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We developed spatially detailed source-impact estimates of population health burden measures of air pollution for the United States and Canada by quantifying sources-receptor relationships using the benefit-per-ton (BPT 1 ) metric. We calculated BPTs as the valuations of premature mortality counts due to fine particulate matter (PM 2.5 ; particulate matter ≤2.5 μm in aerodynamic diameter) exposure resulting from emissions of one ton of a given pollutant. Our BPT estimates, while accounting for a large portion of societal impact, do not include morbidity, acute exposure mortality, or chronic exposure mortality due to exposure to other pollutants such as ozone., The adjoint version of a widely used chemical transport model (CTM) allowed us to calculate location-specific BPTs at a high level of granularity for source-impact characterization. Location-specific BPTs provides a means for exploiting the disparities in source impact of emissions at different locations. For instance, estimated BPTs show that 20% of primary PM 2.5 and ammonia emissions in the United States account for approximately 50% and 60% of the burden of each species, respectively, for an estimated burden of $370B USD. Similarly, 10% of the most harmful emissions of primary PM 2.5 and ammonia emissions in Canada account for approximately 60% and 50% of their burden, respectively. By delineating differences and disparities in source impacts, adjoint-based BPT provides a direct means for prioritizing and targeting emissions that are most damaging., Sensitivity analyses evaluated the impact of our assumptions and study design on the estimated BPTs. The choice of concentration-response function had a substantial impact on the estimated BPTs and is likely to constitute the largest source of uncertainty in those estimates. Our method for constructing annual BPT estimates based on episodic simulations introduces low uncertainty, while uncertainties associated with the spatial resolution of the CTM were evaluated to be of medium importance. Finally, while recognizing that the use of BPTs entails an implied assumption of linearity, we show that BPTs for primary PM 2.5 emissions are stable across different emission levels in North America. While BPTs for precursors of secondary inorganic aerosols showed sensitivity to emission levels in the past, we found that those have stabilized with lower emissions and pollutant concentrations in the North American atmosphere., We used BPTs to provide location-specific and sectoral estimates for the cobenefits of reducing carbon dioxide emissions from a range of combustion sources. Cobenefit estimates rely heavily on the emission characteristics of the sector and therefore exhibit more pronounced sectoral fingerprints than do BPTs. We provide cobenefit estimates for various subsectors of on-road transportation, thermal electricity generation, and off-road engines. Off-road engines and various heavy-duty diesel vehicles had the largest cobenefits, which in most urban locations far exceeded estimates of the social cost of carbon. Based on our cobenefit estimations, we also provide per-vehicle burden estimates for different vintages of vehicle subsectors such as transit buses and short-haul trucks in major US cities., (© 2024 Health Effects Institute. All rights reserved.)

We evaluated the sensitivity of estimated PM 2.5 and NO 2 health impacts to varying key input parameters and assumptions including: 1) the spatial scale at which impacts are estimated, 2) using either a single concentration-response function (CRF) or using racial/ethnic group specific CRFs from the same epidemiologic study, 3) assigning exposure to residents based on home, instead of home and work locations for the state of Colorado. We found that the spatial scale of the analysis influences the magnitude of NO 2 , but not PM 2.5 , attributable deaths. Using county-level predictions instead of 1 km 2 predictions of NO 2 resulted in a lower estimate of mortality attributable to NO 2 by ∼ 50 % for all of Colorado for each year between 2000 and 2020. Using an all-population CRF instead of racial/ethnic group specific CRFs results in a 130 % higher estimate of annual mortality attributable for the white population and a 40 % and 80 % lower estimate of mortality attributable to PM 2.5 for Black and Hispanic residents, respectively. Using racial/ethnic group specific CRFs did not result in a different estimation of NO 2 attributable mortality for white residents, but led to ∼ 50 % lower estimates of mortality for Black residents, and 290 % lower estimate for Hispanic residents. Using NO 2 based on home instead of home and workplace locations results in a smaller estimate of annual mortality attributable to NO 2 for all of Colorado by 2 % each year and 0.3 % for PM 2.5 . Our results should be interpreted as an exercise to make methodological recommendations for future health impact assessments of pollution., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Background: Air pollution risk assessments do not generally quantify health impacts using multipollutant risk estimates, but instead use results from single-pollutant or copollutant models. Multipollutant epidemiological models account for pollutant interactions and joint effects but can be computationally complex and data intensive. Risk estimates from multipollutant studies are therefore challenging to implement in the quantification of health impacts., Objectives: Our objective was to conduct a case study using a developmental multipollutant version of the Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE) to estimate the health impact associated with changes in multiple air pollutants using both a single and multipollutant approach., Methods: BenMAP-CE was used to estimate the change in the number of pediatric asthma emergency department (ED) visits attributable to simulated changes in air pollution between 2011 and 2025 in Atlanta, Georgia, applying risk estimates from an epidemiological study that examined short-term single-pollutant and multipollutant (with and without first-order interactions) exposures. Analyses examined individual pollutants (i.e., ozone, fine particulate matter, carbon monoxide, nitrogen dioxide ( NO 2 ), sulfur dioxide, and particulate matter components) and combinations of these pollutants meant to represent shared properties or predefined sources (i.e., oxidant gases, secondary pollutants, traffic, power plant, and criteria pollutants). Comparisons were made between multipollutant health impact functions (HIF) and the sum of single-pollutant HIFs for the individual pollutants that constitute the respective pollutant groups., Results: Photochemical modeling predicted large decreases in most of the examined pollutant concentrations between 2011 and 2025 based on sector specific (i.e., source-based) estimates of growth and anticipated controls. Estimated number of avoided asthma ED visits attributable to any given multipollutant group were generally higher when using results from models that included interaction terms in comparison with those that did not. We estimated the greatest number of avoided pediatric asthma ED visits for pollutant groups that include NO 2 (i. e., criteria pollutants, oxidants, and traffic pollutants). In models that accounted for interaction, year-round estimates for pollutant groups that included NO 2 ranged from 27.1 [95% confidence interval (CI): 1.6, 52.7; traffic pollutants] to 55.4 (95% CI: 41.8, 69.0; oxidants) avoided pediatric asthma ED visits. Year-round results using multipollutant risk estimates with interaction were comparable to the sum of the single-pollutant results corresponding to most multipollutant groups [e.g., 52.9 (95% CI: 43.6, 62.2) for oxidants] but were notably lower than the sum of the single-pollutant results for some pollutant groups [e.g., 77.5 (95% CI: 66.0, 89.0) for traffic pollutants]., Discussion: Performing a multipollutant health impact assessment is technically feasible but computationally complex. It requires time, resources, and detailed input parameters not commonly reported in air pollution epidemiological studies. Results estimated using the sum of single-pollutant models are comparable to those quantified using a multipollutant model. Although limited to a single study and location, assessing the trade-offs between a multipollutant and single-pollutant approach is warranted. https://doi.org/10.1289/EHP12969.

Fine particle pollution is a well-established risk to human health. Observational epidemiology generally treats events as though they are independent of one another and so do not examine the role air pollution may play in promoting the progression of disease. Multistate survival models account for the complex pathway of disease to death. We employ a multistate survival model to characterize the role of chronic exposure to PM 2.5 in affecting the rate at which Medicare beneficiaries transition to first hospitalization for cardiovascular disease and then subsequently death. We use an open cohort of Medicare beneficiaries and PM 2.5 concentrations estimated with photochemical model predictions, satellite-based observations, land-use data, and meteorological variables. The multistate model included three transitions: (1) entry to cardiovascular hospital admission; (2) entry to death; and (3) cardiovascular hospital admission to death. The transition intensity was modeled using a Cox proportional hazards model. For a 1 µg/m 3 increase in annual mean PM 2.5 , we estimate a nationally pooled hazard ratio of 1.022 (95% confidence interval [CI] = 1.018, 1.025) for the transition from entry to first cardiovascular hospital admission; 1.054 (95% CI = 1.039, 1.068) for the transition from entry to death; 1.036 (95% CI = 1.027, 1.044) for the transition from first cardiovascular hospital admission to death. The hazard ratios exhibited some heterogeneity within each of nine climatological regions and for each of the three transitions. We find evidence for the role of PM in both promoting chronic illness and increasing the subsequent risk of death., Competing Interests: The authors declare that they have no conflicts of interest with regard to the content of this report.

Epidemiologic studies have consistently observed associations between fine particulate matter (PM 2.5 ) exposure and premature mortality. These studies use air quality concentration information from a combination of sources to estimate pollutant exposures and then assess how mortality varies as a result of differing exposures. Health impact assessments then typically use a single log-linear hazard ratio (HR) per health outcome to estimate counts of avoided human health effects resulting from air quality improvements. This paper estimates the total PM 2.5 -attributable premature mortality burden using a variety of methods for estimating exposures and quantifying PM 2.5 -attributable deaths in 2011 and 2028. We use: 1) several exposure models that apply a wide range of methods, and 2) a variety of HRs from the epidemiologic literature that relate long-term PM 2.5 exposures to mortality among the U.S. population. We then further evaluate the variability of aggregated national premature mortality estimates to stratification by race and/or ethnicity or exposure level (e.g., below the current annual PM 2.5 National Ambient Air Quality Standards). We find that unstratified annual adult mortality burden incidence estimates vary more (e.g., ~3-fold) by HR than by exposure model (e.g., <10%). In addition, future mortality burden estimates stratified by race/ethnicity are larger than the unstratified estimates of the entire population, and studies that stratify PM 2.5 -attributable mortality HRs by an exposure concentration threshold led to substantially higher estimates. These results are intended to provide transparency regarding the sensitivity of mortality estimates to upstream input choices.

Evidence of alterations in emotion processing in maltreated youth has been hypothesized to reflect latent vulnerability for psychopathology. However, previous studies have not systematically examined the influence of psychopathology on the results. Here, we examined emotion recognition and learning in youth who differed in terms of presence vs. absence of maltreatment and psychopathology and tested for potential sex effects. Maltreatment and psychopathology were assessed in 828 youth (514 females) aged 9-18 years using diagnostic interviews and self- and parent-report questionnaires. Emotion recognition was assessed via identification of morphed facial expressions of six universal emotions. For emotion learning, reward and punishment values were assigned to novel stimuli and participants had to learn to correctly respond/withhold response to stimuli to maximize points. A three-way interaction of maltreatment by psychopathology by emotion indicated that when psychopathology was low, maltreated youth were less accurate than non-maltreated youth for happy, fear and disgust. A three-way interaction of sex, maltreatment and emotion indicated that maltreated girls and boys were impaired for fear, but girls showed an impairment for happy, while boys for disgust. There were no effects of maltreatment, psychopathology, or sex on reward learning. However, a two-way interaction between sex and maltreatment showed that maltreated girls were worse at learning from punishment relative to non-maltreated girls, while maltreated boys were better than non-maltreated boys. The study provides the first clear evidence of latent-vulnerability in emotion recognition in maltreated youth and suggests that girls and boys might be characterized by distinct profiles of emotion recognition and learning following maltreatment., (© 2023. The Author(s).)

Atmospheric methane directly affects surface temperatures and indirectly affects ozone, impacting human welfare, the economy, and environment. The social cost of methane (SC-CH 4 ) metric estimates the costs associated with an additional marginal metric ton of emissions. Current SC-CH 4 estimates do not consider the indirect impacts associated with ozone production from changes in methane. We use global model simulations and a new BenMAP webtool to estimate respiratory-related deaths associated with increases in ozone from a pulse of methane emissions in 2020. By using an approach consistent with the current SC-CH 4 framework, we monetize and discount annual damages back to present day values. We estimate that the methane-ozone mechanism is attributable to 760 (95% CI: 330-1200) respiratory-related deaths per million metric tons of methane globally, for a global net present damage of $1800/mT (95% CI: $760-$2800/Mt CH 4 ; 2% Ramsey discount rate); this would double the current SC-CH 4 if included. These physical impacts are consistent with recent studies, but comparing direct costs is challenging. Economic damages are sensitive to uncertainties in the exposure and health risks associated with tropospheric ozone, assumptions about future projections of NO x emissions, socioeconomic conditions, and mortality rates, monetization parameters, and other factors. Our estimates are highly sensitive to uncertainties in ozone health risks. We also develop a reduced form model to test sensitivities to other parameters. The reduced form tool runs with a user-supplied emissions pulse, as well as socioeconomic and precursor projections, enabling future integration of the methane-ozone mechanism into the SC-CH 4 modeling framework.

Reduced-form modeling approaches are an increasingly popular way to rapidly estimate air quality and human health impacts related to changes in air pollutant emissions. These approaches reduce computation time by making simplifying assumptions about pollutant source characteristics, transport and chemistry. Two reduced form tools used by the Environmental Protection Agency in recent assessments are source apportionment-based benefit per ton (SA BPT) and source apportionment-based air quality surfaces (SABAQS). In this work, we apply these two reduced form tools to predict changes in ambient summer-season ozone, ambient annual PM 2.5 component species and monetized health benefits for multiple sector-specific emission control scenarios: on-road mobile, electricity generating units (EGUs), cement kilns, petroleum refineries, and pulp and paper facilities. We then compare results against photochemical grid and standard health model-based estimates. We additionally compare monetized PM 2.5 health benefits to values derived from three reduced form tools available in the literature: the Intervention Model for Air Pollution (InMAP), Air Pollution Emission Experiments and Policy Analysis (APEEP) version 2 (AP2) and Estimating Air pollution Social Impact Using Regression (EASIUR). Ozone and PM 2.5 changes derived from SABAQS for EGU scenarios were well-correlated with values obtained from photochemical modeling simulations with spatial correlation coefficients between 0.64 and 0.89 for ozone and between 0.75 and 0.94 for PM 2.5 . SABAQS ambient ozone and PM 2.5 bias when compared to photochemical modeling predictions varied by emissions scenario: SABAQS PM 2.5 changes were overpredicted by up to 46% in one scenario and underpredicted by up to 19% in another scenario; SABAQS seasonal ozone changes were overpredicted by 34% to 83%. All tools predicted total PM 2.5 benefits within a factor of 2 of the full-form predictions consistent with intercomparisons of reduced form tools available in the literature. As reduced form tools evolve, it is important to continue periodic comparison with comprehensive models to identify systematic biases in estimating air pollution impacts and resulting monetized health benefits., Competing Interests: CONFLICTS OF INTEREST There are no conflicts to declare

Air pollution risk assessments typically estimate ozone-attributable mortality counts using concentration-response (C-R) parameters from epidemiologic studies that treat temperature as a potential confounder. However, some recent epidemiologic studies have indicated that temperature can modify the relationship between short-term ozone exposure and mortality, which has potentially important implications when considering the impacts of climate change on public health. This proof-of-concept analysis quantifies counts of temperature-modified ozone-attributable mortality using temperature-stratified C-R parameters from a multicity study in which the pooled ozone-mortality effect coefficients change in concert with daily temperature. Meteorology downscaled from two global climate models is used with a photochemical transport model to simulate ozone concentrations over the 21st century using two emission inventories: one holding air pollutant emissions constant at 2011 levels and another accounting for reduced emissions through the year 2040. The late century climate models project increased summer season temperatures, which in turn yields larger total counts of ozone-attributable deaths in analyses using temperature-stratified C-R parameters compared to the traditional temperature confounder approach. This analysis reveals substantial heterogeneity in the magnitude and distribution of the temperature-stratified ozone-attributable mortality results, which is a function of regional variability in both the C-R relationship and the model-predicted temperature and ozone.

Background: Much of the current evidence of associations between long-term PM 2.5 and health outcomes relies on national or regional analyses using exposures derived directly from regulatory monitoring data. These findings could be affected by limited spatial coverage of monitoring data, particularly for time periods before spatially extensive monitoring began in the late 1990s. For instance, Pope et al. (2009) showed that between 1980 and 2000 a 10 μg/m 3 reduction in PM 2.5 was associated with an average 0.61 year (standard error (SE) = 0.20) longer life expectancy. That analysis used 1979-1983 averages of PM 2.5 across 51 U.S. Metropolitan Statistical Areas (MSAs) computed from about 130 monitoring sites. Our reanalysis re-examines this association using modeled PM 2.5 in order to assess population- or spatially-representative exposure. We hypothesized that modeled PM 2.5 with finer spatial resolution provides more accurate health effect estimates compared to limited monitoring data., Methods: We used the same data for life expectancy and confounders, as well as the same analysis models, and investigated the same 211 continental U.S. counties, as Pope et al. (2009). For modeled PM 2.5 , we relied on a previously-developed point prediction model based on regulatory monitoring data for 1999-2015 and back-extrapolation to 1979. Using this model, we predicted annual average concentrations at centroids of all 72,271 census tracts and 12,501 25-km national grid cells covering the contiguous U.S., to represent population and space, respectively. We averaged these predictions to the county for the two time periods (1979-1983 and 1999-2000), whereas the original analysis used MSA averages given limited monitoring data. Finally, we estimated regression coefficients for PM 2.5 reduction on life expectancy improvement over the two periods, adjusting for area-level confounders., Results: A 10 μg/m 3 decrease in modeled PM 2.5 based on census tract and national grid predictions was associated with 0.69 (standard error (SE) = 0.31) and 0.81 (0.29) -year increases in life expectancy. These estimates are higher than the estimate of Pope et al. (2009); they also have larger SEs likely because of smaller variability in exposure predictions, a standard property of regression. Two sets of effect estimates, however, had overlapping confidence intervals., Conclusions: Our approach for estimating population- and spatially-representative PM 2.5 concentrations based on census tract and national grid predictions, respectively, provided generally consistent findings to the original findings using limited monitoring data. This finding lends additional support to the evidence that reduced fine particulate matter contributes to extended life expectancy., (© 2021. The Author(s).)

BERNHARD, A., J. S. Mayer, N. Fann, and C. M. Freitag. Cortisol response to acute psychosocial stress in ADHD compared to Conduct Disorder and Major Depressive Disorder: A systematic review. NEUROSCI BIOBEHAV REV XX(X) XXX-XXX, 2020. - Heterogeneous alterations of the cortisol stress response in Attention-deficit/hyperactivity Disorder (ADHD) were recently reported by a systematic literature review. To investigate the moderating effect of frequent psychiatric comorbidities, we systematically searched for studies on cortisol stress response to psychosocial stress in ADHD compared to Conduct Disorder (CD) and Major Depressive Disorder (MDD) following PRISMA guidelines. EBSCOhost and PubMed databases were searched in July 2020, employing relevant keywords. Nineteen studies met inclusion criteria. While blunted cortisol stress response was consistently reported in individuals with CD and/or Oppositional Defiant Disorder (ODD), alterations of cortisol stress response were less pronounced in ADHD. Consistently blunted cortisol stress response in ADHD was only found in children with comorbid CD/ODD. Results on cortisol stress response in children and adolescents with MDD were mixed, and no indication for influence of comorbid MDD on cortisol stress response in ADHD was found. Taken together, altered cortisol stress response in ADHD is driven by comorbidity with disruptive behavior disorders. Limitations of previous research and suggestions for future studies are discussed., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

The risk for major depressive disorder (MDD) is considerably increased in young adults with attention-deficit/hyperactivity disorder (ADHD) but underlying mechanisms are poorly understood. This review explores ADHD-specific neurocognitive impairments as possible underlying mechanisms for ADHD-depression comorbidity. Two systematic literature searches were conducted in EBSCOhost, PubMED, and Cochrane Reviews databases according to PRISMA guidelines. The first search identified 18 meta-analyses of cross-sectional and longitudinal studies on cognitive dysfunctions in MDD across the lifespan. The second search identified six original studies on reaction time variability in MDD. During acute depression, children and adults showed cognitive deficits that overlapped with some of the ADHD-related impairments. Findings from remitted patients, high-risk individuals, and few prospective studies suggest that a subset of these shared impairments, specifically executive dysfunctions (selective attention, verbal fluency, working memory) and long-term memory problems, are candidate pre-existing risk markers of depression. We discuss if and how these specific neurocognitive mechanisms may mediate developmental pathways from ADHD to depression. If replicated by longitudinal studies, these findings may guide future prevention strategies., (Copyright © 2020. Published by Elsevier Ltd.)

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social communication and interaction as well as stereotypical and repetitive behavior. Transcranial direct current stimulation (tDCS) has been proposed as a new intervention method in ASD with the potential to improve cognitive, motor and social communication abilities by targeting specific underlying neuronal alterations. Here, we report results of a systematic literature review on tDCS effects on EEG and behavioral outcomes, and discuss tDCS as treatment option for ASD. PsychInfo, PubMed, ScienceDirect, Web of Science, https://clinicaltrials.gov and the German Clinical Trials Register (Deutsches Register Klinischer Studien) were searched systematically for randomized, sham-controlled clinical trials of tDCS in individuals with ASD, and information regarding study designs and relevant results was extracted. Six eligible studies were identified. The dorsolateral prefrontal cortex (DLPFC) was targeted in four trials, with core ASD symptoms and working memory as outcome measures. One study targeted the primary motor cortex (M1) with motor skills as outcome, and one study targeted the temporoparietal junction (TPJ) with social communication skills as outcome measure. Comparison of the implemented study designs showed high methodological variability between studies regarding stimulation parameters, trial design and outcome measures. Study results indicate initial support for improved cognitive and social communication skills in ASD following tDCS stimulation. However, systematic and comparison studies on the best combination of stimulation intensity, duration, location as well as task related stimulation are necessary, before results can be translated into routine clinical application., Competing Interests: Conflicts of interest statement CMF receives research funding by the German Ministry of Education and Science (BMBF), the German Research Association (DFG), and the European Commission (EC). She receives royalties for books on ASD, ADHD, and MDD. CL's, SB's, MS's and NF's research work is funded by the EC., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Rationale: Approximately 8% of the U.S. population suffers from asthma, a chronic condition. It poses a substantial economic burden to society in the form of lost productivity and healthcare costs. Objectives: We use the Medical Expenditure Panel Survey 2002-2010 to quantify the lifetime costs of asthma at each age, the impact of adult asthma on earnings and choice of occupation, and the impact of childhood asthma on parental income. Methods: We developed a framework to estimate the present discounted value of the cumulative lifetime asthma-related healthcare costs and lost productivity experienced by an individual after onset. This approach allows for age- and asthma duration-related variability in annual costs as well as for the intermittent nature of asthma symptoms. Results: Estimated asthma-related annual healthcare expenditures across all life stages are $700-$2,200 (2010 U.S. dollars). Lost annual earnings among individuals aged 30-49 are over $4,000 (2010 U.S. dollars). The present discounted value of the cumulative lifetime healthcare costs and lost productivity for a new case of asthma is estimated at $36,500 using the 3% discount rate (2010 U.S. dollars). Conclusions: The economic burden of asthma is substantial and larger than previously estimated, reflecting expenditures on treatment and lost earnings.

Macpherson et al. (2017) presented a mathematical programming model that identifies minimum-cost control strategies that reduce emissions regionally to meet ambient air quality targets. This project introduces the Cost And Benefit Optimization Tool for Ozone (CABOT-O 3 ), which extends the previous model by updating emissions and air quality relationships, adding a health impacts module, and quantifying distributional impacts. The tool draws upon source apportionment photochemical air quality modeling to characterize the contribution of emissions reductions to ambient ozone concentrations across the contiguous United States. The health impacts analysis module estimates the change in the number and economic value of premature deaths using modeled changes in ozone levels resulting from the application of emission control strategies. These extensions allow us to evaluate strategies to attain ozone air quality standards at minimum cost or to maximize net benefit, while assessing the change in the distribution of health impacts. In a case study applied to stationary pollution sources, we find that, when compared to minimizing costs to meet a uniform ozone standard, maximizing net benefits results in greater emissions and ozone concentration reductions in some parts of the country and fewer in others. Our results highlight potential equity-efficiency trade-offs in designing air quality policies.

Mobile sources emit particulate matter as well as precursors to particulate matter (PM 2.5 ) and ground-level ozone, pollutants known to adversely impact human health. This study uses source-apportionment photochemical air quality modeling to estimate the health burden (expressed as incidence) of an array of PM 2.5 - and ozone-related adverse health impacts, including premature death, attributable to 17 mobile source sectors in the US in 2011 and 2025. Mobile sector-attributable air pollution contributes a substantial fraction of the overall pollution-related mortality burden in the U.S., accounting for about 20% of the PM 2.5 and ozone-attributable deaths in 2011 (between 21 000 and 55 000 deaths, depending on the study used to derive the effect estimate). This value falls to about 13% (between 13 000 and 37 000 deaths) by 2025 due to regulatory and voluntary programs reducing emissions from mobile sources. Similar trends across all morbidity health impacts can also be observed. Emissions from on-road sources are the largest contributor to premature deaths; this is true for both 2011 (between 12 000 and 31 000 deaths) and 2025 (between 6700 and 18 000 deaths). Non-road construction engines, C3 marine engines and emissions from rail also contribute to large portions of premature deaths. Across the 17 mobile sectors modeled, the PM 2.5 -attributable mortality and morbidity burden falls between 2011 and 2025 for 12 sectors and increases for 5. Ozone-attributable mortality and morbidity burden increases between 2011 and 2025 for 10 sectors and falls for 7. These results extend the literature beyond generally aggregated mobile sector health burden toward a representation of highly-resolved source characterization of both current and future health burden. The quantified future mobile source health burden is a novel feature of this analysis and could prove useful for decisionmakers and affected stakeholders.

Scientific evidence spanning experimental and epidemiologic studies has shown that air pollution exposures can lead to a range of health effects. Quantitative approaches that allow for the estimation of the adverse health impacts attributed to air pollution enable researchers and policy analysts to convey the public health impact of poor air quality. Multiple tools are currently available to conduct such analyses, which includes software packages designed by the World Health Organization (WHO): AirQ+, and the U.S. Environmental Protection Agency (U.S. EPA): Environmental Benefits Mapping and Analysis Program - Community Edition (BenMAP - CE), to quantify the number and economic value of air pollution-attributable premature deaths and illnesses. WHO's AirQ+ and U.S. EPA's BenMAP - CE are among the most popular tools to quantify these effects as reflected by the hundreds of peer-reviewed publications and technical reports over the past two decades that have employed these tools spanning many countries and multiple continents. Within this paper we conduct an analysis using common input parameters to compare AirQ+ and BenMAP - CE and show that the two software packages well align in the calculation of health impacts. Additionally, we detail the research questions best addressed by each tool., Competing Interests: Conflicts of Interest: The authors declare no conflict of interest.

Ozone exposure is associated with higher risk of asthma-related emergency department visits. The meteorological conditions that govern ozone concentration are projected to be more favorable to ozone formation over much of the United States due to continued climate change, even as emissions of anthropogenic ozone precursors are expected to decrease by 2050. Our goal is to quantify the health benefits of a climate change mitigation scenario versus a "business-as-usual" scenario, defined by the United Nations Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs) 4.5 and 8.5, respectively, using the health impact analytical program Benefits Mapping and Analysis Program - Community Edition (BenMAP - CE) to project the number of asthma ED visits in 2045-2055. We project an annual average of 3100 averted ozone-related asthma ED visits during the 2045-2055 period under RCP4.5 versus RCP8.5, with all other factors held constant, which translates to USD $1.7 million in averted costs annually. We identify counties with tens to hundreds of avoided ozone-related asthma ED visits under RCP4.5 versus RCP8.5. Overall, we project a heterogeneous distribution of ozone-related asthma ED visits at different spatial resolutions, specifically national, regional, and county levels, and a substantial net health and economic benefit of climate change mitigation., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Policy analysts and researchers often use models to translate expected emissions changes from pollution control policies to estimates of air pollution changes and resulting changes in health impacts. These models can include both photochemical Eulerian grid models or reduced complexity models; these latter models make simplifying assumptions about the emissions-to-air quality relationship as a means of reducing the computational time needed to simulate air quality. This manuscript presents a new database of photochemical- and reduced complexity-modelled changes in annual average particulate matter with aerodynamic diameter less than 2.5 μm and associated health effects and economic values for five case studies representing different emissions control scenarios. The research community is developing an increasing number of reduced complexity models as lower-cost and more expeditious alternatives to full form Eulerian photochemical grid models such as the Comprehensive Air-Quality Model with eXtensions (CAMx) and the Community Multiscale Air Quality (CMAQ) model. A comprehensive evaluation of reduced complexity models can demonstrate the extent to which these tools capture complex chemical and physical processes when representing emission control options. Systematically comparing reduced complexity model predictions to benchmarks from photochemical grid models requires a consistent set of input parameters across all systems. Developing such inputs is resource intensive and consequently the data that we have developed and shared (https://github.com/epa-kpc/RFMEVAL) provide a valuable resource for others to evaluate reduced complexity models. The dataset includes inputs and outputs representing 5 emission control scenarios, including sector-based regulatory policy scenarios focused on on-road mobile sources and electrical generating units (EGUs) as well as hypothetical across-the-board reductions to emissions from cement kilns, refineries, and pulp and paper facilities. Model inputs, outputs, and run control files are provided for the Air Pollution Emission Experiments and Policy Analysis (APEEP) version 2 and 3, Intervention Model for Air Pollution (InMAP), Estimating Air pollution Social Impact Using Regression (EASIUR), and EPA's source apportionment benefit-per-ton reduced complexity models. For comparison, photochemical grid model annual average PM 2.5 output is provided for each emission scenario. Further, inputs are also provided for the Environmental Benefits and Mapping Community Edition (BenMAP-CE) tool to generate county level health benefits and monetized health damages along with output files for benchmarking and intercomparison. Monetized health impacts are also provided from EASIUR and APEEP which can provide these outside the BenMAP-CE framework. The database will allow researchers to more easily compare reduced complexity model predictions against photochemical grid model predictions.

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 PM 10 (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 PM 10 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., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

By-products of mobile source combustion processes, such as those associated with gasoline- and diesel-powered engines, include direct emissions of particulate matter as well as precursors to particulate matter and ground-level ozone. Human exposure to fine particulate matter with an aerodynamic diameter smaller than 2.5 μm (PM 2.5 ) is associated with increased incidence of premature mortality and morbidity outcomes. This study builds upon recent, detailed source-apportionment air quality modeling to project the health-related benefits of reducing PM 2.5 from mobile sources across the contiguous U.S. in 2025. Updating a previously published benefits analysis approach, we develop national-level benefit per ton estimates for directly emitted PM 2.5 , SO 2 /pSO 4 , and NO X for 16 mobile source sectors spanning onroad vehicles, nonroad engines and equipment, trains, marine vessels, and aircraft. These benefit per ton estimates provide a reduced-form tool for estimating and comparing benefits across multiple mobile source emission scenarios and can be applied to assess the benefits of mobile source policies designed to improve air quality. We found the benefit per ton of directly emitted PM 2.5 in 2025 ranges from $110,000 for nonroad agriculture sources to $700,000 for onroad light duty gas cars and motorcycles (in 2015 dollars and based on an estimate of PM-related mortality derived from the American Cancer Society cohort study). Benefit per ton values for SO 2 /pSO 4 range from $52,000 for aircraft sources (including emissions from ground support vehicles) to $300,000 for onroad light duty diesel emissions. Benefit per ton values for NO X range from $2100 for C1 and C2 marine vessels to $7500 for "nonroad all other" mobile sources, including industrial, logging, and oil field sources. Benefit per ton estimates increase approximately 2.26-fold when using an alternative concentration response function to derive PM 2.5 -related mortality. We also report benefit per ton values for the eastern and western U.S. to account for broad spatial heterogeneity patterns in emissions reductions, population exposure and air quality benefits., (Published by Elsevier B.V.)

Pollen is an important environmental cause of allergic asthma episodes. Prior work has established a proof of concept for assessing projected climate change impacts on future oak pollen exposure and associated health impacts. This paper uses additional monitor data and epidemiologic functions to extend prior analyses, reporting new estimates of the current and projected future health burden of oak, birch, and grass pollen across the contiguous United States. Our results suggest that tree pollen in the spring currently accounts for between 25,000 and 50,000 pollen-related asthma emergency department (ED) visits annually (95% confidence interval: 14,000 to 100,000), roughly two thirds of which occur among people under age 18. Grass pollen in the summer season currently accounts for less than 10,000 cases annually (95% confidence interval: 4,000 to 16,000). Compared to a baseline with 21st century population growth but constant pollen, future temperature and precipitation show an increase in ED visits of 14% in 2090 for a higher greenhouse gas emissions scenario, but only 8% for a moderate emissions scenario, reflecting projected increases in pollen season length. Grass pollen, which is more sensitive to changes in climatic conditions, is a primary contributor to future ED visits, with the largest effects in the Northeast, Midwest, and Southern Great Plains regions. More complete assessment of the current and future health burden of pollen is limited by the availability of data on pollen types (e.g., ragweed), other health effects (e.g., other respiratory disease), and economic consequences (e.g., medication costs).

The U.S. Southwest is projected to experience increasing aridity due to climate change. We quantify the resulting impacts on ambient dust levels and public health using methods consistent with the Environmental Protection Agency's Climate Change Impacts and Risk Analysis framework. We first demonstrate that U.S. Southwest fine (PM 2.5 ) and coarse (PM 2.5-10 ) dust levels are strongly sensitive to variability in the 2-month Standardized Precipitation-Evapotranspiration Index across southwestern North America. We then estimate potential changes in dust levels through 2099 by applying the observed sensitivities to downscaled meteorological output projected by six climate models following an intermediate (Representative Concentration Pathway 4.5, RCP4.5) and a high (RCP8.5) greenhouse gas concentration scenario. By 2080-2099 under RCP8.5 relative to 1986-2005 in the U.S. Southwest: (1) Fine dust levels could increase by 57%, and fine dust-attributable all-cause mortality and hospitalizations could increase by 230% and 360%, respectively; (2) coarse dust levels could increase by 38%, and coarse dust-attributable cardiovascular mortality and asthma emergency department visits could increase by 210% and 88%, respectively; (3) climate-driven changes in dust concentrations can account for 34-47% of these health impacts, with the rest due to increases in population and baseline incidence rates; and (4) economic damages of the health impacts could total $47 billion per year additional to the 1986-2005 value of $13 billion per year. Compared to national-scale climate impacts projected for other U.S. sectors using the Climate Change Impacts and Risk Analysis framework, dust-related mortality ranks fourth behind extreme temperature-related mortality, labor productivity decline, and coastal property loss., Competing Interests: Conflict of Interest The authors declare no conflicts of interest relevant to this study.

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., (Published by Elsevier Inc.)

Recent assessments have found that a warming climate, with associated increases in extreme heat events, could profoundly affect human health. This paper describes a new modeling and analysis framework, built around the Benefits Mapping and Analysis Program-Community Edition (BenMAP), for estimating heat-related mortality as a function of changes in key factors that determine the health impacts of extreme heat. This new framework has the flexibility to integrate these factors within health risk assessments, and to sample across the uncertainties in them, to provide a more comprehensive picture of total health risk from climate-driven increases in extreme heat. We illustrate the framework's potential with an updated set of projected heat-related mortality estimates for the United States. These projections combine downscaled Coupled Modeling Intercomparison Project 5 (CMIP5) climate model simulations for Representative Concentration Pathway (RCP)4.5 and RCP8.5, using the new Locating and Selecting Scenarios Online (LASSO) tool to select the most relevant downscaled climate realizations for the study, with new population projections from EPA's Integrated Climate and Land Use Scenarios (ICLUS) project. Results suggest that future changes in climate could cause approximately from 3000 to more than 16,000 heat-related deaths nationally on an annual basis. This work demonstrates that uncertainties associated with both future population and future climate strongly influence projected heat-related mortality. This framework can be used to systematically evaluate the sensitivity of projected future heat-related mortality to the key driving factors and major sources of methodological uncertainty inherent in such calculations, improving the scientific foundations of risk-based assessments of climate change and human health.

Background: Asthma is the most prevalent chronic respiratory disease worldwide, affecting 358 million people in 2015. Ambient air pollution exacerbates asthma among populations around the world and may also contribute to new-onset asthma., Objectives: We aimed to estimate the number of asthma emergency room visits and new onset asthma cases globally attributable to fine particulate matter ([Formula: see text]), ozone, and nitrogen dioxide ([Formula: see text]) concentrations., Methods: We used epidemiological health impact functions combined with data describing population, baseline asthma incidence and prevalence, and pollutant concentrations. We constructed a new dataset of national and regional emergency room visit rates among people with asthma using published survey data., Results: We estimated that 9–23 million and 5–10 million annual asthma emergency room visits globally in 2015 could be attributable to ozone and [Formula: see text], respectively, representing 8–20% and 4–9% of the annual number of global visits, respectively. The range reflects the application of central risk estimates from different epidemiological meta-analyses. Anthropogenic emissions were responsible for [Formula: see text] and 73% of ozone and [Formula: see text] impacts, respectively. Remaining impacts were attributable to naturally occurring ozone precursor emissions (e.g., from vegetation, lightning) and [Formula: see text] (e.g., dust, sea salt), though several of these sources are also influenced by humans. The largest impacts were estimated in China and India., Conclusions: These findings estimate the magnitude of the global asthma burden that could be avoided by reducing ambient air pollution. We also identified key uncertainties and data limitations to be addressed to enable refined estimation. https://doi.org/10.1289/EHP3766.

Exposure to ambient fine particulate matter (PM 2.5 ) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM 2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM 2.5 -mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM 2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM 2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations., Competing Interests: Conflict of interest statement: J.V.S. is an independent consultant and not benefiting commercially from the results of this research., (Copyright © 2018 the Author(s). Published by PNAS.)

Incomplete information regarding emissions from oil and natural gas production has historically made it challenging to characterize the air quality or air pollution-related health impacts for this sector in the United States. Using an emissions inventory for the oil and natural gas sector that reflects information regarding the level and distribution of PM 2.5 and ozone precursor emissions, we simulate annual mean PM 2.5 and summer season average daily 8 h maximum ozone concentrations with the Comprehensive Air-Quality Model with extensions (CAMx). We quantify the incidence and economic value of PM 2.5 and ozone health related effects using the environmental Benefits Mapping and Analysis Program (BenMAP). We find that ambient concentrations of PM 2.5 and ozone, and associated health impacts, are highest in a handful of states including Colorado, Pennsylvania, Texas and West Virginia. On a per-ton basis, the benefits of reducing PM 2.5 precursor emissions from this sector vary by pollutant species, and range from between $6,300 and $320,000, while the value of reducing ozone precursors ranges from $500 to $8,200 in the year 2025 (2015$).

Objectives: To demonstrate the benefits-mapping software Environmental Benefits Mapping and Analysis Program-Community Edition (BenMAP-CE), which integrates local air quality data with previously published concentration-response and health-economic valuation functions to estimate the health effects of changes in air pollution levels and their economic consequences., Methods: We illustrate a local health impact assessment of ozone changes in the 10-county nonattainment area of the Dallas-Fort Worth region of Texas, estimating the short-term effects on mortality predicted by 2 scenarios for 3 years (2008, 2011, and 2013): an incremental rollback of the daily 8-hour maximum ozone levels of all area monitors by 10 parts per billion and a rollback-to-a-standard ambient level of 65 parts per billion at only monitors above that level., Results: Estimates of preventable premature deaths attributable to ozone air pollution obtained by the incremental rollback method varied little by year, whereas those obtained by the rollback-to-a-standard method varied by year and were sensitive to the choice of ordinality and the use of preloaded or imported data., Conclusions: BenMAP-CE allows local and regional public health analysts to generate timely, evidence-based estimates of the health impacts and economic consequences of potential policy options in their communities.

[This corrects the article DOI: https://doi.org/10.1289/EHP507.].

A number of software tools exist to estimate the health and economic impacts associated with air quality changes. Over the past 15 years, the U.S. Environmental Protection Agency and its partners invested substantial time and resources in developing the Environmental Benefits Mapping and Analysis Program - Community Edition (BenMAP-CE). BenMAP-CE is a publicly available, PC-based open source software program that can be configured to conduct health impact assessments to inform air quality policies anywhere in the world. The developers coded the platform in C# and made the source code available in GitHub, with the goal of building a collaborative relationship with programmers with expertise in other environmental modeling programs. The team recently improved the BenMAP-CE user experience and incorporated new features, while also building a cadre of analysts and BenMAP-CE training instructors in Latin America and Southeast Asia., Competing Interests: Competing interests The authors declare they have no competing financial interests.

Introduction: Wildland fires degrade air quality and adversely affect human health. A growing body of epidemiology literature reports increased rates of emergency departments, hospital admissions and premature deaths from wildfire smoke exposure., Objective: Our research aimed to characterize excess mortality and morbidity events, and the economic value of these impacts, from wildland fire smoke exposure in the U.S. over a multi-year period; to date no other burden assessment has done this., Methods: We first completed a systematic review of the epidemiologic literature and then performed photochemical air quality modeling for the years 2008 to 2012 in the continental U.S. Finally, we estimated the morbidity, mortality, and economic burden of wildland fires., Results: Our models suggest that areas including northern California, Oregon and Idaho in the West, and Florida, Louisiana and Georgia in the East were most affected by wildland fire events in the form of additional premature deaths and respiratory hospital admissions. We estimated the economic value of these cases due to short term exposures as being between $11 and $20B (2010$) per year, with a net present value of $63B (95% confidence intervals $6-$170); we estimate the value of long-term exposures as being between $76 and $130B (2010$) per year, with a net present value of $450B (95% confidence intervals $42-$1200)., Conclusion: The public health burden of wildland fires-in terms of the number and economic value of deaths and illnesses-is considerable., (Published by Elsevier B.V.)

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.

Future climate change is expected to lengthen and intensify pollen seasons in the U.S., potentially increasing incidence of allergic asthma. We developed a proof-of-concept approach for estimating asthma emergency department (ED) visits in the U.S. associated with present-day and climate-induced changes in oak pollen. We estimated oak pollen season length for moderate (Representative Concentration Pathway (RCP) 4.5) and severe climate change scenarios (RCP8.5) through 2090 using five climate models and published relationships between temperature, precipitation, and oak pollen season length. We calculated asthma ED visit counts associated with 1994-2010 average oak pollen concentrations and simulated future oak pollen season length changes using the Environmental Benefits Mapping and Analysis Program, driven by epidemiologically derived concentration-response relationships. Oak pollen was associated with 21,200 (95% confidence interval, 10,000-35,200) asthma ED visits in the Northeast, Southeast, and Midwest U.S. in 2010, with damages valued at $10.4 million. Nearly 70% of these occurred among children age <18 years. Severe climate change could increase oak pollen season length and associated asthma ED visits by 5% and 10% on average in 2050 and 2090, with a marginal net present value through 2090 of $10.4 million (additional to the baseline value of $346.2 million). Moderate versus severe climate change could avoid >50% of the additional oak pollen-related asthma ED visits in 2090. Despite several key uncertainties and limitations, these results suggest that aeroallergens pose a substantial U.S. public health burden, that climate change could increase U.S. allergic disease incidence, and that mitigating climate change may have benefits from avoided pollen-related health impacts., (©2017. The Authors.)

The magnitude, shape, and degree of certainty in the association between long-term population exposure to ambient fine particulate matter (PM2.5 ) and the risk of premature death is one of the most intensely studied issues in environmental health. For regulatory risk analysis, this relationship is described quantitatively by a concentration-response (C-R) function that relates exposure to ambient concentrations with the risk of premature mortality. Four data synthesis techniques develop the basis for, and derive, this function: systematic review, expert judgment elicitation, quantitative meta-analysis, and integrated exposure-response (IER) assessment. As part of an academic workshop aiming to guide the use of research synthesis approaches, we developed criteria with which to evaluate and select among the approaches for their ability to inform policy choices. These criteria include the quality and extent of scientific support for the method, its transparency and verifiability, its suitability to the policy problem, and the time and resources required for its application. We find that these research methods are both complementary and interdependent. A systematic review of the multidisciplinary evidence is a starting point for all methods, providing the broad conceptual basis for the nature, plausibility, and strength of the associations between PM exposure and adverse health effects. Further, for a data-rich application like PM2.5 and premature mortality, all three quantitative approaches can produce estimates that are suitable for regulatory and benefit analysis. However, when fewer data are available, more resource-intensive approaches such as expert elicitation may be more important for understanding what scientists know, where they agree or disagree, and what they believe to be the most important areas of uncertainty. Whether implicitly or explicitly, all require considerable judgment by scientists. Finding ways for all these methods to acknowledge, appropriately elicit, and examine the implications of that judgment would be an important step forward for research synthesis., (© 2015 Society for Risk Analysis.)

Designing air quality policies that improve public health can benefit from information about air pollution health risks and impacts, which include respiratory and cardiovascular diseases and premature death. Several computer-based tools help automate air pollution health impact assessments and are being used for a variety of contexts. Expanding information gathered for a May 2014 World Health Organization expert meeting, we survey 12 multinational air pollution health impact assessment tools, categorize them according to key technical and operational characteristics, and identify limitations and challenges. Key characteristics include spatial resolution, pollutants and health effect outcomes evaluated, and method for characterizing population exposure, as well as tool format, accessibility, complexity, and degree of peer review and application in policy contexts. While many of the tools use common data sources for concentration-response associations, population, and baseline mortality rates, they vary in the exposure information source, format, and degree of technical complexity. We find that there is an important tradeoff between technical refinement and accessibility for a broad range of applications. Analysts should apply tools that provide the appropriate geographic scope, resolution, and maximum degree of technical rigor for the intended assessment, within resources constraints. A systematic intercomparison of the tools' inputs, assumptions, calculations, and results would be helpful to determine the appropriateness of each for different types of assessment. Future work would benefit from accounting for multiple uncertainty sources and integrating ambient air pollution health impact assessment tools with those addressing other related health risks (e.g., smoking, indoor pollution, climate change, vehicle accidents, physical activity)., (© 2016 Society for Risk Analysis.)

The effectiveness of regulatory actions designed to improve air quality is often assessed by predicting changes in public health resulting from their implementation. Risk of premature mortality from long-term exposure to ambient air pollution is the single most important contributor to such assessments and is estimated from observational studies generally assuming a log-linear, no-threshold association between ambient concentrations and death. There has been only limited assessment of this assumption in part because of a lack of methods to estimate the shape of the exposure-response function in very large study populations. In this paper, we propose a new class of variable coefficient risk functions capable of capturing a variety of potentially non-linear associations which are suitable for health impact assessment. We construct the class by defining transformations of concentration as the product of either a linear or log-linear function of concentration multiplied by a logistic weighting function. These risk functions can be estimated using hazard regression survival models with currently available computer software and can accommodate large population-based cohorts which are increasingly being used for this purpose. We illustrate our modeling approach with two large cohort studies of long-term concentrations of ambient air pollution and mortality: the American Cancer Society Cancer Prevention Study II (CPS II) cohort and the Canadian Census Health and Environment Cohort (CanCHEC). We then estimate the number of deaths attributable to changes in fine particulate matter concentrations over the 2000 to 2010 time period in both Canada and the USA using both linear and non-linear hazard function models., Competing Interests: The authors declare that they have no competing financial interests.

Among industrialised countries, fine particle (PM2.5) and ozone levels in the Sydney metropolitan area of Australia are relatively low. Annual mean PM2.5 levels have historically remained below 8 μg/m(3) while warm season (November-March) ozone levels occasionally exceed the Australian guideline value of 0.10 ppm (daily 1 h max). Yet, these levels are still below those seen in the United States and Europe. This analysis focuses on two related questions: (1) what is the public health burden associated with air pollution in Sydney; and (2) to what extent would reducing air pollution reduce the number of hospital admissions, premature deaths and number of years of life lost (YLL)? We addressed these questions by applying a damage function approach to Sydney population, health, PM2.5 and ozone data for 2007 within the BenMAP-CE software tool to estimate health impacts and economic benefits. We found that 430 premature deaths (90% CI: 310-540) and 5800 YLL (95% CI: 3900-7600) are attributable to 2007 levels of PM2.5 (about 2% of total deaths and 1.8% of YLL in 2007). We also estimate about 630 (95% CI: 410-840) respiratory and cardiovascular hospital admissions attributable to 2007 PM2.5 and ozone exposures. Reducing air pollution levels by even a small amount will yield a range of health benefits. Reducing 2007 PM2.5 exposure in Sydney by 10% would, over 10 years, result in about 650 (95% CI: 430-850) fewer premature deaths, a gain of 3500 (95% CI: 2300-4600) life-years and about 700 (95% CI: 450-930) fewer respiratory and cardiovascular hospital visits. These results suggest that substantial health benefits are attainable in Sydney with even modest reductions in air pollution., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Unlabelled: In this United States-focused analysis we use outputs from two general circulation models (GCMs) driven by different greenhouse gas forcing scenarios as inputs to regional climate and chemical transport models to investigate potential changes in near-term U.S. air quality due to climate change. We conduct multiyear simulations to account for interannual variability and characterize the near-term influence of a changing climate on tropospheric ozone-related health impacts near the year 2030, which is a policy-relevant time frame that is subject to fewer uncertainties than other approaches employed in the literature. We adopt a 2030 emissions inventory that accounts for fully implementing anthropogenic emissions controls required by federal, state, and/or local policies, which is projected to strongly influence future ozone levels. We quantify a comprehensive suite of ozone-related mortality and morbidity impacts including emergency department visits, hospital admissions, acute respiratory symptoms, and lost school days, and estimate the economic value of these impacts. Both GCMs project average daily maximum temperature to increase by 1-4°C and 1-5 ppb increases in daily 8-hr maximum ozone at 2030, though each climate scenario produces ozone levels that vary greatly over space and time. We estimate tens to thousands of additional ozone-related premature deaths and illnesses per year for these two scenarios and calculate an economic burden of these health outcomes of hundreds of millions to tens of billions of U.S. dollars (2010$)., Implications: Near-term changes to the climate have the potential to greatly affect ground-level ozone. Using a 2030 emission inventory with regional climate fields downscaled from two general circulation models, we project mean temperature increases of 1 to 4°C and climate-driven mean daily 8-hr maximum ozone increases of 1-5 ppb, though each climate scenario produces ozone levels that vary significantly over space and time. These increased ozone levels are estimated to result in tens to thousands of ozone-related premature deaths and illnesses per year and an economic burden of hundreds of millions to tens of billions of U.S. dollars (2010$).

Many time-series studies have characterized the relationship between short-term ozone exposure and adverse health outcomes, controlling for temperature as a confounder. Temperature may also modify ozone effects, though this has been largely under-investigated. In this study, we explored whether temperature modifies the effect of short-term ozone exposure on mortality. We used the database developed for the National Morbidity and Mortality Air Pollution Study to estimate ozone mortality risks in 97 US cities in May through September, 1987-2000. We treated temperature as a confounder as well as an effect modifier by estimating risks at low, moderate, and high temperature categories. When temperature was treated as a confounder, a 10-ppb increase in daily 24-h ozone was associated with a 0.47% (95% CI: 0.19%-0.76%) increase in mortality. When we assessed effect modification by temperature, the interaction between ozone and temperature was not statistically significant. However, there was a U-shaped pattern in mortality risk, which was greater at the low (<25th percentile) and high (>75th percentile) temperature levels than moderate temperature levels. At the high temperature category, a 10% increase in AC prevalence mitigated mortality risk associated with 10-ppb of ozone exposure by -0.18% (95% CI: -0.35%, -0.02%). Furthermore, ozone mortality risk in the high temperature category increased as we restricted our analyses to hotter days. On days where temperatures exceeded the 75th, 90th, and 95th percentile temperatures, a 10-ppb increase in ozone was associated with a 0.65% (95% CI: 0.20%-1.09%), 0.83% (95% CI: 0.17%-1.48%), and 1.35% (95% CI: 0.44%-2.27%) increase in mortality, respectively. These results suggested that high temperatures may exacerbate physiological responses to short-term ozone exposure., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Background: Epidemiologic studies find that long- and short-term exposure to fine particles (PM2.5) is associated with adverse cardiovascular outcomes, including ischemic and hemorrhagic strokes. However, few systematic reviews or meta-analyses have synthesized these results., Methods: We reviewed epidemiologic studies that estimated the risks of nonfatal strokes attributable to ambient PM2.5. To pool risks among studies we used a random-effects model and 2 Bayesian approaches. The first Bayesian approach assumes a normal prior that allows risks to be zero, positive or negative. The second assumes a gamma prior, where risks can only be positive. This second approach is proposed when the number of studies pooled is small, and there is toxicological or clinical literature to support a causal relation., Results: We identified 20 studies suitable for quantitative meta-analysis. Evidence for publication bias is limited. The frequentist meta-analysis produced pooled risk ratios of 1.06 (95% confidence interval = 1.00-1.13) and 1.007 (1.003-1.010) for long- and short-term effects, respectively. The Bayesian meta-analysis found a posterior mean risk ratio of 1.08 (95% posterior interval = 0.96-1.26) and 1.008 (1.003-1.013) from a normal prior, and of 1.05 (1.02-1.10) and 1.008 (1.004-1.013) from a gamma prior, for long- and short-term effects, respectively, per 10 μg/m PM2.5., Conclusions: Sufficient evidence exists to develop a concentration-response relation for short- and long-term exposures to PM2.5 and stroke incidence. Long-term exposures to PM2.5 result in a higher risk ratio than short-term exposures, regardless of the pooling method. The evidence for short-term PM2.5-related ischemic stroke is especially strong.