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Velocity dependent passive sampling for monitoring of micropollutants in dynamic stormwater discharges

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Authors:
  • Birch, Heidi ;
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    Orcid logo0000-0002-7152-3832
    Department of Environmental Engineering, Technical University of Denmark
  • Sharma, Anitha Kumari ;
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    Department of Environmental Engineering, Technical University of Denmark
  • Vezzaro, Luca ;
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    Orcid logo0000-0001-6344-7131
    Department of Environmental Engineering, Technical University of Denmark
  • Lützhøft, Hans-Christian Holten ;
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    Residual Resource Engineering, Department of Environmental Engineering, Technical University of Denmark
  • Mikkelsen, Peter Steen
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    Orcid logo0000-0003-3799-0493
    Department of Environmental Engineering, Technical University of Denmark
DOI:
10.1021/es403129j
Abstract:
Micropollutant monitoring in stormwater discharges is challenging because of the diversity of sources and thus large number of pollutants found in stormwater. This is further complicated by the dynamics in runoff flows and the large number of discharge points. Most passive samplers are non-ideal for sampling such systems because they sample in a time-integrative manner. This paper reports test of a flow-through passive sampler, deployed in stormwater runoff at the outlet of a residential-industrial catchment. Momentum from the water velocity during runoff events created flow through the sampler resulting in velocity dependent sampling. This approach enables the integrative sampling of stormwater runoff during periods of weeks to months while weighting actual runoff events higher than no flow periods. Results were comparable to results from volume-proportional samples and results obtained from using a dynamic stormwater quality model (DSQM). The paper illustrates how velocity-dependent flow-through passive sampling may revolutionize the way stormwater discharges are monitored. It also opens the possibility to monitor a larger range of discharge sites over longer time periods instead of focusing on single sites and single events, and it shows how this may be combined with DSQMs to interpret results and estimate loads over extended time periods.
Type:
Journal article
Language:
English
Published in:
Environmental Science and Technology, 2013, Vol 47, Issue 22
Main Research Area:
Science/technology
Publication Status:
Published
Review type:
Peer Review
Submission year:
2013
Scientific Level:
Scientific
ID:
249884053

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