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ADVANCES IN MINE TAILINGS AND WATER
MANAGEMENT IN THE MINING INDUSTRY
FOR A CIRCULAR ECONOMY
Natalia Andrea Araya Gómez
Thesis presented in accordance to the requirements to obtain the degree of Ph.D. in
Mineral Process Engineering
Supervisors
Luis Cisternas Ph.D. - Andrzej Kraslawski Ph.D.
Laboratory of Optimization and Modelling
Department of Chemical and Mineral Process Engineering Universidad de Antofagasta
Antofagasta, Chile
2020
AVANCES EN EL MANEJO DE RELAVES Y DE
AGUA EN LA INDUSTRIA MINERA PARA UNA
ECONOMÍA CIRCULAR
Natalia Andrea Araya Gómez
Tesis para optar al grado de Doctor en Ciencias de la Ingeniería de Procesos de
Minerales
Profesor Patrocinante Luis Cisternas Ph.D.
Profesor copatrocinante
Andrzej Kraslawski Ph.D.
Laboratorio de Optimización y Modelamiento Departamento de Ingeniería Química y Procesos de Minerales
Universidad de Antofagasta Antofagasta, Chile
2020
Supervisors
Professor Luis Cisternas Arapio Departamento de Ingeniería Química y Procesamiento de Minerales Universidad de Antofagasta Chile
Professor Andrzej Kraslawski
Industrial Engineering and Management
LUT School of Engineering Science
Lappeenranta-Lahti University of Technology
Finland
1
Abstract
Natalia Araya Gómez
The mining industry consumes vast quantities of water and energy to produce a metal
or mineral product from mineral resources on the earth’s crust, leaving an enormous
amount of mining waste.
The linear thinking of the economy needs to be replaced with the circular economy to
achieve sustainable development goals. In this context, the mining industry needs to
improve in several aspects, such as reducing primary resource consumption and
improve the efficiency of its processes. Strategies to reduce water and energy
consumption, recycle water and wastes, and to recover energy are needed.
The objective of this thesis is to develop methodologies to advance towards the
circular economy in mining, with a focus on mine tailings and water management.
The strategies and tools proposed are meant to be applied in mining processes to
mitigate environmental impacts.
The strategies proposed in water management include an integrated water
distribution network to supply water to several mine plants while recovering energy
using energy recovery devices. The method used is mathematical optimization to
design the water distribution network. The methodology is validated with a case
study that corresponds to an area of the Antofagasta Region. Results show that the
optimal solution is an integrated system with energy recovery devices in areas with a
complex topography where energy production is feasible.
Reducing waste is a key component of the circular economy. Mine tailings are the
main waste produced by the mining industries. Re-processing of mine tailings to
obtain critical materials is proposed, the methodology is an economic assessment
validated with a case study of tailing deposits of the Antofagasta Region. The
economic evaluation considers the discounted cash flow method, sensitivity analysis,
and real options analysis. Results show that an investment based on re-processing
mine tailings to obtain critical materials is feasible in some cases.
The contribution of this thesis is a collection of methodologies to improve mine
tailings and water management to improve mining processes. About mine tailings
management, the strategy proposed is re-processing mine tailings, which will reduce
the amount of waste produced by mining plants and will reduce the need for mining
primary ores. In the case of water management, the mining industry needs to reduce
the demand for freshwater. To supply seawater is still an expensive option but having
an integrated water distribution network with energy recovery devices will reduce
the total cost of the network.
2
Keywords: Water Distribution Networks, water management, mine tailings, mining,
circular economy, critical materials, resource valorization, economic assessment
Resumen La industria minera consume grandes cantidades de agua y energía para producir un
producto metálico o mineral a partir de recursos minerales en la corteza terrestre,
dejando una enorme cantidad de desechos mineros.
El pensamiento lineal de la economía necesita ser reemplazado por la economía
circular para lograr los objetivos de desarrollo sostenible. En este contexto, la industria
minera necesita mejorar en varios aspectos, como reducir el consumo de recursos
primarios y mejorar la eficiencia de sus procesos. Se necesitan estrategias para reducir
el consumo de agua y energía, reciclar agua y desechos, y recuperar energía.
El objetivo de esta tesis es desarrollar metodologías para avanzar hacia la economía
circular en la minería, con un enfoque en los relaves mineros y la gestión del agua. Las
estrategias y herramientas propuestas están destinadas a aplicarse en los procesos
mineros para mitigar los impactos ambientales de estos.
Las estrategias propuestas en la gestión del agua incluyen una red integrada de
distribución de agua para proveer de agua a varias plantas mineras mientras se
recupera energía utilizando dispositivos de recuperación de energía. El método
utilizado es la optimización matemática para diseñar la red de distribución de agua.
La metodología fue validada con un caso de estudio que corresponde a un área de la
Región de Antofagasta. Los resultados muestran que la solución óptima es un sistema
integrado con dispositivos de recuperación de energía en áreas con una topografía
compleja donde la producción de energía es factible.
Reducir la cantidad de residuos es un componente clave de la economía circular. Los
relaves mineros son los principales desechos producidos por las industrias mineras.
Se propone el reprocesamiento de relaves mineros para obtener materiales críticos, la
metodología consiste en una evaluación económica validada con un caso de estudio
de relaves mineros de la Región de Antofagasta. La evaluación económica considera
el método de descuentos de flujos, el análisis de sensibilidad y el análisis de opciones
reales. Los resultados muestran que en algunos casos es factible una inversión basada
en el reprocesamiento de relaves de minas para obtener materiales críticos.
La contribución de esta tesis es una colección de metodologías para mejorar la gestión
de los relaves mineros y la gestión del agua en los procesos mineros. Acerca de la
gestión de relaves mineros, la estrategia propuesta es reprocesar los relaves mineros,
lo que reducirá la cantidad de relaves producidos por las plantas mineras y reducirá
la necesidad de extraer minerales primarios. En el caso de la gestión del agua, la
industria minera necesita reducir la demanda de agua dulce. Suministrar agua de mar
sigue siendo una opción costosa, pero tener una red integrada de distribución de agua
con dispositivos de recuperación de energía reducirá el costo total de la red.
3
Acknowledgment I would like to express my deepest appreciation to Professor Luis Cisternas for being
my supervisor and for encouraging me to pursue a double degree with LUT
University. I must also thank the project Anillo Agua de Mar Atacama ACT 1201 -
ANID in which I started my thesis research. I’m also grateful of the collaboration
developed in the project Anillo Grant ACM 170005 - ANID.
I would also like to extend my deepest gratitude to Professor Teófilo Graber as head
of the Ph.D. program in Mineral Process Engineering and to all members of Ph.D. in
the Mineral Process Engineering program for all the support during the duration of
my Ph.D. studies.
I would also like to express my deepest gratitude to Professor Andrzej Kraslawski, my
supervisor at LUT University, for support during the realization of the double degree
for my Ph.D. studies.
I would also like to extend my gratitude to Professor Edelmira Gálvez for her support
and collaboration in my firsts two years of my Ph.D. studies in project Anillo Agua de
Mar Atacama ACT 1201-ANID.
I am also grateful to Freddy Lucay for support and collaboration in my research while
being in the Project Anillo Agua de Mar Atacama, resulting in two publications.
I am extremely grateful to ANID for the grant (2017, No. 21170815) for pursuing
doctoral studies.
I am also grateful to Ella and Georg Ehrnrooth Foundation for a grant to continue my
doctoral studies in LUT University.
4
List of publications
Publication I
Araya, N., Lucay, F. A, Cisternas, L. A., Gálvez, E. D. (2018). Design of desalinated
Water Distribution Networks: Complex Topography, Energy Production, and Parallel
Pipelines. Industrial and Engineering Chemistry Research, 57, 9879-9888. DOI:
10.1021/acs.iecr.7b05247.
Publication II
Araya, N., Kralawski, A., Cisternas, L. A. (2019). Towards mine tailings valorization:
Recovery of critical materials from Chilean mine tailings. Journal of Cleaner
Production, 263, 121555. DOI: 10.1016/j.jclepro.2020.121555
Publication III (submitted)
Araya, N., Rámirez, Y., Kraslawski, A., Cisternas, L. A. (2019) Real options valuation
of processing mine tailings to obtain critical materials. Sustainable Development
(submitted).
Book Chapters
Araya, N., Cisternas, L. A., Lucay, F. A., Gálvez, E. D. (2017). Design of desalinated
water distribution networks including energy recovery devices. In Computer Aided
Chemical Engineering Vol. 40, pp. 925-930. Elsevier.
Herrera, S., Araya, N., Cisternas, L., Gálvez, E. (2016) Diseño de plantas
desalinizadoras y redes de distribución de agua: una mirada holística. “Agua de Mar
Atacama: Oportunidades y avances para el uso sostenible del agua de mar en
minería”. Capítulo 3. RIL Editores. ISBN: 978-956-01-0388-8.
5
Preface
This thesis titled Advances in mine tailings and water management for a circular
economy presents the work performed during the Ph.D. studies started in April 2015
and finished in June 2020. This Ph.D. thesis was developed under a joint supervision
agreement between Universidad de Antofagasta in Chile and LUT University in
Finland.
This document is arranged in two sections. The first section contains the thesis
overview divided into six chapters. The first chapter is the introduction and provides
a context about the background of the study and the motivation and scope of this
thesis. The second chapter, theoretical background, gives an overview of the literature
context. The third chapter contains the research methodology and methods developed
during the study. The fourth chapter contains a review of the results and publications
obtained during the duration of the Ph.D. studies. The fifth chapter is Conclusion, and
it summarizes the theoretical contribution of this Ph.D. thesis, it also provides the
limitation found and future suggestions. Chapter six contains the references. The
second section includes the articles published during the Ph.D. study. The first article,
“Design of desalinated water distribution networks: Complex topography, energy
production, and parallel pipelines” was published in the Journal Industrial and
Engineering Chemistry Research. The second article titled “Towards mine tailings
valorization: Recovery of critical materials from Chilean mine tailings” was published
in the Journal of Cleaner Production. The third article, currently submitted in
Sustainable Development, is titled “Feasibility of re-processing mine tailings to obtain
critical materials using real options analysis.”
6
Prefacio
La tesis titulada Advances in mine tailings and water management for a circular
economy presenta el trabajo realizado durante los estudios de doctorado que
comenzaron en abril de 2015 y terminaron en junio 2020. Los estudios de doctorado
fueron realizados bajo un convenio de doble graduación entre la Universidad de
Antofagasta en Chile y LUT University en Finlandia.
Este documento está dividido en dos secciones. La primera sección contiene una
visión general dividida en seis capítulos. El primer capítulo es la introducción, la que
provee un contexto sobre los antecedentes del estudio, la motivación y objetivos de la
tesis. El segundo capítulo, antecedentes generales, proporciona una visión sobre el
contexto de la literatura. El tercer capítulo contiene la metodología de investigación y
los métodos desarrollados durante los estudios de doctorado. El cuarto capítulo
contiene la revisión de los resultados y las publicaciones realizadas durante los
estudios de doctorado. El quinto capítulo, las conclusiones, resume las contribuciones
teóricas de la tesis de doctorado, también proporciona las limitaciones y sugerencias
para investigaciones futuras. El sexto capítulo contiene las referencias. La segunda
sección contiene los artículos publicados durante los estudios de doctorado. El primer
artículo “Design of desalinated water distribution networks: Complex topography,
energy production, and parallel pipelines” fue publicado en la revista Journal
Industrial and Engineering Chemistry Research. El Segundo artículo titulado
“Towards mine tailings valorization: Recovery of critical materials from Chilean mine
tailings” fue publicado en la revista Journal of Cleaner Production. El tercer artículo,
fue enviado a la revista Sustainable Development tiene como título “Feasibility of re-
processing mine tailings to obtain critical materials using real options analysis”.
7
Contents
Abstract..................................................................................................................................... 1
Resumen ................................................................................................................................... 2
Acknowledgment .................................................................................................................... 3
List of publications .............................................................................................................. 4
Book Chapters ..................................................................................................................... 4
Preface ....................................................................................................................................... 5
Prefacio ..................................................................................................................................... 6
SECTION I: DISSERTATION OVERVIEW ......................................................................... 9
1. Introduction ................................................................................................................... 10
1.1. Background .......................................................................................................... 10
1.2. Motivation and Scope ........................................................................................ 11
2. Theoretical Background ............................................................................................... 14
2.1. Circular economy and sustainability in mining ............................................. 14
2.2. Water supply for mining ................................................................................... 15
2.3. Mine tailings ........................................................................................................ 16
3. Research Methodology ................................................................................................. 18
3.1. Water Distribution Network (WDN) design for areas with complex
topography considering the energy recovery devices ................................................. 18
3.1.1. Optimization of Water Distribution Networks (WDN) ............................ 18
3.1.2. Problem Statement .......................................................................................... 18
3.1.3. Mathematical Formulation ............................................................................ 19
3.2. An economic evaluation of re-processing of mine tailings to obtain critical
materials ............................................................................................................................. 19
3.2.1. Project valuation Tools ................................................................................... 19
3.2.2. Discounted Cash Flow (DCF) ........................................................................ 20
3.2.3. Real Options Analysis (ROA) ........................................................................ 20
3.2.4. Sensitivity Analysis......................................................................................... 21
4. Publications and Results Reviews .............................................................................. 22
4.1. Publication I: Design of desalinated water distribution networks: Complex
topography, energy production, and parallel pipelines ............................................. 22
4.1.1. Research Objective .............................................................................................. 22
4.1.2. Contributions ....................................................................................................... 22
8
4.2. Publication II: Towards mine tailings valorization: Recovery of critical materials
from Chilean mine tailings .............................................................................................. 23
4.2.1. Research Objective .............................................................................................. 23
4.2.2. Contributions ....................................................................................................... 23
4.3. Publication III: Feasibility of re-processing mine tailings to obtain critical
materials using real options analysis (submitted in Science of The Total
Environment) ..................................................................................................................... 23
4.3.1. Research objective ............................................................................................... 23
4.3.2. Contributions ....................................................................................................... 24
5. Conclusions .................................................................................................................... 25
5.1. Theoretical Contribution of the Study ............................................................. 27
5.2. Limitation and Future Research Suggestions ................................................. 27
References .............................................................................................................................. 29
SECTION II: PUBLICATIONS ............................................................................................ 35
9
SECTION I: DISSERTATION OVERVIEW
10
1. Introduction 1.1. Background
Mining is water and energy-intensive activity, an industry that is needed to ensure the
wellbeing of modern society, moreover mining is present in civilization since ancient
times. Mining activities are usually located in remote and arid areas where water
resources are scarce (Cisternas and Gálvez, 2018; Herrera-León et al., 2019; Ramírez et
al., 2019).
Environmental and social awareness in the last decades around the use of resources
has increased. Nowadays, terms like “circular economy” and “sustainability” resonate
in different fields, mining is no exception (Adibi et al., 2015; Caron et al., 2016; Dong
et al., 2019; Gorman and Dzombak, 2018; Lottermoser, 2011; Reyes-Bozo et al., 2014).
A circular economy is an economy that is restorative and regenerative by design, using
principles of reusing, recovery, recycling, it is about looking beyond the take-make-
waste extractive industrial model (Kirchherr et al., 2017). The concept of circular
economy recognizes the need to work on all scales, while sustainability focuses on
three pillars: economic, environmental, and social, to meet the demands of the present,
ensuring the ability of future generations to also meet their needs.
In Chile, there are numerous mineral processing plants, since Chile is the world´s first
producer of copper. Other metallic elements extracted in Chile are silver,
molybdenum, and gold. As well as for non-metallic elements as boron, iodine, lithium
carbonate, among others (SERNAGEOMIN, 2019). Most of the mining facilities in
Chile are located in the Atacama Desert in Northern Chile, as it features plenty of
minerals. Mining is the principal activity in this area. Usually, plants are located away
from the seashore, so in case of using desalinated water, piping water through long
distances is a must (Herrera-León et al., 2019). Seawater use in mining has been
growing since mines need to reduce the amount of raw water intake from
groundwater and freshwater sources since these are limited and scarce (Cisternas and
Gálvez, 2018). The methodologies developed in this thesis are applied to study cases
based on the mining industry in Northern Chile, specifically the copper mining
activities develop in the Antofagasta Region.
Reducing water consumption and increasing energy efficiency are two essential
requirements to have a more sustainable mining industry. A typical base-metal mine
site consists of an underground or open-pit mine and a mineral processing plant or
mill (Gunson et al., 2010). Most mills use wet processes such as froth flotation to
separate valuable minerals from the non-valuable minerals in the ore. Wet processes
require less energy, but they can use large quantities of water (Gunson et al., 2010).
Currently, each plant has built its desalination plant and water distribution system.
Since mining plants are located far away from the seashore, a way of reducing the
energy used for pumping desalinated water through different mine sites is to have an
integrated water supply system, where industrial symbiosis can be achieved between
desalination companies and mining plants (Cisternas and Gálvez, 2018; Herrera-León
11
et al., 2019; Ihle and Kracht, 2018). Energy can be saved by using an integrated water
supply system, efficiency can be achieved by using fewer pipelines and pump stations
if energy recovery systems are placed in the pipelines, energy can be produced and
used in the network (Corcoran et al., 2016; McNabola et al., 2014; Nogueira-Vilanova
and Perrella-Balestieri, 2014a, 2014b; Zakkour et al., 2002).
Another issue in mining is mine tailings, which are the waste produced in mining
processing plants. They are a mixture of fined solid materials remaining after the
recoverable metals and minerals have been extracted from mined ore, together with
water, which includes also dissolved metals and ore processing reagents (Edraki et al.,
2014). Mine tailings can account for 95-99% of the crushed and ground ores (Edraki et
al., 2014).
Environmental impacts and land use aspects should be considered when choosing a
tailing disposal method (Adiansyah et al., 2017). Environmental impacts of tailings
dam failures include human fatalities, contamination of water, and soil (Kossoff et al.,
2014). One of the most severe environmental problems associated with mine tailings
is acid mine drainage, which is produced when sulfide minerals are exposed to
oxygen and water (Akcil and Koldas, 2006). Acid mine drainage is one of the most
significant forms of water pollution (Moodley et al., 2017). Mine tailings management
is crucial in mining operations because of the irreversible impacts of tailings
(Adiansyah et al., 2015).
Mine tailings contain several elements that are not separated from the mineral in the
processing plant. Mine tailings could be reprocessed to obtain valuable elements
contained in them (Binnemans et al., 2015; Falagán et al., 2017). The valorization of
mine tailings is still at its infancy, globally speaking (Kinnunen and Kaksonen, 2019).
Critical materials are a group of materials that are considered of large economic
importance and have high risk in their supply. Now, secondary sources like metal
scrap and mine tailings have a promising future as critical materials sources. Using
secondary sources to recover critical materials has multiple benefits: it allows to
reduce primary ore extraction, decrease the amount of waste, hence decreasing its
environmental impact, give value to waste, contributes to industrial symbiosis, among
others.
1.2. Motivation and Scope
A requirement to achieve sustainable development is to reduce primary resource
consumption, consequently mining activities on primary sources. However, the
demand for metals will continue to exist throughout the transition to a more
sustainable society. Therefore, research must be conducted to explore the role of the
mining industry in the circular economy paradigm and identify strategies for it to
transitioning to a more sustainable mining industry.
In mining, circular economy advocates for reducing primary resource extraction by
replacing it with secondary sources, reducing raw water intake by reusing or recycling
12
water, reducing energy dependency, reducing the environmental footprint, reducing
greenhouse gas emissions (Lèbre et al., 2017).
Effective water management in the mining industry can reduce the dependence on
freshwater sources that are scarce in arid regions where most of the mining facilities
are located. In 2018, in Chile freshwater consumption reached 13.36 m3/s, more than
three times seawater consumption, which reached 3.99 m3/s (COCHILCO, 2019a).
Integrated water supply systems between desalination plants and several industries
reduce energy consumption (Herrera-León et al., 2019) and the stress on freshwater
resources. Different strategies can be applied to reduce water consumption and
optimize its use.
Mine tailings are a critical issue in mining as tailings are the waste of processing plants
and are produced in large quantities. In Chile, to March of 2018, 740 tailing deposits
are registered in a national cadaster, being the majority located in the north of the
country. Currently, 101 tailing deposits are in active use, which will accumulate 14,470
million cubic meters, of the 16,000 million cubic meters of the total of tailings stored
in the country, ergo 90.6% of stored tailings come from active mining operations
(SERNAGEOMIN, 2018).
Strategies to save water, recover energy, and reducing waste are needed to make the
mining industry more sustainable and to help to achieve the circular economy. The
motivation of this thesis is to elaborate research to contribute to the literature on water
and tailings management in the mining industry by providing methodologies and
tools that mitigate the environmental impact of mining activities.
This thesis aims to propose strategies to manage water and tailings in the mining
industry. Optimized water distribution networks and efficient water use in tailing
management are proposed as water management strategies. Recovery of critical
materials and reducing water content in tailings are the tailings management
strategies proposed as well. The aim is attained by fulfilling the following specific
objectives and the related research questions:
1. To design integrated water supply systems that include energy recovery
devices in areas with complex topography
RQ 1.1. Is an integrated water supply system that includes energy recovery devices a
feasible option in areas with complex topography?
RQ 1.2. Is it economically and technically feasible to use energy recovery devices in the
water supply system?
RQ 1.3. When using parallel pipes is a feasible option in the water supply system?
2. To investigate the feasibility of re-processing mine tailings to obtain critical
materials
RQ 2.1. What critical materials can be recovered from mine tailings?
13
RQ 2.2. What are the challenges in the production of critical materials using mine tailings
as a source?
RQ 2.3. Is it economically feasible to invest in a project developed around the idea of re-
processing mine tailings to obtain critical materials?
3. To develop a methodology to assess the feasibility of re-processing mine
tailings to obtain critical materials
RQ 3.1. How can real options improve the decision to invest in a project using mine tailings
as a source of critical materials?
RQ 3.2. How can the net present values variables influence real options performance?
14
2. Theoretical Background Building on the literature review, this section explains the main concepts used in the
thesis and the current situation of the mining industry encompassing the concepts and
definitions used in this thesis.
The demand for copper expected to increase and to exceed copper mineral resources
by mid-century. The increase in copper demand will be associated with a strong
increase in the energy demand and, consequently, the environmental impacts
(Elshkaki et al., 2016). Environmental impacts associated with mining are stress and
pollution of water resources, air pollution, land usage, and production of several
waste streams.
In Chile, mining is a long-standing industry, since the country owns vast mineral
resources. Most of the mining activity is located in the Atacama Desert, northern Chile,
where sulfides ores containing copper are abundant; additionally, non-metallic
resources are also found in the area. Therefore, Chile produces various elements, such
as copper, silver, molybdenum, lithium, boron, among others (SERNAGEOMIN,
2019). Mining represents 10% of the national Gross Domestic Product (Reporte
Minero, 2018). To achieve sustainable mining, the Chilean state must balance
economic growth with the strictness of environmental policies by continuing to
address the challenge of energy use, water scarcity, indigenous rights, and
governmental organization (Ghorbani and Kuan, 2017).
2.1. Circular economy and sustainability in mining
The circular economy is a concept that resonates lately, which describes an economic
system that is based on business models that replaces the linear economy thinking,
with reducing, alternatively reusing, recycling, and recovering materials in
production/distributions and consumption processes, thus operating at all levels, to
accomplish sustainable development, which implies creating environmental quality,
economic prosperity and social equity, to the benefit of current and future generations
(Kirchherr et al., 2017).
Mining is a global industry, and it is often located in remote, ecologically sensitive,
and less-developed areas that include indigenous land and territories. If managed
poorly, mining can lead to environmental degradations, displaced populations,
inequality, and increased conflict, among other challenges (World Economic Forum,
2016). In the report “Mapping Mining to the Sustainable Development Goals: An
Atlas, 17 Sustainable Development Goals (SDGs) are presented. This report presents
an overview of the opportunities and challenges that the mining industry needs to
address, from exploration through production and finally mine closure. SDG6 is about
water in mining, the goal includes reduce water consumption, use alternatives water
sources as seawater and greywater, integrate technical, social, economic, and political
water concerns and identify high-value water areas. About waste, SDG 12 is about
mining and responsible consumption, the mining industry should aim to minimize
the production of waste and give value to waste (World Economic Forum, 2016).
15
2.2. Water supply for mining
Mining consumes large quantities of water; in Chile, water consumption in mining
was 62.7 m3/s in 2018, where 72% correspond to recirculated water, 22% to freshwater
from inland sources, and 6% to seawater (COCHILCO, 2019a). However, mine water
use accounts for a small portion of overall use (Gunson et al., 2012). Nevertheless,
when mining sites are located in areas where water is a scarce resource, then mine
water consumption can have a significant impact on local water resources (Northey et
al., 2016). There is clear overexploitation of water resources in northern Chile, water
resources are insufficient to meet environmental, domestic, and industrial
requirements (Aitken et al., 2016).
Most mineral processing plants use wet processes, such as flotation, which typically
takes place at 25-30% solids by mass (Gunson et al., 2012). Water and energy are
interconnected as water needs energy to be treated and transported until the
processing plant. The mining industry consumes vast quantities of energy. In Chile,
copper mining consumed 176,745 TJ in 2018, which represents 14% of overall energy
consumption in the country (COCHILCO, 2019b). As freshwater sources are getting
scarce, water from other sources is needed. Recycled water from the processes and
desalinated water are options to fulfill the water requirements in the processing plant.
Seawater requires energy to be desalinated and transported until the mining site
(Cisternas and Gálvez, 2018).
Nowadays, freshwater sources are scarce, hence other water sources are needed to
fulfill the demand for water that the mining industry requires. The advances in
desalination technologies, reduction of membrane cost, and lower energy
consumption have made seawater a viable source of freshwater for mining (Knops et
al., 2013). Reverse osmosis (RO) is the desalination process most utilized worldwide
due to its simplicity and lower energy consumption in comparison to distillation-
based thermal processes (Shenvi et al., 2015).
2.2.1. Optimization of water supply systems
The water supply system consists of the water treatment plant, pipeline, and pump
station to supply water to an industrial site or urban community. Methodologies to
design water supply systems usually result in mixed-integer non-linear problems
(MINLP) models (Araya et al., 2018). The water supply system is transformed into a
network to be analyzed, and this is called Water Distribution Network (WDN).
Optimization of WDN has been done by several authors with different approaches
(Ahmetović and Grossmann, 2011; Atilhan et al., 2011; El‐Halwagi, 1992; Herrera-
León et al., 2019; Lira-Barragán et al., 2016; Liu et al., 2011). An integrated water supply
system has demonstrated to be more efficient economically and technically than
having an independent water supply to each mining processing plant (Herrera-León
et al., 2019).
16
The reliability of WDN can be improved by adding a parallel pipeline (Gupta et al.,
2014). Parallel pipelines are arranged to divide flow, keeping the head loss at the same
rate, meaning that head loss in all parallel pipes remains the same (Swamee, 2001).
2.2.2. Energy production in water supply systems
The use of pumps as turbines (PATS) could be an option to produce energy in the
network that can be used to reduce the dependency of external sources of energy.
PATs have been used in WDN instead of pressure reducing valves to reduce pressure.
Additionally, PATs can produce electricity the same way turbines are used in
hydropower generation (Corcoran et al., 2016; De Marchis et al., 2014; McNabola et
al., 2014; Tricarico et al., 2014; Zakkour et al., 2002). The energy efficiency of water
supply systems can be increased through the recovery of hydraulic energy implicit in
the volumes of water transported through the supply system (Nogueira-Vilanova and
Perrella-Balestieri, 2014b).
2.3. Mine tailings
A critical issue in mining is the waste streams that are discarded from the processing
plants, being mine tailings, the main waste produced in mineral processing plants,
obtained after using wet processes, such as flotation. Mine tailings consist in a
combination of fine-grained solid materials remaining after the recoverable metals
and minerals have been extracted from mined ore, together with the water used in the
recovery process (Industry.gov.au, 2016), which includes dissolved metals and ore
processing reagents (Edraki et al., 2014). Mine tailings can account for 95-99% of the
crushed and ground ores (Edraki et al., 2014).
2.3.1. Environmental impacts of mine tailings
Environmental implications of tailings dam failures include human fatalities,
contamination of water, and soil (Kossoff et al., 2014). One of the most severe
environmental problems associated with mine tailings is acid mine drainage, which is
produced when sulfide minerals are exposed to oxygen and water (Akcil and Koldas,
2006). Acid mine drainage is one of the most significant forms of water pollution
(Moodley et al., 2017). Mine tailings management is a crucial issue in mining
operations because of the irreversible impacts of tailings (Adiansyah et al., 2015).
2.3.2. Water reclamation in mine tailings
There are a variety of ways to stored mine tailings. Conventional tailing disposal
consists of transport tailings as a slurry to an impoundment or dam. Large volumes
are required to be transported with the tailings to a storage facility (Edraki et al., 2014).
Tailings in conventional residues disposal have approximately 60% water content.
Dewatering technologies, such as thickeners and filters, can reduce water content in
tailings until 20% of water (Gunson et al., 2012). Water-energy nexus in mine tailings
is associated with the pumping system and the technology used in processing the
tailings (Adiansyah et al., 2016). Environmental impacts and land use aspects should
be considered when choosing a tailing disposal method (Adiansyah et al., 2017).
17
2.3.3. Re-processing of mine tailings
Re-processing of tailings with the objective of extract valuable elements is a novel
approach of mine tailing management. Studies about geochemical content of mine
tailings have been done with samples of tailings storage facilities to analyze the
content of valuable elements such as critical materials (Ceniceros-Gómez et al., 2018;
Markovaara-Koivisto et al., 2018; Moran-Palacios et al., 2019; Tunsu et al., 2019). The
next step seems to be the re-processing of secondary sources to obtain elements of
interest. However, the environmental implications are still unknown, as re-processing
tailing with such purpose is still not at an industrial level. Further analysis of Reuse
opportunities of mine tailings is needed in the ongoing discussion of sustainable
tailings management (Adiansyah et al., 2017).
Critical raw materials (CRMs) are those raw materials that are highly important to the
European economy and but have high risk associated with their supply (European
Commission, 2017). The most recent list of CRMs includes 27 raw materials, which
consists of three groups elements: heavy rare earth elements (HREEs), light rare earth
elements (LREEs), and PGMs (platinum group metals). As the supply of these
materials is of high risk, the diversification of their sources is needed. Secondary
sources like recycling from landfills and industrials waste as mine tailings appear as
options for obtaining CRMs.
Re-mining wastes and re-processing tailings are possible connections between the
primary resource sector and the waste management sector, which would close a loop
in the circular economy (Lèbre et al., 2017).
The potential use of secondary sources, like landfills and mine tailings facilities, faces
several challenges. The environmental impacts will vary according to the
characteristics of the minerals and rocks and techniques used. There is a need for
statistics about waste facilities with official data about volumes and composition of
waste sites (Careddu et al., 2018). The valorization of mine tailings is still at its infancy.
To valorize mine tailings, the mining industry needs to advance in filling the
knowledge gaps of mine tailings management. The situation is expected to improve
as the mining industry needs to shift from a linear economy to a circular economy
(Kinnunen and Kaksonen, 2019).
18
3. Research Methodology After having collected knowledge from literature, methodologies were designed to
examine the issues identified in the previous stage. Next, the required quantitative
data were collected from research articles, public government reports and datasheets,
and company reports. The research methodology is divided into two sections. Section
1 explains the methodology developed to fulfill objective 1, and Section 2 describes
the methodology developed to achieve objectives 2 and 3.
3.1. Water Distribution Network (WDN) design for areas with
complex topography considering the energy recovery devices
This section is intended to explain the process and development of the methodology
designed to answer objective 1 and that is later presented in this document in
publication “Design of Desalinated Water Distribution Networks: Complex
Topography, Energy Production, and Parallel Pipelines.”
3.1.1. Optimization of Water Distribution Networks (WDN)
Water supply systems are usually divided into four components: water intake, storage
and water treatment, water pumping, and the water pipelines for the water
distribution. The WDN for this thesis will be defined as the set of water treatment
plants and the water distribution network, which is composed of pumping stations
and the pipeline to a mining plant.
To analyze WDN, basic principles of fluid mechanics have applied: the continuity
equation, the momentum principle (or conservation of momentum), and the energy
equation. A related principle is the Bernoulli equation, which derives from the motion
equation (Chanson, 2004). Darcy-Weisbach and Hazen Williams equations are applied
to know head loss along pipelines (Swamee, 2001).
WDN design is a complex problem that includes the determination of demand, the
optimal layout of WDN, the dimension of the components like pipes pumps, valves,
tanks, and other components (Amit and Ramachandran, 2009). When designing a
WDN, the goal is to reduce the initial investment and operational costs of the system.
The primary constraint is that the desired demands are supplied with adequate
pressure heads at withdrawal locations. Additionally, the water flow in a WDN, and
the pressure heads at nodes must satisfy the governing laws of conservation of mass
and energy (Amit and Ramachandran, 2009). Providing water at minimal cost results
in an optimization problem, which has been solved using linear programming (LP),
non-linear programming (NLP), Mixed Integer Non-Linear Programming (MINLP),
Mixed Integer Linear Programming (MILP), dynamic programming, and heuristic-
based optimization methods (Amit and Ramachandran, 2009; D’Ambrosio et al.,
2015).
3.1.2. Problem Statement
To achieve objective number 1, a methodology was designed to represent the WDN,
including the selection of desalination plants, specifically RO plants, to supply mining
19
sites. The model includes energy recovery devices for energy production located in
areas where due to the difference of altitude between 2 points is possible to produce
energy like in the hydropower industry, these energy recovery devices are known as
PATs. Additionally, parallel pipelines are considered to split the water flow when
needed.
Mine sites are located away from the coast; these sites have a water requirement that
needs to be fulfilled with desalinated water coming from RO plants located on the
coast. The area features a complex topography, which means several changes in
altitude from the coast until the mine site. The only option to fulfill the water
requirement needed is desalinated water from RO plants. The methodology proposed
by Herrera-León et al., 2019 was used as a reference for this methodology.
3.1.3. Mathematical Formulation
A superstructure was used to represent the WDN, which includes RO plants,
pipelines, pump stations, PATs, and the mine sites as nodes. Distances between nodes
and altitude of each node were designed base on topography data obtained in Google
Earth. The superstructure also includes the option to use parallel pipelines.
The objective function minimized the total annualized cost of RO plants, pipes, pump
stations, and PATs required to supply several mine sites located in an isolated area far
away from the coast. The objective function is not linear, so the problem results in an
MINLP problem, which is transformed into a MILP problem using a piecewise
methodology extracted from Lin et al., 2013. This methodology allows converting a
non-linear programming problem into a linear programming problem or a mixed-
integer convex programming problem for obtaining an approximated global optimum
solution.
3.2. An economic evaluation of re-processing of mine tailings to
obtain critical materials
This section is intended to explain the methodology designed to complete objectives
2 and 3. It also presents an overview of the methods applied in publications 2 and 3.
3.2.1. Project valuation Tools
Project valuation is probably the most crucial part of the selection process because it
assigns a monetary value to the project. Broadly defined, the project value is the net
difference between the project revenues and costs over its entire life cycle. If the net
revenues of the project during the production phase are higher than the investment
costs, the project is considered worthy of investment (Kodukula and Papudesu, 2006).
The quality of the project valuation will depend on how they effectively include these
three factors:
Cash flow streams through the entire life cycle of the project
The discount rate used to discount future cash flows to account for their
uncertainty
20
Availability of management’s contingent decisions to change the course of the
project
Project cash flows represent the revenues and the costs of the project through the
entire life cycle of the project. The costs should include the initial investment for the
project and the production phase.
Valuation methods assume that money today is worth more than in the future, so to
acknowledge that a discount rate is used. The discount rate is the rate that is utilized
to convert the future value of the project cash flows to today’s money. The discount
rate is adjusted to the risk perceived to be associated with the project, so the higher
the risk, the higher the discount rate (Kodukula and Papudesu, 2006).
3.2.2. Discounted Cash Flow (DCF)
Discounted Cash Flow (DCF) is a valuation method that is based on calculating future
cash flows of a project to decide whether it is feasible or not to invest. DCF is based on
the estimation of the Net Present Value (NPV) of the project in its entire project life
(Kodukula and Papudesu, 2006).
NPV is the preferred metric for project valuation under most circumstances (Arnold,
2014). To calculate NPV, cash outflows, which are the costs of the project, are deducted
from the cash inflows, which represents the revenues of the project. Additionally, all
cash flows are discounted to generate NPV. If the NPV is positive, then the project is
feasible because the revenues exceed the expenses of the project. On the contrary, if
the NPV is negative, then the project is not feasible because the costs are higher than
the revenues. If the NPV is zero, then the return of the project is equal to the expenses.
Traditional valuation tools, including the DCF method, have been employed for many
decades in the economic evaluation of projects. Although these methods have been
effective in many cases, under specific conditions, they have certain challenges. One
of the biggest dilemmas when using DCF is to choose a discount rate. The main factors
that determine the discount rate for a given cash flow stream is the magnitude and the
type of risk (Kodukula and Papudesu, 2006). An important consideration to determine
the discount rate is whether there is uncertainty associated with the cash flow streams.
There are several methods designed to consider uncertainty when calculating the
NPV, such as: to increase the discount rate, to apply sensitivity analysis, to compare
pessimistic and optimistic cash flows or, to estimate the expected cash flows through
scenario planning and the probability distribution (Gaspars-Wieloch, 2019).
3.2.3. Real Options Analysis (ROA)
When there is considerable uncertainty related to the project cash flows, and
contingent decisions are involved, traditional tools don’t include the flexibility to
change the course of the project and its possible outcome (Kodukula and Papudesu,
2006). ROA addresses the issue of choices a manager may have throughout the life of
the project and how those choices can enhance the value of a project (Arnold, 2014).
21
ROA is a complement to traditional methods as the DCF method, which seeks to
analyze different possible choices for an investment project to give flexibility to the
project, unlike conventional valuation methods. A real option is a right, but not an
obligation, to undertake business initiatives that are connected to and exist on real
assets or within real assets (Trigeorgis, 1993).
ROA adds value to an economic analysis like the DCF method by considering different
options such as wait to invest, abandon an investment, or expand a business. Then,
more opportunities and flexibility are available when a project is surrounded by
considerable uncertainty.
ROA can be applied using different methods such as Black & Scholes Equation,
Decision trees or binomial trees, Datar-Mathews model, which uses cash flow
scenarios combined with Monte Carlo simulation, and Fuzzy Pay-off Method (Collan,
2011).
3.2.4. Sensitivity Analysis
As a complement to the DCF method, sensitivity analysis (SA) can be performed on
the NPV to explore the sensitivity of key input parameters. Sensitivity analysis is the
study of how the uncertainty in the inputs of a mathematical model or system can be
distributed into different sources of uncertainty in its inputs. Alongside sensitivity
analysis, uncertainty analysis is usually performed. Uncertainty analysis assesses the
uncertainty in model outputs that derives from the uncertainty in the inputs. Methods
to perform SA include simulation and scenario techniques. Global sensitivity analysis
methods consider the changes in model outputs as input factors change all together
over specified ranges. These methods have the ability to manage non-linear and non-
additive responses and to observe relationships between multiple factors.
Monte Carlo Simulation is a method that consists of the simulation of thousands of
possible project scenarios, calculation of the NPV for each scenario using the DFC
method, and analyzing the probability distribution of the NPV results (Kodukula and
Papudesu, 2006).
22
4. Publications and Results Reviews An overview of the publications is included in chapter 4, which includes the
objectives, findings, and contributions of each publication of this doctoral dissertation.
The overall purpose of the dissertation is to…
4.1. Publication I: Design of desalinated water distribution networks:
Complex topography, energy production, and parallel pipelines
4.1.1. Research Objective
The objective of this publication is to provide a methodology to design the water
distribution network (WDN) and reverse osmosis (RO) plants to supply mining
companies with desalinated water, the mathematical model considers the following
elements to design the WDN: energy recovery devices, parallel pipelines, and complex
topography. Energy recovery devices considered in the model are PATs for producing
energy in the network using hydropower principles. Parallel pipelines are considered
when the water requirement is large and cannot be supplied with one pipeline. In this
study complex topography means
4.1.2. Contributions
PATs are often used in urban water distribution networks to reduce pressure, and
there are some applications to produce energy. The main contribution of this study is
proposing the use of energy recovery devices in areas with the mining industry where
they are yet not used. These devices can be used in areas with complex topography,
meaning isolated areas and presents changes in elevation as the pipelines go from the
seashore to the mining site. Mining sites are usually located in areas suffering from
water scarcity; thus, the use of desalinated water is a must.
A methodology to simultaneously design the WDN to supply several mining sites
located in an area with complex topography, additionally to find the location and sizes
of desalination plants, pipelines, pump stations, and energy recovery devices, was
addressed. A case study based on an area in northern Chile was used to validate the
model. A superstructure was used to represent the WDN, which includes RO plants,
pipelines, pump stations, and energy recovery devices. The objective of the model is
to minimize the total annual cost by finding the optimal WDN.
Results show the use of PATs in a region with complex topography is indeed feasible
for producing energy in the WDN in areas like the Coastal Cordillera, where larger
elevations in altitude are often avoided by mining companies. The use of parallel
pipelines is a feasible option to supply with desalinated water to several mining sites,
instead of having their own RO plant and own pipeline system for each mining site.
23
4.2. Publication II: Towards mine tailings valorization: Recovery of critical
materials from Chilean mine tailings
4.2.1. Research Objective
This study aims to conduct a technical and economic assessment of the valorization of
mine tailings of Chile as a source of critical materials. In recent years, the use of
secondary sources, such as mining waste and electrical waste, has gained importance.
This research adds knowledge to that field of study by adding a novel techno-
economic assessment for producing critical materials by re-processing mine tailings.
4.2.2. Contributions
Results show that mine tailings facilities of the copper industry in Chile store valuable
elements such as critical materials. Therefore, the evaluation of geochemical content
alongside the identification of suitable technologies, and an economic analysis will
help to find alternative sources of critical materials, as is the case of re-processing mine
tailings with such purpose.
The DCF method is a method widely used in economic assessment but is not a decisive
metric for a final decision on real investment. To ensure the robustness of the
assessment, a sensitivity analysis was performed on the results of the NPV, by
analyzing the effect of the market prices of critical materials, capital, and operating
costs on the options assessed for producing critical materials. The options analyzed
were producing rare earths concentrate or producing vanadium pentoxide. Results
show that under certain conditions the production of vanadium pentoxide is feasible.
The main contribution of this study is to show the economic potential of Chilean mine
tailings by performing a techno-economic assessment of the valorization of tailings.
4.3. Publication III: Feasibility of re-processing mine tailings to obtain critical
materials using real options analysis (submitted in Sustainable
Development)
4.3.1. Research objective
This study aims to propose a framework to assess the feasibility of re-processing mine
tailings to obtain critical materials, considering flexibility aspects, such as waiting for
investment in the case of a negative outcome in the present.
The NPV estimated with the DCF is used as a starting point; then, with ROA, different
outcomes for an investment project are assessed. ROA is applied using binomial tree
analysis. The binomial tree is built by using the method of risk-neutral probabilities.
For re-processing mine tailings, technology development and business models are still
needed. To study the influence of several variables on the NPV outcome, Monte Carlo
simulation is applied to perform sensitivity and uncertainty analyses.
The framework developed in this study is applied to a case study based on active mine
tailings located in the Antofagasta Region in Northern Chile. This region features
24
several mining projects based on copper resources, leaving tremendous volumes of
mine tailings that are stored without any economic purpose.
4.3.2. Contributions
The novelty of this study is to consider ROA and sensitivity analysis to provide
flexibility to the economic assessment of re-processing mine tailings, acknowledging
the uncertainties involved. Traditional valuation tools such as the DCF method are
statistic methods that do not consider the uncertainty of the variables used to estimate
the profitability of an investment.
ROA gives additional value, so decision-makers can explore alternatives while
waiting to uncertainty to clear off to invest, to re-estimate the project payoff, or they
can decide to abandon a project.
25
5. Conclusions Reducing primary ore extraction and reducing waste are part of the strategies that the
mining industry needs to apply for implementing sustainable manufacturing.
Reducing approaches in every manufacturing and processing industry is the core of
the circular economy. Re-processing mine tailings will reduce the amount of waste
that a mining plant left behind, and it will reduce the need for primary mining ores.
Another challenge for the mining industry is to reduce and optimize the demand for
freshwater, especially in arid zones where water is a scarce resource. The purpose of
this thesis is to develop methodologies to improve water and mine tailings
management in mining processes.
The conclusions, related to the research questions, are presented below:
RQ 1.1. Is an integrated water supply system that includes energy recovery devices a
feasible option in areas with complex topography?
A methodology was developed to simultaneously design a water distribution network
to supply mining plants located in an area with complex topography with desalinated
water, as well as the location and size of desalination plants, pipelines, pump stations,
and PATs stations. The methodology was validated with a case study that
corresponds to a geographic area located in the Antofagasta region, which includes
four mining plants (Araya et al., 2018). This area features several changes in altitude,
as is located in the Atacama Desert, which is cross by the Coastal Cordillera.
The optimal solution resulted in a WDN that considers one desalination plant to
supply the four mining plants, as well as PATs located in locations with altitude.
Additionally, the optimal solution included the use of parallel pipelines. A ranking of
solutions was presented, which showed that an integrated system prevails to the
traditional water supply system, which consists of a desalination plant and a set of
pumping stations and pipelines to each mining plant (Araya et al., 2018).
RQ 1.2. Is it economically and technically feasible to use energy recovery devices in the
water supply system?
The use of energy recovery devices, in this case, PATs is feasible in the presence of a
great difference in altitude between two nodes. Having an integrated system to supply
desalinated water to several mining plants reduces the costs of the water supply
system and enhances the industrial symbiosis between different companies.
Moreover, the use of PATs can reduce the costs by producing energy, which can be
used in the water distribution network (Araya et al., 2018, 2017).
The difference of altitude between two nodes, in which the option of using PATS was
considered, was varied to understand in which situations PATs are a feasible option,
from both technical and economic aspects. This analysis showed that there is a
difference in altitude where the option of PATs is no technically possible(Araya et al.,
2018).
26
RQ 1.3. When using parallel pipes is a feasible option in the water supply system?
Parallel pipes are needed when the water flow is larger than the maximum water flow
allowed in industrial pipelines, so in the case of an integrated water supply system
using parallel pipes is a feasible option to supply water to several mining companies.
The optimal solution features parallel pipes, as a set of three pipes and two pipes.
Furthermore, the three first solutions include parallel pipes, demonstrating that
parallel pipes are needed when having to supply several mines (Araya et al., 2018).
RQ 2.1. What critical materials can be recovered from mine tailings?
Mine tailings contain several elements, including some critical materials. A
methodology to assess the valorization of mine tailings was developed, with the focus
on the recovery of critical materials. The methodology was validated with a case study
that corresponds to inactive mine tailings deposits located in the Antofagasta region
(Araya et al., 2020). Mine tailings of copper mining in Chile contains several critical
materials, including rare earths, vanadium, cobalt, and scandium. A ranking of critical
materials that could be extracted from mine tailings was presented, the critical
materials were evaluated according to the quantity present in tailings deposits and
the price of the critical material. This analysis showed that rare earths, cobalt,
scandium, and vanadium could be extracted from inactive mine tailings in the
Antofagasta Region, due to their price and quantity (Araya et al., 2020).
RQ 2.2. What are the challenges in the production of critical materials using mine tailings
as a source?
Emerging technologies for recovering critical materials from mine tailings were
reviewed, showing that Technology development is still much needed to make the
recovery of critical materials from mine tailings at an industrial scale. At this time,
most of the research is still in the laboratory and pilot-scale (Araya et al., 2020). Further
research should address new strategies to anticipate the future use of material beyond
the closing of a mine (Lèbre et al., 2017).
RQ 2.3. Is it economically feasible to invest in a project developed around the idea of re-
processing mine tailings to obtain critical materials?
The economic assessment developed to assess the production of critical materials from
mine tailings showed that, in certain conditions, the recovery of critical materials is
feasible. DCF method was used to calculate the NPV of two projects, one based on the
production of rare earths concentrate and another one based on the production of
vanadium pentoxide. Results showed that a project based on the recovery of
vanadium pentoxide is feasible (Araya et al., 2020).
Alongside the DCF method, a sensitivity analysis was performed on the inputs of
NPV, to understand which variables have a more significant effect on the NPV. The
inputs variables studied were capital expenditures, operational expenditures, price of
the critical material, and discount rate (Araya et al., 2020).
27
RQ 3.1. How can real options improve the decision to invest in a project using mine tailings
as a source of critical materials?
A project based on the recovery of critical materials from mine tailings can have great
uncertainty in their inputs. ROA complements traditional valuation methods such as
the DCF, by including other options for investment. ROA provides flexibility to a
project based on the re-processing of mine tailings, acknowledging the uncertainties
involved.
RQ 3.2. How can the net present value variables influence real options performance?
The inputs of the NPV can have uncertainties that affect the outcome. Using the NPV
as a decisive metric for investments can lead to errors in the decision-making process.
The NPV is used as a starting point to ROA since it is a complement to traditional tools
rather than a method by itself.
5.1.Theoretical Contribution of the Study
This thesis contributes with a collection of methodologies to assess water management
and mine tailings management in mining. The mining industry is facing many
challenges as industries need to fulfill sustainable development goals to achieve a
circular economy.
The first contribution of this thesis is to provide a methodology to design integrated
water supply systems to provide desalinated water to several mining plants. The
novel contribution of this methodology is to include the option of placing energy
recovery devices in locations where the difference of altitude can be advantageous to
produce energy as it is done in hydropower plants. Additionally, the methodology
includes parallel pipes to fulfill the demand of several mine plants at the same time.
The other contributions of the thesis are embedded in the field of mine tailings
management. These contributions are a methodology to assess the feasibility of re-
processing mine tailings to obtain critical materials and a methodology to assess the
feasibility of re-processing mine tailings with a real options approach. The novelty of
theses methodologies is to assess the feasibility of projects based on the idea of
obtaining critical materials from a secondary source such as mine tailings.
5.2.Limitation and Future Research Suggestions
A limitation of this study is the difficulty to find data about technologies suitable for
recovering critical materials from mine tailings. Data about capital expenses,
operational expenses, and prices are not easy to find.
Another limitation is that all the methodologies presented in this thesis are validated
with case studies of the copper mining industry in the Antofagasta Region. These
methodologies could be applied to other case studies, but some considerations and
changes should be made.
Future research suggestions will be focused on implementing the circular economy in
mining processes with a focus on mine tailings management. Mine tailings are the
28
biggest sink of water of the mineral processing, so efforts should be made to create a
framework that integrates water management for mine tailings with the re-processing
of mine tailings. Future studies should also incorporate an environmental assessment
of projects based on the re-processing of mine tailings.
29
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35
SECTION II: PUBLICATIONS
PUBLICATION I
Araya, N., Lucay, F.A., Cisternas, L.A., Gálvez, E.D.
Design of Desalinated Water Distribution Networks: Complex Topography, Energy
Production, and Parallel Pipelines.
Industrial & Engineering Chemical Research
https://doi.org/10.1021/acs.iecr.7b05247
Vol 57 (30), 9879-9888, 2018
Reprinted with the permission of Industrial & Engineering Chemical Research, Copyright ©
2018, American Chemical Society
Design of Desalinated Water Distribution Networks: ComplexTopography, Energy Production, and Parallel PipelinesNatalia Araya,† Freddy A. Lucay,† Luis A. Cisternas,† and Edelmira D. Galvez*,‡
†Depto. de Ing. Química y Procesos de Minerales, Universidad de Antofagasta, Antofagasta, Chile‡Depto. de Ing. Metalurgia y Minas, Universidad Catolica del Norte, Antofagasta, Chile
ABSTRACT: A methodology was developed to determinate thelocation and size of desalination plants, the water distributionnetwork, and the location and size of energy recovery devices toprovide desalinated water in regions with complex topography. Thenovelty of this methodology is that energy recovery devices such aspumps as turbines are incorporated to produce energy. Anothernovelty is the consideration of using multiple pipelines. Themethodology proposed uses a superstructure with a set ofalternatives in which the optimal solution is found. A mathematicalmodel is generated that corresponds to a mixed integer nonlinearprogramming (MINLP) problem, which is linearized to become amixed integer linear programming (MILP) problem solved usingthe CPLEX solver in GAMS. A case study is presented todemonstrate the applicability of the methodology to real sizeproblems.
1. INTRODUCTION
Water and energy are vital elements to the well being ofsociety. At a basic level, electricity generation requires water,and water treatment and transport require electricity. World-wide energy consumption destined for water supply represents7% of global energy consumption.1 Hamiche et al.2 reviewedthe nexus between water and energy comprehensively andpresented a classification system; their work suggested that thisnexus should be explored widely.Nowadays, fresh water sources are scarce, and nontraditional
water sources are utilized more every day to fulfill theincreasing demand for both human and industrial consump-tion. The advance in desalination processes, reduction ofmembrane cost, and lower energy consumption have madeseawater a viable source of freshwater.3
Reverse osmosis (RO) is a feasible option to provide waterfor isolated and desert areas where there is access to seawater.RO is the desalination process most utilized worldwide; morethan 50% of desalination plants correspond to RO plants dueto its simplicity and because its energy requirements are minorwhen compared to distillation-based thermal processes.4
The transport of desalinated water in areas with complextopology, e.g., areas with mountains, is a major challenge forseveral reasons. On the one hand, the transport costs due tothe elevations are significant, which can be several times thecost of desalting, and on the other hand, finding only upwarddistribution systems is difficult. An example corresponds to thenorth of Chile (Antofagasta Region) where there are severalmining plants located at high altitude in a desert area. Fromthis area, Chile produces more than half of the Chilean copper
production (35% of the world’s copper production) and othermetallic elements like silver, gold, and molybdenum andnonmetallic minerals like potassium nitrate, lithium carbonate,and boron. The Antofagasta Region is located in the AtacamaDesert, the driest nonpolar desert of the world, and water isneeded to process these ore resources. Water is a limitedresource due to the overexploitation of groundwater sources.On the other hand, the Antofagasta Region has a large seacoast; therefore, seawater has become the main source of freshwater for the mining industry and urban populations.The mines are often located far from the coast and, more
importantly, at high altitudes. These changes in elevation arethe result of the presence in the coast of the Coastal Cordillera,which is a mountain range, and the presence of the AndesMountains. Mine elevations vary between 1000 and 4000 mabove sea level. In the region, there are several mining plantsalready using desalinated water obtained through RO. Eachmining company has a desalination plant with a waterdistribution network (WDN) to provide fresh water for itsprocesses without any integration between companies. Theneed to develop a more efficient desalination and WDNsystem, for example, through the integration of several WDNs,motivates this work.
Special Issue: 2017 European Symposium on Computer-AidedProcess Engineering
Received: December 22, 2017Revised: June 5, 2018Accepted: June 7, 2018Published: June 7, 2018
Article
pubs.acs.org/IECRCite This: Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX
© XXXX American Chemical Society A DOI: 10.1021/acs.iecr.7b05247Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX
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There have been several works regarding the design of ROplants and water supply systems. The methodologies to designwater supplies systems usually result in mixed integer nonlinearproblem (MINLP) models. Amit and Ramachandran5 realizeda review of the current status of optimization models fordesigning water distribution networks and presented recom-mendations for future research; Coehlo and Andrade-Campos1
provided a review about methods to achieve water supplysystem efficiency, which also included design optimization.Khor et al.6 provided state of the art water networks synthesisfocusing on a single site and continuous process problems,where major modeling and computational challenges werediscussed exploring issues such as nonconvexity and non-linearity.El-Halwagi7 introduced the novel notion of synthesizing RO
networks applied to waste reduction. The synthesis wasformulated as MINLP, and the objective of this work was tominimize the total annualized cost of RO networks. Since then,considerable research has been made regarding the design ofRO plants and water distribution systems.Liu et al.8 considered using desalinated water, wastewater,
and reclaimed water to supply water deficient areas using amixed integer linear programming (MILP) model taking intoaccount geographical aspects of the region; however, this workdid not consider using energy production. Ahmetovic andGrossman9 proposed a general superstructure and a model tooptimize integrated process water networks using MINLP andNLP models, considering multiple sources of water anddifferent qualities of water; the methodology was applied indifferent case studies. Atilhan et al.10 proposed a novelapproach for the design of desalination and water distributionnetworks considering first a source-interception sink repre-sentation; then, an optimization problem was formulatedresulting in a NLP problem whose objective was to meet therequirements for the sinks at the minimum cost while satisfyingconstraints for the sinks. The methodology was applied to acase study. Lira-Barragan et al.11 proposed that mathematicalprogramming models for synthetizing WDN associated withshale gas production take into account uncertainties, and theproposed superstructure for water integration allows themanagement of fresh water consumption and wastewaterstreams. Liang et al.12 proposed a convex model, whichcorresponded to a MINLP problem, to obtain the optimaldesign of water distribution systems using the Hanoi network,which is a known problem of the looped water distributionnetwork as a case study.13 Gonzalez-Bravo et al.14 proposed amultiobjective optimization approach for synthesizing waterdistribution networks considering domestic, agricultural, andindustrial users involving dual purpose plants consideringenvironmental, economic, and social aspects. Gonzalez-Bravoet al.15 presented an approach to design water and energydistribution networks based on a multistakeholder environ-ment where a multiobjective model considering economic,environmental, and social impacts was applied in a stressedscheme, and the proposed method identified the optimalsolution to minimize the dissatisfaction level of the involvedstakeholders.The WDN including RO selection in complex topography
has not been studied in depth. Herrera et al.16 developed amodel to design water distribution networks considering ROplants to supply mining plants located in high areas that areisolated and arid, up to 4000 m above sea level. They used asuperstructure to design the whole system using a MINLP
model. The methodology was demonstrated with a case study,and its application was adaptable to similar problems.However, they did not consider WDN design including siteswith changes in the elevations resulting from the presence ofmountains.The use of pumps as turbines (PATs) can be an option of
producing energy in the network that can be used to supplyenergy for water pumping. Pumps operating as turbines can beused in water distribution systems to reduce pressure instead ofusing pressure reducing valves. Additionally, they can produceelectricity.17
There are some reviews on energy efficiency in water supplysystems that include hydropower generation and PATsimplementation. Vilanova and Balestieri18 presented modelsof hydropower recovery in water supply systems that could beapplied in a water distribution network design. Zakkour et al.19
reviewed some emerging technologies and practices forsustainable water utility. McNabola et al.20 presented a reviewof energy use in the water industry and opportunities formicrohydropower (MHP) energy recovery.Vilanova and Balestieri21 evaluated the possibilities and
benefits of recovering and producing energy in water supplysystems. They illustrate technical, economic, and environ-mental aspects of hydropower recovery in water supply systemsusing a case study. Corcoran et al.22 developed a methodologyto find the optimal location of turbines in a water distributionnetwork using a MINLP approach and an evolutionaryapproach as a comparison. Tricarico et al.17 presented amethodology to implement PATs combined with pumpscheduling to recover energy and pressure water regime in awater distribution network, showing clear economic benefits.De Marchis et al.23 analyzed the application of PATs in a waterdistribution network using a hydrodynamic model. The modelwas demonstrated to correctly represent the impact of energyrecovery on water supply distribution. Carravetta et al.24
presented the implementation of microhydroelectric plantswhich included PATs in urban water networks. The project ofa small hydroelectric plant was performed at the inlet node of areal network. The case study showed that the installation ofsmall hydroelectric plants could provide interesting economicbenefits for the manager of pipe networks in urban areas. Noneof the works reviewed analyzed the implementation of PATs ina WDN on a larger scale; furthermore, none consideredproducing energy like that in the hydropower industry fromthe downfall of water in a WDN that included RO plants andindustrial sites with a large requirement of water.Parallel pipelines are arranged to divide flow and to keep the
head loss at the same rate, meaning that head loss in all parallelpipes remains the same.25 The reliability of a water distributionnetwork can be improved by adding a parallel pipe to anexisting one.26 In actual industrial operations, more than onepipeline is often utilized to provide higher flows, mainly inmining operations which require a great amount of water intheir operations, so one pipeline cannot satisfy the waterrequirements. Parallel pipes must be included in the WDNdesign.The objective of this work is to provide a methodology to
design the WDN and selection of RO plants to supplyindustrial plants with desalinated water. The developed modelfor this methodology considers using energy recovery devicessuch as pumps as turbines for energy production in thenetwork in places where there is a considerable difference ofheight that allows producing energy like in the hydropower
Industrial & Engineering Chemistry Research Article
DOI: 10.1021/acs.iecr.7b05247Ind. Eng. Chem. Res. XXXX, XXX, XXX−XXX
B
industry. Another novelty of the work is to considerer morethan one pipeline in cases where flows are high.Pumps as turbines are usually used in urban water
distribution networks to reduce pressure, and there are someapplications of energy production. The novelty of this workrelies in proposing the use of energy recovery devices in areaswhere they are usually not used, meaning areas that have acomplex topography that are also isolated and suffering fromwater scarcity, so the only source of fresh water is desalinatedwater.
2. PROBLEM STATEMENTIndustrial sites such as mining plants are water consumers thatare located far away from the coast, in areas with a complextopography; by complex, this refers to an area with changes inelevation between the RO plants and water consumers. Waterdemand of industrial sites can only be satisfied with desalinatedwater from RO plants located along the coast; no other optionwas taken into account as the industrial sites are located inisolated areas, which means that water is a scarce resource. Themethodology used by Herrera et al.16,27 was used as a referencein this work.A superstructure was used to represent the WDN, which
included RO plants; pipelines; nodes with pump stations,pumps as turbines, or just a junction; and industrial sites. Somenodes of the WDN are located in mountains where there is apronounced altitude, so pipelines have to ascend and thendescend, so the downfall of water is used to produce energywith the passage of water through a pumping station withpumps as turbines (PATs) like in Figure 1. The possibility of
producing energy with water passing through the downstreamwas evaluated and compared to water ascending through theWDN until reaching industrial sites in the traditional way ofavoiding the descend of water.Another consideration in the superstructure is to use more
than one pipeline until three pipelines are allowed; the choicebetween using one, two, or three pipelines depends mainly onthe requirements of water of each consumer’s site. There is amaximum velocity allowed in a pipeline, which is used as arestriction in the model. The diameters of the pipelines aredetermined by the model by choosing between a set of discretediameters that are commercial sizes.The objective of the model was to minimize total annual
cost and find the locations and sizes of RO plants, locationsand sizes of pumping stations, locations of PATs, pipediameters, operational conditions of pumping stations, andnumber of pipelines in the WDN in order to providedesalinated water to industrial sites.
3. MATHEMATICAL FORMULATIONFour sets were used to represent the superstructure: RO plantsSO = {so| so is an RO plant}; nodes which can be pumpingstations, pumping stations working as turbines, or just ajunction without a pumping stations, so N = {n|, n is a node};industrial sites or water consumers SI = {si|, si is industrialsite}; and the set of diameters D = {d|, d is a diameter}.Distances and elevations of each point were designated basedon the topography data obtained using Google Earth, anddistances were defined as Li,j and elevations as ΔZi,j.Water flow is only in one direction, from RO plants located
along the shore to the user that are industrial sites, which areusually mining plants. Bidirectional flow makes no sense giventhe high costs of transporting water from a low altitude to ahigh altitude location. Only feasible connections betweennodes were considered in the WDN.Known parameters are the water requirements of industrial
sites, according to the needs of its facilities, water capacities ofRO plants, altitude of each node, and distances between eachnode.The model has equations of continuity for RO plants, nodes,
and mining plants; these equations are presented as eqs 1−3
∑* = ∀ ∈∈
Q Q so SOson N
so n,(1)
∑ ∑= ∀ ∈∈ ∈
Q Q n Ni input
i nj output
n j, ,(2)
∑* = ∀ ∈∈
Q Q si SIsin N
n si,(3)
where Qi,j is the volumetric flow pumped from i to j;constraints associated with the maximum production capacityof RO plants and desalinated water demands of the miningplants were also included in the model.
3.1. Pipe Diameter. For selecting the pipe diameter frompoints i to j, a disjunction expressed using the Convex Hullmethod28,29 was used (eq 4).
∨=
∀ ∈∈
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É
Ö
ÑÑÑÑÑÑÑÑÑÑÑ
y
D Di j FIJ( , )
d D
i j d
i j d
, ,
, (4)
The friction factor is assumed to be a function of the pipediameter and the roughness. The Reynolds number isconsidered big enough to not represent a contribution to thefriction factor.30 A set of discrete values were considered tochoose diameter. The values used for the diameter were 0.7,0.8, 0.9, 1, and 1.1 m.
3.2. Objective Function. The objective function mini-mizes the total annualized cost of desalination plants, pipes,pumping stations, and pumps as turbines required to supplyindustrial sites located in a geography with complex top-ography. This function includes four terms that are costs: (1)cost of producing desalinated water, (2) costs of pumpingstations, (3) costs of pumps as turbines stations, and (4) costsof pipelines. The fifth term is the valorization of energyproduced by PATs that can be used in the grid.
∑ ∑ ∑ ∑
∑
= + + +
−
∈ ∈ ∈ ∈
∈
TC C C C C
E
so SOSO
i j FI Ji j
n Nn
n NPAT
n NPATs
, ,,
(5)
Figure 1. Mountain scheme: Point A represents a node with a pumpstation. Point B represents a node that is only a junction betweenpipes. Point C represents a PATs station and a traditional pumpstation.
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C
The cost of producing desalinated water was extracted fromthe database cost raised by Wittholz et al.31 The function usedincluded UPC, which is the unit cost of producing desalinatedwater.
∨ = × × *
≤ * ≤
∀ ∈∈
Ä
Ç
ÅÅÅÅÅÅÅÅÅÅÅÅÅÅÅÅÅÅÅ
É
Ö
ÑÑÑÑÑÑÑÑÑÑÑÑÑÑÑÑÑÑÑ
y
C PA UPC Q
Q Q Q
so SOc C
so c
so so c so
cLO
so cUP
,
,
(6)
The cost of water transport is represented by a functionproposed by Swamee;25 this function includes two functions:annualized capital cost of pipelines and operational and capitalcost of pumping stations. So, the function that described theannualized capital cost of pipelines proposed by Swamee25 isdescribed below
=+
∀ ∈( )
Ck L D
Pi j FIJ
1( , )i j
PH
H i j i jm
L,
, ,i j
b
,
(7)
where kP is a proportionality constant; Hi,j is the pressure head;Hb is the length parameter; Li,j is the pipe length; Di,j is the pipediameter; and m is the exponent.The function to estimate pumping station costs is
∑
ρη
ρη
=+
+ ×
× ∀ ∈∈
ikjjjjj
y{zzzzzC
k s gP
F F E g
Q H n N
(1 ) 8.76n
N b
L
D A C
j outputn j n j, ,
(8)
where kN is a proportionality constant; sb is the standbyfraction; ρ is the mass density of water; g is the gravitationalacceleration; η is the combined efficiency of pump and primemover; FD is the daily averaging factor; FA is the annualaveraging factor; EC is the unit electrical cost ($/kW h); and PLis the plant life years.The function includes the pumping head Hn,j, which is
calculated with the Darcy−Weisbach equation, which is
π= + Δ +H H z
fL Q
gD
8n j n j
n j n j
n j, 0 ,
, ,2
2,
5(9)
where Δzn,j is the elevation difference from n to j; H0 is theterminal head; f is the friction factor; and Ln,j is the length ofthe pipe from n to j.3.3. Pumps as Turbines (PATs) for Energy Production.
For pumps as turbines stations, the net head for producingenergy was also calculated with the Darcy−Weisbach equationextracted from ref 32. In turbines, the net head is the actualhead used to produce energy. Net head is the gross head whichis the difference in height between two points minus the headloss. So, in the case of pumps as turbines, the head loss wouldhave a minus sign in the Darcy−Weisbach equation. Thevalorization of the energy produced in a year by PATs iscalculated using the next equation:
∑ ρ η=ikjjjjj
y{zzzzzE g Q H t E
USDyearPATs
n
N
n n C
PATS
(10)
where NPATS is the number of PATs; Qn,k is the hourly flowthrough the nth PATs (m3/s); Hn,k is the net head (m) acrossthe same PATs at the same time; η is the efficiency; t is
operating hours in a year (h); and EC is the electricity cost($/kW h).33
To obtain the cost of pumps as turbines CPAT, the price ofthese devices was estimated using catalogs from the pumpscompany’s using the net head and the flow as a reference. Civilwork and maintenance work of PATs was estimated usingvalues from ref 33.
3.4. Parallel Pipelines. In order to distribute thedesalinated water flow, the superstructure has the option ofchoosing up to three parallel pipelines depending on the waterflow. The velocity of water has a maximum value of 1.5 m/s;34
this condition is fulfilled using the next equation
π≤Q v
D
4n j n ji j
, ,,
2
(11)
The diameter of pipelines is the same for all pipelines ifmore than one is chosen. So, the next conditions must befulfilled
∑= ∀ ∈=
Q Q n Nn jp
n jp
,1
3
,(12)
= = =H H H Hn j n j n j n j, ,1
,2
,3
(13)
The total water flow is the sum of the water flow of eachpipeline where p is the pipeline, and the head drop is the samefor every pipeline and corresponds to the total head drop.
3.5. Piecewise Linearization. The objective function isnot linear because UPC and Q3 are not linear, Q3 appears whenthe Darcy−Weisbach equation is multiplied for the water flow,soQ2 is multiplied for Q. Since the objective function is notlinear, the model is a MINLP model.UPC is the amortized capital cost and the operating cost of
obtaining desalinated water and is included in the cost ofproducing desalinated water; this cost is a compound of thenext form
= × ×C Q UPC cte2SO SO (14)
where QSO is the desalinated water flow, and cte2 is a constantwhich includes desalination plant availability and time andmoney conversions to obtain the requirements units.To obtain the global optimum in short time, UPC and Q3
were linearized using a piecewise methodology extracted fromLin et al.35 Piecewise methodologies allowed us to convert anonlinear programming problem into a linear programmingproblem or a mixed-integer convex programming problem forobtaining an approximated global optimal solution.
4. CASE STUDYAn area of the Antofagasta region was used as a case study; thisarea is mainly desert and isolated and features significantchanges in elevation due to the presence of the CoastalCordillera that crosses this area. The case study contained fourmining plants that can be supplied water by three potential ROplants. Between the RO plants and the mining plants, there arepotential pumping stations, and since there are mountains inthe area, PATs were considered in some points. Connectionsthat were unfeasible were not considered as an option.Locations of RO plants and industrial sites were determined
on assumptions based on actual places where RO plants andmining plants could be located. Pipeline lengths weredetermined based on real data about the water supplies of
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D
different mining companies. The area was chosen using GoogleEarth; distances between points and elevations weredetermined using this software. Figure 2 shows the chosenarea as a case study.RO plants are located on the coast, so their elevation is zero.
There is a zone where the Coastal Cordillera goes throughabout 40 km of extension; this zone is where the use of PATswas considered and compared to the possibility of avoidingthese mountains and to only go up until reaching the miningsites. Elevation of pumping stations varied from 0 to 2.860 kmabove sea level, and mining plants were located between 3.046and 3.875 km above sea level. The elevation of each node isshown in Table 1, and the distance between each node isshown in Table 2.
5. RESULTSThe model was solved as a MILP problem using the Cplexsolver in a GAMS environment. GAMS stands for GeneralAlgebraic Modeling System; it is a high-level modelingsoftware for mathematical programming and optimization.
GAMS is designed for modeling linear programming (LP),mixed integer linear programming (MILP), and mixed integernonlinear programming (MINLP) problems.36 The Cplexsolver in GAMS is designed to solve large and difficultproblems quickly and works to solve the majority of linearproblems (LP).37
The global optimum was found in a short time aslinearization allows a model to be obtained that can be solvedquickly using Cplex, which is a desirable attribute for complexmodels like this one.
5.1. Global Optimum. The requirements of desalinatedwater of the WDN was 3.2 m3/s in total; the requirements foreach mining plant was 0.8 m3/s. These values were similar tothe requirements of the mining plants in the area.
Figure 2. Superstructure. SO are RO plants with a pumping station; n are pumping stations; P are PATs stations, and Si are industrial sites.
Table 1. Height Above Sea Level of Each Node
NodesHeight above sea level
(km) NodesHeight above sea level
(km)
SO1-n1 0 n12 2.860SO2-n2 0 n13 2.720SO3-n3 0 n14 1.585n4 2.116 n15 1.755n5 1.364 n16 2.453n6 2.231 n17 2.874n7 2.431 Si1 3.485n8 1.753 Si2 3.046n9 1.375 Si3 3.339n10 1.765 Si4 3.875n11 1.382
Table 2. Distances between Each Node
NodesDistance between nodes
(km) NodesDistance between nodes
(km)
n1-n4 40.7 n6-n9 22.5n1-n5 43.9 n7-n8 59.9n2-n4 30.7 n7-n10 47.2n2-n5 75.4 n10-n15 14.3n2-n7 34.8 n8-n12 45.7n2-n8 80.7 n8-n13 40.2n3-n7 63.4 n11-si1 80.7n3-n8 50.4 n11-si2 55.9n4-n5 46.1 n12-si3 53.6n4-n6 22.7 n12-si4 51.5n5-n14 64.9 n13-si3 62.1n13-si4 49.6 n15-si2 54.3n14-si1 55.9 n15-si3 55.0n14-si2 51.2 n15-si4 76.5n14-n16 49.1 n16-si3 37.7n14-n17 67.2 n17-si4 53.7
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The global optimum solution considers using only one ROplant to supply all mining sites; in n9, there were PATs sincethe previous node, n6, is located at a high altitude. In node n9,a PATs station was followed by a traditional pump station. Allpipelines going between n2 and n11 considered using threepipelines to fulfill the water requirements of the three industrialsites (continuous line in Figure 3). Between n2 and n13, therewere two pipes to supply si4. When the requirements of waterof the industrial sites were elevated, parallel pipes that camefrom one single RO plant seemed to be a suitable solution tosupply more than one industrial site instead of using differentRO plants with a single or double pipeline to supply eachindustrial site, which is the conventional way. The optimalsolution generated 168,593 MW-h/year, which considering0.12 USD/kW-h represents a saving of 20.231 million USD/
year. Furthermore, considering that energy is produced fromfossil fuels, this energy production can contribute to reducinggreenhouse gas emissions.A ranking of the first three optimal solutions was made to
compare them economically and operationally (Table 3). Thethree first solutions considered using PATs in the same area;the first two solutions considered only the SO2 RO plant tosupply desalinated water. Instead, the third solution consideredusing desalinated water from SO2 and SO3. Additionally, theWDN of solutions 1 and 2 used seven pumping stations,whereas the WDN of solution 3 used eight pumping stations.The differences in costs between these optimal solutions wereless than one million USD/year. More details are present inTable 3, and solutions 2 and 3 are illustrated in Figures 4 and5, respectively.
Figure 3. Optimal solution. Solid line represents three parallel pipes, and segmented line represents two parallel pipes.
Table 3. Ranking of Solutions
Solution RO plants No. of pumping stations No. of PATs stations Energy generated by PATs (MW-h/year) Total cost (million USD/year)
1 SO2 7 1 168,593 250.712 SO2 7 1 168,593 251.553 SO2-SO3 8 1 168,593 251.78
Figure 4. Solution 2. Solid line represents three pipes, and segmented line represents two pipes.
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F
Figure 5. Solution 3. Solid line represents three pipes, and segmented line represents two pipes.
Figure 6. Solution found when big changes in altitude are avoided. Solid line represents three pipes, and segmented line represents two pipes.
Figure 7. Traditional water supply system for mining plants.
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G
By way of comparison, a network was designed withoutconsidering the PATs. For this purpose, the pipes in the areawhere the PATs could be installed were not considered in thesuperstructure. The optimal solution without PATs is shown inFigure 6, which considered the SO1 RO plant and fivepumping stations. The cost was 258.52 million USD/year; thisis 7.81 million USD/year more expensive than the option withPATs. This difference was due to a higher cost in the pipes, areduction in costs for not considering the equipment for PATs,and an increase in energy costs.Another comparison was made to compare the optimal
solution with the water supply strategy currently used bymining companies, where each company had its own RO plantand water distribution network. Since there is no energyproduction, and mining companies usually avoid puttingpipelines in places with pronounced changes in elevations,the pipelines were located where there was not a big differencein altitude. The cost of this system (Figure 7) was 258.56million USD/year.The optimal solution was considered going through n6,
which was 2.231 km above sea level; the next pump stationcoupled to a PATs station was n9, which was 1.375 km abovesea level, so 0.856 km was the difference in height and 22.47km the distance between each point. In order to analyze theeffect of height in the optimal solution, several differences ofheight between n6 and n9 were used. Results are shown inTable 4.The optimal solution generated 168,593 MW-h/year, which
is 20.231 million USD/year that can be utilized in the network.If the height of the mountains was 200 m less high, the optimalsolution still considered energy generation with an importantamount of energy generated, 127,950 MW-h/year.With a height of 1.831 km, the optimal solution considered
two RO plants, SO1 and SO3, which were located at theextremes of the network, instead of choosing SO2 as theoptimal solutions as in the cases of 2.231 and 2.031 km ofheight solutions. Energy production was low in comparisonwith the solutions obtained when elevations were higher; this isdue to the water flow sent to n6 was 0.2 m3/s, which was verylow in comparison to 2.4 m3/s which is the water flow sent ton6 where the elevation was 2.231 km. The reason for such lowwater flow is that the net head was lower as the gross head,which is the actual elevation of the mountains, was lower.Head loss was high due to the distance between each point andwater velocity, so the gross head had to be high to compensatefor the head loss.
6. CONCLUSIONS
A methodology to simultaneously design a WDN to supplyindustrial sites located in regions with complex topography,find the location and sizes of desalination plants, pipelines,pump stations, and PATs stations, was addressed. A case studywas used to validate the model.
Results showed that using PATs in a region with complextopography was feasible for producing energy in the WDN bypassing through a region with changes in elevation like theCoastal Cordillera where big changes in altitude are oftenavoided by mining companies.Linearization of two functions allowed us to find the global
optimum with low computational cost, which is a desiredattribute for complex models.Using parallel pipes is a feasible option to supply several
industrial sites using water from one RO plant when therequirements of water are elevated, instead of having a differentRO plant supply every industrial site with its respectivepipeline.In the future, more elements will be added to the model
such as considering more than one water quality to supplymultiple users and multiple sources of water to broaden thewater offer. Another element that can be included is usingrenewable energies like solar energy.
■ AUTHOR INFORMATIONCorresponding Author*E-mail: [email protected] D. Galvez: 0000-0001-9558-443XNotesThe authors declare no competing financial interest.
■ ACKNOWLEDGMENTSThe financial support from CONICYT (Fondecyt 1171341) isgratefully acknowledged. N.A. thanks CONICYT for thenational Ph.D. scholarship.
■ NOMENCLATURECSO = Annualized cost of RO plants (million USD/year)Ci,j = Annualized cost of pipelines (million USD/year)Cn = Annualized cost of pumping stations (million USD/year)CPAT = Annualized cost of PATs stations (million USD/year)Di,j = Diameter of pipeline between i and j (m)EC = Unit electrical cost ($/(kW-h))EPAT = Valorization of energy generated by PATs in oneyear (million USD/year)f = Friction factor (dimensionless)FA = Annual average factor (dimensionless)FD = Daily average factor (dimensionless)g = Gravitational acceleration (m/s2)Hi,j = Pressure head (m)Hb = Length parameter (m)Hn,j = Pumping head (m)H0 = Terminal head (m)Hn,k = Net head (m)
Table 4. Comparison between Different Heights of Nodes
Q(m3/s)
Height n6(km)
ΔH n6 and n9(km) RO plants
No. of pumpingstations
No. of PATsstations
Total cost(million USD/year)
Energy generated by PATs(MW-h/year)
3.2 2.231 0.856 SO2 7 1 250.71 168,5933.2 2.031 0.656 SO2 7 1 254.67 127,9503.2 1.831 0.456 SO1-SO3 10 1 257.08 76303.2 1.631 0.256 SO1-SO3 10 1 257.95 39313.2 1.431 0.056 SO1 5 0 258.52 0
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kN = Proportionality constant for pumping stations(dimensionless)kP = Proportionality constant for pipelines (dimensionless)Li,j = Pipe length (m)PA = Desalination plant availability (dimensionless)PL = Desalination plant life (years)Qi,j = Volumetric flow pumped from i to j (m3/s)Qi,n = Volumetric flow pumped from i to n (m3/s)Qn,j = Volumetric flow pumped from n to j (m3/s)Qn,si = Volumetric flow pumped from n to an industrial site(m3/s)Qsi = Volumetric flow required in an industrial site (m3/s)Qso = Volumetric flow pumped from RO plant (m3/s)Qso,n = Volumetric flow pumped from a RO plant to n(m3/s)Qn,k = Volumetric flow through PATs (m3/h)sb = Standby fraction (dimensionless)t = Operating hours in a year (h)TC = Total annualized cost (million USD/year)UPC = Unit cost of producing desalinated water (USD)vn,j = Water velocity (m/s)yi,j,d = Disjunction to choose diameterρ = Water density (kg/m3)Δzn,j = Elevation difference from n to j (m)η = Combined efficiency of pump and prime mover
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J
PUBLICATION II
Araya, N., Kraslawski, A., Cisternas, L.A.
Towards mine tailings valorization: Recovery of critical materials from Chilean mine
tailings.
Journal of Cleaner Production
Vol 263, 2020
https://doi.org/10.1016/j.jclepro.2020.121555
Towards mine tailings valorization: Recovery of critical materials fromChilean mine tailings
Natalia Araya a, b, *, Andrzej Kraslawski b, Luis A. Cisternas a
a Departamento de Ingeniería Química y Procesos de Minerales, Universidad de Antofagasta, Antofagasta, 1240000, Chileb School of Engineering Science, Lappeenranta-Lahti University of Technology (LUT University), Lappeenranta, FI-53851, Finland
a r t i c l e i n f o
Article history:Received 16 June 2019Received in revised form6 March 2020Accepted 5 April 2020Available online 9 April 2020
Handling editor:Yutao Wang
Keywords:Mine tailingsCritical raw materialsTechno-economic assessmentDiscounted cash flowSensitivity analysis
a b s t r a c t
The mining industry produces large volumes of mine tailings e a mix of crushed rocks and process ef-fluents from the processing of mineral ores. Mine tailings are a major environmental issue due to im-plications related to their handling and storage. Depending on the mined ore and the process used, itmay be possible to recover valuable elements from mine tailings, among them critical raw materials(CRMs) like rare earths, vanadium, and antimony.
The aim of this study was to investigate the techno-economic feasibility of producing critical rawmaterials from mine tailings. Data from 477 Chilean tailings facilities were analyzed and used in thetechno-economic assessment of the valorization of mine tailings in the form of CRMs recovery. A reviewof applicable technologies was performed to identify suitable technologies for mine tailings processing.To assess the economic feasibility of CRMs production, net present value (NPV) was calculated using thediscounted cash flow (DCF) method. Sensitivity analysis and design of experiments were performed toanalyze the influence of independent variables on NPV. Two options were assessed, rare earth oxides(REOs) production and vanadium pentoxide (V2O5) production. The results show that it is possible toproduce V2O5 with an NPV of 76 million US$. In the case of REOs, NPV is positive but rather low, whichindicates that the investment is risky. Sensitivity analysis and the ANOVA run using the design of ex-periments indicated that the NPV of REOs is highly sensitive to the price of REOs and to the discount rate.
© 2020 Elsevier Ltd. All rights reserved.
1. Introduction
Mine tailings are waste from the processing of mineral ores.They are a mixture of ground rocks and process effluents generatedduring processing of the ores, and their composition depends onthe nature of the mined rock and the recovery process used. Incopper mining, tailings can account for 95e99% of crushed andground ores (Edraki et al., 2014). Worldwide, mine tailings areproduced at a rate of anywhere from five to fourteen billion tonsper year (Adiansyah et al., 2015; Edraki et al., 2014; Schoenberger,2016).
In view of the volumes of mine waste produced and the natureof the chemicals involved, the storage and handling of mine tailingsis a significant environmental problem. Mine tailings are a source of
serious contamination of soils and groundwater with nearbycommunities particularly badly affected by the results of eolian andwater erosion of tailing disposal sites (Mendez and Maier, 2008).Another cause of environmental pollution frommine tailings is acidmine drainage (AMD) (Larsson et al., 2018; Moodley et al., 2017).AMD is formed from the exposure of sulfide ores and minerals towater and oxygen, once the ore is exposed, sulfate and heavymetals are released into the water (Moodley et al., 2017). AMD isconsidered one of the most significant forms of water pollution andthe USA Environmental Protection Agency (US-EPA) considers it tobe the second only to global warming and ozone depletion in termsof ecological risk (Moodley et al., 2017).
Tailing storage facilities (TSF), also called tailing deposits, are thesource of most mining-related disasters (Schoenberger, 2016). Ap-proaches to the handling and storage of mine tailings includeriverine disposal, wetland retention, backfilling, dry stacking andstorage behind damned impoundments (Kossoff et al., 2014). Minetailings dam failures can have catastrophic consequences. 237 casesof significant tailings accidents were reported for the period 1971 to2009 (Adiansyah et al., 2015). More recently, in January 2019, an
* Corresponding author. School of Engineering Science, LUT University, FI-53851,Lappeenranta, Finland.
E-mail addresses: [email protected] (N. Araya), [email protected] (A. Kraslawski), [email protected] (L.A. Cisternas).
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Journal of Cleaner Production 263 (2020) 121555
accident at the C�orrego do Feij~ao mine in Brumadinho in themetropolitan region of Belo Horizonte in southeastern Brazil killedat least 65 people with about 280 people were missing (De S�a,2019).
To achieve a circular economy model, the valorization of minetailings is crucial for the mining industry, which needs to improveits processes to minimize its environmental impact and close theloops (Kinnunen and Kaksonen, 2019). Different approaches totailings valorization can be taken, such as reprocessing to extractmetals and minerals, tailings as backfill material, tailings as con-struction material, energy recovery and carbon dioxide sequestra-tion (Lottermoser, 2011).
Challenges that the mining industry needs to face to achieve thevalorization of tailings aligned with circular economy principlesinclude improving the rather limited knowledge about mineralogy,impurities concentration, and the quantity of tailings; developingnew business models that take account of price development,lower disposal costs, and market demand; providing institutionalimpulse indispensable to encourage the transformation from alinear to a circular economy; technology development to makeprocesses economically feasible since most mine tailings have lowgrades of different elements mixed with residues of previous pro-cesses (Kinnunen and Kaksonen, 2019; Lottermoser, 2011).
Due to the geological heterogeneity of the rocks mined and thecontinuous flow processes used in mineral processing, tailingsdeposits contain large quantities of valuable elements whose re-covery could bring potential economic benefits. A number ofstudies have investigated the recovery of valuable elements frommine tailings (Ahmadi et al., 2015; Alcalde et al., 2018; Anderssonet al., 2018; Ceniceros-G�omez et al., 2018; Falag�an et al., 2017;Figueiredo et al., 2018; Khalil et al., 2019; Khorasanipour, 2015;Mohamed et al., 2017; Sracek et al., 2010).
As shown by recent studies (Ceniceros-G�omez et al., 2018;Markovaara-Koivisto et al., 2018; Moran-Palacios et al., 2019; Tunsuet al., 2019), among elements contained in mine tailings, there aremany critical raw materials (CRMs). Raw materials have significanteconomic importance and are utilized in the manufacture of a widerange of goods. In particular, critical rawmaterials can be applied inareas such as alternative energy production and communicationsdevices, and they play a significant role in the development ofglobally competitive and eco-friendly innovations. Securing accessto a stable supply of many raw materials has become a majorchallenge for national and regional economies with a limited pro-duction, which relies on imports of numerous minerals and metals(European Commission, 2017a).
Many studies have examined the criticality of raw materials.This study utilizes the list compiled by the European Commission(EC), where raw materials are considered critical when they areboth of high economic importance for the European Union (EU) andvulnerable to supply disruptions (European Commission, 2017b).The term “vulnerable to supply disruption”means that their supplyis associated with a high risk of not meeting the demand of the EUindustry. High economic importancemeans that the rawmaterial isof fundamental importance to industry sectors that create addedvalue and jobs, which may be lost in the case of inadequate supplyand if adequate substitutes cannot be found (Blengini et al., 2017).The most critical metals are those for which supply constraintsresult from the fact that they are largely or entirely mined as by-products, generate environmental impacts during production,have no effective substitutes, and are mined in areas prone togeopolitical conflict (Graedel et al., 2015).
In 2011, the European Commission (EC) published a list of 14 rawmaterials that are critical for emerging technologies of Europeanindustries, so-called critical raw materials (CRMs) (EuropeanCommission, 2017a, 2014, 2011). The list has been updated twice
since 2011, the last update was in 2017, and it currently containstwenty-seven CRMs including 3 element groups: light rare earthelements (LREEs), heavy rare earth elements (HREES) and platinumgroup elements.
According to the International Union for Pure and AppliedChemistry (IUPAC), rare earth elements (REEs) are a group of 17elements that includes lanthanides, composed of 15 elements, andyttrium and scandium, which are included in this group due to thesimilarity in chemical characteristics. REEs can be found in over 250different minerals (Jordens et al., 2013; Sadri et al., 2017). REEs havean important role in the transition to green technologies because oftheir use in crucial components such as permanent magnets andrechargeable batteries, and their use as catalysts (Binnemans et al.,2013a). China is responsible for almost 80% of the global supply ofREEs, such monopoly has raised concerns about a possible shortageof supply, (Hornby and Sanderson, 2019; Vekasi and Hunnewell,2019).
Other elements on the list of CRMs are platinum group elements(PGEs), which include ruthenium (Ru), rhodium (Rh), palladium(Pd), osmium (Os), iridium (Ir) and platinum (Pt). These metals arevery rare in the Earth’s continental crust, ranging from 0.022 ppbfor iridium to 0.52 to Pd (Mudd et al., 2018).
Nowadays, due to the increasing demand for CRMs, new sourcesare being sought, and secondary sources such as metal scrap andindustrial waste are attracting more attention. The use of thehitherto unexploited secondary sources can reduce demand forvirgin materials and, in consequence, contribute to a decrease inmining production. One of the core principles of the circulareconomy is the reduction and minimization of resource use, andways to achieve that goal include recycling and reuse of wastes(Kirchherr et al., 2017). Mine tailings from mineral processing of acertain branch of the metal industry could be used as a source in aprocess designed to obtain one or more critical raw materials, asimplified flowsheet of this idea is shown in Fig. 1.
Chile has a long history of mining and large-scale mining startedin the first decade of the twentieth century. In 2016, Chileanminingexports were valued at 30,379 million USD according to the Na-tional Service of Geology and Mining (SERNAGEOMIN), 90% ofwhich came from copper mining (SERNAGEOMIN, 2017). Chile isthe world’s leading producer of copper. Currently, a decrease in thegrade of mined copper ores is being observed, which increases theamount of processed ore and, consequently, leads to greater tailingsdeposits for the same level of copper production. Currently, Chileproduces 1,400,000 tons of mine tailings daily and there are 696tailings storage facilities (TSF) (SERNAGEOMIN, 2018).
The objective of this study is to conduct a technical and eco-nomic assessment of the valorization of mine tailings of Chile as asource of CRMs. Therefore, the research questions addressed in thispaper are:
What critical materials can be recovered from mine tailings?What are the challenges in the production of critical materials
using mine tailings as a source?In recent years, the use of secondary sources for obtaining raw
materials has gained growing importance. This research supple-ments these works with a techno-economic feasibility study forproducing critical raw materials from mine tailings.
The data used in the study refer to mine tailings samples of 477Chilean copper mining industrial deposits. These data have notbeen previously used to assess the economic potential of the re-covery of critical materials.
2. Methodology
The first step to evaluate the recovery of CRMs from mine tail-ings is the calculation of the amount of each CRM present in
N. Araya et al. / Journal of Cleaner Production 263 (2020) 1215552
tailings. The feasibility of recovery is next assessed for criticalmaterials found in larger quantities.
In the technological assessment, technologies for processingmine tailings are first examined. If no technologies are available,technologies for processing ore, as an analogous process, areconsidered taking into account differences between the processingof ore and processing of waste.
In the economic assessment, the discounted cash flow (DCF)method is used to assess the feasibility of the options for the re-covery CRMs frommine tailings. This method has beenwidely usedfor valuation projects (De Reyck et al., 2008; Kodukula andPapudesu, 2006; �Zi�zlavský, 2014). DCF is a commonly adoptedeconomic valuation technique and consists of discounting expectedcash flow of a future project at a given discount rate and thensumming all the cash flows of a determined period of time (Ib�a~nez-For�es et al., 2014; �Zi�zlavský, 2014).
Sensitivity analysis is performed to assess the impact of variousparameters on the NPV of CRMs recovery from mining tailings.Sensitivity analysis is a tool used to analyze how different values ofa set of independent variables affect a dependent variable. The saleprice of critical materials, operating costs, capital costs, and dis-count rate are the main inputs in the DCF method, then thesevariables are studied in the sensitivity analysis. These variables andinteractions among them were also tested using a design of ex-periments with response surface methodology.
3. Mine tailings assessment
Mining is one of the main economic activities in Chile due to thecountry’s favorable geochemical and mineralogical characteristics.Chile is the world’s leading producer of copper, producing 5,552.6thousand tons of copper in 2016 (SERNAGEOMIN, 2017), theworld’ssecond supplier of molybdenum, producing 62,746.1 tons in 2017,and the second producer of lithium, producing 77,284 tons oflithium carbonate in 2017 (SERNAGEOMIN, 2017). For some regionsin Chile, mining is the main economic activity; most mining activityis found in the Atacama Desert in northern Chile.
The Atacama Desert is the driest non-polar desert on the earth,and its copper ore deposits are world-class porphyry copper de-posits (Oyarzún et al., 2016; Tapia et al., 2018). Porphyry depositsare the principal sources of copper and molybdenum(Khorasanipour and Jafari, 2017). Porphyry deposits consist ofdistributed and stockwork sulfide mineralization located in varioushost rocks that have been altered by hydrothermal solutions intoroughly concentric zonal patterns (Dold and Fontbot�e, 2001).
Chilean mining processing plants produce large quantities ofwaste every year. Tailings dams are the most common type of
tailing deposit in the country (Ghorbani and Kuan, 2017). Previ-ously, prior to the adoption of appropriate regulations, tailings wereabandoned in deposits and no efforts were made to ensure thesafety of the nearby communities but nowadays the handling andstorage of tailings are strictly regulated. In 2011, the Law 22.551waspromulgated. It regulates the closing of mining facilities andspecifies that tailings must be physically and chemically stabilized(Ministerio de Minería, 2011; SERNAGEOMIN, 2011).
In Chile, there are 696 mine tailings deposits registered in anational registry, compiled between 2016 and 2018. The registry isexpected to be updated as new mine tailings facilities are openedand old abandoned tailing deposits are discovered. AntofagastaRegion hosts larger mine tailings deposits (SERNAGEOMIN, 2018)because of the size of the mining sector in this region, which ac-counts for 47% of the contribution to Chilean mining activity. Themost serious problems associated with tailings and handling andstorage of tailings are related to the seismic nature of the country,and risks associated with tailings dam failure include fatalities,serious water contamination, and destruction of the land.
3.1. Characterization of mine tailings
The chemical composition of tailings in 477 mine tailings de-posits is available on the website of the National Service of Geologyand Mining of Chile (SERNAGEOMIN) (SERNAGEOMIN, 2018). Thisdatabase contains values for concentrations of 56 elements,including 22 CRMs featuring on the latest EC list. The CRMsanalyzed in the SERNAGEOMIN database are vanadium, cobalt,yttrium, niobium, scandium, hafnium, tantalum, antimony, bis-muth, tungsten, lanthanum, cerium, praseodymium, neodymium,samarium, europium, gadolinium, terbium, dysprosium, holmium,erbium, thulium, ytterbium and lutetium (SERNAGEOMIN, 2018).
Chemical composition in each mine tailings deposit is differentand it depends on the type of mineral rocks mined and the pro-cesses used in the plant. In the geochemical characterization ofChilean tailings, it can be noticed that most tailings deposits have ahigh percentage of silicon oxide or ferric oxide due to the type ofminerals processed (SERNAGEOMIN, 2018).
Data in the SERNAGEOMIN database are classified by the currentstatus of the tailings deposits: active, inactive, and abandoned. In themethodology used in this study, only inactive and abandoned tailingswere analyzed, because their volume and chemical composition donot change over time. In the case of active tailings, although theirvolume is greatest, their chemical composition may change over thecourse of years, which is why they have not been considered in thisstudy. Mine tailings of the Antofagasta Region are examined becausethe tailing volume storage is greater in this region than in other
Fig. 1. Simplified mining processes flowsheet featuring conventional processes to obtain metal and the re-processing of tailings to obtain CRMs.
N. Araya et al. / Journal of Cleaner Production 263 (2020) 121555 3
regions. The TSFs analyzed cover 16 inactive deposits. The location ofmine tailings of the Antofagasta Region can be seen in Fig. 2.
CRMs found in larger quantities are given in Table 1. The sum ofREEs was also calculated, to produce REE concentrate or mis-chmetal, which is an alloy of REEs. The sum of REEs does notconsider scandium because it is separated in a different process.
3.2. Technology assessment
A literature review was conducted to investigate the availabletechnologies for the recovery of critical raw materials from minetailings. If no technologies are available for tailings processing, thenthose used for processing of primary ores are considered as areference. It is important to notice that mine tailings are already inthe form of slurry or paste, depending on the percentage of waterpresent, so there are no mining costs, which represent approxi-mately 43% of operating cost in a mine (Curry et al., 2014).
Existing technologies for CRMs production are briefly describedin Table 2. Most of these technologies are for primary ores. Someapplications for secondary sources such as industrial waste andmine tailings exist (Abisheva et al., 2017; Binnemans et al., 2015;Figueiredo et al., 2018; Innocenzi et al., 2014; Jorjani and Shahbazi,2016; Peelman et al., 2016), but they should be treated as emergingtechnologies. Significant further development of these new tech-nologies is required before they are suitable for industrial-scaleusage (Kinnunen and Kaksonen, 2019).
In spite of the low concentration of REEs in comparison to end-of-life consumer goods, mine tailings are a potential source of REEsbecause of the large volumes of mine tailings, which mean that thetotal amount of recoverable REEs could be high (Binnemans et al.,2015). Several processes have been proposed for the recovery ofREEs from mine tailings. Peelman et al. (2018) have proposed amethod for the recovery of REEs from mine tailings from apatitemineral with an REE content of 1200e1500 ppm using acidicleaching followed by cryogenic crystallization and solvent extrac-tion. They achieved a 70e100% recovery of REE.
There are no processing plants using copper mine tailings as asource of CRMs. Therefore, technologies used for primary sources
are assumed to be also applicable to the processing of mine tailings.Based on the content of the mine tailings analyzed, two feasibilitystudies are conducted; the first for producing rare earth oxides andthe second for vanadium recovery, using mine tailings as a source.
The extraction process for REEs, in a general form, includes threesteps: mining and comminution; ore beneficiation processes con-sisting of flotation, gravity and magnetic techniques to generateREE concentrate; and hydrometallurgical methods to extract REEcompounds (Sadri et al., 2017). Hydrometallurgical methodsinclude cracking of REE concentrate; leaching, neutralization andprecipitation processes; and separation and purification techniquessuch as solvent extraction. Solvent extraction allows recoveringREEs with a high degree of purity, moreover, a variety of solventextraction reagents is available. For secondary waste, selectiveextraction of REEs is required from solutions with a high content ofother species (Tunsu et al., 2019).
A life cycle inventory and impact assessment of the productionof RE oxides from primary bastnasite and monazite has been pre-sented for the Bayan Obo mine in Inner Mongolia, China, in (Koltunand Tharumarajah, 2014). The study found out the mining andbeneficiation stage accounts for 6.98% of energy consumption and6.51% of water consumption. When processing mine tailings, thereis no mining stage, so the values were adapted. Adapted values ofenergy and water consumption to obtain RE oxides from wastematerial are included in the supplementary material.
Primary ores of REEs are usually treated with alkaline pressureleaching or sulfuric acid roasting. However, mine tailings are a low-grade source of REEs, so these technologiesmaynot be economicallyfeasible. Chloride-based hydrometallurgical processes may be apotential alternative to traditional capital intensive hydrometallur-gical processes based on high temperature and pressure (Onyedikaet al., 2012) and they could be a suitable option for REE recoveryfrom tailings at economically viable capital and operating cost.
In the case of vanadium, it is mainly produced as a co-productfrom the vanadium slag before the steel converter. The main va-nadium products are vanadium pentoxide (V2O5) and ferrovana-dium (FeV) (European Commission, 2017b). Other sources ofvanadium are stone coal, steel scrap, and fossil fuels.
The mine tailings analyzed in this study have a CRMs contentthat varies between 80 and 214,000 g per ton of tailing. In Chile,there are currently no projects providing for the use ofmine tailingsas a source of CRMs, nor approved initiatives for the production ofCRMs from primary ores.
3.3. Economic assessment
The economic assessment is done in two main steps. The firststep focuses on the economic potential of CRMs found in inactivemine tailings as an in-situ value, considering the monetary value ofthe CRMs to assess the feasibility of CRMs production. The secondstage concentrates on the analysis of the feasibility of CRMs pro-duction using mine tailings as a source.
Prices of critical materials may differ fromone source to another.In addition, the prices of some critical materials are not publiclyavailable as they are traded privately. To calculate the economicpotential of inactive mine tailings deposits, the following priceswere used, see Table 3.
The economic potential of CRMs recovery was calculated as thefraction of each CRM in the tailings multiplied by the mass of eachTSF for the 16 TSFs studied. The economic potential is a referencevalue for the total REE value of the mine tailings. The economicpotential of these TSFs is shown as supplementary material.
To assess the feasibility of CRMs recovery, the DFC method wasused to calculate the NPV and IRR for REOs production and V2O5productionusingmine tailings. TheNPV is thedifferencebetween the
Fig. 2. Tailings storage facilities in Antofagasta Region, blue represents inactive orabandoned deposits and red is for active deposits. (For interpretation of the referencesto colour in this figure legend, the reader is referred to the Web version of this article.)
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presentvalueof cash inflowsand thepresentvalueof cashoutflows inaparticularperiodof time. IRR is thediscount rate atwhich theNPVoffuture cash flows is equal to the initial investment. NPV and IRR aremetrics used in capital budgeting and decision-making. The calcula-tion does not include external factors such as inflation. To obtain theNPVand IRR for theoptionsassessed, capital costs andoperating costsof projects with similar characteristics were used.
Capital costs, also referred to as capital expenses or CAPEX,
represent the investment made for the project, which includescosts of the development phase which, among other costs, com-prises the purchase of the equipment, building a manufacturingplant and the cost of product launch. The investment represents thefirst cash flow in the DFC method.
Operating costs, operating expenses or OPEX, are expensesincurred during the lifetime of the project. In the case of a miningproject, these would include the cost of labor, water, and energy,
Table 1Total tonnage and uses of CRMs present in inactive tailings deposits of the Antofagasta Region (16 deposits).
CRMs Tons Uses
Vanadium (V) 46,110 Most of the vanadium produced is used in ferrovanadium or as a steel additive. Another use is as vanadium pentoxide.Cerium (Ce) 22,886 Cerium is used as a catalyst converter for carbon monoxide emissions, as an additive in glass for reducing UV transmission, and in carbon-arc
lighting.Cobalt (Co) 16,940 The main uses of cobalt are in battery chemicals for NieCd, Ni-metal hydride and Li-ion battery types, superalloys, hard materials, catalysts, and
magnets.Yttrium (Y) 16,039 Yttrium is used for energy-efficient fluorescent lamps, in the treatment of various cancers, in aerospace surface and barriers, as a superconductor,
in aluminum and magnesium alloys, and in-camera lenses.Neodymium
(Nd)14,880 Neodymium is used to create high-strength magnets for computers, cell phones, medical equipment, electric cars, wind turbines, and audio
systems. It is also used in the glass and ceramic industries.Lanthanum (La) 10,253 Lanthanum is used in nickel metal hydride rechargeable batteries for hybrid automobiles, in high-quality camera and telescope lenses, and in
petroleum cracking catalysts in oil refineries.Scandium (Sc) 9,359 Scandium is used to increase strength and corrosion resistance in aluminum alloys, in high-intensity discharge lamps, and in fuel cells to increase
efficiency at lower temperatures.Niobium (Nb) 4,823 Niobium is used in high strength low alloy (HSLA) steels as ferroniobium and in superconducting magnets.Antimony (Sb) 3,751 Principal uses for antimony are in alloys with lead and tin, and in lead-acid batteries.Samarium (Sm) 3,456 The main use of samarium is in cobalt-samarium alloy magnets for small motors, quartz watches, and camera shutters. Samarium is also used in
lasers.Gadolinium
(Gd)3,357 Gadolinium is mainly used for NdFeB permanent magnets, lightning applications and in metallurgy.
Praseodymium(Pr)
3,245 Praseodymium is used in NdFeB magnets, ceramics, batteries, catalysts, glass polishing and fiber amplifiers.
Dysprosium(Dy)
2,705 Dysprosium is used mainly and almost inclusively in NdFeB magnets.
REEs (total) 82,254
Table 2Available and emerging technologies for CRMs processing.
CRMs Production process
Rare earthelements
- Acidic leaching-cryogenic crystallization-solvent extraction from mine tailings with apatite and monazite. (Peelman et al., 2016).- Bioleaching for REEs extraction from low-grade sources. (Peelman et al., 2014).- Solvent extraction to recover REEs from mine tailings of gold and tellurium mining (Tunsu et al., 2019).-Use of solvent impregnated resins (SIR) to recover REEs from low concentration solutions (Onishi et al., 2010; Sun et al., 2009; Yoon et al., 2016)
Antimony - Crushing and pyrometallurgical methods for primary ores (Anderson, 2012).-Crushing and hydrometallurgical methods like leaching and electrodeposition (Anderson, 2012)
Cobalt - Bioleaching of sulfidic tailings of iron mines. (Ahmadi et al., 2015).- Mineral beneficiation, comminution, flotation, smelting, leaching or refining for sulfide ores (European Commission, 2017b).-Calcination, pyrometallurgical process, hydrometallurgical methods for lanthanides ores (European Commission, 2017b)
Niobium -Gravity separation, froth flotation, magnetic and electrostatic separation, and acid leaching depending on the ore (European Commission, 2017b)Vanadium - Extraction of vanadium as a co-product to iron from vanadium slag includes bearing, roasting, acid leaching solvent extraction, ion exchange, and
precipitation (Xiang et al., 2018).- Desliming-flotation from low-grade stone coal (European Commission, 2017b).-Preform reduction process (PRP) based on a metallothermic reduction of vanadium pentoxide (V2O5). (Miyauchi and Okabe, 2010).
Table 3CRMs prices in July 2018.
Critical material Price ($US/kg)a Critical material Price (US$/kg)a
Antimony 8.51 Neodymium metal � 99.5% 68.0Cerium metal � 99.5% 7.00 Neodymium oxide � 99.5% 66.7Cerium oxide � 99.5% 5.59 Praseodymium metal � 99% 125.00Cobalt 87.5 Praseodymium oxide � 99.5% 81.6Dysprosium metal � 99% 268.57 Samarium metal � 99.9% 15Dysprosium oxide � 99.5% 226.80 Scandium metal � 99.9% 3,458Gadolinium metal � 99.9% 44.00 Scandium oxide � 99.95% 1,079Gadolinium oxide � 99.5% 20.94 Vanadium (as V2O5 80%) 40.00Lanthanum metal � 99% 7.00 Yttrium metal � 99.9% 36.5Lanthanum oxide � 99.5% 7.80 Yttrium oxide � 99.99% 4.60
a Sources: (Mineralprices.com, 2018), (Thenorthernminer.com, 2018), (LME, 2018).
N. Araya et al. / Journal of Cleaner Production 263 (2020) 121555 5
maintenance, spare parts, and indirect costs (Bhojwani et al., 2019).The first option assessed is the production, using mine tailings
as a source, of the following rare earth oxides (REOs): cerium,lanthanum, neodymium, yttrium, samarium, gadolinium, praseo-dymium and dysprosium. Scandium is also considered as REE but ithas different properties and a different production process, whichis why it was not assessed togetherwith the abovementioned REEs.
The second option assessed is vanadium as the production ofvanadium pentoxide (V2O5). It is due to the fact that vanadium isthe main CRM found TSFs in the Antofagasta Region (see Table 1).
3.3.1. Feasibility of producing rare earth elements using minetailings as a source
For REOs production, we have considered only REEs found inlarger quantities. Due to the lack of data about similar projects thatuse mine tailings or industrial waste as source material, we useddata from a Canadian project that produces rare earth oxides(Hudson Resources Inc, 2013) from primary sources to produce ofneodymium, praseodymium, lanthanum, and cerium. Data used forNVP calculation are shown in Table 4.
The price used to calculate NPV corresponds to the weightedaverage for REOs; cerium, lanthanum, samarium, gadolinium,praseodymium, dysprosium, and yttrium oxide, which is 37 USD/kgof REOs produced, 40% was discounted to reflect the differencebetween REO concentrate and separated individual rare earth oxideprices, so the price used for NPV calculations is 22 USD/kg, as in thereport it was used as a reference price. The grade of REEs corre-sponds to the average REEs grade in all the deposits analyzed. In themine tailings covered by the analysis, the average grade is lowerthan in most primary ore processing projects, so the productionwas reduced accordingly.
It is important to note that operating costs and capital costs arereferential values. In the case of mine tailings, costs related toextracting mineral ores should not be considered since tailings arematerials that have already been mined and processed.
The NPV is 672,987 USD which means that the projected earn-ings generated for this proposed REOs production exceed theanticipated costs and the overall value for the project is positive.However, even though the NPV is positive, its value is too low toinvest in a project of such a magnitude. The IRR is 10.03% which isalmost the same as the discount rate chosen for the project, thisconfirms that the project is not highly profitable. Cash inflows andoutflows are included as supplementary material.
3.3.2. Feasibility of producing vanadium using mine tailings as asource
Vanadium is the main CRM found in mine tailings in the Anto-fagasta Region. There are 46,110 tons of vanadium in inactive TSFs,but active tailings in this area have the potential for ca. 900, 000tons of vanadium.
Capital and operating costs for vanadium production are takenfrom a preliminary economic assessment study for the Gibellini
vanadium project (Lee, 2018). This project has been designed as anopen pit heap leaching operation to obtain vanadium pentoxide(V2O5). The Gibellini project is designed for processing of low-grademinerals, so it is suitable for mine tailings, but in this study, pro-duction is reduced because the grade in mine tailings is lower inmine tailings. The values used for the calculation of NPV and IRR aregiven in Table 5. The values of NPV and IRR for vanadium produc-tion from Chilean mine tailings are shown in the supplementarymaterial.
The NPV is 76 million US$ and the IRR is 21%, these valuesindicate that the project is profitable as the NPV is positive and theIRR is higher than the discount rate. Cash inflows and outflows areshown as supplementary material.
3.4. Sensitivity analysis
In this study, a sensitivity analysis was performed on four pa-rameters: capital cost, operating cost, critical materials price, andthe effect of the discount rate on NPV for the examined options. Theobjective of the sensitivity analysis is to understand the uncertaintyin the NPV for the examined parameters. These parameters werechosen because they are the key components in the DCF method.
Sensitivity analysis determines how different values of one ormore independent variables affect a dependent variable under agiven set of assumptions. Sensitivity analysis is the last stage of theprocess of assessing and selecting a technological alternative(Ib�a~nez-For�es et al., 2014). Sensitivity analysis studies how severalsources of uncertainty contribute to the entire uncertainty of amathematical model.
In the DCF method, the discount rate is the rate used to convertthe future value of a project cash flows to today’s value. The dis-count rate is adjusted to the risk associated with a project. There-fore, the higher the risk, the higher the discount rate (Kodukula andPapudesu, 2006). Risk is associated with the uncertainty of aproject. In business, risks may have a positive or negative effect. Thediscount rate was varied to acknowledge that mining projects dealwith uncertainties that can be included in the model by choosing ahigher discount rate.
Mining commodity prices always show greater volatility thanthose of any other primary products (Foo et al., 2018). Prices ofcritical materials may experience price spikes due to their insta-bility caused by the risk of supply disruption. Critical materials haveinelasticity element in their prices, this means that the demand forthese materials is not highly affected by the price (Binnemans et al.,2013b; Leader et al., 2019). Critical materials are needed in tech-nologies, such as clean energy technologies, in which there are notsubstitutes for the critical materials needed (Leader et al., 2019).
The price of each critical material assessed was considered as animportant parameter that contributes to the overall uncertainty ofthe project.
Since capital costs and operating costs used in this study arereferential values, and they are further used as inputs in the DCF
Table 4Data for REOs project.
Data Value Unit
Capital cost 342,514,448 US$Life of mine 20 yearsOperating cost 13,080 US$/ton REOsREOs Price 22,000 US$/ton REOsProduction capacity 4,000 tons REOs/yearAnnual increase (OPEX) 1.5 %Annual increase (PRICE) 1.5 %Discount rate 10 %
Table 5Data for vanadium project.
Data Value Unit
Capital cost including 25% contingency 116,760,000 US$Life of mine 14 yearsOperating cost 14,767 US$/ton V2O5
Vanadium pentoxide price 40,000 US$/ton V2O5
Production capacity 1,000 tons V2O5/yearAnnual increase (OPEX) 1.5 %Annual increase (PRICE) 1.5 %Discount rate 10 %
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method, it was necessary to address the variability of the real valuesof these parameters vis-a-vis the values used here.
Capital cost, operating costs, and prices varied between�30 and30% of the original value. The discount rate varied between 0.05 and0.3.
The results of the sensitivity analysis for the REOs price areshown in Fig. 3. It can be seen that for every 5% increase in the priceof the REOs, the NPV increases by 38 million US$. NPV is highlysensitive to changes in REO prices. NPV becomes negativewhen theprice of REOs is below 22 US$/kg, making the project financiallyunviable.
The NPV is less sensitive to changes in operating costs thanprice; NPV decreases to 21 million US$ with an increase of 5% inoperating costs. The results of the sensitivity analysis of the NPV tothe capital cost show that as the investment cost increases by 5%,the NPV decreases by ca. 15 million US$.
The discount rate varied between 0.05 and 0.3. The NPV is not alinear function of the discount rate, the value considered was 0.1.When the discount rate is 0.11, NPV decreases by approximately 21million US$. With a discount rate higher than 0.1, NPV becomesnegative, making the project unviable.
Results of sensitivity analysis of NPV for vanadium pentoxideproduction are shown in Fig. 3. When the price increases by 5%,NPV increased by ca. 14 million US$. When the price drops by 26%,NPV becomes negative and the project unviable.
Results of the sensitivity analysis of NPV to operating costs showthat NPV is slightly sensitive to changes in operating costs. Whenoperating costs increase by 5%, the NPV decreases by ca. 5 millionUS$. Sensitivity analysis of the NPV to changes in capital cost showsthat with an increase of 5% in the capital cost, the NPV decreases byca. 5 million US$. The values of NPV are very similar for bothoperating costs and capital costs.
The sensitivity analysis of NPV to changes in the discount rate
shows that if the discount rate increases by 0.01 from the value of0.1 used to 0.11, the NPV decreases by 10million US$ approximately.When the discount rate is higher than 0.21, NPV becomes negative.
Results show that under certain prices, operating costs andcapital costs, it is possible to invest in producing CRMs using asecondary source such as mine tailings.
The parameters analyzed in the sensitivity study may changesimultaneously. Therefore, their interactions were analyzed usingdesign-of-experiments together with response surface methodol-ogy. In the analysis of the NPV of both projects, REOs productionand V2O5 production, four factors and three levels were considered.The factors are: the price, capital costs (CAPEX), operating costs(OPEX), and the discount rate (iÞ. The levels correspond to the valueused in the economic assessment, then low and high levels for thesame value were multiplied by 0.85 and 1.15, respectively, whichmeans the experimental design results are valid in the rangebetween�15% andþ15%. A percentage of 15%was chosen to ensurea good adjustment. The values tested for the discount rate are 0.05,0.1, and 0.15. ANOVA results show which parameters and in-teractions influence the NPV by analyzing the p-value. For the p-value < 0.01 all linear parameters and the interaction with thediscount rate were significant. Also, the statistical analysis confirmsthat price and the discount rate are the parameters exerting greaterinfluence. Regression models obtained have the following form:
NPV ¼ aþ b CAPEX þ c OPEX þ d priceþ e iþ f i2 þ g CAPEX i
þ h OPEX iþ j price i
The values for a; b; c; d; e; f ; g; h and j are �17.6, �0.9103,�59.55, 67.1, �1766, 14323, 0.0, 242.9, and �299.5 for REOs project,and 47.64, �0.9932, �12.572, 12.572, �1143.3, 5717, 0.828,49.63, �49.625 for V2O5 project, respectively. The units for NPV and
Fig. 3. Sensitivity analysis, a) Sensitivity of the NPV (REOs project) to the price of REOs, operating costs and capital costs; b) Sensitivity of NPV to discount rate in REOs project; c)sensitivity of NPV (vanadium project) to the price of V2O5, operating costs and capital costs; d) Sensitivity of NPV to discount rate in vanadium project.
N. Araya et al. / Journal of Cleaner Production 263 (2020) 121555 7
CAPEXaremillionUS$,OPEXandprice arekUS$/ton, and thediscountrate is dimensionless. The R-squared values or the coefficient of theregressions were R2 ¼ 98:17%, R2adj ¼ 97:99%, and R2pred ¼ 97:79%for REOs project, and R2 ¼ 99:95%, R2adj ¼ 99:95%, and R2pred ¼99:94% for the V2O5 project. The R2 for both projects are over 98%which means that at least 98% of the variation of the NPV can beexplained by the model. Also, excellent values of adjusted R2 andpredicted R2 were observed which suggests that the number of pa-rameters is themodel is correct and that themodel is able to producehigh quality predictions. The ANOVA results and Pareto graphics areincluded in the supplementary material. Also, supplementary mate-rial gives the results of the design-of-experiment and response sur-facemethodology for the IRRwhichbehavesdifferently fromtheNPV.
4. Discussion
Mine tailings are waste obtained from the processing of a rockwith a view to obtain one or more products that will be refined tofinally get a metal(s) that is needed. Tailings should be stored infacilities where they are disposed in accordance with the regula-tions binding in each region, otherwise, the consequences to theenvironment can be devastating.
The lack of a long-term consideration of the entire life-cycle of amine and the instability of mine projects contribute to irreversiblemineral losses and resource sterilization. With this knowledge inmind, further research should address new strategies to anticipatethe future use of material beyond the closing of a mine (L�ebre et al.,2017). Mine waste hierarchy goes from prevention as the mostfavorable option to treatment and disposal as the least favorableoptions; if waste cannot be prevented then reuse and recycling areneeded (Lottermoser, 2011). Nowadays most mine tailings go to thetreatment and disposal phase. In the Sustainable DevelopmentGoals, the World Economic Forum suggests the re-use of tailings,these goals are meant to be achieved by 2030 (World EconomicForum, 2016). The reprocessing of mine tailings is also anelement of the transformation from a linear to a circular economythat the mining industry must face. Reprocessing mine tailings toobtain critical materials reduces the dependency on reserveextraction (El Wali et al., 2019).
Other approaches to mine tailings management from a circulareconomy point of view include recovering water from mine tail-ings, which helps to reduce the reliance on seawater (Cisternas andG�alvez, 2018). Recovering water or reducing the amount of water intailing diminish the need to pump water, which decreases energyconsumption and greenhouse gas emissions involved in pumpingwater to high altitudes, where mines are usually located in Chile(Araya et al., 2018; Herrera-Le�on et al., 2019; Ramírez et al., 2019).Another approach is to use mine tailings as cementitious materialsand pigment for sustainable paints (Barros et al., 2018; Vargas andLopez, 2018).
There have been conducted several studies on new technologiesor processes to recover CRMs from secondary sources such as minewaste (Alcalde et al., 2018; Andersson et al., 2018; Figueiredo et al.,2018; Khalil et al., 2019; Markovaara-Koivisto et al., 2018; Peelmanet al., 2018). Most of these studies are carried out at laboratory andpilot plant scale. Nevertheless, the literature on the recovery ofCRMs from mine tailings is constantly growing. It is due to the factthat new sources of CRMs are urgently needed as their importancein the global economy is constantly growing. Moreover, the utili-zation of wastes such as mine tailings, instead of mineral deposits,is essential from a circular economy point of view. Therefore,extrapolation of the potential of these technologies is immenselyneeded.
Results show that mine tailings facilities of the copper industryin Chile store valuable elements such as CRMs. Therefore, the early
evaluation of geochemical content, identification of suitable tech-nologies, and an economic analysis will help to find more sus-tainable alternatives to CRMs production.
The DCF is a widely used method of financial assessment, but itis not a decisive metrics for making a final decision on real in-vestment. In order to ensure the robustness of assessment, sensi-tivity analysis was performed to analyze the effect of the possiblefluctuations of market prices, capital and operating costs on theanalyzed options of CRMs production. It has been found out thatthe discount rate and both capital and operating costs play criticalroles in economic decisions in different areas (Choi et al., 2018;Cisternas et al., 2014; Santander et al., 2014).
Reprocessing mine tailings will also have an impact on theenvironment. Due to the nature of chemical and physical processes,mineral processing is water and energy intensive, some quantitiesof solvents and reagents are used and at the end of the process,therewill still bewaste that should be stored in a tailing facility. Themining waste obtained after the reprocessing of tailings should bestored in a tailing facility complying with the regulations designedto protect people and the environment.
5. Conclusions
There are 696 tailings storage facilities in Chile, mainly fromcopper mining, which is the biggest mining industry in the country.The biggest TSF has the capacity to store 4,500,000,000 tons oftailings. Currently, there are some initiatives for recovering metalsof interest frommine tailings, but such initiatives are all in the earlystages of feasibility assessment. This study provides valuable in-formation for the assessment of the techno-economic feasibility ofindustrial-scale critical materials recovery from copper industrytailings.
Copper production will continue to grow as the copper gradedecrease. Therefore, the volume of mine tailings that are producedevery year will increase as well. Mine tailings are a worldwideenvironmental problem as they can generate acid drainage, andcause air pollution and soil contamination. Yet, mine tailingscontain several valuable elements, among them critical raw mate-rials. Therefore, the use of mine tailings as a secondary sourcewould help mitigate shortages in critical raw materials by mini-mizing the reliance on primary sources.
Chilean copper mine tailings have substantial economic poten-tial as a source of critical materials such as vanadium, cobalt, rareearth elements and antimony. Minerals contained in Chilean minetailings from copper production are mostly silicates with a lowgrade of CRMs; currently, no approved projects exist that considermine tailings as a source of CRMs. Although mine tailings have alow grade of CRMs, their already stored quantity is enormous. Inaddition, prices of critical rawmaterials can be very high, and thesefactors could make a future production of CRMs from mine tailingsfeasible.
Two options of producing CRMs using mine tailings wereassessed; production of rare earth oxides (REOs) and production ofvanadium pentoxide (V2O5). The DFC method was used to evaluatethe economic feasibility of both operations. The NPV and IRR for theproduction of REOs are positive, which means that the project isfeasible. Nevertheless, the NPV is low for an investment of this scaleand the IRR is close to the discount rate value. The sensitivityanalysis of the NPV of REOs production from mine tailings showedthat NPV is highly sensitive to the discount rate and REO prices.Results of the ANOVA confirm that the discount rate and price arethe most significant variables influencing the NPV behavior.
Vanadium pentoxide production is feasible for an investment of14 years, as the NPV is 76 million US$ and the IRR IS 21% for V2O5production. Vanadium is the main CRMs found in tailings in the
N. Araya et al. / Journal of Cleaner Production 263 (2020) 1215558
Second Region in Chile. It is concluded that producing CRMs usinginactive tailings and later tailings from the active mining processesmay be a feasible option to ensure profitable use of mine tailingsand to diversify CRMs supply.
Declaration of competing interest
The authors declare that they have no known competingfinancial interests or personal relationships that could haveappeared to influence the work reported in this paper.
CRediT authorship contribution statement
Natalia Araya: Conceptualization, Methodology, Validation,Formal analysis, Investigation, Writing - original draft, Visualiza-tion. Andrzej Kraslawski: Conceptualization, Methodology,Writing - review & editing, Supervision. Luis A. Cisternas:Conceptualization, Validation, Formal analysis, Writing - review &editing, Visualization, Supervision, Funding acquisition.
Acknowledgments
This publication was supported by Agencia Nacional de Inves-tigaci�on y Desarrollo de Chile (ANID), AnilloeGrant ACM 170005. N.Araya thanks the ANID (2017, No. 21170815) for a scholarship insupport of her doctoral studies. L.A.C. thanks the supported ofMINEDUCUA project, code ANT1856 and Fondecyt program grantnumber 1180826. The authors are grateful to Peter Jones for his helpin editing the paper.
Appendix A. Supplementary data
Supplementary data to this article can be found online athttps://doi.org/10.1016/j.jclepro.2020.121555.
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PUBLICATION III
Araya, N., Ramírez, Y., Kraslawski, A., Cisternas, L.A.
Feasibility of re-processing mine tailings to obtain critical materials using real options
analysis (submitted)
Submitted in Sustainable Development
For Peer ReviewFeasibility of re-processing mine tailings to obtain critical
materials using real options analysis
Journal: Sustainable Development
Manuscript ID SD-20-0738
Wiley - Manuscript type: Research Article
Keywords: critical materials, real options, circular economy, mine tailings valorization, mine tailings management, net present value
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Feasibility of re-processing mine tailings to obtain critical materials using real
options analysis
Abstract
The re-processing of mine tailings to obtain critical materials could reduce the mining of new
deposits as well as ensure the profitable use of the waste materials. Though, it requires
large scale industrial installations and the development of specialized technologies to obtain
critical materials. New investment in mining activities is an operation, engaging for
considerable financial resources involved. The scale of such an endeavor makes a new
mining activity a high-risk operation due to several uncertainties present. Therefore, there is
an acute need to use new tools to assess the risk associated with the planning and
development of new mining activities.
This study introduces a framework to evaluate the economic risk related to the re-processing
of mine tailings to obtain critical materials. The framework, based on real options analysis
(ROA), and sensitivity and uncertainty analysis, was applied to analyze the profitability of
using mine tailings as a source of critical materials in the Chilean mining industry.
Results show that tailing storage facilities in Chile have some stocks of critical materials, like
scandium, whose extraction could be profitable. For the data used, the results of uncertainty
and sensitivity analyses show that capital expenditure has a more significant influence than
the other variables. Therefore, for the case of mine tailings re-processing, it is essential to
develop processes and technologies that enable lower capital expenses.
Keywords: Critical Materials; Real Options; Circular Economy; Mine Tailings Valorization; Mine
Tailings Management; Net Present Value
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1. Introduction
Critical materials (CMs) are vital for the functioning of modern society. They are fundamental
to the production of a broad range of goods and applications in our everyday life. Some raw
materials are more important than others due to their role in digital technologies, low-carbon
technologies, and sustainable mobility (David & Koch, 2019; Mathieux et al., 2017; X. Wang
et al., 2017). According to European Commission, critical raw materials are a group of raw
materials possessing two common characteristics: they have a high economic importance
to European Union and their supply is associated with high risk (European Commission,
2017b). The recent list made by European Commission includes elements such as rare
Earth Elements (REEs), vanadium, cobalt, platinum group metals, among others (European
Commission, 2017b).
Currently, extracting raw materials and metals from ore bodies of declining ore grade means
potentially bigger mine size generating more waste, overburden to the environment, higher
consumption of energy, water, and auxiliary materials which overall produce severe
environmental consequences and larger political risks (de Koning et al., 2018; Mudd, 2010;
Northey, Mudd, Saarivuori, Wessman-Jääskeläinen, & Haque, 2016; Žibret et al., 2020).
Furthermore, by 2050 the overall demand for metals will rise by a factor of 3-4 (de Koning
et al., 2018). When a mine has exhausted its resources whose extraction is economically
viable, an alternative is to close it and then reopen when the market and technology
conditions enable a profitable re-processing of tailings (Northey et al., 2016).
Long-term supply of metals highly depends on actual and expected prices, cumulative
availability curve, and new mining technologies (de Koning et al., 2018; Gordon, Bertram, &
Graedel, 2007; Tilton & Lagos, 2007; Yaksic & Tilton, 2009). Additionally, the development
of new high-tech technologies might lead to disruptive demand change (Tukker, 2014);
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meanwhile, it may take ten years or more to open new mines and adjust production (de
Koning et al., 2018).
Mine tailings are waste obtained after the processing of some minerals to acquire one or
more elements of interest. They are composed of a mixture of heavy metals, water, sand,
and fine-grained solid material, and generally are deposited in ponds without further
treatment (Babel, Chauhan, Ali, & Yadav, 2016; Santibañez et al., 2012; L. Wang, Ji, Hu,
Liu, & Sun, 2017).
Mine tailings deposits may contain many valuable elements as has been shown in several
studies (Alcalde, Kelm, & Vergara, 2018; Andersson, Finne, Jensen, & Eggen, 2018;
Figueiredo et al., 2018; Khalil et al., 2019; Khorasanipour & Jafari, 2017; Macías-Macías,
Ceniceros-Gómez, Gutiérrez-Ruiz, González-Chávez, & Martínez-Jardines, 2019;
Markovaara-Koivisto et al., 2018; Medas, Cidu, De Giudici, & Podda, 2013). In the particular
case of Chilean copper mine tailings, 0.82% are metals, non-metals, and metalloids, 0.01%
rare earth elements, and the rest major rock-forming elements (SERNAGEOMIN, 2017).
Nowadays, mine tailings are increasingly often seen as a potential source of raw materials,
and secondary sources are attracting more and more attention due to the benefits of a
circular economy approach (Jeswiet, 2017; Kinnunen & Kaksonen, 2019).
Mine tailings could be re-processed to extract CMs. This study aims to propose a framework
to assess the feasibility of re-processing mine tailings to obtain CMs. The presented
methodology is illustrated by the set of unique data applicable to Chilean mine tailings.
However, thanks to its generality, the proposed approach could be applied in other mine
tailings deposits where geochemical data are available. For example, the contents of CMs
in mine tailings have been already measured in some deposits in Finland, Sweden, Portugal,
Indonesia, and Mexico (Ceniceros-Gómez, Macías-Macías, de la Cruz-Moreno, Gutiérrez-
Ruiz, & Martínez-Jardines, 2018; Hällström, Alakangas, & Martinsson, 2018; Markovaara-
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Koivisto et al., 2018; Peelman, Kooijman, Sietsma, & Yang, 2018; Szamałek, Konopka,
Zglinicki, & Marciniak-Maliszewska, 2013; Tunsu, Menard, Eriksen, Ekberg, & Petranikova,
2019).
The research questions that this study seeks to answer are:
• Is it economically feasible to invest in a project developed around the idea of re-
processing mine tailings to obtain critical materials?
• How can real options analysis improve the decision to invest in a project using mine
tailings as a source of critical materials?
• How can the net present value variables influence real options performance?
The framework developed in this study is applied to a case study based on active mine
tailings located in northern Chile. This area features several mining projects based on
copper resources, leaving tremendous volumes of tailings that are stored without any
economical purpose.
The novel contribution of this article consists in considering ROA and sensitivity and
uncertainty analysis to give flexibility to the economic assessment of mine tailings re-
processing, acknowledging the uncertainties involved. Net present value (NPV) is calculated
using the DCF method as a starting point, then with ROA, different outcomes for an
investment project are estimated (Arnold, 2014; Brandão, Dyer, & Hahn, 2005; Kodukula &
Papudesu, 2006; Trigeorgis, 1996). The viability of mining investments depends on
variables that have high uncertainty as to market prices of metals. In the case of re-
processing mine tailings, technology developments and business model development are
still needed. To study the influence of several variables on NPV outcome, Monte Carlo
simulation is used to perform sensitivity and uncertainty analysis.
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1.1. The current state of mine tailings re-processing technologies
The annual amount of mine tailings generated by the mining industry exceeds 10 billion tons
(Adiansyah, Rosano, Vink, & Keir, 2015) and is expected to be growing because of the
increasing production forecast by 2035 the volume of tailings will double (CESCO, 2019).
Due to higher demand for mineral products and lower grades of ore as a result of which
more materials will have to be processed in more energy-intensive processes (C. Wang,
Harbottle, Liu, & Xu, 2014). Particularly, Chile has 6,500 million m3 of mine tailings and has
an approved capacity of over 14,470 million m3 (SERNAGEOMIN, 2019a).
Mine tailings contain several CMs, even if their content is low, the volumes of mine tailings
are big enough to consider re-processing (Binnemans, Jones, Blanpain, Van Gerven, &
Pontikes, 2015; Careddu, Dino, Danielsen, & Přikryl, 2018). Several studies analyze the
geochemical content of mine tailings to demonstrate that they contain CMs and point out
that tailings could be re-processed in the future (Ceniceros-Gómez et al., 2018; Dino, Mehta,
Rossetti, Ajmone-Marsan, & De Luca, 2018; Markovaara-Koivisto et al., 2018; Moran-
Palacios, Ortega-Fernandez, Lopez-Castaño, & Alvarez-Cabal, 2019; Tunsu et al., 2019).
Rare earth elements (REEs) are considered CMs due to their importance for generation of
clean energy and technologies essential for the transition to a low carbon economy. The
dominant position of China as the main producer, strong dependency of industrialized
countries on imports, geopolitical factors, and high specificity are additional factors
contributing to their criticality (European Commission, 2017a; Tunsu et al., 2019). The
world’s REEs reserves are found in the Inner Mongolia region of North China, with 59.3% of
world amount (Zhang, Liu, Li, & Jiang, 2014).
The prospect of using waste like metal scrap or mine tailings for obtaining REEs is gaining
attention since it reduces the dependency on primary sources. Several studies are drawing
attention to the possibility of re-processing mine tailings to get REEs using hydrometallurgy
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processes (Borra, Pontikes, Binnemans, & Van Gerven, 2015; Peelman et al., 2018;
Peelman, Sun, Sietsma, & Yang, 2016; Zhang et al., 2014).
Sustainable development components involved in mine tailings management strategy
should include energy, water, technology, environmental impact, cost (Adiansyah et al.,
2015), and policy. The valorization of mine tailings appears a critical component to achieving
a circular economy model in the mining industry, which needs to improve its processes to
minimize the environmental impacts of mining waste (Lèbre, Corder, & Golev, 2017; Tayebi-
Khorami, Edraki, Corder, & Golev, 2019). The valorization of tailings is still in the early
stages, but it is expected to improve in the future (Kinnunen & Kaksonen, 2019).
1.2. Project valuation tools
Traditional valuation tools, such as the DCF method, are static methods that do not consider
the uncertainty of the variables used to estimate the profitability of an investment (Arnold,
2014; Brandão et al., 2005; Kodukula & Papudesu, 2006; Trigeorgis, 1996).
Investments in the mining sector are capital intensive and mostly irrevocable with a limited
economic life span. Their economic viability depends on the uncertain world market price
and on how project risks emerge (Guj & Chandra, 2019). The project value is determined by
the commodity market and flexibility inherent in the metal mining system to respond to
uncertainties (Savolainen, Collan, & Luukka, 2017). The available future metal prices can
be used as certain in the project valuation process, where their maturity is maximum
between two to five years (Savolainen, 2016).
Project valuation techniques that ignore the real option nature of the project are widely used
in the mining industry, e.g., NPV, IRR, and static DCF (Savolainen, 2016). However, static
NPV is used as a benchmark for a real NPV option and option agreement methods (Arnold,
2014). DCF method treats future cash flows as deterministic values. Methods to include
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uncertainty in the result of NPV are: increasing the discount rate, applying sensitivity
analysis, comparing pessimistic and optimistic cash flows, or to use scenario planning to
estimate expected cash flows (Gaspars-Wieloch, 2019).
There are many approaches to analyze cost-intensive investments under the conditions of
uncertainty (Cristóbal et al., 2013). One of the methods gaining popularity is ROA as it is
being applied in different fields (Insley, 2002; Nelson, Howden, & Hayman, 2013; Regan et
al., 2015; Schatzki, 2003; Slade, 2001). Real options are a right, not an obligation, to
undertake business initiatives connected with tangible assets (Kodukula & Papudesu, 2006;
T. Wang & Neufville, 2005). Real options acknowledge managerial flexibility and readiness
to adjust investment projects due to future uncertainty and the changing environment,
involving possible managerial options that can reshape a project and adapt it to changing
conditions to maintain or enhance its profitability (Trigeorgis, 1993). Real options for a
project exploit the flexibility of sequential investment with flexible strategies and the
capability to delay decisions in an engineering system to react to an uncertain outcome;
where the changes depend on exogenous and endogenous uncertainties, so it is hard to
make credible value estimates (Guj & Chandra, 2019). Common attributes of real options
valuation design include identification of sources of uncertainty, available real options
recognition, modeling of uncertain variables, and real option valuation (Kozlova, 2017).
Methods used to evaluate real options are decision trees, Monte Carlo simulations, and the
Black-Scholes model (Arnold, 2014; Collan, 2011; Kodukula & Papudesu, 2006).
ROA is of rising importance in metal mining to assess possible future metal scenarios to
cope with mining projects under growing market uncertainty and project complexity. The real
options valuation method aims to protect and increase the economic return from a project
(Savolainen, 2016) and is applied predominantly in investment project valuation (Kozlova,
2017).
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1.3. Sensitivity and Uncertainty Analysis
A project is based on many inputs that are uncertain, such as production costs, price of
materials and equipment, and sales volume. The analysis and modeling of uncertainty
enhances the ability to make appropriate decisions. The need to analyze uncertainties
comes from the awareness that data abundance does not necessarily provide certitude, and
sometimes can lead to errors in the decision-making process (Attoh-Okine & Ayyub, 2005).
Due to uncertainty, there is no project without risk, and the uncertainty could be caused by
the different factors, e.g. lack of information or data (Munier, 2014).
Sensitivity analysis examines the response or reaction of an output variable, such as the
NPV to the variations of input variables, such as price or sales volume, etc. (Munier, 2014).
Sensitivity analysis methods explore and quantify the impact of possible errors in the input
data on predicted model outputs (Loucks & van Beek, 2005). Sensitivity analysis is used in
a broad spectrum of disciplines to study how various sources of uncertainty in a model
contribute to the model’s overall uncertainty. On the other hand, uncertainty analysis
assesses the impact of ambiguous values of parameters on the final results (Cacuci, 2003).
Sensitivity analysis may be performed together with uncertainty analysis to ensure the
quality of the model and the transparency of the decision-making process (Borgonovo,
2017).
Monte Carlo simulation methods are tools widely used to perform sensitivity and uncertainty
analysis (Attoh-Okine & Ayyub, 2005). Monte Carlo simulation can be used for risk analysis
by modeling the probability of the different outcomes of a process; it can be used as a
valuation tool for projects (Arnold, 2014; Collan, 2011; Kodukula & Papudesu, 2006). Monte
Carlo simulation randomly generates values of the uncertain variables within a certain range
to simulate the potential outcomes (Kodukula & Papudesu, 2006; Mun, 2002). Sensitivity
and uncertainty analysis can be used as complementary tool to the DCF method and ROA
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to study the effect of the inputs on NPV (De Reyck, Degraeve, & Vandenborre, 2008;
Gaspars-Wieloch, 2019; Kodukula & Papudesu, 2006; Pivorienė, 2017).
2. Methodology
The profitability analysis of mine tailings processing requires the identification of
geochemical characteristics of the tailing deposit, also named tailing storage facility (TSF).
Mineral characteristics and concentration of elements that are present in the TSF along with
the mass of tailings accumulated in the deposit allow estimating the quantity of each CM
(Araya, Kraslawski, & Cisternas, 2020; Markovaara-Koivisto et al., 2018; Moran-Palacios et
al., 2019).
In the economic analysis, in-situ value is estimated by multiplying the total mass of a specific
CM by its price. Total mass is calculated based on the average concentration and mass in
a TSF (Araya et al., 2020; Markovaara-Koivisto et al., 2018). DCF method is used to
estimate the NPV of a project for extracting one or more CMs from one of the TSF analyzed.
Criteria used to choose which CM could be extracted include concentration, total mass, and
price. In some cases, finding such data, as well as get access to data for estimating CAPEX
and OPEX for each CM is rather difficult.
Subsequently, an overview of technologies suitable for re-processing mine waste stored in
a TSF to extract the CMs is needed. If these technologies are still not applicable on an
industrial scale, then, technologies used to process primary ores to obtain such CM are
considered, the same goes for economic inputs such as CAPEX, OPEX, and production.
When dealing with mine waste, some consideration needs to be given to aspects, such as
a lower grade of elements contained in it (Araya et al., 2020; Binnemans et al., 2015;
Falagán, Grail, & Johnson, 2017). Mine tailings are already in the form of a paste or slurry,
so there are no mining costs, which usually represent 43% of operating costs in a mine
(Curry, Ismay, & Jameson, 2014).
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Sensitivity and uncertainty analysis is applied to the NPV estimated by the DCF method.
ROA is applied using the NPV obtained with the DCF method using the method of risk-
neutral probabilities presented in. The binomial tree analysis is used to apply ROA. A
binomial tree is built by using the method of risk-neutral probabilities presented by Kodukula
and Papudesu (2006); this methodology involves adjusting the risk of the cash flows across
the lattice with risk-neutral probabilities and discounting them at a risk-free rate (Kodukula
& Papudesu, 2006).
2.1. Discounted Cash Flow (DCF) method
DCF method is based on the calculation of NPV of a project over its entire life cycle
accounting for the investment and the free cash flows throughout its whole life (Kodukula &
Papudesu, 2006).
𝑃𝑟𝑜𝑗𝑒𝑐𝑡 𝑁𝑃𝑉 = 𝑃𝑉 𝑜𝑓 𝑓𝑟𝑒𝑒 𝑐𝑎𝑠ℎ 𝑓𝑙𝑜𝑤𝑠 𝑖𝑛 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑝ℎ𝑎𝑠𝑒 ― 𝑃𝑉 𝑜𝑓 𝑖𝑛𝑣𝑒𝑠𝑡𝑚𝑒𝑛𝑡𝑠 𝑐𝑜𝑠𝑡𝑠 (1)
According to the DCF method, if the project NPV is greater than zero, it means that the
project revenues are greater than the costs of the project, so it is financially attractive
(Arnold, 2014; Kodukula & Papudesu, 2006).
Present value (PV) is the estimation of costs and net revenues of the development
production phase. These are the free cash flows over the entire life cycle of the project
(Kodukula & Papudesu, 2006).
𝑃𝑉 =𝐹𝑉
(1 + 𝑟)𝑛 (2)
Where FV is the future value, r is the discount rate per time period, and n is the number of
the time period.
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To estimate NPV of a project, capital expenses (CAPEX) and operating expenses (OPEX)
of a project with similar characteristics in terms of ore grade and production capacity are
used. CAPEX may include treatment equipment, water intake structure, site preparation,
concentrate discharge system, auxiliary equipment, piping, valves, among other cost items
(Bhojwani, Topolski, Mukherjee, Sengupta, & El-Halwagi, 2019). OPEX include labor,
energy cost, chemicals, maintenance, spare parts, and indirect cost (Bhojwani et al., 2019).
The following equation was employed to estimate NPV and PV of a project based on the
use of mine tailings:
𝑐𝑎𝑠ℎ 𝑓𝑙𝑜𝑤 = (𝑝𝑟𝑖𝑐𝑒 ∙ 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 ― 𝑂𝑃𝐸𝑋 ∙ 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 ―𝐶𝐴𝑃𝐸𝑋
𝑛 ) ∙ (1 ― 𝑡𝑎𝑥𝑒𝑠) +𝐶𝐴𝑃𝐸𝑋
𝑛 (3)
𝐴𝑛𝑛𝑢𝑖𝑡𝑦 = 1 ―1
(1 + 𝑅)𝑛
𝑅
(4)
𝑃𝑉 = 𝑐𝑎𝑠ℎ 𝑓𝑙𝑜𝑤 ∙ 𝑎𝑛𝑛𝑢𝑖𝑡𝑦 (5)
𝑁𝑃𝑉 = 𝑃𝑉 ― 𝐶𝐴𝑃𝐸𝑋 (6)
Where n is the time of the project development, and r is the discount rate or interest rate.
The equations formulated replace calculating cash flows for every year of the project and
then adding them up to calculate the PV.
2.2. Real Options Analysis (ROA)
A ROA or real options valuation (ROV) is performed alongside with the DCF method; ROA
is applied using PV of free cash flows and NPV of a project calculated with DCF method as
a basis to estimate different outcomes (Kodukula & Papudesu, 2006). Traditional options
used in ROA are the option to defer or the option to wait to invest in a project, expand a
project, and an option to choose between projects (Kodukula & Papudesu, 2006).
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In this study, a binomial tree is used, which is a decision tree. The binomial model can be
solved using risk-neutral probabilities or market-replicating portfolios, both have the same
theoretical framework leading to the same solutions but with different mathematical
approaches (Kodukula & Papudesu, 2006). The inputs required to build a binomial tree and
calculate the option value are the risk-free rate (r), the value of the underlying asset (S0)
which is the PV of the expected free cash flows based on the DFC method, the cost of
exercising the option (X) which is the investment required, the life of the option (T), the
volatility factor (σ) which is a measure of the variability of the underlying asset during its
lifetime, and the time frame chosen for the calculations (δt) (Kodukula & Papudesu, 2006).
In Figure 1, a generic binomial tree of 2 steps is shown.
The up (u) and down (d) factors are functions of the volatility of the underlying asset, and
they are described as follows:
𝑢 = exp (𝜎 𝛿𝑡 ) (7)
𝑑 =1𝑢 (8)
The risk-neutral probability is a mathematical intermediate that allows for discounting the
cash flows using a risk-free interest rate. The risk-neutral probability (p) is defined as follows:
𝑝 =exp (𝑟𝛿𝑡) ― 𝑑
𝑢 ― 𝑑 (9)
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Figure 1: Generic recombining binomial tree (source: adapted from Kodukula and
Papudesu, 2006).
The option to wait also called the option to defer should be included in every project. A
company may prefer to wait before it invests in a project with either negative or marginal
NPV when it is highly uncertain that the project will achieve a high NPV in the future
(Kodukula & Papudesu, 2006). An example is a delay in mining a deposit until the market
conditions are favorable.
3. Case study
Chile has a large mining industry (Cisternas & Gálvez, 2014; Jane, 2003); mining represents
9.8% of the gross domestic product, and copper mining is responsible for 8.9% (COCHILCO,
2019). Chile has a rich territory endowed with porphyric deposits in terms of copper and
molybdenum (Oyarzún & Oyarzún, 2011). In 2018, Chile produced 5,872 million of fine
copper tons equivalent to 28.3% of global production, which made it the No. 1 world producer
of copper (SERNAGEOMIN, 2019a). The country is also the second world producer of
molybdenum, a copper by-product, with 60,248 tons representing 20.4% of the world
production.
The production of copper in Chile is concentrated mainly in the northern and central parts of
the country, where 40% of the worldwide reserves of copper are found (SERNAGEOMIN,
2019a). Copper can be found in sulfide ores and oxides. Sulfide ores are the primary source
of copper. Copper is obtained from sulfide ores by flotation to concentrate copper; mine
tailings are the waste of flotation.
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In Chile, there are 740 tailing storage facilities. Most of them come from copper mining, and
all are registered in a national cadaster kept by The National Service of Geology and Mining
- SERNAGEOMIN, out of which geochemical characteristics of 634 tailing deposits are
available online, 56 chemical elements have been analyzed, including 25 CMs. The content
of silicon dioxide is also analyzed because silicon metal is a CM that can be obtained from
silicon dioxide (SERNAGEOMIN, 2019c).
The Antofagasta Region is located in the Atacama Desert in northern Chile, and it holds the
largest tailings deposits of the country, including the biggest one with the capacity of 4,500
million tons (SERNAGEOMIN, 2019b). This study is focused on active tailing deposits, i.e.,
those currently used until they reach the legally allowed capacity. These tailing deposits are
Laguna Seca, Talabre, Esperanza, Sierra Gorda, and Mantos Blancos; the location of these
mine tailings deposits is shown in Figure 2. The capacity of the active mine tailings analyzed
in this study is presented in Error! Reference source not found..
Figure 2: Active TSF located in the Antofagasta Region, source: (SERNAGEOMIN,
2019b).
4. Results
Despite low concentrations of CMs found in mine tailings, these appear as possible sources
of CMs due to their availability in larger volumes and the ease with which they can be treated
on-site using the geochemical analysis provided by SERNAGEOMIN, which shows the
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average concentration of 56 chemical elements present in tailing facilities
(SERNAGEOMIN, 2019c). The total mass of each CM contained in the TSF was calculated
using its average concentration and the mass of the tailing facility. The in-situ values were
calculated using current prices, in some cases when it was not possible to find the price of
the CM as metal, the price of the oxide was used, so these are estimates based on the
available data provided by the United States Geological Survey in their report about
commodities released in 2019 (U.S. Geological Survey, 2019), the prices that were not
available in this report were taken from websites providing metal prices (Metal Prices, 2019;
Statista, 2019). The average concentration, total mass, and price of each CM of Esperanza
TSF appear in Error! Reference source not found. as an example. The same calculations
for the other four TSF analyzed can be found in Supplementary Material.
The profitability of using mine tailings as a source of CMs is analyzed using a ROA to
produce a CM using the examined TSF. The ROA is illustrated using the option to wait if the
investment is not an attractive option according to the results of the DFC method. Reasons
to wait include situations when capital cost and/or operating costs are too high, and the
prices of CMs are not high enough to obtain a positive NPV for the project.
The example used to illustrate this analysis is the production of scandium metal. Scandium
was chosen as a CM to be extracted from mine tailings out of Table 2 due to its elevated
price and the quantity present in the TSF, as well as the availability of data about CAPEX
and OPEX for a similar project of scandium production. Scandium is not reported to be
recovered from mine tailings; it is produced mainly from primary resources and the principal
source for scandium is metal imports from China (U.S. Geological Survey, 2019), from REE
and iron ore processing in Bayan Obo, China (European Commission,
2017b).Hydrometallurgy processes have been suggested to recover scandium from
secondary sources.
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4.1. Discounted cash flow method
Data from an actual scandium feasibility study were used to estimate PV and NPV of a
mining project consisting of producing scandium (Investorintel, 2014). The following
considerations were made to adapt the data to the case of mine tailings: concentration of
scandium in the tailing deposits is 26 ppm, ten times lower than in primary sources of
scandium, mining costs are discounted considering that there is no need to incur these costs
when dealing with mine tailings, lower production is considered according to the demand for
scandium metal, an updated price is considered. The input parameters are listed in Error!
Reference source not found..
The DCF method using a risk-adjusted discount rate for five years showed that the PV for
the project is 195 million USD, an NPV -138 million, for an investment of 333 million USD. If
the DCF method is screened for a longer period, e.g., ten years, it shows a higher value of
PV and NPV, 244 million USD, and -89 million USD, respectively. It is essential to point out
that traditional mining projects, planned for 15 or 20 years, are used for calculating NPV
because they are long term investment projects, but in the case of a project based on mine
tailings and CMs it is more reasonable to use a shorter period.
4.2. Uncertainty and sensitivity analysis of NPV
To study the effect of uncertainties of input variables and their distribution on NPV results
and their sensitivity. Sensitivity and uncertainty analysis was performed using Monte Carlo
simulation in RStudio. NPV was modeled using equations (6) to (9), which is a function of
the inputs used to calculate the NPV; in this analysis, taxes, and depreciation were included.
The inputs ranged between a minimum and maximum value, considering a range 20%, ±
the following values for each output were considered: price 4.4– 6.6 million USD/ton, CAPEX
268 – 402million USD/ton, OPEX 4400 – 6600 USD/ton, discount rate 0.08 – 0.12,
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production 6.4 – 9.6 ton, and the number of years of the project was constant since NPV is
highly sensitive to changes in the period of investment. The analysis was made for an
investment of five and ten years. Fifty thousand simulations were run.
Summary of results shows, for an investment of 5 years, a minimum value of -229.03 and
maximum value of -32.5 for NPV and a mean and median that are almost equal, - 137.33
and -137.47, respectively.
Histogram and boxplot are graphical methods to test normality. The histogram purpose is to
graphically summarize the distribution of a data set; it shows the frequency of NPV results.
The histogram is presented as supplementary material.
The Boxplot represents the summary and the representation of primary data; it allows to
visualize the minimum, lower quartile, median, upper quartile, and a maximum of a data set
(Spitzer, Wildenhain, Rappsilber, & Tyers, 2014). Boxplots as a visualization method enable
to see characteristics that might not be seen otherwise, and they are a straightforward and
informative method of data interpretation (Sun & Genton, 2011). 3 presents the boxplot, BC
stands for the base case which is the case using a ± 20% variation for each input, then in
the rest of the boxplots uncertainty of one input was expanded leaving the other inputs in
the ±20%previously settled, so in C1 the price was wider, between 3.3 and 7.7 million
USD/ton, leaving the rest of the variables in the previous range of ±20%. In C2 CAPEX was
varied between 201 and 469 million USD; in C3 OPEX was varied between 3300 and 7700
USD/ton; in C4 the return rate was varied between 0.06 and 0.14; and in C5 annual
production was varied between 4.8 and 11.2 tons.
.
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Figure 3: Boxplot of net present value uncertainties for different scenarios of a 5-year
investment scandium project.
To perform global sensitivity analysis, the function of R-studio Soboljansen implements the
Monte Carlo estimation of Sobol´-Jansen indices with independent inputs. Figure 4 shows
the main and total effects of the inputs. It can be seen that the main effect and the total effect
of each variable are very close which indicates that there are no significant interactions
between them, and it confirms results obtained by the boxplot that CAPEX in this investment
case has the most significant effect on NPV.
Figure 4: Sobol´-Jansen indexes for 5- years investment scandium project.
4.3. ROA using a binomial tree method
ROA is performed using a binomial decision tree methodology presented by Kodukula and
Papudesu (2006), for an investment of five years and an investment of ten years. The
input parameters and option parameters are shown in Error! Reference source not
found..
For the two cases, five years and ten years, option parameters are the same. Next, the
development of a decision tree for an investment of five years is explained; the procedure
is the same for both cases. With the option parameters, the binomial tree is built by
calculating asset values and options values over the life cycle of the option; asset values
are obtained after multiplying S0 to u and d raised to the power indicated in each node. Those
are the numbers on top of every node of the binomial tree. For example, in node S0u5, the
expected asset value is 874 million USD.
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Option values are the bottom numbers in the tree. The option to wait expires at the end of
the binomial tree, so a decision cannot be made after the time that the decision tree takes.
Option values at year five are calculated as the expected asset value of each node minus
the cost of exercising the option, which corresponds to the investment. So, for example, in
node S0u5, the expected asset value is 874 million USD, the investment is 333 million USD,
then the net asset value is 541 million USD. The decision in node S0u5 would be to invest.
If the option value is negative, then the option value is equal to zero, because a real option
is a choice, not an obligation. The option to invest is exercised at nodes where the option
value is not zero.
Option values are the numbers below each node, and they are calculated with backward
induction. Figure 5 and Figure 6 show the binomial tree for five years and ten years’
investment, respectively. Each node represents value maximization to invest in that point or
to wait until the next period; at every node, there is an option to either invest in the project
or the option to wait until the next period, until the option expires, the net asset value, in this
case, represents the NPV. Since the option is evaluated at five-year intervals, in node S0u5,
see Figure 5 the decision is to invest in this point, and the option value is 541 million USD,
but in year five, there are also nodes where the option value is zero. In node S0u3d2, the
expected asset value is 263 million, for an investment of 333 million, the net asset value is
-70 million. Hence, the option value in this point is zero, so the decision in this node would
be not to invest.
Figure 5: Binomial tree for the option to wait for five years to invest in the scandium
project.
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Next on the intermediate nodes, the expected asset value for keeping the option open is the
discounted weighted average of potential future option values using the risk-neutral
probability that value, e.g., at node S0u4 is:
𝑝(𝑆0𝑢5) + (1 ― 𝑝)(𝑆0𝑢4𝑑) ∙ 𝑒𝑥𝑝( ―𝑟𝛿𝑡) (10)
In this node, if the option is exercised the payoff would be 647 million, resulting in a net asset
value of 314 million, by investing 333 million, since the net asset value obtained by keeping
the option open is higher, 330 million, then the option to invest is not exercised. In some
intermediate nodes, the expected asset value is lower than the investment, which results in
a net loss, then the decision at that node is to wait, which means that the option value is $0.
The option valuation binomial tree is completed until year 0.
In each node, the upper numbers represent the expected future values of the underlying
asset during the option life cycle as it evolves according to its cone of uncertainty, see Figure
5. For example, in year 2, the project is estimated to produce a total payoff between 107
and 355 million USD, at the end of year five, the payoff is between 44 and 874 million. The
bottom numbers represent option values on the maximization of investing in that point or
applying the option to wait until the next period. The option expires in the fifth year because
it is framed in such a way that it considers competitive forces and uncertainty in the market.
Based strictly on DCF results, the payoff of the project will be 195 million USD, resulting in
a negative NPV of -38 million USD. If the decision is based exclusively on the NPV result,
then the decision would be not to invest.
Real options analysis provides an additional value of 33 million USD, considering a net
present value of -138 million USD, the added value with real options analysis is 171 million
USD. The same analysis was made for a 10-year investment as shown in Figure if the same
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investment is screened to 10 years, NPV based on the DCF method is -89 million, ROA
analysis gives an added value of 105 million.
Figure 6: Binomial tree for the option to wait for ten years to invest in the scandium project.
5. Discussion
Waste valorization is a crucial component that the mining industry must do to shift from a
linear economy to a circular economy (Khaldoun, Ouadif, Baba, & Bahi, 2016; Kinnunen &
Kaksonen, 2019). There are different approaches to mine tailings valorization, e.g., the
simplest and traditional one is to recover water or to decrease water usage in the tailing
stage. Other strategies consist in recovering metals from mine tailings or using mine tailings
as a construction material (Ahmari & Zhang, 2012; Lam, Zetola, Ramírez, Montofré, &
Pereira, 2020).
The cyclic nature of the supply and demand for specific metals whose production is
extremely concentrated in geographic terms and controlled, and where society cannot solely
rely on ore mining (Kirchherr, Reike, & Hekkert, 2017) makes sticking to circular economy
principles, such as effective recycling and processing of secondary sources, a must (Tunsu
et al., 2019). Mine tailings are now seen as a potential source of several metals and minerals
(Binnemans et al., 2015; Tunsu et al., 2019). The valorization of mine tailings is at an early
stage of research; there is a lack of technology that would enable transferring knowledge
from the laboratory scale to an industrial level (Kinnunen & Kaksonen, 2019).
Results show that tailing storage facilities of copper mines in Chile contain significant
quantities of CMs. Therefore, the early evaluation of the project's profitability and feasibility
to recover CMs from mine tailings help in finding alternatives, considering the flexibility given
by real options, even to postpone the investment. Additionally, it represents a secondary
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source of CMs, decreasing the dependence on reserve extraction (El Wali, Golroudbary, &
Kraslawski, 2019).
Economic gains from the recovery of CMs come with added benefits of reducing the volume
of mine waste. Additional benefits can be achieved if, as a result of the processing of mine
tailings, these can be chemically and physically stabilized, reducing the costs of mine
closure by decreasing environmental impact and health consequences. A significant
advantage is to recover water for mining reuse from mine tailings while reducing its reliance
on seawater (Cisternas & Gálvez, 2018; Ramírez, Cisternas, & Kraslawski, 2017). Another
essential factor is decreasing energy consumption and greenhouse gas emissions involved
in pumping seawater to high altitudes for hyperarid locations, where mining companies are
located (Araya, Lucay, Cisternas, & Gálvez, 2018; Ramírez, Kraslawski, & Cisternas, 2019).
It is also essential to notice that obtaining CMs from mine tailings reduces the processing of
comminution stages (Falagán et al., 2017), minimizing energy consumption and greenhouse
gas emissions. Notably, greenhouse gas emissions can vary for every CM, e.g., in the case
of phosphorus the greenhouse gas emissions rise gradually in the mining phase and
increase exponentially in the recycling stage (Rahimpour Golroudbary, El Wali, &
Kraslawski, 2019); in the case of niobium, mining represents 21% of greenhouse gas
emissions, 72% are generated in the production stage and recycling from scrap accounts
for only 7% (Rahimpour Golroudbary, Krekhovetckii, El Wali, & Kraslawski, 2019); on the
other hand, recycling of lithium from lithium-ion batteries generates greenhouse gas
emissions by 16-20% higher than its primary production (Rahimpour Golroudbary, Calisaya-
Azpilcueta, & Kraslawski, 2019).
The analysis made on the in-situ value of TSFs of active tailings of northern Chile shows
that they contain the considerable quantities of several critical metals such as REEs,
vanadium, cobalt, silicon metal and scandium. The advantages of mine tailings re-
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processing include the recovery of desirable metals in one location, ensuring land
reclamation, reduction of landfill areas, diminishing the concentration of harmful compounds,
and no need to open new mines (Binnemans et al., 2013; Farjana, Huda, Parvez Mahmud,
& Saidur, 2019; Ganguli & Cook, 2018).
Since mine tailings have been already part-processed, by comminution, the costs, both
CAPEX and OPEX, of extracting metals from tailings could be attractive in comparison to
development of a new project based on primary ores (Falagán et al., 2017). For the data
used, the results of the sensitivity and uncertainty analysis shows that CAPEX has a greater
influence than the other studied variables. Therefore, it is justified to develop processes and
technologies that enable lower capital expenses. If time is a variable in an investment
project, then time and CAPEX are both variables with greater influence.
ROA brings in additional value, so decision-makers can explore alternatives while waiting to
invest or decide to abandon a project. While waiting for the uncertainty to clear off, to re-
estimate the project payoff (Arnold, 2014; Kodukula & Papudesu, 2006). If the payoff
continues to be unfavorable, the decision may be to keep waiting; otherwise, if the conditions
to invest in scandium production from mine tailings are favorable with a high expected
payoff, the decision would be to invest. ROA calculations are a supplement to traditional
valuation methods such as DCF based NPV (Brandão & Dyer, 2005; Kodukula & Papudesu,
2006).
ROA is usually framed in shorter periods than the ones used for long term investments
(Kodukula & Papudesu, 2006), in this study five and ten-year time horizons were used to
frame the project; for both periods, NPV is negative, but if the uncertainty clears out, the
project may be feasible. Framing the investment in a longer period, such as ten years, but
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not as long as twenty years, allows decision-makers to wait to invest in a project when
investment can be regained.
The methodology presented in this study was validated using copper tailings of northern
Chile as case study. The geochemical content of tailings may vary from one geographical
area to another depending on the type of mineral deposits. In consequence, the content of
the valuable elements will be different depending on the mine tailing analyzed. The
geochemical results of mine tailings analysis are essential to perform profitability analysis of
their re-processing.
On the limitations of the study, it considers only the economic aspect of valorization of the
project to obtain CMs from mine tailings. However, it should be mentioned that the
valorization of the tailing may be profitable in the most cases if environmental, social and
safety factors are considered, e.g. chemical and physical stabilization, land reclamation,
social license to operate. As was previously stated by Kinnunen and Kaksonen (2019)
technology development is still much needed to add value to mine tailings. Therefore, a
multidisciplinary approach is imperative to develop projects based on re-processing mine
tailings. Future research should include the assessment of environmental impact of the re-
processing of mine tailings, as they can contain heavy metals that could be scattered during
the process. Some tailings deposits in Chile need urgent intervention due to the presence
of one or more heavy metal (Lam, Montofré, et al., 2020).
The main contribution of this study is to provide a methodology to assess the feasibility of
re-processing of mine tailings by taking into account the flexibility needed for investing in the
mining projects. This approach is based on use of DCF method combined with ROA and
sensitivity and uncertainty analysis.
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6. Conclusions
Mine tailings need to be adequately stored; otherwise, they can lead to massive
catastrophes that can affect human settlements and the ecosystem inflicting irreparable
damage. Proper mine tailings management includes their chemical and physical
stabilization; however, resource recovery can also add profitability to the last stage of mine
closure. Moreover, the re-processing of wastes contributes to limiting the number of new
mining projects based on virgin resources, which usually have a considerable environmental
impact. The assessment of the economic potential of wastes is a crucial activity facilitating
the implementation of the circular economy principles. This work presents universal,
quantitative methodology for the assessment of the economic potential for the recovery of
valuable elements from mine tailings.
In this study a novel approach to assess the profitability of mine tailings to obtain CM is
introduced. A framework that includes ROA, sensitivity and uncertainty analysis is proposed,
which allows for adding flexibility, contrary to traditional valuations tools.
The mine tailings deposits have usually lower concentrations of CMs than ore mines.
However, the mine tailings are an attractive alternative for exploitation as they are stored in
deposits with large volumes and hence, having a considerable potential for the production
of CMs.
The additional factor is the fact that tailings have been already pre-processed, e.g. in
comminution processes. The case study features Chilean copper mine tailings, to analyze
the ones with significant volume among the 740 tailing storage facilities present in the
country. Mine tailings deposits that are currently active were analyzed, using geochemical
content information provided by The National Service of Geology and Mining
(SERNAGEOMIN). These deposits contain important quantities of rare earths elements,
cobalt, vanadium, silicon, and barium. Therefore, these copper mine tailings could have
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substantial economic potential as secondary sources to obtain CMs. It is well-known that
some CMs are more economically attractive than others, due to their high market price.
Therefore, demand, supply risk and economic importance of each CM should be considered
when analyzing the profitability of mine tailings re-processing.
DCF and ROA were applied to analyze the feasibility of producing scandium by re-
processing the tailing deposits featured in the case study. Additionally, sensitivity and
uncertainty analysis was performed to study the influence of price of commodity, CAPEX,
OPEX, and discount rate. These evaluations were used as a complement to the DCF and
they include Monte Carlo simulation of the NPV and the representation of the results as
boxplot and Sobol´-Jansen indices. The DCF method showed a negative NPV for
investments of 5 and 10 years. The results of the sensitivity and uncertainty analysis indicate
that CAPEX has a greater influence on NPV. ROA adds flexibility and the possibility, as an
alternative, to choose to wait until the uncertainty is reduced. Based on the calculations, it
is concluded that using a real options approach to analyze an investment for the production
of CMs from mine tailings is a useful instrument, considering the high uncertainties in the
market and the development of process technology.
When traditional methods, such as the DCF method, indicate that a project is not
economically attractive, a ROA reevaluates the project by considering options such as wait
until the project is economically feasible. The option of waiting is an interesting alternative
in the case of resource valorization of mine tailings. It is due to the lack of technological
development and economic business models for treating mine tailings as a source of CMs.
Therefore, more research on these aspects is still needed.
Mine tailings as a secondary source for obtaining valuable elements is still a novel option
that needs to be developed on an industrial scale. Therefore, there are many opportunities
for improvement that may eventually lead to the successful valorization of mining waste. A
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multidisciplinary approach is essential to secure the success of re-processing of mine
tailings to obtain CMs.
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Table 1: Allowed capacity in active tailings storage facilities in Antofagasta Region,
source:(SERNAGEOMIN, 2019b).
Tailing storage facility (TSF) 106 t (until 23.04.2019) 106 t (allowed capacity)
Laguna Seca 1,302.24 4,500
Talabre 1,792.72 2,103.95
Sierra Gorda 142.80 1,350
Esperanza 240.50 750
Mantos Blancos 130.71 138.2
Table 2: Concentration, content, and in-situ values of critical materials in Esperanza tailing
storage facility.
Critical materials Average concentration (ppm)
Mass (t) Price (USD$/t)
CM in-situ value (10 6 USD$)
Vanadium 160 120,000 30,865 3,704
Cobalt 11 8,250 72,753 600
REE – Yttrium 49 36,750 36,000 1,323
Niobium 21 15,750 21,000 331
Barium 185 138,750 180 25
REE† – Scandium 26 19,500 5,420,000 105,690
Hafnium 3.88 2,910 775,000 2,255
Silicon metal 224,632 168,474,330 3,042 512,563
REE – Lanthanum 15.96 11,970 2,000 24
REE – Cerium 32.32 24,240 4,830 117
REE – Praseodymium 4.31 3,233 92,400 299
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REE – Neodymium 17.46 13,095 51,000 668
REE – Samarium 3.65 2,738 14,850 41
REE – Europium 1.06 795 56,000 45
REE – Gadolinium 3.43 2,573 22,330 57
REE – Terbium 0.49 368 647,500 238
REE – Dysprosium 2.87 2,153 280,700 604
REE – Holmium 0.55 413 38,000 16
REE – Erbium 1.71 1,283 140,000 180
REE – Thulium 0.26 195 not available 0
REE – Ytterbium 1.6 1,200 not available 0
REE – Lutetium 0.23 173 1,258,000 217
REE – mischmetal 85.9 63,630 20,300 1,292
†RRE: rare earth element
Table 3: Input parameters for the Discounted Cash Flow method
Input parameters Value Unit
Capital expenses 333 million USD
Operating expenses 5,700 USD/t
Price of scandium metal 5.42 million USD/ t
Ore grade 26 ppm
Production 8 Ton/year
Discount rate/ interest rate 0.1
Period 5 &10 years
Taxes rate 0.35
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Table 4: Input and option parameters for ROA.
Input parameters Unit
S0 (5 years) 195 million USD
S0 (10 years) 244 million USD
T (time to expiration) 5/10 years
X 333 million USD
σ (volatility) 30 %
r (risk-free rate) 5 %
Δt (time step) 1
Option parameters
u (up factor) 1.35
d (down factor) 0.74
P (risk-neutral probability) 0.51
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Generic recombining binomial tree (source: adapted from Kodukula and Papudesu, 2006).
109x85mm (96 x 96 DPI)
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Active TSF located in the Antofagasta Region, source: (SERNAGEOMIN, 2019b).
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Boxplot of the net present value uncertainties for different scenarios of a 5-year investment scandium project.
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Sobol´-Jansen indexes for 5- years investment scandium project.
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Binomial tree for the option to wait for five years to invest in the scandium project.
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Binomial tree for the option to wait for ten years to invest in the scandium project.
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