Application of static adaptive grid techniques for regional-urban multiscale air quality modeling

Abstract

Texas Air Quality Study 2000 revealed that ozone productivity in the Houston Ship Channel area was abnormally higher than other comparable cities in USA due to the large emissions of highly reactive unsaturated hydrocarbons from petrochemical industries. Simulations with popular Eulerian air quality models were shown to be inadequate to represent the transient high ozone events in the Houston Ship Channel area. In this study, we apply a multiscale Eulerian modeling approach, called CMAQ/SAFE, to reproduce the measured ozone productivity in the Houston Ship Channel and surrounding urban and rural areas. The modeling tool provides a paradigm for the multiple-level regional and local air quality forecasting operations that can utilize modern computational infrastructure such as grid computing technologies allowing to harness computing resources across sites by providing programmatic and high-bandwidth data linkage and establishing operational redundancy in the case of hardware or software failures at one operational site. © Springer-Verlag Berlin Heidelberg 2005.