Modeling contributions of major sources to local and regional air pollutant exposures and health impacts
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Elevated concentrations of ambient fine particulate matter (PM2.5) and ozone (O3) contribute to adverse health outcomes in exposed populations. Anthropogenic source sectors, including aviation, residential combustion (RC), and electricity generating units (EGUs), lead to increased concentrations of these combustion-related pollutants. Quantification of the influence of emissions from specific source sectors on ambient pollutant concentrations can be very useful in better informing public health policy decision making on air quality improvements. Due to complex emissions dynamics, background concentrations, and meteorology, determining contributions of these sources to related health risks is challenging. To assess local impacts of aviation activity, concentrations of nitrogen oxides (NOx) and the PM2.5 constituent black carbon (BC) were monitored near airports. Moreover, aviation-attributable fractions were derived from monitored concentrations using regression modeling, and values were compared with predicted aviation-attributable concentrations from a near-field dispersion model. Regional impacts of aviation, RC, and EGUs were assessed using the Community Multiscale Air Quality (CMAQ) atmospheric chemistry and transport model with the Direct Decoupled Method (DDM) to determine sensitivity of ambient PM2.5 and O3 concentrations to emissions from individual sources. Health damage functions, quantified as mortality per thousand tons of emitted precursor species, were created by individual airport for 66 of the highest fuel-burning airports in the United States and by state for RC and EGUs. Physically-interpretable regression models were built to predict aviation-related health damage functions. With local aviation, comparisons of regression-predicted and dispersion-predicted BC and NOx concentrations are similar when aggregated, though diurnal patterns show potential weaknesses in near-field dispersion and emissions inventory accuracy. For regional aviation impacts, health damage function values varied by more than an order of magnitude across airports for each precursor-ambient pollutant pair, with seasonal effects present in secondary pollutant formation. Health damage functions were predicted by combinations of upwind and downwind population, meteorology, and atmospheric chemistry regime. State-resolution contributions of RC and EGUs varied both within and between source sectors, based on local characteristics including population density and EGU location. These findings reinforce the importance of quantification of source-specific air quality and health impacts in the design of health-maximizing emissions control policies.