TY - JOUR
T1 - Microbial immigration in wastewater treatment systems
T2 - analytical considerations and process implications
AU - Frigon, Dominic
AU - Wells, George
N1 - Publisher Copyright:
© 2019
PY - 2019/6
Y1 - 2019/6
N2 - Microbial immigration from sewers to wastewater treatment systems is attracting increasing attention for understanding community assembly mechanisms, and improving process modeling and operation. While there is no consensus on approaches to analyze immigration, we suggest to classify them as relevant to either rare (non-observable) diffusive immigration or to time-continuous high-rate mass flow immigration (i.e. mass effects). When analyzed by a mass flow approach, heterotrophs appear to be strongly influenced by deterministic selection, suggesting that the heterotrophs should be subdivided into several functional guilds when assessing their assembly mechanisms. Conversely, nitrifiers appear to transfer neutrally from sewer to activated sludge, and this immigration can restore full nitrification in otherwise non-nitrifying reactors. With further refinement, these findings could be included in predictive process models with various objectives.
AB - Microbial immigration from sewers to wastewater treatment systems is attracting increasing attention for understanding community assembly mechanisms, and improving process modeling and operation. While there is no consensus on approaches to analyze immigration, we suggest to classify them as relevant to either rare (non-observable) diffusive immigration or to time-continuous high-rate mass flow immigration (i.e. mass effects). When analyzed by a mass flow approach, heterotrophs appear to be strongly influenced by deterministic selection, suggesting that the heterotrophs should be subdivided into several functional guilds when assessing their assembly mechanisms. Conversely, nitrifiers appear to transfer neutrally from sewer to activated sludge, and this immigration can restore full nitrification in otherwise non-nitrifying reactors. With further refinement, these findings could be included in predictive process models with various objectives.
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U2 - 10.1016/j.copbio.2019.02.021
DO - 10.1016/j.copbio.2019.02.021
M3 - Review article
C2 - 31030172
AN - SCOPUS:85064590053
SN - 0958-1669
VL - 57
SP - 151
EP - 159
JO - Current Opinion in Biotechnology
JF - Current Opinion in Biotechnology
ER -