Optimization of ICP-AES and ICP-MS Techniques for the Determination of Major, Minor and Micro Elements in Lichens

Lichens are one of the best materials for air quality biomonitoring, and they have been widely used in atmospheric element deposition monitoring in many regions. Inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma atomic emission spectrometry (ICP-AES) are two efficient techniques widely used in quantifying and quantifying plant elements. However, elemental levels in lichens from some regions in China are much higher than in other plants, and their variation is highly dependent on space, time, species and elements. Although atmospheric pollution monitoring is urgently needed in China in recent decades, little studies have been performed on biomonitoring in the country. Therefore, the methodological studies on the determination of lichen elements in China are needed to accelerate future biomonitoring studies with lichens. Two techniques such as ICP-MS and ICP-AES were used to determine elements in four reference materials, as GBW10014 (cabbage), GBW10015 (spinach), GBW10052 (green tea) and IAEA-336 (lichen), with an attempt to reveal the effects of different digestions, sampling size, spectral lines, isotopes and internal standard elements on measured results. ICP-AES after dry ashing-alkali fusion digestion and ICP-MS after microwave digestion were optimized for lichen element determination. In the optimized techniques, good linear relationship (r>0.999 0), low detection limit, high analytic accuracy and precision were obtained. The optimized techniques were applied to lichen samples collected from Taihang Mountains of China and Ardley Island of Antarctica. The results show that all lichen samples from Taihang Mountains were much higher in elemental concentration with the contribution of atmospheric deposition higher than those from Antarctica. These results suggest the applicability of the techniques in determining lichen elements, and provide evidences and technique supports for air pollution biomonitoring in China.