Air quality models have become basic scientific tools used in formulating policy decisions involving tremendous capital resources. The air quality of one region is affected by the emissions and transport of pollutants from the surrounding regions. This necessitates the use of regional scale models which cover large areas on the order of 10(6) km(2), and are computationally intensive. The next generation air quality models will include more complex chemistry and aerosol physics, and will employ sub-grid scales to treat atmospheric turbulence and other processes. These advancements in the models will significantly increase their computational demands. One way to maintain a reasonable turnaround time will be to use massively parallel computational architectures. An important issue in the parallel applications to these models is the portability of the model across various architectures. The urban and regional multiscale (URM) model has been parallelized and applied to various computational environments. Significant decreases in elapsed computational time are observed when the model is applied to a cluster of workstations. Portability issues of the application are analyzed with regard to architecture-independent code, good performance on different architectures, and a uniform run-time environment.