Please use this identifier to cite or link to this item:
Developing a Fourier-transform Infrared (FT-IR) Spectroscopy Classification Tool to Identify Common Beach Plastics on Hawaiʻi Island
|Title:||Developing a Fourier-transform Infrared (FT-IR) Spectroscopy Classification Tool to Identify Common Beach Plastics on Hawaiʻi Island|
|Authors:||Strong, Kathryn L.|
|Contributors:||Hamad, Mazen L. (advisor)|
Tropical Conservation Biology & Environmental Science (department)
show 2 moreMarine Debris
|Date Issued:||Dec 2021|
|Publisher:||University of Hawaii at Hilo|
|Abstract:||Many studies rely on Fourier-transform infrared spectroscopy (FT-IR) to identify the plastic polymer types of micro to macro plastics collected from marine and coastal environments. FT-IR research predominantly uses pre-installed reference library software to identify unknown plastic polymer types. However, plastic recovered from the outdoor environment is often altered by heat and ultraviolet light, which changes its chemical composition and consequently its FT-IR spectrum. Reference library limitations make proper identification of weathered plastic spectra challenging. In the following study, various separation and machine learning techniques were developed and evaluated to create a FT-IR beach plastic classification tool. The multivariate classification algorithm of Principal Component Analysis (PCA) served as the model framework for the tool, and two PCA models were developed and tested. The first PCA model served as a baseline and was built based on the spectra of known unweathered plastic polymers, referred to as standards. After five preprocessing techniques were applied to the spectra, the first PCA model separated the 96 standards into eight distinct groups within the modeled 99% confidence limit. Initially, the second PCA model, composed of the same standards with the addition of unknown beach plastics calibrated into the model, was unable to separate plastic polymer types into eight groups. The second PCA model was then modified to reduce the number of plastic polymer standards and beach plastics to the three most common beach plastic types sampled. Polyethylene (PE), polypropylene (PP) and polystyrene (PS) served as the framework for the new model, which classified 77% of beach plastics sampled, compared to the first PCA model, which classified 42% of all beach plastic samples. As a result of numerous metrics and preprocessing applications, developing a robust identification tool for common beach plastics remains a challenge. The results indicate the new PCA model provided an improvement in plastic polymer classification and holds promise to serve as a tool to identify weathered plastics found not only on Hawai'i Island beaches but worldwide.|
|Rights:||All UHH dissertations and theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission from the copyright owner.|
|Appears in Collections:||
Tropical Conservation Biology and Environmental Science
Please email email@example.com if you need this content in ADA-compliant format.
Items in UH System Repository are protected by copyright, with all rights reserved, unless otherwise indicated.