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Abstract: A quantification procedure of trace elements during colloid size fractionation was developed and validated. This procedure is based on the hyphenation between Asymmetrical Flow Field-Flow Fractionation (As-Fl-FFF) and Inductively Coupled Plasma Mass Spectrometer (ICP-MS). The optimisation of the procedure was performed on a soil leachate spiked with six trace elements selected for their environmental and health impact (As, Cd, Sb, Se, Sn and Pb). The elements in the spiked sample were on-line monitored during the fractionation. The validation was carried out by comparison with a second off-line quantification procedure based on fraction collection and total element analysis by ICP-MS. This off-line one was previously validated using reference materials. Finally, the analytical performances of the two procedures were compared. [Copyright &y& Elsevier]

A good knowledge of the dynamic of pollutant concentration and flux in a combined sewer network is necessary when considering solutions to limit the pollutants discharged by combined sewer overflow (CSO) into receiving water during wet weather. Identification of the parameters that influence pollutant concentration and flux is important. Nevertheless, few studies have obtained satisfactory results for the identification of these parameters using statistical tools. Thus, this work uses a large database of rain events (116 over one year) obtained via continuous measurement of rainfall, discharge flow and chemical oxygen demand (COD) estimated using online turbidity for the identification of these parameters. We carried out a statistical study of the parameters influencing the maximum COD concentration, the discharge flow and the discharge COD flux. In this study a new test was used that has never been used in this field: the conditional regression tree test. We have demonstrated that the antecedent dry weather period, the rain event average intensity and the flow before the event are the three main factors influencing the maximum COD concentration during a rainfall event. Regarding the discharge flow, it is mainly influenced by the overall rainfall height but not by the maximum rainfall intensity. Finally, COD discharge flux is influenced by the discharge volume and the maximum COD concentration. Regression trees seem much more appropriate than common tests like PCA and PLS for this type of study as they take into account the thresholds and cumulative effects of various parameters as a function of the target variable. These results could help to improve sewer and CSO management in order to decrease the discharge of pollutants into receiving waters. [ABSTRACT FROM AUTHOR]