P1.2
Industrial Source Complex (ISC) Modeling with ASOS Data
PAPER WITHDRAWN
John White, NC Department of Environment and Natural Resources, Raleigh, NC; and M. Yoder
When the Automated Surface Observing System (ASOS) was implemented as the backbone of the NWS surface observing network, the air quality community lost some key data necessary to execute some of the most widely used air dispersion models, particularly the Industrial Source Complex (ISC) suite. Cloud information above 12,000 feet, which is required to determine the Pasquill-Gifford (P-G) stability categories in these models, is not currently collected by the stand-alone, un-augmented ASOS. However, the meteorological pre-processor for these models, PCRAMMET, uses cloud reports only up to 16,000 feet. We speculated that if the absence of cloud information between 12,000 and 16,000 feet resulted in no significant difference in the concentrations calculated by ISC, ASOS reports -- because of their greater density and proximity to sources -- would generate more representative ambient air concentrations at modeled facilities across our state.
To assess the impact of this new data set on ISC modeled concentrations, we determined the frequency of cloud reports in this "missing" layer based on 30 years of pre-ASOS weather reports (1961 through 1990) from first order stations in North Carolina. We then calculated and compared ambient air concentrations from a hypothetical facility comparing pre- and post-ASOS data bases. This paper presents the results of this comparison.
In addition, to illustrate the significance of the differences resulting from using "nearby" instead of "distant" sites, we offer example comparisons based on the existing North Carolina modeling guidelines.
The Environmental Protection Agency's Guideline on Air Quality Models (Revised) suggests that proximity of meteorological data, especially considering terrain differences, is the priority in air quality modeling. North Carolina's geography presents a variety of mesoscale conditions, and , therefore, closer, more representative ASOS data are more representative than distant data. We propose ASOS data be adopted as the standard meteorological data set for ISC and similar models.
Poster Session 1, (Formal Viewing with Coffee)
Wednesday, 12 January 2000, 3:00 PM-4:00 PM
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