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Understanding the Structure-Function Relationships of Aquatic Sediment Flocs

AquaFloc is a three year project funded by a Natural Environment Research Council (NERC) Standard Project Grant. Beginning in November 2016, the Project aims to use a suite of interdisciplinary imaging techniques combined with numerical modelling in order to answer how the physical properties of composite particles formed in suspension by flocculation processes affect their hydrodynamic behaviour and eventual fate, i.e., floc transport and mass settling flux.

Flocs influence a wide array of environmental phenomena, from the transport of sediments, contaminants and biological matter within rivers and estuaries, to the effective removal of impurities during industrial drinking and waste water treatment. Reliable models describing the hydrodynamic behaviour of flocs are therefore critical to making informed management decisions. Yet, flocs are highly dynamic and their physical properties (e.g., size, shape and structure etc.), which vary both spatially and temporally, often span several orders of magnitude in scale, i.e., the nanometre to millimetre-scale. This makes their characterisation for modelling problematic.

The AquaFloc Project utilises a novel sampling and multi-scale imaging workflow which permits floc structure-function relationships to be investigated in detail for the first time. The main aspects of this strategy are:

  • Non-destructive sampling and stabilisation. In order to ensure minimal perturbation to flocs during their capture and stabilisation the project uses methods previously developed in floc research in addition to techniques adapted from other scientific disciplines.
  • Multi-scale imaging. The Project combines settling measurements obtained using the Laboratory Spectral Flocculation Characteristics (LabSFLOC) apparatus with structural data acquired using 3D X-ray computed tomography (X-ray CT), 3D focused ion beam nanotomography (FIB-nt) and 2D scanning transmission electron microscopy (STEM). X-ray CT enables the 3D size, shape and density of large numbers (100’s) of flocs to be measured simultaneously and the identification of those floc parameters that distinguish different populations. Representative individual flocs can then be further analysed using FIB-nt, which provides details regarding their composition and the 3D particle-particle and structural associations within the flocs. Additional information regarding particle associations can then be gained using STEM, which also informs on the presence of biostabilising extracellular fibrils secreted by floc colonising microorganisms. The co-visualisation of these nested, multi-scale 3D datasets enables a clear understanding of how the organisation of individual particles at the nanometre-scale culminates to result in an entire floc potentially several millimetres in size.
  • Parametrization of numerical models. Numerical modelling is critical to the Project since it provides the capability to study the dynamic behaviour of flocs and their interaction with the surrounding aquatic environment in real time. Hydrodynamic floc behaviour will be simulated by extending software for particulate flows developed at QMUL to simulate particles connected into a floc network. This innovative software accounts for full hydrodynamic interaction between the particles, and between the particles and the fluid, and handles finite-Reynolds number effects that are important when simulating large flocs, or flocs in turbulence.

Aims of the Project

The two main research questions of the AquaFloc Project are:

  1. Do sediment composition and physico-chemical characteristics of transporting medium result in indicative floc microstructure? The physical properties of flocs depend on different types of particles in suspension (e.g., clay minerals, microorganisms, decaying organic detritus etc.), the prevailing conditions of their aquatic surroundings (e.g., turbulence, salinity etc.) and the transport history of the floc (i.e., number of cycles of settling, consolidation in the bed, erosion and re-suspension). However, it is unknown if flocs exhibit microstructures that are indicative of the environmental conditions under which they formed. Answering this question could enable us to better predict the ‘types’ of flocs likely to be present within a given environment and an understanding of their potential behaviour.
  2. What is the influence of 3D floc shape and internal structure on floc behaviour? Flocs are currently described as 2D geometric simplifications (e.g., equivalent spherical diameter) and their density and internal porosity is inferred from Stokes’ Law based on the assumption of spherical shape and fractal behaviour (e.g., that floc structure is self-similar across scales). This is due to the difficulties associated with floc sampling and characterisation, and it remains unclear what exact effects their 3D shape and internal structure has on their behaviour. The AquaFloc Project can explore whether 3D multi-scale datasets of floc structure provide effective parameters that better describe the effect of floc microstructure on settling compared with traditional fractal mathematics. Additionally, the ability to investigate particle-particle and structural associations within individual flocs enables an improved understanding of how floc stability is influenced by their internal structure and the mechanisms that promote its development (e.g., cohesive and adhesive inter-particle forces).

 Project Team

  • Kate Spencer (Project Lead), Professor of Environmental Geochemistry, School of Geography, Queen Mary University of London
  • Andy Bushby, Reader in Materials, School of Engineering and Materials Science, Queen Mary University of London
  • Simon Carr, Senior Lecturer in Geography, School of Geography, Queen Mary University of London
  • Lorenzo Botto, Senior Lecturer in Fluid Mechanics, Reader in Materials, School of Engineering and Materials Science, Queen Mary University of London
  • Andy Manning, Lecturer in Coastal and Shelf Physical Oceanography, School of Biological & Marine Sciences, University of Plymouth
  • Jonathan Wheatland, Senior Postdoctoral Research Associate, School of Geography, Queen Mary University of London
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