Modeling Inactivation of Highly Persistent Pathogens in Household-Scale Semi-Continuous Anaerobic Digesters

Document Type

Article

Publication Date

11-1-2016

Abstract

© Copyright 2016, Mary Ann Liebert, Inc. 2016. Household-scale anaerobic digesters (ADs) are used to stabilize and recover energy from organic wastes generated by rural agricultural communities. These systems are typically operated under ambient conditions and fed intermittently; however, use of ADs in this manner may not be sufficient to inactivate prominent human pathogens such as Ascaris spp. In this study, a mathematical model was developed to describe and predict inactivation of Ascaris suum in household-scale semi-continuous ADs. The model was based on the segregated flow model, which combines the following: (1) an expression for the residence time distribution of semi-continuous reactors in terms of feeding interval (FI) and solids retention time (SRT) and (2) an expression for A. suum inactivation in a batch reactor. Three mathematical expressions for pathogen inactivation in batch reactors are presented based on results of laboratory experiments. The segregated flow model predicted that, under mesophilic conditions (35°C), pathogen inactivation was weakly dependent on FI (61% inactivation when FI = 2 days, 64% when FI = 7 days) but strongly dependent on SRT (40% inactivation when SRT = 15 days, 73% when SRT = 45 days). Comparison of segregated flow model results using different pathogen inactivation expressions suggested that a "sudden-die-off" model offered a conservative approach when detailed laboratory data are not available. Near 100% removal of A. suum can be achieved when the FI exceeds the time required for complete inactivation under ambient conditions. This result identified a potential design and operational strategy for small-scale ADs that are operated in areas afflicted with neglected tropical diseases, such as soil-transmitted helminths.

Publication Title

Environmental Engineering Science

Link to Full Text

Share

COinS