Ultrasound- and microwave-assisted extractions followed by hydride generation inductively coupled plasma optical emission spectrometry for lead determination in geological samples

Followed the current idea of simplified sample pretratmet before analysis we evaluated the procedure for the determination of Pb in calcium-rich materials such as dolomites after ultrasound- or microwave-assisted extraction with diluted acids using hydride generation inductively coupled plasma optical emission spectrometry (HG-ICP-OES). Corresponding Pb hydride was generated in the reaction of an acidified sample solution with NaBH4 after pre-oxidation of Pb(II) to Pb(IV) by K-3[Fe(CN)(6)]. Several chemical (acidic media: HCl, HNO3 or CH3COOH, concentration of the reductant as well as type and concentration of oxidazing agents) and physical (reagents flow rates, reaction coil length) parameters affecting the efficiency of plumbane formation were optimized in order to improve the detectability of Pb using HG-ICP-OES. Limitation of the method derived from the matrix effects was pointed out. Employing Pb separation by HG technique allows the significant reduction of interferences caused by sample matrix constituents (mainly Ca and Mg), nevertheless they could not be overcame at all, hence calibration based on the standard addition method was recommended for Pb quantification in dolomites. Under the selected conditions, i.e. 0.3 mol L-1 HCI, HNO3 or CH3COOH, 1.5% NaBH4 and 3.0% K-3[Fe(CN)(6)] the limits of detection (LODs) between 2.3-5.6 mu g L-1 (3.4-6.8 mu g L-1 considering matrix effects) and the precision below 5% were achieved. The accuracy of the procedure was verified by analysis of certified reference materials (NCS DC70308 (Carbonate Rock) and NIST 14000 (Bone Ash)) and recovery test with satisfactory results of Pb recoveries ranging between 94-108% (CRMs analysis) and 92-114% (standard addition method). The applicability of the proposed method was demonstrated by the determination of Pb in dolomites used by different fertiliser factories. (C) 2015 Elsevier B.V. All rights reserved.