Environmental and toenail metals concentrations in copper mining and non mining communities in Zambia.

Copper mining contributes to increased concentrations of metals in the environment, thereby increasing the risk of metals exposure to populations living in and around mining areas. This study investigated environmental and toenail metals concentrations of non-occupational human exposure to metals in 39 copper-mining town residents and 47 non-mining town residents in Zambia. Elevated environmental concentrations were found in samples collected from the mining town residents. Toenail concentrations of cobalt (GM 1.39 mg/kg), copper (GM 132 mg/kg), lead (21.41 mg/kg) selenium (GM 0.38 mg/kg) and zinc (GM 113 mg/kg) were significantly higher in the mining area and these metals have previously been associated with copper mining. Residence in the mining area, drinking water, dust and soil metals concentrations were the most important contributors to toenail metals concentrations. Further work is required to establish the specific pathways of exposure and the health risks of elevated metals concentrations in the copper mining area.

Multivariate statistical methods for the environmental forensic classification of coal tars from former manufactured gas plants.

Compositional disparity within a set of 23 coal tar samples (obtained from 15 different former manufactured gas plants) was compared and related to differences between historical on-site manufacturing processes. Samples were prepared using accelerated solvent extraction prior to analysis by two-dimensional gas chromatography coupled to time-of-flight mass spectrometry. A suite of statistical techniques, including univariate analysis, hierarchical cluster analysis, two-dimensional cluster analysis, and principal component analysis (PCA), were investigated to determine the optimal method for source identification of coal tars. The results revealed that multivariate statistical analysis (namely, PCA of normalized, preprocessed data) has the greatest potential for environmental forensic source identification of coal tars, including the ability to predict the processes used to create unknown samples.

Ultra resolution chemical fingerprinting of dense non-aqueous phase liquids from manufactured gas plants by reversed phase comprehensive two-dimensional gas chromatography.

Ultra resolution chemical fingerprinting of dense non-aqueous phase liquids (DNAPLs) from former manufactured gas plants (FMGPs) was investigated using comprehensive two-dimensional gas chromatography coupled with time of flight mass spectrometry (GC×GC TOFMS). Reversed phase GC×GC (i.e. a polar primary column coupled to a non-polar secondary column) was found to significantly improve the separation of polycyclic aromatic hydrocarbons (PAHs) and their alkylated homologues. Sample extraction and cleanup was performed simultaneously using accelerated solvent extraction (ASE), with recovery rates between 76% and 97%, allowing fast, efficient extraction with minimal solvent consumption. Principal component analysis (PCA) of the GC×GC data was performed in an attempt to differentiate between twelve DNAPLs based on their chemical composition. Correlations were discovered between DNAPL composition and historic manufacturing processes used at different FMGP sites. Traditional chemical fingerprinting methods generally follow a tiered approach with sample analysis on several different instruments. We propose ultra resolution chemical fingerprinting as a fast, accurate and precise method of obtaining more chemical information than traditional tiered approaches while using only a single analytical technique.