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Peer-reviewedCC BY 4.0Scientific Reports

A framework to determine the optimum number and configuration of wastewater treatment plants

Abstract

Clean water is essential for life, ecosystems, and economic development. As water treatment technologies advance and sewage systems grow more complex, wastewater treatment plants (WWTPs) are essential for protecting public health and water resources. However, constructing these plants—particularly in developing countries—remains economically and technically challenging. This research investigates the optimum number and configuration of wastewater treatment plants (WWTP) for certain zones considering their served area, aspect ratio, and population density. The research methodology is developed to evaluate six different plant configurations, ranging from a single WWTP to four WWTPs. A parametric study is conducted to assess the impact of these three key factors on the total cost of the system, including pipes networks, pump stations, and treatment facilities, and excluding land acquisition and operational costs and considering plant cost model depending on number of buildings. The results clarify that land area is the strongest predictor of total system cost, while population density has a weak effect. The aspect ratio of the service area plays a secondary role, with ratios between 1.0 and 1.5 minimizing costs. Among the six configurations, Alternative 1 (Single WWTP) delivers the lowest total cost when WWTP cost is relatively high compared with network cost. On the opposite side, Alternative 6 (four WWTPs) becomes optimal when WWTP cost is relatively low. These findings provide engineers and urban planners with a practical framework for making early-stage decisions about wastewater infrastructure.

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BibTeX
@article{mansour2026framework,
  title = {{A framework to determine the optimum number and configuration of wastewater treatment plants}},
  author = {Dina M. Mansour and Ibrahim Mahdi and Ahmed Ebid},
  journal = {Scientific Reports},
  year = {2026},
  month = oct,
  doi = {10.1038/s41598-026-73184-5},
  url = {https://www.nature.com/articles/s41598-026-73184-5},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - A framework to determine the optimum number and configuration of wastewater treatment plants
AU  - Dina M. Mansour
AU  - Ibrahim Mahdi
AU  - Ahmed Ebid
PY  - 2026
DA  - 2026/10/22
JO  - Scientific Reports
DO  - 10.1038/s41598-026-73184-5
UR  - https://www.nature.com/articles/s41598-026-73184-5
AB  - Clean water is essential for life, ecosystems, and economic development. As water treatment technologies advance and sewage systems grow more complex, wastewater treatment plants (WWTPs) are essential for protecting public health and water resources. However, constructing these plants—particularly in developing countries—remains economically and technically challenging. This research investigates the optimum number and configuration of wastewater treatment plants (WWTP) for certain zones considering their served area, aspect ratio, and population density. The research methodology is developed to evaluate six different plant configurations, ranging from a single WWTP to four WWTPs. A parametric study is conducted to assess the impact of these three key factors on the total cost of the system, including pipes networks, pump stations, and treatment facilities, and excluding land acquisition and operational costs and considering plant cost model depending on number of buildings. The results clarify that land area is the strongest predictor of total system cost, while population density has a weak effect. The aspect ratio of the service area plays a secondary role, with ratios between 1.0 and 1.5 minimizing costs. Among the six configurations, Alternative 1 (Single WWTP) delivers the lowest total cost when WWTP cost is relatively high compared with network cost. On the opposite side, Alternative 6 (four WWTPs) becomes optimal when WWTP cost is relatively low. These findings provide engineers and urban planners with a practical framework for making early-stage decisions about wastewater infrastructure.
SN  - 2045-2322
ER  -