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dc.contributor.authorMartins Júnior, Antônio Carlos de Oliveirapt_BR
dc.contributor.authorSilva, Maria Cristina de Almeidapt_BR
dc.date.accessioned2022-02-18T04:33:55Zpt_BR
dc.date.issued2022pt_BR
dc.identifier.issn1751-231Xpt_BR
dc.identifier.urihttp://hdl.handle.net/10183/235278pt_BR
dc.description.abstractThis study aimed at providing a set of optimal kinetic and stoichiometric parameters of ASM1 representative of wastewater from a subtropical climate region in Brazil. ASM1 was applied on the STOAT program, and the model parameters were evaluated and optimized with sensitivity analysis and Response Surface Methodology (RSM) to reach minimum prediction errors of effluent TSS, COD, and NH3. Six sensitive parameters were identified: YH, YA, μA, KNH, bA, and kOA. Predictions of RSM regression models were strongly correlated to the STOAT predictions. YH mainly affected TSS and COD, and the other parameters affected NH3. ASM1 calibration with estimated optimal values of sensitive parameters resulted in approximately null prediction errors for modeling state variables. NH3 presented similar results in the ASM1 validation; meanwhile, TSS and COD presented high errors related to the increase in YH due to the RSM optimization. The optimal parameters, mainly YA, μA, KNH, bA, and kOA, constitute references for other studies on ASM1 modeling using wastewater data from a subtropical climate region. YH optimal value should be evaluated as well as the effect of sludge wastage methods and the simulation periods.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.relation.ispartofWater Practice and Technology. London. Vol. 17, n. 1 (Jan. 2022), p. 268-284pt_BR
dc.rightsOpen Accessen
dc.subjectTratamento de esgotopt_BR
dc.subjectMathematical modelingen
dc.subjectResponse surface methodologyen
dc.subjectClima subtropicalpt_BR
dc.subjectLodo ativadopt_BR
dc.subjectSensitivity analysisen
dc.subjectModelos matemáticospt_BR
dc.subjectSystematic model calibrationen
dc.subjectCalibraçãopt_BR
dc.titleEvaluation and optimization of ASM1 parameters using large-scale WWTP monitoring data from a subtropical climate region in Brazilpt_BR
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb001136667pt_BR
dc.type.originEstrangeiropt_BR


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