Estimating specific surface area of fine stream bed sediments from geochemistry

Rawlins, B.G.; Turner, G.; Mounteney, I.; Wildman, G.. 2010 Estimating specific surface area of fine stream bed sediments from geochemistry. Applied Geochemistry, 25 (9). 1291-1300. https://doi.org/10.1016/j.apgeochem.2010.05.009

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Abstract/Summary

Specific surface area (SSA) of headwater stream bed sediments is a fundamental property which determines the nature of sediment surface reactions and influences ecosystem-level, biological processes. Measurements of SSA – commonly undertaken by BET nitrogen adsorption – are relatively costly in terms of instrumentation and operator time. A novel approach is presented for estimating fine (<150 μm) stream bed sediment SSA from their geochemistry – after removal of organic matter – for agricultural headwater catchments across 15,400 km2 of central England, UK. From a regional set of 1972 stream bed sediment sites with common characteristics for which geochemical data were available, 60 samples were selected – based on maximising their variation in Al concentrations – and their BET SSA measured by N2 adsorption. After careful selection of potential regression predictors following a principal component analysis and removal of a subset of samples with the largest Mo concentrations (>2.5 mg kg−1), four elements were identified as significant predictors of SSA (ordered by decreasing predictive power): V > Ca > Al > Rb. The optimum model from these four elements accounted for 73% of the variation in bed sediment SSA (range 6–46 m2 g−1) with a root mean squared error of prediction – based on leave-one-out cross-validation – of 6.3 m2 g−1. It is believed that V is the most significant predictor because its concentration is strongly correlated both with the quantity of Fe-oxides and clay minerals in the stream bed sediments, which dominate sediment SSA. Sample heterogeneity in SSA – based on triplicate measurements of sub-samples – was a substantial source of variation (standard error = 2.2 m2 g−1) which cannot be accounted for in the regression model. The model was used to estimate bed sediment SSA at the other 1792 sites and at 30 duplicate sites where an extra sediment sample had been collected, 25 m from the original site. By delineating sub-catchments for the headwater sediment sites only those sub-catchments were selected with a dominant (>50% of the sub-catchment area) bedrock formation and land use type; the bedrock and land use classes accounted for 39% and 7% of the variation in bed sediment SSA, respectively. Variation in estimated, fine bed sediment SSA from the paired, duplicate sediment sites was small (2.7 m2 g−1), showing that local variation in SSA at stream sites is modest when compared to that between catchments. How the approach might be applied in other environments and its potential limitations are discussed.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1016/j.apgeochem.2010.05.009
Programmes:	BGS Programmes 2010 > Land Use, Planning and Development
ISSN:	0883-2927
Date made live:	16 Aug 2010 13:39 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/10687

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