Journal
JOURNAL OF GEOCHEMICAL EXPLORATION
Volume 170, Issue -, Pages 39-57Publisher
ELSEVIER
DOI: 10.1016/j.gexplo.2016.08.003
Keywords
Heavy metals; Fluvial sediments; Enrichment; Pollution
Categories
Funding
- Czech Science Foundation [15-00340S]
Ask authors/readers for more resources
This paper provides an overview of the natural variability of the element composition of fluvial sediments, paying particular attention to As, Al, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Ti, and Zn. The primary factors controlling the sediment composition are source rocks in the river catchment, the extent of their weathering, the sorting of so-formed solids during transport through the catchment, and their chemical transformations, in particular reductive/oxidative-driven processes, particularly affecting the finest particles in the fluvial systems. Those factors result in grain-size control as the major source of variation of the sediment's chemical composition; they also change element patterns (ratios, associations) in the finest sediment components compared to Earth's upper crust. Grain-size control of element composition (the grain-size effect) is suppressed by geochemical normalization and is best treated through geochemical background functions applied to analyses of bulk samples. Robust regression should be preferred for inter-element relationships in fluvial sediments. Conversely, the evaluation of element concentrations in sediments neglecting grain size or using particle-size separation (e.g., sieving to submillimetre size fractions) to separate only a minor weight fraction of the sediment should be avoided in research. Improper data processing and a lack of respect for natural variability may prevent the recognition of anthropogenic pollution. The use of inappropriate statistic tools in this task, such as the mean +/- 2 sigma,boxplots, and ordinary least-squares' regression, is primarily hindered by the lack of a Gaussian distribution of element concentrations in real collections of fluvial sediments and neglect of a suite of natural factors inherent to fluvial sediments. The applicability of geochemical background concepts is discussed at three levels of approaching reality: (1) a normalization of target element concentrations M using reference element M-REF, M/M-REF, where M-REF is typically Al, Fe, Ti, or Rb; (2) a comparison of normalized concentrations with normalized mean upper crustal concentrations by double normalization producing enrichment factors, EF = (M/M-REF)(sample)/(M/M-REF)(UCC), where UCC refers to the mean composition of the upper continental crust; and (3) empirical geochemical background functions predicting background concentration M-GB and producing local enrichment factor LEF = M/M-GB. The latter of these three approaches is recommended as it performs well also in immature sediments (unlike double normalization with Al as M-REF) and considers the specificity of individual river catchments. The empirical background functions (linear, non-linear, with variable intercepts) derived from unpolluted and post-depositionally unaffected sediments and LEF are effective in avoiding the grain-size bias of enrichment factors typical of the commonest method of double normalization with Al as M-REF, An overview is provided regarding exogenic processes that produce element patterns different from those of the catchment rocks and thus biasing EF obtained by double normalization. The processes' consequences for fine chemical weathering products include the following: (1) the natural enrichment of elements, such as Cd, Cu, Fe, Mn, Pb, and Zn in fine fluvial sediments as compared to parent rocks and (2) the formation or strengthening of the risk elements' association with Fe. We hypothesize that both phenomena result from the preferential chemical weathering of felsic minerals and biogeochemical processes in catchment and fluvial systems. The list of risk elements naturally enriched in the finest fluvial sediments is not complete and probably also include As, Bi, Hg, and Sb; the phenomena responsible for that deserve further research. (C) 2016 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available