Literature DB >> 26283620

A high-precision sampling scheme to assess persistence and transport characteristics of micropollutants in rivers.

Marc Schwientek1, Gaëlle Guillet2, Hermann Rügner3, Bertram Kuch4, Peter Grathwohl2.   

Abstract

Increasing numbers of organic micropollutants are emitted into rivers via municipal wastewaters. Due to their persistence many pollutants pass wastewater treatment plants without substantial removal. Transport and fate of pollutants in receiving waters and export to downstream ecosystems is not well understood. In particular, a better knowledge of processes governing their environmental behavior is needed. Although a lot of data are available concerning the ubiquitous presence of micropollutants in rivers, accurate data on transport and removal rates are lacking. In this paper, a mass balance approach is presented, which is based on the Lagrangian sampling scheme, but extended to account for precise transport velocities and mixing along river stretches. The calculated mass balances allow accurate quantification of pollutants' reactivity along river segments. This is demonstrated for representative members of important groups of micropollutants, e.g. pharmaceuticals, musk fragrances, flame retardants, and pesticides. A model-aided analysis of the measured data series gives insight into the temporal dynamics of removal processes. The occurrence of different removal mechanisms such as photooxidation, microbial degradation, and volatilization is discussed. The results demonstrate, that removal processes are highly variable in time and space and this has to be considered for future studies. The high precision sampling scheme presented could be a powerful tool for quantifying removal processes under different boundary conditions and in river segments with contrasting properties.
Copyright © 2015. Published by Elsevier B.V.

Entities:  

Keywords:  Diurnal patterns; Mass balances; Micropollutants; Removal processes; River segments

Mesh:

Substances:

Year:  2015        PMID: 26283620     DOI: 10.1016/j.scitotenv.2015.07.135

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


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3.  Smarter Sediment Screening: Effect-Based Quality Assessment, Chemical Profiling, and Risk Identification.

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  4 in total

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