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Anaerobic digestion of agricultural manure and biomass – Critical indicators of risk and knowledge gaps
Nag, Rajat Auer, Agathe Markey, Bryan K. Whyte, Paul Nolan, Stephen O'Flaherty, Vincent Russell, Lauren Bolton, Declan Fenton, Owen Richards, Karl
Nag, Rajat
Auer, Agathe
Markey, Bryan K.
Whyte, Paul
Nolan, Stephen
O'Flaherty, Vincent
Russell, Lauren
Bolton, Declan
Fenton, Owen
Richards, Karl
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2019-11
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Rajat Nag, Agathe Auer, Bryan K. Markey, Paul Whyte, Stephen Nolan, Vincent O'Flaherty, Lauren Russell, Declan Bolton, Owen Fenton, Karl Richards, Enda Cummins, Anaerobic digestion of agricultural manure and biomass – Critical indicators of risk and knowledge gaps, Science of The Total Environment, Volume 690, 2019, Pages 460-479, ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2019.06.512.
Abstract
Anaerobic digestion (AD) has been identified as a potential green technology to treat food and municipal waste, agricultural residues, including farmyard manure and slurry (FYM&S), to produce biogas. FYM&S and digestate can act as soil conditioners and provide valuable nutrients to plants; however, it may also contain harmful pathogens. This study looks at the critical indicators in determining the microbial inactivation potential of AD and the possible implications for human and environmental health of spreading the resulting digestate on agricultural land. In addition, available strategies for risk assessment in the context of EU and Irish legislation are assessed. Storage time and process parameters (including temperature, pH, organic loading rate, hydraulic retention time), feedstock recipe (carbon-nitrogen ratio) to the AD plant (both mesophilic and thermophilic) were all assessed to significantly influence pathogen inactivation. However, complete inactivation of all pathogens is unlikely. There are limited studies evaluating risks from FYM&S as a feedstock in AD and the spreading of resulting digestate. The lack of process standardisation and varying feedstocks between AD farms means risk must be evaluated on a case by case basis and calls for a more unified risk assessment methodology. In addition, there is a need for the enhancement of AD farm-based modelling techniques and datasets to help in advancing knowledge in this area.