Purpose <p>Passive particle traps (PTs) are cost-efficient and easy to operate tools for the time integrative monitoring of particulate contaminants in surface fresh waters. Box-type PTs are designed as boxes through which the river flow is slowed down in order to collect Suspended Particulate Matter (SPM). However, a particle-size distribution bias in collection suggests that the finest particles pass through PTs without settling. The aim of this study is to quantify SPM trapping efficiency as a function of particle size, and to develop a predictive model.</p> Methods <p>We designed laboratory experiments using box-type PTs. The trap was either submerged in a SPM-laden flow (in-flow experiment); or directly supplied with water and SPM with a pipe connected to its inlet (in-line experiments). SPM concentration, particle-size distributions (PSD), flow velocity were controlled and recorded.</p> Results <p>In-line experiment results confirmed that coarser particles are more efficiently trapped than smaller ones due to their higher settling velocity. The particle-size trapping efficiency was regressed against PT dimensions and incoming flow velocity. The application of these results to in-flow and field experiments confirmed the validity of our predictive model.</p> Conclusion <p>This study highlighted how crucial it is to deploy particle traps in an area with low current velocities, in order to limit the granulometric bias. We developed a predictive model that will be an asset to quantify particle-size distribution bias and to better understand potential particulate contaminants concentrations shifts. This work represents a significant step forward to a thorough use of PTs.</p>

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Integrative sampling of suspended particulate matter in rivers: assessing the grain-size dependent efficiency of passive particle traps

  • Céline Berni,
  • Yann Bonenfant,
  • Matthieu Masson,
  • Jérôme Le Coz,
  • Aymeric Dabrin,
  • Fabien Thollet

摘要

Purpose

Passive particle traps (PTs) are cost-efficient and easy to operate tools for the time integrative monitoring of particulate contaminants in surface fresh waters. Box-type PTs are designed as boxes through which the river flow is slowed down in order to collect Suspended Particulate Matter (SPM). However, a particle-size distribution bias in collection suggests that the finest particles pass through PTs without settling. The aim of this study is to quantify SPM trapping efficiency as a function of particle size, and to develop a predictive model.

Methods

We designed laboratory experiments using box-type PTs. The trap was either submerged in a SPM-laden flow (in-flow experiment); or directly supplied with water and SPM with a pipe connected to its inlet (in-line experiments). SPM concentration, particle-size distributions (PSD), flow velocity were controlled and recorded.

Results

In-line experiment results confirmed that coarser particles are more efficiently trapped than smaller ones due to their higher settling velocity. The particle-size trapping efficiency was regressed against PT dimensions and incoming flow velocity. The application of these results to in-flow and field experiments confirmed the validity of our predictive model.

Conclusion

This study highlighted how crucial it is to deploy particle traps in an area with low current velocities, in order to limit the granulometric bias. We developed a predictive model that will be an asset to quantify particle-size distribution bias and to better understand potential particulate contaminants concentrations shifts. This work represents a significant step forward to a thorough use of PTs.