Sulfur isotope analysis of microcrystalline iron sulfides using secondary ion mass spectrometry imaging: Extracting local paleo-environmental information from modern and ancient sediments.

RATIONALE:Sulfur isotope ratio measurements of bulk sulfide from marine sediments have often been used to reconstruct environmental conditions associated with their formation. In situ microscale spot analyses by secondary ion mass spectrometry (SIMS) and laser ablation multiple-collector inductively coupled plasma mass spectrometry (LA-MC-ICP-MS) have been utilized for the same purpose. However, these techniques are often not suitable for studying small (≤10 μm) grains or for detecting intra-grain variability. METHODS:Here, we present a method for the physical extraction (using lithium polytungstate heavy liquid) and subsequent sulfur isotope analysis (using SIMS; CAMECA IMS 7f-GEO) of microcrystalline iron sulfides. SIMS sulfur isotope ratio measurements were made via Cs+ bombardment of raster squares with sides of 20-130 μm, using an electron multiplier (EM) detector to collect counts of 32 S- and 34 S- for each pixel (128 × 128 pixel grids) for between 20 and 960 cycles. RESULTS:The extraction procedure did not discernibly alter pyrite grain-size distributions. The apparent inter-grain variability in 34 S/32 S in 1-4 μm-sized pyrite and marcasite fragments from isotopically homogeneous hydrothermal crystals was ~ ±2‰ (1σ), comparable with the standard error of the mean for individual measurements (≤ ±2‰, 1σ). In contrast, grain-specific 34 S/32 S ratios in modern and ancient sedimentary pyrites and marcasites can have inter- and intra-grain variability >60‰. The distributions of intra-sample isotopic variability are consistent with bulk 34 S/32 S values. CONCLUSIONS:SIMS analyses of isolated iron sulfide grains yielded distributions that are isotopically representative of bulk 34 S/32 S values. Populations of iron sulfide grains from sedimentary samples record the evolution of the S-isotopic composition of pore water sulfide in their S-isotopic compositions. These data allow past local environmental conditions to be inferred