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Coupling simulation of mineral processing with Life Cycle Assessment

To assess the environmental impacts of copper production

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8th International Conference on Life Cycle ManagementLCM 2017, 3-6 Sept 2017, Luxembourghttp://lcm-conferences.org/

Speakers: Antoine Beylot (BRGM) Augustin Chanoine (Deloitte sustainability)

http://lcm-conferences.org/

Coupling simulation of mineral processing with LCA| Bodin et al. | BRGM and DELOITTE

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Focus of our presentation

Context and objectives of the studyIn Europe, most of the primary sources w/ high or moderate grades, reasonable accessibility and that are easy to process are exhausted. Primary resources: still available resources are polymetallic, lower-grade ores

Secondary resources: mining waste contains residual quantities of valuable metals

Focus on copper: need for alternative extraction processes of copper. Bio-hydrometallurgical technologies have the potential to: 1/ better adapt to lower-grade ores, 2/ extract metals in copper mining waste and 3/ lower the environmental impact of the mining industry

Objective of German-French EcoMetals project: to develop bioleaching, pretreatment and metal recovery techniques for copper extraction and demonstrate their efficiency, profitability and sustainability

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Pretreatment BioleachingMetal

RecoveryRun-of-Mine Concentrate

Pregnant Liquid

SolutionCopper Cathode

Aqueous phase (15% Cu + other

metals)

~1% Cu 13,7% Cu 25,7 g Cu/L 100% Cu

Copper precipitate

Recoverable metals (Ni, Co, Zn)

Solid waste: recoverable metals

(Lead, Silver)

Iron recovery


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Process chain environmental impacts

“Coupling” process simulation with LCA: concept

Building the model on a Case Study

Coherent material balance calculationModel calibration

Operational and experimental data

- Reconciliated mass balances- Intermediate exchanges- Elementary flows

LCA + LCC

Life Cycle Inventory modellingEnvironmental impact and economic assessment

Scenarios Modelling

Modification of input parameters

Redesigning the process

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Scope of the study

Case study: exploitation of a Kupferschiefer copper ore at Lubin mine (Poland)

Lithotypes and chemical composition• Carbonates: 17,6 wt% in share, with 1,50% Cu• Shale: 13,2 wt% in share, with 2,78% Cu• Sandstone: 69,2% wt% in share, with 0,91% Cu

Functional Unit• To produce 1 ton of Cu in 13,7% Cu concentrate

System boundary• From Run-of-Mine (RoM) ore to copper concentrate

Life Cycle Inventory dabatase• ecoinvent 3.3

Environmental impact categories• Selection of a restricted list of 6 mid-point impact categories assessed with recognized

characterization methods: UseTox 2 for toxicity indicators + latest PEF recommendations for other impact categories

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Model construction: Mass Balances

Initial raw data on mass balances• On-site operational data completed

with hypotheses

• Global mass flows and substance flows (Cu, Corg and Cinorg)

• Inconsistent mass balances:

Mass in ≠ Mass out

Reconciliation of mass balances • i.e. finding estimators which are:- Consistent with mass balance constraints- Close to initial values, as a function of the data accuracy

• Lowering the uncertainty of global mass balances by benefiting from the higher accuracy on substance flows

Water

Tailings

W1 –Classification &

Grinding

W0 – ROM crushing & screening

W3 – Shale/ Carbonate

Beneficiation

Concentrate thickener

Tailings thickener

W2 –Sandstone

BeneficiationConcentrate

Recycled water

RoM

Recycled water

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Model construction: Implementing standard models

Energy consumption• Bond Formula, as a function of:

Crushability of lithotypes

Particle size distribution

Steel and reagents consumption• Steel as a function of abrasion indices of lithotypes

Data from UVR (German partner in Ecometals project)

Air emissions• Dust and CS2 emission factors drawn from the literature

Descriptive models

≠ Predictive

models

Lithology Shale Carbonate Sandstone

Work Index (kWh/t) 16,2 7,6 20,2

Abrasion Index (kg/kWh)

0,02 0,32 0,6

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Case study: Inventory of inputs and outputs

W1 – Ball Mill 1

Solid flow: 1285 t/hrd80 ≈ 1500 microns1,12 wt% of Cu

Electricity: 7,69 kWh/t ore

Steel: 1,09 kg/t ore

Solid flow: 1285 t/hrd80 ≈ 300 microns1,12 wt% of Cu

Tailings

W1 –Classification &

Grinding

W0 – ROM crushing & screening

W3 – Shale/ Carbonate

Beneficiation

Concentrate thickener

Tailings thickener

W2 –Sandstone

BeneficiationConcentrate

Recycled water

RoM

W1 – Classification & Grinding

W1 – Rod Mills

W1 – Ball Mill 1

W1 – Ball Mill 2

Water

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0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

CC - Climate change

PM - Particulate matter

RD - Resource depletion

WU - Water use

FE wLT - Freshwater ecotoxicity with long term

FE woLT - Freshwater ecotoxicity without long term

Impact Assessment for 1 ton of Cu in 13,7% Cu concentrate - Base Scenario

W0 - ROM crushing and screening W1 - Classification and grinding W2 - Sandstone benefication

W3 - Shale/Carbonate benefication W4 - Tailings thickeners W5 - Concentrate thickener

Case study: impact calculation

Direct emissions from tailings account for a

dominant part in freshwater ecotoxicity

on the long term

Resource depletion

here is exclusively

copper intake

Heavy contribution of W1, especially

electricity consumption


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0

0,5

1

1,5

2

2,5

1995 2000 2005 2010 2015 2020

Cu

co

nte

nt

(wt%

)

Evolution of the Cu content in Lubin ore

Historical ore productiondata (1998-2011)

Mine Five Year ProductionPlan (2012-2016)

Worst case scenario

Scenario modelling

Historical trend

Scenario:Cu = 0.85wt%

Case study:Cu = 0.94wt%

Figures from MICON TECHNICAL REPORT ON THE COPPER-SILVER PRODUCTION OPERATIONS OF KGHM POLSKA MIEDŹ S.A. IN THE LEGNICA-GLOGÓW COPPER BELT AREA OF SOUTHWESTERN POLAND (Feb. 2013)

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0% 20% 40% 60% 80% 100% 120%

BS - 1 ton of Cu in 13,7% Cu Concentrate

WCS - 1 ton of Cu in 12,6% Cu concentrate









CC

PM

WU

FE w

LTFE

wo

LT

Impact Assessment - 1 ton of Cu in concentrate - Base Scenario (BS) and Worst Case Scenario (WCS)

W0 - ROM crushing and screening W1 - Classification and grinding W2 - Sandstone benefication

W3 - Shale/Carbonate benefication W4 - Tailings thickeners W5 - Concentrate thickener

Scenario: impact calculation

+13%

+12%

+12%

+11%

+10%

A RoM initially 9% poorer in copper requires >13% more energy to produce the same amount of copper concentrate. It also generates more emissions to air and more waste.

Most impacts rise by 10 to 13%.


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Conclusions and outlook

Elaboration of a joint process and environmental simulation applied to the mineral industry:• Provides gains in robustness and time spent for mass balance’s

calculations• Direct link between process performance and environmental impacts• Highlights key unit operations to be improved/optimized on both

technical and environmental viewpoints

Applicability proven using “descriptive” process models in a prospective case study

Complementarity / coupling to be improved by:• Implementing a “hard” software connection between process simulation

software and LCA software• Using “predictive” process models in relation with equipment sizing and

upscaling data

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THANK YOU FOR YOUR ATTENTION!ANY QUESTIONS?

www. .de

Study team (WP5 contribution):

BRGM: J. Bodin, J. Villeneuve, A. Beylot, K. Bru, F. BodénanDeloitte: A. Chanoine, P.A. Duvernois, C. Tromson, J. Bitar

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ECOMETALS Partners

Project Coordination

Project Partners

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