A plume-in-grid approach to characterize air quality impacts of aircraft emissions at the Hartsfield-Jackson Atlanta International Airport
1Energy Innovation: Policy and Technology LLC, 98 Battery St. Ste. 202, San Francisco, CA 94111, USA
2Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
3Department of Environmental Science and Engineering, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
4Department of City and Regional Planning, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
Abstract. This study examined the impacts of aircraft emissions during the landing and takeoff cycle on PM2.5 concentrations during the months of June 2002 and July 2002 at the Hartsfield-Jackson Atlanta International Airport. Primary and secondary pollutants were modeled using the Advanced Modeling System for Transport, Emissions, Reactions, and Deposition of Atmospheric Matter (AMSTERDAM). AMSTERDAM is a modified version of the Community Multiscale Air Quality (CMAQ) model that incorporates a plume-in-grid process to simulate emissions sources of interest at a finer scale than can be achieved using CMAQ's model grid. Three fundamental issues were investigated: the effects of aircraft on PM2.5 concentrations throughout northern Georgia, the differences resulting from use of AMSTERDAM's plume-in-grid process rather than a traditional CMAQ simulation, and the concentrations observed in aircraft plumes at sub-grid scales. Comparison of model results with an air quality monitor located in the vicinity of the airport found that normalized mean bias ranges from −77.5% to 6.2% and normalized mean error ranges from 40.4% to 77.5%, varying by species. Aircraft influence average PM2.5 concentrations by up to 0.232 μg m−3 near the airport and by 0.001–0.007 μg m−3 throughout the Atlanta metro area. The plume-in-grid process increases concentrations of secondary PM pollutants by 0.005–0.020 μg m−3 (compared to the traditional grid-based treatment) but reduces the concentration of non-reactive primary PM pollutants by up to 0.010 μg m−3, with changes concentrated near the airport. Examination of sub-grid scale results indicates that puffs within 20 km of the airport often have average PM2.5 concentrations one order of magnitude higher than aircraft contribution to the grid cells containing those puffs, and within 1–4 km of emitters, puffs may have PM2.5 concentrations 3 orders of magnitude greater than the aircraft contribution to their grid cells. 21% of all aircraft-related puffs from the Atlanta airport have at least 0.1 μg m−3 PM2.5 concentrations. Median daily puff concentrations vary between 0.017 and 0.134 μg m−3, while maximum daily puff concentrations vary between 6.1 and 42.1 μg m−3 during the 2-month period. In contrast, median daily grid concentrations vary between 0.015 and 0.091 μg m−3, while maximum daily grid concentrations vary between 0.751 and 2.55 μg m−3. Future researchers may consider using AMSTERDAM to understand the impacts of aircraft emissions at other airports, for proposed future airports, for airport expansion projects under various future scenarios, and for other national-scale studies specifically when the maximum impacts at fine scales are of interest.