Evaluation of operational efficiency and performance for a water treatment plant

计算机科学 环境科学
作者
Joseph K. Bwapwa,Nonsindiso Mkhize,Mohamed K. Seyam
出处
期刊:South African Journal of Chemical Engineering [Elsevier BV]
卷期号:49: 11-34
标识
DOI:10.1016/j.sajce.2024.04.003
摘要

The current study presents a comprehensive analysis of the operational efficiency and performance evaluation of the Hazelmere Water Treatment Plant over the period from 1999 to 2018. By focusing on the removal efficiencies of few parameters including iron (Fe), turbidity, and E. coli, the study provides valuable insights into the plant's ability to treat water effectively and produce high-quality drinking water. Leveraging data analysis techniques and computational tools, the research also explores the forecasting of water quality parameters beyond the study period, enhancing predictive capabilities for monitoring and managing water quality in the future. The Hazelmere Water Treatment Plant (WTP) has a daily capacity of 75 Ml it supplies water to the surroundings. Its intricate treatment process, featuring chemical dosing, clarification, filtration, and disinfection, operates harmoniously. The plant consistently exceeded global standards. Effluent turbidity consistently met stringent World Health Organization/South African National (WHO/SANS) discharge standards at ≤ 1 NTU. The turbidity removal efficiencies ranged from 65.88 to 99.61% on average over the period from 1999 to 2018. Iron removal also adhered to WHO/SANS criteria, registering ≤ 2 mg/L. The removal efficiencies have ranged from 82 to 99 % on average for the same period. Most impressively, E. coli removal efficiency maintained a flawless 100% for the same period, indicating a pathogen-free effluent throughout the period, with a steady annual average of 0 MPN/100m, some challenges have occurred including the contamination of the freshwater from the dam, the limited data availability, and issues related to sustainability and compliance. These challenges were overcome by using advanced tools for data analyses such as R package, developing a performance evaluation framework and establishing recommendations for the adoption of innovative technologies, and improvements in operation and maintenance practices. Overall, this study makes significant contributions to the field of wastewater treatment and water quality management, advancing our understanding of sustainable water resource management and environmental protection.
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