%0 Journal Article
%T Reconstructing historical trends of Berre lagoon contamination from surface sediment datasets: Influences of industrial regulations and anthropogenic silt inputs
%+ Centre européen de recherche et d'enseignement des géosciences de l'environnement (CEREGE)
%+ Laboratoire de MicrobiologiE de Géochimie et d'Ecologie Marines (LMGEM)
%+ Groupement d'intérêt public pour la réhabilitation de l'étang de Berre (GIPREB)
%A Rigaud, Sylvain
%A Radakovitch, O.
%A Nerini, David
%A Picon, P.
%A Garnier, J. M.
%< avec comité de lecture
%Z MIO:11-123
%@ 0301-4797
%J Journal of Environmental Management
%I Elsevier
%V 92
%N 9
%P 2201-2210
%8 2011-09
%D 2011
%R 10.1016/j.jenvman.2011.04.002
%K Sediment contamination
%K Temporal evolution
%K Statistical approach
%K Industrial regulation
%K Hydroelectric power plant
%K Berre lagoon
%Z Sciences of the Universe [physics]/Ocean, AtmosphereJournal articles
%X These last decades, the Berre lagoon (in southeastern France) has been deeply affected since the 1930s by strong inputs of contaminants associated with industrial development and since 1966 by huge inputs of freshwater and silts due to the installation of a hydroelectric power plant. Surveys of the surface sediment contamination have been sparsely performed since 1964 for management and research purposes. These surveys were performed by various laboratories that investigated different chemicals and sampling areas using different analysis protocols. Therefore, the available data are disconnected in time and space and differ in quality. In order to reconstruct coherent time series of sediment contamination from this heterogeneous datasets and to discuss the influences of industrial and hydroelectric discharges we used a statistical approach. This approach is based on Principal Component Analysis (PCA) and Fuzzy clustering analysis on data from one extensive survey realized on surface sediments in 1976. The PCA allowed identifying two geochemical indexes describing the main surface sediment geochemical characteristics. The fuzzy clustering analysis on these indexes allowed identifying sub-areas under the specific influence of industrial or hydroelectric discharges. This allowed us to reconstruct, for each sub-area, a coherent and interpretable long-term time series of sediment contamination from the available database. Reconstructed temporal trends allowed us to estimate: (i) the overall decrease of sediment contamination since the mid-1970 attributed to industrial discharge regulations enacted at this period and (ii) the dilution of the concentrations of sediment bound contaminants induced by the hydroelectric power plant and its associated particulate matter inputs.
%G English
%L hal-00745106
%U https://hal.science/hal-00745106
%~ INSU
%~ CNRS
%~ UNIV-AMU
%~ CDF
%~ CEREGE
%~ OSU-INSTITUT-PYTHEAS
%~ GIP-BE
%~ LMGEM
%~ PSL
%~ INRAE
%~ CDF-PSL
%~ INRAEPACA