Assessment of seasonal and spatial fluctuations in wastewater quality using multivariate statistical methods.

Abstract

This study aims at evaluating the seasonal and spatial fluctuations in the quality of wastewater passing through the stormwater flow (SWF) channel located in Kolkata, India, using multivariate statistical methods. In this study, the primary quality data were collected from eight selected sampling stations on the SWF channel during three seasons (summer, monsoon, and winter of 2019) for 10 parameters (ammonia, biochemical oxygen demand, dissolved oxygen, nitrate, orthophosphate as phosphorous, pH, temperature, total coliform, total suspended solids, and discharge). Cluster analysis was used to group the eight sampling stations into three categories of similar water quality characteristics. This resulted in three water quality rating zones: bad, moderately bad, and good. Principal component analysis (PCA) was carried out to identify the significant parameters responsible for the wastewater quality fluctuations during all three seasons. The results of the PCA revealed that temperature and pH are the most important constituents contributing to wastewater quality fluctuations in the SWF channel for all seasons in a year. The PCA studies additionally led to the conclusion that a parameter that may be massive in contribution to wastewater quality fluctuations within the channel once of a year may not be substantial for every different season. The study revealed the current state of the wastewater quality in the SWF channel by using just 1year of primary data. In addition, it is expected to provide help for future studies on the channel.