Analysis of Chemometrics Date and Apportionment of Pollution Sources of Urban Rivers from Northeast China a Case from Baitapu River

DOI

10.2991/icseee-16.2016.134How to use a DOI?

Keywords

Urban river; Spatial/temporal distribution; Principal component analysis (PCA); Source identification

Abstract

Baitapu River is an important tributary of Hun River and a typical city river in northeast China. Analysis of cheometrics date of water quality and environmental heterogeneity was used in 17 monitoring sites consisted of 12 water-quality parameters from 2012 to 2013. Spatial and temporal variations in water quality were assessed and pollution sources were identified which aimed to offer foundations to comprehensive treatment and the construction of water environment ecosystem for this kind of rivers in northeast China. Results of these monitoring indicators show that two segments is classified by spatial distribution, temporal distribution and Nemerow index: including upstream minor polluted segment in rural areas and downstream moderate polluted segment in urban areas. The main pollution of Baitapu River are TN, NH3-N, COD, TOC, TP, and chlorophyll a (Chl-a) based on principal component analysis (PCA). The upstream are mainly polluted by agricultural non-point pollution while the downstream are mainly contaminated by industrial wastewater and domestic sewage.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Bingfei Yan
AU  - Peng Jianfeng
PY  - 2016/12
DA  - 2016/12
TI  - Analysis of Chemometrics Date and Apportionment of Pollution Sources of Urban Rivers from Northeast China a Case from Baitapu River
BT  - Proceedings of the 2016 5th International Conference on Sustainable Energy and Environment Engineering (ICSEEE 2016)
PB  - Atlantis Press
SP  - 740
EP  - 747
SN  - 2352-5401
UR  - https://doi.org/10.2991/icseee-16.2016.134
DO  - 10.2991/icseee-16.2016.134
ID  - Yan2016/12
ER  -