Peristaltic pump autosamplers for solids measurement in stormwater runoff

Shirley E. Clark, Christina Y.S. Siu, Robert Pitt, Christopher D. Roenning, Daniel P. Treese

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

Regulatory agencies approve automatic samplers containing peristaltic pumps as a sample collection method for stormwater characterization and for treatment-device evaluation. Autosampler performance, as discussed in the limited available literature, can vary across the entire particle size range typically found in stormwater from different source areas and outfalls-reasonably consistent performance for particle sizes <250 μm, but much less consistency for particles >250 μm. Therefore, a series of experiments was undertaken to quantify the upper range of consistent particle capture that may occur with sampling stormwater suspended sediment and particulate-bound pollutants. These experiments, based on triplicate sampling at each experimental condition, found that peristaltic pump autosamplers commonly used in stormwater monitoring could not repeatedly and effectively capture particles >250 μm from a simulated stormwater whose particles have a specific gravity of 2.65. It was expected that the effective size for autosamplers would be correspondingly larger for particles having smaller specific gravities. The height of the sampler had no influence on particle recovery up to a height of 2.5 m, with slightly decreasing recoveries of large particles occurring at greater heights, as a result of reduced sampler intake velocity. Therefore, to characterize the solids across the entire size range and specific gravities that may occur in stormwater runoff, autosamplers should be deployed in conjunction with bedload and floatables sampling. Water Environ.

Original languageEnglish (US)
Pages (from-to)192-200
Number of pages9
JournalWater Environment Research
Volume81
Issue number2
DOIs
StatePublished - Feb 2009

All Science Journal Classification (ASJC) codes

  • Environmental Chemistry
  • Ecological Modeling
  • Water Science and Technology
  • Waste Management and Disposal
  • Pollution

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