A quantitative risk ranking model to evaluate emerging organic contaminants in biosolid amended land and potential transport to drinking water. Issue 4 (18th May 2016)

• Record Type: Journal Article
• Authors: Clarke, Rachel; Healy, Mark G.; Fenton, Owen; Cummins, Enda
• Is Part Of: Human & ecological risk assessment. Volume 22:Issue 4(2016)
• Page Start: 958
• Page End: 990
• Publication Date: 2016-05-18
• Subjects: water -- contaminants -- biosolids -- risk -- soil -- human consumption; Health risk assessment -- Periodicals; Ecological risk assessment -- Periodicals; Ecology -- Periodicals; Risk Assessment -- Periodicals; 363.102
• DOI: 10.1080/10807039.2015.1121376
• Languages: English
• ISSNs: 1080-7039

Abstract

ABSTRACT: A quantitative risk ranking model was developed for human exposure to emerging contaminants (EC) following treated municipal sewage sludge ("biosolids") application to Irish agricultural land. The model encompasses the predicted environmental concentration (PEC) in soil, surface runoff, groundwater, and subsequent drinking water ingestion by humans. Human exposure and subsequent risk was estimated for 16 organic contaminants using a Monte Carlo simulation approach. Nonylphenols ranked the highest across three environmental compartments: concentration in soil (PECsoil ), runoff (PECrunoff ), and groundwater (PECgroundwater ), which had mean values of 5.69 mg/kg, 1.15 × 10 −2 µg/l, and 2.22 × 10 −1 µg/l, respectively. Human health risk was estimated using the LC50 (chemical intake toxicity ratio, (RR)) as a toxicity endpoint combined with PECrunoff and PECgroundwater . NP ranked highest for LC50 combined with PECrunoff and PECgroundwater (mean RR values 1.10 × 10 −4 and 2.40 × 10 −3, respectively). The model highlighted triclocarban and triclosan as ECs requiring further investigation. A sensitivity analysis revealed that soil sorption coefficient and soil organic carbon were the most important parameters that affected model variance (correlation coefficient –0.89 and –0.30, respectively), highlighting the significance of contaminant and soil properties in influencing risk assessments. This model can help to prioritize emerging contaminants of concern requiring vigilance in environmental compartments.