HYBRID PLUME DISPERSION MODEL (HPDM) IMPROVEMENTS AND TESTING AT 3 FIELD SITES

Descriptions of several technical improvements to the Hybrid Plume Disperion Model (HPDM) are given. The boundary-layer meteorological preprocessor now makes use of a surface moisture availability parameter and now accounts for mechanical mixing due to buildings in urban areas. A new dispersion algorithm has been added in order to simulate conditions better when a buoyant plume ''lofts'' against the capping inversion and spreads laterally before dispersing down to the ground. The modified model has been evaluated using 89 h of SF6 tracer data at an urban power plant in Indianapolis, IN, and using a full year (8760 h) of SO2 data at the Baldwin, IL, power plant and the Summit County, OH, industrial complex. The EPA's RAM and ISC models are also included in the evaluation exercises. Emphasis is on the second-highest concentrations, the correlation, the fractional mean bias and the fraction of predictions within a factor of two of observations for 1-, 3- and 24-h averaging times. The HPDM model exhibits significantly better performance (at the 95% confidence level) than the RAM or ISC model for most sites and performance measures. In most cases, the HPDM ''second-highest'' predictions are within 10-20% of the observations and the fractional mean bias values are less than 10%. Furthermore, the relative error of HPDM shows little trend with input variables such as wind speed and mixing depth.