Use of selected chemical markers in combination with a multiple regression model to assess the contribution of domesticated animal sources of fecal pollution in the environment

Abstract

Human and animal wastes are major sources of environmental pollution. Reliable methods of identifying waste sources are necessary to specify the types and locations of measures that best prevent and mitigate pollution. This investigation demonstrates the use of chemical markers (fecal sterols and bile acids) to identify selected sources of fecal pollution in the environment. Fecal sterols and bile acids were determined for pig, horse, cow, and chicken feces (10–26 feces samples for each animal). Concentrations of major fecal sterols (coprostanol, epicoprostanol, cholesterol, cholestanol, stigmastanol, and stigmasterol) and bile acids (lithocholic acid, deoxycholic acid, cholic acid, chenodeoxycholic acid, ursodeoxycholic acid, and hyodeoxycholic acid) were determined using a gas chromatography and mass spectrometer (GC–MS) technique. The fecal sterol and bile acid concentration data were used to estimate parameters of a multiple linear regression model for fecal source identification. The regression model was calibrated using 75% of the available data validated against the remaining 25% of the data points in a jackknife process that was repeated 15 times. The regression results were very favorable in the validation data set, with an overall coefficient of determination between predicted and actual fecal source of 0.971. To check the potential of the proposed model, it was applied on a set of simulated runoff data in predicting the specific animal sources. Almost 100% accuracy was obtained between the actual and predicted fecal sources. While additional work using polluted water (as opposed to fresh fecal samples) as well as multiple pollution sources are needed, results of this study clearly indicate the potential of this model to be useful in identifying the individual sources of fecal pollution.