N
Neil R. Thomson
Researcher at University of Waterloo
Publications - 133
Citations - 3497
Neil R. Thomson is an academic researcher from University of Waterloo. The author has contributed to research in topics: Persulfate & In situ chemical oxidation. The author has an hindex of 33, co-authored 132 publications receiving 3101 citations. Previous affiliations of Neil R. Thomson include United States Geological Survey & State University of New York System.
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Fluid flow in synthetic rough‐walled fractures: Navier‐Stokes, Stokes, and local cubic law simulations
David J. Brush,Neil R. Thomson +1 more
TL;DR: In this article, the results of three-dimensional Navier-Stokes (NS) and Stokes simulations and two-dimensional local cubic law (LCL) simulations of fluid flow through single rough-walled fractures are presented Synthetic rough-wall fractures were created by combining random fields of aperture and the mean wall topography or midsurface, which quantifies undulation about the fracture plane.
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Treatment of Organic Compounds by Activated Persulfate Using Nanoscale Zerovalent Iron
TL;DR: In this article, a method was applied to treat a selection of hazardous organic compounds using nanoscale zerovalent iron (nZVI) particles as activators for persulfate.
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Persistence of persulfate in uncontaminated aquifer materials.
TL;DR: The estimated k(obs) indicate that unactivated persulfate is a persistent oxidant for the range of aquifer materials explored with half-lives ranging from 2 to 600 d.
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Laboratory-scale in situ chemical oxidation of a perchloroethylene pool using permanganate.
L.K MacKinnon,Neil R. Thomson +1 more
TL;DR: The results of this experimental study indicate that ISCO using permanganate is capable of removing substantial mass from a DNAPL pool; however, the performance of ISCO as a pool removal technology will be limited by the formation and precipitation of hydrous MnO2 that occurs during the oxidation process.
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highway stormwater runoff quality: development of surrogate parameter relationships
TL;DR: In this paper, the development of relationships for predicting the impact of highway stormwater runoff is described, and the predictive relationships are regression-based equations reflecting variations in the magnitude of the constituents of interest.