| The purpose of this research was to develop input parameters required for modeling the fate and transport of pathogenic microorganisms. A computer model, calibrated with these input parameters, can then be used to assess the health risks of sewage contamination, especially from separate sewer overflows (SSOs). Laboratory and field studies were conducted to generate model input data for fate and transport simulation. As an example, a simple mathematical model was developed, using these data, to assess the health risks from pathogens in SSO discharges to several local urban streams.;The pathogens studied were Escherichia coli ( E. coli) O157:H7, Cryptosporidium parvum, and Giardia lamblia. The indicator bacteria, total coliforms, E. coli, and Enterococci, were also included since they are of historical significance—allowing comparison to Previous studies. Fate and transport computer models require environmental decay, settling, and scour characterizations of the microorganisms to be modeled. Previously, this information has been unavailable for these pathogens.;This research has shown evidence of the following. The traditional method of using simple, first order decay constants is not appropriate for simulating the long-term decay of these pathogens. A biphasic, or dual regression, model is more suitable. The decay is first order for approximately the first 7 days. After 7 days, decay decreases such that it is not significantly different than zero (95 percent confidence). The first order, linear decay component, occurring during the first seven days, was measured as follows: Giardia, 0.42 (0.37– 0.47); Cryptosporidium, 0.03 (–0.48–0.54); E. coli O157:H7, 0.78 (0.22–1.3), (days–1) at 20–25°C. The values in parentheses are the 95 percent confidence intervals about the decay rate estimate. Current surface-water fate and transport models are not designed to evaluate decay other than first-order, which this study shows to be invalid beyond 7 days. Predicting the fate of Cryptosporidium oocysts and Giardia cysts [(oo)cysts] using indicator bacteria is inappropriate; however, Enterococci most-closely approximates their decay patterns. Decay of (oo)cysts does occur, albeit at a much reduced rate than that of indicator bacteria. The indicator bacteria are adequate predictors for E. coli O157:H7. Finally, settling is rarely a significant removal mechanism for pathogens in stream environments. Decay is a more important modeling parameter. |
