Performance Assessment of Natural Wastewater Treatment Plants by Multivariate Statistical Models: A Case Study

Mahmoud Gad, Sayeda M. Abdo, Anyi Hu, Mohamed Azab El-Liethy, Mohamed S. Hellal, Hala S. Doma and Gamila H. Ali
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Mahmoud Gad: Environmental Parasitology Laboratory, Water Pollution Research Department, National Research Centre, Giza 12622, Egypt
Sayeda M. Abdo: Hydrobiology Laboratory, Water Pollution Research Department, National Research Centre, Giza 12622, Egypt
Anyi Hu: CAS Key Laboratory of Urban Pollutant Conversion, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
Mohamed Azab El-Liethy: Environmental Microbiology Laboratory, Water Pollution Research Department, National Research Centre, Giza 12622, Egypt
Mohamed S. Hellal: Water Pollution Research Department, National Research Centre, Giza 12622, Egypt
Hala S. Doma: Water Pollution Research Department, National Research Centre, Giza 12622, Egypt
Gamila H. Ali: Hydrobiology Laboratory, Water Pollution Research Department, National Research Centre, Giza 12622, Egypt

Sustainability, 2022, vol. 14, issue 13, 1-17

Abstract: Waste stabilization ponds (WSPs) as natural wastewater treatment plants are commonly utilized for wastewater treatment due to their simple design, low cost, and low-skilled operator requirements. Large-scale studies assessing the performance of WSPs using multivariate statistical models are scarce. Therefore, this study was conducted to assess the performance of 16 full-scale WSPs regarding physicochemical parameters, algae, bacterial indicators, and pathogens (e.g., Cryptosporidium , Entamoeba histolytica ) by using multivariate statistical models. The principal component analysis revealed that the chemical pollutants were removed significantly ( p < 0.001) through the treatment stages of 16 WSPs, indicating that the treatment stages made a substantial change in the environmental parameters. The non-multidimensional scale analysis revealed that the treatment stages restructured the bacterial indicators significantly ( p < 0.001) in the WSPs, implying that the bacterial indicators were removed with the progress of the treatment processes. The algal community exhibited a distinct pattern between the geographical location (i.e., upper WSPs versus lower WSPs) and different treatment stages ( p < 0.001). Four out of the sixteen WSPs did not comply with the Egyptian ministerial decree 48/1982 for discharge in agriculture drainage; three of these stations are in lower Egypt (M.K., Al-Adlia, and Ezbet El-Borg), and one is in upper Egypt (Armant). The continuous monitoring of WSPs for compliance with regulatory guidelines with the aid of multivariate statistical models should be routinely performed.

Keywords: performance assessment; natural wastewater treatment plants; physicochemical parameters; microbiological parameters; multivariate statistical models (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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