Footprint of Arsenic Contamination in Sediments and Water from Mining Sites – A case study based on multivariate optimization by GF AAS

Abstract

Arsenic contamination is worrisome in mineral exploration regions. Efficient arsenic monitoring is dependent on detectability at trace level in environmental matrices. This paper presents a procedure to evaluate the occurrence of arsenic in environmental sediment and water samples collected from a mining area in Catalão, Goiás State (GO), Brazil. The water and sediment samples were analyzed by graphite furnace atomic absorption spectrometry (GF AAS) after appropriate chemical treatment. For the arsenic determination, analytical performance was improved employing multivariate tools. The instrumental conditions were optimized using a 23 factorial design and the response surface methodology (RSM) was applied with a central composite design (CCD). Iridium was used as a permanent modifier. The results for the sediment samples showed arsenic concentrations below the threshold for adverse effects ranging from 2.06 to 3.82 mg Kg-1. The concentrations in water samples were below LOD. The LOD and LOQ were, respectively, 0.33 and 1.09 µg L-1 to water and digested sediment samples. Under the optimal conditions, the dynamic working range was linear of LOQ to 50.0 µg L-1. The method was applied to determine concentrations of arsenic in water and sediments collected from mining sites, which can be used to assess the availability of arsenic in the region.