scholarly journals Incorporating terrain specific beaching within a lagrangian transport plastics model for Lake Erie

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Juliette Daily ◽  
Victor Onink ◽  
Cleo E. Jongedijk ◽  
Charlotte Laufkötter ◽  
Matthew J. Hoffman
Keyword(s):  
Great Lakes ◽  
Hydrodynamic Model ◽  
Turbulent Mixing ◽  
Lake Erie ◽  
Three Dimensional ◽  
Absolute Amount ◽  
Plastic Pollution ◽  
Surface Samples ◽  
Mixing Density ◽  
Bodies Of Water

AbstractMass estimates of plastic pollution in the Great Lakes based on surface samples differ by orders of magnitude from what is predicted by production and input rates. It has been theorized that a potential location of this missing plastic is on beaches and in nearshore water. We incorporate a terrain dependent beaching model to an existing hydrodynamic model for Lake Erie which includes three dimensional advection, turbulent mixing, density driven sinking, and deposition into the sediment. When examining parameter choices, in all simulations the majority of plastic in the lake is beached, potentially identifying a reservoir holding a large percentage of the lake’s plastic which in previous studies has not been taken into account. The absolute amount of beached plastic is dependent on the parameter choices. We also find beached plastic does not accumulate homogeneously through the lake, with eastern regions of the lake, especially those downstream of population centers, most likely to be impacted. This effort constitutes a step towards identifying sinks of missing plastic in large bodies of water.

scholarly journals Visualizing The Big Three: Geospatial Interpolation Of Heavy Metal Sediment Contamination In Lake Erie

2021 ◽  
Author(s):  
Danielle E. Mitchell
Keyword(s):  
Heavy Metal ◽  
Great Lakes ◽  
Pollution Control ◽  
Lake Erie ◽  
Scientific Evidence ◽  
Three Dimensional ◽  
Sediment Contamination ◽  
Great Lakes Basin ◽  
Lake Ecosystems ◽  
Essential Heavy Metal

A wealth of resources for economic prosperity have driven development along the shorelines of the Great Lakes for over 150 years. The rapid growth of industrial, agricultural, and residential land use has degraded many natural components of lake ecosystems, including sediments and water quality. In this dissertation, spatiotemporal patterns of non-essential heavy metal sediment contamination in Lake Erie will be examined from historic and contemporary sediment surveys. Three inter-related studies explore innovative methods for improving the validity and overall usefulness of sediment contamination maps that could be used by a variety of stakeholders in pollution control efforts throughout the Lake Erie basin. First, sediment survey designs are analyzed for their utility in creating valid interpolated surfaces from which spatiotemporal comparisons of mercury sediment contamination can be compared over time. The next study explores how ancillary sediment variables and contamination categorization methods can support interpolated maps of cadmium sediment contamination from low-density sediment surveys. The final study introduces a novel method of three-dimensional geovisualization to enhance the geographic representation of lead sediment contamination patterns throughout the Lake Erie basin. Innovative research methodologies designed for this dissertation may be applied to sediment contamination studies in other Great Lakes. The visualization techniques employed in mapping sediment contamination patterns provide strong scientific evidence for spatiotemporal change in non-essential heavy metal pollution throughout Lake Erie. Combined, the research findings and maps produced throughout this dissertation can contribute to the growing body of knowledge used in environmental decision making for pollution control in the Great Lakes basin

scholarly journals Visualizing The Big Three: Geospatial Interpolation Of Heavy Metal Sediment Contamination In Lake Erie

2021 ◽  
Author(s):  
Danielle E. Mitchell
Keyword(s):  
Heavy Metal ◽  
Great Lakes ◽  
Pollution Control ◽  
Lake Erie ◽  
Scientific Evidence ◽  
Three Dimensional ◽  
Sediment Contamination ◽  
Great Lakes Basin ◽  
Lake Ecosystems ◽  
Essential Heavy Metal

A wealth of resources for economic prosperity have driven development along the shorelines of the Great Lakes for over 150 years. The rapid growth of industrial, agricultural, and residential land use has degraded many natural components of lake ecosystems, including sediments and water quality. In this dissertation, spatiotemporal patterns of non-essential heavy metal sediment contamination in Lake Erie will be examined from historic and contemporary sediment surveys. Three inter-related studies explore innovative methods for improving the validity and overall usefulness of sediment contamination maps that could be used by a variety of stakeholders in pollution control efforts throughout the Lake Erie basin. First, sediment survey designs are analyzed for their utility in creating valid interpolated surfaces from which spatiotemporal comparisons of mercury sediment contamination can be compared over time. The next study explores how ancillary sediment variables and contamination categorization methods can support interpolated maps of cadmium sediment contamination from low-density sediment surveys. The final study introduces a novel method of three-dimensional geovisualization to enhance the geographic representation of lead sediment contamination patterns throughout the Lake Erie basin. Innovative research methodologies designed for this dissertation may be applied to sediment contamination studies in other Great Lakes. The visualization techniques employed in mapping sediment contamination patterns provide strong scientific evidence for spatiotemporal change in non-essential heavy metal pollution throughout Lake Erie. Combined, the research findings and maps produced throughout this dissertation can contribute to the growing body of knowledge used in environmental decision making for pollution control in the Great Lakes basin

Zebra Mussels as Biomonitors for Organic Contaminants in the Lower Great Lakes

1996 ◽  
Vol 31 (2) ◽  
pp. 411-432 ◽  
Author(s):  
Michael E. Comba ◽  
Janice L. Metcalfe-Smith ◽  
Klaus L.E. Kaiser
Keyword(s):  
Great Lakes ◽  
Organic Contaminants ◽  
Lake Erie ◽  
Soft Tissues ◽  
Lake Ontario ◽  
Dry Weight ◽  
Zebra Mussels ◽  
Organic Contamination ◽  
Contamination Levels ◽  
St Lawrence River

Abstract Zebra mussels were collected from 24 sites in Lake Erie, Lake Ontario and the St. Lawrence River between 1990 and 1992. Composite samples of whole mussels (15 sites) or soft tissues (9 sites) were analyzed for residues of organochlo-rine pesticides and PCBs to evaluate zebra mussels as biomonitors for organic contaminants. Mussels from most sites contained measurable quantities of most of the analytes. Mean concentrations were (in ng/g, whole mussel dry weight basis) 154 ΣPCB, 8.4 ΣDDT, 3.5 Σchlordane, 3.4 Σaldrin, 1.4 ΣBHC, 1.0 Σendosulfan, 0.80 mirex and 0.40 Σchlorobenzene. Concentrations varied greatly between sites, i.e., from 22 to 497 ng/g for ΣPCB and from 0.08 to 11.6 ng/g for ΣBHC, an indication that mussels are sensitive to different levels of contamination. Levels of ΣPCB and Σendosulfan were highest in mussels from the St. Lawrence River, whereas mirex was highest in those from Lake Ontario. Overall, mussels from Lake Erie were the least contaminated. These observations agree well with the spatial contaminant trends shown by other biomoni-toring programs. PCB congener class profiles in zebra mussels are also typical for nearby industrial sources, e.g., mussels below an aluminum casting plant contained 55% di-, tri- and tetrachlorobiphenyls versus 31% in those upstream. We propose the use of zebra mussels as biomonitors of organic contamination in the Great Lakes.

scholarly journals Microplastics distribution in the Eurasian Arctic is affected by Atlantic waters and Siberian rivers

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Evgeniy Yakushev ◽  
Anna Gebruk ◽  
Alexander Osadchiev ◽  
Svetlana Pakhomova ◽  
Amy Lusher ◽  
...  
Keyword(s):  
Surface Water ◽  
Surface Waters ◽  
Water Masses ◽  
The Arctic ◽  
Plastic Pollution ◽  
Siberian River ◽  
Highest Weight ◽  
Surface Samples ◽  
Atlantic Origin ◽  
Type Size

AbstractPlastic pollution is globally recognised as a threat to marine ecosystems, habitats, and wildlife, and it has now reached remote locations such as the Arctic Ocean. Nevertheless, the distribution of microplastics in the Eurasian Arctic is particularly underreported. Here we present analyses of 60 subsurface pump water samples and 48 surface neuston net samples from the Eurasian Arctic with the goal to quantify and classify microplastics in relation to oceanographic conditions. In our study area, we found on average 0.004 items of microplastics per m3 in the surface samples, and 0.8 items per m3 in the subsurface samples. Microplastic characteristics differ significantly between Atlantic surface water, Polar surface water and discharge plumes of the Great Siberian Rivers, allowing identification of two sources of microplastic pollution (p < 0.05 for surface area, morphology, and polymer types). The highest weight concentration of microplastics was observed within surface waters of Atlantic origin. Siberian river discharge was identified as the second largest source. We conclude that these water masses govern the distribution of microplastics in the Eurasian Arctic. The microplastics properties (i.e. abundance, polymer type, size, weight concentrations) can be used for identification of the water masses.

Three-dimensional bluff evolution in response to seasonal fluctuations in Great Lakes water levels

2020 ◽  
Vol 46 (6) ◽  
pp. 1533-1543 ◽  
Author(s):  
C.A. Volpano ◽  
L.K. Zoet ◽  
J.E. Rawling ◽  
E.J. Theuerkauf ◽  
R. Krueger
Keyword(s):  
Great Lakes ◽  
Three Dimensional ◽  
Water Levels ◽  
Seasonal Fluctuations

Investigation of Turbulent Mixing in a Macro-Scale Multi-Inlet Vortex Nanoprecipitation Reactor by Stereoscopic-PIV

2014 ◽  
Author(s):  
Zhenping Liu ◽  
James C. Hill ◽  
Rodney O. Fox ◽  
Michael G. Olsen
Keyword(s):  
Reynolds Number ◽  
Turbulent Mixing ◽  
Three Dimensional ◽  
Stereoscopic Particle Image Velocimetry ◽  
Vortex Center ◽  
Mean Velocity ◽  
Vortex Model ◽  
Functional Nanoparticles ◽  
Turbulent Characteristics ◽  
Macro Scale

Flash Nanoprecipitation (FNP) is a technique to produce monodisperse functional nanoparticles through rapidly mixing a saturated solution and a non-solvent. Multi-inlet vortex reactors (MIVR) have been effectively applied to FNP due to their ability to provide both rapid mixing and the flexibility of inlet flow conditions. Until recently, only micro-scale MIVRs have been demonstrated to be effective in FNP. A scaled-up MIVR could potentially generate large quantities of functional nanoparticles, giving FNP wider applicability in the industry. In the present research, turbulent mixing inside a scaled-up, macro-scale MIVR was measured by stereoscopic particle image velocimetry (SPIV). Reynolds number of this reactor is defined based on the bulk inlet velocity, ranging from 3290 to 8225. It is the first time that the three-dimensional velocity field of a MIVR was experimentally measured. The influence of Reynolds number on mean velocity becomes more linear as Reynolds number increases. An analytical vortex model was proposed to well describe the mean velocity profile. The turbulent characteristics such as turbulent kinematic energy and Reynolds stress are also presented. The wandering motion of vortex center was found to have a significant contribution to the turbulent kinetic energy of flow near the center area.

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