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Water Res. 2019 Sep 1;160:380-393. doi: 10.1016/j.watres.2019.05.009. Epub 2019 May 18.

Large-scale determination of micropollutant elimination from municipal wastewater by passive sampling gives new insights in governing parameters and degradation patterns.

Author information

1
Luxembourg Institute of Science and Technology, 5, avenue des Hauts-Fourneaux, L-4362, Esch-sur-Alzette, Luxembourg. Electronic address: tom.galle@list.lu.
2
Luxembourg Institute of Science and Technology, 5, avenue des Hauts-Fourneaux, L-4362, Esch-sur-Alzette, Luxembourg. Electronic address: christian.koehler@list.lu.
3
Luxembourg Institute of Science and Technology, 5, avenue des Hauts-Fourneaux, L-4362, Esch-sur-Alzette, Luxembourg.
4
Rovira i Virgili University, Tecnatox - Department of Chemical Engineering, Països Catalans, 26, 43007, Tarragona, Spain.
5
University of Luxembourg, Faculty of Science, Technology and Communication, 6, rue Richard Coudenhove-Kalergi, L-1359, Luxembourg.

Abstract

A simple balancing method using passive samplers over a week's period has been developed and tested successfully to determine elimination rates of 22 common micropollutants of household and industrial sources in 18 full-scale wastewater treatment plants of different design and performance. Independent reactor tests to delineate elimination rates with native sludge of the treatment plants correlated very well with the full-scale elimination rate determinations. As opposed to common assumptions, this large dataset indicated that shorter sludge retention times - read: higher active biomass - showed higher micropollutant elimination rates in many cases. Multivariate statistical analysis of the elimination rates over the 18 treatment plants was able to group compounds according to common degradation pathways and showed that sensitivity to SRT drove the grouping. The dataset also allowed to determine population equivalent normalized loads of the investigated micropollutants. The application of WWTP balancing with passive sampling makes it relatively easy to gather elimination rates and inlet loads on a much broader basis than before and gives orientation for more in-depth analysis of degradation pathways.

KEYWORDS:

HRT; Metabolic pathways; Micropollutants; POCIS; Respirometry; SRT

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