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Quantitative image analysis as a robust tool to assess effluent quality from an aerobic granular sludge system treating industrial wastewater

2021-11-03Journal article Open access
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dc.contributor.authorCosta, Joana G.
dc.contributor.authorPaulo, Ana M. S.
dc.contributor.authorAmorim, Catarina L.
dc.contributor.authorAmaral, A. Luís
dc.contributor.authorCastro, Paula M. L.
dc.contributor.authorFerreira, Eugénio C.
dc.contributor.authorMesquita, Daniela P.
dc.date.accessioned2022-02-07T11:38:41Z
dc.date.available2023-11-30T01:31:14Z
dc.date.issued2021-11-03
dc.description.abstractQuantitative image analysis (QIA) is a simple and automated method for process monitoring, complementary to chemical analysis, that when coupled to mathematical modelling allows associating changes in the biomass to several operational parameters. The majority of the research regarding the use of QIA has been carried out using synthetic wastewater and applied to activated sludge systems, while there is still a lack of knowledge regarding the application of QIA in the monitoring of aerobic granular sludge (AGS) systems. In this work, chemical oxygen demand (COD), ammonium (N–NH4+), nitrite (N–NO2-), nitrate (N–NO3-), salinity (Cl−), and total suspended solids (TSS) levels present in the effluent of an AGS system treating fish canning wastewater were successfully associated to QIA data, from both suspended and granular biomass fractions by partial least squares models. The correlation between physical-chemical parameters and QIA data allowed obtaining good assessment results for COD (R2 of 0.94), N–NH4+ (R2 of 0.98), N–NO2- (R2 of 0.96), N–NO3- (R2 of 0.95), Cl− (R2 of 0.98), and TSS (R2 of 0.94). While the COD and N–NO2- assessment models were mostly correlated to the granular fraction QIA data, the suspended fraction was highly relevant for N–NH4+ assessment. The N–NO3-, Cl− and TSS assessment benefited from the use of both biomass fractions (suspended and granular) QIA data, indicating the importance of the balance between the suspended and granular fractions in AGS systems and its analysis. This study provides a complementary approach to assess effluent quality parameters which can improve wastewater treatment plants monitoring and control, with a more cost-effective and environmentally friendly procedure, while avoiding daily physical-chemical analysis.pt_PT
dc.description.versioninfo:eu-repo/semantics/acceptedVersionpt_PT
dc.identifier.doi10.1016/j.chemosphere.2021.132773pt_PT
dc.identifier.eid85118859559
dc.identifier.issn0045-6535
dc.identifier.pmid34742770
dc.identifier.urihttp://hdl.handle.net/10400.14/36612
dc.identifier.wos000757975400003
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectEffluent quality parameterspt_PT
dc.subjectFood industry wastewaterpt_PT
dc.subjectPartial least squarespt_PT
dc.subjectSalinitypt_PT
dc.subjectSuspended and granular biomass fractionspt_PT
dc.titleQuantitative image analysis as a robust tool to assess effluent quality from an aerobic granular sludge system treating industrial wastewaterpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleChemospherept_PT
oaire.citation.volume291pt_PT
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

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