Variation of wastewater contaminants in China and source identification using hierarchical clustering based on weighted factor scores

Abstract

Abstract Human activities have huge impact on the aquatic environment. Knowledge on sources of the contaminants provides guidelines to determine the ideal location and maintenance of monitoring stations, thus advancing environmental monitoring and pollution control. Factor analysis (FA) may be the most popular method for source identification, but the results should be affirmed. Following this logic, in this research, firstly the potential sources were determined, and secondly the contaminant concentrations in the source regions and the non-source regions were compared. To identify the potential sources, 75 meteorological, economic and social indicators were used to group the study regions. FA was used to reduce dimensionality and factor scores were calculated. The grouping was based on the weighted factor scores while the weight was variance explained by each factor respectively. Each group was supposed to correspond to a factor; that is, a potential source. The results indicated that the concentrations of chemical oxygen demand (COD), ammonia nitrogen, phosphorus and arsenic in wastewater were significantly different between groups. Animal husbandry, mining and/or energy industry were the main sources of COD, ammonia nitrogen and phosphorus; animal husbandry, mining, energy industry, and/or heavy and chemical industry were the main sources of phosphorus; humid climate and/or secondary industry were the main sources of arsenic.