Radionuclide, organic matter and metal contamination properties of sediment deposits collected along the Seine River, in Paris City, following major floods in 2016, 2020 and 2021
Description
Following major floods in June 2016, March 2020 and February 2021, sediment has been collected on the quays along the Seine River across Paris City o investigate potential changes in sediment sources, dynamics and their metal contamination, including lead (Pb). Indeed, the fire that affected Notre-Dame Cathedral in April 2019 reignited concerns from the general public about the associated Pb emissions into the environment. To address this issue, sediment that deposited during significant floods that occurred both before (i.e., June 2016) and after the fire (i.e., March 2020 and February 2021) was analysed. In addition to the analysis of metal contamination (determined by elemental geochemistry and Pb isotope ratios) in sediment, it was also analysed for fallout radionuclide activities, organic matter properties and particle size with the objective to determine their physico-chemical properties, spatial sources and temporal dynamics. Fallout radionuclide activities were determined by gamma spectrometry using hyperpure germanium detectors at the Laboratoire des Sciences du Climat et de l’Environnement (LSCE, Paris-Saclay, France). Particle size distribution was determined using a Malvern Panalytical Mastersizer 3000 instrument at LSCE. Major, minor and trace elemental concentrations were analysed at LSCE with an Inductively Coupled Plasma – Mass Spectrometer equipped with 3 quadrupoles (TQ-ICP-MS, Thermo ScientificTM iCAPTM). Stable radiogenic lead isotope (206Pb, 207Pb, 208Pb) ratios were also determined at LSCE using the same instrument.TOC and TN elemental concentrations and stable isotope ratios (δ13C, δ15N) were determined by the combustion method using a continuous flow elemental analyser (Elementar VarioPyro cube) coupled with an Isotope Ratios Mass Spectometer (EA-IRMS) at the Institute of Ecology and Environmental Sciences (iEES, Paris, France).This dataset is described and interpreted in a manuscript submitted for publication to the 'Environmental Pollution' journal.
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Publication Details
Subfield
Ecology
Field
Environmental Science
Domain
Physical Sciences
Confidence Score
46%
Source
Scholar Data Model