| An Adaptive Grid Module based on DSAGA-PPM (Srivastava et al. 2000) and suitable for use in air quality models was developed and implemented in the Multiscale Air Quality Simulation Platform (MAQSIP): a three-dimensional photochemical air quality model. The module is responsible for, (1) computing the weight function that drives the grid node reposition process, (2) repositioning the grid nodes, (3) redistributing the concentration field on the adapted grid, (4) processing of emissions and meteorological data on the adapted grid and (5) coordinate transformation that allows the use of numerical solution algorithms developed in fixed grid models.; An historical air pollution episode (July 7–17th, 1995) over Tennessee Valley and surrounding areas was simulated using the adaptive grid model. For comparison and verification, two additional simulations were conducted using the fixed grid version of the air quality model at 4 and 8-km grid resolution (referred to as the fine and coarse grids respectively). The results presented in the research work show that the adaptive grid model is able to resolve a significant number of plumes that are likely to remain unresolved even in a higher resolution static grid simulation. To a large degree, the ability of the adaptive grid to resolve concentrated plumes is reflected in improved ozone predictions at a majority of monitoring stations. The full extent of this improvement can be better quantified by comparing the modeling results against a more comprehensive measurement dataset (e.g., aircraft measurements, intensive monitoring). The use of three dimensional concentration field and estimates of the rate of chemical transformation of relevant species increases the ability of the adaptive grid to capture surface as well as elevated plumes.; In the operational sense, the three dimensional adaptive grid model developed here represents a shift in the modeling paradigm and is the first model, among the next generation of atmospheric models that would tightly couple emissions, meteorology and air quality models within the same framework. Processing of the emissions inventory at run-time provides an opportunity to evaluate episode specific emission control strategies that now require off-line emissions processing. Better resolution of plumes from large sources can foster the development of more effective emission control strategies. |
