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SIMULATING ATMOSPHERIC EXPOSURE IN A NATIONAL RISK ASSESSMENT USING AN INNOVATIVE METEOROLOGICAL SAMPLING SCHEME
Citation:
Schwede, D B., W B. Petersen, R. W. Brode, AND M. Jindal. SIMULATING ATMOSPHERIC EXPOSURE IN A NATIONAL RISK ASSESSMENT USING AN INNOVATIVE METEOROLOGICAL SAMPLING SCHEME. Presented at Society of Environmental Toxicology and Chemistry Annual Meeting, Philadelphia, PA, November 14-18, 1999.
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 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 are not amendable to estimating wet deposition. In an effort to produce the required estimates without the computational burden, we developed an extension to the Sampled Chronological Imputed Model (SCIM) for use in ISCST3. SCIM samples the long term meteorological record at regular, user-specified intervals. Since hourly meteorology is being used, the serial correlation between wet deposition and concentration is maintained. Our results show that, for a 5 year meteorological-database, sampling every 193rd hour produced concentration and dry deposition estimates essentially the same as those obtained when using the full meteorological record. However, this simple sampling scheme significantly underestimated wet deposition, particularly at sites with infrequent precipitation. For wet deposition, the key to the success of SCIM is the addition of an additional sampling interval (every 8th hour)for hours with precipitation . this approach resulted in wet deposition estimates that were not significantly different than those obtained from the full record. The development of this innovative sampling approach has resulted in an efficient methodology for use in multimedia risk assessments.