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Multivariate statistical assessment of a polluted river under nitrification inhibition in the tropics

Environmental science and pollution research international, 2017-05, Vol.24 (15), p.13845-13862 [Peer Reviewed Journal]

The Author(s) 2017 ;Environmental Science and Pollution Research is a copyright of Springer, (2017). All Rights Reserved. ;ISSN: 0944-1344 ;EISSN: 1614-7499 ;DOI: 10.1007/s11356-017-8989-2 ;PMID: 28409429

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Title:
Multivariate statistical assessment of a polluted river under nitrification inhibition in the tropics
Author: Le, Thi Thu Huyen ; Zeunert, Stephanie ; Lorenz, Malte ; Meon, Günter
Subjects: Aquatic Pollution ; Atmospheric Protection/Air Quality Control/Air Pollution ; Cluster Analysis ; Discriminant analysis ; Earth and Environmental Science ; Ecotoxicology ; Environment ; Environmental Chemistry ; Environmental Health ; Environmental Monitoring ; Inhibition ; Iron ; Nitrates ; Nitrification ; Nutrients ; Oxidation ; pH effects ; Pollution ; Pollution sources ; Principal Component Analysis ; Principal components analysis ; Quality assessment ; Research Article ; River basins ; Rivers ; Rivers - chemistry ; Statistical analysis ; Tropical environments ; Waste Water Technology ; Wastewater ; Wastewater discharges ; Water Management ; Water pollution ; Water Pollution Control ; Water Quality ; Water quality assessments
Is Part Of: Environmental science and pollution research international, 2017-05, Vol.24 (15), p.13845-13862
Description: A large complex water quality data set of a polluted river, the Tay Ninh River, was evaluated to identify its water quality problems, to assess spatial variation, to determine the main pollution sources, and to detect relationships between parameters. This river is highly polluted with organic substances, nutrients, and total iron. An important problem of the river is the inhibition of the nitrification. For the evaluation, different statistical techniques including cluster analysis (CA), discriminant analysis (DA), and principal component analysis (PCA) were applied. CA clustered 10 water quality stations into three groups corresponding to extreme, high, and moderate pollution. DA used only seven parameters to differentiate the defined clusters. The PCA resulted in four principal components. The first PC is related to conductivity, NH 4 -N, PO 4 -P, and TP and determines nutrient pollution. The second PC represents the organic pollution. The iron pollution is illustrated in the third PC having strong positive loadings for TSS and total Fe. The fourth PC explains the dependence of DO on the nitrate production. The nitrification inhibition was further investigated by PCA. The results showed a clear negative correlation between DO and NH 4 -N and a positive correlation between DO and NO 3 -N. The influence of pH on the NH 4 -N oxidation could not be detected by PCA because of the very low nitrification rate due to the constantly low pH of the river and because of the effect of wastewater discharge with very high NH 4 -N concentrations. The results are deepening the understanding of the governing water quality processes and hence to manage the river basins sustainably.
Publisher: Berlin/Heidelberg: Springer Berlin Heidelberg
Language: English
Identifier: ISSN: 0944-1344
EISSN: 1614-7499
DOI: 10.1007/s11356-017-8989-2
PMID: 28409429
Source: MEDLINE
Springer Nature OA/Free Journals
ProQuest Central

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Multivariate statistical assessment of a polluted river under nitrification inhibition in the tropics

The Author(s) 2017 ;Environmental Science and Pollution Research is a copyright of Springer, (2017). All Rights Reserved. ;ISSN: 0944-1344 ;EISSN: 1614-7499 ;DOI: 10.1007/s11356-017-8989-2 ;PMID: 28409429

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