Applied Science, Faculty of
Mining Engineering, Keevil Institute of
DSpace
UBCV
Kumar, Amit
Doctor of Philosophy - PhD
University of British Columbia
Electrical and electronic equipment has become an integral part of modern society. With the current technological advances, the life span of this equipment has been shrinking, leading to waste generation and issues related to end-of-life waste disposal. The circular economy model has been proposed to address the growing volume of e-waste. The model encourages reduction and reuse to decrease waste generation and encourages recycling to promote efficient natural resource usage. One of the challenges with promoting the circular economy model for e-waste is the insufficiency or absence of the recycling process for the non-metal fraction. The low value associated with the non-metal fraction increases its probability of being disposed of in landfills. This research explored the possibility of utilizing low-cost physical separation processes common in the mineral processing industry to recycle the non-metal fraction obtained from waste printed circuit board. The study showed that a density-based separation could theoretically be used to separate organic, inorganic, and residual metal streams from the non-metal fraction, thus increasing its reusability. The float-sink test and derived washability curves and washability indices showed that a conceptual three-product gravity separation process could produce an organic fraction with 47% yield at 86% organic content and a reject stream with a 35% yield at 72% fiberglass content. A gravity separation-based flowsheet was proposed for the recycling of non-metal fraction, and the potential applications of the recycled products were identified. Further test work at the pilot level would be required to estimate the process efficiency, related costs and understand the product characteristics for their proper application. This research also provided a simplified approach for determining the loss on ignition that can be used to estimate the separation efficiency. It also showed the applicability of advanced techniques such as inverse gas chromatography and micro-FTIR for analyzing the surface heterogeneity and polymeric identification of non-metal fraction components. Overall, the research used an interdisciplinary approach to provide a potential solution for the non-metal fraction to the recycling industry using tools and processes used in the coal and mineral processing industry.
CHARACTERIZATION OF NON-METAL FRACTION OF WASTE PRINTED CIRCUIT BOARDS TO PROMOTE RECYCLING by Amit Kumar B.Tech., Indian School of Mines, 2011 M.Tech., Indian School of Mines, 2011 M.A.Sc., University of British Columbia, 2014 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Mining Engineering) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) November 2020 © Amit Kumar, 2020 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: CHARACTERIZATION OF NON-METAL FRACTION OF WASTE PRINTED CIRCUIT BOARDS TO PROMOTE RECYCLING submitted by Amit Kumar in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Mining Engineering Examining Committee: Dr. Maria Holuszko, Assistant Professor, Mining Engineering Supervisor Dr. Marek Pawlik, Professor, Mining Engineering Supervisory Committee Member Dr. Bern Klein, Professor, Mining Engineering Supervisory Committee Member Dr. W Scott Dunbar, Professor, Mining Engineering University Examiner Dr. Tom Troczynski, Professor, Materials Engineering University Examiner iii Abstract Electrical and electronic equipment has become an integral part of modern society. With the current technological advances, the life span of this equipment has been shrinking, leading to waste generation and issues related to end-of-life waste disposal. The circular economy model has been proposed to address the growing volume of e-waste. The model encourages reduction and reuse to decrease waste generation and encourages recycling to promote efficient natural resource usage. One of the challenges with promoting the circular economy model for e-waste is the insufficiency or absence of the recycling process for the non-metal fraction. The low value associated with the non-metal fraction increases its probability of being disposed of in landfills. This research explored the possibility of utilizing low-cost physical separation processes common in the mineral processing industry to recycle the non-metal fraction obtained from waste printed circuit board. The study showed that a density-based separation could theoretically be used to separate organic, inorganic, and residual metal streams from the non-metal fraction, thus increasing its reusability. The float-sink test and derived washability curves and washability indices showed that a conceptual three-product gravity separation process could produce an organic fraction with 47% yield at 86% organic content and a reject stream with a 35% yield at 72% fiberglass content. A gravity separation-based flowsheet was proposed for the recycling of non-metal fraction, and the potential applications of the recycled products were identified. Further test work at the pilot level would be required to estimate the process efficiency, related costs and understand the product characteristics for their proper application. iv This research also provided a simplified approach for determining the loss on ignition that can be used to estimate the separation efficiency. It also showed the applicability of advanced techniques such as inverse gas chromatography and micro-FTIR for analyzing the surface heterogeneity and polymeric identification of non-metal fraction components. Overall, the research used an interdisciplinary approach to provide a potential solution for the non-metal fraction to the recycling industry using tools and processes used in the coal and mineral processing industry. v Lay summary This research studied e-waste recycling with a focus on the possibility of recycling low-value non-metal fraction. A conceptual flowsheet able to separate various components from the rejects of waste printed circuit boards recycling is proposed along with the theoretical process outputs. If adopted, the increased e-waste collection, combined with the recovery of the non-metal fraction, would reduce the disposal of e-waste and, in turn, would promote the circular economy. vi Preface I was responsible for designing and conducting the experiments and analyzing the data. The data obtained from this research has been published in several journal papers, as indicated below. The results from this research were also presented at two conferences. These papers were later published in a refereed journal. I was responsible for designing the experimental plan, the data collection and analysis, and the manuscript preparation. Dr. Maria Holuszko and Travis Janke from Ronin8 Technologies Ltd. provided inputs regarding data analysis and editing assistance for the preparation of the manuscript. Dr. Marek Pawlik and Dr. Bern Klein provided their inputs for the thesis, as appropriate for the supervisory committee members. The publications are as follow: Published papers in refereed journals: 1. Kumar A., Holuszko M., Espinosa D. C. R. (2017). E-waste: An overview on generation, collection, legislation and recycling practices. Resources, Conservation and Recycling, Volume 122, Pages 32-42, DOI: 10.1016/j.resconrec.2017.01.018. I was responsible for data collection, analysis and writing the manuscript. Dr. Holuszko and Dr. Espinosa reviewed the manuscript and assisted with manuscript proofreading. 2. Kumar A., Holuszko M. E., Janke T. (2018). Characterization of the non-metal fraction of the processed waste printed circuit boards. Waste Management, Volume 75, Pages 94-102, DOI: 10.1016/j.resconrec.2017.01.018. I was responsible for literature review, sample collection, test work, data analysis and manuscript composition. Dr. Holuszko and Mr. Janke reviewed the manuscript and assisted with manuscript proofreading. Mr. Jake also assisted with test and data review. vii 3. Kumar A., Holuszko M. E., Janke T. (2018). Separating Inorganics from the Non-metal Fraction of the Processed Waste PCBs Using Heavy Liquid Separation. International Journal of Waste Resources, Volume 8, Issue 4, DOI: 10.4172/2252-5211.1000355. I was responsible for literature review, sample collection, test work, data analysis and manuscript composition. Dr. Holuszko and Mr. Janke reviewed the manuscript and assisted with manuscript proofreading. 4. Kumar A., Kumar V. K., Holuszko M. E., Janke T. (2018). Improving the Energy Concentration in Waste Printed Circuit Boards Using Gravity Separation. Recycling, Volume 3, Issue 21, DOI: 10.3390/recycling3020021. I was responsible for literature review, sample collection, test work, data analysis and manuscript composition. Mr. Kumar V. K. assisted with the test work. Dr. Holuszko and Mr. Janke reviewed the manuscript and assisted with manuscript proofreading. 5. Kumar A., Holuszko M., Janke T. (2020). Examining the surface properties of waste printed circuit boards rejects using inverse gas chromatography. Resources, Conservation and Recycling, Volume 163, DOI: 10.1016/j.resconrec.2020.105093. I was responsible for literature review, sample collection, test work, data analysis and manuscript composition. Dr. Holuszko and Mr. Janke reviewed the manuscript and assisted with manuscript proofreading. 6. Kumar A., Holuszko M., Janke T. (2020). Determination of loss on ignition test conditions for non-metal fraction from processed waste printed circuit boards. Resources, Conservation and Recycling, Volume 163, DOI: 10.1016/j.resconrec.2020.105105. I was responsible for literature review, sample collection, test work, data analysis and manuscript composition. Dr. Holuszko and Mr. Janke reviewed the manuscript and assisted with manuscript proofreading. 7. Kumar A., Holuszko M., Janke T. (2020 Accepted). Analysis of rejects from waste printed circuit board processing as an alternative fuel for the cement industry. Waste Management & Research. I was responsible for literature review, sample collection, test work, data analysis and viii manuscript composition. Dr. Holuszko and Mr. Janke reviewed the manuscript and assisted with manuscript proofreading. Conference papers: 8. Kumar A., Kumar V., Holuszko M., Janke T. (2018). Recycling of the non-metal fraction from the electronic waste to achieve zero waste scenario for sustainable society, Canada-Korea Conference of Science & Technology, Vancouver, Canada. I was the presenter and was responsible for sample collection, test work, data analysis and presentation preparation. Mr. Kumar V., Dr. Holuszko and Mr. Janke reviewed the presentation. 9. Kumar A., Kumar V., Holuszko M., Janke T. (2018). Energy recovery and utilization from waste printed circuit boards, 5th International Conference on Recycling and Waste Management, London, UK. I was responsible for sample collection, test work, data analysis and presentation preparation. Mr. Kumar V., Dr. Holuszko and Mr. Janke reviewed the presentation. Mr. Kumar V. was the presenter in the conference. Journal articles under review: 10. Kumar A., Holuszko M., Janke T. (submitted). Assessing the applicability of gravity separation for recycling of non-metal fraction from waste printed circuit board. I was responsible for literature review, sample collection, test work, data analysis and manuscript composition. Dr. Holuszko and Mr. Janke reviewed the manuscript and assisted with manuscript proofreading. A total of seven papers were published in refereed journals. Two papers were presented at conferences, and one paper is under review for publication. ix Table of contents Abstract ......................................................................................................................................... iii Lay summary ..................................................................................................................................v Preface ........................................................................................................................................... vi Table of contents .......................................................................................................................... ix List of tables..................................................................................................................................xv List of figures ............................................................................................................................. xvii List of abbreviations ................................................................................................................ xxiii Acknowledgments .................................................................................................................... xxvi Dedication ................................................................................................................................ xxvii Chapter 1: Introduction ................................................................................................................1 1.1 Background ..................................................................................................................... 1 1.2 Problem statement ........................................................................................................... 3 1.3 Research objectives ......................................................................................................... 4 1.4 Thesis outline .................................................................................................................. 6 Chapter 2: Electronic waste – A literature review .....................................................................9 2.1 E-waste definition ........................................................................................................... 9 2.2 Lifespan of electronic products ..................................................................................... 11 x 2.3 E-waste generation statistics ......................................................................................... 13 2.4 Circular economy .......................................................................................................... 19 2.5 Benefits of e-waste recycling ........................................................................................ 20 2.5.1 Economic and employment opportunities ................................................................ 21 2.5.2 Environmental protection and public health ............................................................. 25 2.6 Printed circuit boards .................................................................................................... 29 2.6.1 PCB types and composition ...................................................................................... 30 2.7 Recycling techniques .................................................................................................... 34 2.7.1 Pre-processing ........................................................................................................... 34 2.7.2 End-processing .......................................................................................................... 37 2.8 Non-metal fraction ........................................................................................................ 40 2.8.1 Non-metal fraction composition ............................................................................... 40 2.8.2 Recycling of non-metal fraction ............................................................................... 43 2.8.3 Physical separation processes ................................................................................... 45 2.9 Loss on ignition............................................................................................................. 57 2.10 Summary ....................................................................................................................... 59 Chapter 3: Characterization of NMF from processed waste PCB ..........................................61 3.1 Introduction ................................................................................................................... 61 xi 3.2 Methodology ................................................................................................................. 62 3.2.1 Non-metal fraction sample ........................................................................................ 63 3.2.2 Test procedures ......................................................................................................... 64 3.3 Results and discussion .................................................................................................. 68 3.3.1 Economic benefits ..................................................................................................... 72 3.3.2 Environmental protection and public health ............................................................. 79 3.4 Summary ....................................................................................................................... 86 Chapter 4: Determination of loss on ignition test conditions for NMF ..................................88 4.1 Introduction ................................................................................................................... 88 4.2 Methodology ................................................................................................................. 89 4.2.1 Non-metal fraction sample ........................................................................................ 89 4.2.2 Loss on ignition test .................................................................................................. 90 4.2.3 Thermogravimetric analysis...................................................................................... 90 4.3 Results and discussion .................................................................................................. 91 4.4 Summary ..................................................................................................................... 103 Chapter 5: Selection of physical separation process for NMF recycling ..............................104 5.1 Introduction ................................................................................................................. 104 5.2 Methodology ............................................................................................................... 105 xii 5.2.1 Non-metal fraction sample ...................................................................................... 105 5.2.2 Size classification assessment ................................................................................. 105 5.2.3 Float-sink test for assessing gravity separation ...................................................... 105 5.2.4 IGC test for studying surface properties relevant to flotation ................................. 107 5.3 Results and discussion ................................................................................................ 110 5.3.1 Size classification.................................................................................................... 110 5.3.2 Gravity separation ................................................................................................... 113 5.3.3 Froth flotation ......................................................................................................... 117 5.4 Summary ..................................................................................................................... 130 Chapter 6: Washability analysis of NMF for assessing gravity separation ..........................132 6.1 Introduction ................................................................................................................. 132 6.2 Methodology ............................................................................................................... 133 6.3 Results and discussion ................................................................................................ 134 6.3.1 Washability curves .................................................................................................. 134 6.3.2 Washability indices ................................................................................................. 137 6.4 Gravity separation circuit design consideration .......................................................... 147 6.4.1 Fiberglass content analysis ..................................................................................... 156 6.4.2 Metal content analysis............................................................................................. 158 xiii 6.4.3 Thermogravimetric analysis.................................................................................... 166 6.4.4 Scanning electron microscope (SEM) .................................................................... 170 6.5 Recommended flowsheet for NMF recycling ............................................................. 175 6.6 Potential candidates for gravity separation ................................................................. 177 6.7 Potential application of recycled components ............................................................ 180 6.7.1 Organic materials .................................................................................................... 180 6.7.2 Inorganic materials.................................................................................................. 188 6.8 Summary ..................................................................................................................... 191 Chapter 7: Effect of the sample variability .............................................................................193 7.1 Introduction ................................................................................................................. 193 7.2 Methodology ............................................................................................................... 194 7.2.1 Non-metal fraction sample ...................................................................................... 194 7.2.2 Methodology ........................................................................................................... 195 7.3 Results and discussion ................................................................................................ 196 7.3.1 Sample variation ..................................................................................................... 196 7.3.2 Recycling process outputs....................................................................................... 199 7.4 Summary ..................................................................................................................... 203 Chapter 8: Conclusions and recommendations ......................................................................204 xiv 8.1 Main research findings ................................................................................................ 204 8.2 Recommendations for future research ........................................................................ 206 Chapter 9: Claims of original contributions and benefits of the research ...........................208 9.1 Summary ..................................................................................................................... 210 9.2 Benefits of the research ............................................................................................... 212 References ...................................................................................................................................213 Appendices ..................................................................................................................................255 Appendix A - E-waste generation statistics ............................................................................ 255 Appendix B - NMF characterization data ............................................................................... 257 Appendix C - Loss on ignition test data.................................................................................. 260 Appendix D - Gravity separation data .................................................................................... 269 Appendix E - IGC test data ..................................................................................................... 270 Appendix F - Washability data ............................................................................................... 273 Appendix G - Data for sample variation ................................................................................. 277 Appendix H - Electronic waste management in Canada ........................................................ 279 Appendix I - Short details of experimental methodologies .................................................... 323 xv List of tables Table 2-1: Estimated lifespan of EEE ........................................................................................... 11 Table 2-2: Average metal content in various waste EEE and run-of-mine ore ............................ 23 Table 2-3: Concentration of typical pollutants in e-waste ............................................................ 26 Table 2-4: Carbon footprint reduction from recycled metal production....................................... 27 Table 2-5: Energy savings between virgin and recycled materials production ............................ 28 Table 2-6: Description of most common types of PCB ................................................................ 32 Table 2-7: Metal concentration in waste PCB .............................................................................. 33 Table 2-8: Density of various components of the non-metal fraction .......................................... 47 Table 2-9: ASTM standards related to the LOI test or equivalent for different materials ............ 58 Table 2-10: Methods used for organic content determination by various researchers ................. 59 Table 3-1: 80% and 50% passing size for as-received NMF obtained from screening test ......... 71 Table 3-2: Amount of fiberglass locked in e-waste ...................................................................... 79 Table 3-3: TCLP test results for studied NMF ............................................................................. 81 Table 3-4: PBDEs concentration in studied NMF ........................................................................ 83 Table 3-5: PCBs concentration in studied NMF ........................................................................... 84 Table 3-6: PCDD/Fs concentration in studied NMF .................................................................... 85 Table 5-1: IGC test conditions .................................................................................................... 108 xvi Table 5-2: Band assignment for FTIR spectra for identified polymers ...................................... 129 Table 6-1: Comparison of washability indices for coal and non-metal fraction sample ............ 146 Table 6-2: Two-product separation at 1.8 g/cm3 ........................................................................ 154 Table 6-3: Three-product separation at 1.8 and 2.0 g/cm3 .......................................................... 155 Table 6-4: Properties of alternative fuels and NMF organic stream ........................................... 182 Table 6-5: Heating values of various alternative fuels and studied NMF .................................. 184 Table 6-6: Chemical composition of metal oxides of NMF concentrate and coal ash ............... 185 Table 6-7: NMF feed and product characteristics of different studies ....................................... 187 Table 6-8: Feed composition before pyrolysis for the preparation of activated carbon ............. 188 Table 6-9: Chemical composition of NMF inorganic stream and e-glass .................................. 191 Table 7-1: Process outputs for three-product separation at 1.8 and 2.0 g/cm3 ........................... 201 Table 7-2: Process outputs to obtain same inorganic content products for Sample 1 and 2 ....... 202 Table 9-1: Summary of key objectives, methodologies, and novel contributions ...................... 211 xvii List of figures Figure 1-1: Simplified flow of electrical and electronic equipment ............................................... 2 Figure 1-2: Links between core research chapters .......................................................................... 8 Figure 2-1: Discard probability of various EEE over their lifetime ............................................. 13 Figure 2-2: Global e-waste generation trend ................................................................................ 14 Figure 2-3: Total waste generation in various e-waste categories ................................................ 15 Figure 2-4: Total e-waste generated by different regions ............................................................. 16 Figure 2-5: E-waste generated per capita in the world ................................................................. 17 Figure 2-6: E-waste generated per capita with respect to the PPP and population....................... 18 Figure 2-7: Estimated value of metals and materials present in e-waste ...................................... 22 Figure 3-1: Process flowsheet at Ronin8 Technologies Limited .................................................. 64 Figure 3-2: Oven-dried NMF used for subsequent tests ............................................................... 65 Figure 3-3: Particle size distribution of as-received dried NMF .................................................. 70 Figure 3-4: Percent weight distributions for as-received NMF in different size fractions ........... 70 Figure 3-5: Particle size data fitted to Rosin-Rammler distribution function ............................... 72 Figure 3-6: Total metal content and its distribution in various NMF size fractions ..................... 73 Figure 3-7: Concentration and distribution of Al, Sb and Ca in NMF size fractions ................... 75 Figure 3-8: Concentration and distribution of Cu, Fe and Pb in NMF size fractions ................... 75 xviii Figure 3-9: Concentration and distribution of Mn, Ni and Sn in NMF size fractions .................. 76 Figure 3-10: Concentration and distribution of Zn in NMF size fractions ................................... 76 Figure 3-11: Fiberglass content in various NMF size fractions .................................................... 78 Figure 4-1: Flow chart of sample preparation for LOI test standardization ................................. 89 Figure 4-2: LOI test results for NMF feed at varying temperature and duration ......................... 92 Figure 4-3: LOI test results for -1180+850 µm at varying temperature and duration .................. 93 Figure 4-4: LOI test results for -600+425 µm at varying temperature and duration .................... 94 Figure 4-5: TGA test results on NMF feed at varying temperature .............................................. 95 Figure 4-6: TGA test results for -1180+850 µm at varying temperature ...................................... 96 Figure 4-7: TGA test results for -600+425 µm at varying temperature ........................................ 96 Figure 4-8: LOI test results on different samples at varying sample mass ................................... 98 Figure 4-9: LOI test results for different size fraction .................................................................. 99 Figure 4-10: TGA test results on different size fraction ............................................................. 100 Figure 4-11: Derivative thermogravimetric curves for various size fractions ............................ 102 Figure 5-1: NicoletTM iS50 FTIR spectrometer paired with a NicoletTM ContinuumTM infrared microscope .................................................................................................................................. 110 Figure 5-2: Loss on ignition and distribution of organic materials in various size fraction ....... 112 Figure 5-3: Loss on ignition-recovery-yield curve based on size classification ......................... 113 xix Figure 5-4: Percent yield at different specific gravities for tested size fractions ........................ 114 Figure 5-5: LOI values of different specific gravity products for various size fractions ........... 116 Figure 5-6: Surface area of different particle size of as received NMF ...................................... 118 Figure 5-7: Surface energy, work of adhesion, and hydrophilicity profile of – 1180 + 600 µm 119 Figure 5-8: Surface energy, work of adhesion, and hydrophilicity profile of – 600 + 300 µm .. 120 Figure 5-9: Surface energy, work of adhesion, and hydrophilicity profile of – 300 + 150 µm .. 120 Figure 5-10: Surface energy, work of adhesion, and hydrophilicity profile of – 150 + 75 µm .. 121 Figure 5-11: Surface energy, work of adhesion, and hydrophilicity profile of – 75 µm ............ 121 Figure 5-12: SEM micrographs for + 500 µm sample ................................................................ 123 Figure 5-13: SEM micrographs of + 500 µm fiberglass bundles ............................................... 124 Figure 5-14: SEM micrographs for - 500 µm ............................................................................. 125 Figure 5-15: SEM micrographs for - 500 µm fiberglass bundles and individual strands ........... 125 Figure 5-16: FTIR spectra of various polymers obtained from micro-FTIR study .................... 127 Figure 6-1: Washability plots for -1180 + 600 µm ..................................................................... 135 Figure 6-2: Washability plots for -600 + 300 µm ....................................................................... 135 Figure 6-3: Washability plots for -300 + 150 µm ....................................................................... 136 Figure 6-4: Washability plots for -150 + 75 µm ......................................................................... 136 Figure 6-5: Washability plots for -75 µm ................................................................................... 137 xx Figure 6-6: Degree of washing of different size fraction against the separation SG .................. 138 Figure 6-7: Washability number for different size fraction at optimum separation density ....... 139 Figure 6-8: Recovery of organic and inorganic materials for -1180 + 600 µm .......................... 140 Figure 6-9: Recovery of organic and inorganic materials for -600 + 300 µm ............................ 141 Figure 6-10: Recovery of organic and inorganic materials for -300 + 150 µm .......................... 141 Figure 6-11: Recovery of organic and inorganic materials for -150 + 75 µm ............................ 142 Figure 6-12: Recovery of organic and inorganic materials for -75 µm ...................................... 142 Figure 6-13: NGM index values plotted against specific gravity ............................................... 144 Figure 6-14: Float and sink products at various density fraction for – 1180 + 600 µm ............. 148 Figure 6-15: Float and sink products at various density fraction for – 600 + 300 µm ............... 149 Figure 6-16: Float and sink products at various density fraction for – 300 + 150 µm ............... 150 Figure 6-17: Float and sink products at various density fraction for – 150 + 75 µm ................. 151 Figure 6-18: Float and sink products at various density fraction for – 75 µm ........................... 152 Figure 6-19: Fiberglass concentration and recoveries in various SG ranges for + 500 µm ....... 157 Figure 6-20: Fiberglass concentration and recoveries in various SG ranges for - 500 µm ........ 157 Figure 6-21: Concentration and distribution of Al, Sb and Ca in various SG ranges for + 500 µm..................................................................................................................................................... 159 Figure 6-22: Concentration and distribution of Cu, Fe and Pb in various SG ranges for + 500 µm..................................................................................................................................................... 160 xxi Figure 6-23: Concentration and distribution of Mn, Ni and Sn in various SG ranges for + 500 µm..................................................................................................................................................... 161 Figure 6-24: Concentration and distribution of Zn in various SG ranges for + 500 µm ............ 161 Figure 6-25: Concentration and distribution of Al, Sb and Ca in various SG ranges for - 500 µm..................................................................................................................................................... 162 Figure 6-26: Concentration and distribution of Cu, Fe and Pb in various SG ranges for - 500 µm..................................................................................................................................................... 163 Figure 6-27: Concentration and distribution of Mn, Ni and Sn in various SG ranges for - 500 µm..................................................................................................................................................... 164 Figure 6-28: Concentration and distribution of Zn in various SG ranges for - 500 µm ............. 164 Figure 6-29: Total metal content and distribution in various SG ranges for + 500 µm.............. 165 Figure 6-30: Total metal content and distribution in various SG ranges for - 500 µm .............. 165 Figure 6-31: TGA thermograph for various SG ranges for + 500 µm ........................................ 167 Figure 6-32: TGA thermograph for various SG ranges for - 500 µm size fraction .................... 167 Figure 6-33: Derivative thermogravimetric curves for various SG ranges for + 500 µm .......... 169 Figure 6-34: Derivative thermogravimetric curves for various SG ranges for - 500 µm ........... 169 Figure 6-35: SEM micrograph for -1.8 SG fraction for + 500 µm ............................................. 171 Figure 6-36: SEM micrograph for +1.8-2.0 SG fraction for + 500 µm ...................................... 171 Figure 6-37: SEM micrograph for +2.0-2.5 SG fraction for + 500 µm ...................................... 172 xxii Figure 6-38: SEM micrograph for +2.5 SG fraction for + 500 µm ............................................ 172 Figure 6-39: SEM micrograph for -1.8 SG fraction for - 500 µm .............................................. 173 Figure 6-40: SEM micrograph for +1.8-2.0 SG fraction for - 500 µm ....................................... 173 Figure 6-41: SEM micrograph for +2.0-2.5 SG fraction for - 500 µm ....................................... 174 Figure 6-42: SEM micrograph for +2.5 SG fraction for - 500 µm ............................................. 174 Figure 6-43: Recommended flowsheet for NMF recycling ........................................................ 176 Figure 7-1: Particle size distribution of two NMF samples ........................................................ 197 Figure 7-2: Percent weight distributions for two NMF samples in different size fractions ....... 197 Figure 7-3: LOI test results on different size fraction for tested NMF samples ......................... 198 Figure 7-4: Washability plots for + 500 µm for NMF samples (solid–S 1 & dotted–S 2) ......... 199 Figure 7-5: Washability plots for - 500 µm for NMF samples (solid–S 1 & dotted–S 2) .......... 200 xxiii List of abbreviations ASTM American Society for Testing and Materials CEM Composite epoxy materials CFL Compact fluorescent lamp CFW Cumulative fractional recovery CRT Cathode ray tube EEE Electrical and electronic equipment EPA Environmental Protection Agency EU European Union E-waste Electronic waste FR Flame retardant FTIR Fourier transform infra-red GDP Gross domestic product GJ Giga joules GJ/t Giga joules per tonne IGC Inverse gas chromatography inh. inhabitants IT Information technology kT kilo tonnes LCD Liquid crystal display LED Light-emitting diode LOI Loss on ignition xxiv mg/kg milligrams per kilogram MJ Mega joules Mt Million tonnes NGM Near gravity material NGMI Near gravity material index NMF Non-metal fraction PBDD/F Polybrominated dibenzo-p-dioxin and dibenzofurans PBDE Polybrominated diphenyl ethers PCB Printed circuit boards PCBs Polychlorinated biphenyls PCDD/F Polychlorinated dibenzo-p-dioxin and dibenzofurans pg picogram ppm parts per million PPP Purchasing power parity RA Recovery of ash materials RN Recovery of non-ash materials SEM Scanning electron microscopy SG Specific gravity TCLP Toxicity characteristic leaching procedure TEF Toxic equivalency factor TEQ Toxic equivalent quotient TGA Thermogravimetric analysis xxv UNEP United Nations Environment Programme WEEE Waste electrical and electronic equipment WHO World health organization XRF X-ray fluorescence xxvi Acknowledgments I would like to share my most profound appreciation for my supervisor, Dr. Maria Holuszko, who provided me the opportunity and the platform to conduct this research. I would like to thank Dr. Holuszko for her supervision, guidance, and support throughout this research. I would also like to acknowledge the support, guidance, advice, criticism, and feedback provided by my committee members, Dr. Marek Pawlik and Dr. Bern Klein. I would like to thank Mr. Travis Janke, Director of Engineering, Ronin8 Technologies Limited, to provide constant guidance throughout the research and provide samples for the research. The financial support provided by Ronin8 Technologies Limited and MITACS Inc. is sincerely acknowledged. I would also like to thank the panelists of the GOE2 Initiative for providing additional funding for this research. The suggestions from Amber Springer and Heather McKenzie at ALS Environmental, Burnaby, providing the analytical tests' details are appreciated. I would like to thank the owners, engineers, and managers of recycling sites in British Columbia for allowing me to visit their facilities and for providing details of their processes. I want to acknowledge the help of Pius Lo, Aaron Hope, Sally Finora, and other staff at the NBK Institute of Mining Engineering. I would like to thank my friends and colleagues, Chengtie Wang, Vinoth Kumar, Santiago Seiler, Genzhuang Li, Stefan Nadolski, AJ Gunson, Tulio Marques, Daozhen Gong, Giovanni Pamparana, Cherezade Saud, and Maren Klein for their support. Finally, I would like to thank my wife, Preeti Rani, my parents, Arun Kumar Gupta and Rajkumari Devi, and my brother, Vikash Kumar, and my cousins for their love and constant support. xxvii Dedication To My Family1 Chapter 1: Introduction 1.1 Background Electronic waste (discarded electronics) is one of the fastest-growing waste streams in the world. It has been a serious concern due to its vast volume and potentially detrimental environmental and health effects. The amount of e-waste generated worldwide has been growing at a rate of 3–4% per year and is expected to reach 120 million tonnes by 2050 (Baldé et al., 2017; Wahlen, 2019). The development of innovative technologies and the dwindling lifespan of electronic products is the foremost cause of the elevated e-waste generation rate. If this waste is recycled correctly, it offers an opportunity for urban mining and for the recovery of valuable metals such as copper, gold, silver, and palladium. The fate of e-waste can be described by the simplified flowsheet shown in Figure 1-1. The primary focus of any federal or local jurisdiction should be the collection, reuse, and recycling of e-waste. However, not all e-waste is collected. A portion of the e-waste stream is disposed of in landfills or incinerators. The collected materials are usually sent for recycling, where high-value components such as metals and high-value plastics are recovered and fed back to the manufacturing stream, whereas low-value materials are landfilled or incinerated. The circular economy concept has been introduced to reduce the landfill and incineration scenarios and, thus, provide opportunities for the efficient use of natural resources. Researchers have shown that the future of e-waste management lies in the circular economy model with the target to keep materials in use as long as possible; thus, increasing material and resource utilization. The development of laws and policies in various jurisdictions to tackle the e-waste challenge is based 2 on the circular economy model. For example, the European Commission Directive 2008/98/EC (2008), that deals with defining, categorizing, and setting collection and recycling targets, was developed to facilitate efficient resource recovery and utilization. Figure 1-1: Simplified flow of electrical and electronic equipment To reduce the e-waste landfilling/incineration and promote the circular economy, the e-waste collection rate must be increased, thus increasing the amount of material recirculating back in the manufacturing system and reducing the amount of material being disposed. At the same time, rejects from the e-waste recycling process must also be studied for the potential recovery of its constituents and their applications. It would, in turn, minimize the final waste volume needing disposal. Sales of electronic productsEnd of lifeE-waste generationStorage/collection Landfill / incinerationReuse RecycleEnd of lifeRecovered stream Rejected streamRaw material for manufacturingLandfill / incineration3 1.2 Problem statement Researchers have shown that e-waste is a growing concern worldwide and has proposed that the circular economy model would provide the solution to reduce the issues associated with e-waste and improve resource utilization. Figure 1-1 showed that the e-waste management chain contains two exit points for the materials to be discharged in landfills and in incineration. One point revolves around the e-waste collection section, where if the e-waste is not properly collected, it has a higher probability of being disposed of in landfills. Forti et al. (2020) reported that the formal documented collection and recycling rate of e-waste was 17.4% in 2020. The discarded electronics' collection rate must be increased and then processed at a recycling facility to increase the circularity. The current e-waste management situation needs to be studied and analyzed to increase the e-waste collection and recycling rate. This study will lead to an understanding of the e-waste management system's challenges and provide possible recommendations to increase circularity. The second point of material exit in the e-waste management chain is the rejected stream in the e-waste recycling process. The metal-containing fraction in the e-waste is the central focus of recycling due to its high monetary value, whereas the non-metal fraction is mostly sent to landfills because of its negligible value. Most of the research in e-waste recycling is always focused on the analysis and recovery of metals. Since the majority of the collected e-waste is processed in some fashion before disposal, consequently, a study for the separated non-metal fraction is necessary in order to evaluate characteristics of this material and assess it for appropriate end-of-life utilization and/or issues associated with the landfill disposal, if the latter becomes the final option. 4 1.3 Research objectives The primary objective of this doctoral thesis focuses on the characterization of the non-metal fraction obtained from the processing of waste printed circuit boards for its recycling using physical separation methods to promote the circular economy. An interdisciplinary approach was used to understand the characteristics of the non-metal fraction for recycling by using tools, processes, and parameters most common in mineral processing and coal industry. Studying the advancement of e-waste circular economy through an increased collection rate was not the main objective of this research. However, a study was performed to understand the e-waste collection and management system from the Canadian economy perspective. The study elaborated on the challenges of the e-waste management system in Canada and provided recommendations to increase the e-waste collection rate. The detail of this study is presented in a published refereed journal paper and is added as Appendix H of the thesis. The research questions identified in this thesis were: • Which physical processes could theoretically be used to recover components from the non-metal fraction to produce value-added material, close the material loop, promote the circular economy, and ultimately, reduce the final waste needing disposal? • What would be the theoretical grade-recovery estimates for a selected process and the possible end-use of the recovered streams based on those estimates? The following specific objectives were defined and explored to achieve the primary research objectives of non-metal recycling obtained from a commercial waste printed circuit board recycling facility: 5 • Characterizing the non-metal fraction obtained from a waste printed circuit board recycling facility and understanding the economic incentives of NMF recycling, if any; • Adopting the standard loss on ignition testing parameters for the non-metal fraction in order to define the efficiency of separation for the proposed physical separation methods; • Understanding the applicability of commonly used physical processing methods for non-metal fraction recycling. This would help to identify various physical processing methods commonly used in the mineral processing sector for their application in NMF recycling; • Estimating the theoretical recovery and grade for the best-suited physical separation process. This section would use the data from the previous step to determine the theoretical performance of the best-suited process; • Understanding the feasibility of the selected process using various indices used in mineral processing. This would identify the ease of separation based on comparative literature and reports from other processing sectors; • Identifying the possible application or utilization for the recovered streams based on the characteristics of recovered products. It would help to determine the suitable application of the recycling products and facilitate the circular economy model by closing the material loop; • Analyzing the sample variation and sample heterogeneity and their effects on the selected processing route. This would assess the adaptability and flexibility of the recommended process for the highly heterogeneous and ever-changing recycling feedstock. Since the printed circuit board (PCB) is one of the most valuable components of any electrical and electronic equipment and has the highest recycling potential, the non-metal fraction obtained from the waste PCB was selected for this study. It should also be noted that most of the research and 6 publications related to waste PCB recycling are limited to waste PCB before any processing and samples obtained from individual electronics units. Since most PCBs are processed in some fashion, this research was focused on non-metal fraction samples obtained from a waste PCB recycling facility processing a mixture of PCBs obtained from various electronics equipment, presenting a more realistic scenario. One of the challenges with NMF recycling is the unknown specifications for end products. In the mineral processing study, physical separation focuses on obtaining specific product grades as defined by end-users. Research in the field of NMF utilization is aimed at reusing NMF as raw materials in composite manufacturing without any modifications, whereas research in the field of NMF recycling is usually focused on separating organic and inorganic materials without accounting for any specific end-product quality requirements. Hence, this research was aimed to obtain a relatively cleaner organic and inorganic stream with high recoveries. 1.4 Thesis outline Chapter 1 of this thesis introduces the research, provides details of the research questions, and outlines the objectives. The outcomes of previous research in the field of e-waste are summarized in Chapter 2. This chapter also provides a brief discussion on the circular economy, electronic waste and its definition and categories, and global e-waste generation statistics. It also emphasizes the benefits of recycling and outlines conventional recycling technologies. Finally, it also reviews the research conducted in the field of recycling of the non-metal fraction. 7 To increase the circularity of e-waste with specific attention to the recycling rejects, it is necessary to understand the characteristics of e-waste non-metal fraction as this stream is mostly disposed of in landfills and incinerators. Chapter 3 focuses on characterizing the non-metal fraction obtained from a waste printed circuit board recycling facility. It discusses the benefit of NMF recycling and the issues associated with its improper disposal. Chapter 4 elaborates on establishing a standard test parameter for the loss on ignition test. This test is one of the most common methods used to evaluate the efficiency of separation of different components, especially the separation of the organic components from the inorganic components. Various mineral processing separation methods such as size classification, gravity separation, and froth flotation were analyzed to assess their applicability for separating organic and inorganic components in NMF. Chapter 5 provides the results obtained from this assessment. The so-called “washability analysis” data obtained from the gravity separation test is presented in Chapter 6. The washability analysis evaluates the possibility of using gravity separation as a method for NMF recycling and discusses the product characteristics obtained from gravity-based recycling processes. Chapter 7 studies the effects of sample variation on the proposed recycling flowsheet. Since the feed to the recycling industry is highly variable, it is essential to understand its impact on the process outputs. Major conclusions from the study are listed in Chapter 8, along with the recommendations for future work. 8 Chapter 9 outlines the originality claims resulting from this study and their contribution to applied science and the recycling industry. The links between core chapters and their relevance to the primary research objective are shown in Figure 1-2. Figure 1-2: Links between core research chapters Sales of electronic productsEnd of lifeE-waste generationStorage / collectionLandfill / incinerationReuse RecycleEnd of lifeRecovered streamRejected streamRaw material for manufacturingLandfill / incinerationChapter 3: NMF characterizationChapter 4: LOI parametersChapter 5: Physical separationChapter 6: Gravity separationChapter 7: Sample variationPROMOTING CIRCULAR ECONOMY9 Chapter 2: Electronic waste – A literature review This chapter provides detailed background information regarding the status of e-waste around the world. It provides a definition of e-waste, its categories as well as global e-waste generation statistics. It also emphasizes the importance and the benefits of recycling, and it provides an overview of conventional recycling technologies. It also discusses the status of non-metal fraction, issues associated with improper disposal, and the current situation of non-metal fraction recycling. A version of this chapter has been published as a review article in Resource, Recycling, and Conservation journal. The published article provided the definition of e-waste and its category and an overview of generation estimates, recycling benefits, and recycling technologies. The current chapter provides a more detailed review of these topics. In addition, the information about the circular economy, printed circuit boards, and non-metal fraction, along with its types, composition, and recycling processes, have been added to this chapter. 2.1 E-waste definition Any electrical and electronic product that have been discarded are considered as waste and are known as electronic waste, or e-waste, in short. Wath et al. (2010) and Mmereki et al. (2016) reported that there is still no standard definition for e-waste globally, and each country has its definition. However, due to rapid technological changes and the shorter lifespan of EEE, a well-versed definition is fundamental to formulate policies and define disposal standards for e-waste. One of the most suitable definitions of e-waste is provided by the European Commission Directive 2008/98/EC (2008) and the European Union Directive 2012/19/EU (2012) that described e-waste as: 10 “any electrical or electronic equipment (EEE) which is waste (substance or object which the holder discards or intends or is required to discard), including all components, sub-assemblies and consumables which are part of the product at the time of discarding.” The EEE was classified into ten categories in the Directive 2012/19/EU during a transitional period from August 13th, 2012 to August 14th, 2018 (The European Union, 2012). After the transitional period (after August 15th, 2018), the EEE categories were consolidated into six (6) classes. These classes of items (not limited to) in the categories are listed as 1. Temperature exchange equipment: refrigerators, freezers, air conditioning equipment, and heat pumps 2. Screens, monitors, and equipment containing screens (surface > 100 cm2): televisions, LCD photo frames, monitors, laptops, notebooks, and tablets 3. Lamps: fluorescent lamps, high-intensity discharge lamps, including pressure sodium lamps and metal halide lamps, low-pressure sodium lamps, and light-emitting diode (LED) lamps 4. Large equipment (external dimensions > 50 cm): washing machines, dryers, dishwashers, electric stoves, musical equipment, large computer-mainframes, large printing machines, copying equipment, large coin slot machines, large medical devices, large automatic dispensers, and photovoltaic panels 5. Small equipment (external dimensions < 50 cm): vacuum cleaners, appliances for sewing, luminaires, microwaves, irons, toasters, electric kettles, clocks and watches, electric shavers, scales, radio, video cameras, electrical and electronic toys, sports equipment, smoke detectors, heating regulators, thermostats, small electrical and electronic tools, small medical devices, small automatic dispensers 11 6. Small IT and telecommunication equipment (external dimension < 50 cm): mobile phones, GPS, pocket calculators, routers, personal computers, printers, and telephones The e-waste is also categorized into these six classes and has been used to estimate e-waste quantities and their inherent value by Baldé et al. (2017; 2015). 2.2 Lifespan of electronic products The e-waste estimation method requires the average lifespan or the distribution of the lifespan of any given EEE. The lifespan of a product is the time it takes for any product to be discarded by its owner. The estimated lifespan of a few electronics products is listed in Table 2-1. Table 2-1: Estimated lifespan of EEE Items Average lifespan (Ely, 2014) (Abbondanza & Souza, 2019) Cellphones 4.7 2.3 Desktop computer 5.9 5.9 Flat-panel TV 7.4 4.3 Laptop 5.5 4.0 Printer - 2.9 Refrigerator - 7.8 Smartphones 4.6 1.8 Washing machine - 6.8 12 It shows that the lifespan of consumer electronics has decreased in the past few years. Ala-Kurikka (2015a, 2015b), Ely (2014), Geere (2015), Ahmed (2016), and Umweltbundesamt (2016) have all suggested a similar trend, indicating a significant reason for the increasing e-waste quantities around the globe. A product might go through various phases such as storage and reuse before being discarded; hence, modeling a realistic lifespan is quite challenging. Thiébaud (2018) used social media and emailed surveys out to Swiss households to obtain information relating to the service lifetime and the storage lifetime of ten electronic devices. Oguchi (2015) also proposed methods based on survey data to obtain discard-rate distributions for different products. Researchers have shown that the Weibull distribution is the most suitable probability distribution function to model the discard behavior of EEE (Baldé et al., 2017; Environmental Protection Agency, 2016; Miller et al., 2016; Oguchi & Fuse, 2015; Polák & Drápalová, 2012; Santoso et al., 2019; Sumasto et al., 2019; Tran et al., 2016). The simplified Weibull distribution of product discard-based lifetime profile is shown in Equation 2-1 (Forti et al., 2018). The discard-based lifetime echoes the probability of an EEE entering the waste stream in a given year after its sale. 𝐿 (𝑡) = 𝛼𝛽𝛼(𝑛 − 𝑡)𝛼−1𝑒−(𝑛−𝑡𝛽)𝛼 Equation 2-1 where, L(t) is the discard-based lifetime profile of an EEE product sold in a base year t,  is the distribution parameter, also known as the shape parameter,  is the average lifespan, also known as the scale parameter, 13 n is the year for which the lifespan is being modeled. Figure 2-1 shows a sample plot for the discard probability and cumulative discard probability of various electrical and electronic equipment using Equation 2-1. Baldé et al. (2015) and the Environmental Protection Agency (2016) have used this method and the average lifespan and the distribution factor of various EEE reported by Forti et al. (2018) to estimate the e-waste generation around the globe in 2014 and 2016 (Baldé et al., 2017; Baldé et al., 2015). Figure 2-1: Discard probability of various EEE over their lifetime 2.3 E-waste generation statistics Using the sales data obtained from domestic sales and international trade and the Weibull lifespan distribution of EEE, Baldé et al. (2017) estimated the total e-waste generated worldwide and for individual countries. The method for this estimation is detailed by Forti et al. (2018). The total e-14 waste generated worldwide in 2016 was 44.7 million tonnes and is expected to reach 52.2 million tonnes per annum in 2021. By 2021, the waste generated per capita is expected to increase from 6.1 kg/inhabitants in 2016 to 6.8 kg/ inhabitants. The global trend of e-waste generation is shown in Figure 2-2. Wahlen (2019) reported that under the business-as-usual case, the total e-waste generation would reach 120 million tonnes per year by 2050. Figure 2-2: Global e-waste generation trend Drawn from data reported by Baldé et al. (2017) Figure 2-2 shows that the amount of e-waste has been steadily increasing every year. The growth rate of e-waste generation has been reported to be 3–5% by Cucchiella et al. (2015), 3–4% by Baldé et al. (2017) and Aaron (2019), and as high as 8% by LeBlanc (2018). According to the Transparency Market Research report (2017), the global e-waste market is anticipated to increase 15 at a compound annual growth rate of 5.6% by volume from 2016 to 2026. The data for 2017–2021 in Figure 2-2 is projected based on the general growth rate of 3–4% per year (Baldé et al., 2017). Figure 2-3 shows the waste generation in the six e-waste categories defined by the European Union Directive 2012/19/EU. It shows the e-waste generated by weight in each category in 2016. The larger waste amount for large equipment and temperature exchange equipment, despite a longer lifespan, is primarily due to the higher weight per unit for these appliances than other categories. For example, the unit weight for small IT equipment and screens is approximately 0.2–0.3 kg and 5–6 kg, respectively, whereas the weight of large appliances and temperature exchange equipment such as washing machines and refrigerators are 41.5 kg and 56.5 kg, respectively (Abbondanza & Souza, 2019). Figure 2-3: Total waste generation in various e-waste categories Drawn from data reported by Baldé et al. (2017) 16 The study from the United Nations University (2017) divided the countries into five regions and listed the amount of e-waste generated in these regions, as shown in Figure 2-4. It shows that the waste generated in the Asia region was the highest and Oceania was the lowest, mostly due to the population difference. The population in Asia was 4.4 billion, compared to 39 million in Oceania. If the generation of e-waste is compared on a per-inhabitant basis, regions with high purchasing power parity (PPP) such as Oceania and Europe have a higher amount of waste generated per inhabitant, compared to lower PPP regions such as Africa and Asia. These behaviors are further illustrated in Figure 2-5, where the e-waste per capita is projected on the world map, clearly showing this difference. Figure 2-4: Total e-waste generated by different regions Drawn from data reported by Baldé et al. (2017) 17 The data for the electronic waste generation per capita for each country, provided by Baldé et al. (2017) is projected on the world map in Figure 2-5 and has also been plotted with each country’s GDP, adjusted for purchasing power parity (PPP) in Figure 2-6. It clearly shows the trend in e-waste generation in different regions. Western countries such as the United States of America, Canada, and countries of the European region generate a higher amount of e-waste per person than Asian and African nations. This is mostly due to higher per capita income and a higher standard of living in American and European regions, allowing for the more frequent purchase of new technologically advanced devices, thus putting older devices into the waste stream. Figure 2-5: E-waste generated per capita in the world Drawn from data reported by Baldé et al. (2017) 18 It can also be seen in Figure 2-5 and Figure 2-6 that certain countries in Asia with relatively higher per capita income such as the United Arab Emirates, Qatar, and Japan produced more waste compared to other Asian countries with lower PPP such as India, Bangladesh, and Pakistan. The size of the marker in Figure 2-6 represents the population of the country. It suggests that e-waste generation is proportional to the purchasing power for any given country. For example, India and China are two Asian countries with similar populations (1324.2 and 1378.7 million). However, in terms of the GDP per capita, PPP for China ($15,548) is almost two and a half times higher than that for India ($6,637), which in turn relates to much higher waste generation in China (7,211 kT at 5.2 kg/inh.) compared to India (1,975 kT at 1.5 kg/inh.). Figure 2-6: E-waste generated per capita with respect to the PPP and population Drawn from data reported by Baldé et al. (2017) and World Bank (2019) 19 Kusch et al. (2017) studied the relation of waste generation and gross domestic product (GDP) for fifty countries of the pan-European region. It also showed that the GDP per capita adjusted for purchasing power parity (PPP) has a linear dependency with e-waste generated per capita. The PPP-adjusted GDP takes price differences and differences in the cost of living into account; thus, truly reflecting the purchasing power of a country’s inhabitant (Kusch et al., 2017). Sthiannopkao & Wong (2013) and Li et al. (2015) have shown that the increasing growth and development of countries such as India, China, and Brazil would likely escalate the amount of e-waste generation in these countries, and this amount will likely surpass that of the most developed countries. The economic growth and increase in the purchasing power of residents in other developing countries will add more fuel to the global generation of e-waste. A model proposed for dealing with the massive amount of generated e-waste is the circular economy model. 2.4 Circular economy The concept of the circular economy has been introduced to promote efficient use of natural resources. Researchers have shown that the future of e-waste management lies in the circular economy model, with the target to keep materials in use as long as possible; thus, increasing material and resource utilization. The circular economy concept has been promoted by the European Union and several other countries, including China, Japan, Canada, and the United Kingdom (Korhonen et al., 2018). The definition of a circular economy as provided by the European Commission (2015) and discussed by Sillanpää & Ncibi (2019) is, 20 “a production and consumption model which involves reusing, repairing, refurbishing, and recycling existing materials and products to keep materials within the economy wherever possible.” The goal of the circular economy model is to reduce the consumption of raw materials by designing the product for an efficient end-of-life utilization, increasing the product’s lifespan by reuse and repair, and finally incorporating appropriate recycling techniques to recover materials from the waste (van Buren et al., 2016). Xavier et al. (2019) proposed that reverse logistics, the 3Rs concept (reduce, reuse, and recycle), and urban mining are the three critical aspects of the circular economy in e-waste. Reverse logistics is the process of the movement of goods for reuse, recycling, and their final disposal (Islam & Huda, 2018). The reduce concept helps with the reduction of electronics purchased, thus, reducing the overall number of electronic items in circulation. The reuse step helps to increase the lifespan of electronic devices through repairs. Recycling and urban mining help to extract the value from a waste stream and provide secondary resources for the manufacturing of new goods (Ramanayaka et al., 2020). Recycling also provides significant benefits to the economy, reducing waste in the environment, and positively impacting the issues related to public health and safety. In recent years, the research and the development of e-waste recycling techniques have been gaining significant attention. 2.5 Benefits of e-waste recycling Recycling is one of the most researched areas to deal with the ever-growing e-waste issue around the world. The metals and materials present in e-waste provides economic benefits to the recyclers and reduce the environmental concerns associated with improper disposal. This section of the 21 chapter provides a detailed analysis of the benefits associated with e-waste recycling. The benefits are presented in two sections. 2.5.1 Economic and employment opportunities Electrical and electronic equipment is one of the major consumers of numerous metals such as copper, gold, silver, and iron. Namias (2013) suggested that electronic devices can contain up to sixty different elements that could be valuable or hazardous. Natural Resources Canada (2019) showed that, globally, 18% of aluminum, 31% of copper, 9.5% of gold, 9% of platinum group metals, and 24% of rare earth elements were used for electrical and electronic equipment manufacturing in 2017. In the United States of America, 9% of the total aluminum, 21% of beryllium, 19% of copper, 40% of gold, and 26% of silver were used in the electrical and electronic equipment manufacturing industry in 2019 (U.S. Geological Survey, 2019). Recovery of these metals from the waste EEE provides an economic incentive to the recycling industry. BullionStreet (2012) showed that approximately 290 tonnes of gold and 6800 tonnes of silver are consumed by the electronic industry every year. Baldé et al. (2017) estimated the amount of various elements and materials present in e-waste. It showed that the total contained/potential value of all the metal and materials present in e-waste was forty-eight billion Euros in 2014 and increased to fifty-five billion Euros in 2016 (Baldé et al., 2017; Baldé et al., 2015). Figure 2-7 shows a breakdown of the various metals and materials present in e-waste with their total amount and estimated values. It should be noted that the estimated value depicted in Figure 2-7 represents an ideal case scenario of 100% collection and metal recovery without the cost associated with the collection and recycling. It indicates the economic opportunity for e-waste recycling. 22 It should also be noted that the concentration of metals in e-waste is significantly higher than that of conventional ore deposits for a mining operation. The global ore grade has been decreasing, and the increased global metal demand has forced mining operations to increase the plant throughput and excavate more complex and fine-grained ore deposits (Lèbre & Corder, 2015). Figure 2-7: Estimated value of metals and materials present in e-waste Drawn from data reported by Baldé et al. (2017) Table 2-2 shows the concentration of various metals in different types of e-waste and an average ore. Calvo et al. (2016) summarized that the global average copper grade for run-of-mine ore is ~0.62% and will be declining in the coming years due to the depletion of high-grade mineral deposits. AME Research (2018) showed that the average copper grade has decreased from 0.74% in 2005 to 0.59% in 2017, with a compound annual decline rate of 1.8%. The global average gold grade of all the deposits was 1.01 ppm in 2013 (Desjardins, 2014) whereas, the average gold grades 23 from e-waste range from 30 to 350 ppm, as shown in Table 2-2. The highest gold grade for the underground operation was reported at 21.5 ppm in Fosterville, Australia, whereas for open pit, it was 7.60 ppm in Way Linggo, Indonesia (Basov, 2018). The average output of the top-six silver mines was 7.6 oz (215 g) per tonne in 2012 and has dropped to 4.4–5.5 oz per tonne in 2017 (McLeod, 2014; Money Metals Exchange, 2018). Table 2-2: Average metal content in various waste EEE and run-of-mine ore (Bizzo et al., 2014; Calvo et al., 2016; Desjardins, 2014; Fornalczyk et al., 2013; Işıldar, 2016; Khaliq et al., 2014; Liu, 2014; McLeod, 2014; Namias, 2013; North American Palladium Ltd., 2018; Shah et al., 2014; Tickner et al., 2016; Zeng et al., 2016) Copper Aluminum Iron Gold Silver Palladium % % % ppm ppm ppm Air conditioner 6–19 7–9 46 15 58 - Desktop 7–20 2–4 18–47 46–240 207–570 18–25 Laptop 1–19 1–2 20 32–30 190–1100 19 Mobile phone 10–33 3 5 30–1500 2000–3800 300–1700 Printed circuit board 12–19 2–8 0–11 29–1120 100–5200 33–220 Refrigerator 3–17 1–2 48–50 44 42 - Television 1–21 1–15 13–43 5–300 120–600 0–20 Washing machine 3–7 0–3 52–53 17 51 - E-waste (average) 12–35 1.5–5 5–11 30–350 80–1000 30–200 Run-of-mine ore 0.5–3 20–24 30–60 0.5–10 5–10 1–10 24 The palladium grade reported in Table 2-2 is based on the average palladium grade of the Lac des Iles Mine Property in Northern Ontario. It indicates that the average metal grade present in e-waste is significantly higher than in conventional mines, thus providing the opportunity for extraction/urban mining. According to the World Gold Council (2019), the global gold mine production in 2016 was 3397.3 tonnes. The amount of gold present in e-waste in 2016 was 500 tonnes, nearly 15% of the total global gold production. Some of the critical raw materials for electronics manufacturing, such as gallium and indium, with an estimated availability of twenty years, will be exhausted; and the recycling of used electronics could provide significant prospects in the coming years (Li et al., 2015). Zeng et al. (2018) showed that pure copper and gold could be recovered from e-waste in China at costs comparable to the production costs from conventional mining operations. It should be noted that the cost of recycling will vary significantly for different countries and different commodities. The e-waste recycling industry also has the potential to create significant employment opportunities. The United Nations University reported that the recycling and refurbishment sectors hold vast economic and employment opportunities (Baldé et al., 2017). There are nearly 100,000 people directly or indirectly working in the e-waste sector in Nigeria (Wahlen, 2019). Approximately 100,000 people are working as e-waste recyclers in Guiyu, China (Heacock et al., 2015). Zeng et al. (2016) suggested that up to 600 new recycling centers would be required by 2030, employing 30,000 people in China at the current throughput. The e-waste recycling industry would add over 500,000 new jobs directly or indirectly in India by 2025 (The Economic Times, 2019). This shows the vast economic and employment potential of the e-waste recycling sectors around the globe. 25 2.5.2 Environmental protection and public health The previous section indicated that e-waste recycling holds a substantial opportunity for value-recovery due to the presence of valuable metals, and it could provide direct or indirect employment opportunities. The recycling industry also plays an essential role in improving environmental protection. As mentioned in the earlier section, e-waste contains up to sixty elements, including hazardous elements (Namias, 2013). It also contains toxic chemicals in the form of flame retardants and ozone-depleting chemicals (Baldé et al., 2015). Typical pollutants in e-waste are • metals: antimony, cadmium, chromium, lead • flame retardants: chlorinated and brominated flame retardants • ozone-depleting chemicals: chlorofluorocarbons Antimony (Sb) is widely used in flame-retardants plastics, printed circuit boards, and lead batteries. Cadmium (Cd) is widely used in rechargeable nickel-cadmium batteries, CRT screens, printer inks, and toners. Historically, chromium (Cr) was widely used in audio cassettes, tapes, and floppy disks. Lead (Pb) was primarily used in the obsolete CRT screens, lead-acid batteries, and in the solder in printed circuit boards. It is one of the primary heavy metals present in e-waste. Heavy lead contamination and exposure have been reported in e-waste recycling facilities in India, China, Ghana, and Uruguay (Brigden et al., 2005; Brigden et al., 2008; Pascale et al., 2016). Organo-halogen compounds such as polychlorinated biphenyls (PCBs) and polybrominated diphenyls (PBDE) have been widely used as flame-retardant chemicals in circuit boards and other electrical components. The production of polychlorinated biphenyls has been banned in the USA since 1979 because of their harmful health effects (Agency for Toxic Substances and Disease 26 Registry, 2014). Europe also banned the use of penta- and octa- polybrominated diphenyl in 2004 and deca- polybrominated diphenyl in 2008 (Betts, 2008). The reported concentration of these metals and compounds are listed in Table 2-3. It shows the presence of a high level of pollutants in e-waste and the surrounding area. Table 2-3: Concentration of typical pollutants in e-waste Metals/ compounds Material Concentration Source Antimony E-waste 22–4600 ppm Gaidajis et al. (2010), Alassali et al. (2019), Okkenhaug et al (2015) Cadmium E-waste 180 ppm Gaidajis et al. (2010), Robinson (2009) Chromium E-waste Up to 9900 ppm Robinson (2009), Varshney et al. (2019) Lead E-waste 2200–23000 ppm Liu (2014), Brigden et al. (2005; 2008), Pascale et al. (2016) PBDE Workshop 15.6–317.0 mg/kg Guo et al. (2015) PCB 14567 mg/kg penta-BDE, 2718 mg/kg hexa-BDE Chen et al. (2012) PCBs E-waste 14 mg/kg Gaidajis et al. (2010) Tree near recycling center 112 ng/g Wen et al. (2009) Soil near recycling center 0.08–21.06 ng/g Liu et al. (2008) 27 Baldé et al. (2015) concluded that the hazardous materials from e-waste could impair mental development, induce kidney and liver damage, and could have carcinogens released into the air, causing lung damage. The elevated levels of hazardous metals show the importance of proper recycling techniques and safer recycling facilities to reduce the risks related to public health and safety issues. Recycling e-waste could also reduce the total global demand for new metal production, reducing greenhouse gas emissions. According to the Electronics TakeBack Coalition (2014), it requires 240 kg of fossil fuels, 22 kg of chemicals, and 1.5 t of water to produce one computer with a monitor. The benchmark carbon footprint reduction for metal recycling compared to virgin metal production, as reported by the Bureau of International Recycling (2008, 2016), is listed in Table 2-4. The analysis boundary was limited to a.) raw material extraction to final product for virgin materials and b.) scarp material delivered to the recycling facility to final product for recycled materials. Table 2-4: Carbon footprint reduction from recycled metal production Metal % savings in CO2 equivalent emissions per 100 kT of metal produced (kT) Savings in annual CO2 emission (Mt) Aluminum 354 63.3 Copper 81 4.8 Ferrous 97 503.9 Lead 161 4.8 Nickel 190 .6 Tin 215 0.1 Zinc 180 1.8 28 Recycling also provides significant energy savings compared to virgin materials (ISRI, 2018). The energy required to produce aluminum was reported to be 6–10 MJ/kg with 60–80% recycling efficiency (Bureau of International Recycling, 2016). Table 2-5 lists the percentage of energy savings that can be achieved by the production of metals through secondary resources, compared to the primary mining route. It should be noted that the energy savings potential for recycled materials is usually estimated based on scrap material recycling such as aluminum cans, electrical wires, glass bottles, and plastic containers, not e-waste. Hence, Table 2-4 and Table 2-5 do not reflect the actual savings from e-waste recycling. Table 2-5: Energy savings between virgin and recycled materials production (Bureau of International Recycling, 2008, 2016; Cui & Forssberg, 2003; ISRI, 2018) Metal Energy savings per 100 kT of metal produced (%) Aluminum 94.9–95.0 Copper 62.7–85.0 Ferrous 16.4–74.0 Lead 65.0–98.7 Nickel 91.0 Tin 98.9 Zinc 25.0–60.0 Glass 34.0 Plastics 80.0–88.0 29 Van Eygen et al. (2016) compared the natural resources savings for recycling compared to landfill scenarios based on the life-cycle analysis of desktops and laptops in Belgium. It showed that overall, 80–87% of natural resources could be saved if desktops and laptops are recycled, compared to the landfilling option. It included resource savings for materials collection, primary treatment, and end-processing. The natural resources include fossil fuels, nuclear energy, metal ores, water, land, and atmospheric resources. Overall, e-waste could provide a secondary source for various raw materials and reduce the total global demand for new metal production, reducing the total energy consumption and overall greenhouse gas emissions. 2.6 Printed circuit boards The primary objective of this research is to study the recyclability of the non-metal fraction to promote the circular economy. E-waste contains several types of non-metals such as ceramics, plastics, fiberglass, resins, cellulose, rubber, and glass, depending on the EEE type. Different types of e-waste also have different compositions of non-metals. Since the printed circuit board (PCB) is one of the most valuable components of any EEE and has the highest recycling potential, the non-metal fraction obtained from the waste PCB was the focus of this research. Printed circuit boards (PCB) are the platform that provides the connections for all other electronic components such as resistors, capacitors, diodes, memory, and processors (Awasthi et al., 2017; Ghosh et al., 2015; Ning et al., 2017). With the development of newer technologies, the printed circuit board market is expected to grow with a compound annual growth rate of 4.3 % from 2014 to 2019, and is expected to reach an estimated $89.7 billion by 2024 (Research and Markets, 2019). 30 Average metal concentration in PCB is usually 30–35% metals such as copper, silver, gold, and palladium, while the rest is the non-metal fraction such as resin, fiberglass, cellulose, and chemicals such as flame retardants (Bizzo et al., 2014; Luda, 2011; Szałatkiewicz, 2014b; Veit et al., 2014; Zheng at al., 2009). The percentage weight of PCB in an electronic device depends on the type of unit and can vary from 2% to 22% (Szałatkiewicz, 2013). On average, printed circuit boards account for 3–6% (by weight) of the total e-waste (Das et al., 2009; Ghosh et al., 2015; Golev et al., 2016, Golev et al., 2019; Ning et al., 2017; Szałatkiewicz, 2014a). Although representing a relatively smaller fraction by weight, waste PCB accounts for ~ $150 million per year of the total metal recovery value in e-waste, which in turn represents ~ 40% of its total estimated value (Golev et al., 2019; Golev & Corder, 2017), thus, providing a significant incentive for recycling organizations. Rocchetti et al. (2018) reported that until July 2017, over 200 patents were considered relevant to the field of PCB recycling, with more patents approved/filed towards the end of the decade. This shows the growing interest of various organizations and research institutes in the field of PCB recycling. 2.6.1 PCB types and composition There are several types of PCB available in the market, depending on the requirement, and these can be single-sided, double-sided, or multi-layered (Ghosh et al., 2015). Single-sided PCB has circuitry on only one side of the board, whereas double-sided PCB has circuitry on both sides of the board. These boards are for low-cost, high-volume, and low-functionality boards (Nakahara, 2016). Multi-layered PCB was limited to modern industrial electronic products, but with the increase in modern consumer electronics' power and functionality, multi-layered circuit boards are now used in all electronic devices, including cellphones, cameras, and other consumer electronics. 31 Multi-layered PCB can have three (3) or more double-sided PCB, secured together with specialized glue and inserted between a piece of insulation. Different layers of the boards are electrically connected through a hole (vias) punched through the board (Nakahara, 2016; Pcbcart, 2017). The PCB is also classified based on the type of base material. IPC-4101 is the most common specification used for the PCB base materials and has 131 different specification sheets. More broadly, the National Electrical Manufacturers Association (NEMA) classification has been widely used for base materials. The base material for PCB consists of a reinforcement encapsulated in resin material. Phenolic, epoxy, and polyester resins are the most commonly used resins in PCB manufacturing, whereas cotton/cellulose paper and fiberglass are the primary reinforcement. There are several types of PCB, such as FR-1 to FR-6, CEM-1 to CEM-8, and G-10 and 11, XXP, and XXXPC (Kelley & Trobough, 2016b; Weil & Levchik, 2004). FR stands for flame retardant, CEM stands for composite epoxy materials, and G stands for glass-reinforced. The major difference in different types of PCB is the reinforcement and resin materials. These differences in types of materials affect the physical properties and the cost of the PCB, rendering it suitable for specific applications. Kelley & Trobough (2016b) suggested that the most common types of PCB are FR-2, FR-4, CEM-1, and CEM-3. Table 2-6 lists the details of these four types of PCB. All four boards have flame-retardant properties. 32 Table 2-6: Description of most common types of PCB (Kelley & Trobough, 2016b) Type Resin Reinforcement Application FR-2 Phenolic Cotton paper Low cost, radios, calculators and, toys FR-4 Epoxy Woven glass cloth Computers, servers, data storage, telecommunications, industrial applications CEM-1 Epoxy Cotton paper core with woven glass cloth on surface Consumer & industrial electronics CEM-3 Epoxy Non-woven glass core with woven glass cloth on surface Early home computers, automobiles, home entertainment products CEM-1 provides improved electrical and physical properties compared to FR-2 but can only be used as a single-layered PCB. CEM-3 is more suitable for plated through holes that allow the circuitry to be printed on both sides and can be used as a complete replacement for FR-4 but has a higher cost than other PCB. FR-4 is the most common PCB type with outstanding electrical, mechanical, and thermal properties, rendering it useful for a wide range of applications. The price of alternatives to FR-4 is usually two to four times higher (Lassen & Løkke, 1999). In the field of consumer electronics, FR-2 and FR-4 are the most commonly used PCB. Lassen & Løkke (1999) suggested that 90% of the produced PCB is FR-4 based, and the remaining 10% includes FR-2 and other types. FR-2 is widely used in televisions and home electronics, whereas FR-4 is mostly used in high-value EEE such as computers and electronics for telecommunications (Guo et al., 2009; Hall & Williams, 2007; Lassen & Løkke, 1999; Marques et al., 2013). 33 The metal concentration in PCB widely varies depending on the types of EEE. Table 2-7 provides the range of metal concentrations, as reported in various literature. It shows the potential of metal recovery from the waste PCB. Due to the high concentration of metals, the waste PCB is mostly processed in some fashion before disposal. The next section discusses some of the most common ways used for metal recovery from e-waste and printed circuit boards. Table 2-7: Metal concentration in waste PCB (Awasthi et al., 2017; Bizzo et al., 2014; Das et al., 2009; Golev et al., 2019; Guo et al., 2009; Ning et al., 2017; Park & Fray, 2009; Szałatkiewicz, 2014a) Element Units Range Aluminum % 1.7–7.06 Copper % 12.5–28.7 Gold ppm 29–1120 Iron % 0.08–11.47 Lead % 1.01–5.53 Nickel % 0.26–5.35 Palladium ppm 33–220 Silver ppm 79–5210 Tin % 1.0–8.83 Zinc % 0.08–5.92 34 2.7 Recycling techniques The monetary benefits of e-waste and PCB recycling provides incentives for research and development of recycling technologies. This section lists the most common techniques and technologies used for e-waste recycling, especially for waste PCB. The recycling methods could be broadly categorized into two sections, pre-processing and end-processing (Namias, 2013). 2.7.1 Pre-processing The pre-processing step deals with the dismantling, size reduction, and physical separation of various components such as metals, glass, and plastics from e-waste. Dismantling The dismantling process is mostly a manual disassembly process to remove the hazardous materials out of the e-waste before recycling, such as the removal of inks and toners from the printers, CR front panels from CRT screens, batteries from laptops, coolants from refrigerators, and the degassing and de-oiling of various electrical equipment (Kaya, 2018). The process is also used to reduce the cross contaminations and segregate different streams such as plastics, steel, aluminum, copper, and printed circuit boards (Abdelbasir et al., 2018). Automatic and semi-automatic dismantling systems have increased in recent years; however, manual dismantling is still the most widely used (Hsu et al., 2019). Dismantling improves the quality of streams/products for subsequent steps; it has low investment and reduces/eliminates dust. However, it becomes harder to dismantle new complex technologies; it is time-consuming and increases the risk of worker safety. It also presents a significant cost concern, especially in high labor cost economies. 35 Comminution/size reduction and size separation Similar to the metal recovery process in the mining industry, the comminution step involves reducing the particle size to increase liberation and provide proper particle size for subsequent processing/enrichment. The liberation of metal and non-metal fraction is achieved by using a combination of shredders (coarse crushing), hammer mills, and knife/cutting mills (fine crushing) (Bizzo et al., 2014; Ghosh et al., 2015; Mou et al., 2004; Ogunniyi et al., 2009; Otsuki et al., 2019; Veit et al., 2006; Wen et al., 2005; Zhang & Forssberg, 1999). The material breakage is achieved by impact and shear forces (Schubert & Hoberg, 1997). Recently, high voltage pulse fragmentation has also gained attention for size reduction as it reduces dust and provides liberation at a coarser size (Duan et al., 2015; Kumar et al., 2018b). Following comminution, screening, hydrocyclones, or air cyclones could be used to provide a product of a specific particle top size or for subsequent processing steps (Menad, 2016). The major drawbacks of the comminution process are the generation of dust and the loss of valuable metals with the dust. It could also decrease metal grade and cause the cross-contamination of streams if performed without proper dismantling. Physical separation The physical separation-based e-waste recycling has been gaining popularity due to its relatively low-cost operation. It recovers the metallic fraction without destroying the non-metal fraction, which improves non-metal fraction recycling potential and promotes the circular economy (Ning et al., 2017). Physical recycling of waste PCB is usually based on density separation, magnetic separation, or electrostatic separation. 36 Gravity separation is one of the most studied methods for separating metallic fraction from non-metallic fraction. A lab-scale float-sink test was able to recover 75% of metallic fraction using organic liquids (Nekouei et al., 2018). A recovery of 87% for copper and 67% for gold was obtained using Wilfley shaking table (Ventura et al., 2018). He et al. (2015) and Eswaraiah et al. (2008) used air classifiers with a recovery rate of over 90% for metals. Other equipment such as air tables, the Mozley concentrator, centrifugal separators, the Falcon concentrator, and jigs have also been used by various researchers for recovering the metallic fraction (Forssberg et al., 1998; Hanafi et al., 2012; Meng et al., 2018; Sarvar et al., 2015; Veit et al., 2014; Wen et al., 2005; Zhou et al., 2016). Magnetic separation to recover ferrous materials and conductivity-based separation, such as eddy current separation for aluminum and electrostatic separation for other metals, has also shown potential for metal recovery (Jiang et al., 2009; Li et al., 2007; Silvas et al., 2015). Guo et al. (2011) obtained over 90% recovery for copper using electrostatic separation with a copper grade of 71%, whereas Veit et al. (2005) used electrostatic separation to enrich the copper, tin, and lead concentration. Eddy current separators were used to recovery over 90% aluminum from electronic scrap (Zhang et al., 1998). Yoo et al. (2009) used magnetic separation to recover 83% of iron and nickel as magnetic concentrate from shredder printed circuit boards. The froth flotation process has also been researched to recover metals from waste PCB. The reverse flotation process is mostly used to recover the metallic fraction in the tailings, while floating the non-metallic fraction due to its mostly hydrophobic nature (Flores-Campos et al., 2017; Vidyadhar & Das, 2013, 2012; Xu et al., 2015). Flotation without any reagent has shown excellent metal recovery (Mäkinen et al., 2015; Ogunniyi & Vermaak, 2009). Flotation using kerosene and 37 terpenic oil showed a metallic recovery of over 84% at a particle size of below 75 µm (He & Duan, 2017), whereas a soapy collector was used in the flotation experiments conducted by Zhu et al. (2019). He & Duan (2017) reported a copper recovery of over 94% at optimum condition, whereas the recovery for Zhu et al. (2019) was only 47%, most likely due to larger particle size (- 1 + 0.5 mm). It was suggested that the main reason for low recovery was the poor liberation of copper from organic matter. These physical methods recover the metallic fraction and reduce the overall mass to be transported for further processing. As a result, they reduce the overall energy requirement for final processing by hydro- or pyrometallurgy, since less material will be processed by these energy-intensive processes. At the same time, physical methods are usually less energy-intensive. On the other hand, it requires the employment of proper dust control units if dry processing is used, while requiring proper water recycling systems if wet processing is employed. 2.7.2 End-processing End-processing involves techniques used to extract metals from the concentrate recovered from the pre-processing step. It increases the metal purity by separating them from one another. Three techniques used in this stage are pyrometallurgy, hydrometallurgy, and biometallurgy, and these are described in sections below. Pyrometallurgy Pyrometallurgy is one of the most common methods to recover metals from e-waste or e-waste concentrates (Hsu et al., 2019). The process includes incineration, smelting, or high temperature roasting to mainly recover non-ferrous metals such as copper, silver, gold, platinum, and 38 palladium. More than 70% of waste printed circuit boards are treated in smelters (Kaya, 2016). The smelting process involves melting the e-waste/concentrate in a high-temperature furnace to obtain a mixture of desired metals (Ma, 2019; Namias, 2013). Boliden’s Ronnskar smelter in Sweden, Glencore’s Horne smelter in Canada, and Umicore’s Hoboken smelter in Belgium are some of the leading smelters that treat electronic scrap combined with the copper concentrate obtained from traditional mining operations (Khaliq et al., 2014; Namias, 2013; Zhang & Xu, 2016). The smelting process is usually followed by the hydrometallurgical and electrowinning process to obtain pure metals (Abdelbasir et al., 2018). The major downside of the pyrometallurgical process is the loss of iron, aluminum, and non-metal fraction in the slag (Khaliq et al., 2014; Namias, 2013). It also poses a high risk due to the release of toxic metals and dioxins, which could be minimized by state-of-the-art emissions control systems (Hsu et al., 2019). The high energy requirement associated with this process could also be reduced by the energy released from the incineration of plastics and other organic fractions such as resins present in e-waste (Abdelbasir et al., 2018). Hydrometallurgy The hydrometallurgical process involves leaching out valuable metals from the e-waste/concentrates in solutions using various chemicals and then extracting target metals from the solution using precipitation, ion-exchange, solvent extraction, or adsorption, and finally using electrowinning for purification (Ashiq et al., 2019; Cui & Anderson, 2016; Ghasem & Khoramnejadian, 2015; Kamberović et al., 2018; Kim et al., 2018; Sivakumar et al., 2018; Tuncuk et al., 2012; Xu & Liu, 2016). Specific leaching agents such as sulfuric acid, cyanide, and thiosulfate are used to extract metals from e-waste. The metal is extracted from the 39 leachate/pregnant solution using processes such as precipitation, ion-exchange, solvent extraction, or adsorption (Ashiq et al., 2019). Hydrometallurgical processes are comparatively less energy-intensive, have lower capital cost, produce reduced air pollution, and are easily controlled (Veit et al., 2014). However, they require a high amount of toxic chemicals, they are slow and time-consuming, and they require grinding to obtain finer particle sizes for efficient dissolution, and mechanical pretreatment is also preferred before hydrometallurgical treatment (Abdelbasir et al., 2018; Khaliq et al., 2014; Namias, 2013). Biometallurgy Biometallurgy has been gaining much attention to recover metals from secondary sources such as solid and liquid wastes, including electronic waste (Chen et al., 2015; Garlapati, 2016; Sethurajan et al., 2018). The process has two main steps, bioleaching and biosorption (Hsu et al., 2019). Bioleaching uses microorganisms such as acidophilic bacteria, cyanogenic heterotrophs, and/or acid-producing heterotrophs to selectively convert insoluble metal forms to soluble metals (Işıldar, 2016; Sethurajan et al., 2018). The step depends on several factors such as the type of bacteria, culture media, particle size, pH, and metal concentrations. Biosorption is the process of adsorption of metals from the leach solution on the cell walls of microorganisms (Sethurajan et al., 2018). Baniasadi et al. (2019) have summarized recent studies where biometallurgy was used to extract copper, zinc, aluminum, lead, tin, gold, chromium, and nickel from waste printed circuit boards while lithium, manganese, zinc, cobalt, cadmium, and nickel were extracted from spent lithium, nickel-cadmium, or zinc-manganese batteries. Biometallurgy was also used to obtain zinc and yttrium from CRT screens, whereas copper, gold, and silver were extracted from SIM cards. Wang 40 et al. (2009) showed that in some instances, up to 99.9% of copper present in the printed circuit board was solubilized at - 1.0 + 0.5 mm size fraction. The biometallurgy process has lower operating costs and significantly lower energy consumption. It reduces the usage of chemicals and provides an eco-friendly solution for metal recovery (Baniasadi et al., 2019; Namias, 2013; Valix, 2017). However, the process is time-consuming due to the slower kinetics (Işıldar, 2016). The pyrometallurgical, hydrometallurgical, and biometallurgical routes are widely used to recover metallic fractions from the waste PCB. However, the recycling of non-metal fraction through these routes is not recommended as it degrades the mechanical and chemical properties of the non-metal fraction (Ning et al., 2017). 2.8 Non-metal fraction As discussed in the previous section, the metallic fraction in the waste printed circuit boards is one of the major economic drivers for the recycling industry (Hadi et al., 2015). However, the separated non-metal fraction (NMF) that accounts for approximately 70% of the total weight is usually sent to the landfills (EPA, 2012; Ghosh et al., 2015; Hadi et al., 2015). Duan et al. (2016) reported that the total amount of NMF would reach 279 kT by 2020 in China without accounting for the waste NMF produced during printed circuit board manufacturing. 2.8.1 Non-metal fraction composition Several studies have suggested that the NMF consists of fiberglass (65% by wt.), epoxy resins (32% by wt.), and residual metals (copper and other metals) (Duan et al., 2016; Muniyandi et al., 2014; Zheng et al., 2009). Zheng et al. (2009) showed that fiberglass concentration is highest in 41 the fine fraction, whereas the resins are mostly concentrated in coarse fractions. An XRF analysis of the NMF obtained from the waste PCB showed a high concentration of silica, calcium oxide, and alumina, which is mostly from the fibers present in the circuit boards with a trace amount of bromine, copper oxide, magnesium oxide, and other metallic oxides (Muniyandi et al., 2014). Duan et al. (2016) used XRF analysis to show that, on average, NMF contains 2.95% copper, 0.35% lead, 0.41% tin, 0.07% nickel, 0.04% zinc, 0.02% manganese, and 0.02% chromium as residual metals. It should be noted that these studies were performed on waste PCB obtained from personal computers containing FR-4 boards only. Research in the field of characterization of the NMF and associated risks with its disposal are limited (Duan et al., 2016). A review of different literature sources has shown that the only study that attempted separation of NMF obtained from a waste printed circuit board recycling plant was from the Anhui province in China. In this study, a combination of eddy current and electrostatic separation was used to separate metals from non-metal fraction (Wang et al., 2018; Zhang et al., 2018; Zhang et al., 2017). However, the only point of this study was to discuss the residual metal concentration in NMF. All other research is usually limited to the waste printed circuit boards from a particular type of EEE unit. A concentration of 6–12% of bromine and 0.02–1% of chlorine has been reported in the NMF obtained from FR-2, FR-3, and FR-4 in the study by Duan et al. (2016); however, this study was limited to PCB obtained from eleven electronics products. The concentration of polybrominated diphenyl ether (PBDEs) in waste PCB is reported to be 3045 mg/kg (Zhou et al., 2013), whereas the concentration in the NMF after processing is not available in any literature. Similarly, the concentration of polychlorinated biphenyls is limited to the soil or dust in the area around the e-waste recycling centers but not in the NMF itself. The polychlorinated 42 biphenyls concentration in the twenty-two tree bark samples from an e-waste recycling area in China showed a concentration of 0.112 mg/kg of dry sample (Wen et al., 2009). Landfilling is the main disposal route for the non-metal fraction after the processing of waste printed circuit boards. However, the issues associated with NMF landfilling are not well reported in the literature. Studies are limited to the PCB obtained from individual and specific EEE and without any prior processing. An analysis from milled waste PCB shows the presence of 133 mg/L lead and 22 mg/L cadmium (Bizzo et al., 2014), whereas leaching characteristics for the NMF have not been reported. It was also reported that the NMF has a gross calorific value of 11.63 GJ/t compared to 4.88 GJ/t for the whole waste PCB, when the NMF was separated at a density of 2.89 g/cm3 using organic liquids. Guanghan et al. (2016) suggested that the NMF does not decay for a long time, and it also reduces the air permeability of the soil and pollutes the groundwater due to the presence of heavy ions and curing agents. The concentration of polychlorinated dibenzo-p-dioxin and dibenzofurans (PCDD/F) and polybrominated dibenzo-p-dioxin and dibenzofurans (PBDD/F) in unheated printed circuit boards was 4.7 ng Toxic Equivalent Quotient (TEQ)/kg and 16000 ng TEQ/kg (Duan et al., 2011). The PCDD/F concentration reported by Wen et al. (2009) in the twenty-two tree bark samples was 1800 pg/g (19.2 pg WHO-TEQ/g). The PCDD/F concentration in the soil and snails near various e-waste recycling sites in China was 53.39 pg WHO-TEQ/g, and 75.47 pg WHO-TEQ/g, respectively (Liu et al., 2008). The PCDD/F concentration from the soil and combusted residue from the e-waste recycling site in Guiyu, China, was 0.8-506 pg WHO TEQ/g in various sample sources (Leung et al., 2007). 43 2.8.2 Recycling of non-metal fraction According to the Environmental Protection Agency (2012), the recycling of NMF from waste PCB is not usually practiced, and up to 94% is discarded in landfills. Some researchers have suggested alternative uses of NMF as secondary materials in various applications (Guo et al., 2009; Marques et al., 2013; Ning et al., 2017; Sohaili et al., 2012). Zheng et al. (2009) have suggested using NMF as reinforcing fillers in polypropylene composites that would enhance their tensile strength and improve their heat resistivity. Mou et al. (2005) suggested using NMF to manufacture composite boards with enhanced strength due to its compatibility with epoxy resin that can be used in furniture, automobiles, and decorative materials. In contrast, Guo et al. (2010) have used NMF in producing wood-plastic composites. The NMF was also used with the recycled plasticized polyvinyl chloride from waste wires and cables to produce a composite with enhanced strength (Das et al., 2019). Hadi et al. (2015; 2013) have suggested that the presence of carbonaceous and siliceous materials in NMF provides an opportunity for it to be used as an adsorbent to remove pollutants from aqueous solutions. Rajagopal et al. (2016) and Ke et al. (2013) showed that the NMF from waste PCB could also be used to prepare activated or porous carbon with high surface areas. One of the challenges in using the NMF as composites or filler is its heterogeneous composition. The presence of inorganics in the NMF decreases its usability because the bundles of fiberglass can form higher stress concentration points that would reduce the strength of composites (Zhang et al., 2017; Zhang et al., 2017). The removal of inorganics from the NMF increases the flexural strength, flexural modulus, and impact strength of the high-density polyethylene composite and improves its usability. Wang et al. (2018) suggested that separating the components of NMF is 44 necessary to increase its reuse. The organics could be used as a filler in composite or for energy recovery. The fiberglass can be used in construction/building materials, and residual metal can be sent for metal purification. Guo et al. (2009) listed four ways to recycle the NMF by chemical or thermal methods. These methods are pyrolysis, gasification, supercritical fluid depolymerization, and hydrogenolytic degradation, with the primary goal of converting the polymers in the NMFs into chemical feedstocks or fuels. The pyrolysis process converts the organic resins into oil and gases, and the fiberglass is reported to the char residue. Major gases produced in the process are carbon dioxide, carbon monoxide, and methane, whereas phenol and its derivatives are the main oils produced. Zheng et al. (2009) used a fluidized bed in combination with air cyclones at temperature ranges from 400 to 6000C to recover high-value fiberglass from the NMF, but acknowledged that the strength of fibers had been severely weakened. The gasification process converts the organic matter into synthesis gas (carbon monoxide and hydrogen) at reaction temperatures up to 16000C that can then be used as fuel. Supercritical water, methanol, or ammonia have been used to decompose resins, but the method requires high temperature and pressure (Guo et al., 2009). Yousef et al. (2017) extracted the woven fiberglass at a temperature of 500C with dimethylformamide chemical and ultrasonic treatment; however, the average strength of the recycled fiberglass decreased by 48%. The hydrogenolytic degradation process can solubilize epoxy resin with a hydrogen donor such as phthalic anhydride at 3400C in two hours (Braun et al., 2001). One of the most common disadvantages of these chemical or thermal processes is the higher operations cost and environmental risks associated with the by-production of toxic chemicals. In 45 comparison, physical recycling methods are relatively simple, environmentally friendly, and have lower energy and operating costs. However, the physical separation of individual components of NMF is more complicated than the chemical treatment due to the complex structure of various electronic parts and their encapsulation. 2.8.3 Physical separation processes There are several different methods to separate materials based on the physical properties of particles to segregate it into two or more streams. These properties are their size, magnetic behavior, density, conductive properties, and surface properties. A process could use the differences in these properties for separation. Some of the most common properties widely used in the mineral processing/mining industry are discussed in this section, along with their applicability for non-metal fraction recycling. Studying the possibility of physical recycling of NMF is one of the main objectives of this research. Size classification Size classification relies on the difference in sizes of various particles. Researchers have shown that fiberglass concentration is highest in the fine fraction (- 75 µm), whereas the resins are mostly concentrated in coarse fractions. Thus, the loss on ignition for the coarser fraction is higher than the finer fractions (Yang et al., 2019; Zhang et al., 2017; Zheng et al., 2009). The liberation of inorganic fiberglass from the resin would require further fine grinding of the NMF material, which is an energy-intensive process. However, the differences in the organic and inorganic content in different size fractions for non-metal fractions without additional grinding may or may not be 46 significant enough for separation. Research utilizing size classification to separate the organic and inorganic stream and quantify the process outputs has not been reported in any literature. Gravity separation Gravity separation is one of the most common low-cost physical processing methods and has been used for the separation of metals from non-metals (Eswaraiah et al., 2008; Forssberg et al., 1998; Hanafi et al., 2012; He at al., 2015; Meng et al., 2018; Nekouei et al., 2018; Sarvar et al., 2015; Veit et al., 2014; Ventura et al., 2018; Wen et al., 2005; Zhou et al., 2016). It has been successfully used in the separation of different types of plastic wastes. Processes such as air classifiers, jigs, hydrocyclones, shaking tables, and float-sink have been widely studied in the separation of different types of plastics (Bauer et al., 2018; Ruj et al., 2015; Serranti & Bonifazi, 2019). Previous researchers have utilized heavy liquids of higher densities (~2.89 g/cm3) to separate the metallic fraction from the NMF (Bizzo et al., 2014); however, the application of heavy liquid/gravity separation to separate various components of NMF in waste circuit boards has not been studied before. The float-sink procedure using heavy liquids has been used to separate waste plastics into <1.0, 1.0–1.1, and 1.1–1.2 specific gravity ranges by Lee (2007). Hori et al. (2009) used jigs with water pulsation to separate polyvinyl chloride (PVC), polyethylene terephthalate (PET), and polyethylene (PE) with a specific gravity difference as low as 0.11. Choi (2004) used gravity separation to recover PVC (specific gravity 1.32–1.42) from a mix of polyolefin plastic waste (specific gravity 0.90–1.06). In contrast, Dodbiba et al. (2002) used a drum separator at a speed of 1 RPM to separate at a specific gravity of 1.11 to separate PET from polypropylene (PP). 47 Pongstabodee et al. (2008) used a three-stage float-sink method to classify six different plastics into low (specific gravity 0.90–1.00), medium (specific gravity 1.00–1.20), and high (specific gravity 1.20–1.40) density ranges. The density of various components of NMF is listed in Table 2-8. These differences in the densities provide the prospect of producing a relatively cleaner organic and inorganic stream to upgrade the quality of both and improve the utilization of these products. Further chapters investigate the applicability of gravity separation to separate components of the NMF using heavy liquids. Table 2-8: Density of various components of the non-metal fraction Components Density [g/cm3] Reference Epoxy fiberglass laminate (FR-4) 1.94 Li et al. (2014) Epoxy resin 1.11–1.23 Wang et al. (2011) Fiberglass 2.48–2.70 Shrivastava (2018) Phenolic paper laminate (FR-2) 1.55 Li et al. (2014) Phenolic resin 1.2–1.4 Dixit et al. (2016) Cotton/paper fiber 1.5–1.6 Foulk et al. (2006) & Wakeham (1949) Residual metals > 2.7 The Engineering ToolBox (2004) Float-sink test The float-sink test is the most common technique used to determine the efficiency of gravity separation for coal samples, where the coal sample is subjected to increasing density liquids, and 48 the floated-and-sunk fractions are analyzed for their ash content (mineral content in organic coal). The yield and ash content at each density is used to plot so-called washability curves. Researchers have shown that the separation is formidable at a given density if the near density materials (material in the ±0.1 specific gravity range of the separation density) are > 25%. However, more efficient separators could operate in a narrower ±0.05 specific gravity range (Laskowski & Walters, 1987; Leonard & Hardinge, 1991). The data obtained from the float-sink test is further utilized to determine the index representing the ease of separation (Holuszko, 1994). The efficiency of gravity separation and the ease of coal washing highly depends on the particle size, ash content, float-and-sink product properties, and near-gravity materials. Washability indices Several authors have developed indices to interpret the washability data and to quantify the ease of washing. These indices include the degree of washing (N), the washability number (W), the index of washability (IW), and the near-materials index (Aksogan Korkmaz & Bentli, 2017). The degree of washing and the washability number indicates the differences in the ease of coal washing at the optimum separation conditions. Easy-to-wash coal has a higher washability number (W). The degree of washing and washability numbers are calculated using Equation 2-2 and Equation 2-3 (Holuszko & Grieve, 1990; Holuszko, 1994). 𝐷𝑒𝑔𝑟𝑒𝑒 𝑜𝑓 𝑤𝑎𝑠ℎ𝑖𝑛𝑔 (𝑁) = 𝑤 (𝑎 − 𝑏)𝑎 Equation 2-2 where, a is ash content in the feed 49 b is ash content of clean coal at a given separation density w is the yield of clean coal at a given separation density 𝑊𝑎𝑠ℎ𝑎𝑏𝑖𝑙𝑖𝑡𝑦 𝑛𝑢𝑚𝑏𝑒𝑟 (𝑊) = 𝑁𝑜𝑝𝑡𝑏𝑜𝑝𝑡 × 10 Equation 2-3 where, Nopt is the optimum degree of washing bopt is the ash content of clean coal at the optimum degree of washing One of the issues with the washability number is that it does not provide a mathematical expression to precisely determine the ease of washing (Govindarajan & Rao, 1994). The index of washability (IW) was developed based on the recovery of ash and non-ash material in clean coal to determine the amenability of coal towards washing. The index of washability can theoretically vary from 0 to 100, but it ranges from 20 to 80 for most coals. The recoveries of ash (RA) and non-ash (RN) forming materials are estimated by Equation 2-4 and Equation 2-5. RA and RN values plotted against X fit cubic functions shown in Equation 2-6 and Equation 2-7 (Govindarajan & Rao, 1994). 𝑅𝑁 = 100𝑋(100 − 𝐶𝐴)100 − 𝐻𝐴 Equation 2-4 𝑅𝐴 = 100 𝑋𝐶𝐴𝐻𝐴 Equation 2-5 𝑅𝑁 = 𝑎𝑋 + 𝑏𝑋2 + 𝑐𝑋3 Equation 2-6 50 𝑅𝐴 = 𝑝𝑋 + 𝑞𝑋2 + 𝑟𝑋3 Equation 2-7 where, X is the cumulative fractional weight of floated coal CA and HA are the ash contents of the floated fraction and feed, respectively a, b, c, p, q, and r are fitted constants The fitted values are then used to estimate the index of washability from Equation 2-8 (Govindarajan & Rao, 1994) and to provide a precise evaluation of the ease of coal washability. The index of washability is a single number that could be used to evaluate the amenability of coal towards gravity separation and could also be used to compare different samples. 𝐼𝑊 = [6𝑎 + 4𝑏 + 3𝑐 − 600][6(𝑎 − 𝑝) + 4(𝑏 − 𝑞) + 3(𝑐 − 𝑟)]3600 𝐻𝐴 100 Equation 2-8 The ease of coal washing is also highly dependent on the amount of near-gravity material (amount in ±0.1 specific gravity range of the separation density). Two coals with the same index of washability but with different amounts of near-gravity material would differ in the ease of processing. Coal washing at a given density might be easier than at another density due to the difference in the amount of near-gravity material. Majumder & Barnwal (2004) used Equation 2-6 and Equation 2-7, provided by Govindarajan & Rao (1994), to estimate the near-gravity material index (NGMI) using Equation 2-9. NGMI increases from 0 to 1 for easy-wash to difficult-wash coal. The NGMI, combined with the index of washability, could precisely evaluate the coal washability characteristics. For difficult-to-wash Indian coals, the index of washability varied from 51 26 to 40, and NGMI varied from 0.35 to 0.55 at 1.45 specific gravity (Majumder & Barnwal, 2004). These indices will determine the ease of washing for the NMF obtained from waste printed circuit boards recycling. 𝑁𝐺𝑀𝐼 = ∫ [(𝑎𝑋 + 𝑏𝑋2 + 𝑐𝑋3) − (𝑝𝑋 + 𝑞𝑋2 + 𝑟𝑋3)]𝑑𝑋 𝑋2𝑋1∫ [(𝑎𝑋 + 𝑏𝑋2 + 𝑐𝑋3) − (𝑝𝑋 + 𝑞𝑋2 + 𝑟𝑋3)]𝑑𝑋 10 Equation 2-9 where, X1 and X2 are the cumulative fractional weight at ±0.1 specific gravity range of the separation density. Magnetic separation Magnetic separation has been mostly used to recover ferrous materials from crushed waste printed circuit boards (Cui & Forssberg, 2003; Guo et al., 2011; Silvas et al., 2015; Veit et al., 2006). Yoo et al. (2009) used magnetic separation to recover 83% of iron and nickel as the magnetic concentrate from shredder printed circuit boards. In NMF recycling, magnetic separation was used to recover the residual magnetic material from the NMF (Wang et al., 2018). It was shown that the magnetic concentrate accounted for nearly 6% of the total NMF feed and the recover concentrate had a low organic content (12%). It was suggested that the magnetic separation could be used to recover residual magnetic materials from the NMF but not to separate organic resins and inorganic fiberglass as they both would report to the tailings due to their diamagnetic properties. 52 Electrical separation Similar to magnetic separation, the electrical properties (conductivity) have been widely used to separate metals from the non-metals using electrostatic separators and eddy current separator (Cui & Forssberg, 2003; Guo et al., 2011; Veit et al., 2005; Zhang et al., 1998). In NMF recycling, researchers have shown that the triboelectric separation can be used to separate the organic resins from the inorganic fiberglass. Zhang et al. (2017) and Yang et al. (2019) used triboelectric separation to separate inorganics from the non-metal fraction to improve the quality of the product. Overall, a concentrate yield of 47% was achieved with an organic content of 69%, combustible recovery of 59%, and an upgradation ratio of 1.27 by Zhang et al. (2017). In the case of Yang et al. (2019), an upgradation ratio of 1.17 was achieved. It should be noted that the separation based on electrical properties is only feasible for completely dry materials and a plant using dry separation technology as the upstream process. A plant utilizing wet (water-based) separation would require drying the metal recycling rejects completely before the electrical separation of NMF. Froth flotation Froth flotation uses the difference in the surface properties to separate different particles from each other. Researchers have shown the difference in the floatability of metals and non-metal fractions, hence, the froth flotation process could be used to recover metals from waste circuit boards with or without the use of additional reagents (He & Duan, 2017; Mäkinen et al., 2015; Ogunniyi & Vermaak, 2009; Zhu et al., 2019). 53 However, the applicability of the froth flotation process to separate the organic resins and inorganic fiberglass has not been studied in any literature. Since the fiberglass is mostly encapsulated in epoxy resins, the unliberated fiberglass would mostly be hydrophobic due to the presence of organic resins on the surface. Only the fully liberated fiberglass would be separated by froth flotation due to its hydrophilic characteristics. One of the most common ways of measuring the wetting behavior of particles is by contact angle measurement. The contact angle depends on the surface tension of the solid, liquid, and gas interface; however, the contact angle measurement is only possible for smooth and coarse particles. The surface tension at three interfaces is highly affected by the surface properties of the solids, and surface energy is one of the most critical surface properties (Ali et al., 2013). The surface energy of the solids can be measured using inverse gas chromatography (IGC). IGC has been regularly used to measure the surface energy in various polymers and in the pharmaceutical industry. The surface energy of the particles can be divided into dispersive and specific components and is measured using the interaction of non-polar and polar organic solvents with the solid particles. The solid sample is placed into a column, and a fixed number of moles of organic probe molecules, depending on the surface coverage required, is passed through the column using an inert carrier gas, and the time taken for the molecule to exit the column is measured. The dispersive component of the surface energy is measured based on the Schultz method from Equation 2-10 and Equation 2-11 and using non-polar probe molecules such as nonane, octane, heptane, and hexane. 54 𝑉𝑁 = 𝑗𝐹𝐶 (𝑡𝑅 − 𝑡0) Equation 2-10 𝑅𝑇𝑙𝑛 𝑉𝑁 = (2 𝑁𝐴 √𝛾𝑆𝐷) (𝑎 √ 𝛾𝐿𝐷) + C Equation 2-11 where, VN is the net retention volume of the probe molecule (ml) j is the James-Marin compressibility factor FC is the flow rate of carrier gas (ml/min) tR and t0 are the gross and dead retention time (retention time is the time taken for the probe molecule to exit from the column). The dead retention time is measured using an inert gas. R and T are gas constant (8.314 J/K/mol) and absolute temperature NA is the Avogadro’s number a is the cross-sectional area of the probe molecule (m2) 𝛾𝑆𝐷 and 𝛾𝐿𝐷 are the dispersive free energy of the solid and probe molecules (mJ/m2) When the value of RTlnVN is plotted against the a √𝛾𝐿𝐷 for a series of non-polar probe molecules, the slope of the resulting line (alkane line) provides the dispersive surface energy at a given surface coverage of the studied sample. In this method, the vertical distance between the points of the polar probe molecule and the alkane line is the specific Gibbs free energy. The specific Gibbs free energy is a function of the acid-base (specific) interactions of the solid and probe molecule and can be related by Equation 2-12. By 55 passing two monopolar acidic and basic probe molecules such as dichloromethane and ethyl acetate through the sample column, the specific free energy of the solids is measured using Equation 2-13. − ∆𝐺 = 2 𝑁𝐴 𝑎(√𝛾𝑆+𝛾𝐿− + √𝛾𝑆−𝛾𝐿+) Equation 2-12 𝛾𝑆𝑆𝑃 = 2(√𝛾𝑆+ 𝛾𝑆−) Equation 2-13 where, ∆𝐺 is the specific Gibbs free energy (mJ/mol) 𝛾𝑆+ 𝑎𝑛𝑑 𝛾𝑆− are the Lewis acid and Lewis base component of specific surface free energy for solids (mJ/m2) 𝛾𝑆+ 𝑎𝑛𝑑 𝛾𝑆− are the Lewis acid and Lewis base component of specific surface free energy for probe liquid (mJ/m2) 𝛾𝑆𝑎𝑏 is the specific surface free energy for solids (mJ/m2) Once the dispersive and specific free energy of the solids are determined, the work of adhesion of the solid with any liquid can be estimated using Equation 2-14. In the case of flotation, the work of adhesion with water is studied. An increase in the surface free energy increases the work of adhesion with water and therefore renders the particle more hydrophilic/wettable (Ali et al., 2013). 𝑊𝑎𝑑ℎ = 2 (√𝛾𝑆𝐷 𝛾𝐿𝐷 + √𝛾𝑆+ 𝛾𝐿− + √𝛾𝑆− 𝛾𝐿+) Equation 2-14 56 The degree of hydrophilicity (hydrophilicity index) of a given sample can also be estimated using the specific and dispersive component of the surface free energy using Equation 2-15. 𝐷𝑒𝑔𝑟𝑒𝑒 𝑜𝑓 ℎ𝑦𝑑𝑟𝑜𝑝ℎ𝑖𝑙𝑖𝑐𝑖𝑡𝑦 (ℎ𝑦𝑑𝑟𝑜𝑝ℎ𝑖𝑙𝑖𝑐𝑖𝑡𝑦 𝑖𝑛𝑑𝑒𝑥) = 𝛾𝑆𝑎𝑏𝛾𝑆𝑡 = 𝛾𝑆𝑎𝑏(𝛾𝑆𝐷+ 𝛾𝑆𝑎𝑏) Equation 2-15 One of the benefits of using an IGC for estimating the hydrophilicity/hydrophobicity of particles is that it can be used on fine particles, powders, and rough/uneven surfaces. It can also be used to understand the sample surface energy heterogeneity by estimating the free energy at different surface coverage. At very low coverage (infinite dilution), the probe molecule only interacts with high energetic sites and provides a high energy value. Increasing the overall surface coverage provides an averaged value as the probe molecule will interact with all surfaces regardless of their surface energy (Mohammadi-Jam & Waters, 2014). Researchers have shown that the IGC could be used to measure the surface energy of mineral particles at different surface coverage and can be directly correlated with their flotation behavior (Ho et al., 2010). Mohammadi-Jam & Waters (2016) and Mohammadi-Jam et al. (2014) showed that decreasing the surface energy of particles decreased the work of adhesion with water and increased the floatability of particles. Ali et al. (2013) have shown that the surface energy of quartz was higher than that of galena, making quartz comparatively more hydrophilic. Niu et al. (2018) have shown that the surface energy is directly correlated with flotation responses, and a higher hydrophilicity index leads to a lower flotation recovery. The research also showed that the flotation recovery was governed by the surface energy, hydrophilicity index, and work of adhesion. The surface characteristics of NMF relevant to flotation were tested using IGC without any size reduction in the further chapter. The test is performed to observe if any differences exist in the 57 surface energy of various NMF particles that might provide some preliminary information regarding their response to flotation. This type of assessment of NMF using IGC has never been studied before. 2.9 Loss on ignition Any of the physical or chemical processing methods described in the previous section had to be assessed for their efficiency. In minerals, the metal grade is measured, whereas, in coal, the ash content is used for the analysis. In the case of the NMF, loss on ignition (LOI) is one of the most common methods to estimate the content of organic matter in the NMF or in waste printed circuit boards, and it can be used to determine the efficiency of separation of the method/process used. The LOI is a thermogravimetric method where a given amount of sample is burned in the presence of air for a particular time at a specific temperature. The weight of the residue will effectively provide the total weight loss during the combustion process, i.e., loss on ignition. Critical variables for estimating the LOI are the mass of the sample used, the ignition temperature, combustion duration, and particle size. There are several standard procedures by the American Society for Testing and Materials (ASTM) that could be either directly used or adopted to estimate the LOI for NMF or waste PCB. Table 2-9 provides a list of different ASTM standard test conditions to estimate loss on ignition or equivalent thermogravimetric analysis for various types of materials that contain organic fraction and could be relevant to LOI determination in the NMF. Method D7348 – 13 or D3174 – 12 requires pulverizing the sample to 250 µm size (ASTM International, 2012a, 2013b), but the presence of resin and fiberglass make it harder to pulverize the NMF to a fine size, whereas the sample mass requirement for D2974 – 14 is comparatively 58 high to be feasible for the NMF especially for laboratory-scale test processes (ASTM International, 2014). One method of pulverizing the polymer sample is cryogenic grinding, where the sample is ground in a small chamber with liquid nitrogen circulating the grinding chamber (Retsch, 2009). This method is mostly used for tissue, plastics, polymers, food, wood, bones, and other soft materials. However, the set-up is relatively expensive and not available at every laboratory. Method D4963 – 11 and D2584 – 18 are favorable for NMF testing, but these are designed for pure materials and might not translate directly for a mixture (ASTM International, 2011, 2018). Table 2-9: ASTM standards related to the LOI test or equivalent for different materials Designation Material Sample mass [g] Particle size [µm] Temperature [0C] Total time [h] D7348 – 13 Combustion residue 1 250 750/950 3 D4963 – 11 Fiberglass strands 6 - 625 0.5 D2584 – 18 Cured reinforced resin 5 - 565 - D2974 – 14 Peat or organic soils 50 - 440/750 - D3174 – 12 Coal or coke 1 250 750/950 3 To overcome these challenges, various researchers have used a variation of these methods for determining the organic and inorganic contents in waste printed circuit boards or the NMF. Table 2-10 shows a list of methods/processes used by various researchers to determine organic and inorganic contents in NMF or waste printed circuit boards. 59 Table 2-10: Methods used for organic content determination by various researchers Literature Sample mass [g] Particle size [µm] Temperature [0C] Total time [h] Bizzo et al. (2014) 5 - 4000 700 - Eswaraiah et al. (2008) - - 1400 650 1 Iji & Yokoyama (1997) - - 500 2 Nekouei et al. (2018) 0.3 up to 800 750 1 Wang et al. (2010) - up to 250 900 - Zheng et al. (2009; 2009) - up to 710 500 3 Zhang et al. (2017) - - 1400 200 - It can be seen in Table 2-10 that the temperature used for estimating the organic content varied widely from 200 to 9000C, and time variation was from one hour to the time until the sample reaches a constant mass. Hence, it becomes necessary to establish a standard test parameter for the study that could estimate the total organic and inorganic content in the tested NMF and that could be used for determining the efficiency of the process. 2.10 Summary Electronic waste has been a growing concern around the world. The amount of e-waste generated has been growing at a 3–4% rate and is expected to reach 120 million tonnes annually by 2050. If this waste is recycled correctly, it could offer an opportunity to recover precious metals with an estimated annual value of fifty-five billion Euros. 60 Among all the e-waste streams, the waste PCB is one of the most valuable components of any EEE and has the highest recycling potential; hence, the NMF obtained from the waste PCB was selected for this study. Various routes are currently being implemented to recover metals from the e-waste stream. Physical separation methods have been focused on separating the metals from the non-metals, thus reducing the amount to be processed in subsequent energy-intensive and cost-intensive stages. The pyrometallurgical route is still the most common process for metal extraction from e-waste, and smelters worldwide are adding e-waste with the concentrates derived from mining operations. The hydrometallurgical and biometallurgical processes have been researched intensively in recent years due to their lower energy intensity, cost-effectiveness, environmental friendliness, and selectivity. However, these methods have also been shown to have drawbacks. The NMF obtained from the processing of waste PCB presents a significant proportion by weight and contains residual metals and fiberglass that could provide an economic incentive for recycling. It also contains heavy metals such as lead and toxic flame-retardant chemicals such as PBDEs that, if not treated properly, will cause environmental damage and health and safety issues for humans. One of the challenges for the recycling of the NMF is the relatively low economic value of its components; hence, opting for a low-cost processing technique could be a critical component for the successful recycling of the NMF. Generally, physical processing techniques based on density, magnetic behavior, conductivity, or surface properties have lower operating cost than chemical or thermal processing such as hydro or pyrometallurgy. The physical properties of the NMF, as suggested by various researchers, does provide an opportunity to explore the applicability of physical processes for separating its components. 61 Chapter 3: Characterization of NMF from processed waste PCB 3.1 Introduction One of the significant barriers to the circular economy of electronic waste is the lack of recycling of the NMF. The metallic fraction in e-waste is the focus of recycling for major operations due to its higher monetary value, whereas the NMF is mostly sent to landfills because of its lower value. An efficient recycling system that recovers metals and provides a solution for the non-metal fraction would help promote the circular economy. Since the printed circuit board (PCB) is one of the most valuable components of any EEE and has the highest recycling potential, the NMF obtained from the waste PCB was selected for this study. Most of the research regarding waste PCB recycling is focused on the analysis and recovery of metals. To increase the recycling of the NMF, it is necessary to understand and establish the benefits of NMF recycling. However, this information is either unavailable in literature or limited to individual circuit boards. The primary objective of this research is characterizing the non-metal fraction obtained from the processing of waste PCB to promote recycling, and one of the sub-objectives of the research was to NMF characterization to understand the economic incentives of its recycling. To achieve this sub-objective, the research questions addressed in this chapter are, • What are the characteristics of the NMF obtained after printed circuit board recycling at the pilot/industrial scale? • How could the recycling of the NMF provide an economic incentive to the recycling industry? 62 • What are the issues related to the NMF following its improper disposal? This chapter provides a comprehensive characterization of the NMF related to its value and environmental concerns upon its disposal. The relevant information for the waste PCB prior to any processing is usually readily available in literature. Since most waste PCB is processed in some fashion before disposal, the characterization of the separated NMF is more appropriate for evaluating characteristics for suitable end-of-life solutions and the issues associated with improper disposal after recycling. A version of this chapter has been published in the Waste Management journal. Additional details related to the particle size distribution analysis, quantification of fiberglass, and environmental risks due to the presence of polychlorinated biphenyls and dioxins and furans are added in the current chapter. 3.2 Methodology This section provides details about the samples used for this study and the description of characterization tests performed on the samples. The tests performed were selected to establish a benchmark for an industrial waste printed circuit board operation, not available in technical literature. Simultaneously, the tests were selected to emphasize the need and benefits of the recycling of NMF and the issues associated with the improper disposal of NMF. As indicated earlier, similar studies were conducted in the past but were limited to waste PCB without any prior processing. 63 3.2.1 Non-metal fraction sample The NMF used for this study was obtained from the waste PCB processing pilot plant located in Richmond, British Columbia, owned by Ronin8 Technologies Limited. The company aims to recirculate the metals and non-metals from the printed circuit boards to manufacture new products, creating a circular economy. This facility focuses on the recycling of waste PCB obtained from various electronics. The plant processes a mixture of FR-2 and FR-4 printed circuit boards obtained from computers, printers, televisions, printers, servers, cellphones, and other household electronics. Figure 3-1 shows the process flowsheet adopted at the Ronin8 recycling center. The initial stage of size reduction is achieved by using a combination of the shredder and hammer mill. The crushed material is suspended in water and is separated into metal and non-metal streams using a wet shaking table, whereas middling is split into + 0.85 mm and – 0.85 mm streams. The coarse middling stream is sent for further size reduction, whereas the fine middling stream is circulated through the patented sonic chamber technology. The chamber uses low frequency and high amplitude sound waves to liberate the metals from the non-metals. The liberated material is recirculated back to the shaking table. The separated streams are dewatered, air dried, and stored in 750 kg bulk bags for shipment. The metal concentrate is shipped to a smelter for metal refining, whereas the company explores the best possible usage for the non-metal rejects. The company is in the process of designing a commercial plant with a nominal throughput of 10,000 tonnes per annum (1.2 tonnes per hour). The mass yield for the metal concentrate is reported to be 36% with 93% metal recovery, whereas 7% of the metals are lost in non-metal fraction (Ronin8 Technologies Ltd, 2018). 64 Figure 3-1: Process flowsheet at Ronin8 Technologies Limited Drawn from Ronin8 Technologies Ltd. report (2018) A representative sample of 25 kg NMF was collected using the cone-and-quarter method from a 750 kg bulk bag and was oven dried at 60°C for 96 hours to remove any residual moisture. The oven dried NMF, as shown in Figure 3-2, was then used for all subsequent test work. 3.2.2 Test procedures Particle size distribution To establish the particle size distribution of the received NMF sample, the particle size distribution analysis using screening was conducted, following the standard √2 sieve series. One subsample of approximately 300 g was split from the dried sample for screening using a Ro-Tap shaker. The Circuit boardsSize reductionScreening @ 3 mmNon-metal tailingsMetal concentrateOversizeWet shaking tableMiddlingsScreening @ 0.85 mmSonic liberationOversizeUndersizeUndersize65 screening was performed for five, fifteen, thirty, and sixty minutes to provide sufficient time for the fiberglass to pass through a given screen size. The size distribution was then plotted, and 80% and 50% cumulative passing size was determined. Figure 3-2: Oven-dried NMF used for subsequent tests Metal content analysis To establish the potential economic benefit of NMF recycling, metal content analysis was performed. Previous research has shown the presence of residual metals in the NMF. Approximately 20 g of subsamples were split from the dried NMF and each size fraction and were sent to an external laboratory for metal assay. The metal content was determined using standard EPA200.2/6020A for metals and EPA200.2/1631E for mercury. This procedure is designed to determine total recoverable elements from water and solid, except silica (Martin et al., 1994). Fiberglass content analysis The major constituents of the NMF are the residual metals, fiberglass, and resins. The fiberglass present in the NMF could be used in preparing composites, as reported in the literature. 66 To ensure the complete removal of the organic materials, the coal ash content analysis procedure, as defined by the American Society for Testing and Materials D3174 – 12, was used (ASTM International, 2012a). Approximately 1 g of dried NMF as well as screened size fractions were analyzed using the ASTM procedure. This test was performed in triplicate, and the average residual mass was then used for calculation. Then, the fiberglass content in the residue was measured by quantifying the silicon dioxide (SiO2) concentration in the sample using the procedure described by Iji & Yokoyama (1997). The SiO2 content in the fiberglass used in circuit boards, also called E-glass, is 52–56% or 54% on average (Kelley & Trobough, 2016a). The SiO2 content in the sample was determined by conducting the whole-rock analysis on the combustion residue. The method is used to determine the major metal oxides in a rock sample. The combustion residue was sent to an external laboratory for metal oxide analysis. Once the SiO2 concentration is known, the fiberglass concentration in the sample was estimated by using Equation 3-1, as described by Iji & Yokoyama (1997). 𝐹𝑖𝑏𝑒𝑟𝑔𝑙𝑎𝑠𝑠 𝑐𝑜𝑛𝑡𝑒𝑛𝑡 = 𝑆𝑖𝑂2 Conc.54.0 (100 − % 𝑤𝑡. 𝑙𝑜𝑠𝑠 𝑑𝑢𝑟𝑖𝑛𝑔 𝑐𝑜𝑚𝑏𝑢𝑠𝑡𝑖𝑜𝑛) Equation 3-1 Toxicity characteristic leaching procedure (TCLP) test The TCLP test is a soil extraction process to simulate and analyze leaching through landfills. It determines the mobility of metals through the soil. According to the BC Ministry of Environment guidelines, a waste is hazardous if it produces leachate with a concentration higher than the defined limits when subjected to the US EPA method 1311 (Oliver, 2016). In Alberta, the TCLP test is suggested as a standard test to classify a solid waste to be hazardous (Fernandes, 2012). The Resource, Conversation, and Recovery Act requires the organizations dealing with waste 67 management to perform this test for waste characterization (Phoslab Environmental Laboratories, 2015). Approximately 120 g of dried NMF sample was sent to an external laboratory for the TCLP test. The test was performed following the standard EPA 1311 method (EPA, 1992) using acetic acid as a leaching agent, and leachate was analyzed using EPA 245.7 (EPA, 2005) for mercury and EPA 6010B (EPA, 1996) for other metals. Polybrominated diphenyl ethers (PBDEs) analysis PBDEs are a set of organobromine compounds with 209 possible congeners with 3–10 bromine atoms. These compounds are commonly added to the electronic castings as flame retardants (Guo et al., 2016) but have been phased out in Canada since 2003. These compounds were added to the list of toxic substances under the Canadian Environmental Protection act in 2006 and have provided quality guidelines for their concentration in sediments and other samples (Environment Canada, 2013). Approximately 20 g of sample was obtained from the dried NMF and was sent to an external laboratory for PBDEs analysis. PBDEs extraction was performed using standard EPA 3541 procedure (EPA, 1994a), and the extracted solvent was analyzed following standard EPA 8270D (EPA, 2014) guidelines for gas chromatography/mass spectrometry (GC/MS). Polychlorinated biphenyls (PCBs) analysis PCBs are a set of organochlorine compounds with 209 possible congeners with 3–10 chlorine atoms. These compounds were widely used as flame retardants before getting banned in the USA 68 in 1977 due to their harmful health effects, but studies near various recycling facilities have shown the presence of PCBs in the surrounding dust and soil. Approximately 20 g of representative samples from the dried NMF was prepared and sent to an external laboratory for PCBs analysis. The analysis was performed using the standard EPA 1668C method (EPA, 2010). The extracted solvent is then analyzed using high-resolution gas chromatography/mass spectrometry (GC/MS). Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) analysis According to the BC Ministry of Environment guidelines, any waste containing chlorinated dioxin and furans levels of more than 100 parts per billions by weight of toxic dioxin equivalent would be classified as waste-containing dioxins and would be considered hazardous waste (Oliver, 2016). These compounds are the by-products of the manufacturing process of the organochloride compounds and are also formed by the pyrolysis or incineration of the chlorine-containing materials. Approximately 30 g of representative samples from the dried NMF were prepared and sent to an external laboratory for PCDD/Fs analysis. The test was performed using the standard EPA 1613B method (EPA, 1994b) that provided the concentration of all homologs of PCDD/Fs from tetra- to octa-chlorinated dioxins and furans. The extracted solvent is then analyzed using high-resolution gas chromatography/mass spectrometry (GC/MS). 3.3 Results and discussion The main objective of this chapter is to perform the characterization in order to establish the nature, value, and associated environmental concerns of the NMF obtained from an operating plant, 69 representing a realistic scenario for industrial application. As indicated in earlier sections, similar studies have been conducted only on the waste PCB before industrial processing. The material in this study represents samples from an active recycling site. The particle size distribution of the dried NMF obtained from the screen analysis is shown in Figure 3-3 and Figure 3-4. It shows that almost all the materials are smaller than 2 mm, which is an optimum size to achieve a high degree of liberation as reported in the literature. Guo et al. (2011) and Ventura et al. (2018) have shown that in crushed waste PCB, metal content is increased in sizes below 1.25 mm and 1.7 mm, respectively, with the highest concentration in the finest fractions. Duan et al. (2015) have suggested that all metals achieve nearly complete liberation in -1 mm size fraction. Guo et al. (2009) have shown that gravity separation is one of the most common techniques for – 2 + 0.1 mm particles. The percent passing at 75 µm is only 10 %, suggesting a low amount of fine being generated, thus, minimizing the metal loss in tailings as many researchers have suggested a low separation efficiency of a mechanical process for fine particles (Zhao et al., 2012). Figure 3-3 also shows that there was not a significant change after fifteen minutes of screening time. All particles smaller than the screen opening had already passed through the screen. Some fiberglass particles might have a diameter smaller than the screen opening but have a very low probability of falling straight through the screen opening. The particles are mostly distributed in size, ranging from 1180 µm to 300 µm, with most of the materials found in the -600 + 300 µm range (approximately 30%). Only 1% of the particles are coarser than 1180 µm, and approximately 10% of the particles are finer than 75 µm. The 80% and 50% passing sizes for the samples are listed in Table 3-1. 70 Figure 3-3: Particle size distribution of as-received dried NMF Figure 3-4: Percent weight distributions for as-received NMF in different size fractions 71 Table 3-1: 80% and 50% passing size for as-received NMF obtained from screening test Screen time 80 % passing (µm) 50 % passing (µm) % Passing at 75 µm 5 min 844.2 475.9 5.7 15 min 801.6 440.5 8.2 30 min 782.4 425.4 9.3 60 min 768.6 416.1 10.0 The Rosin-Rammler distribution is one of the widely used functions to characterize the particles in mineral processing and has also shown a good fit for waste printed circuit boards, shredded electronics products, and solid waste (Quan et al., 2012; Sun et al., 2015; Vesilind, 1980) as shown in Figure 3-5. The size distribution data were fitted to the Rosin -Rammler distribution, as shown in Equation 3-2. 𝐹(𝑋) = 1 − 𝑒−(𝑋𝑋′)𝑛 Equation 3-2 where, F(x) is cumulative percent passing at size x X is the particle size X’ is size modulus defining the Rosin-Rammler geometric mean diameter (size at 63.2% cumulative passing) n is distribution modulus defining the spread of the distribution (small n represents wide distribution) 72 Figure 3-5: Particle size data fitted to Rosin-Rammler distribution function Figure 3-5 shows the obtained particle size data fitted to the Rosin-Rammler equation and shows a good fit, with a correlation coefficient of 0.9881. The size modulus (X’) and distribution modulus (n) calculated for this sample was 499 µm and 1.26, respectively. It suggests that the Rosin-Rammler distribution is also suitable for the crushed waste printed circuit boards obtained from hammer milling. 3.3.1 Economic benefits The metal analysis was performed to estimate the presence of residual metals in the NMF obtained from PCB recycling at an industrial scale. The recovery of residual metals before disposal could provide an economic incentive and increase the overall metal recovery from PCB recycling. Figure 3-6 shows the total metal content in various size fractions of NMF. The total metal content includes 73 aluminum, antimony, arsenic, barium, boron, cadmium, calcium, chromium, cobalt, copper, iron, lead, magnesium, manganese, nickel, potassium, silver, sodium, tin, titanium, and zinc. It shows that metal content ranges from 10% to 20%, depending on the size fraction. It should be noted that not all of these metals could be recovered with 100% efficiency, but recoverable metals could provide an economic incentive for NMF recycling. The concentrations of specific metals are shown in Figure 3-7 to Figure 3-10. The metal concentration vs. size and their distribution suggests that in most cases, the finest size fraction (-75 µm) has the highest metal concentration, and the middle size fraction (-600 + 300 µm) has the largest metal distribution. This is because the mass fraction of this size range is the highest, as seen by the size distribution plot in Figure 3-4. Figure 3-6: Total metal content and its distribution in various NMF size fractions As shown in Figure 3-7, aluminum and calcium are present in all size fractions in relatively higher concentrations with the highest concentration in the finest fraction, most likely because these 74 metals are a major component of the fiberglass matrix. The calcium oxide and aluminum oxide content in fiberglass could be as high as 25% depending on the type of fiberglass (Kelley & Trobough, 2016a), and fiberglass is one of the major components in the NMF that would, in turn, increase the overall concentration of aluminum and calcium. Zheng et al. (2009) showed that the fiberglass concentration in the finest fraction of NMF is the highest, leading to increased aluminum and calcium concentrations in this size fraction. It should also be noted that the concentration of aluminum and calcium deviate slightly from each other in different size ranges as not all of the aluminum and calcium are present in the fiberglass. Some of the aluminum might be present in metallic form, whereas some of the calcium might be present in ceramics. The antimony grade, as shown in Figure 3-7, is the highest for the coarsest fraction. Antimony is primarily used in the form of antimony oxide to enhance the activity of the halogenated flame retardants (EPA, 2015; Five Winds International, 2001). This compound is found in the circuit board resins applied during laminate production and would not get liberated by any comminution techniques for recovery. Copper, as shown in Figure 3-8, is one of the most abundant metals in the waste PCB, hence, would also have a relatively high concentration in the NMF (in recycling tailings). The highest copper concentration is observed in the coarse fraction due to the presence of long strands of copper wires getting intertwined during the screening process and then reporting to the coarse screens. Sun et al. (2015) showed a similar phenomenon for shredded electronic products, where large strands of copper wires were present in the coarsest size fraction. 75 Figure 3-7: Concentration and distribution of Al, Sb and Ca in NMF size fractions Figure 3-8: Concentration and distribution of Cu, Fe and Pb in NMF size fractions 76 Figure 3-9: Concentration and distribution of Mn, Ni and Sn in NMF size fractions Figure 3-10: Concentration and distribution of Zn in NMF size fractions Iron, as shown in Figure 3-8, is used in PCB as construction elements for contacts or magnetic cores for transformers (Szałatkiewicz, 2014a), and some of the iron strands may not comminute during the shredding and size reduction processes, and thus, slightly increase the iron content in the coarser fraction. In the case of zinc, as shown in Figure 3-10, it is added in the form of zinc borate as a smoke suppressant in the mixtures of flame retardants (EPA, 2015), hence, its presence 77 in the circuit board laminates is found in the coarser sizes, as it might not be fully liberated during processing. Additionally, fiberglass present in the NMF also presents an economic benefit for recycling. Fiberglass is one of the most commonly used reinforcements in thermoplastic, and if appropriately recycled, could be used as fillers in different composites or recycled back for PCB manufacturing. A life cycle analysis of e-glass, commonly used in electronics, showed that the production of one tonne of e-glass consumes 0.4 tonnes of sand, 12.4 GJ of natural gas and electricity, and over 3300 L of water (Dai et al., 2015). Hence, recycling this fiberglass would also provide significant resource savings. The fiberglass concentration was determined to provide an estimate of the amount of fiberglass locked in e-waste. The fiberglass content that was obtained using Equation 2-10 is shown in Figure 3-11. It shows that the overall fiberglass content in the dried NMF is 39%. The concentration in the coarse fraction is as low as 26 %, and the maximum concentration of 69% is reached for the finest size fraction. The slight decrease in the -300+150 µm might be due to the increased presence of FR-2 in this size fraction. FR-2 boards use cotton paper as reinforcement, and the higher concentration of this type of board in a given size fraction will increase its ignition loss and reduce the fiberglass concentration. The LOI analysis and thermogravimetric analysis confirmed this assumption, which is explored in the subsequent chapter. During laminate production, resins are coated rigorously on the reinforcing materials to create a stable and durable core when layered. These materials resist fracture when comminuted, and complete liberation of the fiberglass from resin is almost impossible using any coarse breakage mechanics such as impact (in the hammer mill). Attrition and abrasion would be the only possible 78 mechanisms to comminute fiberglass and produce fine particles, increasing the fiberglass content in the - 75 µm size fraction. Figure 3-11: Fiberglass content in various NMF size fractions Zheng et al. (2009) showed a similar trend with the highest concentration of over 70% in - 106 µm size fraction and 53% in the – 710 + 180 µm size fraction. The concentration in + 710 µm size fraction was not reported. The concentration of fiberglass obtained in this study was lower than the concentration reported in the literature. Zheng et al. (2009) performed the analysis using the FR-4 circuit board obtained from a personal computer and showed a higher fiberglass concentration. An industrial unit processing all types of circuit boards simultaneously would reduce fiberglass concentration due to the presence of other non-fiberglass-containing boards. Based on the amount of e-waste produced in the world, average circuit board concentration in e-waste, average NMF in circuit boards, fiberglass concentration in NMF, and the amount of 79 fiberglass locked in e-waste was estimated and is shown in Table 3-2. It shows the presence of an average of 0.5 million tonnes of fiberglass in e-waste in 2016, that would increase to 1.5 million tonnes by 2050. This shows the potential of the recovery of fiberglass for reuse or as secondary raw material. It should be noted that fiberglass concentration was kept constant at 39% as obtained from this research; however, this concentration would change in the future depending on the development of new types of printed circuit boards. Table 3-2: Amount of fiberglass locked in e-waste Description Units 2016 2021 2050 Source E-waste [Mt] 44.7 52.2 120 Baldé et al. (2017; 2015), Wahlen (2019) PCB [%] 3–6 3–6 3–6 Ning et al. (2017) NMF [%] 65–70 65–70 65–70 Muniyandi et al. (2014) Fiberglass [%] 39 39 39 This study Fiberglass [Mt] 0.53±0.19 0.62±0.23 1.43±0.52 This study 3.3.2 Environmental protection and public health Printed circuit boards contain different heavy metals and toxic compounds in high concentrations that will be harmful to the environment and public safety if disposed of improperly. The concentration and issues associated with these metals and compounds have already been reported in literature. However, the concentration of these materials after PCB processing has not been reported before. The processes used to recover metals may or may not have reduced the concentration of these metals and compounds in the NMF. If disposed of improperly, these 80 chemicals would have a devastating effect on the environment. To understand the issues associated with some of the most common disposal practices, various tests were performed. To quantify problems related to landfill disposal, the TCLP test was performed. The TCLP test is required to classify any material as a hazard. The TCLP results for the received NMF and the British Columbia leachate quality standards are shown in Table 3-3. The results showed that the leachate concentrations are far below the standard limit set by British Columbia (BC) environmental protection laws for all metals, except for lead (Pb). The lead leachate concentration is three times higher than the regulation limits. According to the British Columbia (BC) environmental protection laws, this waste would be prohibited from secure landfill disposal. Compared to the TCLP test results for milled circuit boards obtained by Bizzo et al. (2014), the lead leachate concentration has been reduced from 133 mg/L to 17.5 mg/L, whereas cadmium has been decreased to almost negligible amounts compared to 22 mg/L. This suggests that the majority of the lead and cadmium have been recovered during the metal extraction process. Lead is primarily present in the solder matrix and hard to fully liberate through hammer milling and related physical processing methods due to its malleability. Lead present in the NMF can also form lead acetate when it reacts with the acetic acid used in the TCLP test, which is water-soluble, thus, increasing lead concentration in the leachate. 81 Table 3-3: TCLP test results for studied NMF Element TCLP test result [mg/L] BC compliance limit (2017) [mg/L] Antimony < 1.0 - Arsenic < 1.0 2.5 Barium 3.75 100 Boron 0.91 500 Cadmium 0.08 0.5 Calcium 16.16 - Chromium < 0.25 5 Cobalt 0.09 - Copper 19.31 100 Iron 7.07 - Lead 17.55 5 Magnesium 8.08 - Mercury < 0.001 0.1 Nickel 0.35 - Selenium < 1.0 1 Silver < 0.05 5 Zinc 14.32 500 Along with the issues associated with metal leaching in landfills, countries worldwide have also imposed landfill bans. Séguin (2014) reported that approximately $4,150 of value was created 82 from recycling and related activities for every tonne of materials diverted from landfills. Ylä-Mella & Román (2019) showed that the cost of landfilling in Europe had boosted the e-waste recycling rate by making landfilling a costly waste disposal option. In Canada, a provincial landfill ban for e-waste is implemented in Nova Scotia, Prince Edward Island, and Newfoundland and Labrador. In other provinces, the municipalities are creating goals to divert e-waste from landfills. For example, some municipalities such as North Bay and Waterloo in Ontario; Metro Vancouver, Nanaimo, and Okanagan in British Columbia; and the City of Whitehorse in Yukon have banned landfilling e-waste. Some provinces have introduced additional costs for the landfilling of e-waste to increase the diversion of e-waste from landfills. Manitoba has added $10 per tonne, and Quebec has introduced $20.69 per tonne as a landfill levy, in addition to the landfill tipping fee (Séguin, 2014). The landfill bans and landfilling fee also encourages recycling organizations to investigate alternative solutions to deal with the non-metal fraction obtained from recycling activities. PBDEs are other toxic substances used in the production of circuit boards added as flame retardants to the resins at the laminate product stage. These materials would not be recovered during the metal extraction stage and would report with the NMF. These compounds have been gradually phased out in different parts of the world; hence, the circuit boards manufactured in different parts of the world at different times/years would have highly varying concentrations of PBDEs. The total concentration of PBDEs in the dried NMF in this study was estimated to be 294 mg/kg. Table 3-4 shows the concentration of individual PBDEs in the NMF, along with the federal environmental quality guidelines (FEQG) for PBDEs for sediments to protect the aquatic life in Canada and their contribution towards the overall concentration. It suggests that a significant 83 amount of PBDEs is still present in the NMF and will require further attention before landfilling or distribution as a waste-to-energy product for incineration. Table 3-4: PBDEs concentration in studied NMF Congeners Concentration [mg/kg] FEQG (2013) [mg/kg] Contribution [%] Tri-BDE 15.60 0.044 5.31 Tetra-BDE 71.70 0.039 24.40 Penta-BDE 54.80 0.0004 18.65 Hexa-BDE 16.35 0.44 5.56 Hepta-BDE 5.69 - 1.94 Octa-BDE 0.73 5.6 0.25 Nona-BDE 9.00 - 3.06 Deca-BDE 120.00 0.019 40.83 Total PBDEs 293.87 100.00 Table 3-4 also shows that the deca-BDE has a much higher contribution than other PDBE congeners, followed by tetra and penta-BDE, which is in line with the Environment Canada (2004) report showing that deca-BDE is widely used as a flame retardant in computers, television casings, and electrical/electronic components. Similar to PBDEs, polychlorinated biphenyls (PCBs) are another class of hazardous substances that are highly regulated around the world. The production of PCBs was banned in 1979 in the USA, but the products manufactured before the 1979 ban might contain PCBs. According to the 84 most recent regulation in Canada, no person shall release a solid containing more than 50 mg/kg of PCBs from equipment not in use (Minister of Justice, 2015). Table 3-5 shows the concentration of different PCBs and their contribution towards the total PCBs in the dried NMF. It shows that the total concentration of PCBs in the dried NMF is 3.2 mg/kg, well below the acceptable concentration limit for the environmental release limit by a person. However, if the NMF containing these PCBs is incinerated, it would release dioxins and furans into the environment if improperly managed. Table 3-5: PCBs concentration in studied NMF Congeners Concentration [mg/kg] Contribution [%] Mono-CB 0.016 0.50 Di-CB 0.284 8.89 Tri-CB 1.200 37.58 Tetra-CB 0.988 30.94 Penta-CB 0.342 10.71 Hexa-CB 0.287 8.99 Hepta-CB 0.060 1.86 Octa-CB 0.015 0.48 Nona-CB 0.001 0.04 Deca-CB 0.000 0.01 Total PCBs 3.194 100.00 85 The presence of harmful flame retardants in the NMF poses the risk of releasing toxic dioxins and furans (PCDD/Fs) due to improper incineration; hence, it is necessary to establish the concentration of these substances in the NMF, which is not available in any literature. PCDD/Fs are classified under toxic substances under the Canadian Environmental Protection Act (CEPA). The results from the PCDD/Fs analysis are listed in Table 3-6. It shows that the toxicity limit of PCDD/Fs ranges from 2880 to 3170 pg/kg TEQ. Table 3-6: PCDD/Fs concentration in studied NMF Congeners Concentration [pg/g] Tetra-CDD 12.9 Penta-CDD 11.7 Hexa-CDD 6.4 Hepta-CDD 7.1 Octa-CDD 128.0 Tetra-CDF 55.6 Penta-CDF 82.3 Hexa-CDF 79.4 Hepta-CDF 21.6 Octa-CDF 25.8 Lower limit TEQ (pg/kg) 2880 Upper limit TEQ (pg/kg) 3170 86 Greene et al. (2003) suggested that maintaining a lifetime average daily bodily dosage below 1–10 pg/kg/day (TEQ) is required to eliminate the risk of cancer, whereas the tolerable daily intake value used by Health Canada is 10 pg/kg/day TEQ (Canadian Council of Ministers of the Environment, 2002). The amount of PCDD/Fs produced from a plant processing a unit tonne of NMF per day will be much higher than the tolerable daily intake recommended by Health Canada, emphasizing the requirement of proper disposal of the separated NMF obtained from the processing of circuit boards. 3.4 Summary The NMF obtained from the processing of waste PCB presents a significant proportion by weight and contains residual metals and fiberglass that could provide an economic incentive for recycling. It also contains heavy metals such as lead and toxic flame-retardant chemicals such as PBDEs, that if not treated properly, will cause environmental damage and health and safety issues for humans. Since the circuit boards are usually processed before disposal, this chapter presents methodologies to study and analyze the NMF obtained from a waste PCB recycling facility to quantify the economic opportunities and environmental concerns associated with NMF, while this type of information has not been made available anywhere before. The results showed that the physical processing of waste PCB using a combination of hammer mill and gravity separation does not create an excess of fine materials, and most of the particles lie in the mid-size range (- 1180 + 300 µm), with high metal and fiberglass concentration in fine size fraction. The results showed that the recovery of metals from the waste PCB significantly reduces the landfill leaching concentration of most metals except for lead (Pb). The landfill bans and 87 landfilling fee also encourages recycling organizations to investigate alternative solutions to deal with the non-metal fraction obtained from recycling activities. This study also evaluated the concentration of harmful flame-retardants such as PBDEs and PCBs in the rejected NMF of waste printed circuit boards from a representative sample. The current estimates are only available for unprocessed individual circuit boards. The presence of harmful PBDEs was quantified to be 294 mg/kg, whereas dioxins and furans were estimated to be 2880–3170 pg/kg (TEQ). The presence of these compounds and toxic/heavy metals such as lead requires more attention, as they will be released and volatilized if the NMF is disposed of improperly. It should be noted that waste printed board samples are widely varying in composition. Since a circuit board might come from different equipment, different manufacturers, different countries of origin, and different points of time as, in the past, boards being processed in one plant might have been entirely different from those from another plant. The same set of tests carried out on the NMF obtained on a different day might have different results compared to the results shown in this study. However, the economic benefits and environmental issues presented in this study will still be valid, even if it is on a different scale. 88 Chapter 4: Determination of loss on ignition test conditions for NMF 4.1 Introduction The recycling of the NMF is a crucial step to promote the circular economy, as the NMF is one of the e-waste components that is disposed of into landfills. The previous chapter presented the characteristics of the NMF obtained from a waste PCB recycling plant and showed the economic potential of NMF recycling. It also showed the presence of harmful chemicals in the NMF that require close attention before disposal. One of the most common methods used in literature to evaluate the efficiency of separation of different components, especially the separation of the organic component from the inorganic component, is the loss on ignition. Critical variables for estimating the LOI are the mass of the sample used, the ignition temperature, combustion duration, and particle size. Various researchers have used different values for these variables for estimating the loss on ignition, as listed in Table 2-10, since the loss on ignition is critical for determining the efficiency of separation; a standard test condition needs to be established. The standard analytical methods are a necessary tool to evaluate different processes, and establishing a standard approach for the LOI test was addressed as one of the sub-objectives of this research. To achieve this sub-objective, the research questions addressed in this chapter are, • Understand if sample pulverization has any effect on LOI, as the presence of polymers in the NMF renders it harder to pulverize and would require expensive cryogenic grinding that is not available at all laboratories, 89 • Establish a standard test parameter that could estimate the total organic and inorganic content in the tested NMF This chapter has been published in the Resource, Recycling, and Conservation journal. 4.2 Methodology This section provides details of the sample preparation and the procedures for establishing standard test conditions for all subsequent LOI tests. It should be noted that the test conditions determined from these tests are only applicable for samples similar to the one used in this study. 4.2.1 Non-metal fraction sample The samples described in section 3.2.1 were used for this study. The dried non-metal fraction samples were riffled to obtain 500 g subsamples. The subsample was riffled again following the flow chart, shown in Figure 4-1, to obtain the required samples for the study. Figure 4-1: Flow chart of sample preparation for LOI test standardization To understand the effect of sample pulverization on LOI, as-received dried NMF, - 1180 + 850 µm (coarse), and -600 + 425 µm (intermediate) were obtained, and a subsample was pulverized to 250 µm using a ring and puck pulverizer. Three samples, each with two subsamples (a. as Dried NMFSubsample (500g)As received feed (S1)Remaining NMFAs received feed (S11)Pulverized to 250 µm (S12)- 1180 + 850 µm (S2)- 1180 + 850 µm (S21)Pulverized to 250 µm (S22)- 600 + 425 µm (S3)- 600 + 4250 µm (S31)Pulverized to 250 µm (S32)90 received/screened, and b. pulverized to 250 µm), were tested at varying temperatures and durations. 4.2.2 Loss on ignition test All six samples (three samples of feed, coarse, and intermediate, each with two subsamples of as- received/screened and pulverized) were tested in a conventional muffle furnace. A one (1) gram sample was placed in a porcelain crucible and placed in a muffle furnace at room temperature. The test temperature was set, and samples were left to be roasted for the desired duration. The temperatures tested were 565, 750, and 9500C, selected from the low, average, and high temperatures from the ASTM standard. Once the temperature reached the desired point, the sample was left for combustion for an additional one, three, and five hours, based on the ASTM standards and previous studies (Eswaraiah et al., 2008; Nekouei et al., 2018; Zheng et al., 2009). These conditions were selected to provide a broader range of testing conditions. After the desired time, the crucible was removed from the furnace, left for cooling in a desiccator, and the residue was weighed to estimate the loss on ignition. After establishing the temperature and duration, different sample masses (3 g and 5 g) were tested to understand the difference in using a larger sample mass. A larger sample mass provides a better representation of the bulk that would, in turn, provide better accuracy. All tests were performed in triplicates. 4.2.3 Thermogravimetric analysis The thermogravimetric analysis (TGA) tests were performed to analyze the progressive change in the sample weight with increasing temperature. This would provide a better understanding of the 91 removal of organic matter during combustion with respect to the temperature. All TGA tests were performed using a 50–70 mg sample in a PerkinElmer TGA 4000 (due to limitation of the sample crucible size). The first set of TGA tests were performed at the same setting as the LOI tests. The LOI samples were placed in porcelain crucibles, and the temperature was increased from room temperature to 565, 750, and 9500C at 100C/min and left for an additional three hours for combustion. Previous research has shown that the heating rate did not impact the weight of final residue (Kumar et al., 2018a); hence, the effect of heating rate was not included in this test program. A second set of TGA tests were performed on all size fractions (-1180 + 600 µm, -600 + 300 µm, -300 + 150 µm, -150 + 75 µm and –75 µm). These size fractions were subsequently used for the separation of organic and inorganic materials. Samples were placed in the porcelain crucibles, and the temperature was increased from room temperature to 7500C at 100C/min and then left for three hours. 4.3 Results and discussion To provide standard LOI testing conditions for the sample under consideration, tests were performed on different samples at varying temperatures and durations. The LOI test results at these conditions were averaged for the triplicate samples, and the results are plotted in Figure 4-2 to Figure 4-4 along with the maximum and minimum obtained values. 92 Figure 4-2: LOI test results for NMF feed at varying temperature and duration The results showed that the averaged LOI for different samples were similar with or without sample pulverization. Samples without pulverization showed a higher degree of variation in LOI compared to the pulverized samples; but once the data was averaged, the results for both conditions are nearly identical in all cases. The main reason for this variation is the representativeness of the tested samples. The pulverized samples are more homogeneous due to finer particle size; hence the triplicate samples are more identical to each other compared to the as-received/screened samples. One of the main reasons for the similarity in the results for unpulverized and pulverized samples could be the presence of organic materials on the surface of reinforcement materials, 93 which means that organic materials in the NMF do not need additional grinding to be exposed for combustion. The pulverization process mostly increases the homogeneity of the samples, and thus, reduces the sample variation. If the LOI test is performed in triplicates on unpulverized materials, the averaged LOI would be very close to that for pulverized samples and would also reduce the contamination of the material during the pulverization process. Figure 4-3: LOI test results for -1180+850 µm at varying temperature and duration The results also showed that the tested temperature and time did not significantly impact the LOI results. The most abundant organic material in the NMF is the resin (used to produce the laminates) and has a degradation temperature of approximately 3200C (Kelley & Trobough, 2016b). Hence, 94 when the temperature reached 5650C, most of the organic materials are already combusted, and leaving the material for an additional hour at 5650C provided enough time to combust all the other organic components. The set of TGA tests conducted on the same samples proves this hypothesis. Figure 4-4: LOI test results for -600+425 µm at varying temperature and duration Figure 4-5 to Figure 4-7 show the results obtained from the first set of TGA tests on various samples. It shows that the overall percentage weight loss values are similar for the unpulverized and pulverized samples, as obtained from the LOI test from the muffle furnace (denoted by the red dotted lines). It also shows that the complete combustion of all organic matter is achieved in all cases by 150 min, and no further weight reduction was observed afterward. Slight differences in 95 the overall weight reduction achieved for the coarse samples (-1180 + 850 µm) and the intermediate samples (-600 + 425 µm) are due to the difference in the sample arising from the small sample weight used for the test. The TGA test used approximately 50–70 mg sample, and it is nearly impossible to obtain absolute representativeness at these sizes with such a small sample mass. Figure 4-5: TGA test results on NMF feed at varying temperature 96 Figure 4-6: TGA test results for -1180+850 µm at varying temperature Figure 4-7: TGA test results for -600+425 µm at varying temperature 97 Based on the data obtained from the muffle furnace LOI tests and the TGA tests, the optimum conditions for the LOI test was set to 7500C for three hours (the middle/average values used in the test) using as-received/screened samples similar to the ASTM D3174 – 12. A lower temperature, i.e., 5650C, would also provide similar results; however, the optimum condition for LOI testing was matched with the ASTM D3174 – 12, the coal ash content analysis procedure, due to the similarity between the two samples. Both samples contain organic and inorganic matter, and testing requires the complete combustion of organic matter in both cases. The next set of LOI tests were performed to identify the difference in LOI values if a larger sample mass was used. Figure 4-8 shows the LOI test results conducted on three as received/screened samples of 1 g, 3 g, and 5 g samples. It shows that the LOI values were similar; however, the larger sample mass had reduced variation among the triplicate tests, as expected. A larger sample mass is more representative of the bulk, but the averaged results from the triplicate tests would be similar, independent of the sample mass. 98 Figure 4-8: LOI test results on different samples at varying sample mass To confirm the suitability of the temperature and duration conditions for other samples, another set of TGA tests and LOI tests in the muffle furnace were performed on all other size fractions. Figure 4-9 shows the LOI results obtained from other size fractions in the muffle furnace, whereas Figure 4-10 shows the obtained test plots for the TGA tests. It shows that the loss on ignition decreases with decreased particle size and suggests the presence of a high content of organic materials in the coarser fractions, as also reported in various literature (Yang et al., 2019; Zhang et al., 2017; Zheng et al., 2009). However, there is a slight increase in the LOI for the -300+150 µm size fraction, suggesting slightly higher organic matter content than other size fractions. The 99 fiberglass analysis in section 3.3.1 also showed a slight decrease in fiberglass concentration in this size fraction. This is most likely due to the presence of components of FR-2 boards that have organic cotton paper as the reinforcement. Figure 4-9: LOI test results for different size fraction The TGA test plot in Figure 4-10 shows that all the size fractions were able to reach the steady-state by the end of three hours, suggesting that the temperature of 7500C for sample combustion is sufficient if left for three hours. It also shows that the overall weight reduction has the same trend as that observed in the muffle furnace LOI test results. 100 Figure 4-10: TGA test results on different size fraction Researchers have shown that the decomposition of epoxy-fiberglass based FR-4 boards occurs in two distinct temperature ranges. A fast decomposition step of epoxy-based resins occurs from 250–3700C, followed by a slow combustion process after 5000C (Evangelopoulos et al., 2015; Kim et al., 2013), seen in derivative thermogravimetric (DTG) curves. The FTIR spectrum of the evolved products during the decomposition step shows the presence of low molecular weight compounds such as carbon monoxide, carbon dioxide, ammonia, hydrogen bromide, methane, water molecules, and high molecular weight compounds such as phenol, dioxins, furans, benzene and their derivatives, along with char residue. The second combustion step is mostly due to the residual char oxidation formed during the first stage (Barontini et al., 2005). The decomposition of paper-phenolic based laminate (FR-2) follows a four-step process. The phosphorous-based flame retardant, if present, vaporizes from 100–2800C, followed by the 101 decomposition of laminate paper from 280–3700C. The phenolic resin is decomposed in a temperature range of 370–5000C, followed by the combustion of decomposed residue in the 500–8000C temperature range (Kim, 2015). The decomposition of laminate paper produces levoglucosan, carbon dioxide, water, hydrogen bromide, and brominated aromatics similar to FR-2. The decomposition of phenolic resin produces phenol and its derivatives (Grause et al., 2008; Kim, 2015; Smith, 2016). The DTG curves for the size fractions are shown in Figure 4-11. It shows that the degradation temperature at which the mass of the sample starts to drop due to the thermal breakdown of the epoxy resin or paper laminate reaches a maximum at around 3200C in all cases. The first fast decomposition region ranges from 2500C to 3500C, peaking around 310–3200C, whereas the second decomposition region ranges after 4000C, peaking around 5000C, representing the presence of components from FR-2 and FR-4 boards. The coarse product (- 1180 + 600 µm) shows a decomposition region from 3500C to 4500C, representing the decomposition of phenolic resin; thus, the presence of FR-2 board components in this size. A relatively higher decomposition rate for – 300 + 150 µm size fraction might be due to a higher amount of organic material in this fraction, suggesting a slightly higher concentration of cotton paper reinforcement from the FR-2 board in this size range. The laminate paper decomposes from 280–3700C, as reported in the literature (Kim, 2015). 102 Figure 4-11: Derivative thermogravimetric curves for various size fractions The FR-4 laminates have outstanding physical properties compared to the FR-2 boards in terms of mechanical properties. The fiberglass has four to eight times higher tensile strength and Young Modulus than the cotton paper (Kelley & Trobough, 2016b; Zsiros, 2010). It suggests that during the hammer milling, the FR-2 laminates would quickly be shattered into smaller pieces, and thus, report to the coarser end of the comminuted product. However, the FR-4 boards would resist breakage due to their higher mechanical properties and produce wider distribution in terms of product sizes. A complete breakage behavior testing on individual laminates would be required to prove this supposition. Since the recycling organizations receive circuit boards already removed from the waste electronics that are metal platted, the breakage behavior needs to be studied on newly created laminates without any metal plating. 103 It should be noted that the LOI test was conducted on the NMF sample obtained after the PCB recycling and had depleted metal content. The presence of metals affects the LOI due to metal oxidation if concentrated into a metal-rich stream. The effect of the presence of residual metal should be studied by conducting LOI test on various size fraction of metal-rich PCB or NMF. 4.4 Summary The LOI test is one of the most common methods to estimate the concentration of organic components in the waste PCB or the NMF; however, the LOI test conditions are not standardized. No information on standardization was provided in any literature to the author’s knowledge. Researchers have used varying temperature and time conditions for LOI tests in their experiments, and the experiments were limited to specific boards obtained from specific waste electronics. This chapter endeavored to provide a standardized procedure for the LOI test by conducting experiments on NMF obtained from an industrial operation after separating the metals, a realistic scenario for any PCB recycling organization. To achieve complete combustion of all organic components in the NMF, the study concluded that the LOI test should be conducted at 7500C for three hours using a one-gram sample in triplicates. The sample could be pulverized if feasible or could be used as received. This test condition was used in subsequent chapters to estimate the organic content in various samples obtained after laboratory testing. 104 Chapter 5: Selection of physical separation process for NMF recycling 5.1 Introduction Previous chapters have presented the characteristics of the NMF in waste PCB and showed the economic benefit of NMF recycling due to the presence of inorganic material in the form of residual metals and fiberglass. One of the challenges for the recycling of the NMF is the relatively low economic value of its content; hence, opting for a low-cost processing technique could be a critical component for the successful recycling of NMF. Generally, physical processing techniques based on density, magnetic behavior, conductivity, or surface properties have lower operating cost than chemical or thermal processing such as hydro or pyrometallurgy. The next sub-objective of the research was to understand the applicability of commonly used physical processing methods for non-metal fraction recycling. The research question addressed in this chapter, to achieve this sub-objective is, • Which physical separation methods can be used for the separation of organic and inorganic components in the non-metal fraction? As discussed in the literature review, the magnetic separation could not be used to separate organic resins and inorganic fiberglass as they both would report to the tailings due to their diamagnetic properties. At the same time, researchers have suggested using triboelectric separation, a dry conductivity-based separation process, for the separation of organic materials. However, for a plant using water as the medium of separation, this chapter explores the applicability of water-based physical separation techniques (size classification, gravity separation, and flotation), most widely 105 used in the mineral processing industry, for the separation of organic, inorganic and residual metal streams from the NMF. A version of this chapter has been published in the International Journal of Waste Resources journal that included data obtained from the float-sink test. Another section of this chapter containing flotation related characterization, i.e., surface energy analysis using inverse gas chromatography (IGC), scanning electron microscopy (SEM) study, and Fourier Transform Infrared (FTIR) spectroscopy has been published in the Resource, Recycling, and Conservation journal. In addition to the information provided in the published papers, this chapter also provides details for size classification. 5.2 Methodology 5.2.1 Non-metal fraction sample The samples used in section 3.2.1 were used for this study. The dried NMF samples were riffled to obtain subsamples for various tests. 5.2.2 Size classification assessment To assess the applicability of size classification as a process for separating organic and inorganic components, data on the particle size distribution, as discussed in section 3.3, was analyzed in combination with the LOI test results obtained on various size fractions presented in section 4.3. 5.2.3 Float-sink test for assessing gravity separation Float-sink tests are standard tests to evaluate the feasibility of using a dense medium as a separation technique. Organic liquids with specific gravities (SG) of 1.4, 1.6, 1.8. 2.0, 2.2, and 2.5 were 106 prepared by mixing tetra bromoethane (SG 2.95) and kerosene (SG 0.8). These liquids were used for performing the float-sink test on all size fractions. The dried NMF samples were riffled/split to obtain 2 kg subsamples. To reduce the effect of particle size on the float-sink test results, the subsample was screened to obtain -1180 + 600 µm, -600 + 300 µm, -300 + 150 µm, -150 + 75 µm and, -75 µm. The +1180 µm sample only accounted for 1% of the total mass; hence, a sufficient sample was not available in this size range. In other size ranges, the ratio of the upper size limit and the lower size limit was maintained at 2:1 to decrease the effect of particle size on the separation process (Zhang et al., 2017). The screened size fractions were then subjected to the float-sink test. The standard procedure for coal washability analysis, as defined by ASTM D4371-06, was used for the float-sink test (ASTM International, 2012b). This procedure was used for all the coarse size fractions (-1180 + 600 µm, -600 + 300 µm and -300 + 150 µm). For fine size fractions (-150 + 75 µm and, -75 µm), the same procedure was used; however, a centrifuge was used for accelerated settling. The container with the sample and the heavy liquid was placed in a centrifuge at 3500 RPM for 30 minutes. After centrifuging, the floating fraction was carefully removed along with the liquid; then, the next heavy liquid was added to the container, and the process was repeated. All collected float fractions and the final sink fractions were washed with acetone to remove any residual heavy liquid, then they were filtered, dried, weighed, and used for subsequent LOI tests. For the LOI test, approximately one (1) gram sample was placed in a porcelain crucible and placed in a muffle furnace at room temperature. The test temperature was set to 7500C, and the sample was left for combustion for three hours, as discussed in section 4.4. After three hours, the crucible was removed from the furnace, was left for cooling in a desiccator, and the residue was weighed 107 to estimate the loss on ignition. The LOI tests for each product were performed in triplicates, and the results were averaged. 5.2.4 IGC test for studying surface properties relevant to flotation IGC has been commonly used to determine the surface energy in various polymers and in the pharmaceutical industry. Researchers have shown that the IGC could be used to measure the surface energy of mineral particles at different surface coverages and can be directly correlated with their flotation responses (Ho et al., 2010). BET surface area determination One of the input parameters for the IGC study is the surface area of the sample. The surface areas of the screened fractions were measured using the AUTOSORB -1 (Quantachrome Instruments, USA). The specific surface area is measured using nitrogen gas adsorption based on the Brunauer–Emmett–Teller (BET) model. Approximately 1–2 g of sample was outgassed for 24 hours at room temperature to remove any gas molecules present. After outgassing, samples were analyzed by using nitrogen gas as an adsorbent. IGC test The surface energy measurements were carried out using the Inverse Gas Chromatography- Surface Energy Analyzer (Surface Measurement Systems Ltd., England). Yao et al. (2017) showed that the probe molecule only detects high energetic sites at infinite dilution and provides a high energy value. It is assumed that in a multi-component system like NMF, the probe molecule would also only interact with high energy sites at infinite dilution. To reduce the interaction between multiple components, the IGC tests were carried out at room temperature (300C). All tests were 108 conducted at room temperature. The test conditions for the IGC study are listed in Table 5-1. Tests for all samples were conducted in triplicates, and the average energy values were used for the analysis. The Surface Energy Analyzer analysis software was used to obtain the dispersive energy, specific energy, and the work of adhesion, whereas Equation 2-15 was used to estimate the hydrophilicity. Table 5-1: IGC test conditions Description Details Column type Pre-silanized glass tube Column specifications 6 mm outer diameter, 4 mm inner diameter, and 300 mm length Sample mass 1–2 g Column packing Five minutes vibration Inert carrier gas Helium at 20 ml/min Column conditioning 300C for two hours Dead volume measurement Using methane before and after the test runs Test conditions 0 relative humidity, 300C Non-polar probe molecules Octane, heptane, and hexane Polar probe molecules Dichloromethane, ethyl acetate Area coverage [%] 0.5, 1, 2, 4, 6, 8, 10, 15, 20 SEM and Micro-FTIR The scanning electron microscopy (SEM) study was conducted using FEI Quanta 650 (Thermo Fisher Scientific Inc., USA) on coarse samples (+ 500 µm) and fine samples (- 500 µm) to visualize 109 particle morphology and composition and to assist with the understanding of the IGC results and flotation behavior. SEM is frequently used to understand the surface morphology and elemental composition but has limited application for carbon-based organic compounds. The cut-size was based on the coal industry, where 500 µm is a typical size used for classifying the fine coal for the flotation process (Laskowski, 2001; Zimmerman, 1979). The Fourier Transform Infrared (FTIR) spectroscopy technique has been used to characterize carbon-based compounds and carbon-based polymers. It provides information regarding the chemical composition of the analyzed samples surfaces. The NMF samples contain reinforcement materials encapsulated in the resin system, and FTIR is an appropriate method to analyze various resin systems present in the studied sample. Micro-FTIR spectroscopy was conducted on several particles using the NicoletTM iS50 FTIR spectrometer paired with a NicoletTM ContinuumTM infrared microscope (Thermo Fisher Scientific Inc., USA)., as shown in Figure 5-1. The micro-FTIR analysis was performed in a reflected IR light mode with a resolution of 4 cm-1 with a gold background. The micro-FTIR allows the user to observe individual particles using the coupled microscope and then use infrared light to analyze its surface composition. This helps to individually analyze different resins/polymers present in a heterogeneous mixture using FTIR spectroscopy for their identification. 110 Figure 5-1: NicoletTM iS50 FTIR spectrometer paired with a NicoletTM ContinuumTM infrared microscope 5.3 Results and discussion There are several different methods to separate materials based on the physical properties of particles to segregate them into two or more streams. These properties could be their size, magnetic behavior, density, conductive properties, and surface properties. A process could use the differences in these properties for separation. Some of the most common properties widely used in the mineral processing industry are discussed and analyzed in this section. 5.3.1 Size classification Size classification relies on the difference in sizes of various particles and the concentration of a specific mineral/material of interest in a given size range. Researchers have shown that the concentration of inorganic fiberglass is highest in the fine fraction, whereas the resins are mostly 111 concentrated in coarse fractions. Hence, the loss on ignition for the coarser fraction is higher than the finer fractions (Yang et al., 2019; Zhang et al., 2017; Zheng et al., 2009). However, the differences in the organic and inorganic content in different size fractions may or may not be significant enough for separation. The possibility of using size classification for the separation of the organic and inorganic stream has not been quantified in any published research. As discussed in the previous chapter, the particles are mostly distributed in sizes ranging from 1180 µm to 300 µm, with most of the mass found in the -600 + 300 µm range (approximately 30%). Only 1% of the particles are coarser than 1180 µm, and about 10% of the particles are finer than 75 µm. The particle size data, combined with the loss on ignition for all size fractions, were used to estimate the distribution of organic materials in various size fractions, as shown in Figure 5-2. It shows that the organic content in the coarsest fraction is increased by 12%, whereas there is 55% less organic material in the finest fraction. Wang et al. (2018) have shown that fiberglass bundles were observed in hammer mill crushed coarse particles, and single fiberglass was observed in fine fractions. The fiberglass in coarse particles was embedded in epoxy resin that resulted in a higher loss on ignition. The surface layer of fiberglass present in the finer particles was abraded and rugged, thus, liberating the fiberglass from epoxy and increasing the fiber/inorganic concentration in the finer size fraction, thus reducing the loss on ignition value for fines. 112 Figure 5-2: Loss on ignition and distribution of organic materials in various size fraction Figure 5-3 shows the loss on ignition vs. recovery curve similar to the grade-recovery curve in the mineral processing circuits. It shows that approximately 18% of the materials can be rejected with a comparatively low organic content (LOI) of 38% if screened at 150 µm. This process would result in a loss of 12% organic materials in the rejects. The resulting concentrate would have an organic content of 64%, compared to 59% in the feed. This result suggests that a separation between organic and inorganic content is possible based on size but with a low upgrading ratio. To liberate the inorganic fiberglass from the resin, the sample would require further fine grinding on the NMF material, an energy-intensive process that would increase the overall processing cost. 113 Figure 5-3: Loss on ignition-recovery-yield curve based on size classification 5.3.2 Gravity separation Gravity separation is another low-cost physical processing technique that has been used to recover metals from waste PCB; however, its applicability for the separation of organic and inorganic streams has not been quantified in research. This section provides the data and plots obtained from float-sink tests for all five tested size fractions to access the applicability of gravity separation. Figure 5-4 shows the yield at a different density for various size fractions. It shows that the yield at -1.4 and +2.5 specific gravity fractions are very low compared to other fractions. As listed in Table 2-8, the lower density fraction should represent the epoxy and phenolic resins due to their low densities, and the resin content should decrease with increasing density. The higher density fraction is expected to have higher inorganic content due to the high density of fiberglass. Since the fiberglass is encapsulated in resins and the size reduction process (hammer milling) would not 114 be able to produce a significant amount of pure resin fraction, the mass yield should be lower for the lowest density ranges (-1.4), as evident from Figure 5-4. At the same time, the tested samples are the NMF obtained after the processing of waste printed circuit boards and most of the metals are already removed from the sample; the yield at the highest specific gravity range (+2.5) should also be low. Figure 5-4: Percent yield at different specific gravities for tested size fractions The 1.4–1.6 SG indicates mostly resins fractions with residual inorganic matter. The phenolic paper laminates should report to this density fraction, increasing the yield. The 2.0–2.5 SG indicates mostly inorganic fractions (fiberglass) with residual resins. The 1.6–2.0 SG range would represent a mixture of fiberglass, resins, and cotton fiber. The LOI test discussed later shows the content of organic/inorganic components in these SG fractions and justifies this conclusion. 115 Researchers have shown that the concentration of resins is relatively higher in the coarse fractions leading to a higher yield at the -1.6 SG range for coarse materials compared to fine samples, as shown in Figure 5-4. In terms of fiberglass content, the concentration of fiberglass is higher in the fine sample, as reported in literature (Zheng et al., 2009). Figure 5-4 shows that the yield in +2.2 SG is low in coarse sizes and increased in the fine size fraction. The LOI tests were performed to compare the organic and inorganic content of various density fractions. Figure 5-5 shows the organic concentration in various density products obtained from the float-sink tests. The LOI decreased with an increase in the density, conforming to the presence of organic material (resins or organic fibers) in lighter fractions and decreasing its organic concentration with increasing density. The light fractions (-1.8 SG) would have the liberated resins with residual inorganic content along with the components from the FR-2 boards, such as cotton/paper fibers. The low LOI of the heaviest density fraction (+2.5 SG) suggests the presence of low organic content. Pure fiberglass has an average density of 2.6 g/cm3, suggesting that completely liberated fiberglass should report to the + 2.5 SG range. Very low yields of fiberglass in the +2.5 SG confirms that the probability of complete liberation of fiberglass from resin is very low using physical processing methods. The increased LOI for the heaviest density fraction (+2.5 SG) for -300 + 150 μm could be due to: a. An inefficient separation: Gravity separation is effective for the coarse size fraction, and for fine material, the settling velocity of particles reduces significantly, and thus, lowering the separation efficiency. 116 b. The presence of higher amounts of encapsulated fiberglass with unliberated resins thus, increasing the LOI compared to coarser size fractions. Figure 5-5: LOI values of different specific gravity products for various size fractions The LOI for the heaviest density fraction (+2.5 SG) for -150+75 μm and -75 μm showed that these streams had gained mass after combustion at 7500C. Figure 3-6 showed that these size fractions have an elevated level of residual metal concentration (~12% and 21%, respectively), concentrating in the +2.5 SG fraction during the float-sink test. The negative LOI suggests that metals present in this product are being oxidized (reacting with oxygen), and thus, increase the overall weight; and that the total increase in mass due to the material oxidation is greater than the total decrease in mass due to organic volatilization (Samal, 2016). The TGA analysis is required to understand this effect and is discussed in subsequent chapters. The presence of a high metal 117 concentration in this density range could be recirculated back to the separation stage for increasing the overall metal recovery or could be directly sent for subsequent leaching/smelting. These results suggested that the density-based separation might provide a possibility of producing relatively cleaner organic and inorganic streams using gravity-based processes to upgrade the quality of both, and thus, providing more options for the usability of these products. The evaluation of the applicability of gravity-based separation will be discussed in more detail in subsequent chapters. 5.3.3 Froth flotation The possible flotation response of the NMF was assessed using IGC on the same samples as prepared for the gravity separation tests without any further size reduction. The IGC test was performed to reveal if any differences occur in the surface energy of the NMF particles that might provide some preliminary information regarding the possible response to flotation. The specific surface area of various size fractions is shown in Figure 5-6. It shows the general trend of increasing surface area with reducing particle size. However, the area of the coarsest size fraction was slightly higher compared to the next finer size fraction, most probably due to its composition. The - 1180 + 600 µm size fraction might have a relatively higher concentration of FR-2 board components (paper laminate reinforced in phenolic resin) compared to other size fractions, which might be responsible for this deviation. The cotton paper has four to eight times lower tensile strength and Young modulus than fiberglass (Kelley & Trobough, 2016b; Zsiros, 2010). It suggests that during the size reduction process, the FR-2 laminates would easily be broken into smaller pieces and thus reporting to the coarser end of the comminuted product. A study with 118 individual board types before metal plating would be required to understand the difference in their surface area. Figure 5-6: Surface area of different particle size of as received NMF Using the specific surface area as an input, the surface energies, the work of adhesion, and the hydrophilicity for various size fractions at increasing surface coverage were estimated during the IGC test work and are plotted in Figure 5-7 to Figure 5-11. The error bars represent 95% confidence intervals. The energy profiles of various size fractions suggest the presence of some high energetic sites. These high energetic sites would mostly be the liberated fiberglass. The liberated fiberglass is generally hydrophilic due to its high surface energy and low contact angle (Van de Velde & Kiekens, 2000). At a lower surface coverage, the probe molecules would interact preferentially with these high energetic sites. When these high energetic sites are filled, the molecules would adsorb on relatively low energy sites and report a lower surface energy value. 119 These low energy sites would be the resin matrix itself due to the presence of organic molecules in its composition (Page et al., 2001). With the increase in surface coverage, the surface energy results would provide average energy for all the sites. This energy profile represented the surface heterogeneity of the tested sample. For a highly energetic heterogeneous surface, a wider distribution profile is expected. No significant differences in the surface energy (mJ/m2) were observed for different particle sizes. This might be because the high energy sites in all size fractions would be for fiberglass particles, whereas the low energy sites would be for the resin particles. There would be no significant surface energy differences in individual fiberglass particles in different size fractions or individual resin particles in different size fractions. Figure 5-7: Surface energy, work of adhesion, and hydrophilicity profile of – 1180 + 600 µm 120 Figure 5-8: Surface energy, work of adhesion, and hydrophilicity profile of – 600 + 300 µm Figure 5-9: Surface energy, work of adhesion, and hydrophilicity profile of – 300 + 150 µm 121 Figure 5-10: Surface energy, work of adhesion, and hydrophilicity profile of – 150 + 75 µm Figure 5-11: Surface energy, work of adhesion, and hydrophilicity profile of – 75 µm 122 As suggested by Niu et al. (2018), a sample with a higher proportion of the total energy as dispersive energy represents a highly hydrophobic surface, whereas the higher proportion of specific energy renders the surface hydrophilic. The dispersive energy dominates the major part of the total energy for the analyzed samples, which would render these surfaces hydrophobic. If these samples are subjected to flotation, the particles with a higher degree of hydrophilicity will tend to remain in water due to their high affinity with water, whereas the low degree of hydrophilicity would be floated first due to their low affinity to water. The surface energies and the hydrophilicity values reached the plateau/averaged values by 10% surface coverage, suggesting that approximately 10% of all the available particle surface have relatively higher surface energy compared to other particles and might report to the tailings (remain in water) if subjected to flotation without any reagent. This shows that the flotation system without reagent might provide some separation between the organic resins and inorganic fiberglass but will have a low yield and recoveries. Since the fiberglass is mostly encapsulated in epoxy resins, the unliberated fiberglass would mostly be hydrophobic due to the presence of organic resins on its surface. Only the entirely/partially liberated fiberglass would show any increase in its hydrophilic behavior. To further analyze particle properties, SEM analysis was conducted on coarse and fine materials. Figure 5-12 to Figure 5-15 show SEM micrographs for the coarse and fine samples. It clearly shows the difference between the fiberglass and resin particles. Figure 5-12 and Figure 5-13 show the image for the coarse sample (+ 500 µm) sample. It shows the fiberglass as bundles of fibers at coarse size with a large aspect ratio (longer length with a smaller diameter), as expected. It also shows some regular shape particles, which would be resin or other foreign particles such as 123 plastics. Figure 5-13 shows a magnified image of the coarse fiberglass particle. It shows the loose end of the fiberglass with some fibers being exposed from the resins. These exposed fibers would have a higher hydrophilicity index compared to the unexposed part. Since most of the fiberglass section is still unexposed, the overall particle would behave as a hydrophobic particle. Figure 5-12: SEM micrographs for + 500 µm sample 124 Figure 5-13: SEM micrographs of + 500 µm fiberglass bundles Similar characteristics are observed in the finer -500 µm size fraction size (Figure 5-14 and Figure 5-15). At a higher magnification, some of the free fiberglass particles with a small diameter (Figure 5-15) can be seen, suggesting the complete liberation of fiberglass particles from the resin at a very fine size. However, most of the fiberglass particles in the fine size are still in their original bundled shape, and only a few particles are entirely liberated. This would suggest that majority of the particles in the fine fraction would still be hydrophobic. Increasing the liberation of inorganic fiberglass from the resin to create free fibers would require further fine grinding on the NMF material, an energy-intensive process. It would increase the overall recycling/processing cost, which is not favorable for low-value materials. 125 Figure 5-14: SEM micrographs for - 500 µm Figure 5-15: SEM micrographs for - 500 µm fiberglass bundles and individual strands 126 The micro-FTIR analysis was also conducted to study the chemical composition of the surface of the particles. Micro-FTIR allowed us to observe the particle under the microscope and then identify the polymer/compound using FTIR spectroscopy. The polymer type was identified by matching the obtained spectra with the FTIR library available in the software. The FTIR spectra of identified polymers in the sample are shown in Figure 5-16. The micro-FTIR analysis of NMF has not been reported in any literature. This technique is used here to identify the type of polymers present in the NMF and to show the heterogeneity of the NMF mixture. This method could also be used to map the change in the surface profile of the polymer if any modification is performed using any reagent to study flotation behavior in future studies. The spectra of various fibrous particles, when compared with the library, showed the presence of epoxy resin on all the studied particles, suggesting a poor liberation of resin from the fiberglass, as also evident from the SEM images. The FTIR spectra also showed the presence of phenolic resin, polyamide, polyester, and polypropylene. The phenolic resin is present in the FR-2 boards, as discussed earlier, whereas polyamide and polyester are used as resin systems in some CEM and other circuit boards (Kelley & Trobough, 2016b). Polypropylene would most likely be present as the packaging plastics as a contaminant. All the resin materials, as listed from the FTIR spectra, are organic compounds that are generally hydrophobic, which in turn, would reduce the surface energy of the mixture. 127 Figure 5-16: FTIR spectra of various polymers obtained from micro-FTIR study 128 The band assignment for different FTIR spectra of the identified polymers are listed in Table 5-2. It shows that some of the vibrations are common in all identified polymers, whereas some bands are unique for specific polymers. These bands are used as the base to identify the polymer type in the FTIR software. The presence of all these polymers shows the high heterogeneity of the studied system and suggests that the development of a flotation-based separation system would require a study of all these resins individually, thus making flotation a challenging process for NMF mixture. As shown from the FTIR spectra, the differences in the functional groups in various resin systems suggest that selectivity of various reagents towards one resin compared to the other may exist, potentially providing a path for selective flotation. The reagents that are commonly researched in plastic flotation such as polyethylene glycol, lignosulfonates, tannic acid, methylcellulose, Triton X-100 could also be potentially used for separation of these polymers from each other and should be studied in detail. At the same time, researchers have shown that the flotation process is highly effective for particle size ranging from 15 to 150 µm in the mineral processing industry (Feng & Aldrich, 1999; Mankosa, 2017; Shergold, 1984; Wills & Finch, 2016a), whereas, typical particle size for coal flotation is below 500 µm (Laskowski, 2001; Zimmerman, 1979). The particle size of 2 to 10 mm has been researched for plastic flotation; however, the density of researched plastic ranged from 1.0 to 1.4 g/cm3 (Drelich et al., 1998, 1999; Pascoe, 2005). It suggests that further fine grinding would be required for an effective flotation of NMF, which would not be favorable for low-value materials. 129 Table 5-2: Band assignment for FTIR spectra for identified polymers (Cecen et al., 2008; Chen et al., 2013; González et al., 2012; Pawlik, 2002; Poljanšek & Krajnc, 2005; Porubská et al., 2012; Urbaniak-Domagala, 2012) Wavenumber [cm-1] Assignment Polymer 3500–3200 Various -OH stretch Epoxy and phenolic ~ 3300 N-H stretch Polyamide ~ 3060 C-H in epoxide ring Epoxy 2970–2850 Aliphatic CH3, CH2, and CH stretch All ~ 1730 C=O, ester Polyester ~ 1642 C=O, amide Polyamide ~ 1540 N-H bend Polyamide ~1600 C=C aromatic ring stretch Epoxy and phenolic ~1500 C-C aromatic ring stretch Epoxy and phenolic ~1450 CH3 and CH2 bend All ~1250 C-C-OH stretch Epoxy, phenolic, and polyester ~1200 wagging CH2 bend Epoxy and phenolic ~1120 C-O stretch Polyester 1036 C-O ether stretch Epoxy and phenolic 1021 Carboxylic ester Polyester 690–890 aromatic C-H bend Epoxy and phenolic 600–800 alkyl halide stretches Epoxy, phenolic, and polyester 130 5.4 Summary The non-metal fraction of the printed circuit board contains a significant amount of resins and fiberglass, along with some residual metals that could provide an economic incentive for recycling. The differences in the physical properties between organic resins and inorganic fiberglass were used as the basis of their separation. The size-based separation showed that relatively high-grade fiberglass could be recovered by screening out the finer fractions but with relatively low recovery. Previous research has also shown that the fiberglass concentration is elevated in the finer fraction; however, an attempt to explore the variation in fiberglass concentration for separation has never been reported before. The density-based float-sink separation showed promising results with organic resins accumulated in the lighter density fraction, whereas inorganic fiberglass and residual metals were reported to heavy density ranges. Similar to the size-based separation, the application for the float-sink test to recover metals has been studied by several researchers; however, the application of this method for the separation of organic resins and inorganic fiberglass has not yet been explored. The study showed that the differences in the densities of NMF constituents might be used to separate the organic and inorganic components effectively and would be studied in detail in the subsequent chapter. The potential of surface properties-based separation such as froth flotation for metal recycling has been reported in several studies. This research used inverse gas chromatography to evaluate the potential of flotation for NMF. The energy profile obtained from IGC showed that the difference in energies is negligible since there is only 10% surface coverage, suggesting a low recovery could 131 be expected for flotation. Fine grinding might liberate more of the fiberglass from resins and increase surface heterogeneity, but it would require energy-intensive grinding that would not be economical for this low-cost material. The application for IGC in the field of e-waste recycling has never been explored, and the study showed that the energy distribution obtained from IGC testing could be useful for a preliminary indication of flotation behavior in e-waste. The study also used a micro-FTIR technique to explore the heterogeneity of the NMF sample and to identify the polymeric components present in NMF. These techniques have not been studied in e-waste but could be used as powerful tools and approaches for NMF and e-waste assessment. 132 Chapter 6: Washability analysis of NMF for assessing gravity separation 6.1 Introduction As described in the previous chapter, the float-sink test study showed that the density difference in the NMF particles could be used to separate organic resins from the inorganic fiberglass without any additional size reduction. This chapter presents the feasibility of dense medium separation as the processing technique for separating NMF components and provides the theoretical evaluation of the gravity separation process under ideal conditions. After accessing the applicability of various separation methods, the next sub-objective was to estimate the theoretical recovery and grade for the best-suited physical separation process, to understand the feasibility of the selected process using various indices used in mineral processing, and to identify the possible application or utilization for recovered streams based on the characteristics of recovered products. To achieve these sub-objectives, the research questions addressed in this chapter are, • What is the ideal separation density for NMF recycling, and what would be its amenability to gravity separation? • How could the process outputs, such as yield and grades, be determined? • What could be the application of the obtained concentrate and the rejects? In this chapter, the washability curves and various washability indices are used as indicators to understand the feasibility of using dense medium separation for NMF recycling, and the results are compared to coal processing scenarios. 133 A version of this chapter has been published in the Recycling journal by MDPI that included the characterization of float-sink products for metal content and calorific values. The application of the organic stream as an alternative fuel to the cement industry has been accepted for publication in the Waste Management & Research journal. Another version of the chapter with the information related to washability curves, washability indices, theoretical yield, and grade estimation and product characterization using metal content, fiberglass content, scanning electron microscopy (SEM) study, and thermogravimetric analysis has been submitted for publication. Additional content related to the recommended process flowsheet and the potential application of the recycled products is available in the present chapter. 6.2 Methodology To understand the feasibility of dense medium separation for NMF recycling, the following approach was used • The washability curves were plotted, and the washability indices were estimated using the float-sink data to understand the ease of separation, • The separation density was determined based on washability curves and optimum degree of washing, • The product quality was established using metal grade, fiberglass content, and characteristics derived from TGA and SEM analysis, • A process flowsheet for the separation of organic and inorganic streams was recommended using the information obtained from the washability analysis, • The theoretical yield and grade for two and three product separation scenarios were estimated, 134 • Potential applications for recovered organic and inorganic components were suggested based on product quality and information on utilizing such products available in literature. • The calorific value of the sample was obtained by sending approximately 5 g sample to an external laboratory following ASTM D5965 guidelines (ASTM International, 2013a). 6.3 Results and discussion 6.3.1 Washability curves The yield and LOI data obtained from the float-sink test were used to derive the washability curves and analyze the ease of washing. Figure 6-1 to Figure 6-5 show the washability curves for all five tested size fractions. Figure 6-1 also provides arrows for each plot, showing the corresponding axes. The float-and-sink curves from these plots could be used to estimate the theoretical yields at a given specific gravity for separation and the quality of the rejects. The shape of the primary curve indicates that the tested NMF sample would be difficult to wash as it conforms to a plot diverging from an L-shaped curve (representing easy-to-clean material). The amount of near-gravity material at any density of separation is less than 25% for all size fractions in most cases. The 25% near-gravity material is the threshold defined in the literature for the feasibility of gravity separation, and beyond this threshold, the processing using gravity separation is formidable (Holuszko & Grieve, 1990). 135 Figure 6-1: Washability plots for -1180 + 600 µm Figure 6-2: Washability plots for -600 + 300 µm 136 Figure 6-3: Washability plots for -300 + 150 µm Figure 6-4: Washability plots for -150 + 75 µm 137 Figure 6-5: Washability plots for -75 µm 6.3.2 Washability indices To further quantify the ease of washing, the washability indices, as described in section 2.8.3, were derived for all size fractions. The degree of washing for all size fractions at different densities of separation was estimated and is shown in Figure 6-6. It shows that the maximum/optimum degree of washing of 36 was observed for -300+150 µm size fraction at 1.8 SG. The maximum/optimum degree was also observed for other size fractions at 1.8 SG, and the value ranges from 29 to 36, except for the finest -75 µm size fraction. The optimum degree of washing was achieved at 2.0 SG for the finest fraction, but the index value was significantly lower (16) than other sizes. 138 Figure 6-6: Degree of washing of different size fraction against the separation SG The washability data and curves showed that the products at 1.8 SG have a cumulative inorganic content of 12–18% for all size fractions except -75 µm, with a cumulative yield of approximately 50%. It suggests that nearly half of the NMF could theoretically be separated at a density of 1.8 g/cm3 with the concentrate inorganic content <20%. The washability number at the optimum degree of washing is shown in Figure 6-7. It shows that the washability number ranges from 15 to 28 for the NMF, except for the finest fraction, which would describe this material as difficult to wash. 139 Figure 6-7: Washability number for different size fraction at optimum separation density The washability number for the Gondwana coals (difficult to wash) is approximately 20, with an optimum ash content of 8–16% (Holuszko, 1994). The washability number for some of the lignite coal samples reported in the literature ranges from 5 to 27 (Aksogan Korkmaz & Bentli, 2017; Ayhan et al., 2011). The washability number for all size fractions except the finest size is higher than or similar to the numbers reported in the literature for lignite and difficult-to-wash coal samples. It suggests that the ease of washing of the NMF using gravity separation would be similar to lignite or the difficult-to-wash coal samples. The washability number and degree of washing define the ease of washing of a sample at a given separation density without considering the sample behavior at different densities or separation points. Another index to evaluate the ease of washing by gravity separation is the Index of Washability (IW) for coals developed by Govindarajan & Rao (1994). It utilizes the recoveries of ash and non-140 ash forming components in the products to estimate the index. Figure 6-8 to Figure 6-12 shows recoveries of organic and inorganic materials for all size fractions and used Equation 2-4 to Equation 2-8 to determine the index of washability of the tested samples. Figure 6-8 to Figure 6-12 also showed that equations described by Govindarajan & Rao (1994) had a good fit for the tested samples and can be directly used to determine the index of washability for NMF. Figure 6-8: Recovery of organic and inorganic materials for -1180 + 600 µm 141 Figure 6-9: Recovery of organic and inorganic materials for -600 + 300 µm Figure 6-10: Recovery of organic and inorganic materials for -300 + 150 µm 142 Figure 6-11: Recovery of organic and inorganic materials for -150 + 75 µm Figure 6-12: Recovery of organic and inorganic materials for -75 µm 143 According to Govindarajan & Rao (1994), typical values for the index of washability (IW) for coal ranges from 20 to 60, with a higher value indicating easy-to-wash samples. The IW for the tested NMF samples ranged from 42 to 47, which is higher than the index of washing of difficult-to-wash Turkish lignite coal, and comparable to some of the fine coal being treated using the dense-media cyclone, suggesting the possibility of gravity separation for the NMF (Fourie et al., 1980; Govindarajan & Rao, 1994; Honaker et al., 2000; King & Juckes, 1984; Majumder & Barnwal, 2004). Laboratory and pilot-scale trials using different gravity separators would be necessary to confirm their applicability in NMF separation. One of the challenges with the index of washability is the degree of difficulty associated with near-gravity materials (NGM). Two samples with the same index of washability would have different separation efficiencies depending on the amount of NGM. A lower NGM index indicates easy separation. The NGM index for each size fraction at different separation densities are shown in Figure 6-13. It shows that the NGM index at a separation density of 1.8 g/cm3 ranges from 0.09 to 0.34, suggesting a difficult to wash coal. For comparison, the NGM index for the fine coal (-500 + 75 µm) processed using a dense-medium cyclone was estimated to be 0.56 and 0.51 at the optimum density of separation (Fourie et al., 1980; King & Juckes, 1984), whereas the NGM index for Indian difficult-to-wash non-coking coal (-3+0.5 mm) was ~0.25 (Mohanta et al., 2016). 144 Figure 6-13: NGM index values plotted against specific gravity A comparison of the washability data obtained from this study, two fine coal samples (-500 + 75 µm) processed using a dense media cyclone and an intermediate coal sample (-2000 + 250 µm) processed using a RefluxTM classifier is shown in Table 6-1. The washability data for coal samples was provided in literature by Fourie et al. (1980), King & Juckes (1984), and Kopparthi et al. (2019). It shows that the NMF sample has higher inorganic/ash content than the fine coal used for the comparison study. Based on the reported data, the fine coal has a higher concentrate yield compared to the NMF. It should be noted from Table 6-1 that washability numbers suggest that the fine coal is easier to wash as compared to the NMF at the optimum separation density. In terms of the index of washability, two materials could have similar indices, but depending on the amount of near-gravity materials, their ease of washing would be different. The index of washing and NGM index is 145 obtained from the recoveries of ash and non-ash particles, affected by the locking and liberation of non-ash and ash materials, and hence, would better represent the ease of washing (Sekhar et al., 2007). The NMF sample in this study has a slightly higher index of washability when compared to coal samples, and the NMG index similar to coal 3 as shown in Table 6-1. All of the indices suggested that the ease of washing for the NMF would be comparable to that for coal 3 and would be better than coal 1 and coal 2. Laboratory and pilot-scale trials of different gravity separators would be necessary to assess their applicability for the separation of non-metal fractions. 146 Table 6-1: Comparison of washability indices for coal and non-metal fraction sample Material Size, µm Feed ash/inorganic [%] ODOW SGODOW WN IW NGM [%] NGMI @ SGODOW Conc. yield [%] Conc. ash/inorganic [%] Coal 1 -500+75 16.5 35.4 1.54 42.5 31.2 37.0 0.56 71.9 8.3 Coal 2 -500+75 19.2 39.9 1.54 49.2 37.1 32.7 0.51 68.9 8.1 Coal 3 -2000+250 28.0 32.0 1.60 21.4 33.3 18.0 0.27 69.0 15.0 NMF -1180+600 35.8 33.0 1.80 27.5 44.5 23.2 0.34 49.6 11.9 NMF -600+300 38.9 30.1 1.80 21.8 42.1 18.8 0.28 46.6 13.8 NMF -300+150 35.4 35.6 1.80 25.3 46.5 18.3 0.28 59.0 14.0 NMF -150+75 44.1 28.7 1.80 16.0 46.6 14.2 0.21 48.6 18.0 NMF All 41.0 31.3 1.80 22.8 48.0 18.5 0.27 47.3 13.8 ODOW = Optimum degree of washing, WN = Washability number, IW = Index of washability, NGMI = NGM index147 6.4 Gravity separation circuit design consideration Visual observations were completed to understand the difference in the appearance of the products obtained at various density ranges for all size fractions. Figure 6-14 to Figure 6-18 show images of products of various density ranges for all size fractions. The visual observations show a clear distinction between the products found at higher and lower than 1.8 g/cm3. The products with densities higher than 1.8 g/cm3 show a high concentration of fiberglass compared to that for the product with densities lower than 1.8 g/cm3, especially for the coarser size fractions. The images, especially for the coarser fractions for + 1.8–2.0 g/cm3 density fraction, show a mixture of fiberglass and resin materials, whereas the products in + 2.0–2. 2 and + 2.2–2.5 g/cm3 show high fiberglass concentration. The + 2.5 g/cm3 product shows the presence of liberated copper wires in the coarse product (- 1180 + 600 µm), and a similar nature could be expected for other size fractions. One of the challenges with NMF recycling is the unknown specifications for end products. In the mineral processing study, physical separation focuses on obtaining specific product grades as defined by end-users. 148 Figure 6-14: Float and sink products at various density fraction for – 1180 + 600 µm 149 Figure 6-15: Float and sink products at various density fraction for – 600 + 300 µm 150 Figure 6-16: Float and sink products at various density fraction for – 300 + 150 µm 151 Figure 6-17: Float and sink products at various density fraction for – 150 + 75 µm 152 Figure 6-18: Float and sink products at various density fraction for – 75 µm153 The visual observations combined with the washability analysis suggest that a two-product separation at 1.8 g/cm3 is capable of separating organic and inorganic components. Using a separation density of 1.8 g/cm3, the yield, inorganic content, and other relevant information of a two-product separation are shown in Table 6-2. The analysis was performed by separating the NMF (as received) into two size fractions at a cut size of 500 µm to improve the separation efficiency potential. The size separation at 500 µm was selected for the following reasons: • A typical cut-off size coal cleaning operations is 500 µm (Laskowski, 2001; Zimmerman, 1979), • The geometric median size (size modulus) for the sample, as described by the Rosin-Rammler model, was estimated to be 499 µm. Table 6-2 shows that two-product separation at 1.8 g/cm3 would separate nearly half of the total NMF throughput with an inorganic content of 12–15%, whereas the rejects would have an inorganic content of 59–69 %. The washability indices show that the gravity separation for this material would be difficult, as discussed in section 6.3.2 and shown in Table 6-1. 154 Table 6-2: Two-product separation at 1.8 g/cm3 Description + 500 µm - 500 µm Total Feed inorganic [%] 34.1 45.8 41.0 Concentrate yield [%] 48.9 46.1 47.3 Concentrate inorganic [%] 12.4 14.8 13.8 Reject yield [%] 51.1 53.9 52.7 Reject inorganic [%] 59.6 68.8 65.1 Index of washing 43.8 51.0 48.0 Near-gravity material @ 1.8 SG [%] 22.2 15.9 18.5 NGM index @ 1.8 SG 0.33 0.23 0.27 The reject inorganic content could further be increased if a three-product separation is used. In the case of three-product separation, rejects at 1.8 g/cm3 would be subjected to another cleaning stage at 2.0 or 2.2 g/cm3. The analysis showed that if the second stage of separation is performed at 2.2 g/cm3, a relatively low reject yield would be achieved for the + 500 µm size fraction. Therefore, the second stage of cleaning at 2.0 g/cm3 was selected for further analysis, as shown in Table 6-3. Since there is no known industrial process for NMF recycling, a cost-benefit analysis would be required to support the further separation by introducing an additional step for density separation. 155 Table 6-3: Three-product separation at 1.8 and 2.0 g/cm3 Description + 500 µm - 500 µm All Feed inorganic [%] 34.1 45.8 41.0 Concentrate yield [%] 48.9 46.1 47.3 Concentrate inorganic [%] 12.4 14.8 13.8 Middling yield [%] 24.9 12.7 17.7 Middling inorganic [%] 46.8 43.8 45.5 Reject yield [%] 26.3 41.2 35.0 Reject inorganic [%] 71.8 76.5 75.0 Near-gravity material @ 2.0 SG [%] 20.6 15.0 17.3 NGM index @ 2.0 SG 0.26 0.22 0.24 Table 6-3 shows that the three-product separation is possible and would produce the rejects at an inorganic content of 71–76 %, thus, increasing the inorganic concentration in the rejects by 20% and 10% for the coarse and fine materials, respectively. The middling fraction could be recirculated back to the circuit for further liberation, thus improving the overall circuit recovery. Kartawijaya (1982) and Klein (1992) have reported that heavy media such as magnetite and ferrosilicon are capable of achieving the required separation density in a dense media cyclone circuit for coarse (+ 0.5 mm) and fine (-0.5 mm) coal cleaning. Kartawijaya (1982) and Shi (2016) showed that the maximum limit of relative density obtained by ferrosilicon is 3.2 after allowing for some contaminations in plant operation. Klein (1992) has suggested that magnetite is widely used for medium densities ranging from 1.3 g/cm3 to 1.9 g/cm3 in coal preparation. A mixture of 156 magnetite and ferrosilicon has also been used to produce dense medium with reduced viscosities and a relatively lower cost (Klein, 1992). However, the rheology of dense media suspensions when subjected to the NMF cleaning process, especially for fine NMF feed (- 500 µm), should be studied to confirm their suitability. All the float-and-sink density fractions were divided into the product fractions, as suggested in Table 6-3 for subsequent product characterization. All further analysis was performed based on this three-product separation. 6.4.1 Fiberglass content analysis The three-product separation showed that the rejects (+2.0) would have as high as 76% inorganic materials, including fiberglass and residual metals. The fiberglass concentration in all the density fractions was analyzed to estimate their recoveries in various products. Figure 6-19 and Figure 6-20 show the concentration and recoveries of fiberglass at various density ranges. It shows the highest grade and recovery in rejects (+2.0 SG) with some fiberglass in middling (+1.8-2.0 SG). Fiberglass concentration in the finer fractions is higher due to higher fiberglass content in the fine feed materials, as discussed in Chapter 4. The fiberglass concentration in reject could further be increased if the particles are ground to a finer size. However, a finer particle size would also reduce the efficiency of separation. The middling fraction could be reground for further liberation, especially for the coarse size fraction as the middling fraction content is ~ 35% of the total available fiberglass. The lab-scale and pilot-scale trials would be required to optimize the grades and recoveries. 157 Figure 6-19: Fiberglass concentration and recoveries in various SG ranges for + 500 µm Figure 6-20: Fiberglass concentration and recoveries in various SG ranges for - 500 µm 158 Pure fiberglass has an average density of 2.6 g/cm3, suggesting that completely liberated fiberglass should report to the + 2.5 SG range. Very low recoveries of fiberglass in the +2.5 SG confirm that the probability of complete liberation of fiberglass from resin is very low using physical processing methods. A chemical or heat treatment would be required to obtain pure fiberglass. The light fraction (-1.8 SG) would have the liberated resins with residual fiberglass along with the components from the FR-2 boards, such as cotton/paper fibers. 6.4.2 Metal content analysis Metal content (grade) in various products was analyzed to estimate the recovery of residual metal in various density ranges. The recovery of these residual metals provides an incentive for NMF recycling and improves the overall metal recovery of the PCB recycling process. Figure 6-21 to Figure 6-28 show the concentration and recovery of various metals in various density ranges for coarse and fine samples. It shows that most of the metals such as copper, iron, lead, manganese, nickel, tin, and zinc, that are not associated with fiberglass or resin matrix are concentrated in the heaviest density range (+2.5 SG) for both coarse and fine size fraction due to their high density. These residual metals are mostly liberated metals that have reported to the NMF due to separation inefficiencies at the recycling plant. The waste printed circuit boards were processed using a wet shaking table at this recycling facility, and the overall process did not include any rougher, cleaner, re-cleaner, or scavenger stages, as usually practiced in the mineral processing industry, to maximize grade and recoveries. For copper, the concentration is higher in the coarse heavier product (59.1% Cu) than in the fine heavier product (27.5% Cu), suggesting that long strands of copper metals were not crushed 159 properly during the shredding and size reduction processes, and thus, reported in the + 500 μm size fraction. This result suggests that adding a scavenger stage would enable the recovery of most of these metals and improve the overall process recovery without any additional size reduction and would provide the incentive needed for NMF recycling. Higher metal concentration in the heaviest fraction also suggests that separating these metals from the NMF can be a potential solution for removing hazardous metals if the NMF is sent to incineration or cement plants for energy recovery. Figure 6-21: Concentration and distribution of Al, Sb and Ca in various SG ranges for + 500 µm 160 Figure 6-22: Concentration and distribution of Cu, Fe and Pb in various SG ranges for + 500 µm As discussed before, antimony is used in PCB in the form of antimony oxide to improve the activity of flame retardants. It is added to the PCB resins during laminate production. Since most of the resins reported to the – 1.8 and + 1.8–2.0 SG fraction, it should be expected that the antimony concentration and distribution are higher in this fraction. In the case of calcium and aluminum, these elements are a part of the fiberglass. As most of the fiberglass reported to the + 2.0–2.5 SG fractions, it should be expected that the calcium and aluminum concentration and distribution in this density range should increase as well. In the case 161 of free aluminum that is not bonded with the fiberglass, it should report to the +2.5 SG fraction due to its density of 2.7 g/cm3. Figure 6-23: Concentration and distribution of Mn, Ni and Sn in various SG ranges for + 500 µm Figure 6-24: Concentration and distribution of Zn in various SG ranges for + 500 µm 162 Figure 6-25: Concentration and distribution of Al, Sb and Ca in various SG ranges for - 500 µm 163 Figure 6-26: Concentration and distribution of Cu, Fe and Pb in various SG ranges for - 500 µm 164 Figure 6-27: Concentration and distribution of Mn, Ni and Sn in various SG ranges for - 500 µm Figure 6-28: Concentration and distribution of Zn in various SG ranges for - 500 µm The total metal concentration in both coarse and fine fractions are shown in Figure 6-29 and Figure 6-30. 165 Figure 6-29: Total metal content and distribution in various SG ranges for + 500 µm Figure 6-30: Total metal content and distribution in various SG ranges for - 500 µm 166 Figure 6-29 and Figure 6-30 show the high metal concentration in the heaviest fractions that could be recovered through a scavenging step before the organic and inorganic stream recovery and could be sent directly for leaching or smelting. 6.4.3 Thermogravimetric analysis The TGA test was performed to analyze the progressive change in the sample weight with increasing temperature. This test would provide a better understanding of the removal of organic matter during combustion with respect to changing temperature. The TGA thermograph for all density ranges for the coarse and fine samples is shown in Figure 6-31 and Figure 6-32, respectively. It shows a similar overall remaining weight after combustion (residual weight) as to the inorganic content in various density ranges listed in Table 6-3. It also shows that the weight of the +2.5 SG fraction first decreased and then increased for both size fractions. The weight loss was due to organic volatilization, whereas the increase in the weight can be attributed to the oxidation of the metals present in the sample at higher temperatures (Samal, 2016). The weight loss derivate curve was plotted to analyze the decomposition and combustion processes further. 167 Figure 6-31: TGA thermograph for various SG ranges for + 500 µm Figure 6-32: TGA thermograph for various SG ranges for - 500 µm size fraction 168 Figure 6-33 and Figure 6-34 show the derivative thermogravimetric (DTG) curves that provide the rate of change in the sample weight with respect to the temperature for a given material. The height/depth of the derivative curve (rate of weight loss) would be proportional to the amount of organic matter present in the sample and the particle size. A higher amount of organic matter should have higher depth, as shown in Figure 6-33 and Figure 6-34 that the depth for +1.8-2.0 SG is more than +2.0-2.5 SG and +2.5 SG fraction. The depth for the finer (-500 µm) materials is also higher than that for the coarser samples (+500 µm). Figure 6-33 and Figure 6-34 show two distinct regions of decomposition of the separated streams. The first fast decomposition region ranges from 2500C to 3500C, peaking around 310–3200C, whereas the second slow decomposition region ranges after 4000C, peaking around 500–5500C, representing the presence of components form FR-2 and FR-4 boards. The small decomposition region seen in the fine fraction from 1500C to 2500C is mostly due to the phosphorous vaporization associated with FR-2 boards. The coarse light product (-1.8 SG) shows a decomposition region from 3500C to 4500C, representing the decomposition of phenolic resins, thus, indicating the presence of FR-2 board components. The FR-4 laminates have outstanding physical properties compared to the FR-2 boards in terms of mechanical and electrical strength. The fiberglass has four to eight times higher tensile strength and Young modulus than the cotton paper (Kelley & Trobough, 2016b; Zsiros, 2010). It suggests that during the hammer milling, the FR-2 laminates would easily be broken into smaller pieces, and thus, report to the coarser end of the comminuted product. A complete breakage behavior testing on individual laminates before any metal plating would be required to prove this hypothesis. 169 Figure 6-33: Derivative thermogravimetric curves for various SG ranges for + 500 µm Figure 6-34: Derivative thermogravimetric curves for various SG ranges for - 500 µm 170 6.4.4 Scanning electron microscope (SEM) SEM analysis is an efficient way to study the association of different elements in a given sample and can also be used to analyze the surface morphology. The SEM analysis was used to analyze the characteristics of products obtained from the float-sink tests. Figure 6-35 to Figure 6-42 show SEM micrographs for all density range products for coarse and fine samples. Both figures show that the lowest density ranges have more regular-shaped particles, suggesting the presence of resins and maybe some foreign plastic particles. The +2.0–2.5 density ranges show the abundance of fiberglass particles, as evident from their fibrous shape. The +1.8–2.0 density rage shows a mixture of both particle types; hence, should be sent back for further processing. The heaviest density fraction (+ 2.5 SG) shows the presence of wire-like structures. These particles are the pure copper wires present in the NMF sample. These particles are more abundant in the coarse size fraction, confirming relatively higher copper content in the coarse heavy product. As shown in the SEM image, the accumulation of resin particles in the lighter density increases the LOI content of this fraction, as obtained from the LOI test results. The residual metals are accumulated in the +2.5 SG range, which should be recovered before the organic and inorganic material separation using a scavenging shaking table step. 171 Figure 6-35: SEM micrograph for -1.8 SG fraction for + 500 µm Figure 6-36: SEM micrograph for +1.8-2.0 SG fraction for + 500 µm 172 Figure 6-37: SEM micrograph for +2.0-2.5 SG fraction for + 500 µm Figure 6-38: SEM micrograph for +2.5 SG fraction for + 500 µm 173 Figure 6-39: SEM micrograph for -1.8 SG fraction for - 500 µm Figure 6-40: SEM micrograph for +1.8-2.0 SG fraction for - 500 µm 174 Figure 6-41: SEM micrograph for +2.0-2.5 SG fraction for - 500 µm Figure 6-42: SEM micrograph for +2.5 SG fraction for - 500 µm 175 6.5 Recommended flowsheet for NMF recycling Figure 6-43 shows a possible flowsheet for recycling the NMF, based on the washability analysis and the results obtained from the three-product separation process assessment. The dotted blue region shows the current processing circuit at the Ronin8 recycling plant. It should be noted that the flowsheet required to be studied in more detail for the sizing and selection of the most effective processing units for this sample, and the individual units would also require optimization for improved efficiency. Another shaking table is added in the flowsheet as a scavenging stage to recover the residual metals present in the NMF, thus, increasing the overall metal recovery. In this flowsheet, the tailing from the additional shaking table is suggested to be fed to a hydrocyclone to remove fine (-75 µm) particles. The inorganic content in this fraction is 74–75%, as shown in Figure 4-9, which is similar to that for rejects obtained from the three-product separation process. The gravity separation process at these fine particle sizes is highly inefficient; hence, this size fraction can be bypassed directly to the final inorganic material stream. The hydrocyclone underflow is recommended to be screened at 0.5 mm and then fed to the gravity separation circuit to separate organic materials from inorganic materials. The classification at 0.5 mm would help to improve the efficiency of the gravity separation process by feeding a narrow size fraction. 176 Figure 6-43: Recommended flowsheet for NMF recycling Shaking table Residual metalsMiddlingTailingsCircuit boardsSize reductionScreening @ 3 mmNon-metal tailingsMetal concentrateOversizeWet shaking tableMiddlingsScreening @ 0.85 mmSonic liberationOversizeUndersizeUndersizeHydrocycloneScreening @ 0.5 mmGravity separation @ 1.8 SGGravity separation @ 2.0 SGGravity separation @ 1.8 SGGravity separation @ 2.0 SGOrganic materialsInorganic materialsUnderflow (+ 75 µm)Overflow (- 75 µm)Oversize Undersize Floats Floats Sink Sink Sink Sink Floats Floats Floats Floats 177 The floats at 1.8 SG would contain the recovered organic materials, whereas the sink from this stage would be fed to the second stage gravity separation at 2.0 SG. The floats from this stage could be sent to the sonic liberator for increased liberation and recirculated back to the shaking table or sent to the inorganic stream depending on the pilot-scale trails. The sink fraction from this stage would be the final inorganic materials. The final inorganic content is estimated to be ~14% and 75% for the recovered organic and inorganic fractions. The gravity separation units required to separate the organic and inorganic materials at 1.8 and 2.0 SG need to be further studied. Several potential candidates, as per literature, that could be studied are dense media cyclones, spirals, Reflux classifiers, water-only cyclones, or enhanced gravity separators such as Knelson or Flacon concentrators (Das & Sarkar, 2018; Iveson et al., 2014; Modiga et al., 2019). Once a suitable unit is selected, the circuit could be optimized by running pilot-scale trails. 6.6 Potential candidates for gravity separation As mentioned in the previous section, the gravity separation unit is required to separate the organic and inorganic materials at densities of 1.8 and 2.0 g/cm3. A variety of gravity separators should be tested for the NMF sample, and the most suitable separator should then be optimized by running pilot-scale trails. This section list some of the potential candidates for gravity separation based on available literature in the coal and mineral processing industry. It should be noted that the application of these technologies for NMF would require extensive laboratory and pilot-scale testing. The effect of particle shape also needs to be studied as the NMF sample contains fiberglass particles with a large aspect ratio. 178 Dense media cyclone (DMC) de Korte (2012) reported successful implementation of dense media cyclone in South Africa, Belgium, and China for fine coal processing, and a high separation efficiency could be achieved using a proper optimization of cyclone geometry, dense medium, and cyclone feed pressure. Ma et al. (2018) showed that difficult-to-clean fine coal (-1+0.15 mm) could be processed using dense media cyclone. Pilot plant trials at Koornfontein Colliery in South Africa showed the possibility of using dense media cyclone with high efficiency for fine coal down to 75 µm with an effective density of separation of 2.14 g/cm3 (de Korte, 2002). Several researchers have reported that particle shape influences the separation efficiency in centrifugal classifiers (hydrocyclone). Coarse particles with a flaky and fibrous structure such as mica and asbestos often get misplaced in overflow stream due to their shape and high drag coefficient (Abdollahzadeh et al., 2015; Kashiwaya et al., 2012; Tang et al., 2018; Wills & Finch, 2016c). Li et al. (2013) have suggested that graphite particles could be purified using dense media separation at a density of 2.0 g/cm3. A similar phenomenon could be expected for the fiberglass particles in DMC. Spiral concentrator or flowing film concentrator Successful applications of spiral concentrators for difficult to clean fine coal has been reported by Yang et al. (2018), Tozsin et al. (2018), Bahrami et al. (2018), Ma et al. (2018), Sivrikaya (2014), and (Holland-Batt et al., 1984). Kademli & Gulsoy (2006; 2012) showed excellent separation of mica (2.7–3.4 SG) from feldspar (2.65 SG) using a spiral concentrator, especially for fine particle size ranges (-212+75 µm). Ulukkulama et al. (2018) reported that graphite could also be upgraded 179 using spirals to a grade up to 80% for -500+50 µm size fraction. In the case of flowing-film concentrators, flatter particles have a less tendency to move/roll (Gupta & Yan, 2016) and it might also help the separation of heavy fiberglass from light organic particles. Shaking table and multi-gravity separator Several researchers have suggested the application of shaking table and multi-gravity separators for difficult to clean fine coal cleaning with or without desliming stage (Ç[idot]çek et al., 2008; Majumder et al., 2007; Menéndez et al., 2007; Özbakir et al., 2017; Tozsin et al., 2018). Hoseini et al. (2016) have suggested using a combination of spirals and shaking tables for the enrichment of mica for -2+0.15 mm particle size range. Gershenkop & Khokhulya (2004) also suggested the application of a shaking table for mica recovery for -750+200 µm particles. Shaking table and multi-gravity separator also have shown highly efficient separation for graphite ore with flaky structure (Chehreh Chelgani et al., 2016; Jara et al., 2019; Koca & Koca, 2005). In the case of a shaking table, flat particles have a higher tendency for being stuck on the deck and move to the heavy discharge end of the table (Gupta & Yan, 2016). Other separators such as LARCODEMS that could handle raw coal of size -100+0.5 mm and Dyna Whirlpool separator could treat fine coal as well as diamonds, tin, and lead-zinc ore in -30+0.5 mm size range (Wills & Finch, 2016b) that have also been studied in plastic recycling (Bauer et al., 2018; Choi, 2004; Dodbiba & Fujita, 2004) could also have application in NMF. Fluidized bed separators such as Reflux classifiers have also been successfully utilized in fine coal treatment (Iveson et al., 2014; Kopparthi et al., 2019) and might even be investigated for the NMF gravity separation. 180 6.7 Potential application of recycled components The float-sink test showed the possibility of separating organic and inorganic materials present in the NMF using gravity separation. The separated products would then be used as raw materials for manufacturing or used as secondary resources. Various researchers have shown the possible end-use of NMF, as received after metal recovery, that can be used as a base to provide information regarding the possible end-use of the recovered streams. 6.7.1 Organic materials The organic materials recovered from this process can be used in several applications. It can be used as a filler, adsorbent, or alternative fuel in the cement industry. Alternative fuel in the cement industry The most traditional approach for using organic materials would be as an alternative fuel in cement manufacturing. The organic matter has a high LOI, suggesting that it would also have a relatively high heating value. Bizzo et al. (2014) reported that the NMF has a gross calorific value of 11.63 GJ/t than 4.88 GJ/t for the whole waste PCB, when the NMF was separated at a density of 2.89 g/cm3 using organic liquids. Alternative fuels such as biomass, household waste, and non-hazardous industrial and commercial waste have regularly been used in the cement industry to reduce fossil fuel consumption, provide cost savings, and significantly reduce greenhouse gas emissions (Rahman et al., 2015). The average Canadian coal replacement rate was 10% and as high as 30% in Quebec (The Pembina Institute and Environmental Defence, 2014). European countries such as Germany had an alternative fuel substitution rate of 65% in 2010–12 (Sharabaroff et al., 2017). Shumal et al. (2020) 181 showed that ~130 million tonnes of waste had been treated in more than 600 waste-to-energy plants globally. The yield and inorganic content of the concentrate and middling were used to estimate the combustible recovery of the NMF processing using Equation 6-1. 𝐶𝑜𝑚𝑏𝑢𝑠𝑡𝑖𝑏𝑙𝑒 𝑟𝑒𝑐𝑜𝑣𝑒𝑟𝑦 = 𝑌 (100 − 𝐼𝐶𝑐)(100 − 𝐼𝐶𝐹) Equation 6-1 where, Y is the yield of the concentrate ICC and ICF are the inorganic content of the concentrate and feed. The combustible recovery using Equation 6-1 was estimated to be 69% and 16% for concentrate and middlings, respectively, suggesting that the gravity separation process would be able to recover up to 85% of the total heating value present in the NMF, which could provide a potential source of energy recovery. Several traits of NMF concentrate (organic components) were analyzed to understand its applicability as an alternative fuel for the cement industry. The results obtained from the proximate analysis (moisture, ash, volatile matter, and fixed carbon content), ultimate analysis (carbon, hydrogen, nitrogen, oxygen, and sulfur), and chlorine content are listed in Table 6-4. It showed that the moisture content of the tested sample was low, as the tested samples were oven-dried; hence, most of the water was removed before the testing. It should be noted that the moisture has a negative effect on the economy of alternative fuels. It reduces the net calorific value of the 182 fuel and reduces combustion efficiency. For a water-based recycling process, the moisture content must be accounted for in the economy of alternative fuels. The NMF has a high volatile matter content with low ash content and has a similar value as the refuse-derived fuel, which is more favorable for alternative fuel. The ash in the sample is from the inorganic residual fiberglass present in the NMF. Table 6-4 also shows that the CHNOS concentration of the NMF concentrate is comparable to that for other widely used alternative fuels in the cement industry. However, a high nitrogen content would also increase the risk of NOx emission (Shumal et al., 2020). Table 6-4: Properties of alternative fuels and NMF organic stream (Capablo et al., 2009; Chinyama, 2011; Sharabaroff et al., 2017; Zieri & Ismail, 2019) Description Tire waste Municipal solid waste Refuse-derived fuel Waste solvent NMF organics (this study) Moisture - - - - 1.7 Ash 15.6 35.2 10.9 - 13.8 Volatile matter - 64.8 82.1 - 68.9 Fixed carbon - - - - 15.6 Total carbon - 34.9 47.1 47.7 49.2 Nitrogen 0.24 1.0 0.7 1.0 1.6 Oxygen - 23.1 29.4 23.1 30.8 Hydrogen - 4.7 4.7 8.2 4.9 Sulfur 1.5 0.2 0.2 0.7 0.08 Chlorine 0.15 1.0 0.6 2.4 0.78 183 Rahman et al. (2015) and the Pembina Institute and Environmental Defence (2014) reported that the sulfur and chlorine content should be < 2.5% and 0.2%–0.5%, respectively, to be a viable option as an alternative fuel. The sulfur content in the NMF concentrate is lower than the limit suggested by Rahman et al. (2015), whereas the chlorine content is slightly higher than suggested limits. Sulfur is mostly present in PCB as a contaminant from the etching process and as the solder to mask impurities (Tatariants et al., 2017) and would report to tailings during the concentration process, thus, decreasing the overall sulfur content in the NMF organic stream. In terms of chlorine, various researchers have shown the presence of chlorine in the circuit board resin matrix in the form of chlorine-based flame retardants and as a part of some plastic parts, cable insulators, coatings, rubber, and paper reinforcements (Nimpuno et al., 2009). It should be noted that the chlorine content varies widely depending on the type of PCB. Yao et al. (2015) have shown that the chlorine content in NMF ranges from 0.02 to 1.67%. Table 6-5 shows the net calorific value of NMF concentrate and various alternative fuels used in the cement industry. It should be noted that the listed values are the net heating values and do not account for any moisture present in the material. The gross heating value would change proportionally depending on the amount of water present in the fuel. It shows that the heating value of the NMF concentrate is similar or higher than the listed alternative solid fuels and would be classified as a medium grade fuel. It is also higher than the heating value of peat coal and is comparable to lignite coal. 184 Table 6-5: Heating values of various alternative fuels and studied NMF (Capablo et al., 2009; Chinyama, 2011; Sharabaroff et al., 2017; Zieri & Ismail, 2019) Material Net calorific value [GJ/t] Material Net calorific value [GJ/t] Tire/rubber waste 26–28 Animal meal 15–17 Municipal solid waste 8–15 Peat coal 18 Refuse derived waste 21 Lignite coal 16–21 Waste oil/solvents 25–35 High ash bituminous coal 24 Waste plastic 29–40 NMF (as received) 15.1 Dry wood 16 NMF organics 21.3 Another challenge in using NMF as an alternative fuel in the cement industry is fuel ash composition. The fuel ash would combine with the raw materials and become a part of the clinker. High silica content in fuel ash could reduce the amount to new silica sand needed as feed but could also negatively affect the overall composition of clinker. A high level of alkali oxides (potassium and sodium) would also have an adverse effect on cement quality (Chinyama, 2011). Table 6-6 shows the composition of the residual ash left after the combustion of the NMF concentrate and coal ash (FHWA, 2016). The concentration of alkali oxides in the NMF concentrate is less than 0.6%. It shows that the composition of the residue is similar to coal ash. The NMF concentrate residue is high in silica, alumina, and calcium oxide due to the presence of residual fiberglass in this fraction, providing an additional source of raw materials for the clinker production. 185 Table 6-6: Chemical composition of metal oxides of NMF concentrate and coal ash Metal oxide NMF organics (this study) Bituminous (FHWA, 2016) Subbituminous (FHWA, 2016) Lignite (FHWA, 2016) SiO2 44.7 20–60 40–60 15–45 Al2O3 16.1 5–35 20–30 10–25 Fe2O3 1.2 10–40 4–10 4–15 CaO 14.9 1–12 5–30 15–40 MgO 2.5 0–5 1–6 3–10 Na2O 0.4 0–4 0–2 0–6 K2O 0.2 0–3 0–4 0–4 Another factor for the applicability of alternative fuel in the cement industry is the presence of heavy metals in the fuel that would end up in the clinker and would reduce the overall strength of the produced cement. According to Rahman et al. (2015), the heavy metal content in alternative fuels should be less than 2500 ppm, and the content of volatile and semi-volatile metal should be less than 10 ppm for mercury and less than 100 ppm for cadmium, thallium, and mercury combined. The metal content analysis shown in section 6.4.2 suggests that the total metal concentration in the organic concentrate is higher than the 2500 ppm limit. However, most metals are present in the form of aluminum and calcium from the fiberglass (0.8%) and could potentially provide the feed materials for the clinker. The concentration of mercury, cadmium, and thallium is almost zero in the organic fraction. 186 The analysis of the NMF organic fraction suggests that it could be used as an alternative fuel in the cement industry and provide a safe disposal route for nearly 50% of the total NMF material. However, a complete evaluation of the NMF organic concentrate should be performed in terms of its combustion efficiency, utilization/substitution ratio, combustion gas volume, handling and storage cost, PCDD/F emissions, and other related factors. Fillers in composites Researchers have also shown that the NMF can be used as filler in composites; however, the presence of inorganics in the NMF decreases its usability (Wang et al., 2018; Zhang et al., 2017; Zhang et al., 2017) and removal of inorganics from the NMF increases the strength of the high-density polyethylene composite. Yang et al. (2019) and Zhang et al. (2017) have used triboelectric separation to recover organic materials from the NMF obtained from a recycling plant in China to increase its reusability. The plant used dry processes such as magnetic and electrostatic separation to separate metals. The triboelectric separation is also a dry process; hence, it cannot be used for flowsheets based on water medium. A comparison of the feed and product characteristics from this study and data available in the literature are summarized in Table 6-7. It shows that gravity separation could theoretically separate the organic and inorganic materials more efficiently and with higher recovery. The organic content in the concentrate is higher than reported in other literature and can be increased further by reducing the separation density if needed. A higher organic/lower inorganic content material can then be effectively used as filler in composite manufacturing. 187 Table 6-7: NMF feed and product characteristics of different studies Description Zhang et al. (2017) Yang et al. (2019) This study Particle size [mm] - 1.4 - 0.5 + 0.25 - 1.18 Feed organic [%] 54.7 73.0 59.0 Conc. yield [%] 46.8 28.8 47.3 Conc. organic [%] 69.4 85.1 86.2 Conc. organic recovery [%] 59.4 33.6 68.9 Upgradation ratio [-] 1.27 1.17 1.46 Reject yield [%] 34.1 36.5 35.0 Reject organic [%] 39.3 59.2 25.0 Reject organic recovery [%] 24.5 29.5 14.8 Upgradation ratio [-] 0.72 0.81 0.42 Activated carbon Another potential application of the organic materials recovered from NMF processing could be to prepare activated carbon due to its high carbon content. The organic materials would be pyrolyzed at a temperature ranging from 600 to 8000C to remove the volatile matter. The remaining char residue can be mixed with solid KOH and then activated in nitrogen or carbon dioxide atmosphere at 600 to 9000C for two hours (Kan et al., 2016; Ke et al., 2013; Rajagopal et al., 2016). Ke et al. (2013) used NMF with 72% initial carbon to produce porous carbon with a specific surface area up to 3,112 m2/g in a nitrogen atmosphere at 6000C pyrolysis temperature and 9000C 188 activation temperature. A comparison of the initial composition of samples used in the literature compared to this study is listed in Table 6-8. Table 6-8: Feed composition before pyrolysis for the preparation of activated carbon Description Kan et al. (2016) Ke et al. (2013) Rajagopal et al. (2016) This study Materials NMF powder FR-3 NMF FR-2 boards NMF conc. Total carbon [%] 42.2 72.3 37.7 49.2 Oxygen [%] 17.1 17.1 - 30.8 Nitrogen [%] 5.7 - - 1.6 Metals [%] 31.9 1.5 51.4 3.1 Bromine [%] 3.2 6.6 - - Others [%] - 2.5 10.9 15.4 The FR-3 boards have cotton paper as reinforcement, hence, had very high carbon content to start with for Ke et al. (2013). This study showed that the recovered organic matter is very high in carbon content, which would be favorable to produce activated carbon by methods suggested in research. 6.7.2 Inorganic materials The final inorganic material (sinks) obtained from the NMF recycling flowsheet is very high in fiberglass (72%), which could be used as a filler in building materials to develop porous silica other adsorbents or could be fed back to the printed circuit board manufacturing process. 189 Filler in building materials The recycled inorganic materials could be directly used as fillers in building materials. Marques et al. (2013) have suggested that due to its lighter weight, finer grain size, and thick fiberglass, the NMF could improve the mechanical strength. Wang et al. (2012) have suggested that the NMF can be added in cement mortar and would increase its water retention property and decrease bulk density without significantly affecting the compressive and flexural strength. The ideal ratio of the inorganic fraction in construction materials or cement mortar needs to be studied in detail for its application. Metal adsorbent Researchers have also suggested the application of the NMF as a toxic heavy metal adsorbent for wastewater treatment (Hadi et al., 2015; 2013). Hadi et al. (2013) suggested impregnating the NMF with the 1 M potassium hydroxide solution for three hours and then activating the slurry at 2500C for three hours in a muffle furnace in an inert atmosphere. The activated sample was washed down several times with distilled water and then dried for later use. The activated material with a surface area of over 200 m2/g had a similar elemental composition as the NMF without the carbon and bromine that were burnt off during the activation process. The activated material could be used to adsorb copper, lead, cadmium, zinc, cobalt, and nickel ions from wastewater. Porous silica Another use of the inorganic material in the NMF could be the preparation of high purity porous silica. The fiberglass used in circuit boards is composed of 52–56% high-quality silica, which could be used to produce amorphous porous silica. Porous silica can be used in many applications, 190 ranging from life and space science to physics of high-energy particles due to its large surface area, optical properties, and very low thermal conductivity (Pajonk, 2003). Bazargan et al. (2014) have shown that the NMF with 51% silicon (from XRF) can be treated with 4M nitric acid at 900C for six hours, followed by a heat treatment at 5000C for three hours, and it could produce 99% pure silica with a specific surface area of over 300 m2/g. The inorganic materials obtained in this study have a silica content of 38% (ICP-MS). Laboratory testing determining the optimal conditions to produce porous silica from this sample would be required. Printed circuit board manufacturing The most useful application of the recovered inorganic stream would be as raw material for printed circuit board manufacturing to promote a true circular economy. The inorganic material contains a high concentration of fiberglass that could be fed back to the circuit board manufacturing process. The typical composition of the inorganic stream from this study and fiberglass used in e-glass manufacturing, the most common type of fiberglass used in the electronics industry (Kelley & Trobough, 2016a), is listed in Table 6-9. It can be seen that the composition of the NMF inorganic stream obtained from the recycling process would be very similar to the composition of the e-glass. The residual organic materials present in the NMF inorganic stream would be removed during the manufacturing process of new fiberglass and could potentially provide combustion energy if captured. The NMF inorganic materials could be used as the secondary source of raw materials in the manufacturing stage of reinforcement, where raw materials are melted in a furnace at 1300–15500C for the production of fiberglass filaments. 191 Table 6-9: Chemical composition of NMF inorganic stream and e-glass Component NMF inorganic (this study) E-glass SiO2 52.9 52–56 CaO 21.3 16–25 Al2O3 16.8 12–16 BaO 0.2 5–10 Na2O 0.4 0–2 K2O 0.1 0–2 MgO 0.7 0–5 Fe2O3 0.5 0.05–0.4 TiO2 0.5 0–0.8 Organic content 27.6 - It should be noted that the inorganic components also contain several metals such as copper, lead, and antimony, that could have an adverse effect on the physical and mechanical properties of the new filaments. A comprehensive study would be necessary to investigate the effect of using NMF inorganic materials on the physical and mechanical properties of the manufactured filaments, along with proper substitution ratio, combustion gas volume, handling and storage cost, PCDD/F emissions, and other related factors. 6.8 Summary The difference in the densities of various components of the NMF provided an opportunity for gravity separation. The float-and-sink test using heavy liquids conducted on various size fractions 192 showed a clear separation of organics from inorganics at an optimum density of 1.8 g/cm3. The washability analysis showed the applicability of gravity separation to recover residual metal and separate the organic and inorganic streams for the NMF. The gravity-based separation flowsheet with three-product separation could recover a cleaner organic fraction with a 47% yield at 86% organic content and a reject stream with a 35% yield at 72% fiberglass content. The washability curves and various washability indices suggest that the material would be classified as difficult-to-clean. However, comparing the indices with the similar size ranges for fine coal suggested that the indices are relativity similar to those for the fine coal being processed or studied using a dense medium cyclone, spirals, or RefluxTM classifiers. The washability curves and washability indices have been regularly used to determine the gravity separation behavior for coal preparation. This chapter showed that these methods could also be adopted for non-metal fraction recycling and provide the theoretical estimation of the density-based separation circuit similar to coal processing. The potential application of the recovered products was studied through various examples from literature of the utilization of the NMF. The feed properties of the samples used in these studies were compared with the characteristics of the products expected from an ideal process separation. It shows that the organic matter recovered from NMF processing could be used as an energy source in the cement industry or to prepare activated carbon. In contrast, the inorganic stream could be used as filler in concrete, heavy metal adsorbents or could potentially be reused for the printed circuit board manufacturing process. Future test work is required to study the impact of the NMF recycled products on these potential applications. 193 Chapter 7: Effect of the sample variability 7.1 Introduction The previous chapter showed the applicability of gravity separation to separate residual metals, organic components (resins), and inorganic components (fiberglass) in various streams. The potential applications of recovered organic and inorganic streams were also discussed. However, due to ever-changing technologies, the feed stream to a recycling plant is never consistent. One of the issues with any process in the e-waste recycling industry is the variability in the quality of the feed stream. As practiced in the mining industry, feed blending to provide a consistent feed quality to the processing plant is not implemented in the recycling industries. At the same time, the recycling industry processes material originating from different parts of the world with a different timeline of production, making it impossible to track the feedstock in terms of their compositional differences. A process designed for one type of feedstock might not work efficiently when the composition and design of the incoming feed has changed after a few years. Hence, it is vital to design a flowsheet that could be modified or adapted to the feed variation. The major contributor to the varying feed characteristics is the differences in the types and compositions of circuit boards present in various electronics equipment and different manufacturing timeframes. The circuit boards are processed at a facility without any pre-sorting based on their types or blending to keep the feed characteristics consistent. The recycling facility receives circuit boards collected by different programs from different areas and dissembled at different locations. This creates the issue of uncertainty regarding their types and composition. The received circuit boards are weighed for throughput estimation and then directly processed. This 194 process affects the feed characteristics of the plant, and thus, also affects the characteristics of the obtained NMF. This chapter discusses the sample variation obtained from two different feedstock collected at different times at the recycling plant and discusses its effect on the designed process and obtained product quality. Research questions to be answered to facilitate NMF recycling using physical processes are, • What could the expected sample variation be in the printed circuit board recycling industry? • What would be the effect of this sample variation on the process outputs based on the recommended flowsheet, and how could the proposed flowsheet be adapted for this feed variation? 7.2 Methodology 7.2.1 Non-metal fraction sample A representative sample of 25 kg of NMF was collected using the cone-and-quarter method from a 750 kg NMF bulk bag after one year of the initial tests performed in previous chapters. The obtained sample was oven-dried at 60°C for 96 h to remove any residual moisture. This oven dried NMF was then used for all subsequent test work to analyze the sample variation. 195 7.2.2 Methodology The following tests were conducted on the new samples to understand the effect of sample variation on various process parameters. The test results obtained from the new samples were compared with the old samples to understand the sample variation and its effect on process outputs. Particle size analysis The procedure provided in section 3.2.2 was used for the particle size distribution. One subsample of approximately 300 g was split from the dried sample for screening using a Ro-Tap. The screening was performed for sixty minutes as the fiberglass has a large aspect ratio. The size distribution was then plotted, and 80% and 50% cumulative passing size were determined. Loss on ignition Approximately 1 g sample was placed in a porcelain crucible and placed in a muffle furnace at room temperature. The test temperature was set to 7500C, and the sample was left for combustion for three hours, as discussed in section 4.2.2. After three hours, the crucible was removed from the furnace, was left for cooling in a desiccator, and the residue was weighed to estimate the loss on ignition. The LOI tests for each sample were performed in triplicates, and the results were averaged. Float and sink test The dried non-metal fraction samples were riffled to obtain 2 kg subsamples, and this subsample was screened to obtain + 500 µm and -500 µm size fractions. The float-sink test was performed on these two size fractions, following the procedure described in section 5.2.3. 196 7.3 Results and discussion The results obtained from the old sample (Sample 1) and the new sample (Sample 2) are compared in this section to understand the sample variation. 7.3.1 Sample variation This section presents the differences in the two samples tested for their various characteristics. Particle size distribution The particle size distribution of the two samples is compared in Figure 7-1 and Figure 7-2. It clearly shows that Sample 2 is coarser with a much lower fines content (-75 µm), compared to Sample 1 (2.8% in Sample 2 compared to 10% Sample 1). This difference suggests that Sample 2 has more of the brittle, low-tensile strength boards such as FR-2, compared to the high-tensile FR-4 boards. The FR-2 boards have a weaker mechanical strength and would shatter under impact forces during hammer milling and would provide coarser particles, whereas FR-4 fiberglass boards would resist breakage, thus, generating finer materials. Figure 7-2 shows that Sample 2 has a higher amount of coarse fraction (-1180 + 600 µm) compared to Sample 1, but Sample 1 has a higher amount of fine materials (- 75 µm) than Sample 2, confirming the differences in the concentration of FR-2 and FR-4 boards in the processed sample. One of the options for a better recycling potential and improved product quality would be treating different types of boards separately; however, a recycling organization obtains bulk bags of waste printed circuit boards separated from e-waste from various collection agencies, and categorizing boards by type is not feasible before recycling. 197 Figure 7-1: Particle size distribution of two NMF samples Figure 7-2: Percent weight distributions for two NMF samples in different size fractions 198 Loss on ignition As suggested by the particle size distribution, Sample 2 should have a higher concentration of FR-2 boards compared to Sample 1. This difference should also be reflected in the mass loss during ignition. The FR-2 boards have cotton paper as reinforcement that would be combusted during ignition, increasing the overall LOI value. It means that a higher amount of the FR-2 board in the feed sample should also increase its LOI value, as shown in Figure 7-3. Figure 7-3: LOI test results on different size fraction for tested NMF samples The feed for Sample 2 has the LOI value of 63.5% compared to 59.7 % for Sample 1. The figure also shows a slightly higher LOI value for the coarse fractions in Sample 2 compared to Sample 1, suggesting a higher concentration of FR-2 particles in coarser size ranges. Since the finer fraction (-75 µm) in both cases should mostly have liberated fiberglass, the LOI values for the finest fraction in both samples should be similar. 199 7.3.2 Recycling process outputs The differences in the feed characteristics of the NMF would also affect the performance of the recommended flowsheet. This section uses the washability analysis to understand the impact of this sample difference. Figure 7-4 and Figure 7-5 show the washability plots for two samples split into coarse (+ 500 µm) and fine (- 500 µm) fractions. The solid lines represent Sample 1, whereas results for Sample 2 are shown as dotted lines. Figure 7-4: Washability plots for + 500 µm for NMF samples (solid–S 1 & dotted–S 2) Due to the presence of a higher amount of FR-2 boards in Sample 2 that has a lower density than FR-4 boards (1.55 SG compared to 1.94 SG), a larger yield would be obtained in the lower density ranges while performing the float-sink test as seen in washability plots, and especially in the float curve and yield-gravity curve. If the flowsheet recommended in Figure 6-43 is used with a separation density of 1.8 and 2.0 g/cm3, Sample 2 would have a higher concentrate yield than 200 Sample 1. However, a higher yield would also slightly increase the overall inorganic content in concentrates. Due to the lower density of FR-2 board particles, these would be accumulated in the lower density ranges (-1.6 SG), increasing the yield for this density range. Figure 7-5: Washability plots for - 500 µm for NMF samples (solid–S 1 & dotted–S 2) Table 7-1 shows the process flowsheet output if the recycling is conducted at the same setpoints discussed in section 6.5, i.e., separation density of 1.8 and 2.0 g/cm3. As can be seen from Figure 7-4 and Figure 7-5, the concentrate yield values have increased from 48.9% to 66.2% for coarse fraction, whereas the increase is 46.1 % to 57.1% for fine fractions. The yield values for the middling and rejects have been reduced as more material has been reported to the concentrate. Slight differences in the inorganic content were also observed. The concentrated inorganic content has increased by 2%, whereas the increase in the fines was 1.2%. 201 Table 7-1: Process outputs for three-product separation at 1.8 and 2.0 g/cm3 Description + 500 µm - 500 µm Sample 1 Sample 2 Sample 1 Sample 2 Feed inorganic [%] 34.1 32.3 45.8 39.8 Concentrate yield [%] 48.9 66.2 46.1 57.1 Concentrate inorganic [%] 12.4 15.4 14.8 16.0 Middling yield [%] 24.9 15.3 12.7 12.0 Middling inorganic [%] 46.8 56.4 43.8 51.6 Reject yield [%] 26.3 18.5 41.2 30.8 Reject inorganic [%] 71.8 77.1 76.5 75.9 NGM @ 1.8 SG [%] 22.2 18.8 15.9 17.2 NGM index @ 1.8 SG 0.33 0.27 0.23 0.26 NGM @ 2.0 SG [%] 20.6 8.3 15.0 13.1 NGM index @ 2.0 SG 0.26 0.10 0.22 0.18 Index of washing 43.8 51.8 51.0 50.2 One of the benefits of the recommended density-based process is that the separation density can be adjusted depending on the process requirements by changing the amount of heavy media added to create the media suspension. It provides the flexibility of setpoint adjustment if necessary. If the plant needs to maintain the inorganic content of the product, the separation density could be adjusted to 1.73 and 1.89 g/cm3 for coarse size fraction and 1.77 and 1.81 g/cm3 for the fine size fraction. This adjustment will yield a concentrate and reject with the same inorganic content as 202 Sample 1. Table 7-2 lists the yield and inorganic content of the concentrate, middling, and reject if the separation density is altered to obtain concentrate and reject inorganic content similar to Sample 1. At the same inorganic content, the concentrate yield has increased to 58.4% and 53.7% for coarse and fine samples, respectively. This increment is again, mostly due to the higher concentration of FR-2 boards in Sample 2. A reduction in the amount of FR-4 in the feed to the gravity concentration circuit would also reduce the overall yield of the heavy fraction, i.e., rejects. Table 7-2: Process outputs to obtain same inorganic content products for Sample 1 and 2 Description + 500 µm - 500 µm Sample 1 Sample 2 Sample 1 Sample 2 Feed inorganic [%] 34.1 32.3 45.8 39.8 Concentrate yield [%] 48.9 58.4 46.1 53.7 Concentrate inorganic [%] 12.4 12.4 14.8 14.8 Middling yield [%] 24.9 14.4 12.7 17.4 Middling inorganic [%] 46.8 44.0 43.8 50.1 Reject yield [%] 26.3 27.2 41.2 28.9 Reject inorganic [%] 71.8 71.8 76.5 76.5 Overall, it can be seen that the studied variation in the feed sample does affect the yield of the final products; however, it does not affect the inorganic content significantly. The process flowsheet could also be adjusted for the feed variation to obtain a relatively consistent product quality. It should also be noted that increasing the feed organic content increased the overall concentrate yield and reduced the reject yield. This can be also be used as an indicator for the process 203 performance by the continuous monitoring of feed characteristics. The acceptable variability for the product quality also needs further investigation as it will dictate the need for adjusting the separation density. 7.4 Summary The chapter studied the effect of sample variation on the processing of the NMF. The feedstock received by a recycling plant originates from different parts of a city, country, or world. A recycling flowsheet should always be designed with an understanding of this variation and should have enough flexibility for adjustments in order to provide a consistent product quality. In this research, the recommended flowsheet was tested for a sample collected one year after the initial sampling campaign to understand the effect of the variation in the feed sample. It shows that with the varying contribution of different types of circuit boards, the yield and inorganic content of the final product would also be affected. However, the difference in the quality of the final product in terms of its organic and inorganic content was only 1–2%. At the same time, the separation density in the recommended flowsheet could be adjusted to produce a relatively consistent product quality. 204 Chapter 8: Conclusions and recommendations It has been shown that e-waste is one of the fastest growing types of waste around the globe, and the key for dealing with this waste is a proper e-waste management system that provides an efficient recycling system in order to maximize the recovery of all streams, including non-metals, to promote a circular economy. The major findings of this research program and the recommendations for future work are provided in this section. 8.1 Main research findings This research aimed to study the recycling of the NMF; a fraction often disposed of in landfills due to its low value. This study evaluated the issues associated with the improper disposal of the NMF stream and established the economic benefits of NMF recycling. It then studied the applicability of various low-cost physical separation processes that can be used for NMF recycling. The main outcomes of this part of the research are the following: 1. The study concluded that the recovery of the residual metals and fiberglass present in the NMF stream could provide the economic incentive for NMF recycling and provide resource savings. It also showed that the presence of heavy metals such as lead and toxic flame-retardant chemicals such as PBDEs that, if not treated properly, will cause environmental damage and health and safety issues for humans. 2. The loss on ignition test provided the optimal temperature, size, and duration for conducting organic content analysis for the non-metal fraction and suggested that the LOI test conducted on the as-received sample at 7500C for three hours provides sufficient time for the organic content analysis. 205 3. The evaluation of various physical processes suggests that density-based separation is feasible for NMF recycling, and relatively cleaner organic and inorganic components could be obtained if a three-product separation is conducted at 1.8 and 2.0 g/cm3 specific gravities. This process is also more practical for a water-based metal recycling process as NMF recycling can also be a wet process. The washability curves and washability indices suggest that the sample is comparable with that of a difficult-to-clean coal. 4. The applicability of flotation for NMF recycling was assessed using inverse gas chromatography (IGC). The assessment showed the presence of surface energy heterogeneity in the sample, but the high energetic sites only represented 10% of the total sites, suggesting a low separation efficiency if subjected to froth flotation. The IGC results, coupled with SEM analysis, showed that the fiberglass has poor liberation and would require fine grinding for increased liberation that is not favorable for low-value materials. The micro-FTIR study also showed a heterogeneous mixture of various polymers that would render the flotation process challenging. 5. A three-product gravity separation would produce a cleaner organic fraction with a 47% yield at 86% organic content and a reject stream with a 35% yield at 72% fiberglass content. It was concluded that the organic matter recovered from this process could be used as an energy source in the cement industry or to prepare activated carbon, whereas the inorganic stream could be used as filler in concrete, heavy metal adsorbents or could potentially be reused for circuit board manufacturing. 6. Finally, this research also studied the effect of sample variation on the recommended flowsheet. It showed that changes in the sample feed would change the product quality. The 206 process could also be tuned up easily by adjusting the separation density, if needed, to reduce the effect of sample variation. This would help the recycling organization to deal with the feed variation as the e-waste stream is highly heterogeneous, and the feed characteristics are never constant. 8.2 Recommendations for future research Based on this study, the following areas have been suggested for future research: 1. Since the circuit boards are some of the highest valued wastes in the e-waste stream, the study was conducted on the NMF obtained from a pilot plant that processes printed circuit boards. However, to evaluate the NMF recycling process from different types of e-waste, similar studies are recommended from samples obtained from different recycling facilities across Canada. 2. The loss on ignition test was conducted on the NMF sample obtained after the PCB recycling, and it had depleted metal content. The presence of metals before the recycling will have a significant effect on the LOI due to metal oxidation. The LOI tests should be conducted on various size fraction of printed circuit boards and other e-waste items to standardize the organic content analysis for e-waste. 3. The research showed the feasibility of gravity separation for NMF recycling; however, pilot- level test work is recommended with efficient dense medium cyclones, spiral concentrators, shaking tables, or RefluxTM classifiers to confirm their applicability and estimate the separation efficiency. A cost-benefit analysis is also required to confirm the economic viability of the recommended process. The environmental impacts of various technologies in terms of energy, media, and water consumption should also be considered for the final 207 selection. The separated products obtained from the pilot-scale tests should also be studied for their characteristics, and a proper assessment is required for their suggested potential applications. 4. The research also studied the fundamentals related to the flotation process by using the IGC study. However, flotation is a complex process with a significant number of process- operating variables such as impeller speed, particle size, pH, air flow rate, and reagents such as frothers, collectors, and depressants. A more comprehensive study using pure FR-2 and FR-4 (the most common types of circuit boards) should be conducted to assess the applicability of the flotation process. The effect of other types of circuit boards and the selectivity of various reagents towards one resin compared to the other should also be evaluated. 208 Chapter 9: Claims of original contributions and benefits of the research The outcomes of this research that were original and significant are listed below. Interdisciplinary research The research used an interdisciplinary approach, an amalgamation of recycling and mineral processing, to characterize the non-metal fraction obtained from the recycling of waste printed circuit boards. Widely accepted and verified approaches used in the coal and mineral processing industry were identified, developed, and used to evaluate the applicability of several physical separation processes for NMF recycling and then used to estimate the theoretical process performance. Pilot-scale NMF characterization This thesis studied the NMF obtained from a pilot-scale facility that processes a mixture of circuit boards rather than individual circuit boards, representing a more realistic processing case. It provided a comprehensive characterization of the NMF regarding its environmental concerns regarding improper disposal and the economic benefits of its recycling. Since most waste printed circuit boards are processed in some fashion before disposal, this research initiated a study on the NMF material derived from an industrial operation. Hence, it provided results that could address the concerns related to actual and realistic problems associated with PCB disposal. Loss on ignition test The literature showed a wide range of testing conditions for the LOI test. This study provided the results on the effect of different variables on the ignition of NMF, which was never attempted 209 before in any published literature. The outcomes of this research delivered a simplified approach to determine the loss on ignition of the NMF mixture obtained from waste circuit board samples. Water-based NMF processing The study is the first to provide an in-depth analysis of using various water-based (wet) physical separation processes for NMF recycling, which has not been studied yet in any reported literature. These processes could be adapted to separate the organic and inorganic components in the NMF obtained from processed waste printed circuit boards, especially for the industries using water-based separation processes for metal recovery. Density separation flowsheet of NMF The density separation has been shown to be applicable for separating metals from non-metals in e-waste and different plastics types. This research, however, showed an opportunity for using density separation to recycle components of the NMF. A flowsheet was developed to incorporate the NMF recycling as an extension to the present PCB recycling circuit, and it provided the theoretical means for estimating yield, grade, and recovery. Washability analysis and washability indices The washability curves and washability indices have been regularly used to determine the gravity separation behavior in coal preparation. This research showed that these methods could also be adopted for non-metal fraction recycling and could provide the theoretical estimation of the density-based separation circuit similar to coal processing. The washability index developed for the coal industry also showed its applicability for non-metal recycling, and the research showed that these indices could be used to assess ease-of-washing for the non-metal fraction. 210 Analyzing the effect of feed variation The majority of the reported study only provides estimates related to the test work conducted on individual circuit boards or samples obtained at one point in time. However, the feed to a recycling plant is rapidly changing due to technological advancements, and a process showing high efficiency for one feed might not provide similar benefits for a different feed. This research analyzed the impact of feed variation that has not been reported in any other study. Inverse gas chromatography and micro-FTIR The application for IGC in the field of e-waste recycling has never been explored before, and the study showed that the energy distribution obtained from IGC testing could be useful for a preliminary indication of a froth floatation response of the NMF or of any other type of e-waste. The study also showed the applicability of the micro-FTIR technique to explore the heterogeneity of the NMF sample and to identify the polymeric composition of the non-metal fraction. These techniques have not been researched in the field of e-waste but could be used as potential tools for the characterization of NMF and other e-waste components. 9.1 Summary Various studies on the recycling processes for printed circuit boards have been reported on throughout various literature. However, this is the first study that identifies the issues related to rejects of the circuit board recycling process and then provides recycling opportunities on a sample obtained from a pilot plant, rather than from individual circuit boards. Table 9-1 summarizes the key objectives of the study, the experimental methodologies, and the novel contributions of each chapter. 211 Table 9-1: Summary of key objectives, methodologies, and novel contributions Chapter Key objective Methodology Application of existing materials Novel contributions 3 Characterize NMF from the printed circuit board Conduct various characterization tests on NMF Analyze tests conducted on individual PCB First published characteristics of PCB recycling rejects from pilot-scale samples 4 Establish standard LOI testing parameters Conduct ignition test at varying process parameters List process parameters used by other researchers Establish optimum test conditions for the LOI test 5 Study physical processing methods for NMF recycling Float-sink and IGC test Analyze tests conducted on individual PCB or other materials First attempt to determine the applicability of wet physical process for NMF recycling 6 Establish theoretical process outputs Analyze data from Chapter 6 combined with product characterization Analyze tests conducted on coal First flowsheet of NMF processing using wet physical process and related outputs 7 Analyze feed variation Tests similar to Chapter 4 on a new sample - First effort to provide the effect of feed variation on a process 212 9.2 Benefits of the research This research promotes the circular economy of e-waste by increasing e-waste collection and the recovery of recycling rejects in its native form without damaging their inherent properties. This can help increase the probability of reusing the recovered components as raw materials to upcycle for new product manufacturing, and thus, closing the material loop and motivating the use of the circular economy as an industrial model. The direct benefits of the research are listed below: Industrial benefits: reduced volume of materials requiring transportation and disposal, providing an additional revenue source through NMF recycling. Economic benefits: recovery of valuables from waste that would otherwise be sent to landfills. Environmental benefits: reduction in GRG emissions, landfill disposals, and incineration. Social benefits: reduced health and safety risks to workers and the creation of job opportunities. Benefits to other recycling sectors: adoption of this process for another waste stream such as for waste solar panels, waste LED lamps, and municipal solid waste. 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Available at: https://scholarsarchive.byu.edu/etd/2273 (Accessed: 11 December 2019). 255 Appendices Appendix A - E-waste generation statistics Table A - 1: Global e-waste generation trends Year Total e-waste [million tonnes] E-waste per capita [kg/inh.] 2010 33.8 5.0 2011 35.8 5.2 2012 37.8 5.4 2013 39.8 5.7 2014 41.8 5.9 2015 43.8 6.0 2016 44.7 6.1 2017 45.7 6.3 2018 47.8 6.4 2019 49.8 6.5 2020 50.5 6.7 2021 52.2 6.8 Table A - 2: Total waste generation in various e-waste categories Categories Total e-waste [million tonnes] Lamps 0.7 Small IT 3.9 Screens 6.6 Temp. exchange eq. 7.6 Large eq. 9.1 Small eq. 16.8 256 Table A - 3: Total waste generated by different regions Region Total e-waste [million tonnes] E-waste per capita [kg/inh.] Oceania 0.7 17.3 Africa 2.2 1.9 America 11.3 11.6 Europe 12.3 16.6 Asia 18.2 4.2 Table A - 4: Estimated value of materials present in e-waste Material Amount, kT Estimated value, million Euros Aluminum 2,472 3,585 Copper 2,134 9,524 Gold 0.5 18,840 Iron 16,283 3,582 Palladium 0.2 3,369 Plastics 12,230 15,043 Silver 1.6 884 257 Appendix B - NMF characterization data Table B - 1: Particle size distribution data Screen size [µm] 5 minutes 15 minutes 30 minutes 60 minutes Wt. retained [g] Cum. passing [%] Wt. retained [g] Cum. passing [%] Wt. retained [g] Cum. passing [%] Wt. retained [g] Cum. passing [%] 3350 0.1 99.9 0.1 100.0 0.1 100.0 0.0 100.0 2360 0.4 99.7 0.3 99.8 0.3 99.9 0.3 99.8 1700 0.4 99.5 0.4 99.6 0.3 99.6 0.3 99.7 1180 3.5 97.6 2.4 98.3 0.2 98.4 2.0 98.6 850 30.9 80.4 26.7 83.5 24.6 84.8 23.3 85.7 600 33.9 61.6 33.0 65.3 32.3 67.0 31.6 68.2 425 29.5 45.2 30.4 48.5 30.8 50.0 31.0 51.0 300 24.4 31.7 25.1 34.7 25.4 35.9 25.5 36.9 212 19.0 21.1 19.5 23.9 19.8 25.0 20.0 25.8 150 12.9 14.0 13.1 16.6 13.3 17.6 13.5 18.3 106 8.8 9.0 8.8 11.7 8.8 12.7 8.9 13.3 75 5.9 5.7 6.3 8.2 6.0 9.3 6.0 10.0 Pan 10.3 14.9 16.9 18.1 258 Table B - 2: Metal concentration in NMF sample Metals -1180 + 600 µm -600 + 300 µm -300 + 150 µm -150 + 75 µm -75 µm Feed Back-calculated feed Aluminum 2.97 3.34 2.74 3.49 5.14 3.03 3.30 Antimony 0.42 0.19 0.08 0.08 0.05 0.23 0.22 Barium 0.04 0.05 0.08 0.25 0.46 0.05 0.11 Boron 0.43 0.71 0.61 0.69 1.15 0.63 0.64 Calcium 3.82 6.19 5.63 6.17 9.77 5.35 5.69 Cobalt 0.00 0.03 0.00 0.00 0.01 0.00 0.01 Copper 2.53 1.03 0.37 0.37 0.84 1.27 1.31 Iron 0.07 0.09 0.08 0.18 1.09 0.15 0.19 Lead 0.02 0.03 0.04 0.07 0.39 0.03 0.07 Magnesium 0.16 0.17 0.14 0.17 0.24 0.16 0.17 Manganese 0.00 0.00 0.01 0.02 0.16 0.01 0.02 Nickel 0.02 0.01 0.00 0.01 0.07 0.00 0.02 Phosphorus 0.05 0.03 0.02 0.02 0.02 0.04 0.03 Potassium 0.02 0.03 0.02 0.03 0.05 0.03 0.03 Silver 0.00 0.00 0.00 0.01 0.02 0.00 0.00 Sodium 0.07 0.11 0.10 0.11 0.18 0.10 0.10 Strontium 0.03 0.04 0.04 0.04 0.07 0.04 0.04 Tin 0.03 0.07 0.05 0.10 0.82 0.04 0.13 Titanium 0.02 0.02 0.02 0.02 0.11 0.02 0.03 Zinc 0.04 0.03 0.03 0.05 0.19 0.04 0.05 Total Metal 10.75 12.19 10.07 11.91 20.86 11.23 12.18 259 Table B - 3: Fiberglass concentration in NMF sample Size [µm] SiO2 [%] Fiberglass [%] Distribution [%] Feed 21.0 38.8 100.0 -1180 + 600 15.4 28.4 23.4 -600 + 300 21.0 38.9 31.6 -300 + 150 19.3 35.7 17.1 -150 + 75 25.0 46.3 9.9 - 75 37.5 69.4 18.0 Back-calculated feed 20.9 38.6 100.0 260 Appendix C - Loss on ignition test data Table C - 1: Change in temperature in the muffle furnace Time [min] Trail 1 [oF] Trail 2 [oF] 0 65 67 5 430 397 10 646 622 15 769 757 20 862 855 25 949 934 30 1015 998 35 1074 1058 40 1134 1117 45 1192 1183 50 1246 1236 55 1300 1286 60 1353 1336 70 1451 1436 80 1544 1531 90 1624 1609 105 1737 1724 261 Table C - 2: Loss on ignition test data for feed (as received) Sample id Temp [°C] Time [hours] Sample [g] Residue [g] LOI [%] S11 950 1 1.3683 0.5496 59.8 1.0603 0.4374 58.7 1.1601 0.4656 59.9 3 1.5222 0.6164 59.5 1.2471 0.5058 59.4 1.0408 0.4186 59.8 5 1.2009 0.4808 60.0 1.2394 0.4931 60.2 1.2097 0.4970 58.9 750 1 1.1848 0.4790 59.6 1.0234 0.4019 60.7 1.1067 0.4587 58.6 3 1.3304 0.5183 61.0 1.3722 0.5604 59.2 1.0221 0.4191 59.0 5 1.2240 0.4940 59.6 1.0251 0.4092 60.1 1.1801 0.4715 60.0 565 1 1.2609 0.5082 59.7 1.3799 0.5729 58.5 1.2766 0.5172 59.5 3 0.9973 0.4094 58.9 1.0174 0.4226 58.5 1.3723 0.5724 58.3 5 1.4254 0.5858 58.9 0.7609 0.3066 59.7 1.1862 0.5017 57.7 262 Table C - 3: Loss on ignition test data for feed (pulverized) Sample id Temp [°C] Time [hours] Sample [g] Residue [g] LOI [%] S12 950 1 1.3565 0.5511 59.4 1.1994 0.4880 59.3 0.9244 0.3715 59.8 3 1.1775 0.4790 59.3 1.2904 0.5255 59.3 0.9426 0.3847 59.2 5 1.0281 0.4255 58.6 1.3807 0.5611 59.4 1.0467 0.4263 59.3 750 1 0.9744 0.3937 59.6 1.3398 0.5467 59.2 1.4062 0.5722 59.3 3 1.4005 0.5687 59.4 1.4026 0.5687 59.5 1.3416 0.5463 59.3 5 1.2934 0.5263 59.3 1.5110 0.6133 59.4 1.2822 0.5216 59.3 565 1 1.1165 0.4588 58.9 1.0747 0.4418 58.9 0.9615 0.3938 59.0 3 1.3979 0.5704 59.2 1.1567 0.4760 58.8 1.0233 0.4198 59.0 5 1.1643 0.4756 59.2 1.0302 0.4189 59.3 1.2525 0.5120 59.1 263 Table C - 4: Loss on ignition test data for – 1180 + 850 µm (as screened) Sample id Temp [°C] Time [hours] Sample [g] Residue [g] LOI [%] S21 950 1 1.2157 0.3968 67.4 1.2818 0.4233 67.0 1.3656 0.4442 67.5 3 0.9990 0.3533 64.6 1.4046 0.5033 64.2 1.2526 0.3867 69.1 5 1.4589 0.4605 68.4 1.0182 0.3439 66.2 1.0199 0.3541 65.3 750 1 1.0037 0.3202 68.1 0.9909 0.3127 68.4 1.0456 0.3263 68.8 3 1.0999 0.3433 68.8 0.9385 0.2807 70.1 1.0332 0.3310 68.0 5 1.0294 0.3526 65.7 1.1204 0.3579 68.1 1.0709 0.3478 67.5 565 1 1.2630 0.4742 62.5 1.3488 0.4241 68.6 1.3404 0.4350 67.5 3 1.3538 0.4263 68.5 1.1622 0.3964 65.9 1.0134 0.3773 62.8 5 1.5084 0.4653 69.2 1.0270 0.3228 68.6 1.0092 0.3263 67.7 264 Table C - 5: Loss on ignition test data for – 1180 + 850 µm (pulverized) Sample id Temp [°C] Time [hours] Sample [g] Residue [g] LOI [%] T24 950 1 1.2373 0.4060 67.2 1.1055 0.3615 67.3 1.0833 0.3505 67.6 3 1.0560 0.3449 67.3 1.0852 0.3537 67.4 1.2639 0.4104 67.5 5 1.0524 0.3466 67.1 1.1406 0.3772 66.9 1.1621 0.3758 67.7 750 1 1.0895 0.3517 67.7 1.0867 0.3519 67.6 1.0630 0.3426 67.8 3 1.1511 0.3760 67.3 0.9355 0.3025 67.7 0.9631 0.3125 67.6 5 1.1401 0.3743 67.2 1.0979 0.3598 67.2 1.1631 0.3816 67.2 565 1 1.0170 0.3358 67.0 1.0823 0.3546 67.2 0.9392 0.3050 67.5 3 1.0926 0.3605 67.0 1.0471 0.3434 67.2 1.0437 0.3411 67.3 5 1.1149 0.3638 67.4 0.9793 0.3214 67.2 0.9465 0.3106 67.2 265 Table C - 6: Loss on ignition test data for – 600 + 425 µm (as screened) Sample id Temp [°C] Time [hours] Sample [g] Residue [g] LOI [%] T31 950 1 1.1351 0.4915 56.7 0.9573 0.4027 57.9 0.6956 0.2912 58.1 3 0.9866 0.4120 58.2 0.7514 0.3070 59.1 1.2034 0.5141 57.3 5 1.0043 0.4401 56.2 1.1949 0.4902 59.0 1.0245 0.4399 57.1 750 1 1.0339 0.4501 56.5 0.9289 0.3803 59.1 0.7333 0.3129 57.3 3 1.1193 0.4567 59.2 0.9472 0.3926 58.6 0.9433 0.4023 57.4 5 1.0909 0.4547 58.3 1.0144 0.4198 58.6 0.9673 0.4029 58.3 565 1 1.2883 0.5367 58.3 0.9706 0.4006 58.7 1.1753 0.4952 57.9 3 1.0857 0.4401 59.5 1.0042 0.3947 60.7 1.0913 0.4476 59.0 5 0.9349 0.3890 58.4 0.9082 0.3646 59.9 1.0803 0.4411 59.2 266 Table C - 7: Loss on ignition test data for – 600 + 425 µm (pulverized) Sample id Temp [°C] Time [hours] Sample [g] Residue [g] LOI [%] T33 950 1 1.0921 0.4511 58.7 1.0155 0.4188 58.8 1.2526 0.5178 58.7 3 1.2051 0.5001 58.5 1.1629 0.4805 58.7 1.3156 0.5436 58.7 5 1.2017 0.4979 58.6 1.1811 0.4914 58.4 1.0215 0.4240 58.5 750 1 1.2129 0.5048 58.4 1.2064 0.4971 58.8 1.1924 0.4940 58.6 3 1.2356 0.5208 57.9 1.1542 0.4770 58.7 1.3158 0.5463 58.5 5 1.2078 0.5004 58.6 1.0279 0.4233 58.8 0.8613 0.3547 58.8 565 1 1.1239 0.4673 58.4 1.0514 0.4374 58.4 1.0296 0.4270 58.5 3 1.4011 0.5834 58.4 1.1549 0.4804 58.4 1.1996 0.4972 58.6 5 1.2882 0.5325 58.7 1.2208 0.5056 58.6 1.1947 0.4917 58.8 267 Table C - 8: Loss on ignition test data for sample mass variation (as received/screened) Temp [°C] Time [hours] Sample id Sample [g] Residue [g] LOI [%] 750 3 S11 1.1848 0.4790 59.6 1.0234 0.4019 60.7 1.1067 0.4587 58.6 3.4608 1.4481 58.2 3.4731 1.4144 59.3 3.4370 1.4013 59.2 5.1651 2.1050 59.2 5.0564 2.1443 57.6 5.0189 2.0485 59.2 S21 1.0037 0.3202 68.1 0.9909 0.3127 68.4 1.0456 0.3263 68.8 3.3338 1.1030 66.9 3.3823 1.1552 65.8 3.6486 1.2148 66.7 5.2062 1.7484 66.4 5.2759 1.6992 67.8 5.0013 1.6800 66.4 S31 1.0339 0.4501 56.5 0.9289 0.3803 59.1 0.7333 0.3129 57.3 2.9629 1.2711 57.1 3.0734 1.2719 58.6 3.0030 1.1665 61.2 5.0885 2.1983 56.8 5.2667 2.2274 57.7 4.9221 2.0727 57.9 268 Table C - 9: Loss on ignition test data for all size fractions Sample id Sample [g] Residue [g] LOI [%] Feed 1.3304 0.5183 61.0 1.3722 0.5604 59.2 1.0221 0.4191 59.0 -1180 + 600 µm 1.1726 0.3651 68.4 1.1909 0.3689 68.6 1.2983 0.4027 68.5 -600 + 300 µm 1.0158 0.4091 59.3 1.2473 0.4965 59.8 1.1336 0.4469 60.1 -300 + 150 µm 1.3252 0.4766 63.7 1.1029 0.3837 64.8 1.3609 0.5175 61.6 -150 + 75 µm 1.1682 0.5777 50.1 0.5038 0.2349 52.9 0.8872 0.4108 53.2 - 75 µm 0.9803 0.7122 27.0 1.0232 0.7448 26.8 0.8454 0.6124 27.1 269 Appendix D - Gravity separation data Table D - 1: Yield and LOI data from float-sink test for all size fractions Specific gravity -1180+600 µm -600+300 µm -300+150 µm -150+75 µm -75 µm Wt. [%] LOI [%] Wt. [%] LOI [%] Wt. [%] LOI [%] Wt. [%] LOI [%] Wt. [%] LOI [%] - 1.4 5.5 96.8 5.1 95.5 3.0 95.7 1.5 96.8 0.7 96.2 1.4–1.6 24.5 93.6 22.7 91.5 30.3 90.6 28.7 90.7 9.8 92.7 1.6–1.8 19.6 78.7 18.9 77.4 25.8 79.3 18.4 67.4 8.4 68.5 1.8–2.0 26.7 52.4 18.8 57.3 10.9 55.1 10.1 54.8 5.0 54.1 2.0–2.2 15.6 34.0 18.4 36.4 11.0 34.2 28.1 30.3 17.2 28.8 2.2–2.5 5.2 22.7 14.3 23.2 16.5 22.4 12.4 16.9 50.4 13.5 + 2.5 2.9 2.8 1.8 6.1 2.5 15.4 0.9 -3.1 8.4 -5.1 Total 100.0 64.2 100.0 61.1 100.0 64.6 100.0 56.0 100.0 30.3 270 Appendix E - IGC test data Table E - 1: Specific surface area for various size fractions Size [µm] Test 1 [m2/g] Test 2 [m2/g] Test 3 [m2/g] - 1180 + 600 0.49 0.54 0.39 - 600 + 300 0.32 0.41 0.44 - 300 + 150 0.50 0.51 0.46 - 150 + 75 0.86 0.82 0.76 - 75 1.34 1.25 1.19 Table E - 2: Dispersive surface energy for various size fractions in mJ/m2 Surface coverage [%] - 1180 + 600 µm - 600 + 300 µm - 300 + 150 µm - 150 + 75 µm - 75 µm 0.5 46.47 44.16 46.71 49.39 44.29 1.0 46.32 43.64 45.08 47.45 43.82 2.0 45.04 43.48 43.36 45.65 42.66 4.0 42.96 41.77 41.22 42.92 40.49 6.0 41.94 40.19 38.69 40.33 38.71 8.0 40.67 39.07 37.14 38.40 38.39 10.0 39.78 38.85 36.62 37.14 38.07 15.0 39.61 38.35 36.22 36.61 37.11 20.0 39.69 39.24 37.33 33.55 34.64 Table E - 3: Specific surface energy for various size fractions in mJ/m2 Surface coverage [%] - 1180 + 600 µm - 600 + 300 µm - 300 + 150 µm - 150 + 75 µm - 75 µm 0.5 13.62 14.00 14.94 15.67 14.84 1.0 12.42 12.76 13.47 14.09 13.31 2.0 10.23 10.61 10.78 12.21 11.36 4.0 8.06 8.07 8.46 9.55 9.06 6.0 6.66 6.81 7.08 7.98 7.26 8.0 5.87 6.05 6.21 6.71 6.50 10.0 5.22 5.53 5.72 6.00 6.31 15.0 4.70 4.96 5.04 5.58 5.54 20.0 4.58 4.92 4.96 4.55 4.32 271 Table E - 4: Total surface energy for various size fractions in mJ/m2 Surface coverage [%] - 1180 + 600 µm - 600 + 300 µm - 300 + 150 µm - 150 + 75 µm - 75 µm 0.5 60.09 58.16 61.64 65.06 59.13 1.0 58.74 56.40 58.54 61.55 57.13 2.0 55.27 54.08 54.14 57.85 54.02 4.0 51.02 49.84 49.68 52.47 49.55 6.0 48.59 47.00 45.76 48.30 45.97 8.0 46.54 45.12 43.35 45.10 44.88 10.0 45.00 44.38 42.34 43.14 44.38 15.0 44.31 43.30 41.26 42.19 42.65 20.0 44.26 44.16 42.29 38.10 38.97 Table E - 5: Work of adhesion for various size fractions in mJ/m2 Surface coverage [%] - 1180 + 600 µm - 600 + 300 µm - 300 + 150 µm - 150 + 75 µm - 75 µm 0.5 118.00 118.06 122.37 126.20 120.50 1.0 115.38 114.93 117.96 121.10 116.53 2.0 110.04 110.50 111.10 115.70 111.82 4.0 103.70 103.65 104.34 108.29 105.42 6.0 99.78 99.56 99.12 102.76 100.15 8.0 96.86 96.81 95.83 98.55 98.19 10.0 94.59 95.37 94.14 95.91 97.38 15.0 93.22 93.58 92.19 94.17 94.20 20.0 92.98 94.22 92.96 88.13 87.99 272 Table E - 6: Hydrophilicity for various size fractions Surface coverage [%] - 1180 + 600 µm - 600 + 300 µm - 300 + 150 µm - 150 + 75 µm - 75 µm 0.5 0.23 0.24 0.24 0.24 0.25 1.0 0.21 0.23 0.23 0.23 0.23 2.0 0.19 0.20 0.20 0.21 0.21 4.0 0.16 0.16 0.17 0.18 0.18 6.0 0.14 0.14 0.15 0.17 0.16 8.0 0.13 0.13 0.14 0.15 0.14 10.0 0.12 0.12 0.14 0.14 0.14 15.0 0.11 0.11 0.12 0.13 0.13 20.0 0.10 0.11 0.12 0.12 0.11 273 Appendix F - Washability data Table F - 1: Yield and inorganic content in various size fractions for washability curve Specific gravity -1180+600 µm -600+300 µm -300+150 µm -150+75 µm -75 µm Wt. [%] Ino. [%] Wt. [%] Ino. [%] Wt. [%] Ino. [%] Wt. [%] Ino. [%] Wt. [%] Ino. [%] - 1.4 5.5 3.2 5.1 4.5 3.0 4.3 1.5 3.2 0.7 - 1.4–1.6 24.5 6.4 22.7 8.5 30.3 9.4 28.7 9.3 9.8 7.3 1.6–1.8 19.6 21.3 18.9 22.6 25.8 20.7 18.4 32.6 8.4 31.5 1.8–2.0 26.7 47.6 18.8 42.7 10.9 44.9 10.1 45.2 5.0 45.9 2.0–2.2 15.6 66.0 18.4 63.6 11.0 65.8 28.1 69.7 17.2 71.2 2.2–2.5 5.2 77.3 14.3 76.8 16.5 77.6 12.4 83.1 50.4 86.6 + 2.5 2.9 97.2 1.8 93.9 2.5 84.6 0.9 100.0 8.4 100.0 Total 100.0 35.8 100.0 38.9 100.0 35.4 100.0 44.0 100.0 30.0 Ino. = Inorganic content Table F - 2: Degree of washing for various size fractions SG -1180+600 µm -600+300 µm -300+150 µm -150+75 µm -75 µm 1.4 4.97 4.48 2.60 1.37 - 1.6 25.07 22.19 24.88 23.96 9.47 1.8 33.03 30.08 35.60 28.73 14.07 2.0 24.18 28.26 32.69 28.46 15.80 2.2 11.02 16.58 23.22 12.05 15.51 2.5 4.96 2.61 3.54 1.10 3.58 Table F - 3: Washability number for various size fractions SG -1180+600 µm -600+300 µm -300+150 µm -150+75 µm -75 µm 1.8 27.65 21.81 23.35 15.97 7.80 2.0 9.89 12.79 17.34 12.55 6.62 Table F - 4: Index of washability for various size fractions -1180+600 µm -600+300 µm -300+150 µm -150+75 µm -75 µm 44.49 42.13 46.52 46.51 37.37 274 Table F - 5: NGMI for various size fractions at different SG SG -1180+600 µm -600+300 µm -300+150 µm -150+75 µm -75 µm 1.5 0.19 0.17 0.20 0.22 0.06 1.6 0.25 0.23 0.31 0.28 0.09 1.7 0.27 0.25 0.37 0.26 0.11 1.8 0.34 0.28 0.28 0.21 0.10 1.9 0.38 0.28 0.17 0.15 0.08 2.0 0.26 0.26 0.16 0.26 0.20 Table F - 6: Fiberglass concentration in various density ranges SG [-] +500 µm -500 µm Feed 30.9 44.1 - 1.8 9.9 13.1 +1.8-2.0 47.6 43.7 +2.0-2.5 66.3 75.3 +2.5 15.3 50.8 Back-calculated feed 32.8 41.9 275 Table F - 7: Metal concentration in various density ranges for +500 µm Metals - 1.8 +1.8-2.0 +2.0-2.5 +2.5 Feed Back-calculated feed Aluminum 0.69 3.16 6.47 11.60 3.06 2.96 Antimony 0.50 0.40 0.02 0.02 .037 0.35 Barium 0.02 0.04 0.04 0.22 0.04 0.03 Boron 0.13 0.63 1.00 0.08 0.49 0.46 Calcium 1.04 5.31 8.70 5.61 4.37 4.03 Cobalt 0.00 0.00 0.00 0.01 0.00 0.00 Copper 0.16 0.50 1.02 59.10 2.18 2.01 Iron 0.04 0.08 0.10 0.18 0.08 0.07 Lead 0.01 0.02 0.02 0.54 0.02 0.03 Magnesium 0.09 0.19 0.21 0.04 0.16 0.14 Manganese 0.003 0.005 0.007 0.585 0.005 0.02 Nickel 0.003 0.005 0.003 0.458 0.015 0.03 Phosphorus 0.05 0.02 0.02 0.05 0.04 0.03 Potassium 0.01 0.03 0.04 0.1 0.02 0.02 Silver 0.00. 0.00 0.01 0.01 0.00 0.00 Sodium 0.03 0.11 0.16 0.00 0.08 0.08 Strontium 0.01 0.04 0.06 0.02 0.03 0.03 Tin 0.02 0.02 0.02 0.31 0.04 0.02 Titanium 0.01 0.02 0.03 0.06 0.02 0.02 Zinc 0.05 0.06 0.04 0.26 0.04 0.05 Total Metal 2.88 10.65 17.96 79.27 11.09 10.39 276 Table F - 8: Metal concentration in various density ranges for -500 µm Metals - 1.8 +1.8-2.0 +2.0-2.5 +2.5 Feed Back-calculated feed Aluminum 0.91 3.24 4.74 10.40 3.48 2.96 Antimony 0.20 0.21 0.02 0.02 0.12 0.13 Barium 0.14 0.10 0.04 0.27 0.16 0.10 Boron 0.17 0.69 1.10 0.43 0.75 0.60 Calcium 1.36 5.90 9.72 3.57 6.62 5.19 Cobalt 0.00 0.00 0.00 0.00 0.01 0.00 Copper 0.09 0.13 0.31 27.50 0.69 1.01 Iron 0.06 0.10 0.11 1.86 0.27 0.14 Lead 0.04 0.03 0.02 0.54 0.10 0.05 Magnesium 0.09 0.19 0.20 0.20 0.17 0.15 Manganese 0.006 0.006 0.007 0.276 0.034 0.01 Nickel 0.004 0.003 0.003 0.273 0.019 0.01 Phosphorus 0.03 0.02 0.02 0.05 0.02 0.02 Potassium 0.01 0.03 0.04 0.10 0.03 0.03 Silver 0.00 0.00 0.00 0.06 0.00 0.00 Sodium 0.04 0.11 0.17 0.25 0.12 0.10 Strontium 0.01 0.04 0.07 0.04 0.05 0.04 Tin 0.033 0.031 0.022 1.690 0.199 0.08 Titanium 0.01 0.02 0.03 0.09 0.04 0.02 Zinc 0.087 0.084 0.073 0.342 0.059 0.09 Total Metal 3.29 10.95 16.71 47.99 12.96 10.74 277 Appendix G - Data for sample variation Table G - 1: Particle size distribution data of sample 2 Screen size [µm] Sample 2 Wt. retained [g] Cum. passing [%] 3350 0.6 99.9 2360 0.3 99.9 1700 0.5 99.8 1180 1.7 99.5 850 102.4 82.9 600 140.5 60.0 425 106.3 42.8 300 81.0 29.6 212 62.6 19.4 150 45.7 12.0 106 35.6 6.2 75 21.1 2.8 Pan 17.2 278 Table G - 2: Loss on ignition in NMF sample 2 Size [µm] LOI [%] Feed 63.5 -1180 + 600 68.4 -600 + 300 65.1 -300 + 150 64.4 -150 + 75 51.4 - 75 26.2 Back-calculated feed 63.9 Table G - 3: Yield and inorganic content in coarse and fine size for Sample 1 and 2 Specific gravity +500 µm -500 µm Specific gravity +500 µm -500 µm Wt. [%] Ino. [%] Wt. [%] Ino. [%] Wt. [%] Ino. [%] Wt. [%] Ino. [%] - 1.4 5.4 96.5 3.2 95.7 - 1.4 6.5 96.9 2.0 95.4 1.4–1.6 24.1 93.1 23.8 91.1 1.4–1.6 37.3 92.6 32.9 91.7 1.6–1.8 19.5 78.4 19.2 76.2 1.6–1.8 22,4 67.8 22.3 71.6 1.8–2.0 24.9 53.2 12.7 56.2 1.8–2.0 15.3 43.6 12.0 48.4 2.0–2.2 16.3 34.7 17.3 33.3 2.0–2.4 15.9 26.9 28.2 25.0 2.2–2.5 7.4 22.9 20.9 18.4 + 2.4 2.6 100.0 2.7 15.0 + 2.5 2.7 3.6 3.0 3.0 Total 100.0 63.5 100.0 56.1 Total 100.0 66.9 100.0 61.2 Ino. = Inorganic content 279 Appendix H - Electronic waste management in Canada Introduction The objective of this study is to promote the circular economy in Canada. One of the major components of recycling is the collection of e-waste. To increase circularity, the collection rate of the discarded electronics has to be increased, and then these must be processed at a recycling facility. To understand and increase the collection and recycling of e-waste in Canada, the current situation of e-waste management needs to be studied. This will provide essential background information for the current status of the circular economy in Canada, leading to an understanding of the country’s challenges of e-waste management and to possible recommendations to increase circularity. This is identified as one of the sub-objectives of the thesis. Research gap/questions that are necessary to answer in order to promote the circular economy in Canada are • What is the current status and what are the current policies and regulations relating to e-waste management in Canada? • How does the e-waste collection system work and what is the current collection rate? • How is e-waste recycled in Canada? • What are the major challenges regarding e-waste recycling and what can be done to increase the collection and recycling rates in order to increase material circularity? This chapter presents the statistics and trends of e-waste being generation and collection from the Canadian perspective. Canadian regulations, policies, laws, and challenges with e-waste collection 280 are summarized in the chapter. A version of this chapter has been published in the Resources journal by MDPI (DOI: 10.3390/resources5040035). Methodology To understand the Canadian e-waste management system and to estimate the e-waste collection rates, the following approach was used: • The e-waste generation data was extracted from the Global E-waste Monitor 2017 report published by the United Nations University and International Solid Waste Association • The consumer behavior for e-waste disposal was studied based on the latest survey performed by the Statistics Canada • The programs and regulations related to e-waste management were identified through the Environment and Natural Resources Division of Government of Canada for various e-waste categories • The data published by these identified programs was used to estimate the e-waste collection rate in Canada • The disposal of e-waste was studied by reports published by various sources, and the recycling process was studied from four different e-waste recycling organizations through personal visits or literature • Based on these studies, issues related to e-waste management in Canada were identified, and possible solutions for increasing the collection and recycling rates were recommended. 281 E-waste generation As discussed in section 2.3, the e-waste generated around the globe was 44.7 million tonnes, at 6.1 kg of waste generated per inhabitant in 2016. The total e-waste generated in the Americas (North, Central, and South, combined) was 11.3 million tonnes in 2016 (Baldé et al., 2017). The e-waste produced in Canada was estimated to be 724 kilo tonnes at 20 kg waste generated per inhabitant in 2016, accounting for 1.62 % of the total e-waste produced in the world and 6.41% of the total e-waste produced in the American continent (Baldé et al., 2017). Assuming the same percentage of waste in each waste category defined by Directive 2012/19/EU, the waste generated in each category was estimated for Canada and is listed in Table H - 1. Table H - 1: E-waste in different categories in Canada Categories Amount (in kt) Lamps 11.3 Small IT and telecommunications equipment 63.2 Screens 106.9 Temperature exchange equipment 123.1 Large equipment 147.4 Small equipment 272.1 Total 724 It shows that the small and large equipment and temperature exchange equipment are the major contributors to the e-waste stream. As described in section 2.3, the larger waste amount for large 282 equipment and temperature exchange equipment is primarily due to the higher weight per unit for these appliances compared to other categories. The amount of e-waste generated is also proportional to the number of EEE products being used in a household. The EEE being used in a given year will eventually become obsolete and will report to the waste stream. The last survey data for the percentage of Canadian households owning large electrical appliances is available for 2009 and is shown in Figure H - 1. The total number of households reported in 2009 was 10,900,500 (Statistics Canada, 2010b). Figure H - 1: Penetration of household electrical equipment in Canada in 2009 (Statistics Canada, 2010a) It showed that a large proportion of the households in Canada used electrical equipment in 2009, and the percentage would have increased in recent years due to the increase in the quality of life and per capita income. and per capita income. With a lifespan of 7–8 years for large appliances, as 283 mentioned in section 2.2, these units would have already been reported to waste streams and replaced by new units. Statista (2019) showed that there are 32.86 million mobile phone subscribers in Canada in 2018 and the Canadian Radio-television and Telecommunications Commission (2019) showed that 99.3% of the households reported having a landline or mobile service. Also, 18.8% of households reported having three or more mobile devices. Statistics Canada’s (2018) most recent survey for the year 2017 showed that almost up to 90% of the surveyed households reported owning electronics equipment such as cellphones, televisions, and computers. Figure H - 2 shows that 99% of households reported having a landline or cellular telephone, whereas 77% of households reported having some kind of television connection. With a lifespan of 2–4 years for these items, as mentioned in section 2.2, these would have already been reported to waste streams or will be reporting there in the next few years. Figure H - 1 and Figure H - 2, combined with the average estimated life listed in section 2.2, suggest that most of the equipment currently being purchased or in use will enter the waste stream in the near future, and thus, adding to the total generation of e-waste. 284 Figure H - 2: Penetration of household electronics equipment in Canada in 2017 Drawn from data reported by Statistics Canada (2018) Disposal practices This section looks into the different e-waste disposal practices used by Canadian households. The general trend for e-waste disposal is to put it in the garbage, return it to the supplier, drop it off at a depot, or donate it. Statistics Canada (2019) performs a household and environment survey every two years and gathers information for disposal practices used by Canadian households. Figure H - 3 shows that over half of the Canadian households admitted to having batteries for disposal, and 20% of households admitted having other types of e-waste such as computers, televisions, or cellphones for disposal in 2017. Based on 14,072,080 households in Canada in 2016 (Statistics Canada, 2016), these items will account for over twenty-three million e-waste units for disposal. 285 Figure H - 3: Percentage of households with different e-waste to dispose in 2017 Drawn from data reported by Statistics Canada (2019) Figure H - 4 to Figure H - 9 shows the general trend in disposal practices followed by Canadian households for various e-waste items. It shows that Canadian households are more likely to take their electronic waste to the depot or return them to the suppliers, which would then most likely be sent for recycling. At the same time, it can also be seen that 15–43% of the households still kept the waste as storage. Small IT equipment, such as cellphones, has a higher probability of being stored compared to other e-waste items. It is most likely to be due to a lack of awareness or a lack of drop-off depot locations nearby. Nanos Research (2019) showed that 81% of residents are aware of the cellphone recycling programs in 2018, and this number has not been increased since 2016. The mean storage period for cellphones was 24.3 months in 2018, and the major reason for storing was security reasons or to be kept as a backup. 286 Figure H - 4: Disposal behavior for dead/unwanted batteries Drawn from data reported by Statistics Canada (2019) Figure H - 5: Disposal behavior for dead/unwanted screens Drawn from data reported by Statistics Canada (2019) 287 Figure H - 6: Disposal behavior for dead/unwanted small IT and telecommunication waste Drawn from data reported by Statistics Canada (2019) Figure H - 7: Disposal behavior for dead/unwanted small equipment Drawn from data reported by Statistics Canada (2019) 288 Figure H - 8: Disposal behavior for dead/unwanted CFLs Drawn from data reported by Statistics Canada (2019) Figure H - 9: Disposal behavior for unwanted large appliances Drawn from data reported by Zarbil (2019) 289 Figure H - 4 to Figure H - 9 also show that up to 35% of the households put electronic waste such as dead compact fluorescent lamps (CFLs) in the garbage. This behavior is more common for CFLs and dead batteries but uncommon for other types of e-waste, most likely because of the value, size, and masses of individual units. The unit weight and value of IT equipment, screens, and small and large equipment are usually higher than lamps and batteries, which affect disposal behavior. This shows that the disposal behavior of e-waste is driven by the size and value of the item to be disposed. A large/bulky item such as large household appliance has a higher probability of being collected for recycling compared to the small items such as lamps. Similarly, more valuable items such as computers and cellphones will most likely be collected than dead batteries. Approximately 45–75% of households return the end-of-life EEE to a recycling depot, to the supplier, or to the point of purchase, depending on the type of EEE. A higher return rate was observed for televisions, computers and accessories, and large appliances, confirming that products with higher unit weight or higher value have a larger probability of being recycled. On average, 61% of waste EEE was returned, suggesting that the collection rate for e-waste in Canada should be around 61%. E-waste management The consumer behavior for e-waste disposal was shown in the previous section. However, disposal practices are highly influenced by the policies, rules and regulations, awareness, and the availability of proper drop-off locations in the vicinity. This section discusses the regulations 290 related to e-waste management in Canada and organizations involved in increasing awareness regarding e-waste, e-waste collection, and recycling. Legislations There is no specific federal legislation dedicated to electronic waste management in Canada. However, the federal government does regulate hazardous waste and hazardous recyclable materials, which suggests that computers and other electronic equipment could become hazardous if discarded or recycled improperly (Government of Canada, 2017c). The Canadian Environmental Protection Act, 1999, was developed to govern the import-export of hazardous waste and hazardous recyclable materials, including its transit through Canada. In Canada, all three levels of government handle different aspects of hazardous waste and hazardous recyclable materials. The federal government regulates the transboundary movements (import/export) of hazardous waste and negotiates the related international agreement. Environment and Climate Change Canada is the main regulating authority at the federal level. The provincial and territorial governments control the interprovincial movement of waste and establish controls and criteria for licensing waste generators, carriers, and treatment facilities. The municipal governments manage the collection, recycling, composting, and disposal programs (Government of Canada, 2016; Hunt et al., 2018; VanderPol, 2014). The Waste Reduction and Management Division of Environment and Climate Change Canada implemented three regulations under the Canadian Environmental Protection Act, 1999 (Government of Canada, 2016). 291 1. Export and Import of Hazardous Waste and Hazardous Recyclable Material Regulations governs, controls, and tracks the transboundary flow of hazardous waste and hazardous recyclable material between Canada and other countries. 2. Polychlorinated Biphenyls (PCBs) Waste Export Regulations govern the PCBs export to the United States for treatment and destruction, excluding landfilling if the concentration is over 50 ppm. 3. Interprovincial Movement of Hazardous Waste Regulations controls the flow of hazardous waste and hazardous recyclable material between provinces and territories. As per international agreements, Canada is one of the original signatories of the Basel Convention developed in 1989. It is dedicated to the control of transboundary movements of hazardous waste and their disposal. The key objectives of the Basel Convention are to minimize the generation of hazardous waste, ensuring environmentally-friendly disposal of hazardous waste, and the minimization of the international movement of hazardous waste (Government of Canada, 2017a). Canada is also a participant in the Organization for Economic Co-operation and Development (OECD) that complements the Basel Convention and is applied to the transboundary movement of hazardous waste from one OECD member country to another for recovery/recycling operations (Government of Canada, 2017d). Canada and the United States have a comprehensive agreement for the transboundary movement of hazardous waste, which details the requirements for the transport of hazardous waste across the border. The parties involved must file relevant documents detailing the type and amount of waste, the date for export and the method of recycling, treatment, storage, or disposal (Government of Canada, 2017b). 292 Extended producer responsibility (EPR) and product stewardship programs are managed by the provincial and territorial governments to manage end-of-life products. These programs are developed by industries and funded by consumers through an eco-fee applied during the purchase. The eco-fee, or the environmental handling fee, depends on the size, weight, and value of the EEE and reflects the cost to manage the waste EEE. In 2009, the Canadian Council of Ministers of the Environment approved the Canada-wide Action Plan for EPR, intending to shift the expenses associated with product end-of-life management from taxpayers to producers and consumers. It also focused on the reduction of the toxicity and environmental risks from the products/waste. The management of electrical and electronic products was included in phase 1 of the plan (Canadian Council of Ministers of the Environment, 2009). As per the latest EPR Canada report in 2016, all provinces and territories except Nunavut have EPR, product stewardship, or other programs to manage electronic products/waste. The major issue of program implementation in Nunavut is its small remote population and the cost of waste handling, storing, and transportation (EPR Canada, 2017). The municipal government is responsible for overseeing and managing the local waste. They can also impose landfill bans. Local municipalities also organize e-waste collection events in the area and provide recycling and disposal directions to the public. Programs related to e-waste recycling in Canada There are several programs for the collection and recycling of electronic waste in Canada. These programs are regulated mostly by the provincial and territorial governments. Since the provincial government is responsible for the EPR and stewardship programs, not all programs are being operated in all provinces. British Columbia has one of the most comprehensive lists of EPR and 293 stewardship programs, ranging from laptops and desktops to outdoor equipment. The major programs for the management of various e-waste types in Canada are listed in this section. Temperature exchange equipment There is no regulated EPR or stewardship plan dedicated to this equipment across Canada except in British Columbia. The collection of refrigeration and cooling appliances are managed by local municipalities through community programs or local recyclers. They can also be dropped off at the point of purchase or local stores such as London Drugs or RONA. Some provinces also have a power smart program to collect/drop off the older appliance. This program is usually run by the province’s hydro supplier such as the Refrigerator Retirement Program by Manitoba Hydro and the Hydro Fridge Pick Up by Ontario Power Authority (Manitoba Hydro, 2011; Ontario Power Authority, 2018). In British Columbia, the collection and recycling is operated by the Major Appliance Recycling Roundtable (MARR), a not-for-profit stewardship organization responsible for end-of-life major household appliances including refrigeration and cooling appliances. The stewardship plan was approved by the British Columbia Ministry of Environment in 2012. Over 38,000 tonnes of large appliances were collected in 2016 (Ellacott, 2017). Screens, monitors, and equipment containing screens This is one of the most regulated e-waste categories across Canada. Almost every province has an EPR or stewardship program for the collection of televisions, computers, and accessories. In most provinces, the EPR is managed by the Electronic Product Recycling Association (EPRA), an industry-led, non-profit organization that regulates the recycling programs across Canada to 294 ensure safe, secure, and environmentally friendly handling of electronic waste. All the recyclers associated with EPRA are audited and approved under the national Recycler Qualification Program. EPRA is currently operating in all provinces except Alberta and has over 2,400 drop-off locations (EPRA, 2019). It was estimated that over 97% of the population lived within 30 km or thirty minutes of a collection/drop-off depot (EPRA, 2019; OES, 2019). In Alberta, the computer-and-accessories recycling program is managed by the Alberta Recycling Management Authority (ARMA). It is a non-profit association that manages the collection and recycling of tires, electronic waste, and paint in Alberta. The electronic recycling program was initiated in 2004 in Alberta to keep old computers and televisions out of landfills (Alberta Recycling Management Authority, 2019). In 2018, 563000 units of TVs and computer products were recycled by Alberta’s recycling program, helping to keep nearly 300 kg of hazardous substances such as lead, mercury, and cadmium out of the landfills. In the Northwest Territories, the electronic recycling program (ERP) was launched in February 2016 (Alberta Recycling, 2016). Rethink It is the waste reduction and recovery initiative from the government of Northwest Territories and includes a beverage container program, a single-use retail bag program, and an electronics recycling program. In this program, the electronics collected by the communities are consolidated at Inuvik, Hay River, and Yellowknife and then shipped to a registered recycling facility in Alberta for further processing (Environment and Natural Resources, 2017). Over 200 tonnes of electronics have been collected under this program since 2016. The electronics recycling program in Yukon was implemented in October 2018 along with the recycling of tires. The government of Yukon partnered with EPRA to manage the registration and surcharge collection process in the territory (Yukon Department of Environment, 2019). 295 Lamps The light recycling program was started by ProductCare in British Columbia in 2010 to manage mercury-containing bulbs. ProductCare is a federally incorporated not-for-profit organization that provides recycling services for paint, lighting products, household hazardous waste, and smoke alarms in nine Canadian provinces. The light recycling program from ProductCare is currently being operated only in British Columbia, Manitoba, Quebec, and Prince Edward Island. It has over 1300 permanent collection depots in four provinces. ProductCare collected over eleven million light bulbs in 2018 and over forty million bulbs since 2010. In most provinces, the program is focused on all types of light products, including compact fluorescent lamps, light-emitting diodes lamps, and incandescent bulbs (ProductCare Recycling, 2019a). The light recycling program in Quebec is named RecycFluo. The Recycling Council of Ontario manages the Take Back the Light (TBL) program for safe and proper recycling of lamps and lighting products. The program was launched in 2008 and has collected nearly twenty-eight million lamps since inception (Recycling Council of Ontario, 2019). In other provinces, there is no specific program for the collection and recycling of lamps, and the lamps and lighting products can be dropped off at local municipalities and stores such as London Drugs, RONA, and thrift stores. Large equipment Similar to temperature exchange equipment, large equipment does not have regulated EPR or stewardship plans across Canada. The collection is managed by local municipalities through community programs or local recyclers or could be dropped off at the point of purchase or local 296 stores such as London Drugs or RONA. In British Columbia, the collection and recycling of large appliances are managed and operated by Major Appliance Recycling Roundtable (MARR), Approximately 600,000 units of large appliances were collected in 2018 (Zarbil, 2019). Some of the large appliances, such as large computer-mainframes, printing machines, copying equipment, are also managed by EPRA. Small equipment Similar to large equipment, small appliances do not have a specific stewardship program across Canada, except in British Columbia. Most of the small household appliances, such as vacuum cleaners, microwaves, toasters, electric kettles, can be dropped off at local recycling centers, stores, and thrift stores, or with other garbage to be picked up by the municipalities. ElectroRecycle is a recycling program operated by the Canadian Electrical Stewardship Association (CESA) in British Columbia for the collection and recycling of small household appliances. CESA is a federally incorporated non-profit organization established in 2011 to develop a recycling program to manage end-of-life products like various small household appliances and power tools. More than 300 products are managed in this program, including kitchen countertop, personal care, floor cleaning, and sports and leisure appliances, as well as power tools and exercise machines. It operated 220 collection sites across British Columbia and collected over five million kg of waste in 2018 (CESA, 2019). British Columbia also has a stewardship program for the recycling of outdoor power equipment that was established by the outdoor power equipment institute of Canada (OPEIC) in 2012. Items that can be recycled in this program include electric-powered outdoor equipment such as gardening 297 tools, chain saws, ice drills, grass trimmers, lawn blowers, lawnmowers, snowblowers, pressure washers, woodchippers, and lawn tractors. Fuel-powered outdoor equipment is not included in the program. As of 2018, OPEIC has seventy-six collection sites and recycling networks across British Columbia (Martin, 2019). The absolute number of items or weight of outdoor power equipment collected every year is not available, but OPEIC performs sampling studies in Lower Mainland and Vancouver Island at ten collection sites every year. It showed that 0.14% of the total sampled material was electrical outdoor power equipment (Martin, 2019). In British Columbia, recycling smoke and carbon monoxide alarms is a program started by ProductCare in 2011 for residential alarms. In 2018, this program recycled over 96,000 alarms in British Columbia and is operating over 200 recycling locations. However, the annual report showed that only 42% of residents are aware of this program (ProductCare Recycling, 2019a). Usually, the radioactive element in the alarms is removed, the plastic material is crushed into small pieces, and the metal is used to make new products (ProductCare Recycling, 2019b). Some small equipment such as calculators, radios, and video cameras is managed by EPRA in various provinces. For a thermostat, the thermostat recovery program is a stewardship program operated by the Heating, Refrigeration and Air Conditioning Institute of Canada (HRAI). The program is supported by the Canadian Institute of Plumbing and Heating (CIPH). The program was operated as Switch the ‘Stat from 2006 to 2016 in British Columbia and Manitoba, and it operated voluntarily across Canada. An old thermostat could contain 2.5–10 g of mercury that would contaminate air, soil, and water if disposed of improperly (HRAI, 2016). 298 Small IT and telecommunication equipment Equipment such as mobile phones, GPS, pocket calculators, routers, personal computers, printers, and telephones are managed by several programs across Canada. Recycle my Cell is Canada’s national industry-led recycling program for cellphones, mobile devices, and accessories. It is operated and managed by the Canadian Wireless Telecommunications Association (CWTA) and its members, the cell phone carriers, and manufacturers (Recycle my cell, 2019). It has over 2600 drop-off locations across Canada and has recovered nearly seven million devices since 2009. The latest survey showed that 51% of Canadians reused and recycled their old cellphones, whereas 44% stored it away. Only 1% reported putting their old cellphones in the trash (Nanos Research, 2019). The program operates in all provinces except Nunavut. Call2Recycle is a not-for-profit stewardship, recycling program established in 1997 dedicated to the safe collection, transportation, and recycling of consumer batteries. Over 91% of Canadians live within 15 km of a Call2Recycle drop-off location. The program has recycled over eleven million kg of batteries since its inception (Call2Recycle, 2016b). The program collects rechargeable batteries, single-use batteries, and cellphones. It includes nickel-cadmium, nickel-metal hydride, nickel-zinc, lithium-ion, small sealed lead-acid, and alkaline batteries (Call2Recycle, 2019). Call2Recycle Canada Inc. is the approved battery stewardship organization in British Columbia, Manitoba, and Quebec. It has formal agreements with ministers in the provinces of New Brunswick and Prince Edward Island. It collects batteries in Ontario, but it is not the approved 299 program in Ontario, and it is also available to the residents of Newfoundland, Labrador, Nova Scotia, Alberta, and Saskatchewan through the support from the industry (Call2Recycle, 2016a). It collected over 2.7 million kg of batteries in 2018 with its network of 8,800 collection facilities and partners (Call2Recycle Canada Inc., 2019). EPRA also accepts cellular and non-cellular telephones, personal computers, IT and telecom equipment, and printers. Cellphone network carriers such as Shaw and TELUS also have stewardship plans in British Columbia for the recycling of cellphones, modems, routers, set-top boxes, and their batteries. E-waste collection summary For the EPR and product stewardship plan, the regulation requires the production of an annual report for the government that should be available publicly. The report should include the financial statement, program monitoring statistics, and other matrices, such as the amount collected and the number of drop-off locations (Canadian Council of Ministers of the Environment, 2009). Table H - 2 shows the amount of e-waste collected that is summarized in the annual reports produced by the EPR and stewardship programs. It shows the highest collection amount reported for computers and accessories as all provinces have a stewardship program for the collection of items in these categories. The reduction in the total collection weight in these categories is most likely due to the reduction in the unit weight of consumer electronics, especially screens, monitors, computers, and accessories. It is suggested that fewer old, heavy TVs and monitors are being collected in recent years and are replaced by newer and lighter models (Alberta Recycling Management Authority, 2019; Baldé et al., 2017). The 300 reduction in the weight of these categories also affected the total reported e-waste collection, which decreased to 169 kT in 2018 compared to about 180 kT in 2016. Since the collection data of temperature exchange equipment and large equipment that has the highest unit weights are not available for all the provinces, the total e-waste collection does not represent the actual collection statistics across Canada. 301 Table H - 2: Total reported e-waste collection by various programs Program Province Category 2016 (tonnes) 2018 (tonnes) EPRA/ARMA/OES/ERP All except NU TV/computers/cellphones 126,572 106,744 Recycle my Cell All except NU Cellphones/accessories/batteries 121 86 Call2Recycle All except NU Cellphones/accessories/batteries 2,784 2,700 ElectroRecycle BC Small equipment 4,545 5,092 Light Recycle/TBL BC/MB/ON/QC/PE Lamps 2,113 2,694 Alarm Recycle BC Small equipment 89 96 TRP BC/AB/SK/MB/ON/QC/NB Small equipment 1.1 1.6 Shaw/TELUS program BC IT & telecommunication 1,738 2,150 MARR BC Large appliances/temp. ex. eq. 38,394 45,255 Canada beverage association BC Cooler/vending machines 1,072 452 Ontario orange drop ON Batteries 3,226 2,964 Total reported collection 180,656 168,235 Total generation volume 724,000 723,000* Reported collection rate 25.0% 23.3% *Estimated from the trend of generation volume from 2014 to 2016 and extrapolating to 2018 302 The total amount of e-waste generated in Canada in 2016 was reported to be 724 kT (Baldé et al., 2017), and the total e-waste collection as per Table H - 2 in 2016 was ~180 kT, representing approximately 25% e-waste collection rate. For 2018, the total amount of e-waste generated in Canada in 2018 was estimated to be 723 kT by extrapolating the generation statistics of 2014 and 2016. The total e-waste collection as per Table H - 2 in 2018 was ~168 kT, representing 23.3% of e-waste collection rate. It should be noted that this only represents the collection volume for the reported data from the EPR and stewardship programs. There are well-established informal collection and recycling sites in all parts of Canada for e-waste management (Giroux, 2014). However, the collection volumes are not reported. To estimate the collection volume from all over Canada, the populations in British Columbia and Canada in 2016 and 2018 was obtained from the population survey, and it was used in combination with the reported collection volumes in British Columbia and the average e-waste awareness across Canada, as reported by EPRA and Equation H - 1. It assumes that the disposal behavior of e-waste is consistent across Canada, and the collection statistics in British Columbia can be extrapolated to the entire country. 𝐶𝑜𝑙𝑙𝑒𝑐𝑡𝑖𝑜𝑛 𝑖𝑛 𝐶𝑎𝑛𝑎𝑑𝑎 = 𝑃𝐶𝑎𝑛𝑎𝑑𝑎𝑃𝐵𝐶× 𝐶𝑜𝑙𝑙𝑒𝑐𝑡𝑖𝑜𝑛 𝑖𝑛 𝐵𝐶 ×𝐴𝐶𝑎𝑛𝑎𝑑𝑎 𝐴𝐵𝐶 Equation H - 1 Where, PCanada and PBC are population in Canada and British Columbia 303 ACanada and ABC are percentage awareness for recycling programs/locations for waste EEE reported by EPRA. Awareness in BC was reported to be 70%, and awareness in Canada was estimated by a weighted average of awareness in different provinces and their respective populations. Using this method, the collection for small and large equipment, lamps, thermostats, and IT and telecommunication devices was estimated. Table H - 3 shows the total estimated collection of e-waste in Canada. Total e-waste collection estimated by this method was over 460 kT in 2016, representing a collection rate of approximately 64%. The collection rate was increased to over 72% in 2018, showing an increase in awareness regarding e-waste disposal. This value is also in the range suggested in the disposal practice section (45 – 75%) that was related to the return of e-waste to a collection site or the suppliers. Increasing the number of drop-off locations and providing awareness to residents helps with the increase in the collection rate. It should be noted that these values are estimated using British Columbia’s collection volume as a base, and hence, would not represent accurate collection statistics. To increase the collection rate, the EPR and stewardship programs are adding more drop-off locations, increasing funding to awareness campaigns, and promoting e-waste collection events across Canada. Alberta is expanding the list of items that could be dropped off at collection depots and adding small appliances, audio/visual equipment, telecommunications equipment, and power tools into their existing list of accepted items (Government of Alberta, 2018). In Ontario, the government is doing away with the old WEEE program and replacing it with new electrical and electronic equipment regulations that would cover more e-waste categories (Resource Productivity 304 & Recovery Authority, 2019). These amendments will help to increase the e-waste collection volume in Canada once implemented. Table H - 3: Total estimated e-waste collection in Canada Program Category 2016 (tonnes) 2018 (tonnes) EPRA/ARMA/OES/ERP TV/computers/cellphones 126,572 106,744 Recycle my Cell Cellphones/accessories/batteries 121 86 Call2Recycle Cellphones/accessories/batteries 2,784 2,700 ElectroRecycle Small equipment 32,490 39,283 Light Recycle/TBL Lamps 1,282 1,955 Alarm Recycle Small equipment 636 741 TRP Small equipment 6.5 10.4 Shaw/TELUS program IT & telecommunication 12,424 16,586 MARR Large appliance/temp. ex. eq. 274,462 349,125 Canada beverage association Cooler/vending machines 7,663 3,487 Ontario orange drop Batteries 3,226 2,964 Total estimated collection 461,668 523,681 Total generation volume 724,000 723,000* Estimated collection rate 63.8% 72.4% *Estimated from the trend of generation volume from 2014 to 2016 and extrapolating to 2018 E-waste landfilling Landfilling could be one of the most economical ways for waste management in a large country like Canada (Elbeshbishy & Okoye, 2019). However, landfilling of e-waste could leach toxic 305 materials into the soil and groundwater, if managed poorly. All landfills in Canada must undergo an environmental assessment before their construction (Giroux, 2014). The EPR and stewardship programs for e-waste management are implemented to divert the e-waste from landfills. Séguin (2014) reported that for every tonne of materials diverted from landfill, approximately $4,150 of value was created from recycling and related activities. Landfilling of e-waste is not permitted under the Electronics Recycling Standard (ERS) set by the Electronics Product Stewardship Canada (EPSC). One of the most effective ways of diverting e-waste to recycling facilities is landfill bans. The municipalities could implement a landfill ban to support EPR programs (Séguin, 2014). The landfill bans and increased landfill tipping fees have created incentives for recycling (Kerr, 2013). Currently, a provincial landfill ban for e-waste is implemented in Nova Scotia, Prince Edward Island, and Newfoundland and Labrador. In other provinces, the municipalities are creating goals to divert e-waste from landfills. For example, some municipalities such as North Bay and Waterloo in Ontario; Metro Vancouver, Nanaimo, and Okanagan in British Columbia; and the City of Whitehorse in Yukon have banned the landfilling of e-waste. Some provinces have introduced additional costs for the landfilling of e-waste to increase the diversion of e-waste from landfills. Manitoba has added $10 per tonne, and Quebec has introduced $20.69 per tonne as a landfill levy, in addition to the landfill tipping fee (Séguin, 2014). It should also be noted that the residents’ awareness of e-waste recycling programs also helps to reduce the e-waste being disposed of in landfills. On average, 10% of households reported throwing waste EEE in the garbage. The reported value is as high as 34% for CFLs and as low as 2% for computers and accessories. Once thrown in the garbage, e-waste has a higher probability 306 of ending up in landfills. Increased awareness and additional collection points would reduce the e-waste being thrown in the garbage, and thus, divert it from landfills to recycling centers. Export of e-waste As described in e-waste management section, Canada is one of the signatories of the Basel Convention, a treaty designed to control the transboundary movements of hazardous waste and also one of the OECD members that allows e-waste export purely for recovery and recycling purposes. Canada also has strict regulations such as Export and Import of Hazardous Waste and Hazardous Recyclable Material Regulations (EIHWHRMR) that controls and tracks the transboundary flow of hazardous waste from 1992, that was last amended in October 2016. With all the mentioned treaties and regulations, the export of e-waste from Canada to developing countries in Asia is still a major concern, as reported from the e-trash transparency project report (Puckett et al., 2018). Lower labor costs, poor regulations, and cheaper disposal facilities provide economically favorable conditions for recyclers to export the e-waste to less-developed countries (Ilankoon et al., 2018; Sepúlveda et al., 2010). One of the loopholes in the e-waste export is the distinction between waste EEE and used EEE. Some shipments could include old but still functioning devices but which have no real value or market (Huisman et al., 2015). With no real market, the exported old EEE would be discarded and should be considered e-waste. In 2017, the Basel Action Network (BAN) used GPS trackers on forty-three non-functional and economically unrepairable electronic devices to track the movement of e-waste from Canadian recyclers in various provinces. The trackers showed that 12% of devices were exported out of Canada to Hong Kong, Pakistan, and the United States. Four devices were exported by the non-307 profit organization Electronics Recycling Association (ERA), and one device was exported by an EPRA/ARMA approved recycler (Puckett et al., 2018). BAN has also reported that ERA is a constant Canadian exporter of e-waste to developing countries from three locations in Vancouver, BC, for over ten years. Hunt et al. (2018) also reported the export of e-waste from multiple Vancouver-based companies in 2014. Recyclers in Surrey (BC) were fined $40,000 following an Environment Canada investigation regarding illegal export of hazardous waste, including batteries (Pynn, 2015). It was suggested that authorities need to enforce the Basel Convention rules, performing port inspections and investigating the practices of the ERA (Puckett et al., 2018). Recycling The e-waste collected in Canada would most likely be processed by Canadian recyclers if it is not exported or landfilled. However, the total amount recycled in Canada is not reported by any organization. This section provided details regarding the most common recycling practices adopted in Canada. In the last few years, e-waste recycling has attracted major investment and support from the government. Most of the recyclers would obtain the e-waste collected by the programs mentioned in e-waste management section; e-waste could also be dropped off directly to the recycling company. In most cases, depending on the unit being recycled, hazardous materials such as batteries and mercury-containing parts are removed. The remaining product is manually dismantled, sorted in individual streams, shredded, and then packed for shipment for further 308 processing. The shredded material is separated into various streams using a combination of a magnet, gravity separator, electrical separator, and automated sorters. Some of the major recyclers operating in Canada are: CFER: It offers waste management for organizations. The waste EEE is manually dismantled, sorted, pressed into a bundle, and sent to other recyclers for subsequent processing. The CFER processes over 2000 tonnes of EEE every year. In 2016, there are twenty-four operating CFER in Quebec. Computers for Schools: It refurbishes collected computers and distributes them to schools, libraries, and not-for-profit organizations across Canada. FCM recycling: It is one of the largest e-waste recyclers in Canada and has dismantled and shredded over 29,000 tonnes in 2016 and sent them for downstream handling. It operates in Quebec, Ontario, Nova Scotia, British Columbia, and Alberta. The main shredder is located in Montreal, and other locations collect, sort, and dismantle waste EEE and send it to Montreal for subsequent processing (Chamberlain & Wiens, 2012). Greentec: Operating in Ontario, Greentec has received over 120 million pounds of electronics for recycling. The received materials are sorted, dismantled, shredded, and sold to other recyclers for subsequent processing (Grischow-Pereira, 2018). Greentec uses the technology solutions offered by BlueBox Switzerland for the processing of flat-screen televisions and lamps where the material is shredded, and the mercury vapor used for backlighting is captured using negative pressure. The shredded material is sorted into plastics, glass, metals, and circuit boards. 309 Quantum Lifecycle Partners LP: It is the result of the merger of three recycling companies, GEEP recycling, Shift recycling, and Revolution. It operates in four provinces: Ontario, British Columbia, Alberta, and Quebec. The process is similar to other recyclers, where received materials are sorted, dismantled, shredded, and then shipped for further processing (Barker, 2019). eCycle: Operating in British Columbia, Alberta, Ontario, and Quebec, eCycle provides recycling services for computers and accessories, televisions, batteries, cellphones, and tablets. E-waste recycling process Details of the e-waste recycling process at four recycling facilities in Canada are presented as three cases for analyzing and understanding the e-waste recycling process adopted in some organizations in Canada. The study of the first three facilities was conducted by site visits, whereas the fourth facility was studied through literature. Facility 1: Reuse, refurbish, and dismantling Facility 1 is a center located in Vancouver, British Columbia. This center specializes in the refurbishing, reusing, and recycling of computers and accessories, fax machines, cellphones, and monitors. The e-waste processed at this center is from EPRA, or individuals and businesses can drop off their end-of-life electronics directly at the center. Pick-up service for e-waste can also be requested. Figure H - 10 shows the process flow sheet for this facility. 310 Figure H - 10: Process flowsheet for facility 1 The received units are tested for their reusability, and if the electronic product is still functional, it is sold at a lower cost for reuse. The components of the electronics are tested separately as well, and the working components are either sold individually or sometimes used to refurbish a new unit and then sold. The remaining items are recycled. The waste electronics are manually dismantled and separated into various streams such as metals (especially steel), plastics, printed circuit boards, and ink/toner, and individual streams are shipped to different locations for subsequent processing. A list of the subsequent processors is shown in Table H - 4. The rest of the bulk mixed waste is packed and shipped back to EPRA for further processing. 311 Table H - 4: Customers for individual streams for facility 1 Materials Customer Steel/metals North Star Metal Recycling Plastics Westcoast Plastic Recycling Printed circuit boards The Refining Company Inc. Ink/toner PCR America Facility 2: Dismantling The second facility is one of the largest e-waste processors in Canada, with recycling centers in four provinces and the ability to serve all provinces from these locations. The location studied is in Chilliwack, British Columbia, serving Metro Vancouver and its surrounding areas, and it focuses on recycling only. It specializes in all kinds of e-waste, from computers and televisions to small home appliances. This processing center receives almost fifty tonnes of e-waste every day from EPRA and CESA. There are four separate processing lines at this location, and the process is similar to that at facility 1. The waste EEE is dismantled, and hazardous materials are removed from the waste stream, and then the remaining material is shipped to their central location in Quebec for subsequent processing involving the shredder, eddy current separator, and optical sorters. Figure H - 11 outlines the process used at this facility for separation and dismantling. 312 Figure H - 11: Process flowsheet for facility 2 Processing line 1 deals with computers and laptops. Workers remove components such as wires, circuit boards, and outer casings and put them in separate containers for shipping. Processing line 2 works on removing hazardous materials from small home appliances. Major hazardous materials are batteries and mercury tubes. Processing line 3 is dedicated to computer accessories such as keyboards, printers, scanners, mouse, and hard drives. The major hazardous material to be removed from this line is the ink and toner from the printer as well as the destruction of the data from hard drives. Processing line 4 is the display processing line dealing with the dismantling of televisions and computer displays. The back panel of the CRT screen is leaded glass and is removed from the front panel, which is the high-quality glass. In the case of flat screens, the glycol assembly and mercury bulbs are the major hazardous materials that are removed from the system. 313 After the dismantling and hazardous material removal, the remaining materials (mostly metal and plastic) are bailed and shipped to Quebec for final processing. The facility in Quebec uses a combination of a shredder, eddy currents, magnets, optical sorters, and other proprietary technology to separate plastics and metals by their types. Facility 3: Circuit board recycling This facility focuses on the recycling of waste printed circuit boards obtained from various electronics. The pilot processing plant is located in Richmond, British Columbia. The goal of the company is to recirculate the metals and non-metals from the printed circuit boards back to the manufacturing of new products, and thus, creating a circular economy. The pilot plant processes a mixture of FR-2 and FR-4 printed circuit boards obtained from computers, printers, televisions, printers, servers, cellphones, and other household electronics. Figure H - 12 shows the process flowsheet for facility 3. The initial stage of size reduction is achieved by using a combination of the shredder and hammer mill. The crushed material is suspended in water and is separated into metal and non-metal streams using a wet shaking table, whereas middling is split into + 0.85 mm and – 0.85 mm streams. The coarse middling stream is sent for further size reduction, whereas the fine middling stream is circulated through the patented sonic chamber technology. The chamber uses low frequency and high amplitude sound waves to liberate the metals from the non-metals. The liberated material is recirculated back to the shaking table. The separated streams are dewatered, air dried, and stored in 750 kg bulk bags for shipment. The metal concentrate is shipped to a smelter for metal refining, whereas the company is exploring the best possible usage for the non-metal rejects. The company is in the process of designing a commercial plant with a nominal throughput of 10,000 tonnes per 314 annum (1.2 tonnes per hour). The mass yield for the metal concentrate is reported to be 36% with 93% metal recovery, whereas 7% of the metals are lost in non-metal fraction (Ronin8 Technologies Ltd, 2018). Figure H - 12: Process flowsheet for facility 3 Facility 4: Pyrometallurgy The fourth facility is one of the largest smelters in Canada and owned by Glencore (previously Xstrata). The Horne smelter in Quebec is the world’s largest smelter of e-waste. It uses copper concentrate and metal-containing e-waste to produce copper anodes. The anodes are further refined at the Canadian Copper Refinery in Montreal to produce pure copper (Glencore Recycling, 2019). In 2008, it was announced that Horne Smelter would double its e-waste processing capability to 315 100,000 tonnes per year by 2010, which would represent 60% of the recycling capacity at Horne (Metal Bulletin, 2008). Figure H - 13 shows the simplified smelting process at the Horne reactor. Figure H - 13: Smelting process at Horne reactor (Adapted from Canadian Mining Journal, 2000; Cui & Zhang, 2008) In this reactor, oxides of iron, lead, and zinc produced during the oxidation process report to the slag that is processed to recover metals before disposal. A copper anode is produced with a purity of 99.1%, and the remaining 0.9% contains other metals such as gold, silver, platinum, palladium, selenium, and nickel that are further purified using electrorefining (Cui & Zhang, 2008; Tesfaye et al., 2017). 316 Challenges and recommendation for promoting the circular economy in Canada Previous sections discussed the current situation of e-waste collection and processing in Canada and also the recycling processes adopted at four different facilities in Canada. Based on these details, this section discusses major challenges in e-waste recycling and the hurdles in improving the circular economy in Canada. Some recommendations for increasing the circular economy are also provided. Regulations One of the major challenges for proper e-waste management is the lack of federal regulations. Namias (2013) suggested that a lack of national regulations significantly decreases the recycling rates in a country, and a federal approach acts as a drive to improve collection and recycling rates. Ylä-Mella & Román (2019) showed that a strong national legislative framework in Switzerland, Norway, and Sweden had introduced good examples in Europe, with 70–75% reported e-waste collection rates. The key responsibilities for all stakeholders should be developed and defined at national levels. The regulations for e-waste management in Canada are governed by the provincial government, which is not consistent in different provinces and territories. The federal legislation would remove the discrepancies in the provincial regulations and will help to set the same standards for e-waste recycling across Canada, which would, in turn, boost the collection rate and the recycling rates. Adding synchronicity among the provincial level programs across Canada would also help to boost the collection rates. 317 EPR and stewardship programs There are several EPR and stewardship programs for e-waste management in across Canada. The programs operating in all the provinces are limited mostly to computers and accessories and televisions. The program for small and large household appliances, lamps, and alarms are mostly limited to British Columbia. These programs are essential to increase awareness as well as increasing the collection rate. These programs also summarize and report the collection volumes, which helping to understand the program performance and provide better planning tools for the future. Expanding the EPR and stewardship program from British Columbia to all Canadian provinces and territories will help to improve the collection rates. New programs that would integrate all the e-waste categories under one roof would provide a better solution to the e-waste problem. Provinces such as Alberta and Ontario are already moving towards this approach. Alberta is adding other e-waste categories to their current program, whereas Ontario is s moving away from the old e-waste management program and replacing it with a new program that would include all e-waste categories (Government of Alberta, 2018; Resource Productivity & Recovery Authority, 2019). This would help to improve awareness and properly quantify the e-waste collection volumes across Canada, and thus, help to plan better strategies in order to achieve the old target or set new, more ambitious targets. It would also help to integrate the e-waste collection depots to receive all types of e-waste, thus, increasing the overall availability of drop-off locations. 318 E-waste data management and targets One of the crucial elements of e-waste management is the availability of data related to e-waste generation, collection, and recycling. Eurostat (2019) and Urban Mine Platform (2019) have detailed information regarding the e-waste generation, collection and recycling rates, and volumes for all European Union countries. This publicly accessible data provided a clear picture of the performance of e-waste regulations in Europe and also helped with the future planning for increasing the collection and recycling rates. At the same time, the European Union Directive 2012/19/EU (2012) set out the minimum recovery targets for e-waste collection and recycling targets based on the e-waste types. The minimum target applicable after August 15th, 2018, was set to a 75–85% collection rate and a 55–80% reuse/recycling rate, depending on the type of e-waste. These defined targets help to form the legislation and programs to achieve the minimum targets. In Canada, the only e-waste related available data is for the collected volumes of provincial EPR programs. The Canadian national statistics agency, Statistics Canada, does provide survey data regarding the household behavior of e-waste disposal but does not have any data related to e-waste generation, collection, or recycling volumes. A database with this information and future targets will help the planning and reporting of e-waste management and significantly boost the circularity of e-waste. Landfill bans Landfill fill bans are one of the other significant ways to improve the collection and recycling of electronic waste. It forces the recycling authorities to find alternatives to landfill disposal. Ylä-319 Mella & Román (2019) showed that the cost of landfilling in Europe had boosted the e-waste recycling rate by making landfilling a very expensive waste disposal option. Few provinces and some municipalities have already banned the landfilling of electronic waste. A nationwide landfill ban for e-waste will further divert more materials from the landfill, and thus, improve e-waste collection rates and recycling. Recycling centers Most of the Canadian provinces have some sorting and dismantling facility. These facilities mostly handle the dismantling activity for e-waste and ship dismantled materials to other provinces or sometimes countries for further processing, whereas the Horne smelter processes the shredded e-waste directly without any preconcentration. The process of the transportation of materials is time-consuming and costly. This suggests that one of the significant barriers to recycling would be the lack of advanced and developed recycling centers in different provinces. A province-based central recycling facility, especially in highly populated provinces, equipped with pre-processing capabilities such as shredding and physical separations, e.g., magnetic and gravity separation, would separate materials into various streams in a cost-effective manner. Then the separated stream could be transferred to the nearest end-processing facilities for subsequent processing. Facility 3 has shown that the recycling of printed circuit boards by separating the metals and non-metals is feasible at a local level and reduces the amount of material to be transported for subsequent processing. Based on a three tonnes/hour x eight-hour shift x six days per week x fifty weeks per year operation suggested by the PHA Consulting Associates (2006), it would require ~100 recycling facility to 320 recycle all the e-waste generated in Canada. Pieces of machinery with higher throughput could significantly reduce this number. PHA Consulting Associates (2006) suggested that mechanized facilities would process e-waste in Alberta, British Columbia, Ontario, and Quebec, whereas other provinces would use dismantling facilities and then transport materials to the nearest recycling facility for further processing. Due to increased e-waste generation, a province-based mechanized central recycling facility could operate in Alberta, British Columbia, Ontario, Quebec, Manitoba, Saskatchewan, and Nova Scotia. In contrast, other provinces and territories would perform shredding and physical separations and then transport the separated streams to the nearest recycling facility. These processes would separate the metal from the non-metal stream, reducing the amount of materials that would go through the smelting process. This will reduce the volume needed for transportation and also reduce the transportation distance, thus, reducing the costs and greenhouse gas emissions associated with transportation. Recycling technologies One of the challenges with e-waste recycling, not just in Canada but around the globe, is the rapidly changing and evolving electronics technology. The use of plastic in electronics is increasing, and plastics are hard to recycle due to the presence of different types of polymers. The use of embedded batteries that are glued into the electronics is also increasing, leading to the labor-intensive battery removal processes and also posing safety risks to workers (Shift Recycling, 2018). The development of new, small, and complex technologies used in cellphones, tablets, and laptops also poses a challenge to the current recycling methodology that involves manual dismantling and manual sorting. For example, a recycling facility/system designed to handle only the CRT monitors 321 will not be able to survive in the near future as the feedstock of waste CRT will soon be depleted due to the development of newer screens. Designing and researching flexible and automated systems is required to deal with next-generation e-waste that uses complex and nanoscale manufacturing processes and includes new polymers and materials. The recycling facility should be able to adapt to the inflow of newer technologies to survive. At the same time, most of the e-waste recycling technologies and industries are focused on the recycling of metallic fractions and do not put a high emphasis on the non-metals which represents a significant portion, due to their low economic values. Research and the development of innovative, cost-effective, non-metal recycling processes are also necessary to increase the circularity of non-metals, and thus, further promote the circular economy. Summary Electronic waste in Canada is a growing concern, as evident from the laws, regulations, and programs being either updated or implemented. However, most of the programs for e-waste management are only implemented at the provincial levels and vary in different provinces. The overall reported collection of e-waste in Canada was estimated to be only 25% of the total e-waste generated in 2016, due to e-waste collection only being reported from the EPR and stewardship programs. If extrapolated for the total collection in Canada, the overall e-waste collection was estimated to be ~ 64%. A federal-level e-waste management program or extension of the current programs across Canada would be able to increase the collection rates and also provide a better 322 estimation of e-waste collection; this would also provide a better understanding of the steps required to improve e-waste collection and recycling. On the other hand, e-waste recycling in Canada is mostly focused on hazardous component removal and dismantling, limiting the recycling to the easy-to-be-dismantled units. A province-based, highly mechanized, central recycling facility would help to deal with the issue related to the recycling of new technology and further improve the recycling rate, also decreasing the materials needed to be transported. These steps would, in turn, help to increase the collection and recycling rate of e-waste in Canada, and thus, promote the circular economy. 323 Appendix I - Short details of experimental methodologies Metal content analysis In this procedure, samples are screened at 4 mm (5 mesh), and any coarse material is ground using a mortar and pestle. From the ground sample, 1 ± 0.01 g of a sample is obtained and digested in 4 ml HNO3 and 10 ml HCl in a beaker at 950C for thirty minutes. The solution is then centrifuged to obtain a clear solution, which is then analyzed by inductively coupled plasma atomic emission spectrometry (ICP-AES). Metal oxide analysis The metal oxide is analyzed using whole-rock analysis, where the material is first mixed with lithium tetraborate fusion flux in a platinum crucible. The mixture is then heated to 10000C in a furnace until the mixture melts together to form a homogenous liquid. The liquid is then poured into dilute acid for subsequent ICP-AES. Toxicity characteristic leaching procedure (TCLP) test The maximum particle size requirement for the TCLP test is 9.5 mm, and any oversized material has to be crushed and ground to - 9.5 mm. The solid material is extracted in a column with a slightly acidic fluid (pH 4.93 ± 0.05 or 2.88 ± 0.05) twenty times the weight of the solids at 30 ± 2 RPM for 18 ± 2 hours at room temperature. The liquid is then filtered out and analyzed with the appropriate EPA standard method. 324 Polybrominated diphenyl ethers (PBDEs) analysis Approximately 20 g sample was obtained from the dried NMF and was sent to an external laboratory for PBDEs analysis. PBDEs extraction was performed using standard EPA 3541 procedure (EPA, 1994a), where ten grams of solids are placed in a thimble in soxhlet extractor and extracted with 50 mL of hexane and acetone mixture (1:1 v/v) for sixty minutes. The extracted solvent is then analyzed following standard EPA 8270D (EPA, 2014) guidelines for gas chromatography/mass spectrometry (GC/MS). Polychlorinated biphenyls (PCBs) analysis Approximately 10 g sample is used for this analysis, and any particle larger than 1 mm is ground until the sample particle size is all passing –1 mm. The prepared sample is placed in an extraction thimble in a Soxhlet extractor and extracted with 30–40 mL of toluene for a minimum of three hours. The extracted solvent is then analyzed using high-resolution gas chromatography/mass spectrometry (GC/MS). Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) analysis Approximately 10 g sample is used for this analysis, and any particle larger than 1 mm is ground until the sample particle size is all passing –1 mm. The prepared sample is placed in an extraction thimble in a Soxhlet extractor and extracted with 30–40 mL of toluene for a minimum of three (3) hours. The extracted solvent is then analyzed using high-resolution gas chromatography/mass spectrometry (GC/MS). PCDD/Fs are classified under toxic substances under the Canadian Environmental Protection Act (CEPA). The toxicity equivalency (TEQ) is a tool to assess the cumulative toxicity of a mixture of 325 PCDD/Fs. The toxicity levels (TEFs) for all compounds are assessed relative to the toxicity of 2,3,7,8-tetrachlorodibenzo-p-dioxin (tetra-CDD), the most toxic dioxin. TEQ represents the product of the concentrations of individual congeners and their respective TEFs. The lower limit is calculated by substituting zero (0) for any non-detectable compound, whereas the upper bound represents the worst-case scenario where the detection limit is used for the non-detectable compounds (Johnston, 2016). Float-sink test The standard procedure for coal washability analysis, as defined by ASTM D4371-06, was used for the float-sink test (ASTM International, 2012b). The sample was placed in the heavy liquid with the lowest specific gravity, stirred to free all particles, and allowed to settle. Floating particles were collected with a scoop lined with a fine mesh that allowed the excess liquid to drain, and the sunk material was transferred to the next heavy liquid, stirred, and again allowed to settle. Any particles floating at this specific gravity liquid are lighter than the previous liquid but heavier than the current liquid. Floating particles were again collected, and the sunk material was transferred to the next heavy liquid. The process was repeated for all liquids.
Thesis/Dissertation
eng
Mining Engineering
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Characterization of non-metal fraction of waste printed circuit boards to promote recycling
Text