共 47 条
Fluorescence excitation emission matrices for rapid detection of polycyclic aromatic hydrocarbons and pesticides in surface waters
被引:0
作者:
Yang, Ye Z.
[1
]
Peleato, Nicolas M.
[2
]
Legge, Raymond L.
[3
]
Andrews, Robert C.
[1
]
机构:
[1] Univ Toronto, Dept Civil & Mineral Engn, 35 St George St, Toronto, ON M5S 1A4, Canada
[2] Univ British Columbia Okanagan, Sch Engn, 1137 Alumni Ave, Kelowna, BC V1V 1V7, Canada
[3] Univ Waterloo, Dept Chem Engn, 200 Univ Ave W, Waterloo, ON N2L 3G1, Canada
基金:
加拿大自然科学与工程研究理事会;
关键词:
DISSOLVED ORGANIC-MATTER;
PARALLEL FACTOR;
NEURAL-NETWORKS;
CALIBRATION;
SPECTRA;
SPECTROSCOPY;
WASTE;
RIVER;
QUANTIFICATION;
PARAFAC;
D O I:
10.1039/c8ew00821c
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Application of real-time fluorescence excitation emission matrices (EEM) as a tool for water quality assessment was investigated. A bench-scale fluorescence system with on-line monitoring capabilities was used to quantify several polycyclic aromatic hydrocarbons (PAHs) and pesticides in surface waters of Ontario, Canada. Parallel factors analysis (PARAFAC), an unsupervised multi-way analysis approach, was compared to a supervised peak-picking approach. Both approaches produced sensitive regression models capable of predicting contaminant concentration with mean absolute errors (MAE) that ranged from 0.032 to 0.293 mu g L-1 for lake water, and 0.052 to 0.921 mu g L-1 for river water. In addition, results showed accurate detection of contaminant concentrations exceeding 0.25 mu g L-1. However, concentration and variability of natural organic matter (NOM) in natural waters presented unique challenges to peak-picking, PARAFAC, and regression analysis, which were mitigated by expert supervision as well as site-specific and timely calibration.
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页码:315 / 324
页数:10
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