Why are organic micropollutants not fully biotransformed? A mechanistic modelling approach to anaerobic systems

dc.contributor.affiliationUniversidade de Santiago de Compostela. Departamento de Enxeñaría Químicagl
dc.contributor.areaÁrea de Enxeñaría e Arquitectura
dc.contributor.authorGonzález Gil, Lorena
dc.contributor.authorMauricio Iglesias, Miguel
dc.contributor.authorCarballa Arcos, Marta
dc.contributor.authorLema Rodicio, Juan Manuel
dc.date.accessioned2018-09-24T10:24:39Z
dc.date.available2020-05-21T01:00:08Z
dc.date.issued2018-05-21
dc.descriptionThis is a post-print version of the articlegl
dc.description.abstractBiotransformation of most organic micropollutants (OMPs) during wastewater treatment is not complete and a drastic decrease of the biotransformation rate with time is reported for many OMPs in different biological processes. To minimize and accurately predict the emission of OMPs into the environment, the mechanisms and limitations behind their biotransformations should be clarified. Aiming to achieve this objective, the present study follows a mechanistic modelling approach, based on the formulation of four models according to different biotransformation hypotheses: Michaelis-Menten kinetics, chemical equilibrium between the parent compound and the transformation product (TP), enzymatic inhibition by the TP, and a limited compound bioavailability due to its sequestration in the solid phase. These models were calibrated and validated with kinetic experiments performed in two different anaerobic systems: continuous reactors enriched with methanogenic biomass and batch assays with anaerobic sludge. Model selection was conducted according to model suitability criteria (goodness of fitting the experimental data, confidence of the estimated parameters, and model parsimony) but also considering mechanistic evidences. The findings suggest that reversibility of the biological reactions and/or sequestration of compounds are likely the causes preventing the complete biotransformation of OMPs, and biotransformation is probably limited by thermodynamics rather than by kinetics. Taking into account its simplicity and broader applicability spectrum, the reversible biotransformation is the proposed model to explain the incomplete biotransformation of OMPsgl
dc.description.peerreviewedSIgl
dc.description.sponsorshipThis research was funded by the Spanish Government (AEI) through the COMETT project (CTQ2016-80847-R) and by an FPU Grant (FPU13/01255). The authors belong to CRETUS Strategic Partnership (AGRUP2015/02) and to Galician Competitive Research Group (GRC ED431C 2017/29). All these programs are co-funded by FEDER (EU)gl
dc.identifier.citationGonzalez-Gil, L., Mauricio-Iglesias, M., Carballa, M., & Lema, J. M. (2018). Why are organic micropollutants not fully biotransformed? A mechanistic modelling approach to anaerobic systems. Water research, 142, 115-128.gl
dc.identifier.doi10.1016/j.watres.2018.05.032
dc.identifier.issn0043-1354
dc.identifier.urihttp://hdl.handle.net/10347/17380
dc.language.isoenggl
dc.publisherElseviergl
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/CTQ2016-80847-R/ES
dc.relation.publisherversionhttps://doi.org/10.1016/j.watres.2018.05.032gl
dc.rights© Elsevier 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 licensegl
dc.rights.accessRightsopen accessgl
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectBioavailabilitygl
dc.subjectBiotransformation mechanismgl
dc.subjectIncomplete removalgl
dc.subjectMathematical modellinggl
dc.subjectParameter estimationgl
dc.subjectPharmaceuticalsgl
dc.titleWhy are organic micropollutants not fully biotransformed? A mechanistic modelling approach to anaerobic systemsgl
dc.typejournal articlegl
dc.type.hasVersionAMgl
dspace.entity.typePublication
relation.isAuthorOfPublicationb098e7de-f49e-4335-9f8d-d70a445f4a69
relation.isAuthorOfPublicationf574e8ce-1a88-4045-bc74-d48db358fc70
relation.isAuthorOfPublication9fbac3ef-9f34-48d3-ad2a-afc25f286f08
relation.isAuthorOfPublication.latestForDiscoveryb098e7de-f49e-4335-9f8d-d70a445f4a69

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