An Enhanced Sub-grid Scale Approach to Characterize Air Quality Impacts of Aircraft Emissions

Abstract

AbstractWe present an overview of results from an enhanced sub-grid scale approach to characterize air quality impacts of aircraft emissions at the Hartsfield-Jackson Atlanta International airport (in the U.S.) for June and July 2002 using an adaptation of CMAQ called the Advanced Modeling System for Transport, Emissions, Reactions, and Deposition of Atmospheric Matter (AMSTERDAM). Aircraft emissions during the landing and takeoff cycle (LTO) and below 3,000 m were represented as plume-in-grid (PInG) emissions using AMSTERDAM’s PInG treatment. Initial results from CMAQ-AMSTERDAM focusing on impacts from aircraft emissions to inorganic PM2.5 and total PM2.5 indicated aircraft increased average total PM2.5 concentrations by up to 235 ng m−3 near the airport and by 1–7 ng m−3 throughout the Atlanta metro area. However, aircraft reduced concentrations by 0.5–1 ng m−3 downwind of the airport, attributable to reductions in sulfate aerosol. The subgrid-scale concentrations were an order of magnitude higher than the grid-based concentrations due to aircraft. In an earlier study when aircraft emissions were modeled by CMAQ as traditional point sources within the ATL airport grid cell, we showed that modeled secondary organic aerosol (SOA) concentrations increased by 2 % due to primary organic aerosol (POA) emissions from aircraft, which provided additional surface area for SOA to partition onto. We now present results from additional modeling work performed to a) enhance organic treatment in a 1-D aerosol microphysics model used to provide engine-specific emissions parameters for CMAQ, and b) examine aircraft’s impacts on secondary organic aerosol concentrations using the volatility basis set (VBS) within CMAQ-AMSTERDAM to represent the formation and aging of organic aerosols. Parameterization for the VBS components was determined using current and ongoing field study measurements, chamber studies, and box models specific to aircraft SOA formation, which showed that non-traditional precursors of SOA (NTSOA) were a much higher contributor to aircraft-specific SOA than previously understood.KeywordsCMAQAMSTERDAMPInGAviation EmissionsPM2.5