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Trajectory Analysis for Source-receptor Relation of High O3 events over Houston/Galveston Area during Summer 2005
Fong Ngan, Univ. of Houston, Houston, TX; and D. Byun
Trajectory analysis has been widely used for establishing source-receptor relation of air pollutants and understanding potential impact of pollutant sources. It can help with tracking high ozone events and tracing them back to the points of NOx and VOC emissions. Trajectory is not only a kinematical description of air movement, but also representing the dynamic motion of air parcels which is subject to the evolution of momentum field. In the past two years, the UH Institute for Multidimensional Air Quality Studies (IMAQS) has operated a trajectory system called “Real-time Trajectory Analysis System (RTAS)”. The major function of it is to generate 12-hour backward/forward trajectories for Eastern Texas four times a day in a near real time mode. In order to construct more accurate local-scale trajectories, objective analyses using the so-called LITTLE_R in MM5 (the Fifth Generation Penn State University/National Center for Atmospheric Research Mesoscale Model) system have been performed to improve the NAM grid data with local observations including surface, profiler and sounding data. With this assimilated data, trajectories are computed using the ARL/UH-HYSPLIT model. The main objective of this study is to understand the relation of meteorological condition and high ozone events over eastern Texas. The 12-hour backward trajectories starting at 4 different altitudes (10m, 500m, 1000m and 1500m above ground level) are used in identifying the source of the pollutant reaching the receptor position. Analysis period is summer 2005 from May to August. And the target receptor locate at southwest of Houston downtown. 850mb weather charts presenting geopotential height, potential temperature and horizontal wind vectors are used to classify the weather types during analysis period. To assess the tendency of the source-receptor relationships, not only the graphical representations of the trajectories but also statistical estimates characterizing the behavior and quality of the trajectories may be useful. Two analysis indices, stagnation potential and trajectory travel time, are defined to understand the behavior of air movement. With the weather classification, the pattern of those two index indicate the distribution of trajectories of different weather types. Furthermore, higher stagnation potential shows the higher the probability of the air to be stagnant in the grid cell. Travel time shows how long it took for pollutants to arrive the receptor location.
Session 1, Initial Results from MILAGRO and Texas2006
Tuesday, 16 January 2007, 8:30 AM-12:00 PM, 212A
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