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Impact of in-Sewer Degradation of Pharmaceutical and Personal Care Products (PPCPs) Population Markers on a Population Model.
O'Brien, Jake William; Banks, Andrew Phillip William; Novic, Andrew Joseph; Mueller, Jochen F; Jiang, Guangming; Ort, Christoph; Eaglesham, Geoff; Yuan, Zhiguo; Thai, Phong K.
Afiliación
  • O'Brien JW; Queensland Alliance for Environmental Health Science (QAEHS), The University of Queensland , 39 Kessels Road, Coopers Plains, Queensland 4108, Australia.
  • Banks AP; Queensland Alliance for Environmental Health Science (QAEHS), The University of Queensland , 39 Kessels Road, Coopers Plains, Queensland 4108, Australia.
  • Novic AJ; Queensland Alliance for Environmental Health Science (QAEHS), The University of Queensland , 39 Kessels Road, Coopers Plains, Queensland 4108, Australia.
  • Mueller JF; Queensland Alliance for Environmental Health Science (QAEHS), The University of Queensland , 39 Kessels Road, Coopers Plains, Queensland 4108, Australia.
  • Jiang G; Advanced Water Management Centre (AWMC), The University of Queensland , St. Lucia, Queensland 4072, Australia.
  • Ort C; Eawag, Swiss Federal Institute of Aquatic Science and Technology , CH 8600 Dübendorf, Switzerland.
  • Eaglesham G; Queensland Alliance for Environmental Health Science (QAEHS), The University of Queensland , 39 Kessels Road, Coopers Plains, Queensland 4108, Australia.
  • Yuan Z; Advanced Water Management Centre (AWMC), The University of Queensland , St. Lucia, Queensland 4072, Australia.
  • Thai PK; Queensland Alliance for Environmental Health Science (QAEHS), The University of Queensland , 39 Kessels Road, Coopers Plains, Queensland 4108, Australia.
Environ Sci Technol ; 51(7): 3816-3823, 2017 04 04.
Article en En | MEDLINE | ID: mdl-28244310
ABSTRACT
A key uncertainty of wastewater-based epidemiology is the size of the population which contributed to a given wastewater sample. We previously developed and validated a Bayesian inference model to estimate population size based on 14 population markers which (1) are easily measured and (2) have mass loads which correlate with population size. However, the potential uncertainty of the model prediction due to in-sewer degradation of these markers was not evaluated. In this study, we addressed this gap by testing their stability under sewer conditions and assessed whether degradation impacts the model estimates. Five markers, which formed the core of our model, were stable in the sewers while the others were not. Our evaluation showed that the presence of unstable population markers in the model did not decrease the precision of the population estimates providing that stable markers such as acesulfame remained in the model. However, to achieve the minimum uncertainty in population estimates, we propose that the core markers to be included in population models for other sites should meet two additional criteria (3) negligible degradation in wastewater to ensure the stability of chemicals during collection; and (4) < 10% in-sewer degradation could occur during the mean residence time of the sewer network.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Aguas del Alcantarillado / Teorema de Bayes Tipo de estudio: Prognostic_studies Idioma: En Revista: Environ Sci Technol Año: 2017 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Aguas del Alcantarillado / Teorema de Bayes Tipo de estudio: Prognostic_studies Idioma: En Revista: Environ Sci Technol Año: 2017 Tipo del documento: Article País de afiliación: Australia