Modeled Trends in Impacts of Landing and Takeoff Aircraft Emissions on Surface Air-Quality in U.S for 2005, 2010 and 2018 

Friday, 19 December 2014
Lakshmi Pradeepa Vennam, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
Understanding the present-day impacts of aircraft emissions on surface air quality is essential to plan potential mitigation policies for future growth. Stringent regulation on mobile source-related emissions in the recent past coupled with anticipated rise in the growth in aviation activity can increase the relative impacts of aviation-attributable surface air quality if adequate measures for reducing aviation emissions are not implemented. Though aircraft emissions during in-flight mode (at upper altitudes) contribute a significant (70 - 80%) proportion of the total aviation emissions, landing and takeoff (LTO) related emissions can have immediate impact on surface air quality, as most of the large airports are located in urban areas, specifically those that are designated in nonattainment for O3 and/or PM2.5. In this study, we modeled impacts of aircraft emissions during LTO cycles on surface air quality using the latest version of the CMAQ model for two contemporary years (2005, 2010) and one future year (2018). For this regional scale modeling study, we used highly resolved aircraft emissions from the FAA’s Aviation Environmental Design Tool (AEDT), meteorology from NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA) downscaled with the WRF model, dynamically varying chemical boundary conditions from the CAM-Chem global model (which also used the same AEDT emissions but at the global scale), and spatio-temporally resolved lightning NOx emissions estimated using National Lightning Detection Network (NLDN) flash density data. We evaluated our model results with air quality observations from surface-based networks and in-situ aircraft observation data for the contemporary years. We will present results from model evaluation using this enhanced modeling system, as well as the trajectories in aviation- related air quality (focusing on O3, NO2 and PM2.5) for the three modeling years considered in this study. These findings will help plan potential strategies to be considered for overall reduction in aviation-related air quality and health impacts on U.S. wide basis in future years.