ABSTRACT
Fe oxyhydroxides in riverbanks and their high binding capacity can be used to hypothesize that riverbanks may act as a "biogeochemical filter" between wetlands and rivers and may constitute a major mechanism in the trapping and flux regulation of chemical elements. Until now, the properties of Fe minerals have been very poorly described in riverbanks. The goals of the present work are to identify Fe speciation in riverbanks where ferric deposits are observed and to determine their impact on the metal behavior (As, Co, Cu, Ni, Pb, Zn, etc.). At the surface, Fe speciation is mainly composed of small poorly crystalline Fe phases, i.e. ferrihydrite (~30%), Fe-OM associations (~40%) as well as crystalline Fe phases, i.e. goethite (~35%). At the subsurface, the Fe distribution is dominated by goethite (~35%) and Fe-mica (~35%), the proportion of which increases at the expense of ferrihydrite and the Fe-OM associations. At the riverbank surface, ferrihydrite and the Fe-OM associations are therefore the main Fe hosting phases in response to (i) the fast Fe(II) oxidation induced by the presence of O2 and (ii) the high amount of OM favoring the formation of nano-phases bound to OM (Fe monomers, polymers and nanoparticles) and preventing mineralogical transformation (ferrihydrite into goethite). During the high-water level period (high flow), a strong erosion of the riverbank transfers these ferric deposits into the river. However, the physicochemical parameters of the river (pHâ¯6.6-7.6 and continuous oxic conditions) do not promote the dissolution of Fe oxyhydroxides and OM. Ferric deposits and the associated trace metals are therefore maintained as colloids/particles and are exported to the outlet. All of the results presented here demonstrate that the ferric deposits trap metals on a seasonal basis and are therefore a key factor in the mobilization of metals during riverbank erosion by river flow.
ABSTRACT
Improving the microbiological quality of coastal and river waters relies on the development of reliable markers that are capable of determining sources of fecal pollution. Recently, a principal component analysis (PCA) method based on six stanol compounds (i.e. 5ß-cholestan-3ß-ol (coprostanol), 5ß-cholestan-3α-ol (epicoprostanol), 24-methyl-5α-cholestan-3ß-ol (campestanol), 24-ethyl-5α-cholestan-3ß-ol (sitostanol), 24-ethyl-5ß-cholestan-3ß-ol (24-ethylcoprostanol) and 24-ethyl-5ß-cholestan-3α-ol (24-ethylepicoprostanol)) was shown to be suitable for distinguishing between porcine and bovine feces. In this study, we tested if this PCA method, using the above six stanols, could be used as a tool in "Microbial Source Tracking (MST)" methods in water from areas of intensive agriculture where diffuse fecal contamination is often marked by the co-existence of human and animal sources. In particular, well-defined and stable clusters were found in PCA score plots clustering samples of "pure" human, bovine and porcine feces along with runoff and diluted waters in which the source of contamination is known. A good consistency was also observed between the source assignments made by the 6-stanol-based PCA method and the microbial markers for river waters contaminated by fecal matter of unknown origin. More generally, the tests conducted in this study argue for the addition of the PCA method based on six stanols in the MST toolbox to help identify fecal contamination sources. The data presented in this study show that this addition would improve the determination of fecal contamination sources when the contamination levels are low to moderate.
