Interlaboratory Comparison Reveals State of the Art in Microplastic Detection and Quantification Methods - Supporting Information

S1 Supporting Information Interlaboratory comparison reveals state-of-the-art in microplastic detection and quantification methods Dmitri Ciornii1,*, Vasile-Dan Hodoroaba1,*, Nizar Benismail2, Alina Maltseva2, Juan F. Ferrer3, Jiamin Wang4, Raquel Parra5, Ronan Jézéquel6, Justine Receveur16, Dina Gabriel7, Andreas Scheitler8, Christa van Oversteeg9, Jorg Roosma10, Alex van Renesse van Duivenbode10, Tim Bulters10, Michela Zanella11, Alessandro Perini11, Federico Benetti11, Dora Mehn12, Georg Dierkes13, Michael Soll14, Takahisa Ishimura15, Marius Bednarz16, Guyu Peng17, Lars Hildebrandt18, Mathias Peters19, Seung-Kyu Kim20, Jochen Türk21, Felix Steinfeld22, Jaehak Jung23, Sanghee Hong24, Eunju Kim25, Hye-Weon Yu26, Sven Klockmann27, Christoph Krafft28, Julia Süssmann29, Shan Zou30, Alexandra ter Halle31, Andrea M. Giovannozzi32, Alessio Sacco32, Marta Fadda32, Mara Putzu32, Dong-Hoon Im33, Nontete Nhlapo34, Priscilla Carrillo-Barragán35, Natascha Schmidt36, Dorte Herzke36, Alessio Gomiero37, Adrián JaénGil37, Damien J.E. Cabanes38, Martin Doedt39, Vitor Cardoso40, Antje Schmitz41, Moritz Hawly42, Huajuan Mo43, Justine Jacquin44, Andy Mechlinski45, Gbotemi A. Adediran46, Jose Andrade47, Soledad Muniategui-Lorenzo47, Anja Ramsperger48, Martin G. J. Löder48, Christian Laforsch48, Tanja Cirkovic Velickovic49, Daniele Fabbri50, Irene Coralli50, Stefania Federici51, Barbara M. Scholz-Böttcher52, Jacopo la Nasa53, Greta Biale53, Cassandra Rauert54, Elvis D. Okoffo54, Anna Undas55, Lihui AN56, Volker Wachtendorf1, Petra Fengler1, Korinna Altmann1,* 1Bundesanstalt für Materialforschung und – prüfung (BAM), Unter den Eichen 87 and Unter den Eichen 44-46, Berlin, Germany; E-Mail: [email protected]; dan.hod[email protected]; korinn[email protected] 2Nestlé Quality Assurance Center Vittel (NQAC Vittel), 1020 Avenue Georges Clemenceau - 88804 Vittel Cedex, France 3AIMPLAS – PLASTICS TECHNOLOGY CENTRE, Gustave Eiffel 4, 46980 Paterna, Valencia, Spain 4Beijing Academy of Science and Technology (Beijing Center for Physical and Chemical Analysis), No.27, Xisanhuan (N) Rd., Haidian Dist. Beijing, Beijing, 100089 China 5CAPTOPLASTIC S.L., Calle de Génova, 11, 1ºizda, Chamberí, 28004 Madrid, Spain 6Centre of Documentation, Research and Experimentation on Accidental Water Pollution, 715 rue Alain Colas, CS 41836, 29218 Brest, France 7Currenta GmbH & Co. OHG, Chempark Leverkusen, 51368 Leverkusen, Germany 8DIL German Institute of Food Technology, Professor-von-Klitzing-Straße 7, 49610 Quakenbrück, Germany 9Rijkswaterstaat, Ministry of Infrastructure and Water Management, Zuiderwagenplein 2, 8224 AD Lelystad, The Netherlands 10TNO, Netherlands Organisation for Applied Scientific Research, Princetonlaan 6, 3584 CB Utrecht, The Netherlands 11ECSIN-European Center for the Sustainable Impact of Nanotechnology - EcamRicert SRL, C.so Stati Uniti 4, 35127 Padova, Italy 12European Commission - Joint Research Centre, via E. Fermi, 2749, 21027 Ispra VA, Italy 13Bundesanstalt für Gewässerkunde, Am Mainzer Tor 1, 56068 Koblenz, Germany 14Frontier Laboratories Europe, Bandstrasse 39B, 45359 Essen, Germany 15Frontier Laboratories Ltd. 4-16-20, Saikon, Koriyama, Fukushima, 963-8862 Japan 16Umweltbundesamt, Corrensplatz 1, 14195 Berlin, Germany 17Helmholtz Centre for Environmental Research – UFZ, Department of Environmental Analytical Chemistry, Permoserstrasse 15, 04318 Leipzig, Germany 18Helmholtz-Zentrum Hereon, Institute of Coastal Environmental Chemistry, Department for Inorganic Environmental Chemistry, Max-Planck-Straße 1, 21502, Geesthacht, Germany 19Hohenstein Laboratories GmbH & Co. KG, Schlosssteige 1, 74357 Boennigheim, Germany 20Department of Marine Science, College of Natural Sciences, Incheon National University, 119 Academy-ro, Yeonsu-gu, Incheon 22012, Republic of Korea 21Institute for Energy and Environmental Technology e.V., Bliersheimer Str. 58 - 60, 47229 Duisburg, Germany S2 22RheinMain University of Applied Sciences, Faculty of Engineering, Institute for Environmental and Process Engineering, Am Brückweg 26, 65248 Rüsselsheim, Germany 23Korea Institute of Analytical Science and Technology, SeoulSup AK Valley, Seongsuil-ro 99, Seongdong-gu, Seoul 04790, South Korea 24Korea Institute of Ocean Science & Technology, 385 Haeyang-ro, Yeongdo-gu, Busan, South Korea 25Seoul National University of Science & Technology, 232 Gongneung-ro, Nowon-gu, Seoul, South Korea 26K-water, Sintanjin-ro 200, Daedeok-gu, 34350 Daejeon, South Korea 27Labor IBEN GmbH, Am Lunedeich 157, 27572 Bremerhaven, Germany 28Leibniz Institute of Photonic Technology e.V. (IPHT), Albert-Einstein-Straße 9, 07745 Jena, Germany 29Max Rubner-Institut, Federal Research Institute of Nutrition and Food, Department of Safety and Quality of Milk and Fish Products, Hermann-Weigmann-Straße 1, 24103 Kiel, Germany 30Metrology Research Centre, National Research Council Canada, 100 Sussex Drive, Ottawa, ON K1A 0R6, Canada 31Laboratoire Softmat, Université de Toulouse, CNRS UMR 5623, Bâtiment 2R1, 118 route de Narbonne 31062 Toulouse cedex 9 France 32National Institute for Metrological Research, Strada delle Cacce, 91 10135 Torino, Italy 33Marine Environment Research Division, National Institute of Fisheries Science, Busan 46083, South Korea 34National Metrology Institute of South Africa (NMISA), Private Bag X34, Lynnwood Ridge, Pretoria, South Africa 35The Dove Marine Laboratory, Newcastle University, Newcastle upon Tyne, NE1 7RU, United Kingdom 36NILU, Hjalmar Johansens gate 14, 9007 Tromsø, Norway 37Climate and Environment dep., Norwegian Research Centre, Mekjarvik 12, 4072 Randaberg, Norway 38Laboratoire Phytocontrol - 180 rue Philippe Maupas, 30035 Nîmes, Francehytocontrol, Nîmes, France 39Plastics Institute for medium-sized businesses, Karolinenstraße 8, 58507 Lüdenscheid, Germany 40Empresa Portuguesa das Águas Livres, S.A. – EPAL, Direção de Laboratórios, 1800-031 Lisboa, Portugal 41Private Diepholz University of Economics and Technology, Am Campus 2, 49356 Diepholz, Germany 42SGS INSTITUT FRESENIUS GmbH, Königsbrücker Landstraße 161, 01109 Dresden, Germany 43SGS Testing & Control Services Singapore Pte Ltd – 30 Boon Lay Way #03-01 Singapore 609957, Singapore 44Technical center for plastics processing in France, Biopôle Clermont-Limagne, 3 Rue Emile Duclaux, 63360 Saint-Beauzire, France 45PiCA Prüfinstitut Chemische Analytik GmbH, Rudower Chaussee 29, 12489 Berlin, Germany 46United Kingdom Centre for Ecology and Hydrology, Wallingford, Oxfordshire OX10 8BB, United Kingdom 47Group of Applied Analytical Chemistry, Institute of Environmental Sciences (IUMA), Faculty of Sciences, University of A Coruña, Campus da Zapateira, 15071, A Coruña, Spain 48Animal Ecology I and BayCEER, University of Bayreuth, Universitätsstraße 30, 95445 Bayreuth, Germany 49University of Belgrade-Faculty of Chemistry, Studentski trg 16, 11000 Belgrade, Serbia 50Department of Chemistry “Giacomo Ciamician”, University of Bologna, Technopole of Rimini, via Dario Campana 71, 47922 Rimini, Italy 51University of Brescia, Department of Mechanical and Industrial Engineering & INSTM RU of Brescia, via Branze 38 25123, Brescia, Italy 52University of Oldenburg, Institute for Chemistry and Biology of the Marine Environment, Carl-von-Ossietzky-Straße 9-11, 26129 Oldenburg, Germany 53Department of Chemistry and Industrial Chemistry, University of Pisa, via G. Moruzzi 13, 56124, Pisa, Italy 54Queensland Alliance for Environmental Health Sciences (QAEHS), The University of Queensland, 20 Cornwall Street, Woolloongabba 4102, QLD, Australia 55Wageningen Food Safety Research (WFSR), part of Wageningen University & Research, 6708 WB Wageningen, The Netherlands 56State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, No.8, Dayangfang, Beiyuan,Beijing 100012, China S3 Table of contents Table S1. Overview of interlaboratory comparisons related to the analysis of microplastic…………………………….........S4 Table S2. Mass fraction (as µg polymer per mg tablet) (n=19) in the homogeneity study…………………………………….S5 Table S3. Particle number for both polymers measured with µ-FTIR (n=10)…………………………………………………S5 Table S4. Particle number for both polymers measured with µ-Raman (n=10)……………………………………………….S5 Table S5. Particle number concentration (n=20) per tablet measured by manual counting from SEM micrographs…………S5 Figure S1. Overview of participant by country………………………………………………………………………………..S6 Figure S2. Particle size distribution curves of microplastic polymers as determined with laser diffraction method…………S6 Figure S3. Production process of microplastic powder from commercial plastic granulate………………………………….S6 Figure S4. Preparation of the tablets from microplastic powder………………………………………………………………S6 Figure S5. Filtration for thermo-analytical experiments with use of a crucible………………………………………………S6 Figure S6. Normalized aged PE particle numbers (> 500 µm) per tablet derived from µ-FTIR, µ-Raman and LDIR……….S6 Figure S7. Normalized PET particle numbers (> 500 µm) per tablet derived from µ-FTIR, µ-Raman and LDIR…………..S6 Figure S8. Normalized aged PE particle numbers (100 - 500 µm) per tablet derived from µ-FTIR, µ-Raman and LDIR……S6 Figure S9. Normalized PET particle numbers (100 - 500 µm) per tablet derived from µ-FTIR, µ-Raman and LDIR………S6 Figure S10. Normalized aged PE particle numbers (50 - 100 µm) per tablet derived from µ-FTIR, µ-Raman and LDIR…..S7 Figure S11. Normalized PET particle numbers (50 - 100 µm) per tablet derived from µ-FTIR, µ-Raman and LDIR………S7 Figure S12. Normalized aged PE particle numbers (10 – 50 µm) per tablet derived from µ-Raman measurement…………S7 Figure S13. Normalized PET particle numbers (10 – 50 µm) per tablet derived from µ-Raman measurement………………S7 Figure S14. Normalized aged PE particle numbers (10 – 50 µm and 20 - 50 µm) per tablet derived from µ-FTIR, LDIR….S7 Figure S15. Normalized PET particle numbers (10 – 50 µm and 20 - 50 µm) per tablet derived from µ-FTIR and LDIR….S7 Figure S16. Normalized aged PE particle numbers (5 – 10 µm) per tablet derived from µ-Raman measurements………….S7 Figure S17. Normalized PET particle numbers (5 – 10 µm) per tablet derived from µ-Raman measurements………………S7 Table S6. Main sources of uncertainty………………………………………..………………………………………………S8 Figure S18. Particle size distribution for PET and aged PE calculated from results derived obtained from SEM……………S8 Table S7. Type of particle counting (automated vs manual)…………………………………………………………………S9 Recommendations for best practices………………………………………………………………………………………...S10 References…………………………………………………………………………………………………………………...S10 S4 Table S1. Overview of interlaboratory comparisons related to the analysis of microplastic. Parameters Polymers Particle size (µm) Matrix Methods Nr. labs Drawbacks Reference Particle number, PSD PP, HDPE, LDPE 400-5700 Seawater FTIR, µFTIR, Raman 12 Polymer identity missing, only large particles Isobe et al.1 Mass fraction PE, PET, PS, PP 145-174 Freshwater sediment Py-Gc/MS, TED-GC/MS, TGA-FTIR, TGA-MS, DSC, 16 Pristine polymers, narrow particle size range Becker et al.2 Particle number, polymer type, or particle mass PE, PVC, PMMA, PET, PS, 8-140 Ultrapure water Microscopy, µ-FTIR, µRaman spectroscopy, TED-GC/MS, SEM 17 Pristine MP, test material RSD 2685%, ultra-pure water Müller et al.3 Polymer type, particle number, polymer mass PC, PS, PP, PET, LDPE, EPS 150-300 and 2000-4000 Soda tablets Microscopy, gravimetric, ATR-FTIR, μFTIR, PyGC–MS, Raman, µRaman spectroscopy. 34 Only large particles WEPALQUASIME ME/NORM AN et al.4 Polymer type, particle number PVC, PET, PE, EPS, PS 1-500 Drinking water + gelatine FTIR, Raman 12 Munno et al.5 Polymer type, particle number, particle size PE, PS, PVC, PET 1-500 Drinking water OM, µ-FTIR, µ-Raman spectroscopy 22 Clean water as matrix De Frond et al.6 Particle number, size, mass fraction PET in water 30-200 Clean water µ-FTIR, µRaman spectroscopy, Py-GC/MS, fluorescence microscopy, TGA, LDIR, NMR, HPLC 98 Clean water as matrix European Commision7 Polymer type, polymer mass PE, PS, PVC 125-355 Soda tablets, µ-FTIR, PyGC/MS, microscopy, µ-Raman spectroscopy, LDIR 7 Narrow particle size range INOPOL/SI NOPLAST8 Polymer identity, PSD, particle number PE, PET, PS, PC, PP, PVC 50-300 Soda tablets, sediments, sand samples OM, gravimetric, ATR-FTIR, μFTIR, μFTIR-FPA, Py-GC–MS, Raman, µRaman spectroscopy, LDIR, Fluorescent microscopy, stereomicrosc opy, SPEROQT 90 EUROqCHA RM9 Polymer identity, particle count, total weight HDPE, PET, PC, PP, PVC 300-5000 Marine sediment and sea water ATR-FTIR, FTIR 5 Large MPs, few laboratories, only two methods Cadiou et al.10 S5 Table S2. Mass fraction (as µg polymer per mg tablet) (n=19) in the homogeneity study Table S3. Particle number for both polymers measured with µ-FTIR (n=10) NQAC Vittel * > 20 µm - lowest limit of confident detection for µ-FTIR Table S4. Particle number for both polymers measured with µ-Raman (n=10) NQAC Vittel Table S5. Particle number concentration (n=20) per tablet measured by manual counting from SEM micrographs PET SD RSD PE SD RSD TGA 2.2 0.3 14.1 0.9 0.1 16.0 TEDGC/MS 1.9 0.5 27.5 0.8 0.1 18.0 µ-FTIR PET (n=10) SD RSD PE (n=10) SD RSD >500 µm 0.7 1.6 228.5 3.5 4.9 140.0 100-500 µm 136.5 40.4 29.6 137.8 46.2 33.5 50-100 µm 214.3 45.8 21.3 121.5 38.2 31.4 *20-50 µm 198.4 55.5 27.9 72.9 45.5 62.4 Total 549.9 78.4 14.2 335.7 94.1 28.0 µ-Raman PET (n=10) SD RSD PE (n=10) SD RSD > 500 µm 1.0 0.8 80.0 2.2 2.3 104.5 100-500 µm 107.5 15.1 14.0 129.3 25.2 19.4 50-100 µm 265.6 38.4 14.4 210.4 82.8 39.3 20-50 µm 492.6 73.4 14.9 496.9 228.2 45.9 10-20 µm 275.2 33.2 12.0 450.9 193.1 42.8 5-10 µm 152.3 36.7 24.0 266.9 140.1 52.5 Total 1294.2 151.9 11.7 1556.6 631.2 40.5 PET (n=10) SD RSD PE (n=10) SD RSD >500 µm 0.0 0.0 0.0 0.1 0.3 244.2 100-500 µm 3.9 2.5 65.4 81.7 30.5 37.4 50-100 µm 171.5 63.2 36.8 298.9 97.8 32.7 10-50 µm 730.3 255.5 34.9 494.7 279.8 56.5 Total 905.7 295.7 32.2 876.8 357.1 40.7 S6 Figure S1. Overview of participant by country 110 100 1000 0 20 40 60 80 100 Cumulative distribution Q3(x) / % Particle size / µm 0,0 0,5 1,0 1,5 2,0 2,5 Distribution density q3* 110 100 1000 0 20 40 60 80 100 Cumulative distribution Q3(x) / % Particle size / µm 0,0 0,2 0,4 0,6 0,8 1,0 1,2 Distribution density q3* Figure S2. Particle size distribution curves of microplastic polymers as determined with laser diffraction method: a) PET and b) aged PE. Figure S3. Production process of microplastic powder from commercial plastic granulate: a) plastic granulate, b) cryo-milling, c) sieving, d) microplastic powder (1-100 µm). Figure S4. Preparation of the tablets from microplastic powder: a) homogenization, b) pressing step with press machine, c) pressed tablets (about 250 mg). Figure S5. Filtration for thermo-analytical experiments with use of a crucible. a) placing the crucible; b) MilliQ water dropping on the tablet; c) tablet rests (presumably microplastic) after completing the filtration process. Figure S6. Normalized aged PE particle numbers (> 500 µm) per tablet derived from µ-FTIR, µ-Raman and LDIR measurements. Red, green and blue bars – standard deviations of intra-laboratory results (repeatability). Figure S7. Normalized PET particle numbers (> 500 µm) per tablet derived from µ-FTIR, µ-Raman and LDIR measurements. Red, green and blue bars – standard deviations of intra-laboratory results (repeatability). Figure S8. Normalized aged PE particle numbers (100 - 500 µm) per tablet derived from µ-FTIR, µ-Raman and LDIR measurements. Red, light green and blue bars – standard deviations of intra-laboratory results (repeatability). Figure S9. Normalized PET particle numbers (100 - 500 µm) per tablet derived from µ-FTIR, µ-Raman and LDIR measurements. Red, light green and blue bars – standard deviations of intralaboratory results (repeatability). a b c d a b c a b PROLab Laboratory # 21 25 37 44 47 5456A61 7073A75 7682A63 49 50 17 84 38 1418A11 62 31 57 59 60 65 72 16 3 4 5356B7982B8373B18B26 Normalized particle nr. (%) 1500 1200 900 600 300 0 Probe: Polyethylene Merkmal: 500-1000 Statistische Methode: ISO 5725-2 Anzahl Labore in Berechnung: 40 Sollwert: 100,000 Anzahl (Referenzwert) Rel. Soll-Stdabw.: 94,8% (Standardabweichung der Labormittelwerte) Rel. Wiederhol-Stdabw. (Vr): 88,9% Toleranzbereich: -89,595 - 289,595 Anzahl (|Z-Score| <= 2,0) FTIR LDIR Raman Lab values Interlaboratory mean value Reference value (= 100%) Confidence interval µ-Raman (± 2 STD) Confidence interval µ-FTIR (± 2 STD) Normalized Polyethylene particle nr. (> 500 µm) Normalized particle nr. (%) PROLab Laboratory # 11 1418A25 37 38 44 47 50 5456A61 62 7073A75 7682A21 63 84 17 49 31 57 59 60 65 72 3 4 5356B79 8382B1618B73B26 Normalized particle nr. (%) 3500 3000 2500 2000 1500 1000 500 0 Probe: Polyethylene Terephtalate Merkmal: 500-1000 Statistische Methode: ISO 5725-2 Anzahl Labore in Berechnung: 40 Sollwert: 100,000 Anzahl (Referenzwert) Rel. Soll-Stdabw.: 119,3% (Standardabweichung der Labormittelwerte) Rel. Wiederhol-Stdabw. (Vr): 201,8% Toleranzbereich: -138,652 - 338,652 Anzahl (|Z-Score| <= 2,0) FTIR LDIR Raman Lab values Interlaboratory mean value Reference value (= 100%) Confidence interval µ-Raman (± 2 STD) Confidence interval µ-FTIR (± 2 STD) Normalized Polyethylene Terephtalate particle nr. (> 500 µm) LDIR Normalized particle nr. (%) LDIR PROLab Laboratory # 17 25 70 76 37 8456A54 44 1482A75 62 63 49 61 21 50 3873A1118A47 60 31 57 65 72 59 416 26 53 38382B7956B73B18B Normalized particle nr. (%) 500 400 300 200 100 0 Probe: Polyethylene Merkmal: 100-500 Statistische Methode: ISO 5725-2 Anzahl Labore in Berechnung: 40 Sollwert: 100,000 Anzahl (Referenzwert) Rel. Soll-Stdabw.: 45,0% (Standardabweichung der Labormittelwerte) Rel. Wiederhol-Stdabw. (Vr): 24,9% Toleranzbereich: 9,998 - 190,002 Anzahl (|Z-Score| <= 2,0) FTIR LDIR Raman Lab values Interlaboratory mean value Reference value (= 100%) Confidence interval µ-Raman (± 2 STD) Confidence interval µ-FTIR (± 2 STD) Normalized Polyethylene particle nr. (100 - 500 µm) Normalized particle nr. (%) PROLab Laboratory # 25 70 17 76 37 7556A8482A50 44 63 14 54 61 62 49 21 3818A1173A47 31 57 60 72 65 59 416 53 326 79 8356B82B18B73B Normalized particle nr. (%) 300 200 100 0 Probe: Polyethylene Terephtalate Merkmal: 100-500 Statistische Methode: ISO 5725-2 Anzahl Labore in Berechnung: 40 Sollwert: 100,000 Anzahl (Referenzwert) Rel. Soll-Stdabw.: 26,8% (Standardabweichung der Labormittelwerte) Rel. Wiederhol-Stdabw. (Vr): 14,2% Toleranzbereich: 46,335 - 153,665 Anzahl (|Z-Score| <= 2,0) FTIR LDIR Raman Lab values Interlaboratory mean value Reference value (= 100%) Confidence interval µ-Raman (± 2 STD) Confidence interval µ-FTIR (± 2 STD) Normalized Polyethylene Terephtalate particle nr. (100 - 500 µm) Normalized particle nr. (%) a b c 36 labs 36 labs 36 labs 36 labs S7 Figure S10. Normalized aged PE particle numbers (50 - 100 µm) per tablet derived from µ-FTIR, µ-Raman and LDIR measurements. Red, light green and blue bars – standard deviations of intra-laboratory results (repeatability). Figure S11. Normalized PET particle numbers (50 - 100 µm) per tablet derived from µ-FTIR, µ-Raman and LDIR measurements. Red, light green and blue bars – standard deviations of intralaboratory results (repeatability). Figure S12. Normalized aged PE particle numbers (10 – 50 µm) per tablet derived from µ-Raman measurements. Blue bars – standard deviations of intra-laboratory results (repeatability). Figure S13. Normalized PET particle numbers (10 – 50 µm) per tablet derived from µ-Raman measurements. Blue bars – standard deviations of intra-laboratory results (repeatability). Figure S14. Normalized aged PE particle numbers (10 – 50 µm and 20 - 50 µm) per tablet derived from µ-FTIR and LDIR measurements. Red, light green, dark green and orange bars – standard deviations of intra-laboratory results (repeatability). Figure S15. Normalized PET particle numbers (10 – 50 µm and 20 - 50 µm) per tablet derived from µ-FTIR and LDIR measurements. Red, light green, dark green and orange bars – standard deviations of intra-laboratory results (repeatability). Figure S16. Normalized aged PE particle numbers (5 – 10 µm) per tablet derived from µ-Raman measurements. Blue bars – standard deviations of intra-laboratory results (repeatability). Figure S17. Normalized PET particle numbers (5 – 10 µm) per tablet derived from µ-Raman measurements. Blue bars – standard deviations of intra-laboratory results (repeatability). PROLab Laboratory # 17 70 84 56A 37 76 14 75 44 54 11 62 73A82A 49 25 38 63 50 21 18A47 61 60 31 72 57 59 65 416 53 26 73B 83 79 356B82B18B Normalized particle nr. (%) 1000 800 600 400 200 0 Probe: Polyethylene Merkmal: 50-100 Statistische Methode: ISO 5725-2 Anzahl Labore in Berechnung: 40 Sollwert: 100,000 Anzahl (Referenzwert) Rel. Soll-Stdabw.: 111,9% (Standardabweichung der Labormittelwerte) Rel. Wiederhol-Stdabw. (Vr): 54,1% Toleranzbereich: -123,854 - 323,854 Anzahl (|Z-Score| <= 2,0) FTIR LDIR Raman Lab values Interlaboratory mean value Reference value (= 100%) Confidence interval µ-Raman (± 2 STD) Confidence interval µ-FTIR (± 2 STD) Normalized Polyethylene particle nr. (50 - 100 µm) Normalized particle nr. (%) PROLab Laboratory # 17 70 84 37 56A 44 76 14 75 62 11 82A 25 54 50 73A 38 49 63 18A 21 61 47 31 57 60 72 65 59 416 53 56B 26 83 379 73B82B18B Normalized particle nr. (%) 600 500 400 300 200 100 0 Probe: Polyethylene Terephtalate Merkmal: 50-100 Statistische Methode: ISO 5725-2 Anzahl Labore in Berechnung: 40 Sollwert: 100,000 Anzahl (Referenzwert) Rel. Soll-Stdabw.: 54,8% (Standardabweichung der Labormittelwerte) Rel. Wiederhol-Stdabw. (Vr): 30,8% Toleranzbereich: -9,660 - 209,660 Anzahl (|Z-Score| <= 2,0) FTIR LDIR Raman Lab values Interlaboratory mean value Reference value (= 100%) Confidence interval µ-Raman (± 2 STD) Confidence interval µ-FTIR (± 2 STD) Normalized Polyethylene Terephtalate particle nr. (50 - 100 µm) Normalized particle nr. (%) PROLab Laboratory # 26 416 73B 53 83 79 18B 82B 56B 3 Normalized particle nr. (%) 800 700 600 500 400 300 200 100 0 Probe: Polyethylene Merkmal: 10-50 Statistische Methode: ISO 5725-2 Anzahl Labore in Berechnung: 11 Sollwert: 100,000 Anzahl (Referenzwert) Rel. Soll-Stdabw.: 116,6% (Standardabweichung der Labormittelwerte) Rel. Wiederhol-Stdabw. (Vr): 71,5% Toleranzbereich: -133,250 - 333,250 Anzahl (|Z-Score| <= 2,0) Raman Lab values Interlaboratory mean value Reference value (= 100%) Confidence interval (± 2 STD) Normalized Polyethylene particle nr. (10 - 50 µm) Normalized particle nr. (%) PROLab Laboratory # 26 416 79 53 56B 73B 82B 83 18B 3 Normalized particle nr. (%) 400 300 200 100 0 Probe: Polyethylene Terephtalate Merkmal: 10-50 Statistische Methode: ISO 5725-2 Anzahl Labore in Berechnung: 11 Sollwert: 100,000 Anzahl (Referenzwert) Rel. Soll-Stdabw.: 45,2% (Standardabweichung der Labormittelwerte) Rel. Wiederhol-Stdabw. (Vr): 33,1% Toleranzbereich: 9,523 - 190,477 Anzahl (|Z-Score| <= 2,0) Raman Lab values Interlaboratory mean value Reference value (= 100%) Confidence interval (± 2 STD) Normalized Polyethylene Terephtalate particle nr. (10 - 50 µm) Normalized particle nr. (%) PROLab Laboratory # 11 44 75 37 70 14 56A 38 49 50 62 82A 47 18A 25 61 60 59 65 57 17 73A 54 63 76 21 72 31 Normalized particle nr. (%) 3000 2500 2000 1500 1000 500 0 Probe: Polyethylene Merkmal: 10-50 Statistische Methode: ISO 5725-2 Anzahl Labore in Berechnung: 28 Sollwert: 100,000 Anzahl (Referenzwert) Rel. Soll-Stdabw.: 308,3% (Standardabweichung der Labormittelwerte) Rel. Wiederhol-Stdabw. (Vr): 164,6% Toleranzbereich: -516,583 - 716,583 Anzahl (|Z-Score| <= 2,0) FTIR FTIR20 LDIR LDIR20 Lab values Interlaboratory mean value reference value (= 100%) Confidence interval µ-FTIR20 (± 2 STD) Normalized Polyethylene particle nr. (10 - 50 µm) Normalized particle nr. (%) PROLab Laboratory # 11 44 37 70 75 56A 38 14 50 47 49 82A 62 25 18A 61 60 57 59 65 17 73A 54 21 76 63 31 72 Normalized particle nr. (%) 1200 1000 800 600 400 200 0 Probe: Polyethylene Terephtalate Merkmal: 10-50 Statistische Methode: ISO 5725-2 Anzahl Labore in Berechnung: 28 Sollwert: 100,000 Anzahl (Referenzwert) Rel. Soll-Stdabw.: 132,5% (Standardabweichung der Labormittelwerte) Rel. Wiederhol-Stdabw. (Vr): 50,9% Toleranzbereich: -164,984 - 364,984 Anzahl (|Z-Score| <= 2,0) FTIR FTIR20 LDIR LDIR20 Lab values Interlaboratory mean value reference value (= 100%) Confidence interval µ-FTIR20 (± 2 STD) Normalized Polyethylene Terephtalate particle nr. (10 - 50 µm) Normalized particle nr. (%) PROLab Laboratory # 53 79 82B 56B 73B 318B Normalized particle nr. (%) 500 400 300 200 100 0 Probe: Polyethylene Merkmal: 5-10 Statistische Methode: ISO 5725-2 Anzahl Labore in Berechnung: 7 Sollwert: 100,000 Anzahl (Referenzwert) Rel. Soll-Stdabw.: 18,4% (Standardabweichung der Labormittelwerte) Rel. Wiederhol-Stdabw. (Vr): 26,7% Toleranzbereich: 63,266 - 136,734 Anzahl (|Z-Score| <= 2,0) Raman Lab values Interlaboratory mean value Reference value (= 100%) Confidence interval µ-Raman (± 2 STD) Confidence interval µ-FTIR (± 2 STD) Normalized Polyethylene particle nr. (5 - 10 µm) Normalized particle nr. (%) PROLab Laboratory # 382B 53 56B 73B 79 18B Normalized particle nr. (%) 800 700 600 500 400 300 200 100 0 Probe: Polyethylene Terephtalate Merkmal: 5-10 Statistische Methode: ISO 5725-2 Anzahl Labore in Berechnung: 7 Sollwert: 100,000 Anzahl (Referenzwert) Rel. Soll-Stdabw.: 65,7% (Standardabweichung der Labormittelwerte) Rel. Wiederhol-Stdabw. (Vr): 65,0% Toleranzbereich: -31,402 - 231,402 Anzahl (|Z-Score| <= 2,0) Raman Lab values Interlaboratory mean value Reference value (= 100%) Confidence interval µ-Raman (± 2 STD) Confidence interval µ-FTIR (± 2 STD) Normalized Polyethylene Terephtalate particle nr. (5 - 10 µm) Normalized particle nr. (%) 36 labs 36 labs 11 labs 11 labs 28 labs 28 labs 7 labs 7 labs S8 Table S6. Main sources of uncertainty 5-10 10-50 50-100 100-500 > 500 0 500 1000 1500 2000 2500 SEM µ-FTIR Raman LDIR Mean particle number Size fraction / µm PE Particle number per size class by methods 550 50010 100 1000 0,0 0,5 1,0 1,5 2,0 2,5 Distribution Density*3 Particle size / µm Size distribution by laser diffraction 5-10 10-50 50-100 100-500 > 500 0 200 400 600 800 1000 1200 SEM µ-FTIR Raman LDIR Mean particle number Size fraction / µm PET Particle number per size class by methods 50 50010 100 1000 0,0 0,5 1,0 1,5 2,0 2,5 3,0 Distribution Density*3 Particle size / µm Size distribution by laser diffraction Figure S18. Particle size distribution for aged PE and PET calculated from results derived from SEM, µ-Raman, µ-FTIR, LDIR measurements. Source Uncertainty Comment Sample homogeneity High MP content: RSD particle number = 12-40 %, RSD mass fraction = 18-27% Tablet mass Low Tablet mass variation ±5 mg, corresponding to ±2% Sample preparation (Filtration) High Loss of particles during filtration: assumption of minus 10-30% Method sensitivity Low-Middle Determines whether the smallest particles are counted or not Instrument calibration Middle-High Calibration plays a role in trueness/bias of the measurement result. Not provided by the labs Spectral library used Middle There may be differences in matches between a curated vs laboratory generated library Measurement repeatability Middle-High The repeatability of the results based on 6 samples of the same material Instrument measurement uncertainty Low Measurement uncertainty of the measurand measured with the instrument at best calibration and best settings Instrumental settings Middle-High Software parameter settings, like threshold size, threshold to positively identify spectra by comparison against spectral databases, region of interest, aperture, focus, acquisition time, number of pixels, settings stability during measurement, etc. Background (laboratory and blank samples) Low Presence of MPs even in blank samples (negative control). Estimated <1-6%. Laboratory background contamination not assessed Operator’s effect Middle-High Untraceable. Explains how accurate the sample is handled and how is the measurement carried out Extrapolation of results Middle-High Analysing only X% of the filter surface (sometimes as low as just 1% of the filter) and extrapolating the result to 100% could alter the particle number. Accuracy of the counting software Middle When using automated particle counting, exact uncertainty unknown, particularly for agglomerated and/or small particles with complex shapes S9 Table S7. Type of particle counting (automated vs manual) Lab Nr. Method Automated Semi-automated Manually 56 FTIR YES 21 FTIR YES 18 FTIR YES 17 FTIR YES 50 FTIR YES 73 FTIR YES 3 FTIR YES 38 FTIR YES 14 FTIR YES 82 FTIR YES 75 FTIR YES 54 FTIR YES 47 FTIR YES 44 FTIR YES 63 FTIR YES 27 FTIR YES 49 FTIR YES 84 FTIR YES 31 LDIR YES 59 LDIR YES 72 LDIR YES 56 Raman YES 18 Raman YES 83 Raman YES 73 Raman YES 3 Raman YES 16 Raman YES 26 Raman YES 82 Raman YES