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assignment_turned_in ProjectFrom 2017Partners:UIUC, Curtin Water Quality Research Centre, LEESU, SYNDICAT INTERDEPARTMENTAL POUR L'ASSAINISSEMENT DE L'AGGLOMERATION PARISIENNE, UAUIUC,Curtin Water Quality Research Centre,LEESU,SYNDICAT INTERDEPARTMENTAL POUR L'ASSAINISSEMENT DE L'AGGLOMERATION PARISIENNE,UAFunder: French National Research Agency (ANR) Project Code: ANR-17-CE34-0009Funder Contribution: 272,052 EURNumerous emerging micropollutants (e.g., personal care products, antibiotics, endocrine disruptors) are found in urban waters but their transformation and behavior in wastewater treatment plants and in the urban environment are not well characterized. Current workflows for the non-targeted analysis of organic micropollutants by high resolution mass spectrometry (HRMS) are complex and time-consuming. The aim of this 4-year project is to develop a comprehensive approach for the characterization of organic micropollutants in urban waters by HRMS, by (1) providing an innovative protocol for the extraction and analysis of both polar and non-polar compounds from urban waters; (2) developing data treatment methods and global indices derived from HRMS fingerprints; and (3) applying chemometrics/omics methods for data analyses of urban water samples in conjunction with toxicity analyses, with a focus on the characterization of polar molecules. The achievement of these objectives will provide advances in workflows for the detection of micropollutants using non-targeted analyses. It will allow the potential identification of new classes of chemicals, metabolites and degradation products, and the categorization of products based on several indices (e.g., molecular formula, hydrophilicity/polarity, type of degradation mechanism). Developing specific indices to characterize families of compounds will help getting faster results from HRMS measurements, without reducing the level of details obtained by HRMS analysis. The originality of the WaterOmics project lies in this global approach, by avoiding the time-consuming and complex steps of molecular structure identification. This approach will be tested through the evaluation of performances of advanced wastewater treatment processes towards the elimination of organic micropollutants. Micropollutant transformation during various oxidation processes (ozonation, UV photolysis, chlorination, peracids) will be studied at the lab-scale and pilot-scale. The performance of major wastewater treatment plants of the Paris conurbation will also be evaluated for the removal of micropollutants. Results will provide remediation strategies to limit the impact of micropollutants on the environment. An important sampling program in wastewater plants, discharges and urban rivers will be performed in collaboration with a major wastewater plant operator (SIAAP). The long-term impacts of urban water discharges in the environment will be followed, and multiple HRMS fingerprints from various urban waters (i.e., wastewater, runoff and fresh waters) will be acquired in a database. The validation of methods and indices and their robustness by investigating a broad range of water matrices will be essential. Relationships between classes of urban contaminants and the toxicity of samples will be established to get a comprehensive view of the exposome from urban water samples. This project will provide innovative tools to characterize and monitor the behavior of organic compounds in water systems and their toxic impacts, which will benefit to the water community, from researchers to operational institutions and industrial structures involved in water management and treatment.
more_vert assignment_turned_in Project1994 - 1996Partners:UIUCUIUCFunder: National Science Foundation Project Code: 9315825more_vert assignment_turned_in Project1979 - 1983Partners:UIUCUIUCFunder: National Science Foundation Project Code: 7822068more_vert assignment_turned_in Project2017 - 2017Partners:UIUCUIUCFunder: National Science Foundation Project Code: 1700426more_vert assignment_turned_in Project1974 - 1975Partners:UIUCUIUCFunder: National Science Foundation Project Code: 7463483more_vert
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