J. Osán

Light Element Analysis of Individual Microparticles Using Thin-Window EPMA

Abstract.u2002The determination of the concentration of light elements, such as carbon, nitrogen and oxygen, in e.g. atmospheric aerosol particles is important to study the chemical behaviour of atmospheric pollution. The knowledge of low-Z element concentrations gives us information on the speciation of nutrients (species having nutritional value for plants) and toxic heavy metals in the particles. The capability of the conventional energy-dispersive EPMA is strongly limited for the analysis of low-Z elements, mainly because the Be window in the EDX detector hinders the detection of characteristic X-rays of light elements such as C, N, O and Na. WDS is suitable for analysis of light elements, but the measurement of beam sensitive microparticles requires the minimisation of the beam current and the measurement time. A semi-quantitative analytical method based on EPMA using an ultra-thin window EDX detector was developed. It was found that the matrix and geometric effects that are important for low-energy X-rays can be reliably evaluated by Monte Carlo calculations. Therefore, the quantification part of the method contains reverse Monte Carlo calculation done by iterative simulations. The method was standardised and tested by measurements on single particles with known chemical compositions. Beam-sensitive particles such as ammonium-sulphate and ammonium-nitrate were analysed using a liquid nitrogen cooled sample stage. The shape and size of the particles, which are important for the simulations, were determined using a high-magnification secondary electron image. Individual marine aerosol particles collected over the North Sea by a nine-stage Berner cascade impactor were analysed using this new method. Preliminary results on five samples and 4500 particles show that the method can be used to study the modification of sea-salt particles in the troposphere.

Quantitative characterization of individual aerosol particles by thin-window electron probe microanalysis combined with iterative simulation

Abstract A new data evaluation method and integrated software have been developed for the quantification of individual aerosol particles based on an iterative reverse Monte Carlo simulation combined with successive approximation for the elemental composition. The computer code supports the automatic spectrum processing and the statistical analysis by clustering of the measured and calculated data of the particles: X-ray characteristic intensities, calculated elemental concentrations and the particle sizes. The analytical procedure was tested rigorously by measurement of standard single particles such as (NH4)2SO4, NH4NO3, CaCO3, CaSO4, SiO2, Fe2O3, BaSO4, KNO3, NaCl and a good agreement between the nominal and calculated quantitative composition was found within 5–15 relative %. The correction of the second order processes caused by the characteristic fluorescence line of the substrate material (Alue5f8Kα) on the calculated concentration was estimated theoretically by a single mathematical model for particles with a spherical shape. The k ratio for the fluorescence correction was found to be less than 0.1–0.7% for low-Z analysis. The present semi-automated method was applied to analyse marine aerosol samples collected over the North Sea. Results of approximately 500 small individual particles show the capability of the method to quantify the elemental composition of sub-micrometre particles down to 0.2 μm.

X-Ray analysis of riverbank sediment of the Tisza (Hungary): identification of particles from a mine pollution event

Abstract A serious heavy metal pollution of the Tisza River occurred on March 10, 2000, arising from a mine-dumping site in Romania. Sediment samples were taken from the main riverbed at six sites in Hungary, on March 16, 2000. The objective of this work was to distinguish the anthropogenic and crustal erosion particles in the river sediment. The samples were investigated using both bulk X-ray fluorescence (XRF) and thin-window electron probe microanalysis (EPMA). For EPMA, a reverse Monte Carlo method calculated the quantitative elemental composition of each single sediment particle. A high abundance of pyrite type particles was observed in some of the samples, indicating the influence of the mine dumps. Backscattered electron images proved that the size of particles with a high atomic number matrix was in the range of 2 μm. In other words the pyrites and the heavy elements form either small particles or are fragments of larger agglomerates. The latter are formed during the flotation process of the mines or get trapped to the natural crustal erosion particles. The XRF analysis of pyrite-rich samples always showed much higher Cu, Zn and Pb concentrations than the rest of the samples, supporting the conclusions of the single-particle EPMA results. In the polluted samples, the concentration of Cu, Zn and Pb reached 0.1, 0.3 and 0.2 wt.%, respectively. As a new approach, the abundance of particle classes obtained from single-particle EPMA and the elemental concentration obtained by XRF were merged into one data set. The dimension of the common data set was reduced by principal component analysis. The first component was determined by the abundance of pyrite and zinc sulfide particles and the concentration of Cu, Zn and Pb. The polluted samples formed a distinct group in the principal component space. The same result was supported by powder diffraction data. These analytical data combined with Earth Observation Techniques can be further used to estimate the quantity of particles originating from mine tailings on a defined river section.

Characterisation of Individual Aerosol Particles for Atmospheric and Cultural Heritage Studies

Microanalysis of individual particles allows straightforward and advanced characterisation of environmental samples. The most obvious technique to study large microparticle populations is still electron probe X-ray microanalysis (EPXMA). Recently, technical and methodological progress has been made to remedy some of the limitations of conventional EPXMA, as, for example, in the detection of low Z-elements. Recent examples of the use of EPXMA in various environmental fields are presented, namely concerning atmospheric deposition of micropollutants and nutrients to the sea, characterisation of aerosols in the context of their effect on Global Change (remote continental and biogenic aerosols) and aerosol deposition and soiling of paintings in museums.

Application of chemometric methods for classification of atmospheric particles based on thin-window electron probe microanalysis data

Abstract Conventional single-particle electron probe microanalysis (EPMA) is widely used for evaluating the sources of atmospheric aerosol. The method is capable of simultaneously detecting the chemical composition and the morphology of each particle. Computer-controlled automatic EPMA allows the analysis of huge numbers of individual particles. Cluster as well as factor analysis are used for the classification of particles based on the obtained data set. However, the method is not able to detect low- Z elements (C, N, O), therefore, e.g. organic particles can only be identified by their typical inorganic content and high background. Using a thin-window X-ray detector, the capabilities of EPMA can be extended to determine low- Z elements. The recently developed quantification method based on Monte Carlo simulations is capable to evaluate elemental concentrations in single microscopic particles, including C, N and O. It was shown that also chemical species can be determined from the obtained concentrations. Hierarchical and non-hierarchical cluster analysis, as well as principal component analysis were applied for the classification of particles based on low- Z EPMA data. A mixture of standard particles as well as atmospheric aerosol samples were used to test the classification methods. Different input data (X-ray intensities or elemental concentrations) and scaling functions were used for the chemometric methods. Cluster and factor analysis appear to be efficient tools for classification of particles based on low- Z EPMA data. As an example, atmospheric ammonium sulphate and organic sulphur were classified in separate groups, which was not possible by conventional EPMA.