A quantitative microbial risk assessment model for total coliforms and e. coli in surface runoff following application of biosolids to grassland
Healy, Mark G.
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Clarke, Rachel, Peyton, Dara, Healy, Mark G., Fenton, Owen, & Cummins, Enda. (2017). A quantitative microbial risk assessment model for total coliforms and E. coli in surface runoff following application of biosolids to grassland. Environmental Pollution, 224, 739-750. doi: http://doi.org/10.1016/j.envpol.2016.12.025
In Ireland, the land application of biosolids is the preferred option of disposing of municipal sewage waste. Biosolids provide nutrients in the form of nitrogen, phosphorus, potassium and increases organic matter. It is also an economic way for a country to dispose of its municipal waste. However, biosolids may potentially contain a wide range of pathogens, and following rainfall events, may be transported in surface runoff and pose a potential risk to human health. Thus, a quantitative risk assessment model was developed to estimate potential pathogens in surface water and the environmental fate of the pathogens following dilution, residence time in a stream, die-off rate, drinking water treatment and human exposure. Surface runoff water quality data was provided by project partners. Three types of biosolids, anaerobically digested (AD), lime stabilised (LS), and thermally dried (TD)) were applied on micro plots. Rainfall was simulated at three time intervals (24, 48 and 360 h) following land application. It was assumed that this water entered a nearby stream and was directly abstracted for drinking water. Consumption data for drinking water and body weight was obtained from an Irish study and assigned distributions. Two dose response models for probability of illness were considered for total and faecal coliform exposure incorporating two different exposure scenarios (healthy populations and immuno-compromised populations). The simulated annual risk of illness for healthy populations was below the US EPA and World Health Organisation tolerable level of risk (10−4 and 10−6, respectively). However, immuno-compromised populations may still be at risk as levels were greater than the tolerable level of risk for that subpopulation. The sensitivity analysis highlighted the importance of residence time in a stream on the bacterial die-off rate.