TY - JOUR
T1 - Impact of in-Sewer Degradation of Pharmaceutical and Personal Care Products (PPCPs) Population Markers on a Population Model
AU - O'Brien, Jake William
AU - Banks, Andrew Phillip William
AU - Novic, Andrew Joseph
AU - Mueller, Jochen F.
AU - Jiang, Guangming
AU - Ort, Christoph
AU - Eaglesham, Geoff
AU - Yuan, Zhiguo
AU - Thai, Phong K.
N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].
PY - 2017/4/4
Y1 - 2017/4/4
N2 - 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. © 2017 American Chemical Society.
AB - 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. © 2017 American Chemical Society.
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U2 - 10.1021/acs.est.6b02755
DO - 10.1021/acs.est.6b02755
M3 - RGC 21 - Publication in refereed journal
C2 - 28244310
SN - 0013-936X
VL - 51
SP - 3816
EP - 3823
JO - Environmental Science and Technology
JF - Environmental Science and Technology
IS - 7
ER -