearby ground-based monitoring data even in communities with strong spatial gradients in pollutant concentrations. An assessment of within-ZIP Code variability in pollution estimates indicates that high-resolution pollution estimates (i.e., 1 km2) are not always needed to identify spatial differences in exposure but become increasingly important for larger geographic areas (approximately 50 km2). Taken together, these findings can help inform strategies for use of remote sensing data for air quality management including the screening of locations with air pollution exposures that are not well represented by existing ground-based air pollution monitors.

Air pollution poses a serious threat to children's respiratory health around the world. Satellite remote-sensing technology and air quality models can provide pollution data on a global scale, necessary for risk communication efforts in regions without ground-based monitoring networks. Several large centers, including NASA, produce global pollution forecasts that may be used alongside air quality indices to communicate local, daily risk information to the public. Here we present a health-based, globally applicable air quality index developed specifically to reflect the respiratory health risks among children exposed to elevated outdoor air pollution. Additive, excess-risk air quality indices were developed using 51 different coefficients derived from time-series health studies evaluating the impacts of ambient fine particulate matter, nitrogen dioxide, and ozone on children's respiratory morbidity outcomes. A total of four indices were created which varied based on whether or not the underlying studies controlled for co-pollutants and in the adjustment of excess risks of individual pollutants. Combined with historical estimates of air pollution provided globally at a 25 × 25 km² spatial resolution from the NASA's Goddard Earth Observing System composition forecast (GEOS-CF) model, each of these indices were examined in a global sample of 664 small and 140 large cities for study year 2017. Adjusted indices presented the most normal distributions of locally-scaled index values, which has been shown to improve associations with health risks, while indices based on coefficients controlling for co-pollutants had little effect on index performance. We provide the steps and resources need to apply our final adjusted index at the local level using freely-available forecasting data from the GEOS-CF model, which can provide risk communication information for cities around the world to better inform individual behavior modification to best protect children's respiratory health.

The combination of air quality (AQ) data from satellites and low-cost sensor systems, along with output from AQ models, have the potential to augment high-quality, regulatory-grade data in countries with in situ monitoring networks and provide much needed AQ information in countries without them, including Low and Moderate Income Countries (LMICs). We demonstrate the potential of free and publicly available USA National Aeronautics and Space Administration (NASA) resources, which include capacity building activities, satellite data, and global AQ forecasts, to provide cost-effective, and reliable AQ information to health and AQ professionals around the world. We provide illustrative case studies that highlight how global AQ forecasts along with satellite data may be used to characterize AQ on urban to regional scales, including to quantify pollution concentrations, identify pollution sources, and track the long-range transport of pollution. We also provide recommendations to data product developers to facilitate and broaden usage of NASA resources by health and AQ stakeholders.

Poor air quality affects the health and wellbeing of large populations around the globe. Although source controls are the most effective approaches for improving air quality and reducing health risks, individuals can also take actions to reduce their personal exposure by staying indoors, reducing physical activity, altering modes of transportation, filtering indoor air, and using respirators and other types of face masks. A synthesis of available evidence on the efficacy, effectiveness, and potential adverse effects or unintended consequences of personal interventions for air pollution is needed by clinicians to assist patients and the public in making informed decisions about use of these interventions. To address this need, the American Thoracic Society convened a workshop in May of 2018 to bring together a multidisciplinary group of international experts to review the current state of knowledge about personal interventions for air pollution and important considerations when helping patients and the general public to make decisions about how best to protect themselves. From these discussions, recommendations were made regarding when, where, how, and for whom to consider personal interventions. In addition to the efficacy and safety of the various interventions, the committee considered evidence regarding the identification of patients at greatest risk, the reliability of air quality indices, the communication challenges, and the ethical and equity considerations that arise when discussing personal interventions to reduce exposure and risk from outdoor air pollution.

The health impacts of climate change are substantial and represent a primary motivating factor to mitigate climate change. However, the health impacts in economic models that estimate the social cost of carbon dioxide (SC-CO₂) have generally been made in isolation from health experts and have never been rigorously evaluated. Version 3.10 of the Framework for Uncertainty, Negotiation and Distribution (FUND) model was used to estimate the health-based portion of current SC-CO₂ estimates across low-, middle-, and high-income regions. In addition to the base model, three additional experiments assessed the sensitivity of these estimates to changes in the socio-economic assumptions in the model. Economic impacts from adverse health outcomes represent ∼8.7% of current SC-CO₂ estimates. The majority of these health impacts (74%) were attributable to diarrhea mortality (from both low- and high-income regions) followed by diarrhea morbidity (12%) and malaria mortality (11%); no other health impact makes a meaningful contribution to SC-CO₂ estimates in current economic models. The results of the socio-economic experiments show that the health-based portion of SC-CO₂ estimates are highly sensitive to assumptions regarding income elasticity of health effects, income growth, and use of equity weights. Improving the health-based portion of SC-CO₂ estimates could have substantial impacts on magnitude of the SC-CO₂. Incorporating additional health impacts not previously included in estimates of SC-CO₂ will be a critical component of model updates. This effort will be most successful through coordination between economists and health researchers and should focus on updating the form and function of concentration-response functions.

Wildland fires are diminishing air quality on a seasonal and regional basis, raising concerns about respiratory health risks to the public and occupational groups. This American Thoracic Society (ATS) workshop was convened in 2019 to meet the growing health threat of wildland fire smoke. The workshop brought together a multi-disciplinary group of 19 experts, including wildland fire managers, public health officials, epidemiologists, toxicologists, and pediatric and adult pulmonologists. The workshop examined four major topics: (1) the science of wildland fire incidence and fire management, (2) the respiratory and cardiovascular health effects of wildland fire smoke exposure, (3) communication strategies to address these health risks, and (4) actions to address wildland fire health impacts. Through formal presentations followed by group discussion, workshop participants identified top priorities for fire management, research, communication and public policy to address health risks of wildland fires. The workshop concluded that short-term exposure to wildland smoke causes acute respiratory health effects, especially among those with asthma and chronic obstructive pulmonary disease (COPD). Research is needed to understand long-term health effects of repeated smoke exposures across fire seasons for children, adults and highly exposed occupational groups (especially firefighters). Other research priorities include fire data collection and modeling, toxicology of different fire fuel sources, and the efficacy of health protective measures to prevent respiratory effects of smoke exposure. The workshop committee recommends a unified Federal response to the growing problem of wildland fires, including investment in fire behavior and smoke air quality modeling, research on the health impacts of smoke, and the development of robust clinical and public health communication tools.

Health risks from air pollution continue to be a major concern for residents in Mexico City. These health burdens could be partially alleviated through individual avoidance behavior if accurate information regarding the daily health risks of multiple pollutants became available. A split sample approach was used in this study to create and validate a multi-pollutant, health-based air quality index. Poisson generalized linear models were used to assess the impacts of ambient air pollution (i.e., fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ground-level ozone (O3) on a total of 610,982 daily emergency department (ED) visits for respiratory disease obtained from 40 facilities in the metropolitan area of Mexico City from 2010 to 2015. Increased risk of respiratory ED visits was observed for interquartile increases in the 4-day average concentrations of PM2.5 (Risk Ratio (RR) 1.03, 95% CI 1.01-1.04), O3 (RR 1.03, 95% CI 1.01-1.05), and to a lesser extent NO2 (RR 1.01, 95% CI 0.99"“1.02). An additive, multi-pollutant index was created using coefficients for these three pollutants. Positive associations of index values with daily respiratory ED visits was observed among children (ages 2"“17) and adults (ages 18+). The use of previously unavailable daily health records enabled an assessment of short-term ambient air pollution concentrations on respiratory morbidity in Mexico City and the creation of a health-based air quality index, which is now currently in use in Mexico City.

BACKGROUND:Ambient air pollution is a modifiable risk factor for cardiovascular disease, yet uncertainty remains about the size of risks at lower levels of fine particulate matter (PM2.5) exposure which now occur in the USA and elsewhere. METHODS:We investigated the relationship of ambient PM2.5 exposure with cause-specific cardiovascular disease mortality in 565 477 men and women, aged 50 to 71 years, from the National Institutes of Health-AARP Diet and Health Study. During 7.5 x 106 person-years of follow up, 41 286 cardiovascular disease deaths, including 23 328 ischaemic heart disease (IHD) and 5894 stroke deaths, were ascertained using the National Death Index. PM2.5 was estimated using a hybrid land use regression (LUR) geostatistical model. Multivariate Cox regression models were used to estimate relative risks (RRs) and 95% confidence intervals (CI). RESULTS:Each increase of 10  μg/m3 PM2.5 (overall range, 2.9-28.0  μg/m3) was associated, in fully adjusted models, with a 16% increase in mortality from ischaemic heart disease [hazard ratio (HR) 1.16; 95% CI 1.09-1.22] and a 14% increase in mortality from stroke (HR 1.14; CI 1.02-1.27). Compared with PM2.5 exposure <8  μg/m3 (referent), risks for CVD were increased in relation to PM2.5 exposures in the range of 8-12  μg/m3 (CVD: HR 1.04; 95% CI 1.00-1.08), in the range 12-20  μg/m3 (CVD: HR 1.08; 95% CI 1.03-1.13) and in the range 20+ μg/m3 (CVD: HR 1.19; 95% CI 1.10-1.28). Results were robust to alternative approaches to PM2.5 exposure assessment and statistical analysis. CONCLUSIONS:Long-term exposure to fine particulate air pollution is associated with ischaemic heart disease and stroke mortality, with excess risks occurring in the range of and below the present US long-term standard for ambient exposure to PM2.5 (12  µg/m3), indicating the need for continued improvements in air pollution abatement for CVD prevention.

BACKGROUND:The Air Quality Index (AQI) in the United States is widely used to communicate daily air quality information to the public. While use of the AQI has led to reported changes in individual behaviors, such behavior modifications will only mitigate adverse health effects if AQI values are indicative of public health risks. Few studies have assessed the capability of the AQI to accurately predict respiratory morbidity risks. METHODS AND FINDINGS/RESULTS:In three major regions of California, Poisson generalized linear models were used to assess seasonal associations between 1,373,165 respiratory emergency department visits and short-term exposure to multiple metrics between 2012-2014, including: daily concentrations of NO2, O3, and PM2.5; the daily reported AQI; and a newly constructed health-based air quality index. AQI values were positively associated (average risk ratio = 1.03, 95% CI 1.02-1.04) during the cooler months of the year (November-February) in all three regions when the AQI was very highly correlated with PM2.5 (R2 ≥ 0.89). During the warm season (March-October) in the San Joaquin Valley region, neither AQI values nor the individual underlying air pollutants were associated with respiratory morbidity. Additionally, AQI values were not positively associated with respiratory morbidity in the Southern California region during the warm season, despite strong associations of the individual underlying air pollutants with respiratory morbidity; in contrast, health-based index values were observed to be significantly associated with respiratory morbidity as part of an applied policy analysis in this region, with a combined risk ratio of 1.02 (95% CI: 1.01-1.03). CONCLUSIONS:In regions where individual air pollutants are associated with respiratory morbidity, and during seasons with relatively simple air mixtures, the AQI can effectively serve as a risk communication tool for respiratory health risks. However, the predictive ability of the AQI and any other index is contingent upon the monitored values being representative of actual population exposures. Other approaches, such as health-based indices, may be needed in order to effectively communicate health risks of air pollution in regions and seasons with more complex air mixtures.

Air quality data from satellites and low-cost sensor systems, together with output from air quality models, have the potential to augment high-quality, regulatory-grade data in countries with in situ monitoring networks and provide much-needed air quality information in countries without them. Each of these technologies has strengths and limitations that need to be considered when integrating them to develop a robust and diverse global air quality monitoring network. To address these issues, the American Thoracic Society, the U.S. Environmental Protection Agency, the National Aeronautics and Space Administration, and the National Institute of Environmental Health Sciences convened a workshop in May 2017 to bring together global experts from across multiple disciplines and agencies to discuss current and near-term capabilities to monitor global air pollution. The participants focused on four topics: 1) current and near-term capabilities in air pollution monitoring, 2) data assimilation from multiple technology platforms, 3) critical issues for air pollution monitoring in regions without a regulatory-quality stationary monitoring network, and 4) risk communication and health messaging. Recommendations for research and improved use were identified during the workshop, including a recognition that the integration of data across monitoring technology groups is critical to maximizing the effectiveness (e.g., data accuracy, as well as spatial and temporal coverage) of these monitoring technologies. Taken together, these recommendations will advance the development of a global air quality monitoring network that takes advantage of emerging technologies to ensure the availability of free, accessible, and reliable air pollution data and forecasts to health professionals, as well as to all global citizens.