Selection and Evaluation of Chemical Indicators for Waste Stream Identification

Abstract:

Human and animal wastes pose a threat to the quality of groundwater, surface water and drinking water. This is especially of concern for private and public water supplies in agricultural areas of Wisconsin where land spreading of livestock waste occurs on thin soils overlaying fractured bedrock. Current microbial source tracking (MST) methods for source identification requires the use of polymerase chain reaction (PCR) techniques. Due to cost, these tests are often not an option for homeowners, municipalities or state agencies with limited resources. The Water and Environmental Analysis Laboratory sought to develop chemical methods to provide lower cost processes to determine sources of fecal waste using fecal sterols, pharmaceuticals (human and veterinary) and human care/use products in ground and surface waters using solid phase extraction combined with triple quadrupole mass spectrometry. The two separate techniques allow for the detection of fecal sterol and other chemical markers in the sub part per billion-range. Fecal sterol ratios from published sources were used to evaluate drinking water samples and wastewater from onsite waste treatment systems and municipal wastewater treatment plants. Pharmaceuticals and personal care products indicative of human waste included: acetaminophen, caffeine, carbamazepine, cotinine, paraxanthine, sulfamethoxazole, and the artificial sweeteners; acesulfame, saccharin, and sucralose. The bovine antibiotic sulfamethazine was also targeted. Well water samples with suspected fecal contamination were analyzed for fecal sterols and PPCPs. Results were compared to traditional MST results from the Wisconsin State Laboratory of Hygiene. Chemical indicators were found in 6 of 11 drinking water samples, and 5 of 11 were in support of MST results. Lack of detection of chemical indicators in samples contaminated with fecal waste supports the need for confirmatory methods and advancement of chemical indicator detection technologies.