Assessment of Physiochemical Parameters and Bioremediation of Complex Contaminated Yamuna River, India: An Algal-Based Approach

In India, rivers are the primary source of water for millions of people. However, inadequate wastewater management and excessive dumping of pollutants have led to the pollution of these rivers. In the present study, quality of complexly contaminated Yamuna water was analyzed during and after COVID-19 and concluded that water quality improved during COVID-19 but deteriorated significantly after the pandemic, becoming highly contaminated with both organic and inorganic pollutants. For this study, water samples were collected during and post-COVID from 11 different locations in Delhi, Uttar Pradesh, and Haryana, spanning three different seasons (winter, summer, and monsoon) from 2020 to 2022. The results showed significant changes in pH, conductivity, and salinity during the study. Chemical Oxygen Demand (COD) reached its highest recorded value of 388±3.4 mg/L during the monsoon of 2022 at Tronica City. Biochemical Oxygen Demand (BOD) peaked at 27.6±1.18 mg/L at ITO during the monsoon of 2021. Total hardness was highest, measuring 806±21.4 mg/L, during the summer of 2022 at Katha. Additionally, ammonia content was found to be at its highest, measuring 21.23±0.51 PPM, during the summer of 2021 at ISBT Old Bridge. The study also explored the use of various microalgae, including Scenedesmus sp., Klebsormidium sp., Nephrocytium sp., Oocystis sp., Monoraphidium sp., Chlorococcum sp., and filamentous alga Hydrodictyon reticulatum for phycoremediation. These algae were found to efficiently remove pollutants, with Monoraphidium sp. removing 81.81±0.82% of COD, and Chlorococcum sp. effectively removing 78.38±1.02% of ammonia from the complexly contaminated Yamuna water. This study clearly demonstrates that the concentration of pollutants significantly decreased during COVID-19 but increased afterward. The water quality of the Yamuna River in the study area was found to be hazardous for both humans and animals and statistical methods such as ANOVA (Analysis of Variance) and Principal Component Analysis (PCA) validate the significance of the data, correlations, and variances between different pollutants and the effectiveness of phycoremediating algae. Graphical Abstract