Environmental assessment and decision support for the process design of tailings valorization PhD research plan: Lugas Raka Adrianto 27.01.2020 www.esd.ifu.ethz.ch/ Motivation (1) Trends: Demand of metals ↑↑ , but the ore grade ↓ ↓ (Van der Voet et al., 2019) Environmental burdens Primary resources processing Waste Slag, rock dust, etc. Mining operation Tailings Metal production www.esd.ifu.ethz.ch/ 2 Motivation (2) Tailings The problem The opportunity Leaching and long-term If properly managed, it environmental impacts could be future resources (Lottermosser, 2010) (JRC, 2019) www.esd.ifu.ethz.ch/ 3 The SULTAN project Transforming extractive-waste problem into a resource-recovery opportunity PhD students/ Universities and Work packages 15 “ESR” 8 research institutes 4 (WP) My role in WP4: On what? 1 2 . Environmental assessment Metals Minerals recovery valorization www.esd.ifu.ethz.ch/ 4 State of current research Prospective LCA Sustainability Empirical models for emerging benefits of mine Doka (2017, 2008) technologies waste's valorization Reactive transport Emissions from Steefel et al, 2015 tailings storage Parkhurst,Time 2013 perspective (Bakas et al 2015) Upscaling Industrial ecology (Doka and Hischier, 2005) frameworks in mining (Hellweg et al, 2005) Segura-Salazar et al, 2019 Piccino et al, 2016 Kinnunen, 2019 Zhou et al, 2017 LCA of mine LCA of tailings Process residues’ management simulation valorization Abadias et al, 2019 Assessing Song et al, 2017 Joyce et al, 2019 Reuter et al, 2015 Rahul et al, 2019 impacts of Adiansyah et al, 2016 Reid et al,Regionalized 2009 mining Sarkkinen et al, 2019 assessment Learning effects Future metal Northey et al, 2017 Gavankar et al, 2015 demand Werner et al, 2019 Caduff et al, 2012 Van der Voet et al, 2019 Elshkaki et al, 2016 www.esd.ifu.ethz.ch/ 5 Starting points and research gaps Assessing Sustainability benefits Emissions from Prospective LCA for impacts of of mine waste's tailings storage emerging technologies mining valorization Basis Frameworks for 1) Environmental Available upscaling and performance metrics leaching models Gaps simulations 2) Demand model Missing Lacking Ignoring tech- Limited Unclear No inventories applicability on dependent LCA phase scenario for tailings other sites aspects studies and scale coupling conversion www.esd.ifu.ethz.ch/ 6 Research questions 1. How can mine tailings storage’s emissions be modelled as a function of site-specific characteristics? How do pollutant emissions evolve over time? 2. How can various small-scale results be compared with larger scale systems from a life cycle assessment point of view? 3. What recommendations can be provided for process designers of tailings valorization technologies and policy makers? www.esd.ifu.ethz.ch/ 7 Methodology – Research parts Prediction Future emissions Parameterize Site-specific Conventional (time- and site- models tailings dependent) management Application Waste rocks Waste Spatial assessment to case Part 1 studies Scenarios: Part 3 Reprocessing Full LCA waste waste as alternatives (tailings) Processing Processing Part 2 Scale up, learning Scenario Lab-scale development scenarios Future analysis Metal Prospective LCA recovery and LCA valorization of Waste from sulfidic from sulfidic mining activities Waste Smelter Smelter tailings Hotspots Recommendations waste (slags) waste Feedback identification www.esd.ifu.ethz.ch/ 8 Part 1 – Conventional tailings management Prediction Future emissions Parameterize Site-specific Conventional (time- and site- models tailings dependent) management Application Waste rocks Waste Spatial assessment to case Part 1 studies Scenarios: Part 3 Reprocessing Full LCA waste waste as alternatives (tailings) Processing Processing Part 2 Scale up, learning Scenario Lab-scale development scenarios Future analysis Metal Prospective LCA recovery and LCA valorization of Waste from sulfidic from sulfidic mining activities Waste Smelter Smelter tailings Hotspots Recommendations waste (slags) waste Feedback identification www.esd.ifu.ethz.ch/ 9 Part 1 – Conventional tailings management Aim: Highlight potential hotspot regions and mines Ore deposits influence chosen beneficiation technology Site 2 KGHM Polska, Poland ~0.5 Mt/ year Route a Route b …Route n Sediment hosted deposit Total active SpecificGeneric tailings characteristics sites = ~400 (linked to other models) Site 1 Escondida, Chile ~1.2 Mt/ year Porphyry deposit Copper metal mining Emissions predictions Life cycle inventory improvement Influential beneficiation parameters : • Metal grade, mineralogy, reagent chemicals www.esd.ifu.ethz.ch/ 10 Part 1 – Conventional tailings management Data sources: 1) Market intelligence, 2) Actual operation Deposit Deposit Deposit Deposit Beneficiation model class 1 class 2 class 3 class n (This study) Tailings from various mines Resources and a) Ore grades, b) mine lifetime, c) types of disposal ~ volume of residues operational changes Hydrology and leaching models Time- and site-dependent emission from tailings storage Life cycle impact assessment www.esd.ifu.ethz.ch/ 11 Part 2 – Prospective LCA of emerging processes Prediction Future emissions Parameterize Site-specific Conventional (time- and site- models tailings dependent) management Application Waste rocks Waste Spatial assessment to case Part 1 studies Scenarios: Part 3 Reprocessing Full LCA waste waste as alternatives (tailings) Processing Processing Part 2 Scale up, learning Scenario Lab-scale development scenarios Future analysis Metal Prospective LCA recovery and LCA valorization of Waste from sulfidic from sulfidic mining activities Waste Smelter Smelter tailings Hotspots Recommendations waste (slags) waste Feedback identification www.esd.ifu.ethz.ch/ 12 Part 2 – Prospective LCA of emerging processes Aim: Identify hotspots at early stage Tailings Froth flotation Froth flotation • Inventory collection chemicals synthesis Ion flotation of 10 process chemicals synthesis modules Microwave High pressure Bio (This study) Ion flotation leaching leaching leaching • Design feedback based on LCA Recovered Effluent interpretation Inorganic polymer Ceramic Cement metals production production production (This study) Inorganic polymer Ceramic Cement www.esd.ifu.ethz.ch/ 13 Part 2 – Prospective LCA of emerging processes Energy Chemicals Functional unit Metals + valorized residues Residues Treatment of Process to landfill tailings feedstock modules in the project (1 ton) into main Metals + products products valorized for Credits Other emissions Lab scale stage residues (especially use- phase leaching) Industrial stage market substituted Incl. parameter uncertainties Useful frameworks (foreground inventories) Analysis Approach • Technology upscaling and learning • Contribution analysis • Process-oriented model, metallurgical simulation • Sensitivity www.esd.ifu.ethz.ch/ 14 Part 3 – Scenarios: Reprocessing of tailings as alternatives Prediction Future emissions Parameterize Site-specific Conventional (time- and site- models tailings dependent) management Application Waste rocks Waste Spatial assessment to case Part 1 studies Scenarios: Part 3 Reprocessing Full LCA waste waste as alternatives (tailings) Processing Processing Part 2 Scale up, learning Scenario Lab-scale development scenarios Future analysis Metal Prospective LCA recovery and LCA valorization of Waste from sulfidic from sulfidic mining activities Waste Smelter Smelter tailings Hotspots Recommendations waste (slags) waste Feedback identification www.esd.ifu.ethz.ch/ 15 Part 3 – Scenarios: Reprocessing of tailings as alternatives Aim: Environmental consequences of materials use Resource recovery from inactive stocks (i.e. tailings) Additional Environmental Impacts benefits . Metal recovery processes . Less ‘landfilling’ . Mineral residue . Avoid primary metal production valorization processes . Substitute of building materials Environmental implications of reprocessing tailings (This study) www.esd.ifu.ethz.ch/ 16 Part 3 – Scenarios: Reprocessing of tailings as alternatives Demand system Scrap Forward-looking analysis recycling Evaluation of: Material flow Scenarios: model Primary • Future environmental impacts metal A, B, C… demand of metal production Global-level o Primary route Reduced pressure on supply o Secondary routes (from tailings stocks) Scenario variables From tailings Scenarios and demand projection Adoption of emerging technologies (intergovernmental reports) (This study) www.esd.ifu.ethz.ch/ 17 Research parts as planned publications Prediction Future emissions Parameterize Site-specific Conventional Parameterized LCA(time of- and site- models tailings conventional tailingsdependent) ⦿ management Application Waste rocks Waste storage Spatial assessment to case Part 1 studies Scenarios:Environmental implications Scenario Reprocessingof tailings reprocessing as ⦿ Part 3 modelling waste waste as alternatives (tailings) alternatives Processing Processing Part 2 Scale up, learning Full LCA Lab-scale development scenarios Future modelling Metal Prospective LCA ofProspective novel LCA recovery and LCA ⦿ valorization of valorization processes Waste from sulfidic from sulfidic mining activities Waste Smelter Smelter tailings Hotspots Recommendations waste (slags) waste Feedback identification www.esd.ifu.ethz.ch/ 18 Relevance for science and economy ⦿ ⦿ ⦿ Parameterized LCA of Environmental implications Prospective LCA of novel conventional tailings of tailings reprocessing as valorization processes storage alternatives . Global environmental assessment . Structured