<![CDATA[Industrial Wastewater Treatment Plants (WWTPs) are essential infrastructures for managing industrial waste, maintaining environmental quality, and protecting public health. However, high concentrations of organic and chemical contaminants increase energy demand, particularly for pumping and treatment processes, contributing to indirect greenhouse gas emissions. This study aims to develop a simulation model to assess operational and financial risks in industrial WWTPs. The framework focuses on the linear relationship between technical and financial variables under uncertain conditions, analyzed using Monte Carlo simulations. Variability in wastewater discharge and quality from multiple industrial tenants introduces technical risks that affect process efficiency, operational costs, and compliance with environmental standards. Key input variables, such as discharge volume, BOD/COD concentrations, and energy and chemical prices, are modeled as probability distributions. The simulation generates probabilistic outputs of operational costs and potential penalties. This approach enables systematic analysis of uncertainty and supports more effective, data-driven decision-making in WWTP management.]]>
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