The importance of population susceptibility for air pollution risk assessment: a case study of power plants near Washington, DC

Intra-Continental Transport of Western Wildfire Smoke Heightens Health Risks Across North America

Wildfires in North America, particularly in western states, have caused widespread environmental, economic, social, and health impacts. Smoke from these fires travels long distances, spreading pollutants and worsening the air quality across continents. Vulnerable groups, such as children, the elderly, and those with preexisting conditions, face heightened health risks, as do firefighters working in extreme conditions. Wildfire firefighters are of particular concern as they are fighting fires in extreme conditions with minimal protective equipment. This study examined wildfire smoke during July-August 2021, when intense fires in Canada and the western U.S. led to cross-continental smoke transport and caused significant impacts on the air quality across North America. Using the GEOS-Chem model, we simulated the transport and distribution of PM2.5 (particulate matter with a diameter of 2.5 μm or smaller), identifying significant carcinogenic risks for adults, children, and firefighters using dosimetry risk methodologies established by the U.S. EPA. Significant carcinogenic risks for adult, child, and firefighter populations due to exposure to PM2.5 were identified over the two-month period of evaluation. The findings emphasize the need for future studies to assess the toxic chemical mixtures in wildfire smoke and consider the risks to underrepresented communities.

How should climate actions be planned? Model lessons from published action plans

To effectively protect against the increasingly pervasive effects of climate change, countries and cities around the world are tasked with formulating and implementing climate actions that effectively respond to the challenges ahead. However, choosing the optimal climate actions is complex, since it is necessary to consider many external impacts as early on as the planning phase. Our novel methodology uncovers and integrates into first-of-its-kind decision support framework the identified climate actions of 443 European cities (from 32 countries) and the city structure-related features that influence the basic success of strategy creation into a first-of-its-kind decision support framework. Depending on their budget, population density, development and energy consumption portfolio, the results highlight that the analyzed European cities need to adopt a different way of thinking. The research results lay the foundation for the decision support of evidence-based climate action planning and contribute towards strengthening the role of cities worldwide in the fight against climate change in the future.

Long-Term Exposure to Ambient Fine Particulate Matter and Incidence of Major Cardiovascular Diseases: A Prospective Study of 0.5 Million Adults in China

Few cohort studies explored the long-term effects of ambient fine particulate matter (PM_2.5) on incidence of cardiovascular diseases (CVDs), especially in countries with higher levels of air pollution. We aimed to evaluate the association between long-term exposure to PM_2.5 and incidence of CVD in China. We performed a prospective cohort study in ten regions that recruited 512,689 adults during 2004-2008, with follow-up until 2017. Annual PM_2.5 concentrations were estimated using a satellite-based model with national coverage and 1 x 1 km spatial resolution. Time-varying Cox proportional hazard regression models were used to estimate hazard ratios (HRs) for all-cause and cause-specific CVDs associated with PM_2.5, adjusting for conventional covariates. During 5.08 million person-years of follow-up, 148,030 incident cases of CVD were identified. Long-term exposure to PM_2.5 showed positive and linear association with incidence of CVD, without a threshold below any concentration. The adjusted HRs per 10 μg/m³ increase in PM_2.5 was 1.04 (95%CI: 1.02, 1.07) for total CVD. The risk estimates differed between certain population subgroups, with greater HRs in men, in household with higher income, and in people using unclean heating fuels. This prospective study of large Chinese population provided essential epidemiological evidence for CVD incident risk associated with PM_2.5.

Evidence of susceptibility to autism risks associated with early life ambient air pollution: A systematic review

BACKGROUND

Many studies have found associations between early life air pollution exposure and subsequent onset of autism spectrum disorder (ASD). However, characteristics that affect susceptibility remain unclear.

OBJECTIVE

This systematic review examined epidemiologic studies on the modifying roles of social, child, genetic and maternal characteristics in associations between prenatal and early postnatal air pollution exposure and ASD.

METHODS

A systematic literature search in PubMed and Embase was conducted. Studies that examined modifiers of the association between air pollution and ASD were included.

RESULTS

A total of 19 publications examined modifiers of the associations between early life air pollution exposures and ASD. In general, estimates of effects on risk of ASD in boys were larger than in girls (based on 11 studies). Results from studies of effects of family education (2 studies) and neighborhood deprivation (2 studies) on air pollution-ASD associations were inconsistent. Limited data (1 study) suggest pregnant women with insufficient folic acid intake might be more susceptible to ambient particulate matter less than 2.5 μm (PM2.5) and 10 μm (PM10) in aerodynamic diameter, and to nitrogen dioxide (NO2). Children of mothers with gestational diabetes had increased risk of ozone-associated ASD (1 study). Two genetic studies reported that copy number variations may amplify the effect of ozone, and MET rs1858830 CC genotype may augment effects of PM and near-roadway pollutants on ASD.

CONCLUSIONS

Child's sex, maternal nutrition or diabetes, socioeconomic factors, and child risk genotypes were reported to modify the effect of early-life air pollutants on ASD risk in the epidemiologic literature. However, the sparsity of studies on comparable modifying hypotheses precludes conclusive findings. Further research is needed to identify susceptible populations and potential targets for preventive intervention.

A review on the role of dispersion and receptor models in asthma research

There is substantial evidence that air pollution exposure is associated with asthma prevalence that affects millions of people worldwide. Air pollutant exposure can be determined using dispersion models and refined with receptor models. Dispersion models offer the advantage of giving spatially distributed outdoor pollutants concentration while the receptor models offer the source apportionment of specific chemical species. However, the use of dispersion and/or receptor models in asthma research requires a multidisciplinary approach, involving experts on air quality and respiratory diseases. Here, we provide a literature review on the role of dispersion and receptor models in air pollution and asthma research, their limitations, gaps and the way forward. We found that the methodologies used to incorporate atmospheric dispersion and receptor models in human health studies may vary considerably, and several of the studies overlook features such as indoor air pollution, model validation and subject pathway between indoor spaces. Studies also show contrasting results of relative risk or odds ratio for a health outcome, even using similar methodologies. Dispersion models are mostly used to estimate air pollution levels outside the subject's home, school or workplace; however, very few studies addressed the subject's routines or indoor/outdoor relationships. Conversely, receptor models are employed in regions where asthma incidence/prevalence is high or where a dispersion model has been previously used for this assessment. Road traffic (vehicle exhaust) and NOx are found to be the most targeted source and pollutant, respectively. Other key findings were the absence of a standard indicator, shortage of studies addressing VOC and UFP, and the shift toward chemical speciation of exposure.

Do acute changes in ambient air pollution increase the risk of potentially fatal cardiac arrhythmias in patients with implantable cardioverter defibrillators?

BACKGROUND

Daily changes in ambient air pollution have been associated with cardiac morbidity and mortality. Precipitating a cardiac arrhythmia in susceptible individuals may be one mechanism. We investigated the influence of daily changes in air pollution in the Province of Ontario, Canada on the frequency of discharges from implantable cardio defibrillators (ICDs) which occur in response to potentially life threatening arrhythmias.

METHODS

Using a case- crossover design, we compared ambient air pollution concentrations on the day of an ICD discharge to other days in the same month and year in 1952 patients. We adjusted for weather, lagged the exposure data from 0 to 3 days, and stratified the results by several patient-related characteristics.

RESULTS

Median (interquartile range) for ozone (O₃), fine particulate matter (PM_2.5), sulphur dioxide (SO₂) and nitrogen dioxide (NO₂) were 26.0 ppb (19.4, 33.0), 6.6 μg/m³ (4.3, 10.6), 1.00 ppb (0.4,2.1), 10.0 ppb (6.0,15.3) respectively. Unlagged odds ratios (95%) for an ICD discharge associated with an interquartile range increase in pollutant were 0.97 (0.86, 1.09) for O₃, 0.99 (0.92, 1.06) for PM_2.5, 0.97 (0.91, 1.03) for SO₂, and 1.00 (0.89, 1.12) for NO₂.

CONCLUSION

We found no evidence that the concentrations of ambient air pollution observed in our study were a risk factor for potentially fatal cardiac arrhythmias in patients with ICDs.

Health and Environmental Justice Implications of Retiring Two Coal-Fired Power Plants in the Southern Front Range Region of Colorado

Despite improvements in air quality over the past 50 years, ambient air pollution remains an important public health issue in the United States. In particular, emissions from coal-fired power plants still have a substantial impact on both nearby and regional populations. Of particular concern is the potential for this impact to fall disproportionately on low-income communities and communities of color. We conducted a quantitative health impact assessment to estimate the health benefits of the proposed decommissioning of two coal-fired electricity generating stations in the Southern Front Range region of Colorado. We estimated changes in exposures to fine particulate matter and ozone using the Community Multiscale Air Quality model and predicted avoided health impacts and related economic values. We also quantitatively assessed the distribution of these benefits by population-level socioeconomic status. Across the study area, decommissioning the power plants would result in 2 (95% CI: 1-3) avoided premature deaths each year due to reduced PM2.5 exposures and greater reductions in hospitalizations and other morbidities. Health benefits resulting from the modeled shutdowns were greatest in areas with lower educational attainment and other economic indicators. Our results suggest that decommissioning these power plants and replacing them with zero-emissions sources could have broad public health benefits for residents of Colorado, with larger benefits for those that are socially disadvantaged. Our results also suggested that researchers and decision makers need to consider the unique demographics of their study areas to ensure that important opportunities to reduce health disparities associated with point-source pollution.

Health benefits and control costs of tightening particulate matter emissions standards for coal power plants - The case of Northeast Brazil

Exposure to ambient particulate matter (PM) caused an estimated 4.2 million deaths worldwide in 2015. However, PM emission standards for power plants vary widely. To explore if the current levels of these standards are sufficiently stringent in a simple cost-benefit framework, we compared the health benefits (avoided monetized health costs) with the control costs of tightening PM emission standards for coal-fired power plants in Northeast (NE) Brazil, where ambient PM concentrations are below World Health Organization (WHO) guidelines. We considered three Brazilian PM₁₀ (PM_x refers to PM with a diameter under x micrometers) emission standards and a stricter U.S. EPA standard for recent power plants. Our integrated methodology simulates hourly electricity grid dispatch from utility-scale power plants, disperses the resulting PM_2.5, and estimates selected human health impacts from PM_2.5 exposure using the latest integrated exposure-response model. Since the emissions inventories required to model secondary PM are not available in our study area, we modeled only primary PM so our benefit estimates are conservative. We found that tightening existing PM₁₀ emission standards yields health benefits that are over 60 times greater than emissions control costs in all the scenarios we considered. The monetary value of avoided hospital admissions alone is at least four times as large as the corresponding control costs. These results provide strong arguments for considering tightening PM emission standards for coal-fired power plants worldwide, including in regions that meet WHO guidelines and in developing countries.

The estimated change in the level and distribution of PM2.5-attributable health impacts in the United States: 2005-2014

BACKGROUND

Photochemical modeling can predict the level and distribution of pollutant concentrations over time, but is resource-intensive. Partly for this reason, there are few studies exploring the multi-year trajectory of the historical change in fine particle (PM_2.5) levels and associated health impacts in the U.S.

OBJECTIVES

We used a unique dataset of Community Multi-Scale Air Quality (CMAQ) model simulations performed for a subset of years over a decade-long period fused with observations to estimate the change in ambient levels of PM_2.5 across the contiguous U.S. We also quantified the change in PM_2.5-attributable health risks and characterized the level of risk inequality over this period.

METHODS

We estimated annual mean PM_2.5 concentrations in 2005, 2011 and 2014. Using log-linear and logistic concentration-response coefficients we estimated changes in the numbers of deaths, hospital admissions and other morbidity outcomes. Calculating the Gini coefficient and Atkinson Index, we characterized the extent to which PM_2.5 attributable risks were shared equally across the population or instead concentrated among certain subgroups.

RESULTS

In 2005 the estimated fraction of deaths due to PM_2.5 was 6.1%. This estimated value falls to 4.6% by 2014. Every portion of the contiguous U.S. experiences a decline in the risk of PM-related premature death over the 10-year period. As measured by the Gini coefficient and Atkinson index, the level of PM mortality risk is shared more equally in 2014 than in 2005 among all subgroups.

CONCLUSIONS

Between 2005 and 2014, the level of PM_2.5 concentrations fall, and the risk of premature death, declined and became more equitably distributed across the U.S.

Differential Susceptibility in Ambient Particle-Related Risk of First-Ever Stroke: Findings From a National Case-Crossover Study

Different populations may respond differently to exposure to ambient fine particulate matter, defined as particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5); however, less is known about the distribution of susceptible individuals among the entire population. We conducted a time-stratified case-crossover study to assess associations between stroke risk and exposure to PM2.5. During 2013-2015, 1,356 first-ever stroke events were derived from a large representative sample, the China National Stroke Screening Survey (CNSSS) database. Daily PM2.5 average exposures with a spatial resolution of 0.1° were estimated using a data assimilation approach combining satellite measurements, air model simulations, and monitoring values. The distribution of susceptibility was derived according to individual-specific associations with PM2.5 modified by different combinations of individual-level characteristics and their joint frequencies among all of the CNSSS participants (n = 1,292,010). We found that first-ever stroke was statistically significantly associated with PM2.5 (per 10-μg/m3 increment of exposure, odds ratio = 1.049, 95% confidence interval (CI): 1.038, 1.061). This association was modified by demographic (e.g., sex), lifestyle (e.g., overweight/obesity), and medical history (e.g., diabetes) variables. The combined association with PM2.5 varied from 0.966 (95% CI: 0.920, 1.013) to 1.145 (95% CI: 1.080, 1.215) per 10-μg/m3 increment in different subpopulations. We found that most of the CNSSS participants were at increased risk of PM2.5-related stroke, while only a small proportion were highly susceptible.

Estimated Changes in Life Expectancy and Adult Mortality Resulting from Declining PM2.5 Exposures in the Contiguous United States: 1980-2010

BACKGROUND

PM2.5 precursor emissions have declined over the course of several decades, following the implementation of local, state, and federal air quality policies. Estimating the corresponding change in population exposure and PM2.5-attributable risk of death prior to the year 2000 is made difficult by the lack of PM2.5 monitoring data.

OBJECTIVES

We used a new technique to estimate historical PM2.5 concentrations, and estimated the effects of changes in PM2.5 population exposures on mortality in adults (age ≥30y), and on life expectancy at birth, in the contiguous United States during 1980-2010.

METHODS

We estimated annual mean county-level PM2.5 concentrations in 1980, 1990, 2000, and 2010 using universal kriging incorporating geographic variables. County-level death rates and national life tables for each year were obtained from the U.S. Census and Centers for Disease Control and Prevention. We used log-linear and nonlinear concentration-response coefficients from previous studies to estimate changes in the numbers of deaths and in life years and life expectancy at birth, attributable to changes in PM2.5.

RESULTS

Between 1980 and 2010, population-weighted PM2.5 exposures fell by about half, and the estimated number of excess deaths declined by about a third. The States of California, Virginia, New Jersey, and Georgia had some of the largest estimated reductions in PM2.5-attributable deaths. Relative to a counterfactual population with exposures held constant at 1980 levels, we estimated that people born in 2050 would experience an ∼1-y increase in life expectancy at birth, and that there would be a cumulative gain of 4.4 million life years among adults ≥30y of age.

CONCLUSIONS

Our estimates suggest that declines in PM2.5 exposures between 1980 and 2010 have benefitted public health. https://doi.org/10.1289/EHP507.

Does Mental Health Status Influence Susceptibility to the Physiologic Effects of Air Pollution? A Population Based Study of Canadian Children

Background

Both air pollution exposure and the presence of mental illness are associated with an increased risk of physical illness.

Objective

To determine whether or not children with less favourable mental health are more susceptible to pulmonary and cardiovascular effects of ambient air pollution, compared to those who are mentally healthy.

Methods

We carried out a cross-sectional study of 1,883 children between the ages of 6 and 17 years of age who participated in the Canadian Health Measures population survey between 2007 and 2009. Subjects were assigned the air pollution values obtained from the National Air Pollution monitor closest to their neighborhood. Lung function, heart rate and blood pressure were stratified by indicators of mental health. The latter were ascertained by questions about feelings of happiness, a diagnosed mood disorder, and the emotional symptom subscale of the Strengths and Difficulties Questionnaire.

Results

Among those who reported a mood disorder, an interquartile increase in ozone was associated with increases in systolic and diastolic pressures of 3.8 mmHg (95% CI 1.6, 5.9) and 3.0mmHg (95%CI 0.9, 5.2) respectively, and a decreases in FVC of 7.6% (95% CI 2.9, 12.3). No significant changes in these variables were observed in those who did not report a mood disorder. Among those with unfavourable emotional symptoms, ozone was associated with a 6.4% (95% CI 1.7, 11.3) increase in heart rate, a 4.1% (95%CI 1.2, 7.1) increase in systolic blood pressure, and a 6.0% (95% CI 1.4, 10.6) decrease in FEV_l. No significant effect was seen in these variables among those with no emotional symptoms.

Conclusions

In the Canadian population, children who report mood disorders or unfavourable emotional symptoms appear to be more vulnerable to the adverse physiologic effects of air pollution.

Environmental Justice Aspects of Exposure to PM2.5 Emissions from Electric Vehicle Use in China

Plug-in electric vehicles (EVs) in China aim to improve sustainability and reduce environmental health impacts of transport emissions. Urban use of EVs rather than conventional vehicles shifts transportation's air pollutant emissions from urban areas (tailpipes) to predominantly rural areas (power plants), changing the geographic distribution of health impacts. We model PM2.5-related health impacts attributable to urban EV use for 34 major cities. Our investigation focuses on environmental justice (EJ) by comparing pollutant inhalation versus income among impacted counties. We find that EVs could increase EJ challenge in China: most (~77%, range: 41-96%) emission inhalation attributable to urban EVs use is distributed to predominately rural communities whose incomes are on average lower than the cities where EVs are used. Results vary dramatically across cities depending on urban income and geography. Discriminant analysis reveals that counties with low income and high inhalation of urban EV emissions have comparatively higher agricultural employment rates, higher mortality rates, more children in the population, and lower education levels. We find that low-emission electricity sources such as renewable energy can help mitigate EJ issues raised here. Findings here are not unique to EVs, but instead are relevant for nearly all electricity-consuming technologies in urban areas.

PM2.5 and ozone health impacts and disparities in New York City: sensitivity to spatial and temporal resolution

Air quality health impact assessment (HIA) synthesizes information about air pollution exposures, health effects, and population vulnerability for regulatory decision-making and public engagement. HIAs often use annual average county or regional data to estimate health outcome incidence rates that vary substantially by season and at the subcounty level. Using New York City as an example, we assessed the sensitivity of estimated citywide morbidity and mortality attributable to ambient fine particulate matter (PM_2.5) and ozone to the geographic (county vs. neighborhood) and temporal (seasonal vs. annual average) resolution of health incidence data. We also used the neighborhood-level analysis to assess variation in estimated air pollution impacts by neighborhood poverty concentration. Estimated citywide health impacts attributable to PM_2.5 and ozone were relatively insensitive to the geographic resolution of health incidence data. However, the neighborhood-level analysis demonstrated increasing impacts with greater neighborhood poverty levels, particularly for PM_2.5-attributable asthma emergency department visits, which were 4.5 times greater in high compared to low-poverty neighborhoods. PM_2.5-attributable health impacts were similar using seasonal and annual average incidence rates. Citywide ozone-attributable asthma morbidity was estimated to be 15 % lower when calculated from seasonal, compared to annual average incidence rates, as asthma morbidity rates are lower during the summer ozone season than the annual average rate. Within the ozone season, 57 % of estimated ozone-attributable emergency department for asthma in children occurred in the April-June period when average baseline incidence rates are higher than in the July-September period when ozone concentrations are higher. These analyses underscore the importance of utilizing spatially and temporally resolved data in local air quality impact assessments to characterize the overall city burden and identify areas of high vulnerability.

Impact of a cleaner-burning cookstove intervention on blood pressure in Nicaraguan women

Few studies have evaluated the cardiovascular-related effects of indoor biomass burning or the role of characteristics such as age and obesity status, in this relationship. We examined the impact of a cleaner-burning cookstove intervention on blood pressure among Nicaraguan women using an open fire at baseline; we also evaluated heterogeneity of the impact by subgroups of the population. We evaluated changes in systolic and diastolic blood pressure from baseline to post-intervention (range: 273-383 days) among 74 female cooks. We measured indoor fine particulate matter (PM(2.5); N = 25), indoor carbon monoxide (CO; N = 32), and personal CO (N = 30) concentrations. Large mean reductions in pollutant concentrations were observed for all pollutants; for example, indoor PM(2.5) was reduced 77% following the intervention. However, pollution distributions (baseline and post-intervention) were wide and overlapping. Although substantial reductions in blood pressure were not observed among the entire population, a 5.9 mmHg reduction [95% confidence interval (CI): -11.3, -0.4] in systolic blood pressure was observed among women aged 40 or more years and a 4.6 mmHg reduction (95% CI: -10.0, 0.8) was observed among obese women. Results from this study provide an indication that certain subgroups may be more likely to experience improvements in blood pressure following a cookstove intervention.

Expanding the scope of risk assessment: methods of studying differential vulnerability and susceptibility

Several methodological issues have been identified in analysis of epidemiological data to better assess the distributional effects of exposures and hypotheses about effect modification. We discuss the hierarchical mixed model and some more complex methods. Methods of capturing inequality are a second dimension of risk assessment, and simulation studies are important because plausible choices for air pollution effects and effect modifiers could result in extremely high risks in a small subset of the population. Future epidemiological studies should explore contextual and individual-level factors that might modify these relationships. The Environmental Protection Agency should make this a standard part of their risk assessments whenever the necessary information is available.

Estimation of age-related vulnerability to air pollution: assessment of respiratory health at local scale

This paper demonstrates association of short-term variation in pollution and health outcomes within the same geographical area for a typical urban setting in the northern part of the UK from time series analysis. It utilises publicly available datasets for regulated air pollutants (PM₁₀, NO₂, SO₂, CO and O₃), meteorology and respiratory hospital admissions (and mortality) between April 2002 and December 2005 to estimate the respiratory health effect of pollution exposure, mainly in the elderly. Our results show that PM₁₀ and O₃ are positively associated with respiratory hospital admissions in the elderly, specifically in the age group 70-79. CO effects seem to be concentrated on the most elderly age group (80+) whereas NO₂ seems to have the opposite age-related effect, with lower effects on the more elderly.

Maximizing health benefits and minimizing inequality: incorporating local-scale data in the design and evaluation of air quality policies

The U.S. Environmental Protection Agency undertook a case study in the Detroit metropolitan area to test the viability of a new multipollutant risk-based (MP/RB) approach to air quality management, informed by spatially resolved air quality, population, and baseline health data. The case study demonstrated that the MP/RB approach approximately doubled the human health benefits achieved by the traditional approach while increasing cost less than 20%--moving closer to the objective of Executive Order 12866 to maximize net benefits. Less well understood is how the distribution of health benefits from the MP/RB and traditional strategies affect the existing inequalities in air-pollution-related risks in Detroit. In this article, we identify Detroit populations that may be both most susceptible to air pollution health impacts (based on local-scale baseline health data) and most vulnerable to air pollution (based on fine-scale PM(2.5) air quality modeling and socioeconomic characteristics). Using these susceptible/vulnerable subpopulation profiles, we assess the relative impacts of each control strategy on risk inequality, applying the Atkinson Index (AI) to quantify health risk inequality at baseline and with either risk management approach. We find that the MP/RB approach delivers greater air quality improvements among these subpopulations while also generating substantial benefits among lower-risk populations. Applying the AI, we confirm that the MP/RB strategy yields less PM(2.5) mortality and asthma hospitalization risk inequality than the traditional approach. We demonstrate the value of this approach to policymakers as they develop cost-effective air quality management plans that maximize risk reduction while minimizing health inequality.

The benefits of whole-house in-duct air cleaning in reducing exposures to fine particulate matter of outdoor origin: a modeling analysis

Health risks of fine particle air pollution (PM(2.5)) are an important public health concern that has the potential to be mitigated in part by interventions such as air cleaning devices that reduce personal exposure to ambient PM(2.5). To characterize exposure to ambient PM(2.5) indoors as a function of residential air cleaners, a multi-zone indoor air quality model was used to integrate spatially resolved data on housing, meteorology, and ambient PM(2.5), with performance testing of residential air cleaners to estimate short-term and annual average PM(2.5) of outdoor origin inside residences of three metropolitan areas. The associated public health impacts of reduced ambient PM(2.5) exposure were estimated using a standard health impact assessment methodology. Estimated indoor levels of ambient PM(2.5) varied substantially among ventilation and air cleaning configurations. The median 24-h average indoor-outdoor ratio of ambient PM(2.5) was 0.57 for homes with natural ventilation, 0.35 for homes with central air conditioning (AC) with conventional filtration, and 0.1 for homes with central AC with high efficiency in-duct air cleaner. Median modeled 24-h average indoor concentrations of PM(2.5) of outdoor origin for those three configurations were 8.4, 5.3, and 1.5 microg/m(3), respectively. The potential public health benefits of reduced exposure to ambient PM(2.5) afforded by air cleaning systems were substantial. If the entire population of single-family homes with central AC in the modeling domain converted from conventional filtration to high-efficiency in-duct air cleaning, the change in ambient PM(2.5) exposure is estimated to result in an annual reduction of 700 premature deaths, 940 hospital and emergency room visits, and 130,000 asthma attacks in these metropolitan areas. In addition to controlling emissions from sources, high-efficiency whole-house air cleaner are expected to reduce exposure to particles of outdoor origin and are projected to be an effective means of managing public health impacts of ambient particle pollution.

Uncertainty and variability in health-related damages from coal-fired power plants in the United States

The health-related damages associated with emissions from coal-fired power plants can vary greatly across facilities as a function of plant, site, and population characteristics, but the degree of variability and the contributing factors have not been formally evaluated. In this study, we modeled the monetized damages associated with 407 coal-fired power plants in the United States, focusing on premature mortality from fine particulate matter (PM(2.5)). We applied a reduced-form chemistry-transport model accounting for primary PM(2.5) emissions and the influence of sulfur dioxide (SO(2)) and nitrogen oxide (NO(x)) emissions on secondary particulate formation. Outputs were linked with a concentration-response function for PM(2.5)-related mortality that incorporated nonlinearities and model uncertainty. We valued mortality with a value of statistical life approach, characterizing and propagating uncertainties in all model elements. At the median of the plant-specific uncertainty distributions, damages across plants ranged from $30,000 to $500,000 per ton of PM(2.5), $6,000 to $50,000 per ton of SO(2), $500 to $15,000 per ton of NO(x), and $0.02 to $1.57 per kilowatt-hour of electricity generated. Variability in damages per ton of emissions was almost entirely explained by population exposure per unit emissions (intake fraction), which itself was related to atmospheric conditions and the population size at various distances from the power plant. Variability in damages per kilowatt-hour was highly correlated with SO(2) emissions, related to fuel and control technology characteristics, but was also correlated with atmospheric conditions and population size at various distances. Our findings emphasize that control strategies that consider variability in damages across facilities would yield more efficient outcomes.

Evaluating efficiency-equality tradeoffs for mobile source control strategies in an urban area

In environmental risk management, there are often interests in maximizing public health benefits (efficiency) and addressing inequality in the distribution of health outcomes. However, both dimensions are not generally considered within a single analytical framework. In this study, we estimate both total population health benefits and changes in quantitative indicators of health inequality for a number of alternative spatial distributions of diesel particulate filter retrofits across half of an urban bus fleet in Boston, Massachusetts. We focus on the impact of emissions controls on primary fine particulate matter (PM(2.5)) emissions, modeling the effect on PM(2.5) concentrations and premature mortality. Given spatial heterogeneity in baseline mortality rates, we apply the Atkinson index and other inequality indicators to quantify changes in the distribution of mortality risk. Across the different spatial distributions of control strategies, the public health benefits varied by more than a factor of two, related to factors such as mileage driven per day, population density near roadways, and baseline mortality rates in exposed populations. Changes in health inequality indicators varied across control strategies, with the subset of optimal strategies considering both efficiency and equality generally robust across different parametric assumptions and inequality indicators. Our analysis demonstrates the viability of formal analytical approaches to jointly address both efficiency and equality in risk assessment, providing a tool for decisionmakers who wish to consider both issues.

Evaluating efficiency-equality tradeoffs for mobile source control strategies in an urban area

In environmental risk management, there are often interests in maximizing public health benefits (efficiency) and addressing inequality in the distribution of health outcomes. However, both dimensions are not generally considered within a single analytical framework. In this study, we estimate both total population health benefits and changes in quantitative indicators of health inequality for a number of alternative spatial distributions of diesel particulate filter retrofits across half of an urban bus fleet in Boston, Massachusetts. We focus on the impact of emissions controls on primary fine particulate matter (PM(2.5)) emissions, modeling the effect on PM(2.5) concentrations and premature mortality. Given spatial heterogeneity in baseline mortality rates, we apply the Atkinson index and other inequality indicators to quantify changes in the distribution of mortality risk. Across the different spatial distributions of control strategies, the public health benefits varied by more than a factor of two, related to factors such as mileage driven per day, population density near roadways, and baseline mortality rates in exposed populations. Changes in health inequality indicators varied across control strategies, with the subset of optimal strategies considering both efficiency and equality generally robust across different parametric assumptions and inequality indicators. Our analysis demonstrates the viability of formal analytical approaches to jointly address both efficiency and equality in risk assessment, providing a tool for decisionmakers who wish to consider both issues.

The effects of 3 environmental risks on mortality disparities across Mexican communities

The disparities in the burden of ill health caused by environmental risks should be an important consideration beyond their aggregate population effects. We used comparative risk assessment methods to calculate the mortality effects of unsafe water and sanitation, indoor air pollution from household solid fuel use, and ambient urban particulate matter pollution in Mexico. We also estimated the disparities in mortality caused by each risk factor, across municipios (counties) of residence and by municipio socioeconomic status (SES). Data sources for the analysis were the national census, population-representative health surveys, and air quality monitoring for risk factor exposure; systematic reviews and meta-analyses of epidemiological studies for risk factor effects; and vital statistics for disease-specific mortality. During 2001-2005, unsafe water and sanitation, household solid fuel use, and urban particulate matter pollution were responsible for 3,000, 3,600, and 7,600 annual deaths, respectively. Annual child mortality rates would decrease by 0.2, 0.1, and 0.1 per 1,000 children, and life expectancy would increase by 1.0, 1.2, and 2.4 months, respectively, in the absence of these environmental exposures. Together, these risk factors caused 10.6% of child deaths in the lowest-SES communities (0.9 deaths per 1,000 children), but only 4.0% in communities in the highest-SES ones (0.1 per 1,000). In the 50 most-affected municipios, these 3 exposures were responsible for 3.2 deaths per 1,000 children and a 10-month loss of life expectancy. The large disparities in the mortality effects of these 3 environmental risks should form the basis of interventions and environmental monitoring programs.

Excess infant mortality after nuclear plant startup in rural Mississippi

In the United States, utility companies have recently begun ordering new nuclear power reactors, the first such orders in the country since 1978. One potential site would be the Grand Gulf plant near Port Gibson, Mississippi. In 1983-1984, the first two years in which the existing Grand Gulf reactor operated, significant increases were observed in local rates of infant deaths (+35.3%) and fetal deaths (+57.8%). Local infant mortality remained elevated for the next two decades. These changes match those experienced in the same five local counties during atomic bomb testing in the 1950s and 1960s. This report examines potential reasons why an indigent, largely African American community may be at higher risk than other populations from exposure to an environmental toxin such as radiation. It also considers potential health risks posed by new reactors at Grand Gulf.

Environmental equity in air quality management: local and international implications for human health and climate change

The health burden of environmental exposures, including ambient air pollution and climate-change-related health impacts, is not equally distributed between or within regions and countries. These inequalities are currently receiving increased attention in environmental research as well as enhanced appreciation in environmental policy, where calls for environmental equity are more frequently heard. The World Health Organization (WHO) 2006 Global Update of the Air Quality Guidelines attempted to address the global-scale inequalities in exposures to air pollution and the burden of diseases due to air pollution. The guidelines stop short, however, of addressing explicitly the inequalities in exposure and adverse health effects within countries and urban areas due to differential distribution of sources of air pollution such as motor vehicles and local industry, and differences in susceptibility to the adverse health effects attributed to air pollution. These inequalities, may, however, be addressed in local air quality and land use management decisions. Locally, community-based participatory research can play an important role in documenting potential inequities and fostering corrective action. Research on environmental inequities will also benefit from current efforts to (1) better understand social determinants of health and (2) apply research evidence to reduce health disparities. Similarly, future research and policy action will benefit from stronger linkages between equity concerns related to health consequences of both air pollution exposure and climate change, since combustion products are important contributors to both of these environmental problems.

Vulnerability to air pollution health effects

INTRODUCTION

Ambient air pollution can have adverse effects on the health of exposed populations, but individuals or groups are not equally vulnerable, and pollution reduction benefits are likely to be unevenly distributed within a population. While the use of total-population risks is a valid approach for public health protection, it is increasingly recognized that more attention on vulnerable groups is necessary. This paper describes population vulnerability to the health effects of air pollutants using risk analysis concepts and based on available evidence.

METHODS

Publications reporting air pollution health risks for specific sub-populations, or more conceptual discussions of vulnerability, were selected following a literature search of the PubMed database. Only studies in the context of developed countries were included. Information on population characteristics and factors that can influence risk was assessed from the perspective of the vulnerability framework, and was used to outline interactions with biological susceptibility, exposure, and social coping.

RESULTS

Population characteristics encompass several factors that interact and confer vulnerability. Age, for example, regarded as significant mostly in terms of physiology, also relates to exposure through behaviours and activities that can be more amenable to prevention. Children are recognized as a high-risk group but their vulnerability may differ by childhood stage, while pregnant women are not explicitly identified as a vulnerable group despite growing evidence for reproductive risks. Social-economic factors have received little attention, although they can affect coping capacity as well as interact with susceptibility and exposure to air pollution.

CONCLUSIONS

Evidence for vulnerability components often lies in different fields of study and has not been evaluated in an integrated manner. Better understanding of population vulnerability can improve the scientific basis to assess risks and develop policies or other health protection initiatives to reduce the impacts of air pollution.

Quantifying the efficiency and equity implications of power plant air pollution control strategies in the United States

BACKGROUND

In deciding among competing approaches for emissions control, debates often hinge on the potential tradeoffs between efficiency and equity. However, previous health benefits analyses have not formally addressed both dimensions.

OBJECTIVES

We modeled the public health benefits and the change in the spatial inequality of health risk for a number of hypothetical control scenarios for power plants in the United States to determine optimal control strategies.

METHODS

We simulated various ways by which emission reductions of sulfur dioxide (SO(2)), nitrogen oxides, and fine particulate matter (particulate matter < 2.5 microm in diameter; PM(2.5)) could be distributed to reach national emissions caps. We applied a source-receptor matrix to determine the PM(2.5) concentration changes associated with each control scenario and estimated the mortality reductions. We estimated changes in the spatial inequality of health risk using the Atkinson index and other indicators, following previously derived axioms for measuring health risk inequality.

RESULTS

In our baseline model, benefits ranged from 17,000-21,000 fewer premature deaths per year across control scenarios. Scenarios with greater health benefits also tended to have greater reductions in the spatial inequality of health risk, as many sources with high health benefits per unit emissions of SO(2) were in areas with high background PM(2.5) concentrations. Sensitivity analyses indicated that conclusions were generally robust to the choice of indicator and other model specifications.

CONCLUSIONS

Our analysis demonstrates an approach for formally quantifying both the magnitude and spatial distribution of health benefits of pollution control strategies, allowing for joint consideration of efficiency and equity.

Assessing cumulative health risks from exposure to environmental mixtures - three fundamental questions

Differential exposure to mixtures of environmental agents, including biological, chemical, physical, and psychosocial stressors, can contribute to increased vulnerability of human populations and ecologic systems. Cumulative risk assessment is a tool for organizing and analyzing information to evaluate the probability and seriousness of harmful effects caused by either simultaneous and/or sequential exposure to multiple environmental stressors. In this article we focus on elucidating key challenges that must be addressed to determine whether and to what degree differential exposure to environmental mixtures contributes to increased vulnerability of exposed populations. In particular, the emphasis is on examining three fundamental and interrelated questions that must be addressed as part of the process to assess cumulative risk: a) Which mixtures are most important from a public health perspective? and b) What is the nature (i.e., duration, frequency, timing) and magnitude (i.e., exposure concentration and dose) of relevant cumulative exposures for the population of interest? c) What is the mechanism (e.g., toxicokinetic or toxicodynamic) and consequence (e.g., additive, less than additive, more than additive) of the mixture's interactive effects on exposed populations? The focus is primarily on human health effects from chemical mixtures, and the goal is to reinforce the need for improved assessment of cumulative exposure and better understanding of the biological mechanisms that determine toxicologic interactions among mixture constituents.

Personal Coronary Risk Profiles Modify Autonomic Nervous System Responses to Air Pollution

OBJECTIVE

We investigated whether PM2.5-mediated autonomic modulation depends on individual coronary risk profiles.

METHODS

Five-minute average heart rate (HR) and heart rate variability (HRV, including standard deviation of normal-to-normal intervals [SDNN], square root of the mean squared differences of successive NN intervals [rMSSD], high frequency [HF]) were measured from 24-hour ambulatory electrocardiograms, and personal PM(2.5) exposures were monitored in a prospective study of 10 male boilermakers (aged 34.3 +/- 8.1 years). We used the Framingham score to classify individuals into low (score = 1-3) and high (score = 5-6) risk categories. Mixed-effect models were used for statistical analyses.

RESULTS

Each 1-mg/m(3) increase in the preceding 4-hour moving average PM(2.5) was associated with HR increase (5.3 beats/min) and HRV reduction (11.7%, confidence interval [CI] = 6.2-17.1% for SDNN; 11.1%, CI = 3.1-19.1% for rMSSD; 16.6%, CI = 1.5-31.7% for HF). Greater responses (2- to 4-fold differences) were observed in high-risk subjects than in low-risk subjects.

CONCLUSIONS

Our study suggests that adverse autonomic responses to metal particulate are aggravated in workers with higher coronary risk profiles.

International studies of prenatal exposure to polycyclic aromatic hydrocarbons and fetal growth

OBJECTIVES

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitously distributed human mutagens and carcinogens. However, lack of adequate air monitoring data has limited understanding of the effects of airborne PAHs on fetal growth. To address this gap in knowledge, we examined the association between prenatal exposure to airborne PAHs and birth weight, birth length, and birth head circumference, respectively, in Krakow, Poland, and New York City (NYC).

METHODS

The parallel prospective cohort studies enrolled nonsmoking, healthy, and nonoccupationally exposed women and their newborns. Personal air monitoring of pregnant women was conducted over 48 hr. To control for maternal environmental tobacco smoke (ETS) exposure, we excluded those with umbilical cord plasma cotinine concentrations > 25 ng/mL. Mean cord plasma cotinine concentrations in both ethnic groups were <or= 0.5 ng/mL.

RESULTS

Prenatal PAH exposure was 10-fold higher in Krakow than in NYC. Prenatal PAH exposure was associated with significantly reduced birth weight in both Krakow Caucasians (p < 0.01) and in NYC African Americans (p < 0.01), controlling for known and potential confounders, but not in NYC Dominicans. Within the lower exposure range common to the two cities (1.80-36.47 ng/m3), the effect per unit PAH exposure on birth weight was 6-fold greater for NYC African Americans than for Krakow Caucasians (p = 0.01).

CONCLUSIONS

These results confirm the adverse reproductive effect of relatively low PAH concentrations in two populations and suggest increased susceptibility of NYC African Americans. Fetal growth impairment has been linked to child developmental and health problems. Thus, substantial health benefits would result from global reduction of PAH emissions.

Incorporating concepts of inequality and inequity into health benefits analysis

BACKGROUND

Although environmental policy decisions are often based in part on both risk assessment information and environmental justice concerns, formalized approaches for addressing inequality or inequity when estimating the health benefits of pollution control have been lacking. Inequality indicators that fulfill basic axioms and agree with relevant definitions and concepts in health benefits analysis and environmental justice analysis can allow for quantitative examination of efficiency-equality tradeoffs in pollution control policies.

METHODS

To develop appropriate inequality indicators for health benefits analysis, we provide relevant definitions from the fields of risk assessment and environmental justice and consider the implications. We evaluate axioms proposed in past studies of inequality indicators and develop additional axioms relevant to this context. We survey the literature on previous applications of inequality indicators and evaluate five candidate indicators in reference to our proposed axioms. We present an illustrative pollution control example to determine whether our selected indicators provide interpretable information.

RESULTS AND CONCLUSIONS

We conclude that an inequality indicator for health benefits analysis should not decrease when risk is transferred from a low-risk to high-risk person, and that it should decrease when risk is transferred from a high-risk to low-risk person (Pigou-Dalton transfer principle), and that it should be able to have total inequality divided into its constituent parts (subgroup decomposability). We additionally propose that an ideal indicator should avoid value judgments about the relative importance of transfers at different percentiles of the risk distribution, incorporate health risk with evidence about differential susceptibility, include baseline distributions of risk, use appropriate geographic resolution and scope, and consider multiple competing policy alternatives. Given these criteria, we select the Atkinson index as the single indicator most appropriate for health benefits analysis, with other indicators useful for sensitivity analysis. Our illustrative pollution control example demonstrates how these indices can help a policy maker determine control strategies that are dominated from an efficiency and equality standpoint, those that are dominated for some but not all societal viewpoints on inequality averseness, and those that are on the optimal efficiency-equality frontier, allowing for more informed pollution control policies.

Assessment of public health risks associated with atmospheric exposure to PM2.5 in Washington, DC, USA

In this research, we investigated the public health risks associated with atmospheric exposure to PM2.5 for different subpopulations (black, white, Hispanic, youth, adults, and elderly) in the Washington, DC area. Washington, DC has long been considered a non-healthy place to live according to the American Lung Association due to its poor air quality. This recognition clearly includes the negative PM-related human health effects within the region. Specifically, DC fine particulate matter (PM2.5) [or particulate matter with an aerodynamic diameter less than 2.5 microm] poses notable health risks to subpopulations having an annual mean value of 16.70 microg/m(3) during the years 1999-2004, exceeding the EPA National Ambient Air Quality Standard (NAAQS) of 15 microg/m(3). Incessant exposure to significant levels of PM has previously been linked to deleterious health effects, such as heart and lung diseases. The environmental quality and public health statistics of Washington, DC indicate the need for higher-resolution measurements of emissions, both spatially and temporally, and increased analysis of PM-related health effects. Our findings show that there are significant risks of ward-specific pediatric asthma emergency room visits (ERV). Results also illustrate lifetime excess lung cancer risks, exceeding the 1 x 10(-6) threshold for the measured levels of particulate matter and heavy metals (chromium and arsenic) on behalf of numerous subpopulations in the DC selected wards.

Health, wealth, and air pollution: advancing theory and methods

The effects of both ambient air pollution and socioeconomic position (SEP) on health are well documented. A limited number of recent studies suggest that SEP may itself play a role in the epidemiology of disease and death associated with exposure to air pollution. Together with evidence that poor and working-class communities are often more exposed to air pollution, these studies have stimulated discussion among scientists, policy makers, and the public about the differential distribution of the health impacts from air pollution. Science and public policy would benefit from additional research that integrates the theory and practice from both air pollution and social epidemiologies to gain a better understanding of this issue. In this article we aim to promote such research by introducing readers to methodologic and conceptual approaches in the fields of air pollution and social epidemiology; by proposing theories and hypotheses about how air pollution and socioeconomic factors may interact to influence health, drawing on studies conducted worldwide; by discussing methodologic issues in the design and analysis of studies to determine whether health effects of exposure to ambient air pollution are modified by SEP; and by proposing specific steps that will advance knowledge in this field, fill information gaps, and apply research results to improve public health in collaboration with affected communities.

Possible noncausal bases for correlations between low concentrations of ambient particulate matter and daily mortality

Numerous studies of populations living in areas with good air quality have reported correlations between daily average levels of ambient particulate matter (PM) and daily mortality rates. These associations persist at PM levels below current air quality standards and are difficult to reconcile with the toxicology of PM chemical constituents. The unusual level of lethality per unit PM mass predicted by these associations may result from confounding by unmeasured societal, behavioral, or stress factors. Daily average ambient PM levels may be expected to correlate with societal activity level, because a working population increases PM emissions through increased manufacture, power utilization, construction, demolition, farming, and travel. Also, people's perceived and actual health depend on societal and psychological factors. A stress such as anger strongly increases the risk of death due to heart attack. Societal factors modify mortality as shown by calendar-related changes in mortality that are unrelated to air quality. Cardiovascular and respiratory mortality are correlated to day of the week, end of the month, and to the first week of the year. There is likely a role of such nontoxicologic variables in the PM associations, and without vigorously testing if other variables correlate as well as PM, we may erroneously conclude that reducing already low levels of PM will yield real public health benefits.

Issues and uncertainties in estimating the health benefits of air pollution control

The estimation of health benefits from reductions in ambient air pollution requires information both about the relationship between concentrations and health effects and about the ultimate value of health outcomes. In this commentary, I discuss significant issues and uncertainties that must be addressed for both elements. Critical issues for concentration-response estimation include the shape of the concentration-response curve at current and projected ambient levels, the relevant exposure period, the existence of high-risk subpopulations, and the ability to generalize across study settings. Health outcomes can be valued using either health-based measures like quality-adjusted life years or economic measures like value of statistical life; the choice of measure has a significant effect on the magnitude and distribution of health benefits. Analysts estimating health benefits for ultimate benefit-cost applications should provide results using multiple valuation frameworks and multiple assumptions about health evidence to facilitate interpretation and to determine whether policy decisions depend on these assumptions.