Document rBjV5zLgQgmGGLmevJdJ3KVJE

AR226-2319 y Charles J Zarzecki 04/02/2003 03:14 PM To: cc: Subject: Catherine A Barton/AE/DuPont Beychok Article Cathie, I finally was able to review the Beychok article on error propagation in dispersion modeling. This could add fuel to Dave Rurak's fire. It's common knowledge that Gaussian models overpredict by a factor of 2, however, due to error propagation, he says as high as 80X. Also, as far as 1-hour concentrations are concerned, the actual averaging lime for Pasquill's dispersion coefficients range from 3 minutes to 30 minutes, depending who you talk to. I always thought they were 15-minute averages. This short-term to 1-hour assumption can be shown (by Beychok) to result in a 2.5X overprediction. However, in my opinion, since the 1-hour period is the basic time-step in the ISC (and other) .model, an annual average concentration at any given receptor is 8,760 1-hour concentrations divided by 8,760 hours. If it predicts poorly for each 1-hour period, then it predicts poorly for the whole year. Dave has to understand that the model is a screening tool. The more accurate information you put into a model, the greater the accuracy of the prediction. Instead of lambasting (is that a real word?) the model's 1-hour prediction, we should investigate how to fine-tune the input data and model options (e.g. particle settling, hours of operation, hourly emission rates, more accurate model (AERMOD), etc...). Or, go out and do some sampling to get the "real thing". What do you think? Beychok references about a half-dozen other publications that discuss the shortcomings of Gaussian models. Some of them go way back. As you can see, nobody really took them seriously. What f am getting at: the regulatory agencies (OEPA, WVDEQ) are not going to want to hear about how bad ISC is for particular time periods. They may be open to other "accepted" models and to sharpening our pencils. Regards, Charlie Z. EID747732