Supporting information for Round robin test of secondary raw materials: a systematic review of performance parameters

This document serves as supporting information for the article "Round robin tests of secondary raw materials: a systematic review of performance parameters", published in the journal "Reviews in Analytical Chemistry", https://doi.org/10.1515/revac-2022-0033

Round robin tests of secondary raw materials: A systematic review of performance parameters

An improved management of secondary raw materials (SRM) is a crucial contribution for a circular economy and necessitates knowledge about the composition of wastes and SRM. However, this information is scarce and has to be determined with chemical analysis (CA). CA of SRM faces challenges, which can be approached by using round robin tests (RRT) to identify deviations from the “true value” of an element/molecule content. An RRT is a testing approach, which involves multiple labs to analyze one or more samples and evaluates the lab results with regard to the goal of the RRT. This article presents a systematic literature review and investigates which purposes and which performance parameters (PP) are commonly applied in RRT of SRM. The examined literature shows that the two main purposes applied are assessment of method performance and assessment of lab performance. PP can be categorized into trueness performance parameters (TPP; assessing the deviation of a value from a reference value) and precision performance parameters (PPP; describing the variability of a data set). The main TPP identified are z score and relative deviation, the main PPP identified are standard deviation and relative standard deviation. These results offer the conclusions that RRT can be used as a bespoke method to deal with analytical effects and that the selection of PP for an RRT could be based on simplicity.DFG, 414044773, Open Access Publizieren 2021 - 2022 / Technische Universität Berli

Characterizing the Urban Mine—Challenges of Simplified Chemical Analysis of Anthropogenic Mineral Residues

Anthropogenic mineral residues are characterized by their material complexity and heterogeneity, which pose challenges to the chemical analysis of multiple elements. However, creating an urban mine knowledge database requires data using affordable and simple chemical analysis methods, providing accurate and valid results. In this study, we assess the applicability of simplified multi-element chemical analysis methods for two anthropogenic mineral waste matrices: (1) lithium-ion battery ash that was obtained from thermal pre-treatment and (2) rare earth elements (REE)-bearing iron-apatite ore from a Swedish tailing dam. For both samples, simplified methods comprising ‘inhouse’ wet-chemical analysis and energy-dispersive Xray fluorescence (ED-XRF) spectrometry were compared to the results of the developed matrix-specific validated methods. Simplified wet-chemical analyses showed significant differences when compared to the validated method, despite proven internal quality assurance, such as verification of sample homogeneity, precision, and accuracy. Matrix-specific problems, such as incomplete digestion and overlapping spectra due to similar spectral lines (ICP-OES) or element masses (ICP-MS), can result in quadruple overestimations or underestimation by half when compared to the reference value. ED-XRF analysis proved to be applicable as semi-quantitative analysis for elements with mass fractions higher than 1000 ppm and an atomic number between Z 12 and Z 50. For elements with low mass fractions, ED-XRF analysis performed poorly and showed deviations of up to 90 times the validated value. Concerning all the results, we conclude that the characterization of anthropogenic mineral residues is prone to matrix-specific interferences, which have to be addressed with additional quality assurance measures.DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität BerlinEC/H2020/641999/EU/ Prospecting Secondary raw materials in the Urban mine and Mining waste/ProSU

Characterizing the Urban Mine—Simulation-Based Optimization of Sampling Approaches for Built-in Batteries in WEEE

Comprehensive knowledge of built-in batteries in waste electrical and electronic equipment (WEEE) is required for sound and save WEEE management. However, representative sampling is challenging due to the constantly changing composition of WEEE flows and battery systems. Necessary knowledge, such as methodologically uniform procedures and recommendations for the determination of minimum sample sizes (MSS) for representative results, is missing. The direct consequences are increased sampling efforts, lack of quality-assured data, gaps in the monitoring of battery losses in complementary flows, and impeded quality control of depollution during WEEE treatment. In this study, we provide detailed data sets on built-in batteries in WEEE and propose a non-parametric approach (NPA) to determine MSS. For the pilot dataset, more than 23 Mg WEEE (6500 devices) were sampled, examined for built-in batteries, and classified according to product-specific keys (UNUkeys and BATTkeys). The results show that 21% of the devices had battery compartments, distributed over almost all UNUkeys considered and that only about every third battery was removed prior to treatment. Moreover, the characterization of battery masses (BM) and battery mass shares (BMS) using descriptive statistical analysis showed that neither product- nor battery-specific characteristics are given and that the assumption of (log-)normally distributed data is not generally applicable. Consequently, parametric approaches (PA) to determine the MSS for representative sampling are prone to be biased. The presented NPA for MSS using data-driven simulation (bootstrapping) shows its applicability despite small sample sizes and inconclusive data distribution. If consistently applied, the method presented can be used to optimize future sampling and thus reduce sampling costs and efforts while increasing data quality.EC/H2020/641999/EU/Prospecting Secondary raw materials in the Urban mine and Mining waste/ProSUMTU Berlin, Open-Access-Mittel – 202

Characterizing the Urban Mine—Challenges of Simplified Chemical Analysis of Anthropogenic Mineral Residues

Anthropogenic mineral residues are characterized by their material complexity and heterogeneity, which pose challenges to the chemical analysis of multiple elements. However, creating an urban mine knowledge database requires data using affordable and simple chemical analysis methods, providing accurate and valid results. In this study, we assess the applicability of simplified multi-element chemical analysis methods for two anthropogenic mineral waste matrices: (1) lithium-ion battery ash that was obtained from thermal pre-treatment and (2) rare earth elements (REE)-bearing iron-apatite ore from a Swedish tailing dam. For both samples, simplified methods comprising ‘in-house’ wet-chemical analysis and energy-dispersive X-ray fluorescence (ED-XRF) spectrometry were compared to the results of the developed matrix-specific validated methods. Simplified wet-chemical analyses showed significant differences when compared to the validated method, despite proven internal quality assurance, such as verification of sample homogeneity, precision, and accuracy. Matrix-specific problems, such as incomplete digestion and overlapping spectra due to similar spectral lines (ICP-OES) or element masses (ICP-MS), can result in quadruple overestimations or underestimation by half when compared to the reference value. ED-XRF analysis proved to be applicable as semi-quantitative analysis for elements with mass fractions higher than 1000 ppm and an atomic number between Z 12 and Z 50. For elements with low mass fractions, ED-XRF analysis performed poorly and showed deviations of up to 90 times the validated value. Concerning all the results, we conclude that the characterization of anthropogenic mineral residues is prone to matrix-specific interferences, which have to be addressed with additional quality assurance measures

WEEE Batteries - Sampling data

The attached data include the unit weight of more than 6000 waste electrical and electronic equipments (WEEE) and the batteries they contain. WEEE is classified according to the UNU keys (see Baldé, C.P.; Kuehr, R.; Blumenthal, K.; Gill, S.F.; Kern, M.; Micheli, P.; Magpantay, E.; Huisman, J.: E-waste statistics. Guidelines on classification, reporting, and indicators.). The WEEE batteries were divided into battery keys: LiPrim, LiRecharge, NiMH, NiCd, Pb, Zn, other, and unspecified.EC/H2020/641999/EU/Prospecting Secondary raw materials in the Urban mine and Mining waste/ProSU

Variability and Bias in Measurements of Metals Mass Fractions in Automobile Shredder Residue

The treatment of end-of-life vehicles generates large amounts of automobile shredder residue (ASR), a potential source of recycled metals. Reliable measurement methods are required to determine the composition of ASR and evaluate the resource potential. We reported on research undertaken to investigate bias and variability in the process of measuring trace metals in ASR. Two primary samples of shredder light fraction (SLF) underwent extensive physical sample preparation and chemical analysis. The samples were spiked to control random variations and systematic effects during physical sample preparation. Chemical analysis was conducted using wavelength-dispersive X-ray fluorescence spectrometry (WD-XRF), a fully validated wet-chemical analysis, and a wet-chemical analysis representing an “in-house” lab procedure. Physical sample preparation introduced deviations up to a factor of 2, likely due to preferential losses and heterogeneity. Deviations for WD-XRF measurements of elements were in the range +100%/−50%. In-house chemical analysis produced results that were in good agreement with validated results for Al, Fe and Sn, but led to biased results or high variability for Cd, Dy, La, Nd, Pb, Pd, Pt and Sb. To improve the chemical analysis of trace metals in SLF, we recommended reducing particle size to less than 0.1 mm before chemical analysis and using a larger number of repeated digestions