Measuring selected PPCPs in wastewater to estimate the population in different cities in China

Gao, Jianfa, O'Brien, Jake, Du, Peng, Li, Xiqing, Ort, Christoph, Mueller, Jochen F., & Thai, Phong K. (2016) Measuring selected PPCPs in wastewater to estimate the population in different cities in China. Science of the Total Environment, 568, pp. 164-170.

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Sampling and analysis of wastewater from municipal wastewater treatment plants (WWTPs) has become a useful tool for understanding exposure to chemicals. Both wastewater based studies and management and planning of the catchment require information on catchment population in the time of monitoring. Recently, a model has been developed and calibrated using selected pharmaceutical and personal care products (PPCP) measured in influent wastewater for estimating population in different catchments in Australia. The present study aimed at evaluating the feasibility of utilizing this population estimation approach in China. Twenty-four hour composite influent samples were collected from 31 WWTPs in 17 cities with catchment sizes from 200,000-3,450,000 people representing all seven regions of China. The samples were analyzed for 19 PPCP using liquid chromatography coupled to tandem mass spectrometry in direct injection mode. Eight chemicals were detected in more than 50 % of the samples. Significant positive correlations were found between individual PPCP mass loads and population estimates provided by WWTP operators. Using the PPCP mass load modeling approach calibrated with WWTP operator estimates, we estimated the population size of each catchment with good agreement with WWTP operator estimates (between 50 - 200% for all sites and 75 - 125% for 23 of the 31 sites). Overall despite much lower detection and relatively high heterogeneity in PPCP consumption across China the model provided a good estimate of the population contributing to a given wastewater sample. Wastewater analysis could also provide objective PPCP consumption status in China.

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2 citations in Web of Science®
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ID Code: 96239
Item Type: Journal Article
Refereed: Yes
DOI: 10.1016/j.scitotenv.2016.05.216
ISSN: 0048-9697
Divisions: Current > Institutes > Institute of Health and Biomedical Innovation
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2016 Elsevier
Copyright Statement: Licensed under the Creative Commons Attribution; Non-Commercial; No-Derivatives 4.0 International. DOI: 10.1016/j.scitotenv.2016.05.216
Deposited On: 19 Jun 2016 22:52
Last Modified: 27 Jun 2017 23:01

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