SIMULATING ATMOSPHERIC EXPOSURE USING AN INNOVATIVE METEOROLOGICAL SAMPLING SCHEME D.B. Schwede1, W.B. Petersen1 and S.K. LeDuc1 Atmospheric Sciences Modeling Division, Air Resources Laboratory, National Oceanic and Atmospheric Administration, Research Triangle Park, NC INTRODUCTION 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 is maintained. However, this simple sampling scheme significantly underestimates wet 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 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. RESULTS AND DISCUSSION To analyze the impact on ISCST3 estimates of using the sampled meteorological data, we made model runs using five area sources and two point sources. The sources varied in size and 'On assignment to the National Exposure Research Laboratory, U.S. Environmental Protection Agency. ------- particle size distribution. Each source was run with 5 years of meteorological data for four stations: Lake Charles, LA; Pittsburgh, PA; Salem, OR; Tucson, AZ, The sites were selected to provide a diversity of climatological regimes. A polar grid of receptors along 16 evenly spaced radials at distances ranging from the edge of the source to several kilometers was used. We compared the results of various combinations of sampling rates with the results from using the full meteorological database. The basic SCIM approach worked best for meteorological stations with frequent precipitation (e.g. Salem), while wet deposition at sites with infrequent precipitation (e.g. Tucson) was generally underestimated. The inclusion of a higher "wet" sampling frequency with a fairly low frequency for the "regular" sampling improved the results at all sites. Point sources required a higher sampling frequency (regular = every 25th hour; wet = every 8th hour) than area sources (regular =193; wet = 8) to achieve similar results. We also made model runs varying the start hour of both the "regular" and "wet" sampling to characterize the variability of the results. Figure 1 illustrates the results for an example site and indicates that the sampling introduces little bias. The lowest scatter was observed for higher sampling rates and at locations with frequent precipitation. Ratios of annual values paired in space were calculated and frequency distributions were developed to assess the ability of the sampling scheme to reproduce the spatial pattern of impact. An example plot is shown in Figure 2. These plots showed that the enhanced SCIM methodology reproduced the spatial pattern of deposition. DISCLAIMER This paper has been reviewed in accordance with the U.S. Environmental Protection Agency's peer and administrative review policies and approved for presentation and publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use. REFERENCES Koch, R.C. and S.D. Thayer, 1974. Validity of the multiple-source gaussian-plume diffusion model using hourly estimates of input; also, Sensitivity analysis of the multiple-source gaussian plume urban diffusion model in Proceedings of the fifth Meeting of Expert Panel on Air Pollution Modeling NATO Committee on the Challenges of Modem Society, Roskilde Denmark. USEPA, 1995. User's Guide for the Industrial Source Complex (ISC3) Dispersion Models- Volume II - Description of Model Algorithms. EPA-454/B-95-003b, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, 27711. < v Salem Land Application Unit Regular Sampling - 193 hours Wet Sampling « 8 hours Distance fm) Figure 1. Total annual deposition as a function of distance for an area source. Solid and dashed lines are NoSClM results. Bars represent replicate samples using SCIM. Tucson Point Source Regular S ampling = 25 Wet Sampling - 8 JU <0.25<0.5<0,75<1.0<1.2S<1,S<1.?S<2.0 SCIM to NoScim Ratio Figure 2. Ratio of SCIM to NoSCIM values paired in space for a 35 m point source. Data from all replicate samples are included. ------- NERL-R1P-AMD-00-062 1, REPORT NO. EPA/600/A-00/015 TECHNICAL REPORT DATA 2. 4 . TITLE AND SOBTITLE Simulating Atmospheric Exposure Using An Innovative Meteorological Sampling Scheme 7, AUTHOR(S) D.B. Schwede, W.B. Petersen, and S.K. LeDuc 9. PERFORMING ORGANIZATION NAME AND ADDRESS Same as block 12 12. SPONSORING AGENCY NAME AND ADDRESS National Exposure Research Laboratory Office of Research and Development U.S. Environmental Protection Agency Research Triangle Park, NC 277 1 1 3. RECIPIENT'S ACCESSION NO. 5. REPORT DATE 6.PERFORMING ORGANIZATION CODE 8.PERFORMING ORGANIZATION REPORT NO. 1 0.PROGRAM ELEMENT NO. 1 1. CONTRACT/GRANT NO. i 3.TYPE OF REPORT AND PERIOD COVERED 14. SPONSORING AGENCY CODE EPA/600/9 15, SUPPLEMENTARY NOTES 16, 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 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 is maintained. However, this simple sampling scheme significantly underestimates wet 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 mediodology. 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. 17. KEY WORDS AND DOCUMENT ANALYSIS a. DESCRIPTORS b.IDENTIFIERS/ OPEN ENDED TERMS 18. DISTRIBUTION STATEMENT RELEASE TO PUBLIC 19. SECURITY CLASS (This Report) UNCLASSIFIED 20. SECURITY CLASS (This Page) UNCLASSIFIED c.COSATI 21. NO. OF PAGES 22. PRICE EPA-2220 ------- |