Chemie und Prozesstechnik
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The need for quality assessment of anthropogenic impact on environmental pollution is increasing due to discharge from various industries, the use of chemicals in agriculture and the consumption of fossil fuels. Diminishing resources such as natural waters used for the cultivation of agricultural products, plant and animal habitats are under severe pollution pressure and are at constant risk. Several parameters, such as Pb, Cd, Ni, Hg were listed by Water Framework Directive in Directive(2008/105/EC) in the priority substances. Cadmium and Hg were identified as priority hazardous substances whereas As is an important contaminant for its potential toxicological and carcinogenic effects. An inter-comparison study is organised in EURAMET TC-MC in order to demonstrate the capability participants for measuring five elements in river water. The participants carried out measurements for analytes: Pb, Cd, Ni and As as mandatory elements, and Se as an optional one. Participants were asked to perform the measurements with respect to the protocol provided. To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.
The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
Per- und polyfluorierte Alkylverbindungen (PFAS) sind eine Substanzklasse bestehend aus mehreren tausenden Einzelverbindungen. Unter PFAS zählen alle Verbindungen, die mindestens eine perfluorierte Methyl- (-CF3) oder Methylen-Gruppe (-CF2-) besitzen. Somit zählt auch ein großer Teil der fluorierten Medikamente, Pflanzenschutzmittel oder Biozide in die PFAS-Substanzklasse. Aufgrund der Persistenz, Bioakkumulation in Nahrungsketten, Toxizität und der ubiquitären Verbreitung von PFAS zählen sie zu den „emerging pollutants“. Die PFAS-Analytik ist wegen ihrer vielfältigen physikalisch-chemischen Eigenschaften und der sehr hohen Anzahl an PFAS eine große Herausforderung. Da es für viele Anwendungen noch ungewiss ist, welche PFAS verwendet werden, wie sie in die Umwelt gelangen und welche Transformations- bzw. Abbauprodukte entstehen, stoßen analytische Ansätze, die nur auf Einzelsubstanzen abzielen, hier an ihre Grenzen. PFAS-Summenparameter-Methoden, die darauf abzielen ein möglichst vollständiges Abbild der PFAS-Belastungssituation widerzuspiegeln, werden daher immer wichtiger.
Accurate and precise isotope ratio measurements of heavy elements are playing an increasinglyimportant role in modern analytical sciences and have numerous applications. Today, isotope ratio measurements are typically performed with two principal techniques: thermal ionization mass spectrometry (TIMS) and multiple collector-inductively coupled plasma mass spectrometry (MC-ICP-MS). To obtain accurate results by mass spectrometry, isotopic certified reference materials (iCRMs) are needed for mass bias correction and for the validation of the method used for analysis.Thus, it is of paramount importance to achieve measurement comparability of all data reported, and to assess measurement capability of each CRM producer/National Metrology Institute (NMI). Therefore, the international comparison (CCQM-P213) was performed to assess the analytical capabilities of NMIs for the accurate determination of copper isotope ratio delta values in high purity materials. The study was proposed by the coordinating laboratories, National Research Council Canada (NRC), National Institute of Standards and Technology (NIST), Bundesanstalt für Materialforschung und -prüfung (BAM) and Physikalisch-Technische Bundesanstalt (PTB), as an activity of the Isotope Ratio Working Group (IRWG) of the Consultative Committee for Amount of Substance - Metrology in Chemistry and Biology (CCQM). Participants included six NMIs and one designated institute (DI) from the six countries. Although no measurement method was prescribed by the coordinating laboratories, MC-ICP-MS with either standard-sample bracketing (SSB) or combined SSB with internal normalization (C-SSBIN) models for mass bias correction were recommended. Results obtained from the six NMIs and one DI were in good agreement.