Implications of disparities in social and built environment antecedents to adult nature engagement.

Antecedent factors which influence adult engagement with nature are underexplored given the human health benefits strongly associated with nature exposure. Formative pathways and impediments to nature contact merit understanding as they may contribute to later-life health disparities. We probed experiential pathways and attitudes toward nature engagement among adults purposefully sampled across U.S. regions, age, race/ethnicity, and urbanicity through semi-structured focus group discussions. The research aims were to explore entryways and barriers to experiencing nature and learn how natured and built environments compete in influencing human-nature relationships. Sessions were recorded, transcribed, and analyzed following Braun and Clarke's phases of thematic analysis. Qualitative content analysis of discussions identified three principal themes: 1) formative influences promoting adult nature engagement (i.e., persons/organizations and places of origin), 2) detractors from nature engagement (i.e., perceptual, material, and physical barriers), and 3) role of current setting (i.e., natural and built environments) shaping nature-seeking relationships. We found experiential factors that included early life exposures outdoors, personal mentorship, and organizational affiliation to be highly influential in socializing individuals to nature and in soldering attachment to nature which manifests into adulthood. In contrast, changing demographics and childhood, inequity, social dynamics, metropolitan growth, urban renewal explained alienation from nature. These findings emphasize the importance of efforts to expand opportunities for nature contact, especially for youth living in economically challenged urban areas, which go beyond increasing greenspace to encompass mentoring partnerships for gaining skills and comfort outdoors and redesign of safe natured spaces within cities for hands-on learning and discovery.

Health benefits of decreases in on-road transportation emissions in the United States from 2008 to 2017.

Decades of air pollution regulation have yielded enormous benefits in the United States, but vehicle emissions remain a climate and public health issue. Studies have quantified the vehicle-related fine particulate matter (PM2.5)-attributable mortality but lack the combination of proper counterfactual scenarios, latest epidemiological evidence, and detailed spatial resolution; all needed to assess the benefits of recent emission reductions. We use this combination to assess PM2.5-attributable health benefits and also assess the climate benefits of on-road emission reductions between 2008 and 2017. We estimate total benefits of $270 (190 to 480) billion in 2017. Vehicle-related PM2.5-attributable deaths decreased from 27,700 in 2008 to 19,800 in 2017; however, had per-mile emission factors remained at 2008 levels, 48,200 deaths would have occurred in 2017. The 74% increase from 27,700 to 48,200 PM2.5-attributable deaths with the same emission factors is due to lower baseline PM2.5 concentrations (+26%), more vehicle miles and fleet composition changes (+22%), higher baseline mortality (+13%), and interactions among these (+12%). Climate benefits were small (3 to 19% of the total). The percent reductions in emissions and PM2.5-attributable deaths were similar despite an opportunity to achieve disproportionately large health benefits by reducing high-impact emissions of passenger light-duty vehicles in urban areas. Increasingly large vehicles and an aging population, increasing mortality, suggest large health benefits in urban areas require more stringent policies. Local policies can be effective because high-impact primary PM2.5 and NH3 emissions disperse little outside metropolitan areas. Complementary national-level policies for NOx are merited because of its substantial impacts-with little spatial variability-and dispersion across states and metropolitan areas.

Solid fuel use and early child development disparities in Ghana: analyses by gender and urbanicity.

In Ghana, more than 77% of the population depends on biomass fuels for cooking. Previous studies show that solid fuel use (SFU) has adverse effects on pregnancy and child health outcomes. Yet, no previous study considered potential effects on early child development indicators (ECDI), nor how SFU effects may vary by gender, and rural and urban areas. We investigated the associations of SFU with ECDI measures, and whether these associations exhibited sex and urban/rural differences. We used the 2011-2012 Ghana's Multiple Indicator Cluster Surveys-UNICEF (N = 3326 children; 3-4 years). We derived a binary ECDI measure reflecting whether the child is developmentally on track or not from a caregiver-report of ten yes/no/do not know questions designed specifically to assess four domains of early child development: learning-cognition, literacy-numeracy, socio-emotional, and physical. We used multilevel Poisson regressions adjusting for neighborhood, household, mother, and child's characteristics to estimate covariate-adjusted prevalence ratios (PRs) of the associations between SFU and ECDI and its four dimensions. We run stratified analyses and used z-score tests of differences to evaluate effect modification by sex and urbanicity. Overall, 85% of children were exposed to SFU and 28% of children were not developmentally on track. After adjustment for confounders, children exposed to SFU were more likely to be not developmentally on track in comparison with nonexposed children (PR = 1.16; 95% confidence interval, [95% CI]: 1.10,1.22). These associations were stronger in girls (PR = 1.36; 95% CI: 1.03,1.79) in comparison with boys (PR = 0.87; 95% CI: 0.73,1.04). No difference in associations was observed between urban and rural children. Overall, these associations were mainly driven by the literacy-numeracy dimension. In this study, we show that SFU was associated with developmental delays in Ghanaian girls. Policy efforts which tackle SFU should be mindful of gender disparities in susceptibility to indoor pollution.

Eliminating Take-Home Exposures: Recognizing the Role of Occupational Health and Safety in Broader Community Health.

Toxic contaminants inadvertently brought from the workplace to the home, known as take-home or paraoccupational exposures, have often been framed as a problem that arises due to unsanitary worker behavior. This review article conceptualizes take-home exposures as a public health hazard by (i) investigating the history of take-home contaminants and how they have been studied, (ii) arguing that an ecosocial view of the problem is essential for effective prevention, (iii) summarizing key structural vulnerabilities that lead populations to be at risk, and (iv) discussing future research and prevention effort needs. This article reframes take-home exposures as one of many chronic pathways that contributes to persistent health disparities among workers, their families, and communities. Including the role of work in community health will increase the comprehensiveness of prevention efforts for contaminants such as lead and pesticides that contribute to environmental disparities.

Stress and Health in Nursing Students: The Nurse Engagement and Wellness Study.

BACKGROUND: Evidence suggests that behavioral, social, and environmental factors may modify the effects of life stress on health and performance of new nurses as they transition to hospitals. OBJECTIVES: The aim of this study was to describe the methods of a project designed to investigate the role of social, behavioral, and environmental factors in modifying the adverse effects of stress on new nurses and to discuss demographic, health, and life stress characteristics of the cohort at baseline. METHODS: A prospective cohort design was used to conduct a comprehensive assessment of health endpoints, life stress, behaviors, personal traits, social factors, indicators of engagement and performance, and environmental exposures in nursing students. Adjusted odds ratios and analyses of covariance were used to examine associations between these factors at baseline. RESULTS: Health indicators in the cohort were comparable or better than in the broader United States population, and lifetime stress exposure was lower than among students from other majors. Exposure to more lifetime stressors was associated with greater risk for various health conditions, including hypertension, diabetes, and depression. Conversely, better social, environmental, behavioral, and personal profiles were associated with protective effects for the same health conditions. DISCUSSION: These data comprehensively summarize the lives of predominately Hispanic nursing students and highlight risk and resilience factors associated with their health and well-being. The findings are timely, as the nursing field diversifies in preparation to care for a diverse and aging population. Comprehensively assessing stress-health relationships among student nurses ought to inform the policies, practices, and curricula of nursing schools to better prepare nurses to thrive in the often-strenuous healthcare environment.

Health preparedness plan for dengue detection during the 2020 summer Olympic and Paralympic games in Tokyo.

BACKGROUND: Participants in mass gathering events are at risk of acquiring imported and locally endemic infectious diseases. The 2014 dengue outbreak in Tokyo gathered attention since it was the first time in 70 years for Japan to experience an autochthonous transmission. Preparation for emerging infectious threats is essential even in places where these outbreaks have been largely unknown. The aim of this study is to identify strategies for early detection and prevention of dengue infection during the 2020 summer Olympics and Paralympics in Tokyo. METHODOLOGY/PRINCIPAL FINDINGS: We modified and adapted the failure mode and effect analysis (FMEA) methodology, generally used in industrial manufacturing, to examine the current controls for dengue detection and assessment. Information on existing controls were obtained from publicly available resources. Our analysis revealed that the national infectious disease control system to detect dengue in Japan is robust. However, in the case of large assemblies of international visitors for special events when the spread of communicable and vector-borne diseases increases, there are three main gaps that could be reinforced. First, cyclical training or a certification program on tropical disease management is warranted for physicians, especially those working in non-infectious disease-designated hospitals or clinics. Second, multi-language communication methods need to be strengthened especially in the health and hospitality sector. Third, owners of accommodations should consider incorporating a formal tropical disease-training program for their staff members and have a contingency plan for infectious disease-suspected travelers. CONCLUSIONS/SIGNIFICANCE: Our findings may facilitate physicians and public health officials where new controls would be beneficial for the 2020 summer Olympics and Paralympics. The FMEA framework has the potential to be applied to other infectious diseases, not just dengue.

Assessment of noise in the airplane cabin environment.

OBJECTIVE: To measure sound levels in the aircraft cabin during different phases of flight. METHODS: Sound level was measured on 200 flights, representing six aircraft groups using continuous monitors. A linear mixed-effects model with random intercept was used to test for significant differences in mean sound level by aircraft model and across each flight phase as well as by flight phase, airplane type, measurement location and proximity to engine noise. RESULTS: Mean sound levels across all flight phases and aircraft groups ranged from 37.6 to >110 dB(A) with a median of 83.5 dB(A). Significant differences in noise levels were also observed based on proximity to the engines and between aircraft with fuselage- and wing mounted engines. Nine flights (4.5%) exceeded the recommended 8-h TWA exposure limit of 85 dB(A) by the NIOSH and ACGIH approach, three flights (1.5%) exceeded the 8-h TWA action level of 85 dB(A) by the OSHA approach, and none of the flights exceeded the 8-h TWA action level of 90 dB(A) by the OSHA PEL approach. CONCLUSIONS: Additional characterization studies, including personal noise dosimetry, are necessary to document accurate occupational exposures in the aircraft cabin environment and identify appropriate response actions. FAA should consider applying the more health-protective NIOSH/ACGIH occupational noise recommendations to the aircraft cabin environment.

Geographical Inequalities and Social and Environmental Risk Factors for Under-Five Mortality in Ghana in 2000 and 2010: Bayesian Spatial Analysis of Census Data.

BACKGROUND: Under-five mortality is declining in Ghana and many other countries. Very few studies have measured under-five mortality-and its social and environmental risk factors-at fine spatial resolutions, which is relevant for policy purposes. Our aim was to estimate under-five mortality and its social and environmental risk factors at the district level in Ghana. METHODS AND FINDINGS: We used 10% random samples of Ghana's 2000 and 2010 National Population and Housing Censuses. We applied indirect demographic methods and a Bayesian spatial model to the information on total number of children ever born and children surviving to estimate under-five mortality (probability of dying by 5 y of age, 5q0) for each of Ghana's 110 districts. We also used the census data to estimate the distributions of households or persons in each district in terms of fuel used for cooking, sanitation facility, drinking water source, and parental education. Median district 5q0 declined from 99 deaths per 1,000 live births in 2000 to 70 in 2010. The decline ranged from <5% in some northern districts, where 5q0 had been higher in 2000, to >40% in southern districts, where it had been lower in 2000, exacerbating existing inequalities. Primary education increased in men and women, and more households had access to improved water and sanitation and cleaner cooking fuels. Higher use of liquefied petroleum gas for cooking was associated with lower 5q0 in multivariate analysis. CONCLUSIONS: Under-five mortality has declined in all of Ghana's districts, but the cross-district inequality in mortality has increased. There is a need for additional data, including on healthcare, and additional environmental and socioeconomic measurements, to understand the reasons for the variations in mortality levels and trends.

Linking student performance in Massachusetts elementary schools with the "greenness" of school surroundings using remote sensing.

Various studies have reported the physical and mental health benefits from exposure to "green" neighborhoods, such as proximity to neighborhoods with trees and vegetation. However, no studies have explicitly assessed the association between exposure to "green" surroundings and cognitive function in terms of student academic performance. This study investigated the association between the "greenness" of the area surrounding a Massachusetts public elementary school and the academic achievement of the school's student body based on standardized tests with an ecological setting. Researchers used the composite school-based performance scores generated by the Massachusetts Comprehensive Assessment System (MCAS) to measure the percentage of 3rd-grade students (the first year of standardized testing for 8-9 years-old children in public school), who scored "Above Proficient" (AP) in English and Mathematics tests (Note: Individual student scores are not publically available). The MCAS results are comparable year to year thanks to an equating process. Researchers included test results from 2006 through 2012 in 905 public schools and adjusted for differences between schools in the final analysis according to race, gender, English as a second language (proxy for ethnicity and language facility), parent income, student-teacher ratio, and school attendance. Surrounding greenness of each school was measured using satellite images converted into the Normalized Difference Vegetation Index (NDVI) in March, July and October of each year according to a 250-meter, 500-meter, 1,000-meter, and 2000-meter circular buffer around each school. Spatial Generalized Linear Mixed Models (GLMMs) estimated the impacts of surrounding greenness on school-based performance. Overall the study results supported a relationship between the "greenness" of the school area and the school-wide academic performance. Interestingly, the results showed a consistently positive significant association between the greenness of the school in the Spring (when most Massachusetts students take the MCAS tests) and school-wide performance on both English and Math tests, even after adjustment for socio-economic factors and urban residency.

Indoor air quality in green vs conventional multifamily low-income housing.

Indoor air quality is an important predictor of health, especially in low-income populations. It is unclear how recent trends in "green" building affect the indoor exposure profile. In two successive years, we conducted environmental sampling, home inspections, and health questionnaires with families in green and conventional (control) apartments in two public housing developments. A subset of participants was followed as they moved from conventional to green or conventional to conventional housing. We measured particulate matter less than 2.5 µm aerodynamic diameter (PM2.5), formaldehyde, nitrogen dioxide (NO2), nicotine, carbon dioxide (CO2), and air exchange rate (AER) over a seven-day sampling period coincident with survey administration. In multivariate models, we observed 57%, 65%, and 93% lower concentrations of PM2.5, NO2, and nicotine (respectively) in green vs control homes (p=0.032, p<0.001, p=0.003, respectively), as well as fewer reports of mold, pests, inadequate ventilation, and stuffiness. Differences in formaldehyde and CO2 were not statistically significant. AER was marginally lower in green buildings (p=0.109). Participants in green homes experienced 47% fewer sick building syndrome symptoms (p<0.010). We observed significant decreases in multiple indoor exposures and improved health outcomes among participants who moved into green housing, suggesting multilevel housing interventions have the potential to improve long-term resident health.

Mapping the vertical distribution of population and particulate air pollution in a near-highway urban neighborhood: implications for exposure assessment.

Owing to data collection challenges, the vertical variation in population in cities and particulate air pollution are typically not accounted for in exposure assessments, which may lead to misclassification of exposures based on elevation of residency. To better assess this misclassification, the vertical distribution of the potentially highly exposed population (PHEP), defined as all residents within the 100-m buffer zone of above-ground highways or the 200-m buffer zone of a highway-tunnel exit, was estimated for four floor categories in Boston's Chinatown (MA, USA) using the three-dimensional digital geography methodology. Vertical profiles of particle number concentration (7-3000 nm; PNC) and particulate matter (PM2.5) mass concentration were measured by hoisting instruments up the vertical face of an 11-story (35-m) building near the study area throughout the day on multiple days. The concentrations from all the profiles (n=23) were averaged together for each floor category. As measurement elevation increased from 0 to 35 m PNC decreased by 7.7%, compared with 3.6% for PM2.5. PHEP was multiplied by the average PNC for each floor category to assess exposures for near-highway populations. The results show that adding temporally-averaged vertical air pollution data had a small effect on residential ambient exposures for our study population; however, greater effects were observed when individual days were considered (e.g., winds were off the highways).

Air concentrations of PBDEs on in-flight airplanes and assessment of flight crew inhalation exposure.

To address the knowledge gaps regarding inhalation exposure of flight crew to polybrominated diphenyl ethers (PBDEs) on airplanes, we measured PBDE concentrations in air samples collected in the cabin air at cruising altitudes and used Bayesian Decision Analysis (BDA) to evaluate the likelihood of inhalation exposure to result in the average daily dose (ADD) of a member of the flight crew to exceed EPA Reference Doses (RfDs), accounting for all other aircraft and non-aircraft exposures. A total of 59 air samples were collected from different aircraft and analyzed for four PBDE congeners-BDE 47, 99, 100 and 209 (a subset were also analyzed for BDE 183). For congeners with a published RfD, high estimates of ADD were calculated for all non-aircraft exposure pathways and non-inhalation exposure onboard aircraft; inhalation exposure limits were then derived based on the difference between the RfD and ADDs for all other exposure pathways. The 95th percentile measured concentrations of PBDEs in aircraft air were <1% of the derived inhalation exposure limits. Likelihood probabilities of 95th percentile exposure concentrations >1% of the defined exposure limit were zero for all congeners with published RfDs.

An advanced numerical model for the assessment of airborne transmission of influenza in bus microenvironments.

A CFD-based numerical model was integrated with the Wells-Riley equation to numerically assess the risk of airborne influenza infection in a popular means of public transportation, e.g. the bus microenvironment. Three mixing ventilation methods, which are widely used in current bus configurations, and an alternative displacement ventilation method were numerically assessed in terms of their ability to limit the risk of airborne influenza infection. Furthermore, both the non air-recirculation and air-recirculation with filtration ventilation modes were investigated in terms of the influenza infection probability. According to the simulation results, air-recirculation mode with high efficiency filtration was found to cause almost the same infection risk as non air-recirculation mode (100% outdoor air supply), which indicated a potential benefit of filtration in reducing the infection risk. Additionally, for the commonly used mixing ventilation methods, air distribution method, location of return/exhaust opening and seat arrangement affected the airborne transmission of influenza between passengers. The displacement ventilation method was found to be more effective in limiting the risk of airborne infection. Overall, the developed numerical model can provide insights into how the micro-environmental conditions affect airborne infection transmission in buses. This numerical model can assist in developing effective control strategies related to airborne transmitted diseases for other frequently used public transportation systems, such as trains and airplanes.

Moving environmental justice indoors: understanding structural influences on residential exposure patterns in low-income communities.

OBJECTIVES: The indoor environment has not been fully incorporated into the environmental justice dialogue. To inform strategies to reduce disparities, we developed a framework to identify the individual and place-based drivers of indoor environment quality. METHODS: We reviewed empirical evidence of socioeconomic disparities in indoor exposures and key determinants of these exposures for air pollutants, lead, allergens, and semivolatile organic compounds. We also used an indoor air quality model applied to multifamily housing to illustrate how nitrogen dioxide (NO(2)) and fine particulate matter (PM(2.5)) vary as a function of factors known to be influenced by socioeconomic status. RESULTS: Indoor concentrations of multiple pollutants are elevated in low-socioeconomic status households. Differences in these exposures are driven by the combined influences of indoor sources, outdoor sources, physical structures, and residential activity patterns. Simulation models confirmed indoor sources' importance in determining indoor NO(2) and PM(2.5) exposures and showed the influence of household-specific determinants. CONCLUSIONS: Both theoretical models and empirical evidence emphasized that disparities in indoor environmental exposure can be significant. Understanding key determinants of multiple indoor exposures can aid in developing policies to reduce these disparities.

Air pollution in Accra neighborhoods: spatial, socioeconomic, and temporal patterns.

This study examined the spatial, socioeconomic status (SES), and temporal patterns of ambient air pollution in Accra, Ghana. Over 22 months, integrated and continuous rooftop particulate matter (PM) monitors were placed at a total of 11 residential or roadside monitoring sites in four neighborhoods of varying SES and biomass fuel use. PM concentrations were highest in late December and January, due to dust blown from the Sahara. Excluding this period, annual PM(2.5) ranged from 39 to 53 microg/m(3) at roadside sites and 30 to 70 microg/m(3) at residential sites; mean annual PM(10) ranged from 80 to 108 microg/m(3) at roadside sites and 57 to 106 microg/m(3) at residential sites. The low-income and densely populated neighborhood of Jamestown/Ushertown had the single highest residential PM concentration. There was less difference across traffic sites. Daily PM increased at all sites at daybreak, followed by a mid-day peak at some sites, and a more spread-out evening peak at all sites. Average carbon monoxide concentrations at different sites and seasons ranged from 7 to 55 ppm, and were generally lower at residential sites than at traffic sites. The results show that PM in these four neighborhoods is substantially higher than the WHO Air Quality Guidelines and in some cases even higher than the WHO Interim Target 1, with the highest pollution in the poorest neighborhood.

Evaluating methods for predicting indoor residential volatile organic compound concentration distributions.

Accurate modeling of exposure to volatile organic compounds (VOCs) over a large study population depends on proper characterization of concentrations in the indoor residential environment. However, owing to the high expense of field sampling campaigns for determining indoor air concentrations, such studies have only been conducted for limited populations. Therefore, there is a need to determine the degree to which results can be extrapolated to unstudied settings through the use of models, the most appropriate information required to do so and the potential errors associated with the use of sub-optimal information. The goal of this analysis is to evaluate three different source indicators used to predict indoor VOC concentration distributions for a new study population. Data from two field studies are used. For each data set, source strength, indoor-outdoor (I-O) difference and indoor/outdoor (I/O) ratio, collectively referred to as source indicators, are calculated and fit with distributions. These distributions, as well as distributions for air exchange, volume and outdoor concentrations for the new study population, are used for predicting indoor concentrations using Monte Carlo simulations, which are then compared with actual distributions. As expected, the source strength often provides the most effective predictions (11 out of 20 instances), but is slightly outperformed by, although is still comparable with, the I-O difference on some occasions (4 out of 20). The I/O ratio generally has the greatest prediction errors, given its dependence on outdoor concentrations, but performs optimally in a limited number of cases (5 out of 20). When deciding between the source strength and I-O difference, one must consider the availability and fidelity of both current and future data. On the basis of our findings, exposure-monitoring studies should report the distribution statistics for I-O differences and, if the data are available, for source strengths.

Ancillary benefits for caregivers of children with asthma participating in an environmental intervention study to alleviate asthma symptoms.

Providing care for children with asthma can be demanding and time-intensive with far-reaching effects on caregivers' lives. Studies have documented childhood asthma symptom reductions and improved asthma-related quality of life (AQOL) with indoor allergen-reducing environmental interventions. Few such studies, however, have considered ancillary benefits to caregivers or other family members. Ancillary benefits could be derived from child health improvements and reduced caregiving burden or from factors such as improved living environments or social support that often accompanies intensive residential intervention efforts. As part of the Boston Healthy Public Housing Initiative (HPHI), a longitudinal single-cohort intervention study of asthmatic children, we examined trends in caregivers' quality of life related to their child's asthma (caregiver AQOL) using monthly Juniper Caregiver Asthma Quality of Life Questionnaires (AQLQ) for 32 primary caregivers to 42 asthmatic children aged 4 to 17 years. Longitudinal analyses were used to examine caregiver AQOL trends and their relationship to the child's AQOL, then to consider additional predictors of caregiver AQOL. Caregiver AQLQ improved significantly over the course of the study with overall improvements significantly correlated with child AQOL (p = 0.005). However, caregiver AQOL improved most in the months before environmental interventions, while children's AQOL improved most in the months following. Time trends in caregiver AQOL, controlling for child AQOL, were not explained by available social support or caregiver stress measures. Our findings suggest potential participation effects not adequately captured by standard measures. Future environmental intervention studies should more formally consider social support and participation effects for both children and caregivers.

A cancer risk assessment of inner-city teenagers living in New York City and Los Angeles.

BACKGROUND: The Toxics Exposure Assessment Columbia-Harvard (TEACH) project assessed exposures and cancer risks from urban air pollutants in a population of high school teenagers in New York City (NYC) and Los Angeles (LA). Forty-six high school students participated in NYC and 41 in LA, most in two seasons in 1999 and 2000, respectively. METHODS: Personal, indoor home, and outdoor home 48-hr samples of volatile organic compounds (VOCs), aldehydes, particulate matter with aerodynamic diameter < or = 2.5 microm, and particle-bound elements were collected. Individual cancer risks for 13 VOCs and 6 particle-bound elements were calculated from personal concentrations and published cancer unit risks. RESULTS: The median cumulative risk from personal VOC exposures for this sample of NYC high school students was 666 per million and was greater than the risks from ambient exposures by a factor of about 5. In the LA sample, median cancer risks from VOC personal exposures were 486 per million, about a factor of 4 greater than ambient exposure risks. The VOCs with the highest cancer risk included 1,4-dichlorobenzene, formaldehyde, chloroform, acetaldehyde, and benzene. Of these, benzene had the greatest contributions from outdoor sources. All others had high contributions from indoor sources. The cumulative risks from personal exposures to the elements were an order of magnitude lower than cancer risks from VOC exposures. CONCLUSIONS: Most VOCs had median upper-bound lifetime cancer risks that exceeded the U.S. Environmental Protection Agency (EPA) benchmark of 1 x 10-6 and were generally greater than U.S. EPA modeled estimates, more so for compounds with predominant indoor sources. Chromium, nickel, and arsenic had median personal cancer risks above the U.S. EPA benchmark with exposures largely from outdoors and other microenvironments. The U.S. EPA-modeled concentrations tended to overestimate personal cancer risks for beryllium and chromium but underestimate risks for nickel and arsenic.

Parameter evaluation and model validation of ozone exposure assessment using Harvard Southern California Chronic Ozone Exposure Study data.

To examine factors influencing long-term ozone (O3) exposures by children living in urban communities, the authors analyzed longitudinal data on personal, indoor, and outdoor O3 concentrations, as well as related housing and other questionnaire information collected in the one-year-long Harvard Southern California Chronic Ozone Exposure Study. Of 224 children contained in the original data set, 160 children were found to have longitudinal measurements of O3 concentrations in at least six months of 12 months of the study period. Data for these children were randomly split into two equal sets: one for model development and the other for model validation. Mixed models with various variance-covariance structures were developed to evaluate statistically important predictors for chronic personal ozone exposures. Model predictions were then validated against the field measurements using an empirical best-linear unbiased prediction technique. The results of model fitting showed that the most important predictors for personal ozone exposure include indoor O3 concentration, central ambient O3 concentration, outdoor O3 concentration, season, gender, outdoor time, house fan usage, and the presence of a gas range in the house. Hierarchical models of personal O3 concentrations indicate the following levels of explanatory power for each of the predictive models: indoor and outdoor O3 concentrations plus questionnaire variables, central and indoor O3 concentrations plus questionnaire variables, indoor O3 concentrations plus questionnaire variables, central O3 concentrations plus questionnaire variables, and questionnaire data alone on time activity and housing characteristics. These results provide important information on key predictors of chronic human exposures to ambient O3 for children and offer insights into how to reliably and cost-effectively predict personal O3 exposures in the future. Furthermore, the techniques and findings derived from this study also have strong implications for selecting the most reliable and cost-effective exposure study design and modeling approaches for other ambient pollutants, such as fine particulate matter and selected urban air toxics.

The public health benefits of insulation retrofits in existing housing in the United States.

BACKGROUND: Methodological limitations make it difficult to quantify the public health benefits of energy efficiency programs. To address this issue, we developed a risk-based model to estimate the health benefits associated with marginal energy usage reductions and applied the model to a hypothetical case study of insulation retrofits in single-family homes in the United States. METHODS: We modeled energy savings with a regression model that extrapolated findings from an energy simulation program. Reductions of fine particulate matter (PM2.5) emissions and particle precursors (SO2 and NOx) were quantified using fuel-specific emission factors and marginal electricity analyses. Estimates of population exposure per unit emissions, varying by location and source type, were extrapolated from past dispersion model runs. Concentration-response functions for morbidity and mortality from PM2.5 were derived from the epidemiological literature, and economic values were assigned to health outcomes based on willingness to pay studies. RESULTS: In total, the insulation retrofits would save 800 TBTU (8 x 10(14) British Thermal Units) per year across 46 million homes, resulting in 3,100 fewer tons of PM2.5, 100,000 fewer tons of NOx, and 190,000 fewer tons of SO2 per year. These emission reductions are associated with outcomes including 240 fewer deaths, 6,500 fewer asthma attacks, and 110,000 fewer restricted activity days per year. At a state level, the health benefits per unit energy savings vary by an order of magnitude, illustrating that multiple factors (including population patterns and energy sources) influence health benefit estimates. The health benefits correspond to 1.3 billion dollars per year in externalities averted, compared with 5.9 billion dollars per year in economic savings. CONCLUSION: In spite of significant uncertainties related to the interpretation of PM2.5 health effects and other dimensions of the model, our analysis demonstrates that a risk-based methodology is viable for national-level energy efficiency programs.