Abstract
A new dynamic solution adaptive grid algorithm, DSAGA‐PPM, has been developed for use in air quality modeling. In this paper, this algorithm is described, and is evaluated with a test problem. Cone‐shaped distributions of various chemical species undergoing chemical reactions are rotated to simulate the transport and chemistry processes that occur in the atmosphere. The results obtained by using DSAGA‐PPM are more accurate than those obtained from a static grid with the same number of nodes. The computational cost associated with a static grid solution with the same level of accuracy is prohibitive. Because of its efficient use of computational resources, DSAGA‐PPM has the potential to improve the accuracy, or efficiency, or a combination of both in air quality models.
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