System dynamic modelling to assess the influential factors affecting roughing filter and slow sand filter performance in treating culinary wastewater

Nurina Fitriani, Setyo Budi Kurniawan, Muhammad Fauzul Imron, Inengah Ilham Maulana, Eddy Setiadi Soedjono, Radin Maya Saphira Radin Mohamed, Norzila Binti Othman, Ni'matuzahroh, Maritha Nilam Kusuma

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1 Citation (Scopus)

Abstract

This research aimed to determine the factors that influence the performance of a slow sand filter (SSF) equipped with a roughing filter (RF) as a pretreatment unit using system dynamic (SD) modelling. STELLA was used to model the system and predict the behavior pattern, as well as the system's performance in removing turbidity, total suspended solids (TSS), BOD, COD, and phosphate. SD modelling consisted of system identification, system model framework, model structure building, system modelling, verification, and validation. Two sub-models were obtained from the main model, consisting of the RF and SSF sub-models. Results showed that dissolved oxygen (DO) and the growth rate of microorganisms played significant roles in the parameter removal. Predicted result by SD modelling showed a good fit with actual run, suggesting that factors applied in the model building were adequate to exhibit the actual system. RF removed 80.5 %–85 % of turbidity and 70.63 %–85 % of TSS, while SSF removed 48.50 %–82.43 % of turbidity, 0.92 %–46.15 % of TSS, 1.65 %–65.45 % of BOD, 22.69 %–65.22 % of COD, and 7.96 %–27.11 % of phosphate. Effluent after SSF was still having BOD and COD concentrations exceeding the governmental standard, in which increasing DO inlet and microorganism growth rate were simulated afterward. The scenarios used showed a positive impact on the removal of BOD and COD, resulting in an average concentration lower than the permissible limit (5 mg/L and 50 mg/L, respectively).

Original languageEnglish
Article number104274
JournalJournal of Water Process Engineering
Volume56
DOIs
Publication statusPublished - Dec 2023

Keywords

  • Environmental pollution
  • Food wastewater
  • Model simulation
  • System dynamic
  • Wastewater treatment

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