Concentration Trajectory Route of Air pollution with an Integrated Lagrangian model (C-TRAIL model v1.0) derived from the Community Multiscale Air Quality Modeling (CMAQ model v5.2)

2020 
Abstract. This paper introduces a reliable and comprehensive Lagrangian output (Concentration Trajectory Route of Air pollution with Integrated Lagrangian model, C-TRAIL version 1.0) from an Eulerian air quality model for validating the source-receptor link by following real polluted air masses. To investigate the concentrations and trajectories of air masses simultaneously, we implement the trajectory-grid (TG) Lagrangian advection scheme in the CMAQ (Community Multiscale Air Quality) Eulerian model version 5.2. The TG algorithm follows the concentrations of representative air packets of species along trajectories determined by the wind field. The generated output from C-TRAIL accurately identifies the origins of pollutants. For validation, we analyzed the results of C-TRAIL during the KORUS-AQ campaign over South Korea. Initially, we implemented C-TRAIL in a simulation of CO concentrations with an emphasis on the long- and short-range transport effect. The output from C-TRAIL reveals that local trajectories were responsible for CO concentrations over Seoul during the stagnant period (May 17–22, 2016) and during the extreme pollution period (May 25–28, 2016), highly polluted air masses from China were distinguished as sources of CO transported to the Seoul Metropolitan Area (SMA). We conclude that long-range transport played a crucial role in high CO concentrations over the receptor area during this period. Furthermore, for May 2016, we find that the potential sources of CO over that SMA were the result of either local transport or long-range transport from the Shandong Peninsula and, in some cases, from north of the SMA. By identifying the trajectories of CO concentrations, one can use the results from C-TRAIL to directly link strong potential sources of pollutants to a receptor in specific regions during various time frames.
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