Journal of Water, Sanitation and Hygiene for Development (Jun 2022)

Performance assessment of sewage treatment plants using compliance index

  • D. Ramkumar,
  • V. Jothiprakash,
  • B. N. Patil

DOI
https://doi.org/10.2166/washdev.2022.055
Journal volume & issue
Vol. 12, no. 6
pp. 485 – 497

Abstract

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The aim of this study is to infer the performance assessment of sewage treatment plants (STPs) using the compliance index (CI). The methodology includes three steps, (1) estimation of performance indicators from the quality test, parameter test, and conformity test, (2) hypothesis testing of non-conformity, and (3) hypothesis testing using the non-parametric test. The CI integrates the results of the above nine tests through a scoring system based on individual performance. The study area, Navi Mumbai Municipal Corporation (NMMC), India, treats its domestic sewage through seven centralized STPs located in different zones. The influent and effluent parameters, such as flow rate, biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solids (TSS), pH, dissolved oxygen (DO), and temperature, were studied in this work. The removal efficiency (RE) analysis shows the efficiency of BOD, COD, and TSS varies between 96.67 and 97.30%, 84.55 and 89.70%, and 94.04 and 95.81%, respectively, and indicates that all STPs are performing well. The proposed CI infers that all STPs perform well and comply with NMMC standards, except one STP, namely Airoli. Interestingly, RE analysis shows that Airoli STP's BOD is the third-best compared to all other STPs. This study shows that the CI method can infer the performance of STPs better than RE and help the administrators to plan, execute, operate, and maintain STPs to achieve total sanitation in megacities. HIGHLIGHTS Proposed compliance index (CI) computes the performance of sewage treatment plants (STPs).; The CI is constructed using influent and effluent wastewater quality parameters.; The methodology was tested with seven STPs in one of India's cleanest cities.; The advantage of the CI is that it handles non-stationary datasets.; Proposed CI reveals much better compliance of STPs than the conventional removal efficiency analysis.;

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