Hybrid Modeling Approach to Estimate Exposures of Hazardous Air Pollutants (HAPs) for the National Air Toxics Assessment (NATA)

A hybrid air quality model has been developed and applied to estimate annual concentrations of 40 hazardous air pollutants (HAPs) across the continental United States (CONUS) to support the 2011 calendar year National Air Toxics Assessment (NATA). By combining a chemical transport model (CTM) with a Gaussian dispersion model, both reactive and nonreactive HAPs are accommodated across local to regional spatial scales, through a multiplicative technique designed to improve mass conservation relative to previous additive methods. The broad scope of multiple pollutants capturing regional to local spatial scale patterns across a vast spatial domain is precedent setting within the air toxics community. The hybrid design exhibits improved performance relative to the stand alone CTM and dispersion model. However, model performance varies widely across pollutant categories and quantifiably definitive performance assessments are hampered by a limited observation base and challenged by the multiple physical and chemical attributes of HAPs. Formaldehyde and acetaldehyde are the dominant HAP concentration and cancer risk drivers, characterized by strong regional signals associated with naturally emitted carbonyl precursors enhanced in urban transport corridors with strong mobile source sector emissions. The multiple pollutant emission characteristics of combustion dominated source sectors creates largely similar concentration patterns across the majority of HAPs. However, reactive carbonyls exhibit significantly less spatial variability relative to nonreactive HAPs across the CONUS

Trends in Chemical Composition of Global and Regional Population-Weighted Fine Particulate Matter Estimated for 25 Years

We interpret in situ and satellite observations with a chemical transport model (GEOS-Chem, downscaled to 0.1° × 0.1°) to understand global trends in population-weighted mean chemical composition of fine particulate matter (PM_2.5). Trends in observed and simulated population-weighted mean PM_2.5 composition over 1989–2013 are highly consistent for PM_2.5 (−2.4 vs −2.4%/yr), secondary inorganic aerosols (−4.3 vs −4.1%/yr), organic aerosols (OA, −3.6 vs −3.0%/yr) and black carbon (−4.3 vs −3.9%/yr) over North America, as well as for sulfate (−4.7 vs −5.8%/yr) over Europe. Simulated trends over 1998–2013 also have overlapping 95% confidence intervals with satellite-derived trends in population-weighted mean PM_2.5 for 20 of 21 global regions. Over 1989–2013, most (79%) of the simulated increase in global population-weighted mean PM_2.5 of 0.28 μg m^–3yr^–1 is explained by significantly (<i>p</i> < 0.05) increasing OA (0.10 μg m^–3yr^–1), nitrate (0.05 μg m^–3yr^–1), sulfate (0.04 μg m^–3yr^–1), and ammonium (0.03 μg m^–3yr^–1). These four components predominantly drive trends in population-weighted mean PM_2.5 over populous regions of South Asia (0.94 μg m^–3yr^–1), East Asia (0.66 μg m^–3yr^–1), Western Europe (−0.47 μg m^–3yr^–1), and North America (−0.32 μg m^–3yr^–1). Trends in area-weighted mean and population-weighted mean PM_2.5 composition differ significantly