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Open AccessArticle

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

1
Chair of Circular Economy and Recycling Technology, Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin, Germany
2
German Environment Agency, Wörlitzer Platz 1, 06844 Dessau-Roßlau, Germany
3
Empa, Swiss Federal Laboratories for Materials Science and Technology, Particles-Biology Interactions Laboratory, CH-9014 St. Gallen, Switzerland
*
Authors to whom correspondence should be addressed.
Recycling 2020, 5(3), 19; https://doi.org/10.3390/recycling5030019
Received: 13 August 2020 / Revised: 1 September 2020 / Accepted: 2 September 2020 / Published: 4 September 2020
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. View Full-Text
Keywords: built-in batteries; WEEE; urban mine; sampling; UNUkeys; minimum sample size; data-driven simulation; bootstrapping; recycling-oriented characterization built-in batteries; WEEE; urban mine; sampling; UNUkeys; minimum sample size; data-driven simulation; bootstrapping; recycling-oriented characterization
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  • Externally hosted supplementary file 1
    Doi: 10.14279/depositonce-9338
    Link: https://depositonce.tu-berlin.de/handle/11303/10378
    Description: 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.
MDPI and ACS Style

Mählitz, P.M.; Korf, N.; Sperlich, K.; Münch, O.; Rösslein, M.; Rotter, V.S. Characterizing the Urban Mine—Simulation-Based Optimization of Sampling Approaches for Built-in Batteries in WEEE. Recycling 2020, 5, 19. https://doi.org/10.3390/recycling5030019

AMA Style

Mählitz PM, Korf N, Sperlich K, Münch O, Rösslein M, Rotter VS. Characterizing the Urban Mine—Simulation-Based Optimization of Sampling Approaches for Built-in Batteries in WEEE. Recycling. 2020; 5(3):19. https://doi.org/10.3390/recycling5030019

Chicago/Turabian Style

Mählitz, Paul M.; Korf, Nathalie; Sperlich, Kristine; Münch, Olivier; Rösslein, Matthias; Rotter, Vera S. 2020. "Characterizing the Urban Mine—Simulation-Based Optimization of Sampling Approaches for Built-in Batteries in WEEE" Recycling 5, no. 3: 19. https://doi.org/10.3390/recycling5030019

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