The International Atomic Energy Agency (IAEA) jointly with the Elettra Sincrotrone Trieste (EST) operates a multipurpose X-ray spectrometry endstation at the X-ray Fluorescence beamline (10.1L). The facility has been available to external users since the beginning of 2015 through the peer-review process of EST. Using this collaboration framework, the IAEA supports and promotes synchrotron-radiation-based research and training activities for various research groups from the IAEA Member States, especially those who have limited previous experience and resources to access a synchrotron radiation facility. This paper aims to provide a broad overview about various analytical capabilities, intrinsic features and performance figures of the IAEA X-ray spectrometry endstation through the measured results. The IAEA-EST endstation works with monochromatic X-rays in the energy range 3.7-14 keV for the Elettra storage ring operating at 2.0 or 2.4 GeV electron energy. It offers a combination of different advanced analytical probes, e.g. X-ray reflectivity, X-ray absorption fine-structure measurements, grazing-incidence X-ray fluorescence measurements, using different excitation and detection geometries, and thereby supports a comprehensive characterization for different kinds of nanostructured and bulk materials.

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19A new synchrotron beamline end-station for multipurpose X-ray spectrometry applications 20 has been recently commissioned and it is currently accessible by end-users at the XRF

The capital city of Mongolia, Ulaanbaatar, suffers from high levels of pollution due to excessive airborne particulate matter (APM). A lack of systematic data for the region has inspired investigation into the type, origin and seasonal variations of this pollution, the effects of meteorological conditions and even the time-dependence of anthropogenic sources. This work reports source apportionment results from a large data set of 184 samples each of fine (PM 2.5 ) and coarse (PM 2.5-10 ) fraction atmospheric PM collected over a three-year period (2014)(2015)(2016) in Ulaanbaatar, Mongolia. Positive Matrix Factorization (PMF) was applied using the concentrations of 16 elements measured by an energy dispersive X-ray fluorescence spectrometer along with the black carbon content measured by a reflectometer as input data. The PMF results revealed that whereas mixed sources dominate the coarse fraction, soil and traffic sources are the principle contributors to the fine fraction. The source profiles and the seasonal variations of their contributions indicate that fly ash emanating from coal combustion mixes with traffic emissions and resuspended soil, resulting in variable chemical source profiles. Four sources were identified for both fractions, namely, soil, coal combustion, traffic and oil combustion, which respectively contributed 35%, 16%, 41% and 8% to the coarse fraction and 31%, 27%, 31% and 11% to the fine fraction. Additionally, the probable source contributions from long-range transport events were assessed via concentration-weighted trajectory analysis.

Food fraud is a concern for the producers of high-quality food products as it causes brand damage and loss of profit. Tea (Camellia sinensis L.) is one of the major agricultural products of Sri Lanka and accounts for more than 300 million of kilograms per year, roughly 2% of the national GDP. Trace metals and stable isotope ratios in tea samples originating from various regions in Sri Lanka were determined by using X-ray fluorescence analysis and isotope-ratio mass spectrometry to explore the possibility of classifying the tea according to its origin. In total, 13 elements (Mg, P, S, Cl, K, Ca, Mn, Fe, Cu, Zn, Br, Rb and Sr) were determined in 58 tea samples originating from four production districts in Sri Lanka (Hantana, Thalawakelle, Passara and Ratnapura). Two multivariate analysis techniques, namely principal component analysis and canonical discriminant analysis, were applied to explore the differences in elemental contents among the tea produced in these regions and to find a method for compositional classification. This study, although limited by the number of samples available, clearly shows that the differentiation and classification of tea samples according to the four regions of origin is possible by using the elemental contents and applying canonical discriminant analysis.