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Open AccessArticle

Long-Term River Water Quality Trends and Pollution Source Apportionment in Taiwan

1
Department of Environmental Engineering, College of Engineering, Chung Yuan Christian University, Taoyuan 32023, Taiwan
2
Department of Automation Engineering, Shipbuilding Institute of Polytechnic Surabaya, East Java 60111, Indonesia
3
Taiwan Water Corporation, Taichung 32404, Taiwan
*
Author to whom correspondence should be addressed.
Water 2018, 10(10), 1394; https://doi.org/10.3390/w10101394
Received: 23 August 2018 / Revised: 24 September 2018 / Accepted: 4 October 2018 / Published: 8 October 2018
(This article belongs to the Special Issue Emerging Contaminants in Water: Detection, Treatment, and Regulation )
The application of multivariate statistical techniques including cluster analysis and principal component analysis-multiple linear regression (PCA-MLR) was successfully used to classify the river pollution level in Taiwan and identify possible pollution sources. Water quality and heavy metal monitoring data from the Taiwan Environmental Protection Administration (EPA) was evaluated for 14 major rivers in four regions of Taiwan with the Erren River classified as the most polluted river in the country. Biochemical oxygen demand (6.1 ± 2.38), ammonia (3.48 ± 3.23), and total phosphate (0.65 ± 0.38) mg/L concentration in this river was the highest of the 14 rivers evaluated. In addition, heavy metal levels in the following rivers exceeded the Taiwan EPA standard limit (lead: 0.01, copper: 0.03, and manganese: 0.03) mg/L concentration: lead-in the Dongshan (0.02 ± 0.09), Jhuoshuei (0.03 ± 0.03), and Xinhuwei Rivers (0.02 ± 0.02) mg/L; copper: in the Dahan (0.036 ± 0.097), Laojie (0.06 ± 1.77), and Erren Rivers are (0.05 ± 0.158) mg/L; manganese: in all rivers. A total 72% of the water pollution in the Erren River was estimated to originate from industrial sources, 16% from domestic black water, and 12% from natural sources and runoff from other tributaries. Our research demonstrated that applying PCA-MLR and cluster analysis on long-term monitoring water quality would provide integrated information for river water pollution management and future policy making. View Full-Text
Keywords: Taiwan rivers; water quality; multivariate statistical analysis; river pollution index; pollution source apportionment Taiwan rivers; water quality; multivariate statistical analysis; river pollution index; pollution source apportionment
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Putri, M.S.A.; Lou, C.-H.; Syai’in, M.; Ou, S.-H.; Wang, Y.-C. Long-Term River Water Quality Trends and Pollution Source Apportionment in Taiwan. Water 2018, 10, 1394.

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