Publications by authors named "Neal Fann"

Wind energy projects are being planned and constructed off the northern Atlantic coast to provide additional energy capacity to the eastern U.S. Emissions related to construction, operation, and routine maintenance of these offshore wind projects and the chemical transformation of these emissions in the atmosphere can result in pollutants that have known negative human health effects.

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Climate change has increased forest fire extent in temperate and boreal North America. Here, we quantified the contribution of anthropogenic climate change to human mortality and economic burden from exposure to wildfire particulate matter at the county and state level across the contiguous US (2006 to 2020) by integrating climate projections, climate-wildfire models, wildfire smoke models, and emission and health impact modeling. Climate change contributed to approximately 15,000 wildfire particulate matter deaths over 15 years with interannual variability ranging from 130 (95% confidence interval: 64, 190) to 5100 (95% confidence interval: 2500, 7500) deaths and a cumulative economic burden of $160 billion.

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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.

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We evaluated the sensitivity of estimated PM and NO 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, but not PM, attributable deaths. Using county-level predictions instead of 1 km predictions of NO resulted in a lower estimate of mortality attributable to NO by ∼ 50 % for all of Colorado for each year between 2000 and 2020.

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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.

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Epidemiologic studies have consistently observed associations between fine particulate matter (PM) 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.

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Atmospheric methane directly affects surface temperatures and indirectly affects ozone, impacting human welfare, the economy, and environment. The social cost of methane (SC-CH) metric estimates the costs associated with an additional marginal metric ton of emissions. Current SC-CH estimates do not consider the indirect impacts associated with ozone production from changes in methane.

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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).

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Exposure to fine particulate matter (PM) is associated with asthma development as well as asthma exacerbation in children. PM can be directly emitted or can form in the atmosphere from pollutant precursors. PM emitted and formed in the atmosphere is influenced by meteorology; future changes in climate may alter the concentration and distribution of PM.

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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.

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Background: Much of the current evidence of associations between long-term PM 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.

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Mobile sources emit particulate matter as well as precursors to particulate matter (PM) 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- 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.

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Importance: Future changes in climate are likely to adversely affect human health by affecting concentrations of particulate matter sized less than 2.5 μm (PM2.5) and ozone (O3) in many areas.

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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), which extends the previous model by updating emissions and air quality relationships, adding a health impacts module, and quantifying distributional impacts.

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Approximately 8% of the U.S. population suffers from asthma, a chronic condition.

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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.

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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.

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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.

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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.

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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.

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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 (), ozone, and nitrogen dioxide () concentrations.

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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.

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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) is associated with increased incidence of premature mortality and morbidity outcomes.

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Exposure to ambient fine particulate matter (PM) 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 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-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range.

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