Chemometrics data of water quality and environmental heterogeneity analysis in Pu River, China

• Published in: Environmental earth sciences Vol. 73; no. 9; pp. 5119 - 5129
• Main Authors: Gao, Hongjie, Lv, Chunjian, Song, Yonghui, Zhang, Yu, Zheng, Lijie, Wen, Yujie, Peng, Jianfeng, Yu, Huibin
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer-Verlag 01.05.2015; Springer Berlin Heidelberg; Springer Nature B.V
• Subjects: Ammonia; ammonium nitrogen; biochemical oxygen demand; Biogeosciences; chemical oxygen demand; chemometrics; chlorophyll; cluster analysis; Downstream; Earth and Environmental Science; Earth Sciences; Environmental Science and Engineering; Geochemistry; Geology; Heterogeneity; Household wastes; Hydrology/Water Resources; Industrial pollution; Industrial wastewater; monitoring; Multivariate analysis; Nonpoint source pollution; Plutonium; Pollution abatement; Pollution control; Pollution prevention; Pollution sources; principal component analysis; Principal components analysis; River basins; River flow; Rivers; seasonal variation; Seasonal variations; Segments; Sewage; Spatial analysis; Statistical methods; Terrestrial Pollution; Thematic Issue; Upstream; wastewater; Wastewater treatment; Water pollution; Water quality; Water quality measurements; Water treatment; watersheds; China; China, People's Rep., Jilin Prov., Liao R; China, People's Rep; Cluster analysis; Water quality evaluation; Pu River; Principal component analysis
• ISSN: 1866-6280; 1866-6299
• DOI: 10.1007/s12665-015-4233-x

Pu River is a typical tributary of Liao River basin; in order to investigate water quality variations at different times and spaces in Pu River, the multivariate statistical method was used to analyze 12 water quality indicators measured at 18 different sites in the period from 2012 to 2013. The research assessed water pollution state and factors, identified pollution sources, and proposed some protective measures and schemes to improve the water quality. Based on the water quality indicators monitoring results, spatial hierarchical cluster analysis (HCA) on 18 sampling sites classified, Pu River was classified into four segments, including source clean segment, upstream heavily polluted segment, midstream light polluted segment, and downstream micro-polluted segment. Temporal HCA results on 8 months also performed a significant seasonal variations on heavily pollution in normal river flow period and early flood period. By principal component analysis (PCA), it is founded that the main pollution of Pu River were COD, TOC, BOD₅, NH₃-N, TP, and chlorophyll a (Chl-a). Among them, COD, TOC, and BOD₅mainly came from industrial pollution sources, NH₃-N and TP from domestic pollution sources, and Chl-a from the natural pollution. Combining with the field investigation result, it was found that the upstream and midstream were mainly polluted by the industrial wastewater and domestic sewage, while the downstream were mainly contaminated by agricultural non-point pollution. Therefore, reinforcing the prevention and control of industrial and domestic pollution of upstream region are expected to improve the water quality of Pu River.