title: A predictive multi-linear regression model for organic micropollutants, based on a laboratory-scale column study simulating the river bank filtration process.
abstract: This study investigated relationships between OMP biodegradation rates and the functional groups present in the chemical structure of a mixture of 31 OMPs. OMP biodegradation rates were determined from lab-scale columns filled with soil from RBF site Engelse Werk of the drinking water company Vitens in The Netherlands. A statistically significant relationship was found between OMP biodegradation rates and the functional groups of the molecular structures of OMPs in the mixture. The OMP biodegradation rate increased in the presence of carboxylic acids, hydroxyl groups, and carbonyl groups, but decreased in the presence of ethers, halogens, aliphatic ethers, methyl groups and ring structures in the chemical structure of the OMPs. The predictive model obtained from the lab-scale soil column experiment gave an accurate qualitative prediction of biodegradability for approximately 70% of the OMPs monitored in the field (80% excluding the glymes). The model was found to be less reliable for the more persistent OMPs (OMPs with predicted biodegradation rates lower or around the standard error=0.77d(-1)) and OMPs containing amide or amine groups. These OMPs should be carefully monitored in the field to determine their removal during RBF.
authors.affiliation: Delft University of Technology, Department of Water Management, PO Box 5048, 2600 GA Delft, The Netherlands; Ghent University, Faculty of Bioscience Engineering, Particle and Interfacial Technology Group, Coupure Links 653, B-9000 Ghent, Belgium. Electronic address: c.bertelkamp@tudelft.nl.
authors.forename: C
authors.initials: C
authors.lastname: Bertelkamp
authors.affiliation: Delft University of Technology, Department of Water Management, PO Box 5048, 2600 GA Delft, The Netherlands; Ghent University, Faculty of Bioscience Engineering, Particle and Interfacial Technology Group, Coupure Links 653, B-9000 Ghent, Belgium.
authors.forename: A R D
authors.initials: AR
authors.lastname: Verliefde
authors.affiliation: The University of Auckland, School of Chemical Sciences, Private Bag 92019, Auckland 1142, New Zealand.
authors.forename: J
authors.initials: J
authors.lastname: Reynisson
authors.affiliation: The University of Auckland, Department of Civil and Environmental Engineering, Private Bag 92019, Auckland 1142, New Zealand.
authors.forename: N
authors.initials: N
authors.lastname: Singhal
authors.affiliation: Delft Institute of Applied Mathematics (DIAM), Faculty EEMCS, Mekelweg 4, 2628 CD Delft, The Netherlands.
authors.forename: A J
authors.initials: AJ
authors.lastname: Cabo
authors.affiliation: Vitens N.V., PO Box 1205, 8001 BE Zwolle, The Netherlands.
authors.forename: M
authors.initials: M
authors.lastname: de Jonge
authors.affiliation: Delft University of Technology, Department of Water Management, PO Box 5048, 2600 GA Delft, The Netherlands; Strategic Centre, Waternet, Korte Ouderkerkerdijk 7, 1096 AC Amsterdam, The Netherlands.
authors.forename: J P
authors.initials: JP
authors.lastname: van der Hoek
mesh_terms: D001673:Biodegradation, Environmental; D005374:Filtration; D016014:Linear Models; D045483:Rivers / Q000737:chemistry; D012987:Soil / Q000737:chemistry; D012988:Soil Microbiology; D014874:Water Pollutants, Chemical / Q000032:analysis / Q000737:chemistry / Q000378:metabolism
chemical_list: D012987:Soil; D014874:Water Pollutants, Chemical
keywords: Biodegradation; Organic micropollutants; Predictive model; QSAR; River bank filtration