Flocculation dynamics of cell-associated suspended particulate matter Thu Ha Nguyen School of Civil Engineering Faculty of Engineering The University of Sydney A thesis submitted to fulfil requirements for the degree of Doctor of Philosophy Supervisor: Assoc. Federico Maggi Auxiliary supervisors: Prof. John Patterson Dr. Fiona Tang 2020 Abstract Transport of suspended particulate matter (SPM) plays a vital role in controlling large-scale pro- cesses related to geophysical flows such as dispersal and sinking of organic matter and contaminants to offshore and deep waters, nutrient cycles, food web stability, morphodynamics and sedimen- tation in both limnetic and pelagic ecosystems.
Although it has been recognized that small-scale microbial processes can introduce substantial differences to the way in which SPM moves in natural waters, the extent to which the attached biological matter affects SPM dynamics is still not well characterized. This thesis focuses on quantifying the attached biomass fraction on SPM aggregates and investigating its contribution to SPM flocculation dynamics, which consequently control SPM aggregate geometrical properties and transport. A novel laboratory-based Optical Measurement of Cell Colonization (OMCEC) system and a microbiological-physical model (BFLOC2) are the main achievements of this thesis that allow the analyses of the correlations between environmental conditions, aggregate-attached biomass fraction, cell colonization patterns, aggregate size, fractal dimension and settling velocity. OMCEC is an experimental system that can simultaneously measure the material composition, geometric properties, and motion of individual suspended aggregates in a non-invasive and non- destructive way.
OMCEC consists of a full-color high-resolution optical system and real-time algorithms for (i) material segmentation based on light spectra emission analysis, (ii) quantification of various geometrical properties, and (iii) motion detection with micro particle tracking velocimetry (µPTV). OMCEC was applied herein on three types of aggregates: cell-associated minerals, cell- associated microplastics, and three-phase aggregates made of minerals, microplastics, and biological matter. OMCEC application on Saccharomyces cerevisiae-colonized minerals at four sucrose concentra- tions showed the likelihood of cell colonization to increase with increasing nutrient concentration. The attached biomass fraction was found to increase nonlinearly regarding an increase of aggregate size but almost constant with fractal dimension variation.
Cell distribution on mineral surfaces was then analyzed and classified into three colonization patterns: (i) scattered, (ii) well-touched, and (iii) poorly-touched, with the second being predominant. Cell clusters in the well-touched pattern were found to have lower fractal dimension than those in the other patterns. A strong correlation of colonization patterns with aggregate biomass fraction and properties suggests dynamic colonization iv mechanisms from cell attachment to minerals, to joining of isolated cell clusters, and finally cell growth over the entire aggregate. OMCEC application on microplastics (MPs) being colonized by natural biological matter from Hawkesbury River, NSW, Australia demonstrated that the biomass fraction of MP aggregates has substantial control over their size, shape and, most importantly, their settling velocity.
Polyurethane MP aggregates made of 80% biological matter had an average size almost double that of MP aggregates containing 5% biological matter and sank two times slower. Based on our experimental data, we introduce a settling velocity equation that accounts for the shape irregularity and fractal structure of MP aggregates. This equation can capture the settling velocity of both virgin MPs and cell-associated MP aggregates with 7% error and can be applied widely to predict the settling flux of MP aggregates made of different polymers and various types of biological matter. To consider the complex genesis of cell-associated mineral aggregates, the BFLOC2 model was introduced to predict aggregate geometry and settling velocity under simultaneous effects of hydrodynamic and biological processes.
While minerals can contribute to aggregate dynamics through collision, aggregation, and breakup, living microorganisms can colonize and establish food web interactions that involve growth and grazing, and modify the aggregate structure. Modeling of cell-associated mineral aggregate dynamics over a wide range of environmental conditions showed that maximum aggregate size, biomass fraction, and settling velocity could occur at different optimal environmental conditions. Unlike mineral aggregates, which have maximum size when shear rates tend to zero, a relative maximum size of cell-associated mineral aggregates can be reached at intermediate shear rates as a result of microbiological processes. The settling velocity was ultimately controlled by aggregate size, fractal dimension, and biomass fraction.
The innovative aspect of this thesis is the simultaneous quantification of composition, archi- tecture, and settling velocity of individual aggregates. Therefore, it puts forth the analysis and prediction of cell colonization impacts on dynamics and transport of suspended particulate matter in natural waters. The output of this thesis can be used in natural water monitoring programs to estimate the biological content based on SPM size, capacity dimension, and settling velocity, which can be measured using in-situ methods. Furthermore, the evidence and tools to quantify the sinking and floating of microplastic subjected to bio-fouling can be implemented in microplastics transport models to enable the three-dimension modeling of both low- and high-density microplastics.
The BFLOC2 model can be coupled to traditional sediment transport models to better describe the sediment formation dynamics, thus giving a more precise prediction of sedimentation and carbon flux to deep waters and offshore. v Statement of Originality This is to certify that to the best of my knowledge, the content of this thesis is my own work. This thesis has not been submitted for any degree or other purposes. I certify that the intellectual content of this thesis is the product of my own work and that all the assistance received in preparing this thesis and sources have been acknowledged.
Name: Thu Ha Nguyen Signature: (signed) Date: 30/01/2020 viii Authorship Attribution Statement Chapter 3 of this thesis was published in manuscripts [195, 197, 198]. I developed the method, conducted the experiments, and wrote the manuscripts. The settling column used in the system was designed and built by the co-authors (F. Chapter 4 of this thesis was published in manuscript [195].
I conducted the experiments, ana- lyzed the data, and wrote the manuscripts. Chapter 5 of this thesis was published in manuscript [198]. I conducted the experiments, ana- lyzed the data, developed the equation, and wrote the manuscripts. The field sampling was done by all authors with the support of New South Wales Office of Environment and Heritage (NSW-OEH).
Chapter 6 of this thesis was published in manuscript [196]. I developed the model, conducted the simulation, analyzed the data, and wrote the manuscripts. The source code of the BFLOC model, which is the based of the BFLOC2 model in the thesis, was developed by the co-author (F. List of publications: [195] Nguyen, T.
Optical measurement of cell col- onization patterns on individual suspended sediment aggregates. Micro food web networks on suspended sediment. OMCEC: A novel method for simultaneous detection of composition, geometry and motion of suspended particles. In Proceedings 16th International Conference on Environmental Science and Technology.
Sinking of microbial-associated mi- croplastics in natural waters. Nguyen) confirm that I am the first and the corresponding author of the publications listed above. Name: Thu Ha Nguyen Signature: (signed) Date: 30/01/2020 As supervisor for the candidature upon which this thesis is based, I can confirm that the au- thorship attribution statements above are correct. Federico Maggi Signature: (signed) Date: 30/01/2020 Table of contents Abstract iii Statement of Originality vii Authorship Attribution Statement ix List of figures xv List of tables xvii 1 Introduction 1 1.1 Suspended sediment and microbial colonization in natural waters .2 Anthropogenic perturbation on SPM dynamics .3 Aim and objectives .1 Formation dynamics of SPM aggregates .1 Hydrodynamic-induced aggregation .2 Biogenic-induced aggregation .3 Hydrodynamic-induced breakup .4 Biogenic-induced breakup .5 On-site micro food web network interactions .2 Geometrical and settling properties of SPM aggregates .1 Mineral SPM and cell-associated mineral SPM aggregates .2 Microplastic SPM and cell-associated microplastic SPM aggregates .3 Bridging the gap - Biological heterogeneity in cell-associated SPM aggregates .4 SPM architecture, motion, and composition measurements .1 SPM architecture and motion measurement methods .2 SPM composition measurement methods.
19 xii Table of contents 2. 21 3 Optical Measurement Of Cell Colonization (OMCEC) System 23 3.3 Biological matter sources .3 OMCEC optical system and image acquisition .4 OMCEC coupling to a fully controlled settling column .5 Image processing algorithms .1 Image pre-processing .3 Image post-processing .6 OMCEC example results. 39 4 Cell-associated mineral SPM aggregates 41 4.2 Experiments, image processing, and analyses with OMCEC .3 Classification of aggregate types and cell colonization patterns .1 Sucrose concentration effects on cell colonization .2 Biomass fraction and aggregate geometrical properties .3 Biomass fraction and cell colonization patterns .4 Cell colonization mechanisms .5 Cell colonization patterns and aggregate geometrical properties .6 Interplay between geometric properties. 55 Table of contents xiii 5 Cell-associated microplastic SPM aggregates 57 5.2 Experiments, image processing, and analyses with OMCEC .3 Terminal velocity equation .4 Reynolds number and vertical mass flux .1 Cell colonization on MP aggregates .2 Biological fraction and MP aggregate geometrical properties .3 Biological fraction and MP aggregate settling .4 Modeling the settling velocity of MP aggregates .5 Biological fraction and MP aggregate capacity dimension .6 Terminal velocity of low- and high-density MPs .7 Mass flux of low- and high-density MPs.
72 6 Modeling of cell-associated SPM aggregate formation dynamics 73 6.1 Model calibration against mineral SPM .2 Model calibration against biological SPM .3 Model calibration and validation against cell-associated SPM .4 Aggregate composition response to environmental conditions .5 Aggregate size, capacity dimension, and settling velocity response to envi- ronmental conditions .6 Constituent aggregate volumes response to environmental conditions .7 Aggregate genesis dynamics response to environmental conditions. 92 xiv Table of contents 7 Conclusions and recommendations 95 7.1 Thesis accomplishments and conclusions .2 Thesis applications and recommendations. 97 References 99 Appendix A Data of cell-associated mineral experiments 121 Appendix B Data of cell-associated microplastic experiments 157 List of Symbols 171 Acknowledgements 179 List of figures 2.1 Conceptual SPM formation dynamics in natural waters .2 Control factors of SPM settling velocity .1 OMCEC flow chart .2 Emission spectra of materials used in OMCEC .3 Mineral staining procedure .6 OMCEC image processing flowchart.8 OMCEC error corrections .9 OMCEC example results .1 Examples of material map analyses.2 Classification tree of aggregate types and cell colonization patterns .3 Examples of classified aggregate types and cell colonization patterns .4 Effects of nutrient concentrations on cell colonization .5 Aggregate geometrical properties versus biomass fraction .6 Cell colonization patterns versus biomass fraction .7 Cell colonization patterns versus aggregate geometric properties .8 Interplay between geometric properties .1 Example microscope images .2 Samples of cell-associated MP aggregates acquired with OMCEC .3 MP aggregate size analyses .4 MP aggregate shape analyses .5 MP aggregate experimental settling velocity analyses .6 Terminal velocity equation validation and aggregate capacity dimension estimation 67 5.7 Analyses of low- and high-density MPs associated with biological matter. 69 xvi List of figures 6.3 Aggregate composition response to environmental conditions .4 Aggregate architecture and motion response to environmental conditions .5 Aggregate size response to shear rates .6 Aggregate constituent volumes response to environmental conditions .7 Aggregate genesis dynamics response to environmental conditions.
90 List of tables 4.1 Specifications of samples used for OMCEC testing .2 Results of the one-way analysis of variance (ANOVA) tests for the null hypothesis that the bin-averaged aggregate capacity dimension d, biological phase capacity dimension db , cell cluster count Nc , and cell cluster area over aggregate area ab /A values are invariant over ranges of the aggregate size L and d for each cell colo- nization pattern. Green, turquoise, and red colors indicate that the null hypothesis is rejected (i.01 ) for the scattered, well- and poorly-touched clustered patterns, respectively, while the grey color confirms the null hypothesis (i.1 Parameters used for settling velocity in Eq. Parameters in brackets were estimated from calibration, while the others were measured from experiments, assumed, and retrieved from the manufacture data sheet.1 List of parameters used in BFLOC2 for mineral and biological calibrations, cell- associated mineral validation, and cell-associated mineral analyses described in Section 6. Parameters in brackets were estimated from experiments, while the others were assigned from the experimental inputs and previous literature.
81 xviii List of tables A.