Abstract
This paper presents a methodology based on multivariate data analysis for characterizing potential source contributions of emerging contaminants (ECs) detected in 26 river water samples across multi-scape regions during dry and wet seasons. Based on this methodology, we unveil an approach toward potential source contributions of ECs, a concept we refer to as the “Pharmaco-signature.” Exploratory analysis of data points has been carried out by unsupervised pattern recognition (hierarchical cluster analysis, HCA) and receptor model (principal component analysis-multiple linear regression, PCA-MLR) in an attempt to demonstrate significant source contributions of ECs in different land-use zone. Robust cluster solutions grouped the database according to different EC profiles. PCA-MLR identified that 58.9% of the mean summed ECs were contributed by domestic impact, 9.7% by antibiotics application, and 31.4% by drug abuse. Diclofenac, ibuprofen, codeine, ampicillin, tetracycline, and erythromycin-H2O have significant pollution risk quotients (RQ>1), indicating potentially high risk to aquatic organisms in Taiwan.
Original language | English |
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Journal | PLoS ONE |
Volume | 10 |
Issue number | 4 |
DOIs | |
Publication status | Published - 15 Apr 2015 |
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Kenny Boyd
- Environmental Research Institute - Senior Research Fellow
- Aquaculture Research Network
Person: Academic - Research and Teaching or Research only
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Stuart Gibb
- Environmental Research Institute - Director of ERI
Person: Academic - Research and Teaching or Research only