Persistent Link:
http://hdl.handle.net/10150/196809
Title:
Exploring Holistic Approaches to the Characterization of Particles in the Environment
Author:
Anhalt, Ashley; Peterson, Tawnya; Tratnyek, Paul; Needoba, Joseph; Mather, Amanda
Issue Date:
2011-11-04
Rights:
Copyright © is held by the author. 
Collection Information:
This item is part of the GPSC Student Showcase collection. For more information about the Student Showcase, please email the GPSC (Graduate and Professional Student Council) at gpsc@email.arizona.edu.
Abstract:
Most of the main determinants of water quality either consist of, or are controlled by, particles. Previous water quality research has focused on particular particles in isolation or in binary combinations. In this project, we are taking a holistic approach to the characterization of the particle load in water, focusing on the collective properties of the particles rather than individual components. Because the characterization of particles is often time-consuming, applying an informatics-based approach could speed up the evaluation of water quality and the assessment of treatment effectiveness. Further, the breadth of potential changes that could be detected using this multiplex approach may far surpass the abilities of current approaches to monitor threats to water quality. Among the instruments capable of rapidly detecting and manipulating cells is imaging flow cytometry, which distinguishes cell shape and unique fluorescence properties associated with cell types. Sets of images and corresponding data from a 1.5-year time series of samples from the Columbia River were studied and the different particle properties analyzed. Principal Component Analysis (Empirical Orthogonal Function analysis) was applied in order to reduce the number of variables and identify patterns in particle characteristics when compared to environmental data collected from the observation station. The first three principal components were extracted and the dominant characteristics identified: the most prominent variables are particle size, particle color, and fluorescent qualities (transparency and phytoplankton pigments). Further work will relate these top principal components to specific environmental factors that determine water quality.
Keywords:
Ecological risk assessment; Environmental health and water; Water quality
Sponsors:
Center for Coastal Margin Observation & Prediction (CMOP), Oregon Health & Science University, Beaverton, OR

Full metadata record

DC FieldValue Language
dc.contributor.authorAnhalt, Ashleyen_US
dc.contributor.authorPeterson, Tawnyaen_US
dc.contributor.authorTratnyek, Paulen_US
dc.contributor.authorNeedoba, Josephen_US
dc.contributor.authorMather, Amandaen_US
dc.date.accessioned2011-12-11T02:39:58Z-
dc.date.available2011-12-11T02:39:58Z-
dc.date.issued2011-11-04-
dc.identifier.urihttp://hdl.handle.net/10150/196809-
dc.description.abstractMost of the main determinants of water quality either consist of, or are controlled by, particles. Previous water quality research has focused on particular particles in isolation or in binary combinations. In this project, we are taking a holistic approach to the characterization of the particle load in water, focusing on the collective properties of the particles rather than individual components. Because the characterization of particles is often time-consuming, applying an informatics-based approach could speed up the evaluation of water quality and the assessment of treatment effectiveness. Further, the breadth of potential changes that could be detected using this multiplex approach may far surpass the abilities of current approaches to monitor threats to water quality. Among the instruments capable of rapidly detecting and manipulating cells is imaging flow cytometry, which distinguishes cell shape and unique fluorescence properties associated with cell types. Sets of images and corresponding data from a 1.5-year time series of samples from the Columbia River were studied and the different particle properties analyzed. Principal Component Analysis (Empirical Orthogonal Function analysis) was applied in order to reduce the number of variables and identify patterns in particle characteristics when compared to environmental data collected from the observation station. The first three principal components were extracted and the dominant characteristics identified: the most prominent variables are particle size, particle color, and fluorescent qualities (transparency and phytoplankton pigments). Further work will relate these top principal components to specific environmental factors that determine water quality.en_US
dc.description.sponsorshipCenter for Coastal Margin Observation & Prediction (CMOP), Oregon Health & Science University, Beaverton, ORen_US
dc.language.isoen_USen_US
dc.rightsCopyright © is held by the author. -
dc.subjectEcological risk assessmenten_US
dc.subjectEnvironmental health and wateren_US
dc.subjectWater qualityen_US
dc.titleExploring Holistic Approaches to the Characterization of Particles in the Environmenten_US
dc.description.collectioninformationThis item is part of the GPSC Student Showcase collection. For more information about the Student Showcase, please email the GPSC (Graduate and Professional Student Council) at gpsc@email.arizona.edu.en_US
All Items in UA Campus Repository are protected by copyright, with all rights reserved, unless otherwise indicated.