Development of a large volume injection method using a programmed temperature vaporization injector - gas chromatography hyphenated to ICP-MS for the simultaneous determination of mercury, tin and lead species at ultra-trace levels in natural waters.

The current EU legislation lays down Environmental Quality Standards (EQS) for 45 priority substances in surface waters; among them levels for (organo)metallic species of Hg, Sn and Pb are set between ng L-1 (for Hg and Sn) and µg L-1 (for Pb). To date, only a few analytical methods can reach these very restrictive limits and there is thus a need for comprehensive methods able to analyze these species down to these levels in natural waters. The aim of this work was to develop an online automated pre-concentration method using large volume injections with a Programmed Temperature Vaporization (PTV) injector fitted with a sorbent packed liner coupled to GC-ICP-MS to further improve the detection limits associated to this well-established method. The influence of several parameters such as the PTV transfer temperature and time, carrier gas flow rate and amount of packing material was investigated. Finally, the maximum volume injected through single or multiple injection modes was optimized to obtain the best compromise between chromatographic resolution and sensitivity. After optimization, very satisfactory results in terms of absolute and methodological detection limits were achieved, down to the pg L-1 level for all species studied. The potential of the method was exemplified by determining the concentrations of organometallic compounds in unpolluted river waters samples from the Adour river basin (SW France) and results were compared with conventional (splitless) GC-ICP-MS. The strength of this analytical method lies in the low detection limits reached for the simultaneous analysis of a wide group of organometallic compounds, and the potential to transfer this method to other gas chromatographic applications with inherent lower sensitivity.

Fast assessment of bioaccessible metallic contamination in marine sediments.

A fast (16min) procedure to assess the bioaccessible metallic fraction of Cd, Cr, Cu, Ni, Pb and Zn simultaneously extracted (SEM) from marine sediments plus an indirect approach to determine acid volatile sulfides (AVS) are presented. For the extraction process magnetic agitation was compared with ultrasonic stirring (using a bath and a probe), and several stirring times were assayed. The proposed SEM procedure uses an ultrasonic probe and 1mL of HCl. It dramatically minimizes the turnaround time and the residues. AVS were evaluated as the difference between the amounts of sulphur in the solid residue after the extraction and total sulphur in the original sample. These procedures are fast, easy to implement and cost-effective to assess the potential risk posed by metals in marine sediments. They were tested using several CRMs and applied to sediments from two Galician Rias (NW Spain); their SEM-AVS differences indicated no biological risk.

Interpolation in the standard additions method.

The standard additions method (SAM) has traditionally been performed by using extrapolation. This practice is suboptimal because predictions are affected by even slight departures of calibration points from a straight line. Despite this, most textbooks and papers in analytical chemistry still refer exclusively to extrapolation. In contrast, the use of interpolation is recommended in this paper as a way to get predictions on the central part of the regression line and thus minimize the bias in the prediction and the variance associated with the analytical result. Several scenarios were studied, with concentration errors simulated in different calibration solutions. It was found that translational effects due to variations at the central part of the calibration caused the lowest disturbances on the predicted concentrations. The differences between the interpolated and extrapolated predictions can be as large as ±30%. The confidence interval associated with the extrapolation result is wider than that due to interpolation by as much as 100%. It is shown that commonly used equations underestimate the correct confidence intervals. Both, absence of bias and improved precision, are of relevance in quality assurance, method validation and error propagation.