Background: Wastewater treatment from fish processing industries presents major environmental challenges because of high effluent volume, salinity, and complex organic compounds like fats, proteins, nitrogen, and phosphorus. Efficient treatment plant design requires advanced modeling and simulation to enhance pollutant removal and minimize operational costs. Methods: This study was conducted at the Bandar Abbas tuna canning factory. Wastewater quality data, treatment plant specifications, and previous studies were collected. The treatment process was simulated and optimized using GPS-X software based on the ASM2d biological model. The base model was calibrated and validated, and various operational scenarios, including adjustments to sludge return rate, waste activated sludge discharge, hydraulic retention time, and mixed liquor suspended solids concentration, were evaluated. Results: Simulation under optimized conditions markedly improved pollutant removal. COD, BOD5 , and TSS decreased by 98.46, 99.25, and 98.52%, respectively, approaching national standards. Total nitrogen, ammonia, and phosphorus were reduced by 93, 97, and 80%. Sensitivity analysis revealed that sludge return rate, waste sludge discharge, hydraulic retention time, and activated sludge concentration most strongly influenced effluent quality. Conclusion: Dynamic simulation with GPS-X accurately predicted treatment plant behavior, optimized performance, and reduced energy and sludge production. Overall, the study demonstrates that mathematical modeling and scenario optimization are powerful tools for improving fish processing wastewater treatment efficiency and achieving environmental compliance.
Tavasoli et al. (Sun,) studied this question.
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