Model-based strategy using GPS-X to simulate improvement scenarios for material flow cost accounting—A case study of the municipal wastewater treatment plants Ali Behnami a,b , Khaled Zoroufchi Benis c , Behzad Mohammadi Khangahi d , Nasim Zolfaghari-Firouzsalari e , Mojtaba Pourakbar b,f , Farhad Ghayourdoost e , Ali Abdolahnejad b , Mohammad Shakerkhatibi e,f ,* a Department of Environmental Health Engineering, Iran University of Medical Sciences, Tehran, Iran b Department of Environmental Health Engineering, Maragheh University of Medical Sciences, Maragheh, Iran c Department of Process Engineering and Applied Science, Dalhousie University, Halifax, NS, Canada d Student Research Committee, Tabriz University of Medical Sciences, Tabriz, Iran e Department of Environmental Health Engineering, Faculty of Health, Tabriz University of Medical Sciences, Tabriz, Iran f Health and Environment Research Center, Tabriz University of Medical Sciences, Tabriz, Iran A R T I C L E INFO Editor: Li Gao Keywords: MFCA GPS-X Modeling WWTP Simulation ABSTRACT Material Flow Cost Accounting (MFCA) is a technique that enables the allocation of costs to energy and material flows within a system. This is achieved by estimating the costs associated with material and energy losses throughout various processes. This method enables the formulation of performance improvement scenarios with the objective of minimizing waste, thereby reducing both system costs and environmental impacts in a simul- taneous manner. However, the lack of tangibility of the outcomes of MFCA-derived scenarios may hinder acceptance, as these outcomes may not resonate with stakeholders. In such instances, the utilization of modeling techniques to simulate MFCA outcomes can significantly enhance the clarity of the decision-making process. This research combines MFCA with GPS-X process simulation to assess and enhance the operational efficacy of a municipal wastewater treatment plant (WWTP) operated in two configurations: the conventional activated sludge (CAS) and sequencing batch reactor (SBR) systems. This integrated approach enables accurate monitoring of material and energy flows, as well as financial and environmental performance. The simulation findings reveal that adopting optimized operational strategies achieved a 15 % reduction in electricity usage, a 12 % decline in total operating expenses, and a 17 % decrease in overall sludge generation, resulting in significant environmental advantages. The MFCA framework offered valuable insights by pinpointing costly loss streams and measuring resource inefficiencies. This unified methodology aids in data-informed decision-making and provides a useful tool for plant operators and policymakers aiming to improve sustainability and cost-efficiency in WWTP management. 1. Introduction The increasing population and rapid industrialization and urbani- zation have led to a marked rise in wastewater generation. Wastewater treatment plants (WWTPs) are designed to remove contaminants and mitigate the environmental pollution associated with water usage and wastewater production [1]. However, the operational processes within WWTPs often costly and often lack profitability [2]. In an effort to enhance the performance of WWTPs, various approaches and modeling tools have been employed. These include the development of new pro- cesses or the modification of existing ones. Among the approaches and modeling tools employed are Model Predictive Control [3] and WEST software [4]. These tools and approaches have been used to enhance the efficiency of WWTP processes. While these methods have demonstrated potential in improving WWTP performance, they typically concentrate * Corresponding author at: Department of Environmental Health Engineering, Faculty of Health, Tabriz University of Medical Sciences, Tabriz, Iran. E-mail addresses: ali.behnami64@gmail.com (A. Behnami), khaled.Benis@dal.ca (K.Z. Benis), mohammadi.khangahi@gmail.com (B.M. Khangahi), nasimzol0804@gmail.com (N. Zolfaghari-Firouzsalari), ppourakbar@yahoo.com (M. Pourakbar), ghayurdoostfarhad@yahoo.com (F. Ghayourdoost), abdolahnejad.a@gmail.com (A. Abdolahnejad), shakerkhatibim@tbzmed.ac.ir, shakerkhatibi@yahoo.com (M. Shakerkhatibi). Contents lists available at ScienceDirect Journal of Water Process Engineering journal homepage: www.elsevier.com/locate/jwpe https://doi.org/10.1016/j.jwpe.2025.108550 Received 6 April 2025; Received in revised form 5 August 2025; Accepted 16 August 2025 Journal of Water Process Engineering 77 (2025) 108550 Available online 28 August 2025 2214-7144/© 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.