Simulating Atmospheric Exposure using an Innovative Meteorological Sampling Scheme

Abstract

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 longterm average atmospheric estimates, but traditional methods for calculating long-term averages (e.g. joint frequency function) are not amenable to estimating 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 is maintained. However, this simple sampling scheme significantly underestimates deposition, particularly at sites with infrequent 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 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.