High-throughput screening of oil fingerprint using FT-IR coupled with chemometrics SCIE SCOPUS

Cited 1 time in WEB OF SCIENCE Cited 1 time in Scopus
Title
High-throughput screening of oil fingerprint using FT-IR coupled with chemometrics
Author(s)
Loh, Andrew; Soon, Zhi Yang; Ha, Sung Yong; Yim, Un Hyuk
KIOST Author(s)
Loh, Andrew(Loh, Andrew)Soon, Zhi Yang(Soon, Zhi Yang)Ha, Sung Yong(하성용)Yim, Un Hyuk(임운혁)
Publication Year
2021-03-15
Abstract
An important element of the oil spill emergency response is the ability to rapidly identify the properties of oil spilled. Chemometrics provides large numbers of multivariate analysis tools that allow for more extensive use of data. Fourier transformed infrared spectroscopy coupled with classification and predictionmodels such as partial least square (PLS) and PLS-DA (discriminant analysis) allows the rapid identification of oil type and characteristics. By searching for the maximum covariance with the variables of interest, PLS allows the visualization of relations between samples and variables. The framework of this study is based on two main steps: The first is classification of oil and the second is prediction of physicochemical properties. Separated into fourmain categories: crude, light fuel, heavy fuel, and lubricant, spectrums of 92 oils were calibrated to predict the oil type and physicochemical properties of 26 oils. The predictability and robustness of the model was further validated using weathered oil. The classification and prediction models have accuracy of >95%. Most of the PLS models have root mean square error of calibration and prediction ranging from 0.10-3.07 and 0.3-2.8, respectively. External cross validations using weathered oils showed high prediction accuracy (relative standard deviations <5%). By increasing the number of oil type and samples, this approach is a promising method and can be included as part of the oil spill fingerprinting protocols. (C) 2020 Elsevier B.V. All rights reserved.
ISSN
0048-9697
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/38770
DOI
10.1016/j.scitotenv.2020.143354
Bibliographic Citation
SCIENCE OF THE TOTAL ENVIRONMENT, v.760, 2021
Publisher
ELSEVIER
Subject
HEBEI-SPIRIT
Keywords
Fourier transformed infrared spectroscopy; PLS; PLS-DA; Oil type; Physicochemical property
Type
Article
Language
English
Document Type
Article
Publisher
ELSEVIER
Related Researcher
Research Interests

Oil Spill Environmental Forensics,Persistent Organic Pollutants,Marine Aerosol,유류오염 환경법과학,지속성유기오염물질,해양 에어로졸

Files in This Item:
There are no files associated with this item.

qrcode

Items in ScienceWatch@KIOST are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse