Performing CALPUFF Analyses with Pseudo-station Data Derived from MM5 Data

0
The U.S. Environmental Protection Agency (EPA) recommends that CALPUFF be used as the preferred model for long-range transport analyses in the proposed “Guideline on Air Quality Modeling” (April 2000). In practice, CALPUFF has been routinely required by the Federal Land Managers (FLM), EPA, and state regulatory agencies for Class I area analyses for several years. These analyses include regional haze, acid deposition, and Class I increments in support of Prevention of Significant Deterioration (PSD) permit applications. The meteorological module, CALMET, in the CALPUFF modeling system can generate three-dimensional gridded meteorological data through sophisticated treatment and assimilation of surface/upper air/precipitation observations, prognostic wind field data from the meso-scale models such as MM5, and geophysical data. Unfortunately, in many situations, due to the remote locations of Class I areas, limited surface and/or upper air observations are available within the modeling domain. Moreover, meteorological observations (such as relative humidity) from available surface stations may not even be representative of conditions in the Class I areas. Consequently, the results from CALPUFF analyses with un-representative meteorological data may be questionable. To overcome the lack and shortcomings of surface data for CALPUFF modeling, this study explores the pros and cons of performing CALPUFF analyses with pseudo-station data derived from MM5 data. These pseudo-station data are developed from MM5 data to substitute or supplement the actual surface observations in the modeling domain. A comparison of results from various scenarios is presented. Furthermore, implications of using pseudo-station data in a regional haze analysis (which is sensitive to relative humidity conditions) are discussed.

Customer comments

No comments were found for Performing CALPUFF Analyses with Pseudo-station Data Derived from MM5 Data. Be the first to comment!