These results are for the 0.5 hour extraction of HCl.
See also the metadata records for the 4 hour extraction of HCl, and the time trial data for 1 M HCl extractions.
A regional survey of potential contaminants in marine or estuarine sediments is often one of the first steps in a post-disturbance environmental impact assessment. Of the many different chemical extraction or digestion procedures ... that have been proposed to quantify metal contamination, partial acid extractions are probably the best overall compromise between selectivity, sensitivity, precision, cost and expediency. The extent to which measured metal concentrations relate to the anthropogenic fraction that is bioavailable is contentious, but is one of the desired outcomes of an assessment or prediction of biological impact. As part of a regional survey of metal contamination associated with Australia's past waste management activities in Antarctica, we wanted to identify an acid type and extraction protocol that would allow a reasonable definition of the anthropogenic bioavailable fraction for a large number of samples. From a kinetic study of the 1 M HCl extraction of two certified Certified Reference Materials (MESS-2 and PACS-2) and two Antarctic marine sediments, we concluded that a 4 hour extraction time allows the equilibrium dissolution of relatively labile metal contaminants, but does not favour the extraction of natural geogenic metals. In a regional survey of 88 marine samples from the Casey Station area of East Antarctica, the 4 h extraction procedure correlated best with biological data, and most clearly identified those sediments thought to be contaminated by runoff from abandoned waste disposal sites. Most importantly the 4 hour extraction provided better definition of the low to moderately contaminated locations by picking up small differences in anthropogenic metal concentrations. For the purposes of inter-regional comparison, we recommend a 4 hour 1 M HCl acid extraction as a standard method for assessing metal contamination in Antarctica.
The fields in this dataset are