Aircraft landing and takeoff emission impacts on surface O3 and PM2.5 through aerosol direct feedback effects estimated by the coupled WRF-CMAQ model

The aerosol direct feedback effects (ADFEs) are neglected in traditional air quality modeling studies (where meteorology is used as input and not affected by the chemistry and aerosol microphysics) for estimating the impacts of aircraft emissions on air quality. In this study, aircraft landing and take-off (LTO) attributable change of O3 and PM2.5 concentrations through ADFEs for the year 2005 within the contiguous United States (CONUS) are quantified by a coupled meteorology-chemistry modeling system: Weather Research and Forecasting – Community Multi-scale Air Quality (WRF-CMAQ) model. We first quantified the effects of ADFEs of all aerosols within the CONUS (not the effects of aircraft LTO emissions) on surface meteorology and air quality and found that ADFEs changed on average the downward short-wave radiation (SWR), 2-m temperature (T2), planetary boundary layer (PBL) height, O3 and PM2.5 by −7.38 W/m2, −0.47 K, −20.72 m, −0.41 ppb and +0.28 μg/m3 in 2005. We also found a seasonal influence where ADFE-influenced change (decrease) of SWR, T2, PBL, O3 and change (increase) of PM2.5 were higher in summer than in winter. We found that the aircraft LTO emissions’ contribution to domain average surface concentration of O3 and PM2.5 were +0.0065 ppb and +0.0022 μg/m3 respectively when ADFEs are accounted for. The ADFEs decrease aircraft LTO attributable surface O3 and PM2.5 change by 21% and 23% respectively comparing with that without ADFE in 2005. We also found that in both without-and-with ADFE cases, the aircraft LTO emissions increases domain average of O3 from April to October and decreases from November to March showing a strong seasonal pattern. Our modeling study revealed that use of a coupled model with ADFE shows localized changes in air quality by aircraft LTO emissions across the domain which were masked when looking at domain averages for both O3 and PM2.5, and which may be important for accurately quantifying health risk due to air pollution exposures in densely populated areas.