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SIMULATING ATMOSPHERIC EXPOSURE USING AN INNOVATIVE METEOROLOGICAL SAMPLING SCHEME
Citation:
Schwede, D B., W B. Petersen, AND S K. LeDuc. SIMULATING ATMOSPHERIC EXPOSURE USING AN INNOVATIVE METEOROLOGICAL SAMPLING SCHEME. Presented at Millennium NATO/CCMS International Technical Meeting, Boulder, CO, May 15-19, 2000.
Impact/Purpose:
This task objective is the development and improvement of state-of-the-science meteorology models and contributing process parameterizations for use in advanced air quality simulation model systems such as the Community Multi-scale Air Quality (CMAQ) modeling system and for other modeling studies and situations involving transport and dispersion of pollutants. Components of this work include: (a) improved meteorological and transport modeling, (b) improved meteorological modeling physics, (c) physical modeling of flows- building wakes, complex terrain, urban canyons, (d) modeling of transport and dispersion of specialized situations and (e) develop AERMOD (AMS/EPA Regulatory MODel).
Description:
Multimedia Risk assessments require the temporal integration of atmospheric concentration and deposition estimates with other media modules. However, providing an extended time series of estimates is computationally expensive. An alternative approach is to substitute long-term average atmospheric estimates, but traditional methods for calculating long-term averages (e.g. joint frequency function) are not amenable to estimating wet deposition. In an effort to produce the required estimates without the computational burden, we developed an extension to the Sampled Chronological Input Model (SCIM) (Koch and Thayer, 1974) for use in U.S. Environmental Protection Agency's (USEPA) Industrial Source Complex - Short Term (ISCST3) model (USEPA, 1995). SCIM samples the long term meteorological record at regular, user-specified intervals. Since hourly meteorology is being used, the serial correlation between deposition and concentration and concentration is maintained. However, this simple sampling scheme significantly underestimates wet deposition, particularly at sites with frequent precipitation. We were able to reduce the uncertainty by introducing an additional sampling interval for hours with precipitation into the original SCIM methodology. Using this revised technique, concentration and dry deposition are calculated using the "regular" SCIM sampling; concentration and dry and wet deposition are calculated from hours sampled during "wet" SCIM sampling. A composite, weighted average is taken at the end of the simulation to determine annual values.