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Innovation in the Mining Industry: Technological Trends and a Case Study of the Challenges of Disruptive Innovation

• Open access
• Published: 23 July 2020
• Volume 37 , pages 1385–1399, ( 2020 )

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• Felipe Sánchez   ORCID: orcid.org/0000-0003-2009-6591 1 &
• Philipp Hartlieb   ORCID: orcid.org/0000-0002-6256-2696 2  

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Innovation plays a critical role in the mining industry as a tool to improve the efficiency of its processes, to reduce costs, but also to meet the increasing social and environmental concerns among communities and authorities. Technological progress has also been crucial to allow the exploitation of new deposits in more complex scenarios: lower ore grades, extreme weather conditions, deeper deposits, harder rock mass, and high-stress environments. This paper discusses the importance of innovation for the mining industry and describes the mechanisms by which it is carried out. It includes a review of the drivers and actors involved and current trends. The digital transformation process that the industry is going through is analyzed, along with other relevant trends that are likely to shape the mining of the future. Additionally, a case study is presented to illustrate the technical and economic implications of developing a disruptive innovation project.

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1 Introduction

Over the past decades, the mining industry has had to face a challenging scenario for its operation. Improving productivity to overcome natural factors such as decreasing ore grades, deeper deposits, and harder rock mass, combined with an increasing environmental and social awareness, has boost the industry to constantly work to enhance their processes along the whole value chain. In this, innovation plays a crucial role by providing suitable solutions to surpass these difficulties, ensuring the continuity and sustainability of the mining activity.

There has been a historical debate whether mining is indeed an innovative industry or not. It is often perceived as a conservative sector, where innovation takes only a secondary position in the concerns of companies. But at the same time, many argue that mining is more likely to be comparable with high-tech industries, considering that it utilizes vanguard technologies in its processes, such as automated or remote-controlled machinery, and advanced monitoring systems for the collection and analysis of large amounts of data [ 1 ].

Nowadays, many relevant actors of the industry claim that mining is going through the first stages of a deep changeover from the hand of digital transformation. It is said that this process could change how mining is done, passing from human-run operations to autonomous or semi-autonomous remote-controlled mines. Independent if fully automated operations are achieved in the near future or not, the digital transformation is already impacting the industry and will continue doing so.

This article aims to characterize the innovation environment in the mining industry, specifically:

Importance of innovation for the mining industry: relation between labor productivity and innovation

Dynamics of innovation in the industry: drivers and actors

Current trends and future of the mining industry

It will contribute to improve the understanding of the dynamics and mechanisms involved in the innovation processes, along with analyzing the current status and expected future of the mining industry, in terms of technological advance.

The scope of this paper covers the mining industry in general and its entire value chain (exploration, extraction, processing, and smelting and refining). However, by the nature of the topic, artisanal and small-scale mining have been mostly excluded from the analysis, considering the historical low degree of technological specialization in this sector. Also, for the illustration and exemplification of certain points made in this document, a special focus has been put in the large-scale copper mining sector and the main copper producer countries.

2 Innovation in the Mining Industry

Cambridge Dictionary defines innovation as a new idea, method, design, or product, as well as its development or use [ 2 ]. In general, innovation can be understood as a process of change, through which a new idea or solution is applied in a good, service, or productive procedure to create value and meet new requirements from customers and higher safety or environmental standards, among other goals.

In this section, the importance of innovation for the mining industry is discussed. Firstly, the relation between innovation and labor productivity is examined. Then, a general view regarding the innovation dynamics within the industry is provided, exploring the main drivers and actors involved.

2.1 Innovation and Labor Productivity

A first approach to understand the relevance of innovation within the industry can be made through the analysis of labor productivity. Technological advances usually have an impact on the output, allowing larger production rates while maintaining a similar workforce, or directly reducing the needed personnel by the automation of processes. Nevertheless, changes in labor productivity of a mine may be caused by a series of other reasons. Natural factors, such as decreasing ore grade and deepening of deposits, mean that a larger amount of material in more complex situations must be removed to obtain the same final metallic output, thus impacting negatively on labor productivity, while, in an aggregated view (e.g., when analyzing the mining industry of an specific country), the discovery and exploitation of new and better deposits can also positively impact the overall labor productivity [ 3 ]. On the other hand, in a high-price mineral commodities scenario, companies are willing to compromise their costs in order to increase production (because it is profitable) and, therefore, reduce their labor productivity [ 4 ].

Several authors have analyzed the behavior of labor productivity in specific mining industries in an attempt to isolate the effect of innovation. Tilton et al. [ 5 ] first introduced the importance of innovation and new technologies in the growth of labor productivity while studying the decline and recovery of the US copper industry during the 1970s, 1980s, and 1990s. The authors attributed most of the labor productivity increase in this period to the incorporation of the solver extraction and electrowinning technology (SX-EW), along with the use of larger trucks, shovels and drills, in-pit mobile crushers and conveyor belt systems, computerized scheduling of trucks, and real-time process controls.

In a later study, more concrete evidence regarding the previously mentioned was provided [ 6 ]. Since the exploitation of new deposits can have an impact on the aggregated labor productivity, the authors built two scenarios to analyze this index between 1975 and 1995: one, considering only the mines operating at the beginning of the studied period, and therefore, excluding the effect of new mines, and two, the actual situation, including both old and new operations. In Fig. 1 , the adjusted curve represents what labor productivity would have been if no new mines would have entered in operation in this period of time. As shown, adjusted and actual labor productivity resulted to be not so far different; thus, approximately 75% of the productivity growth in the US copper industry over those years came from productivity improvements at individual mines (i.e., innovation and technological advances), despite the exploitation of new deposits.

Labor productivity in the US copper mining industry, actual and adjusted to exclude the effects of changing location of output , 1975-1995. Modified from [ 6 ]

Under a similar methodology, the labor productivity growth in the Chilean copper industry during the 1978–1997 period was analyzed (Fig. 2 ) [ 7 ]. Their findings, though not as dramatic as in the US copper industry, showed that innovation and the introduction of new technologies were responsible for approximately a third of the productivity growth in the total period. Specifically, during the years prior to 1990, this factor accounted for the total growth, while in the 1990s, the development of new world-class mines (e.g., Escondida) turned over the scenario. Nevertheless, these results were coherent with the findings of previous studies on the US copper industry, regarding the role of innovation in improving the competitiveness of the mining industry.

Labor productivity for the Chilean copper industry, actual and constrained (or adjusted) assuming no change in the location of mine output 1978–1997 (tons of copper contained in mine output per copper company employee). Modified after [ 7 ]

More recent research on the copper industry of Chile and Peru has presented additional supporting evidence that, though not the only factor, innovation, including the adoption of new technologies and managerial changes, remains as a key element for the improvement of labor productivity [ 3 ].

When looking at the following time period (late 1990s to early 2010s), the situation presents a dramatic change. From 2005 onward, the average labor productivity of Chilean mines suffered a sharp decline, as shown in Fig. 3 . The same situation can be observed in other main mining countries, like Australia, Canada, and the USA (Fig. 4 ). Labor productivity in these countries started falling in the first years of the 2000s. This decline can be attributed to a combination of natural and economic factors. On one side, while reserves are depleted, ore grades tend to decrease and the operation advances to deeper locations, increasing hauling distances, stripping ratio, and geotechnical difficulties, all of which have a negative impact on labor productivity. On the other side, in a period of high mineral commodity prices, like the one that the industry went through during the second half of the 2000s and the beginning of the following decade, mining companies will favor production growth despite productivity [ 4 ].

Average labor productivity of Chilean mines for the period 1978–2015, measured as tons of mine production per worker. Modified after [ 4 ]

Labor productivity of the mining sector of selected countries, for the period 1995–2013. Annual value presented as a percentage of labor productivity in 1995 (100%). Modified after [ 4 ]

As presented, labor productivity is affected by a series of factors, mainly by natural characteristics of mineral deposits, market conditions, and innovation. While in periods of labor productivity growth it has been possible to isolate the positive effect of innovation, during declining cycles, this task turns more complicated. However, the fall in these periods is attributed mainly to natural and economic factors. In the meantime, innovation remains crucial to maintain the competitiveness of the industry, to the extent possible, providing the methods and tools to overcome the natural challenges faced by modern mines and exploit new and more complex deposits. In other words, while declining labor productivity may be inevitable during certain periods of time, the development and adoption of new technologies, along with innovation at a managerial level, are essential to maintain mining’s competitiveness through the different cycles.

2.2 Drivers for Innovation and Actors

As discussed in the previous section, innovation constitutes an important factor affecting the productivity of mining operations. Examples of technologies developed to improve the efficiency of processes, reduce costs, and in consequence enhance productivity are easily found. Hydrometallurgical production method SX-EW has been identified as a major contributor for productivity growth in the US copper industry over the last decades of the twentieth century [ 6 ]. Likewise, continuous mining equipment in underground coal mining, along with draglines and bucket wheel excavators in surface coal mining, were key advances to reach new levels of productivity in coal production. In smelting processes, the development of flash, and, more recently, bottom blowing furnaces, has had a great impact in reducing energy consumption and OPEX.

Besides boosting productivity, through innovation, it has been possible to unlock the potential of deposits that were technically infeasible to exploit by traditional methods. For example, preconditioning of the rock mass through hydraulic fracturing, confined blasting, or a mix of both has allowed the exploitation of deeper ore bodies, in high-stress environments.

Addressing safety and environmental concerns has been also a major driver for innovation. Over the recent decades, focus has been put on removing workers from critical activities through the automation of processes and the use of autonomous and semi-autonomous (remote-controlled) equipment.

Meeting more rigorous environmental regulations and attending the concerns of local communities are minimal requirements for maintaining the social license to operate. Therefore, innovation has been also aimed at developing cleaner and more environmentally friendly solutions in the whole value chain of the business, and not only to improve the efficiency and reliability of its processes [ 8 ]. Examples of these are the new tailings disposal methods that have been implemented to reduce the impact of mining on the environment, such as the thickened and paste tailings disposal. These methods improve water efficiency in their processes, reduce the requirement of surface for their disposition, and minimize risks of collapse, among other advantages over traditional methods.

Regardless, extractive firms have historically shown low levels of expenditure in research and development (R&D), often perceived as the main innovation-related index [ 8 ]. During the decades of the 1990s and 2000s, R&D intensity of relevant mining and mineral companies, understood as the R&D expenditure as a percentage of total revenues, was on average only approximately 0.5% [ 9 ].

Figure 5 shows the average R&D intensity for some of the largest mining companies, as revenue level refers, during the 2011–2018 period. Though presenting variation during the period, on average, this index has remained around 0.4%. These levels of R&D intensity are considerably low compared with other industries. For example, in 2015, pharmaceuticals and information and communications technology (ICT) equipment, the most R&D-intensive industries, reached levels of 25.1% and 24.7%, respectively. Moreover, the average R&D intensity in 2015, across all industries in OECD countries, was 5%, more than ten times the level of the selected mining companies [ 10 ].’

R&D intensity of five of the largest mining companies, based on 2018 revenues (companies selected according to availability of information i.e. R&D expenditure informed in annual reports, individualized and separated from exploration expenses). R&D intensity calculated as a percentage of total annual revenues for the 2011–2018 period (in the case of Zijin Mining, R&D intensity was calculated as a percentage of total operating income, according to data reported by the company). Data retrieved from annual reporting of companies Anglo American (available in: https://www.angloamerican.com/investors/annual-reporting ), China Shenhua Energy Company (available in: http://www.csec.com/shenhuaChinaEn/1382683238772/dqbg.shtml ), Codelco (available in: https://www.codelco.com/prontus_codelco/site/edic/base/port/memorias.html ), Rio Tinto (available in: https://www.riotinto.com/investors/results-and-reports-2146.aspx ), and Zijin Mining (available in: http://www.zijinmining.com/investors/Annual-Reports.jsp ).

Measuring the level of innovativeness of an industry by only examining R&D intensity, however, can lead to misinterpretation. Some authors argue that R&D expenditure fails to consider other activities that could be related to innovation efforts, such as engineering development, plant experimentation, and exploration of new markets. Also, R&D expenditure in general does not include mineral exploration expenses [ 8 ]. While these arguments may be reasonable, it is necessary to analyze in more detail how and by whom innovation is done in mining.

Whereas in the past mining companies would have tended to develop technology solutions in-house, over the last decades of the twentieth century the tendency changed. Economies of scale from using larger loading and hauling equipment had an important impact in improving productivity and reducing costs. Yet, these solutions came from equipment manufacturers, not from mining companies [ 1 ]. This is how outsourcing became a tendency among large producer firms, resulting in higher degrees of vertical disintegration [ 11 ]. Companies would focus on their core business, while relying on suppliers for the development of technological solutions, therefore avoiding the risks associated with the large investments involved. At the same time, in many cases, suppliers of such are also subcontractors for mining companies, handling construction and mining activities in projects and operations. These include the development of methods, techniques, and technologies to accomplish these tasks and therefore liberating their clients, the mining companies, from the technological concerns.

Leading technology suppliers, such as Sandvik, Epiroc, and Caterpillar, among others, have not only focused in the development of new equipment according to the technological and sustainability trends (currently, on automation and electromobility), but they have also put effort in the development of the proper digital systems for the operation and coordination of these machinery within the operations (e.g., AutoMine® from Sandvik).

Though large global suppliers are important actors for the development of new technologies, the outsourcing tendency previously mentioned has also opened the opportunity for the emergence of local knowledge intensive mining suppliers. These firms hold specific local knowledge that allows them to provide customized solutions for mining companies in niches that cannot be covered by the standardized products offered by large global suppliers [ 12 ].

Also, this outsourcing trend has promoted the creation of collaboration initiatives between large mining companies, local suppliers, and governmental and academic institutions for the development of technological solutions. Instances like these can be found in Australia, Chile, and Brazil [ 11 ]. In Chile, for example, the World-Class Supplier Program, a public-private partnership between the mining companies BHP, Codelco, and Antofagasta Minerals; Fundación Chile and other governmental institutions; and more than 75 local suppliers has already developed over a hundred innovation initiatives since it was launched in 2009. Though the program has had a positive impact in the development of the knowledge-intensive mining supplier sector in Chile, certain challenges need to be faced to bring this sector to the next level of progress. Among these challenges, it is necessary to escalate the program, promoting high-impact and long-term innovation projects, despite the usual incremental technological solutions developed until now [ 13 ].

Unlike most mining companies, the supplier sector holds in high priority the innovation agenda. A survey conducted on 432 firms from the Mining Equipment, Technology and Services (METS) sector in Australia, in 2015, revealed that for 63% of these companies innovation was core to their business strategy, driven mainly by a customer-focused vision, the necessity of staying ahead of the competition and direct solutions requirements from their customers [ 14 ].

A similar view is shared by the mining supplier sector in Chile. One hundred five of these companies were surveyed in 2019, revealing a high level of innovation-aimed expenditure. On average, they reported innovation expenses for 14.3% of 2018 revenues, reaching levels of 28.7% and 22.3% in the medium- and small-scale suppliers, respectively. Likewise, their innovation projects were driven mainly by direct solutions requirements from their customers, the necessity of staying ahead of the competition and by having innovation as core to their business strategy [ 15 ].

Besides the dynamics involved in the development of technologies, either by mining companies themselves or their suppliers, the mining industry is also recognized for its capacity to adopt technologies from other industries. ICTs have facilitated the introduction of important improvements in exploration techniques, mining, and processing. Simulations, sensor systems, automation and remote-controlled operations are some examples [ 8 ].

Nowadays, ICTs offer a new level of technological advance from the hand of digital transformation. The extractive industry finds itself in the early stages of adopting these new technologies. The full potential of their applicability for mining processes is yet to be unlocked. The implications of the current trends of Industry 4.0 for the mining industry are discussed and analyzed in the following section.

3 Current Trends and Mining of the Future

Defining a future view for an industry is not a simple task. Nowadays, the world is changing faster than ever before. New technologies are developed every day, impacting the way people live. The phrase “we live in a different world than the one where our parents grew up” does not completely cover the reality of the past few decades. For example, in current days, most people would not conceive their lives without their smartphones, and even though the first ones were commercialized in 1992, the massification of these devices came only a little more than a decade ago (e.g., the first iPhone was developed in 2007).

Nevertheless, in the case of the mining industry, it is possible to identify certain trends that can be of help to outline this future scenario. First and most evident, it is the major technological shift occurring across all industries: the so-called Fourth Industrial Revolution, or simply Industry 4.0, as the transition to the digital era. Then, social and environmental concerns are already compelling mining to look for safer, more efficient, and sustainable ways of conducting the business. Reduction of energy and water consumption, lower emissions, and waste generation are all factors that will be in the core of the “mine of the future.”

3.1 Digital Transformation in Mining

Over recent history and since the beginning of industrialization, several changes in production paradigms have taken place, promoted by the surge and application of novel technologies. As shown in Fig. 6 , the world has already seen three paradigm shifts, better known as industrial revolutions. Currently, a new transformation is in progress from the hand of cyber-physical systems and a set of new technology developments, e.g., automation, internet of things, and analytics [ 16 , 17 ].

Industrial revolutions

The Fourth Industrial Revolution brings a new concept of industry, also called Industry 4.0. This concept is based on an advanced digitization of production processes and the combination of internet-oriented technologies, allowing the connection between smart sensors, machines, and IT systems across the value chain. The implementation of these cyber-physical systems should bring a series of benefits, such as productivity increase by the automation of production and decision-making processes, reduction of waste, improvement of equipment utilization, and maintenance costs reduction. However, Industry 4.0 is not only about the adoption of new technologies, but it will also demand organizational changes, specialized knowledge, and expertise [ 16 , 17 ].

To achieve the scenario set by Industry 4.0, companies from all sectors, though at different speeds, are implementing the necessary changes at a technological and organization level. These changes constitute the process of digital transformation.

3.1.1 What Is Digital Transformation?

Though the term digital transformation (DT) has been extensively used in recent years, mainly to describe the adaptation process of organizations to new digital technologies, there is not a unique definition for it. On the contrary, there are many. Acknowledging this situation, and after an exhaustive review of DT-related literature, [ 18 ] offers the following definition: ”a process that aims to improve an entity by triggering significant changes to its properties through combinations of information, computing, communication, and connectivity technologies.”

The reason for the existence of various acceptations for DT may lie in the differences among industries: each sector operates in particular ways; therefore, each digital technology will have a different impact, depending on the industrial sector adopting it.

The specific information, computing, communication, and connectivity technologies involved in DT also vary from one industry to another. In the case of mining, however, it is possible to identify a set of tools that will and are already affecting the processes not only at the mine site but across the operational and corporate units within a firm.

3.1.2 Key Technologies in the Digital Mine

DT is a transversal process of change across the complete value chain of the mining industry, from the exploration to the production of final products, their commercialization, and even the closure of operation sites. Experts, companies, and government agencies have been discussing how the “digital mine” should look like while advancing forward in the DT process. Figure 7 shows how modern digital technologies are and will keep affecting the different areas of the business.

DT technologies in the different stages of the mining value chain. Based on [ 19 , 20 ]

As shown, novel technologies are producing operational changes across the value chain, and their use is not necessarily exclusive for a specific activity. For example, intelligent operation centers are being implemented for both extraction and processing operations. Likewise, augmented and virtual reality, along with digital twinning, are tools that will enhance the design and construction of mining projects (“Establish” in Fig. 7 ), and the extraction and processing operations.

While the view of the “digital mine” may vary among firms and organizations, it is possible to define a set of core technologies that represent the pillars of the DT in the mining industry [ 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 ]. These key elements are described below.

Automation, Robotics, and Remote Operation

These technologies might hold the highest level of implementation among the tools offered by DT. The first and more clear benefit of the automation of processes, use of robots in critical activities, and remote operation centers (ROC) is the improving of safety, by reducing the number of operators required in hazardous sites [ 25 ].

ROCs can also significantly reduce OPEX and CAPEX of mining operations. Since less workforce is needed at the mine site, fewer or none supporting infrastructure is required, such as housing installations, hospitals, or schools. Also, other expenses are reduced, such as transportation of operators. The impact on costs is larger as the location of the mine is more remote, distant, and isolated [ 25 ].

The use of autonomous equipment, such as hauling trucks, LHDs, and drillers, is expanding rapidly. For example, global equipment manufacturer Caterpillar has already provided more than 239 autonomous trucks for large-scale mining operations in Australia, Brazil, Canada, and the USA [ 28 ].

Similarly, Komatsu holds a total fleet of 141 autonomous trucks distributed in Australia, Canada, Chile, Japan, and the USA. In Chile, these vehicles operate in Codelco’s mine Gabriela Mistral. Over the 10 years of operation of the mine, the use of autonomous trucks has allowed a significant collision risk reduction and high levels of productivity and tires performance [ 29 ].

By February 2020, a total of 459 autonomous haul trucks were accounted as active in mining operations around the world [ 30 ]. Though these equipment still represent less than 1% compared with the total of manual trucks currently operating, Footnote 1 they are characterized as high year-to-year growth: 32% in the 2019–2020 period and higher rates are expected for the next years, from the hand of significant investments made by major companies such as BHP, Fortescue Metals Group, Rio Tinto, and Hancock Prospecting in Australia and Suncor Energy and Canadian Natural resources in Canada.

In general terms, besides the benefits in safety, autonomous equipment enhance productivity and reduce operational costs, by increasing equipment’s utilization (due to the continuous operation), reducing variability in the production outcome, and improving tires and components performances [ 20 , 29 ].

Internet of Things (IoT), Smart Sensors/Real-Time Data Capture

IoT is understood as a network of physical objects, such as sensors, equipment, machinery, and other sources of data. The elements connected to this network can then interact, exchange information, and act in a coordinated way [ 31 ]. Thanks to advances in IoT technology, nowadays, it is possible to establish low-cost networks. Additionally, the development of smart sensors allows real-time capture of data from machines and equipment across the operation. This generation of data is the base to conduct an integrated planning and control, considering the different units within the operation, and support the decision-making process [ 20 ].

Analytics, Artificial Intelligence (AI)/Machine Learning (ML)

Due to the digitization of processes, advances in IoT, and real-time data capture, mining operations have enormous amounts of data available regarding production, processes, and performance of machines, among others. Through advanced analytics methods, it is possible to transform this information allowing its use for a better planning of activities and to support fast and effective decision-making processes for the operation. Predictive models can also be developed to enhance maintenance of equipment, therefore improving productivity [ 21 ].

AI/ML methods are also being applied for mineral prospecting [ 32 , 33 , 34 ]. It is expected that these methods will optimize the prospection and exploration activities, reducing costs and improving their accuracy.

Digital Twinning

The concept of digital twinning refers to the construction of a digital model of the physical operation. This is possible using the geological and engineering information of the site, but more importantly, thanks to the real-time data generated from the sensors connected across the operation. With the digital twin of the mine, it is possible to perform simulations and predict potential failures or downturns in equipment performance. Thus, the digital twin constitutes a useful tool to improve operational planning and reduce operational costs, by avoiding unexpected interruption in production processes and optimizing the maintenance of equipment [ 20 , 21 ].

3.1.3 Current Status of DT in the Mining Industry

In its study of 2017, the World Economic Forum and Accenture estimated a potential benefit for the mining industry, as a consequence of DT, of US$ 190 billion over the period 2016–2025, equivalent to approximately 9% of the industry’s profit [ 26 ]. Correspondingly, in the USA, the mining industry has been included among the group of sectors with potential to increase productivity from the further digitization of its assets, customer relations processes, and transformations in its workforce [ 35 ]. These expectations are aligned with the results of a survey conducted by Accenture in 2014 among executives from 151 mining companies around the world. In this, 85% of the surveyed executives reported that their companies were strongly supporting internal DT initiatives and 90% that the DT programs were already elevated into strategies and high-level decision-making [ 25 ].

However, the level of overall digitization of mining is still low, when compared with other industries. By 2014, though DT was mentioned in six out of ten of some of the largest (by market value) global mining companies’ annual reports, Footnote 2 qualitative benefits from DT were reported only by three of them and only one presented actual quantitative gains [ 25 ]. This confirms that, though DT has claimed a relevant position among mining companies’ concerns, on average, the industry is still in the early stages of this transformation, and most of the potential benefits are still to be unlocked.

Correspondingly, a survey conducted on 105 companies from the mining supplier sector in Chile in 2019 revealed that 59% of them perceived a medium level of interest from the mining companies to incorporate DT-related technologies and 32% a low level of interest. Only 9% of the surveyed firms perceived a high level of interest from mining companies to incorporate these technologies in their operations (Fig. 8 ). Regardless, most of these suppliers are already developing or will develop in the next 5 years products or services incorporating technologies 4.0, being remotization, automation, smart sensors, and analytics the most frequent ones [ 15 ]

Level of interest of mining companies in Chile in 2019, perceived by the mining supplier sector, regarding the incorporation of DT-related technologies in their operations. Based on [ 15 ]

In general terms, though DT is frequently mentioned as one of the main concerns among most large-scale mining companies, which over the years has generated great expectations regarding its benefits, the overall level of digitization of the industry remains low. Nevertheless, there are several cases of mining operations where a high level of digitization and automation of its processes has been achieved. LKAB’s iron ore mines, Kiruna and Malmberget, located in northern Sweden, are operated under a combination of remote-controlled and fully automated equipment for drilling, blasting, and hauling processes. Moreover, full automation and electrification are core elements in the future plans for deeper levels, for which development KLAB has been working in close collaboration with high-tech companies, such as ABB, Epiroc, and the Volvo group [ 36 ]. Similarly, the Syama underground gold mine in Mali, owned by Resolute, constitutes the first fully automated mine, incorporating an automated haulage system, automated rehandle level, and mine digitization [ 37 , 38 ].

Likewise, some technologies present a greater level of adoption across the mining industry than others. For example, autonomous and semi-autonomous equipment, such as trucks, LHDs, drills, and trains, started to be tested more than a decade ago (in some cases, even before); some have been successfully operating for several years now and are rapidly spreading [ 28 , 29 , 39 ]. In the same way, many companies have implemented ROCs to control their operations remotely. In Chile, for example, Codelco has a ROC for its mine Ministro Hales and it is developing centers for three more of its divisions [ 40 ]. BHP has also implemented its Centre of Integrated Operations (CIO) in Santiago, Chile, from which it will coordinate all its operations in the region.

Smart sensors and monitoring systems are also already generating large amounts of data. However, the wide and successful application of advanced analytics to support and gradually automate the operational decision-making processes is still to come. Today, its use remains mainly in the construction of predictive models for maintenance purposes and the visualization of data to support human decision-making.

3.1.4 Challenges in the Implementation of DT

For the period 2019-2020, the “digital effectiveness” has been identified as the second most relevant risk for the mining industry [ 41 ]. It highlights the importance of advancing in digitization, as a necessity for companies to remain competitive. The main risk lies then on the fact that DT is often perceived as a task exclusive of the information technology (IT) area. Nonetheless, to achieve a truly effective and value-creative transformation, it must be carried out as a joint task across the organization, with a shared view of the business goals and a strong commitment from the top management. Otherwise, DT initiatives will remain as isolated IT projects, with no significant benefits considering the investments involved [ 22 , 23 , 41 ].

Ensuring the convergence of IT and OT (operational technology) is also key for a successful DT. These areas have traditionally worked by different paths: IT closely to corporate and support systems, while OT running core processes at the operation site. However, the automation of processes requires an integrated IT/OT management [ 20 ].

DT is a process of change that goes beyond technology. As mentioned in the first paragraph of this section, it requires coordination across the whole company. But it is also important to understand what this transformation will mean at an organizational level [ 22 ]. Structures will suffer changes by the automation of processes and introduction of new technologies and methods. For example, a recent study revealed that around 80% of the current labor competences in the mining sector in Chile will potentially change in the middle and long term as a consequence of the technological progress. Even more, at least 40% of them have a high probability of being replaced by automated processes [ 42 ]. This situation must be considered and evaluated. The new structures must be designed in advance and action must be taken to prepare the employees for these new arrangements. New knowledge and skills will be required, so the firms should also invest in the proper training programs to face DT.

Finally, in an increasing digital environment, a special focus must be put in cybersecurity. DT brings a wider connectivity among equipment and sensors but also between different business units. The company could then be exposed to greater risks of security breaches. For this reason, cybersecurity constitutes a fundamental element in DT [ 20 , 25 ]. In fact, [ 41 ] also classified this issue as the fourth most important risk for the mining industry in 2019–2020. To overcome this risk, a solid “cybersecurity culture” must be promoted in every level of the organization, incorporating new security-related practices in the daily responsibilities of the employees, along with the measurement of relevant KPIs and a periodical revision of the adopted strategies to evaluate their effectiveness and generate improvements, if necessary [ 41 ].

3.2 Mining beyond DT

In parallel with the technological wave brought by the digital transformation, a series of other trends have been gaining relevance in the mining industry over recent years. Driven by safety and environmental concerns, cost reduction, enhancement of efficiency, and productivity in the operation, or a mix of these motives, these trends are complementary to the technologies 4.0 and offer an idea of the future paths that mining might follow.

3.2.1 Electromobility

Electromobility, as the development and use of electric-powered vehicles, is a technological trend across industries. From personal-use cars and public transportation vehicles, to heavy machinery, electromobility offers an economical and more environmentally friendly alternative to the use of fossil fuels.

Mining is especially affected by this paradigm change. Most mobile equipment in mining operations has been historically powered by internal combustion engines (ICEs), using diesel fuel. While the impact of the negative aspects of these engines might be bearable in open pit operations, in underground mines, where ventilation can account for up to 25–40% of the total energy costs, the situation is different [ 43 ]. Diesel ICEs emit exhaust gases containing a series of pollutants, such as unburned hydrocarbons (HC), carbon monoxide (CO), nitrogen oxides (NOx), and diesel particulate matter (DPM). Additionally, a large amount of heat is also produced. All these elements increase the demand for fresh air flow in order to ensure a proper working environment for operators and equipment, having a significant impact on costs [ 44 ].

Moreover, due to the increasing environmental and safety awareness in the industry, regulations regarding the admissible levels of pollutants have become stricter in the past decades and are likely to become even stricter in the future. At the same time, after exhausting shallow deposits, mining is moving to deeper locations, aggravating the temperature conditions [ 45 ].

Even though some methods to provide electric power have been used for a long time already (e.g., trolley assist), today there are more incentives to look for electric-powered alternatives to replace the mobile equipment that have been predominantly running with diesel ICEs, like LHDs and haul trucks. According to the method used to supply the motor with electric energy, this equipment can be classified into five categories [ 45 ]:

Trolley powered

Battery powered

Cable powered

Hybrid ICE/electric equipment

Hydrogen fuel cell powered

In Table 1 , a summary of the differences among diesel-powered equipment and the categories mentioned of electric-powered equipment, according to key operational, environmental, and economic parameters, is presented.

In general terms, the main advantages of electric-powered over diesel-powered equipment are higher energy efficiency, higher service life (and, therefore, lower fleet requirements along the life of the mine), lower maintenance requirements, reduced generation of pollutants, heat and noise, and overall lower operating costs. The lower ventilation requirements can also have an impact on the CAPEX of the mining project, by reducing the size of ventilation adits and fans. On the downside, electric-powered equipment usually presents higher CAPEX and, depending on the type, can present some other disadvantages (Table 1 ). Also, the specific conditions of the operation can affect the preference for one specific technology, e.g., open pit vs. underground, haulage distances, deepness and rock temperature, regulations of the country, and diesel and electricity prices. For these reasons, an integral techno-economic evaluation must be conducted in each case.

Nevertheless, a lot of effort is currently being put in R&D regarding electric-powered equipment, especially battery and hydrogen fuel cell-powered. These show the greater potential to replace diesel equipment, due to their high flexibility, besides the safety and environmental advantages already mentioned [ 43 ].

Main mining equipment manufacturers have already developed several models of battery-powered vehicles. The Epiroc’s “zero-emission fleet” for underground operations includes the Minetruck MT42 Battery (articulated low-profile truck), Boomer E2 Battery (drill rig), and the Scooptram ST14 Battery (LHD) [ 47 ]. In the meantime, Caterpillar continues to develop its R1700 XE battery-powered LHD [ 48 ] and Sandvik works on its LH514BE battery-assisted LHD (as a combination of battery and tethered cable) [ 49 ].

Though the transition to electric mining equipment has been relatively slow, it is difficult to think of a mining industry of the future still depending on fossil fuels. The shift to cleaner sources of energy is global: industries and governments across the world are implementing renewable energy sources strategies and policies, regulations are becoming stricter and social scrutiny harder. Electromobility has arrived to stay and the mining industry is not excluded from its influence.

3.2.2 Invisible Zero-Waste Mining

The concept of a mining with no impact on the surface is not new. Underground operations have been using their waste material to backfill open cavities left after ore extraction, mainly for stability reasons and as a mean to reduce haulage costs. At the same time, this practice reduces subsidence effect and, therefore, the impact on the surface above the underground mine. However, it is not possible to use all the waste extracted due to interference with the operation (e.g., during early development stages). Also, not every mining method allows backfilling application (e.g., caving operations). Therefore, it is certain that impact on the surface can be significantly reduced, but most of the time it is unavoidable.

In this regard, in situ leaching (ISL), also referred to as in situ recovery (ISR), constitutes an alternative that minimizes the effect on surface and generates practically zero waste. This method is understood as the in-place leaching of the ore, recovery of the enriched solutions, and their transportation to the surface for further processing.

ISL has been mainly applied in uranium mining (since it was first introduced in 1959 in the U.S.). There is also a record of successful cases of ISL applied in copper and gold deposits, though in relatively small scales. Besides typical characteristics of deposits (e.g., shape, dimensions, mineralization, grade distribution), the most critical factors restricting its applicability are permeability, hydrogeological conditions in site, and the possibility of achieving selective leachability of the ore body [ 50 ]. Containment of the leaching solutions within the zone of interest to prevent the contamination of groundwater might be the greatest environmental risk regarding ISL [ 51 ].

From an economic point of view, ISL presents obvious advantages over traditional mining methods. Energy consumption is reduced, thus lower OPEX needs to be met. ISL also requires lower CAPEX for infrastructure and mine developments. Additionally, this mining method admits a high production flexibility and can be developed as a modular project, if desired [ 50 ].

Future widespread application of ISL depends greatly on the technological advance regarding permeability enhancement and hydrogeological management. Findings in preconditioning techniques used in caving operations are likely to be adapted and applied in ISL mining for permeability improvement. Pilot tests of in situ bioleaching have shown that it is possible to enhance permeability within the orebody after the application of conditioning methods, such as hydraulic fracturing and water pressure blasting [ 52 ], whereas the use of barriers, such as the gel barriers widely used in the oil and gas industry to control the flow of sweep and production, are also potentially applicable for this mining method as a tool for proper leaching solutions containment [ 53 ]. For these reasons, R&D efforts should be mainly aimed at the adaptation and improvement of existing technologies.

Besides environmental benefits of this method, if the restrictions mentioned can be overcome, ISL opens the possibility to exploit very deep low-grade deposits, currently uneconomic or technically infeasible to mine.

3.2.3 Continuous Mining

Continuous extraction and material handling systems have been used for many years in the coal mining industry. In surface operations, this has been carried out combining the action of bucket wheels excavators for the extraction and conveyor belt systems for the transport of coal and waste. Meanwhile, underground methods such as longwall mining and room and pillar (by using continuous miner equipment) have also offered continuous flows of material. However, due to rock strength, most metallic ore deposits do not allow mechanical extraction methods, making necessary the use of drill and blasting, therefore, impeding continuous operation.

Traditional mining methods combining drill and blasting, excavators for loading and mobile equipment for hauling (or LHD for loading and hauling, in underground mining), have high levels of operational inefficiency and low equipment utilization: significant hauling cycles, in which at least half of the time the mobile equipment is empty, along with queues and waiting times at loading and dumping site, are some of the inefficiencies of these processes.

As discussed in the previous sections, increasing productivity and enhancing efficiency of operations are the main drivers for innovation. Then, the development of continuous extraction and material handling systems, outside the coal sector, are trends that will likely gain importance in the future.

Indeed, efforts in this matter have already been done in recent years. One example is the S11D iron mine of Vale in Brazil. This mine operates in four independent truckless systems. Each system consists of an excavator, a mobile sizer rig (MSR), and a mobile belt wagon (MBW) that connects to a belt conveyor (BC). Due to its continuous truckless design, the project has reported high operating productivity rates (about four times higher than Vale’s typical rates in the region) and lower operating costs (approximately three times lower than Vale’s traditional cost levels in the region) [ 54 ].

Initiatives in underground mining have also been developed. Such is the case of the Continuous Mining System (CMS) for caving operations, introduced by Codelco in Chile. This design considered the continuous and simultaneous extraction of broken ore from active drawpoints in a block or panel caving mine, by the combined action of feeders (located at the drawpoints), heavy weight conveyors, and primary crushers [ 55 ].

After almost 20 years of research and testing, the project was finally dismissed as a consequence of difficulties faced in the construction phase for its industrial validation [ 56 ]. Thus, the design did not get to be tested at an industrial level, and therefore, its real potential and applicability remained unclear. However, previous tests and studies suggested that great benefits in terms of productivity, costs, workforce requirements, and ramp-up duration can be achieved through the implementation of the CMS [ 57 ].

4 Case Study: a Continuous Mining System for Caving Operations

The Continuous Mining System (CMS) was an innovation project developed by Codelco, in Chile, that intended to create a continuous material handling system for block and panel caving operations. With the objective of illustrating the impacts and implications of implementing a disruptive innovation project, the CMS initiative is below described and analyzed.

4.1 Codelco

Codelco is a Chilean state-owned mining company, first copper and second molybdenum worldwide producer. It is divided into eight operating divisions located in the central and north of Chile. In total, Codelco possesses seven mining operations, four smelters and three refineries [ 58 ].

Divisions Andina, El Teniente, and Salvador include panel caving operations, thus the importance of projects such as CSM for the corporation. Moreover, Chuquicamata Underground Mine has been recently commissioned, a block caving operation that required over US$ 5.5 billion for its construction and will extend the life of Chuquicamata Division for at least 40 years. Footnote 3

4.2 General Description of the Project

The concept of continuous mining for caving operations was first introduced by Codelco and its Institute for Innovation in Mining and Metallurgy, IM2, in 1998. It was conceived as a tool to face the future challenges of underground mining, specifically the necessity of increasing extraction rates and improving safety [ 59 ].

This mining design was based on the following key elements [ 59 , 60 ]:

Application of preconditioning to ensure a proper fragmentation of the rock mass and an uneventful flow of broken ore through drawpoints

Continuous and simultaneous extraction from active drawpoints by dozer feeders, increasing extraction rate and utilization

Continuous transport of material by panzers

Early size reduction of ore by sizer crushers

Remote operation of the system, reducing the exposition of workers, and increasing productivity

The CMS comprised dozer feeders at the drawpoints, panzers to collect and transport the broken ore from the dozers to the sizer crushers, and finally the sizers themselves. Changing the operation of LHDs for a continuous material handling system also requires a reorganization of the layout of the extraction level. The basic differences between the El Teniente layout (typically used by Codelco in its caving operations) and the CMS layout are presented in Fig. 9 .

El Teniente layout (left) vs. CMS layout (right). Modified after [ 57 ]. Left layout dedicated to LHD access to drawpoints, whereas right layout with perpendicular arrangement dedicated to continuous material flow with panzers (flow direction indicated by arrows)

4.3 Process Validation of CMS

After years of research since the concept was first introduced in 1998, the process validation for the CMS design was carried out in three phases.

4.3.1 Phase I (2005): Dozer Feeder

The first phase took place in Codelco’s Salvador Mine, in 2005. It was focused on the validation at a pilot level of the concept of continuous extraction. For this, the extraction of ore from one drawpoint by a prototype of a dozer feeder was tested.

The test showed the capacity of the dozer feeder to extract the ore from the drawpoint at a reasonable rate (200 t/h on average), allowing a proper flow within the ore column [ 55 ]. With these positive results, the process validation moved forward to Phase II.

4.3.2 Phase II (2006–2008): Module CMS

The second phase in the process validation of CMS was also executed in Salvador Mine. This time, a prototype of a modular system of continuous extraction, haulage, and crushing was tested. The module considered one haulage drift with four drawpoints, each one of them with a dozer feeding the panzer, which transported the ore to a roller impact crusher [ 57 ]. The module was built between 2006 and 2007 and the test itself carried out between 2007 and 2008. During this period, approximately 200,000 t were extracted in total. The results achieved in Phase II were satisfactory, in terms of the performance of the different equipment and their interaction, though the roller impact crusher was dismissed for further tests due to its low availability and high components wear. In its place, a sizer crusher was incorporated afterwards [ 60 ].

4.3.3 Phase III (2012–2016): Industrial Validation of CMS

Due to the promising results in previous phases of validation, the company decided to move forward to Phase III, to validate at an industrial level the CMS method. This test aimed to evaluate the performance of the CMS method under real operating conditions, in Andina Division of Codelco. The design considered a sector of four haulage drifts (equipped with panzers) and eight drawpoints per drift (each one of them equipped with a dozer feeder), and a total test period of 38 months [ 57 ].

Phase III was defined as the validation test of CMS for its application in the Chuquicamata Underground Mine Project, which commissioning was planned for the first semester of 2019. In this sense, the main expected benefits from its applicability in the Chuquicamata Underground Mine originally were [ 57 ]:

Instant production rate: 3 t/m 2 -day

OPEX: 20% lower

Workforce requirements: 30% lower

Ramp-up period: 25% shorter

Improvements in safety and energy efficiency

Net present value for its application in Chuquicamata: US$ 1000 million

The construction of the test module started in 2012. However, due to significant deviations in the execution period and budget, the works were stopped in December 2015. After more than 2 years of being paralyzed, and in the light of new studies and re-evaluations performed by Codelco, the project was finally cancelled in 2018, totaling US$ 138.1 million of loss [ 56 ].

4.4 Analysis and Discussion

From Codelco’s experience in the process validation of the CMS innovation project, several key elements can be identified, and lessons can be learned:

4.4.1 Time required for Process Validation

Developing an innovation project for a technological breakthrough often requires long periods of time. Since the idea is conceived, conceptual studies must be carried out before initiating pilot and industrial validation tests. In the case of Codelco’s CMS, over 20 years passed since the concept was first introduced until the industrial validation project was finally cancelled. During this time, other technologies are developed, which can be incorporated in the innovation project being tested, changing its potential value and future impact of its application. Specifically, during the process validation of CMS, significant advances were made in preconditioning techniques and digital technologies (e.g., automation, robotics). The project team must evaluate the impacts of new technologies developed along the way and incorporate them in the project if they prove to add value.

4.4.2 CAPEX and Execution Period Estimation

Process validation can be expensive, especially the industrial validation phase. Special care must be taken in the economic evaluation that justified the project and in the execution time and budget estimation. CMS project was stopped and finally cancelled due to problems in its construction phase, not because of unsatisfactory results of the test itself: this did not even get to be executed (similarly, also the first Epiroc Mobile Miner—back then Atlas Copco—was initially not accepted for prototype testing by the foreseen mine site [ 61 ]).

4.4.3 Infrastructure Required and Coordination with the Operation

New designs for extraction and material handling methods must be proved under real conditions for their industrial validation. For this, first the company needs to have access to ongoing mining operations, of its own property or coordinate with another company, in other cases. Then, a proper coordination with the current operation must be conducted, to minimize interferences and ensure the availability of resources (e.g., energy, water).

It is important to highlight the relevance of the CMS project, regarding its potential to improve extraction rates and safety in caving operations. Material handling systems through batch operations, such as the use of trucks and LHDs, are highly inefficient, from a macro point of view. Equipment show low levels of utilization and the productivity of the overall operation remains restricted. The design proposed by the CMS initiative offered the possibility of achieving higher production levels with lower requirements of active area, reducing CAPEX and OPEX, and gaining future dividends of the project earlier in time. All these factors have a positive effect on the economic indicators of a mining project: net present value increases and payback period is reduced, for example.

Finally, continuous mining and automated operations are trends that will likely shape the mining of the future. Initiatives like the CMS design should not be immediately dismissed, especially considering that this particular project failed in the construction stage of its industrial validation phase, having no chance to prove its applicability (or inapplicability) in a real operation.

5 Conclusions

Innovation plays an important role in the mining industry as a tool to improve the efficiency of its processes, reduce costs, but also to meet the increasing social and environmental concerns among communities and authorities. Technological progress has also been crucial to allow the exploitation of new deposits in more complex scenarios: lower ore grades, extreme weather conditions, deeper deposits, harder rock mass, and high-stress environments.

That is, the importance of innovation for the mining industry, as a critical factor in the improvement of labor productivity through past decades, was analyzed. Though its relevance, mining companies usually show low levels of R&D intensity, similar to mature industries and far from high-tech sectors. The tendency to vertical disintegration has led firms to focus on their core business, relying mainly on equipment manufacturers and suppliers for the development of innovative solutions. Also, collaborative alliances between mining companies, suppliers, and research centers share a significant participation in the development of new technologies.

Nowadays, several technological trends can be identified as main factors that will shape the mining of the future. The first and most relevant one is the digital transformation (DT), as the process of adoption and incorporation of a set of tools, the so-called technologies 4.0, into the mining business. Automation, robotics, remotization of operations, internet of things, analytics, and digital twinning, among others, have the potential to enhance processes along the whole value chain of mining. However, though DT is frequently mentioned as one of the main concerns among most large-scale mining companies, the level of digitization of the industry remains low, indicating that most of the potential of DT for the sector is still to be unlocked. The main challenges that firms must face to achieve a successful digitization are the commitment and joint-task coordination between the different business units, implementing proper organizational structure changes, and promoting a new cultural mindset regarding cybersecurity strategies and their continuous improvement.

Other important trends are electromobility, invisible zero-waste mining, and continuous mining. These concepts answer the necessity of building a more sustainable and efficient industry, reducing the environmental footprint, and enhancing safety of mining operations. The replacement of fossil fuel-powered vehicles is a “must” in a world moving away from such energy sources to cleaner ones, and stricter safety and environmental regulations being implemented all around the world are a reflection of that. Every day more companies are evaluating the incorporation of electric-powered fleets into their operations, as existing technologies can already offer economic alternatives, while R&D keeps advancing in this matter.

Invisible mining strategies, such as in situ leaching methods, have minimal impact on the surface and surroundings, and generate practically no waste. Yet, for a widespread application of this mining method, progress must be made in rock mass permeability enhancement (e.g. preconditioning techniques) and hydrogeological management, to ensure an optimal leaching process, in the first case, and minimize risks associated with groundwater pollution, in the second one.

Finally, though the concept of continuous mining has been applied for many years in the coal mining industry, its application in other mineral sectors has the potential to increase productivity, reduce costs, and improve safety, along with technological tools brought by DT, such as automation, robotics, and remotization of operations.

According to data from The Parker Bay Company. Available in: https://parkerbaymining.com/mining-equipment/mining-trucks.htm

Companies in this analysis: Rio Tinto, BHP, Vale, Glencore, Anglo American, Codelco, Fortescue Metals Group, OCP Group, Freeport-McMoRan, and Nornickel

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Sánchez, F., Hartlieb, P. Innovation in the Mining Industry: Technological Trends and a Case Study of the Challenges of Disruptive Innovation. Mining, Metallurgy & Exploration 37 , 1385–1399 (2020). https://doi.org/10.1007/s42461-020-00262-1

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Evidence of the impacts of metal mining and the effectiveness of mining mitigation measures on social–ecological systems in Arctic and boreal regions: a systematic map

• Neal R. Haddaway   ORCID: orcid.org/0000-0003-3902-2234 1 , 2 , 3 ,
• Adrienne Smith 4 ,
• Jessica J. Taylor 4 ,
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A Systematic Map Protocol to this article was published on 21 February 2019

Mining can directly and indirectly affect social and environmental systems in a range of positive and negative ways, and may result in societal benefits, but may also cause conflicts, not least in relation to land use. Mining always affects the environment, whilst remediation and mitigation efforts may effectively ameliorate some negative environmental impacts. Social and environmental systems in Arctic and boreal regions are particularly sensitive to impacts from development for numerous reasons, not least of which are the reliance of Indigenous peoples on subsistence livelihoods and long recovery times of fragile ecosystems. With growing metal demand, mining in the Arctic is expected to increase, demanding a better understand its social and environmental impacts. We report here the results of a systematic mapping of research evidence of the impacts of metal mining in Arctic and boreal regions.

We searched multiple bibliographic databases and organisational websites for relevant research using tested search strategies. We also collected evidence from stakeholders and rightsholders identified in the wider 3MK project (Mapping the impacts of Mining using Multiple Knowledges, https://osf.io/cvh3u ). We screened articles at three stages (title, abstract, and full text) according to a predetermined set of inclusion criteria, with consistency checks between reviewers at each level. We extracted data relating to causal linkages between actions or impacts and measured outcomes, along with descriptive information about the articles and studies. We have produced an interactive database along with interactive visualisations, and identify knowledge gaps and clusters using heat maps.

Review findings

Searches identified over 32,000 potentially relevant records, which resulted in a total of 585 articles being retained in the systematic map. This corresponded to 902 lines of data on impact or mitigation pathways. The evidence was relatively evenly spread across topics, but there was a bias towards research in Canada (35% of the evidence base). Research was focused on copper (23%), gold (18%), and zinc (16%) extraction as the top three minerals, and open pit mines were most commonly studied (33%). Research most commonly focused on operation stages, followed by abandonment and post-closure, with little evidence on early stages (prospecting, exploration, construction; 2%), expansion (0.2%), or decommissioning/closure (0.3%). Mitigation measures were not frequently studied (18% articles), with groundwater mitigation most frequently investigated (54% of mitigations), followed by soil quality (12%) and flora species groups (10%). Control-impact study designs were most common (68%) with reference sites as the most frequently used comparator (43%). Only 7 articles investigated social and environmental outcomes together. the most commonly reported system was biodiversity (39%), followed by water (34%), societies (20%), and soil/geology (6%), with air the least common (1%).

Conclusions

The evidence found highlights a suite of potential knowledge gaps, namely: on early stages prior to operation; effectiveness of mitigation measures; stronger causal inference study designs; migration and demography; cumulative impacts; and impacts on local and Indigenous communities. We also tentatively suggest subtopics where the number of studies could allow systematic reviews: operation, post-closure, and abandonment stages; individual faunal species, surface water quality, water sediment quality; and, groundwater mitigation measure effectiveness.

On the impacts of mining

Mining activities, including prospecting, exploration, construction, operation, maintenance, expansion, abandonment, decommissioning and repurposing may affect social and environmental systems in a range of direct and indirect, positive and negative ways. Exploration, construction, operation, and maintenance of mines can change land-use substantially, and may negatively affect environments, for example through deforestation, erosion, contamination and alteration of soil profiles, contamination of local streams and wetlands, and an increase in noise level, dust and emissions [ 1 , 2 , 3 , 4 , 5 ]. Abandonment, decommissioning and repurposing of mines can also cause significant environmental impacts, for example soil and water contamination [e.g. 6 , 7 , 8 . Additionally, infrastructure put in place to support mining activities (i.e. roads, ports, railway tracks, power lines) may affect migratory routes of animals and worsen habitat fragmentation [ 9 , 10 ]. Such infrastructure, together with accompanying institutions, can indeed create new social-technological mega-systems [ 11 , 12 , 13 ].

Mining also affects people and societies. Negative effects include impacts on human health [e.g. 14 and living standards [ 15 ]. Mining is known to affect traditional practices of Indigenous peoples [ 16 ], and land-use conflicts are also often present, as are other societal impacts including those related to public health and human wellbeing [e.g. 17 , 18 , 19 , 20 . In terms of positive impacts, mining is typically a source of local employment and may contribute to economies locally and regionally [e.g. 21 , 22 . Remediation of the potential environmental impacts (e.g. water treatment and ecological restoration) can have positive net effects on the environment [ 23 ]. Mine abandonment, decommissioning and repurposing may positively and negatively affect social impacts. Examples of negative impacts include loss of jobs and local identities [ 24 ], while positive impacts may include opportunities for new economic activities [ 25 ], for example through repurposing of mines into tourist attractions.

Mitigation measures

‘Mitigation measures’ (as they are commonly described in the impact assessment literature) are implemented to avoid, eliminate, reduce, control or compensate for the negative effects of an intervention and ameliorate the local impacts [ 23 ]. Typically, these measures should be considered and described in environmental and social impact assessments (EIAs and SIAs) conducted before major activities, such as resource extraction, begin [ 26 , 27 , 28 ]. If there will be a significant impact, mitigation measures are required by law in most countries to be implemented and monitored. Mitigation of negative environmental effects in one system (e.g. water or soil) can influence other systems in a positive or negative manner, such as the wellbeing of local communities [ 23 ]. A wide range of technologies have been implemented in the treatment of contaminated waters (e.g. constructed wetlands [ 29 ], reactive barriers treating groundwater [ 30 ], conventional wastewater treatment plants). Phytoremediation of contaminated land is also an active research area [ 31 ].

Mitigation measures designed for the alleviation of negative impacts of mining on social and environmental systems may not always be effective and may have undesired and unintended consequences, particularly in the long-term and across diverse systems (e.g. the intersection between environmental and social): for example, a mitigation measure designed to effect an environmental change may have unintended knock-on social impacts. To date, there appears to be little research on the effectiveness of mitigation measures applied to mining projects to achieve the desired mitigation outcome, and we are not aware of any synthesis of the effectiveness of metal mining oriented mitigation measures that considers impacts on both society and the environment.

Mining in the Arctic and boreal regions

The Arctic and boreal regions are particularly sensitive to the effects of mining and mining-related activities [ 32 , 33 ], both on social and environmental systems. However, the Arctic is home to substantial mineral resources [ 34 , 35 ] and has been the focus of interest and resource extraction for centuries. These activities significantly increased during the early 20th Century and there has been an intensification of interest in exploration and exploitation in recent years to meet a growing global metal demand. Given the region’s geological features and expectations of growing global demand for metals, resource extraction already dominates discourse on development here and is likely to continue to do so for the near future. As of 2015, there were some 373 mineral mines across Alaska, Canada, Greenland, Iceland, The Faroes, Norway (including Svalbard), Sweden, Finland and Russia (see Table 1 ), with the top five minerals being gold, iron, copper, nickel and zinc [ 36 ]. Mining in the Arctic has generally intensified: for example, whilst the number of mines in Sweden has decreased substantially over the last 100 years, from a peak of  > 260 in 1917 to just 12 in 2019, the volume of production has conversely increased from < 5 m tonnes to 86.5 m tonnes over the same period [ 37 ].

There is little empirical research on the impacts of mining on environmental and social systems in the literature. For example, there is a dearth of evidence on these impacts on the Sami; a group of traditional people inhabiting a region spanning northern Norway, Sweden, Finland and Russia. Sami people are affected by a range of external pressures, one of which pertains to resource extraction and land rights, particularly in relation to nomadic reindeer herding. However, there is little published research on the topic [ 38 ]. Indigenous peoples reside in many other regions within Arctic and boreal ecosystems (e.g. the many Aboriginal communities in Canada [ 39 ]) and these systems have been shown to be equally limited in evidence on social impacts of resource extraction [ 40 , 41 ]. There is thus a need for improved understanding of the consequences of mining on their lands, waters, and communities.

The evidence base for research on the environmental and social impacts of mining has grown over recent years. However, despite the clear importance of this topic, there has been little rigorous synthesis of research knowledge in Arctic and boreal regions (although see [ 42 ] for a review with high susceptibility to bias on the topic). This lack of rigorous synthesis represents a significant knowledge gap in the face of the continued promotion and expansion of resource extraction in the region. There is thus an urgent need for transparent and robust approaches to collate and describe the nature of research evidence on the environmental and social impacts of mining and its mitigation measures.

Stakeholder and rightsholder Engagement

This systematic map forms part of a broader knowledge synthesis project called 3MK (Mapping the impacts of Mining using Multiple Knowledges, https://osf.io/cvh3u ). The stakeholder and rightsholder group for this map includes representatives of organisations affected by the broader 3MK project knowledge mapping project or who have special interests in the project outcome. We define stakeholders and rightsholders here as all individuals or organisations that might be affected by the systematic map work or its findings [ 43 , 44 ], and thus broadly includes researchers and the Working and Advisory Group for this project.

The systematic map stakeholders and rightsholders and those of the broader 3MK project have an intentionally Scandinavian focus as a result of our research interests and funding. However, evidence on base metal mining impacts in Arctic and Boreal regions was strongly felt to be globally relevant to the review, and as such, the geographic scope of evidence considered was pan-Arctic/Boreal. Some members of the team are based in Canada and the representation of authors on this review was therefore felt to be beneficial in terms of identifying grey literature sources and the search string (see below).

Invitations to be included in this group were based on an initial stakeholder/rightsholder mapping process and soliciting expressions of interest (see Stakeholder Engagement Methodology Document, https://osf.io/cvh3u ). This group included government ministries and agencies such as the Ministry of Enterprise and Innovation, the Mineral Inspectorate (Bergstaten) and County Administrative Boards, the mining industries’ branch organisation (Svemin) and individual companies such as LKAB Minerals and Boliden AB, Sami organisations, including the Sami Parliament, related research projects, and representatives of international assessment processes, such as activities within the Arctic Council. Stakeholders and rightsholders were invited to a specific meeting (held at Stockholm Environment Institute in September 2018) to help refine the scope, define the key elements of the review question, finalise a search strategy, and suggest sources of evidence, and also to subsequently provide comments on the structure of the final protocol [ 45 ].

Objective of the review

The broader 3MK project aims to develop a multiple evidence base methodology [ 46 ] combining systematic review approaches with documentation of Indigenous and local knowledge and to apply this approach in a study of the impacts of metal mining and impacts of mitigation measures. This systematic map was conducted in order to answer the question:

What research evidence exists on the impacts of metal mining and its mitigation measures on social and environmental systems in Arctic and boreal regions?

Definition of the question components.

The review question has the following key elements:

Population Social, technological (i.e. industrial contexts, heavily altered environments, etc.) and environmental systems in circumpolar Arctic and boreal regions.

Intervention/exposure Impacts (direct and indirect, positive and negative) associated with metal mining (for gold, iron, copper, nickel, zinc, silver, molybdenum and lead) or its mitigation measures. We focus on these metals as they represent approximately 88% of Arctic and boreal mines (according to relevant country operating mine data from 2015 [ 36 ]), and contain the 5 most commonly mined minerals in the region (gold, iron, copper, nickel and zinc). Furthermore, these minerals include all metals mined within Sweden, the scope of a related workstream within the broader 3MK project ( https://osf.io/cvh3u ).

Comparator: For quantitative research; the absence of metal mining or metal mining mitigation measures—either prior to an activity or in an independent, controlled location lacking such impacts. Additionally, alternative mining systems are suitable comparators. For qualitative research; comparators are typically implicit, if present, and are thus not required.

Outcome Any and all outcomes observed in social and environmental systems described in the literature were iteratively identified and catalogued. Measured outcomes should be linkable to mining activities or their mitigation measures in the Arctic, irrespective of the scale of the intervention/exposure.

Data type Both quantitative and qualitative research were included.

The review follows the Collaboration for Environmental Evidence (CEE) Guidelines and Standards for Evidence Synthesis in Environmental Management [ 47 ] and it conforms to ROSES reporting standards [ 48 ] (see Additional File 1 ). The review was conducted according to the published protocol [ 45 ].

Deviations from the protocol

We made the following deviations from our published protocol. Several bibliography databases could not be used as planned:

Worldwide Political Science Abstracts (via Proquest)—subscription lapsed

JSTOR—an update to the search functionality meant that complex search strings are no longer accepted and a basic search was not functional at the time of conduct (error: ‘string too long’)

AGRIS—advanced search and export not functional at the time of search conduct

CAB Abstracts (via CAB Direct)—search facility not functional at the time of search conduct

Of the 104 proposed organisational websites, 19 sites could be searched: 9 were duplicate sub-organisations already included in other websites, 9 websites were unavailable at the time of searching, and 1 website could not be searched because of the departure of a Russian speaking colleague ( n  = 1). We chose not to search Google Scholar because of limited resources. Similarly, due to the COVID-19 pandemic and staff personal circumstances, we did not have resources available to perform a search update prior to publication.

Search for articles

Bibliographic databases Searches for relevant research evidence were conducted between 27 and 29th November 2018 using the 21 bibliographic databases shown in Table 2 .

The following Boolean search string formed the basis of searches:

(mine OR mined OR mining OR mines OR (extract* AND resource*) OR (extract* AND industr*) OR (extract* AND (mineral OR minerals)))

(metal* OR iron OR copper OR nickel* OR lead OR zinc OR hematite OR haematite OR magnetite OR chalcopyrite OR digenite OR azurite OR malachite OR chrysocolla OR atacamite OR ore OR mineral* OR tailing OR pyrite OR ferric OR ferrous OR goethite OR limonite OR siderite OR ochre OR cupric OR chalcocite OR tenorite OR cuprite OR bornite OR covellite OR tetrahedrite OR tennantite OR pentlandite OR millerite OR galena OR kamacite OR taenite OR laterite OR garnierite OR boulangerite OR anglesite OR cerussite OR pyromorphite OR calamine OR smithsonite OR sphalerite OR hemimorphite OR wurzite OR hydrozincite OR pb OR zn OR cu OR ni OR fe OR gold OR au OR silver OR ag OR argenite OR chlorargyrite OR galena OR calaverite OR sylvanite OR nagyagite OR petzite OR krennerite OR molybden* OR wulfenite OR powellite OR mo)

(*arctic OR boreal OR boreo* OR *polar OR "snow forest" OR tundra OR taiga OR alaska OR canada OR russia OR sweden OR norway OR finland OR greenland OR iceland OR faroe OR canadian OR swedish OR norwegian OR russian OR icelandic OR subarctic OR "northern latitude" OR "high latitude" OR yukon OR nunavut OR quebec OR "northwest territories" OR newfoundland OR labrador OR alaskan OR sibera OR ural OR volga OR caucasus OR lapland OR lappland OR norrbotten OR västerbotton OR ångermanland OR jämtland OR medelpad OR härjedalen OR hälsingland OR dalarna OR gästrikland OR uppland OR västmanland OR värmland OR ostrobothnia OR kainuu OR karelia OR savonia OR pirkanmaa OR satakunta OR tavastia OR kymenlaakso OR uusimaa OR åland OR Trøndelag OR "kalaallit nunaat" OR avannaata OR qeqertalik OR qeqqata OR sermersooq OR kujalleq OR aleutia* OR "british columbia" OR alberta OR saskatchewan OR manitoba OR "new brunswick" OR "prince rupert island" OR ontario OR "nova scotia" OR "north* europe" OR meadowbank OR ekati OR Meadowbank OR bellekeno OR "Keno Hill" OR Minto OR Tom OR Raglan OR Wolverine OR "Pine point" OR "Red Chris" OR Granduc OR Thompson OR Birchtree OR Seabee OR "Voisey's Bay" OR DSO OR "james mine" OR Schefferville OR "Flin Flon" OR "Triple Seven" OR "Snow lake" OR Huckleberry OR Carol OR Scully OR Wabush OR "Bloom lake" OR "mont wright" OR Eleonore OR "qr gold" OR Musselwhite OR Gibraltar OR "mcleese lake" OR Campbell OR "red lake" OR "rice lake" OR Bralorne-Pioneer OR "new afton" OR "highland valley" OR "detour lake" OR Ming OR rambler OR "pine cove" OR "corner bay" OR "bachelor lake" OR "myra falls" OR "casa berardi" OR Vezza OR "copper mountain" OR similco OR Langlois OR grevet OR Trail OR "duck pond" OR Hemlo OR Williams OR "kidd creek" OR "david bell" OR Hislop OR "bell creek" OR Beaufor OR "black fox" OR glimmer OR Holloway OR Holt OR Porcupine OR "fabie bay" OR "doyon division" OR LaRonde OR Lapa OR Mishi OR Macassa OR Sigma OR Lamaque OR Goldex OR "eagle river" OR Young-Davidson OR "Halfmile lake" OR Coleman OR "nickel rim" OR Fraser OR "McCreedy west" OR Sudbury OR Garson OR Stobie OR "Copper cliff" OR Manitoba OR ontario OR Creighton OR Gertrude OR Ellen OR Lockerby OR Totten OR Dufferin OR Bingo OR "Bonanza ledge" OR Bracemac-McLeod OR Cochenour OR "EP gold" OR Nunavik OR "fire lake" OR "hudson bay" OR Island OR "lac herbin" OR "lalor lake" OR Malartic OR Morrison OR "mount milligan" OR Phoenix OR rubicon OR "reed lake" OR Shakespeare OR "timmins west" OR McGarry OR Westwood-Mooshla OR Yellowjacket OR Alexo OR Monique OR "yellow giant" OR Kittilä OR Kevitsa OR Pahtavaara OR Hannukainen OR Laiva OR Talvivaara OR Kokkola OR Hitura OR Pyhäsalmi OR Pampalo OR Kylylahti OR Orivesi OR Kutemajärvi OR Vammala OR Harjavalta OR Jokisivu OR Sydvaranger OR Rana OR Odda OR Oktyabrsky OR Talnakhskoye OR Taimyrsky OR Komsomolsky OR Mayak OR Kaula-Kotselvaara OR Kola OR Zapolyarnoye OR Zapolyarny OR Ametistovoe OR "Medvezhy rucheu" OR Norilsk-1 OR Skalisty OR Zhdanovskoye OR Mayskoye OR Olenegorsky OR Olenegorsky OR "15th anniversary of october" OR Kovdorsky OR Kupol OR Korpanga OR Kostomuksha OR Kubaka OR Arylakh OR Lunnoye OR Susuman OR Berelekh OR Dukat OR Omsukchan OR Julietta OR Natalka OR Olimpiada OR Sovetskoye OR Blagodatnoye OR Khakanja OR Tarnjerskoye OR Severny OR Severopeschanskoye OR Vorontsovskoye OR "Golets Vysochaishy" OR Kuranakh OR Gusevogorskoye OR Pervenets OR Goroblagodatsky OR Bereznyakovskoye OR Gorevsky OR Vysokogorsky OR Rudnogorsky OR Pervouralskoye OR Berezovskoye OR Tatianinsky OR Korshunovsky OR Safyanovskaya OR Cheremshansky OR Irokinda OR Aginskoye OR Bakalskoye OR Talgansky OR Berezitovy OR Svetlinsky OR Uchalinsky OR Uchalinsky OR Mulginskoye OR Burlukskoye OR Chebachje OR Pioneer OR Mnogovershinnoye OR Abakansky OR Aleksandrinsk OR Pokrovskiy OR Teysky OR Sheregeshsky OR Ozernoye OR Tashtagolsky OR Sibay OR Murzinskoye-1 OR Zun-Holba OR Mikhailovsky OR Asacha OR Novoshirokinskoye OR Oktyabrsky OR Verninsky OR Kyzyl-Tashtyg OR Rubtsovsk OR Osenneye OR Gaisky OR Stepnoy OR Korbalikhinsky OR Stoylensky OR Zarechenskoye OR Lebedinsky OR Stoylo-Lebedinskoye OR Letneye OR Dzhusinskoye OR Kimkanskoye OR Dalpolimetal OR Urupsky OR Sadonsk OR Albazino OR AldGold OR Amazarkan OR "Lena artelj" OR "Tyva artelj" OR Avlayakan OR Albyn OR Belaya OR Birkachan OR Buryatzoloto OR Eldorado OR Festivalnoye OR Fevralskoye OR Goltsovoye OR Gubkin OR Karalveem OR Kirovogorsky OR Kochkarskoye OR Komsomolsky OR Kamaganskoye OR Kazsky OR Kommunarovsky OR Lenzoloto OR "Maly kuybas" OR Malomir OR Mauksky OR Mikheevskoye OR Mezhsopochnoye OR "Novogodnee monto" OR Odinochnaya OR Podotvalnoye OR Pogromnoye OR Samolazovskoye OR Savkino OR Shemurskoye OR Sideritovaya OR Yuzhno-Kirovskoye OR "Sopka Kvartsevaya" OR Sosnovsky OR Tabornoye OR Tardan OR Titimukhta OR Tsokol OR Uzelginsky OR Vasilevsky OR Valunistoye OR Vysokogorsky OR Vysokogorsky OR Vetrensky OR Yakutskoye OR Yubileynoye OR Baumansky OR Degtyarskoye OR Delbe OR Dvoynoye OR Estyuninskaya OR Garbuzovskoye OR Kanavnoye OR Konevinskoye OR Korolevsky OR "South kurasan" OR "West kurasan" OR Kamenskoye OR Krasnokamenskoye OR Lunnoye OR Molodyozhny OR Nikolaevsky OR Nizhneyakokitskoye OR Odolgo OR Olenje OR Olenegorsky OR Ozerny OR Partizanskoye OR Serovsky OR Severnoye OR Severo-Zapadny OR Sibir-Polimetally OR Vesely OR Solcocon OR Svetly OR Shanuch OR Verkhneye OR Yurjevskoye OR Yuzhnoye OR Kiruna OR Kaunisvaara OR Tapuli OR Malmberget OR Salmijärvi OR Aitik OR Kristineberg OR Maurliden OR Renström OR Boliden OR Björkdal OR Kankberg OR Svartliden OR Garpenberg OR Dannemora OR Lovisa OR Zinkgruvan OR Gruvberget OR "red dog" OR "fort knox" OR Pogo OR "stone boy" OR Kensington OR "greens creek" OR "Kelex" OR "Sinyukhinskoye" OR Endako OR Kitsault OR Zhireken OR Sorskoye)

The search string was developed based on intervention terms (mining) combined with metal terms and location terms. Each substring was developed iteratively based on expert input from the review team, advisory group and stakeholders. Location terms were supplemented by collating names for all known mines in boreal and Arctic regions.

For details of the search string adaptations used in each resource, see the searchRxiv search history records detailed in Table 2 . Searches of bibliographic databases were performed only in English, since in each case the bibliographic data were translated to English prior to indexing, meaning that full texts in non-English language would be found this way. Specialist searches (see below) were performed in other languages.

Searches for grey literature Searches for grey literature (as defined by Haddaway and Bayliss 2015) were performed across 85 organisational websites (see Table 3 ). These searches involved manual screening of each website for a ‘publications’ section, followed by searching using basic search terms if a search facility was present. For all English-language websites, searches were performed in English using the following core terms where search functionality allowed: mining impacts; mining effects; mining mitigation; social impacts mine; environmental impacts mine. For 6 websites with non-English language content (Finnish Game and Fisheries Research Institute; Greenland Institute of Natural Resources; Ministry of Natural Resources of the Russian Federation; Norwegian Directorate for Nature Management; Norwegian Institute for Nature Research (NINA); Finnish Sami Parliament; Norwegian Sami Parliament), searches were performed in Finnish (metallien louhinnan vaikutukset; metallien kaivostoiminta; kaivostoiminta; kaivannaisteollisuus; kaivos), and Danish (påvirkning virkning af metalminedrift; metalminedrift; minedrift) and Norwegian (støt effekter på gruvedrift av metal; metall gruvedrift; gruvedrift) as appropriate.

Supplementary searches In addition, we (Adrienne Smith [AS] and Brooke Etherington [BE]) hand searched reference sections of relevant included articles and 47 randomly selected relevant literature reviews which accounted for 30% of the relevant reviews identified in the searching (see Additional File 2 ).

Estimating the comprehensiveness of the search

A set of 49 articles known to be relevant were provided by the review team; the benchmark list (see Additional File 3 ). During scoping and development of the search string, the bibliographic database search results were checked to ascertain whether any of these studies were not found. We found 45 of the 49 benchmark based on search term presence in titles, abstracts and keywords (see Additional File 4 ). Four articles were not found because they lacked abstracts and/or keywords. This was deemed to be an appropriate retrieval level considering the complementary searching outlined above.

Article screening and study eligibility criteria

All articles were screened according to the established eligibility criteria developed in the protocol [ 45 ]. All inclusion criteria were used at title, abstract, and full text screening. However, data type and comparator were not considered useful at title and abstract screening since this information is often not well-reported in these fields.

Eligibility criteria

The following criteria were used to assess relevance (eligibility) of studies identified through searching.

Eligible population We included social, technological and environmental systems in Arctic and boreal regions based on political boundaries as follows (this encompasses various definitions of boreal zones, rather than any one specific definition for comprehensiveness and ease of understanding): Canada, USA (Alaska), Greenland, Iceland, the Faroe Islands, Norway (including Svalbard), Sweden, Finland, and Russia.

Eligible intervention/exposure We included all impacts (positive, negative, direct and indirect) associated with any aspect of metal mining and its mitigation measures. We included research pertaining to all stages of mining, from prospecting onwards as follows: prospecting, exploration, construction, operation, maintenance, expansion, abandonment, decommissioning, reopening and repurposing. Eligible mines included those of gold, iron, copper, nickel, zinc, silver, molybdenum and lead.

Eligible comparator For quantitative research; the absence of metal mining or metal mining mitigation measures—either prior to an activity or in an independent, controlled location lacking such impacts. For qualitative research; comparators are typically implicit, if present and thus were not required.

Eligible outcome Any and all outcomes (i.e. measured impacts) observed in social, technological and environmental systems were included.

Eligible data type We included quantitative, qualitative and mixed methods research.

Eligible study type We included both primary empirical research and secondary research (reviews were catalogued in a separate database). Modelling studies and commentaries were not included.

Screening process

Articles found by searches in databases were combined and screened at three distinct stages: (1) title (2) title and abstract, and (3) full-text. Articles found by other means (i.e., organisational websites and review references) were screened at title and abstract and full-text but were not included in consistency checks.

Any doubt over the presence of a relevant inclusion criterion (or if information is absent) resulted in the articles being retained for assessment at a later stage.

Titles were screened by three reviewers (NRH, JJT, CA). This stage was not subject to consistency checking—it was conducted as a preliminary stage to remove all clearly irrelevant records that could be obviously discerned as ineligible based on titles. Records for which any doubt remained were included to be conservative.

Prior to screening abstracts, all reviewers conducted a consistency checking procedure in EPPI-Reviewer to ensure consistent and repeatable decisions were being made among reviewers in regards to which records were deemed eligible. A total of 1,655 abstracts were screened by 4 reviewers as follows. In the first round, the agreement level achieved was 369/510 abstracts (NRH vs CA). Following discussion, the second round increased slightly to 205/271 (NRH vs JJT) and 216/271 (CA vs JJT). A third round resulted in a 372/510 (NRH vs JJT), 384/510 (JJT vs CA), and 370/510 (NRH vs CA) agreement level. A final round indicated a further increase in agreement, with 292/364 agreements (NRH vs CA). At this point, we felt consistency was as high as possible, and a continued conservative approach was applied to screening of the remaining abstracts. Reviewers did not screen articles (at title and abstract or full-text) for which they were an author.

A consistency check was also conducted prior to screening articles at full-text on 69 articles. Full-texts were screened by four reviewers [NRH, JJT, AS and Amanda Jeansen (AJ)], with a first round of screening resulting in 18/30 article agreement across all four coders. Disagreements were discussed at length and related primarily to uncertainty in this round. Consistency checking on a further set of 39 articles, resulting in only 7 disagreements (κ = 0.62). Following this consistency checking, the remaining articles were split between the two reviewers (AS and AJ) and allowed to proceed. Any query made by a reviewer was discussed with the review team (NRH, JJT, AS and AJ) and a consensus decision made, and conferred to all reviewers. Lists of all articles excluded on the basis of full-text assessment with the reasons for exclusion, and unobtainable articles are provided in Additional File 5 . A list of articles that could not be retrieved at full text is available in Additional File 6 .

Study validity assessment

No formal in-depth critical appraisal was made of study validity after their inclusion in the systematic map, since it is an optional part of systematic mapping methodology [ 49 ]. However, meta-data referring to study setting and design were extracted that could aid future study validity assessments and synthesis of studies on sub-topics of interest identified from our systematic map exercise. We have synthesised these variables along with other meta-data.

Data coding strategy

Following full-text screening of articles, relevant studies were extracted from the included articles: where multiple studies were reported within one article they were entered as independent lines in the database. Here, we define a study to be an experiment or observation that was undertaken at a particular mine site, mitigation or ex-situ experiment with mine-specific treatments. Studies were separated by line if the intervention impacted different systems (populations) within the same article.

The following key data domains were identified through scoping activities and discussion with the review team and advisory group : (1) bibliographic information; (2) mine location and details (e.g., geographic location, metal extracted, type, stage, etc.); (3) broad objectives of the study; (4) study design and setting; (5) system affected; (6) impact/mitigation; (7) measured outcomes; (8) data type and location. Coding variables and meta-data within these domains were then compiled in a partly iterative process, expanding the range of options as they were encountered during scoping and extraction.

Where data are missing they were coded as ‘NR’ (not reported). Where coding is not applicable, ‘NA’ was recorded.

We adapted an outcome coding schema designed within an ongoing environmental and social impact assessment synthesis project [ 50 ]. The coding schema was developed to a small degree during trial data extraction. Our impact coding schema (including editions relative to the source) is outlined in Table 4 .

To ensure that data were extracted in a consistent and repeatable manner, three reviewers (AS, JJT and NRH) piloted the extraction form by independently coding information from 10 articles at the beginning of the process. All disagreements were discussed, and additional, more detailed guidance was added to the extraction codebook to improve clarity. Coding and meta-data extraction then proceeded with one reviewer (AS). The finalised extraction form and codebook for the map (along with descriptions of each meta-data/coding field) is shown in Additional File 7 .

Data synthesis and presentation

We have summarised the review process in a ROSES flow diagram, using the ROSES flow diagram R package [ 51 ]. Our primary outputs are a searchable and filterable systematic map database provided as a CSV file (Additional File 8 ) along with an interactive evidence atlas (geographical information system) provided as a web-based app and downloadable HTML file (Additional File 9 ). All interactive files and visualisations are provided through the dedicated project website; https://3mkproject.github.io/ .

We summarise the evidence base using bar plots, focusing first on the publications (e.g. article publication year), then on the study systems (i.e. the mines), the mitigation measures investigated, the study designs (e.g. data type), and the measured outcomes. We then describe the affected systems using our three-layer hierarchy (system, component, factor) to describe the social or environmental context that was reported to have been affected by the mining. We have visualised this using a bespoke radial bubble plot that clusters outcomes across the hierarchy and show the volume of evidence at each level. Finally, we have produced heat maps that visualise two coding factors (categorical variables) along with the volume of evidence found across combinations of levels of each factor. The interactive plots are available online ( https://3mkproject.github.io/ ) and the code to produce them has been converted into an R script (Additional File 10 ). All data, code and functions are available on GitHub as an Open Source/Open Data resource here; https://github.com/nealhaddaway/3mk .

Knowledge gaps and clusters are highlighted by visually analysing cross tabulations and discussing candidate groups amongst the review team.

No team member was permitted to review their own work. Team members conducting screening, data extraction and coding were not publishing in this field.

Review descriptive statistics

The review process is depicted in a ROSES flow diagram (Fig.  1 ). We obtained a total of 44,870 records from bibliographic database searching. Following deduplication, 32,342 unique records were screened at title level and 5079 at abstract level. A total of 247 records could not be retrieved, leaving 2342 records screened at full text level. Following full text screening, 538 articles were retained. We included a further 47 articles from pre-screened resources (websites and review bibliographies). A final 585 articles were included in the map, corresponding to 902 outcome lines. We differentiate here between articles—the manuscripts in which data are presented—and outcome lines—the smallest independent data point in our map, corresponding to a measured outcome from a research article corresponding to a specific mine or mining area.

ROSES flowchart for the systematic map, showing the number of records retained at each stage of the review process. Produced using the R package ‘ROSES_flowchart’ [ 51 ]

The evidence base

The interactive evidence atlas is available online ( https://3mkproject.github.io/research.html ) and as a downloadable HTML file (Additional File 9 ). We also present an exemplary screenshot in Fig.  2 . The evidence atlas shows the location of each study system examined, displaying details of the system and the article describing it in a popup box that includes a hyperlink to the article on Google Scholar.

Screenshot of the interactive evidence atlas showing the location of all study systems in the 585 included studies across 902 total outcome measures. The popup contains descriptive meta-data and a link to the paper on Google Scholar. The interactive evidence atlas is available here: https://3mkproject.github.io/research.html

The articles

Figure  3 shows the publication dates of the included articles, suggesting a linear increase in the number of publications annually. This is in contrast to many other topics that seem to be experiencing a near exponential increase in published articles; perhaps because of the long and consistent history of mining relative to other topics, such as fossil fuel extraction. Although the environmental impacts of mining have a longer history [e.g. 52 , the social impacts of mining is a fairly new research topic, and we may observe an increase in research attention overall in coming years.

The publication years of articles included in the map

Figure  4 displays a choropleth for the number of articles included in the map from across eligible countries. The majority of articles focused on Canada (n = 317), followed by Russia (n = 84) and Sweden (n = 72). No research was identified from Iceland.

The number of articles in the map from across eligible Arctic and boreal countries

Mines investigated

A total of 177 unique mines were described across the 585 articles: these are described in a database in Additional File 11 . They were distributed across countries as follows: Canada, 97; Russia, 28; Sweden, 18; USA, 12; Finland, 9; Norway, 9; Greenland, 4; Iceland, 0.

Copper was the most commonly reported metal (n = 208), followed by gold (n = 162) and zinc (n = 141) (see Fig.  5 ). The metals extracted were not stated in 32 articles. Some articles stated only the principal metal mined, whilst others reported all metals encountered and extracted—the data are therefore representative of the articles and may not reflect precisely the state of metals mined across the Arctic and boreal regions.

The number of articles in the map reporting different metals mined. Numbers are not mutually exclusive and include articles studying multi-ore mines

The most commonly reported mine type was open pit (n = 218), with less than half this number underground (n = 80) and surface (n = 72), and only 22 articles focused on placer mines (Fig.  6 ). Some 218 articles did not report the type of mine.

The number of articles in the map according to mine type reported

Extraction stage

The most commonly studied extraction stage was operation (n = 276), followed by abandonment (n = 164), post-closure (n = 114), and remediation (n = 60) (see Fig.  7 ). Prospecting, exploration, construction, expansion, and decommissioning/closure were studied far less frequently (n = 1–7).

The number of articles in the map according to the extraction stage. Note some articles report multiple stages

Figure  8 shows the articles reporting multiple extraction stages, demonstrating that the most commonly co-reported stages were post-closure and remediation (n = 21), followed by operation and abandonment (n = 17). Articles more commonly reported multiple stages following resource extraction activities (decommissioning/closure, post-closure, remediation and abandonment), than earlier stages. No articles reported more than three stages together.

The number of articles in the map reporting multiple extraction stages, arranged by order of stages investigated. Yellow blocks indicate the stages were reported in the same article. Decomm./closure = decommissioning or closure

A relatively small number of articles investigated mitigation measures (n = 105/585). The systems, components and factors these mitigation measures were used to ameliorate are listed in Table 5 . Groundwater quality was the most common factor mitigated (n = 57), followed by soil surface quality (n = 13) and flora species groups (n = 11). Full descriptions of the mitigation measures encountered are provided in the map database (Additional File 8 ).

Study design

Most articles in the map used a ‘control-impacts’ study design (n = 396), with a substantial number employing correlative designs (n = 142) (see Fig.  9 ). Only 5 articles examined just the impact/affected site with no real study design.

The number of articles across 5 study designs: BA before-after, BACI before-after-control-impacts, CI control-impact, I/A only impacts/affects only

Related to this, the precise type of comparator is elaborated in Fig.  10 , demonstrating that the most common comparator was a reference site/population (n = 254), followed by background values (n = 149). Full BACI designs (before after control impacts) were least common (n = 5).

The number of articles using each type of comparator

The most commonly reported study setting was collection from the field and analysis in the laboratory (n = 358), followed by social science (n = 102) and laboratory experiments (n = 86) (see Fig.  11 ).

The number of articles reporting each type of study setting. Lab = laboratory; expt = experiment

Similarly, the context of the included articles’ studies was predominantly in situ (n = 459), with a smaller number using ex situ methods (n = 118) and very few employing mesocosms (n = 8) (see Fig.  12 ).

The number of articles reporting study contexts

The great majority of articles reported quantitative data (n = 545), with a very small number collecting qualitative data (n = 40). Similarly, a total of 473 articles reported data from environmental systems, whilst 112 reported data from social systems.

Only 7 articles reported both social and environment data (Table 6 ). The most commonly co-reported social factor was health/safety (n = 5), which was the core focus of several articles measuring environmental health impacts. For several other articles, the social impacts related to economics for otherwise environmental studies. One article [ 53 ] reported across a suite of 7 affected factors.

The measured outcomes/systems

Across all articles, the most commonly reported outcome category was metal concentration (n = 357), followed by water quality (n = 104) and species biomass or distribution (n = 102) (see Fig.  13 ). The most commonly reported social outcome was ‘community’ (i.e. community level social outcome measures) (n = 68), followed by ‘cancer rates/disease/mortality’ (n = 57). The least frequently reported outcome was hydrological flow or landscape change (n = 16).

The number of articles reporting measured outcome categories. Note that some articles reported multiple outcomes

Affected system/component/factor

The systems, components, and factors affected by the mines across included articles is visualised in Fig.  14 and available as an interactive plot on the project website ( https://3mkproject.github.io/research.html ). This shows that the most commonly reported system was biodiversity (n = 352), followed by water (n = 310), societies (n = 178), and soil/geology (n = 52), with air the least common (n = 10).

Radial bubble plot of the systems, components and factors affected across the included studies. Systems are depicted by the bubble colour. Bubble size indicates the number of articles. An interactive version is available at the project website; https://3mkproject.github.io/research.html

Within biodiversity, the most common component was fauna (n = 214), followed by flora (n = 125) and ecosystems (n = 13). Within water, surface, sediment and groundwater were approximately equal (n = 114, 104, and 87 respectively), with ice rather infrequent (n = 5). For societies, health and wellbeing was most common (n = 106), followed by economic (n = 46), service and infrastructure (n = 12), landscapes (n = 8) and culture and history (n = 6). Soil surface was the only component reported for soil/geology articles (n = 52). Within air, atmosphere was most common (n = 9) and climate reported rarely (n = 1).

The most commonly reported factors were individual fauna species (n = 116), water sediment quality (n = 104) and surface water quality (n = 104).

Country-vs-stage

Figure  15 shows how the evidence in the map is distributed across countries and extraction stages, demonstrating that the majority of evidence focuses on operation of mines in Canada. Operation was the most commonly reported stage in Canada, Finland, Russia, Sweden and the USA. In Greenland and Norway post-closure was most frequent. In Russia, the majority of articles focused on operation, with very few on post-closure or remediation relative to Canada and Sweden.

Heat map showing the number of articles across countries and extraction stages

Limitations of the map

Although our systematic mapping spanned 8 countries across the Arctic and boreal regions, we were restricted in the resources available for screening non-English articles from bibliographic databases (although grey literature searching and screening was performed across multiple languages; Finnish, Swedish, Norwegian, and Danish). A total of 307 full texts could not be screened for this reason (see Additional File 5 ).

Due to a lack of resources and time during the COVID-19 pandemic, we were unable to perform a search update as planned. As a result, the systematic map represents a snapshot of research from the end of 2018. An updated search of Web of Science Core Collection databases (see Table 2 ) in June 2021 revealed 2440 records from 2019 to 2021. Assuming the same spread of results across databases, this would have resulted in a total of > 9500 records to screen: almost 25% of the original set of results. Despite this lag from searching to publication, we believe our map is still a valuable assessment of the state of the evidence base, particularly since our assessment of publication rates herein suggested a linear rather than exponential increase in relevant publications over time.

Our screening and data extraction/coding was performed initially using a subset in an attempt to ensure consistency, before proceeding in full with single screening. This is a standard practice amongst systematic reviews and maps published in this journal, and generally considered necessary given the large volumes of evidence common to non-health fields. If we had used full dual screening and data extraction we would have been able to minimise the risk of erroneously excluding some records. However, we believe our methods were both pragmatically necessary and sufficient for the purposes of this mapping exercise.

Limitations of the evidence base

We identified a large evidence base with a long history. The distribution of studies across outcome measures was relatively even (see Fig.  15 ), indicating few biases in research attention across the evidence base as a whole. Studies were spread across eligible regions, but a heavy bias in Canada was evident (317/902 data points; 35%). Any further synthesis of these research studies should be sensitive to this bias.

The majority of study designs compared impacted and control samples (396/585 articles, 68%), followed by correlative studies (142/585 articles, 24%), with very few BACI designs (before-after-control-impacts: 6/585 articles, 1%) and no experimental designs. Although this is to be expected, perhaps, given the systems studied, the causal inference of these designs is poor and could be strengthened with randomised control trial study designs—particularly for impact evaluations of mitigation measures which were completely lacking.

Analysis of the validity of studies was not possible in this map, given the wide diversity of data types and study designs (spanning social and environmental science). Internal validity should be assessed in subsequent systematic reviews.

Implications for research

Our systematic map database and visualisations of the evidence in heat maps allow readers to gauge gaps and clusters, but here we suggest some areas of the evidence base that are sufficient in number to perhaps be suitable for synthesis in full systematic reviews. This list is based on frequently studied higher level categories (the top 3 affected components and factors). This list is indicative only and should not be taken as a priority list of topics for systematic review.

1. On mine operation (n = 428)

1.1. Health/safety (n = 59)

1.2. Air quality (n = 45)

1.3. Fauna individual species (n = 45)

2. On post-closure activities (n = 176)

2.1. Fauna individual species (n = 27)

2.2. Surface water quality (n = 22)

2.3. Water sediment quality (n = 20)

3. On abandonment (n = 167)

3.1. Fauna individual species (n = 47)

3.2. Surface water quality (n = 40)

3.3. Water sediment quality (n = 39)

4. Articles focusing on groundwater quality mitigation measures (n = 60)

Based on our analysis of the evidence base, we also suggest the following topics where there appear to be evidence gaps that warrant further primary research:

Studies on earlier stages of resource extraction prior to operation—from prospecting to construction

Research on the effectiveness of mitigation measures (including ‘how’ things function)

Research employing quasi-experimental (e.g. BACI) and experimental (e.g. randomised control trials) designs for stronger evidence of causality

Migration and demography

Cumulative impacts and multiple pressures, including effects related to a changing climate

Impacts on local and Indigenous communities, especially social, cultural, and health-related

Implications for policy/management

This systematic map demonstrates that there is a large body of evidence on the impacts of metal mining in Arctic and boreal regions. Many topics within the map constitute potential areas for further synthesis or primary research on the impacts of particular types of mining on certain outcomes (described in Implications for Research , above). Relevant funders and decision-makers should ensure they are aware of these gaps and clusters, and commission further research as necessary, making the most of the available evidence. Where large bodies of evidence exist (e.g. operation of mines in Canada), research commissioners should consider whether funding and resources are best placed filling gaps than providing more research on a well-studied topic. Given the inherent connection between mineral development and the Indigenous rightsholders of the north it is also important to ensure that research and synthesis activities are done in ways that involve them and respect their sovereignty, knowledge systems, and cultures.

With efforts to move away from fossil fuels, demand for minerals to support “green” energy technologies is expected to increase. In many parts of the Arctic, these expectations have led to increasing prospecting for minerals and a push for opening new mines. However, mining is often met by protests, especially when new mines or expanded mining activities come into conflict with other land uses and with efforts to protect ecologically valuable nature [ 60 , 61 , 62 , 63 ]. Furthermore, the process for assessing the impacts of mining have been criticised, with calls for more holistic assessment processes that include meaningful engagement by rightsholders and stakeholders [ 64 ] and the whole mining industry is facing increasing distrust [ 65 ]. An essential aspect of transparent assessment processes is access to relevant scientific information on all aspects on the implications of mining, and the mapping provided in this paper shows that information on many aspects is limited, especially impacts related to social wellbeing and the interactions between social and environmental factors. Such studies will require approaches that take the whole social-ecological-technological system into account [ 66 ], while filling such more holistically-oriented studies with details on specific aspects will require the types of research reviewed in this paper. In addition to identifying critical knowledge gaps, the mapping and potential updates of the map thus serve as an important resource for more holistic environmental and social impact assessment that will be essential for (1) protecting the environment, (2) ensuring that the local social consequences of mining are indeed positive also in the longer term, and (3) helping ensure that the mining permit processes do not stall in drawn-out conflicts due to limited (or contested) knowledge about potential impacts. Better assessment processes will not solve conflict over land use but would at least make decisions about acceptable risks and opportunities more transparent.

Whilst it is expected that most mitigation measures will address the construction and operations phases of a mining project, since this is typically what an Environmental and Social Impact Assessment focuses on, the gaps identified in this systematic map point not only to research gaps but problems with the EIA process itself. For example, EIA legislation is rarely applied to the exploration and development phases of mining, which we found evidence of impacts for. This highlights that there should probably be some legal requirement for analysis and addressing these risks in impact assessments in the future. Policy-makers should be aware that the social impacts from mining in particular begin early on in a project’s lifetime. There is a clear need for more research, and more mitigation, to address these issues.

It is also interesting we found no research examining the EIA process itself, including its effectiveness, and no explicit examination of the proposed mitigation measures from EIAs. Monitoring and evaluation of impact assessments are large gaps in mining legislation and research, and this should be addressed with a clear demand for impact assessment evaluation from decision-makers.

Availability of data and materials

All data are available as supplementary information and via the Open Science Framework project site for 3MK: https://osf.io/cvh3u .

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Acknowledgements

We thank the 3MK stakeholders, project team and Advisory Team for comments on the project. The team consisted of Annika E Nilsson, Rasmus Kløcker Larsen, Dag Avango, Steven Cooke, Sif Johansson, Pamela Lesser, Rebecca Lawrence, Kaisa Raito, Rebecca Rees, and Maria Tengö. We also thank Mistra EviEM for co-funding the first Advisory Group meeting and publication fees for the systematic map protocol.

Open Access funding enabled and organized by Projekt DEAL. This manuscript is part of a project (3MK: Mapping the impacts of Mining using Multiple Knowledges) funded by a Formas Open Call Grant (2017-00683).

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Adrienne Smith, Jessica J. Taylor, Christopher Andrews & Steven J. Cooke

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Conceptualisation—NRH; methodology—NRH; software—NRH; formal analysis—NRH; investigation—JJT, AS, CA, NRH; data curation—JJT, NRH; writing—original draft—NRH; writing—review and editing—NRH, AS, JJT, CA, SJC, ARN, PL; visualisation—NRH; supervision—JJT; project administration—NRH, JJT; funding acquisition—NRH, AEN. All authors read and approved the final manuscript.

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Supplementary Information

Additional file 1.

: Roses Form

Additional file 2

: Relevant reviews used for bibliographic checking

Additional file 3

: Benchmark articles used for search comprehensiveness checking

Additional file 4

: Benchmark checking results

Additional file 5

: List of records excluded at full text screening with reasons

Additional file 6

: List of articles not obtainable at full text

Additional file 7

: Meta-data extraction and coding form

Additional file 8

: Systematic map database

Additional file 9

: Interactive evidence atlas

Additional file 10

: R script for producing the visualisations

Additional file 11

: Database of unique mines

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Haddaway, N.R., Smith, A., Taylor, J.J. et al. Evidence of the impacts of metal mining and the effectiveness of mining mitigation measures on social–ecological systems in Arctic and boreal regions: a systematic map. Environ Evid 11 , 30 (2022). https://doi.org/10.1186/s13750-022-00282-y

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The Mining Engineering Department conducts research in state-of-the-art facilities including focus on the following areas of graduate research :

• VR & AI, Robotics
• Ventilation
• Responsible Mining
• Geomechanics, Rock Mechanics and Stability of Underground and Surface Excavation
• Computerized Mine Design and Related Applications (including Geostatistical Modeling)
• Advanced Integrated Mining Systems Incorporating Mine Mechanization and Mechanical Mining Systems
• Underground Excavation (Tunneling) and Construction
• Site Characterization and Geotechnical Investigations, Modeling and Design in Geoengineering
• Rock Fragmentation
• Mineral Processing, Communition, Separation Technology
• Bulk Material Handling

Research Centers

Edgar Experimental Mine

Colorado School of Mines’ Edgar Mine, in Idaho Springs, produced high-grade silver, gold, lead and copper in the 1870s. Today, it serves as an underground laboratory for future engineers, producing valuable experience for those being trained to find, develop and process the world’s natural resources.

Energy, Mining and Construction Industry Safety

EMCIS offers Mine Safety and Health Administration certification classes on a regular basis, including MSHA Part 48 New Miner Training and Annual Refreshers, as well as training in mine rescue, underground search and rescue and tunnel safety.

Excavation Engineering and Earth Mechanics Institute

EMI was established in 1974 to enhance education and research in the field of excavation technology both for mining and civil underground construction. EMI has developed a suite of physical property tests, cutter and cutterhead evaluation procedures for performance prediction, project costing, and design of mechanical rock excavation tools for all types of mechanical excavators.

Underground Construction and Tunneling

The underground community at Mines is comprised of a collaborative, interdisciplinary group of faculty and students from civil engineering, geology and geological engineering, mining engineering and mechanical engineering, as well as geophysics and computer science, with a collective interest in education and research in underground engineering.

In 2024, the year of our 150th anniversary, we will celebrate Colorado School of Mines’ past, present and possibilities. By celebrating and supporting the Campaign for MINES@150 you will help elevate Mines to be an accessible, top-of-mind and first-choice for students, faculty, staff, recruiters and other external partners. The Mining department’s goals for Mines@150 include upgrading facilities, scholarships, and continuing to build on student experiences both in the classroom and out in the field. When you give, you are ensuring Mines becomes even more distinctive and highly sought-after by future students, alumni, industry, and government partners over the next 150 years. We look forward to celebrating Mines’ sesquicentennial with you and recognizing the key role you play in making the MINES@150 vision a reality through your investments of time, talent and treasure. Give now

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Data mining articles from across Nature Portfolio

Data mining is the process of extracting potentially useful information from data sets. It uses a suite of methods to organise, examine and combine large data sets, including machine learning, visualisation methods and statistical analyses. Data mining is used in computational biology and bioinformatics to detect trends or patterns without knowledge of the meaning of the data.

Discrete latent embeddings illuminate cellular diversity in single-cell epigenomics

CASTLE, a deep learning approach, extracts interpretable discrete representations from single-cell chromatin accessibility data, enabling accurate cell type identification, effective data integration, and quantitative insights into gene regulatory mechanisms.

Latest Research and Reviews

Decoding intelligence via symmetry and asymmetry

• Jianjing Fu
• Ching-an Hsiao

Long non-coding RNAs expression and regulation across different brain regions in primates

• Mohit Navandar
• Constance Vennin
• Susanne Gerber

Research on domain ontology construction based on the content features of online rumors

• Jianbo Zhao
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Exploring the pathways of drug repurposing and Panax ginseng treatment mechanisms in chronic heart failure: a disease module analysis perspective

• Chengzhi Xie

Comprehensive data mining reveals RTK/RAS signaling pathway as a promoter of prostate cancer lineage plasticity through transcription factors and CNV

• Guanyun Wei

Anoikis-related gene signatures in colorectal cancer: implications for cell differentiation, immune infiltration, and prognostic prediction

• Taohui Ding

News and Comment

Discovering cryptic natural products by substrate manipulation

Cryptic halogenation reactions result in natural products with diverse structural motifs and bioactivities. However, these halogenated species are difficult to detect with current analytical methods because the final products are often not halogenated. An approach to identify products of cryptic halogenation using halide depletion has now been discovered, opening up space for more effective natural product discovery.

• Ludek Sehnal
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Chroma is a generative model for protein design

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Efficient computation reveals rare CRISPR–Cas systems

A study published in Science develops an efficient mining algorithm to identify and then experimentally characterize many rare CRISPR systems.

SEVtras characterizes cell-type-specific small extracellular vesicle secretion

Although single-cell RNA-sequencing has revolutionized biomedical research, exploring cell states from an extracellular vesicle viewpoint has remained elusive. We present an algorithm, SEVtras, that accurately captures signals from small extracellular vesicles and determines source cell-type secretion activity. SEVtras unlocks an extracellular dimension for single-cell analysis with diagnostic potential.

Protein structural alignment using deep learning

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Home > Statler College of Engineering and Mineral Resources > MININGENG > Mining Engineering Graduate Theses and Dissertations

Mining Engineering Graduate Theses and Dissertations

Theses/dissertations from 2024 2024.

CHARACTERIZATION AND EVALUATION OF VARIOUS BIOCHAR TYPES AS GREEN ADSORBENTS FOR RARE EARTH ELEMENT RECOVERY FROM AQUEOUS SOLUTIONS , Oluwaseun Victor Famobuwa

Selective Recovery of Various Critical Metals from Acid Mine Drainage Sludge , Gorkem Gecimli

Theses/Dissertations from 2023 2023

Development of A Hydrometallurgical Process for the Extraction of Cobalt, Manganese, and Nickel from Acid Mine Drainage Treatment Byproduct , Alejandro Agudelo Mira

Selective Recovery of Rare Earth Elements from Acid Mine Drainage Treatment Byproduct , Zeynep Cicek

Identification of Rockmass Deformation and Lithological Changes in Underground Mines by Using Slam-Based Lidar Technology , Francisco Eduardo Gil Hurtado

Analysis of the Brittle Failure Mechanism of Underground Stone Mine Pillars by Implementing Numerical Modeling in FLAC3D , Rosbel Jimenez

Analysis of the root causes of fatal injuries in the United States surface mines between 2008 and 2021. , Maria Fernanda Quintero

AUGMENTED REALITY AND MOBILE SYSTEMS FOR HEAVY EQUIPMENT OPERATORS IN SURFACE MINING , Juan David Valencia Quiceno

Theses/Dissertations from 2022 2022

Integrated Large Discontinuity Factor, Lamodel and Stability Mapping Approach for Stone Mine Pillar Stability , Mustafa Baris Ates

Noise Exposure Trends Among Violating Coal Mines, 2000 to 2021 , Hanna Grace Davis

Calcite depression in bastnaesite-calcite flotation system using organic acids , Emmy Muhoza

Investigation of Geomechanical Behavior of Laminated Rock Mass Through Experimental and Numerical Approach , Qingwen Shi

Static Liquefaction in Tailing Dams , Jose Raul Zela Concha

Experimental and Theoretical Investigation on the Initiation Mechanism of Low-Rank Coal's Self-Heating Process , Yinan Zhang

Development of an Entry-Scale Modeling Methodology to Provide Ground Reaction Curves for Longwall Gateroad Support Evaluation , Haochen Zhao

Size effect and anisotropy on the strength of shale under compressive stress conditions , Yun Zhao

Theses/Dissertations from 2021 2021

Evaluation of LIDAR systems for rock mass discontinuity identification in underground stone mines from 3D point cloud data , Mario Alejandro Bendezu de la Cruz

Implementing the Empirical Stone Mine Pillar Strength Equation into the Boundary Element Method Software LaModel , Samuel Escobar

Recovery of Phosphorus from Florida Phosphatic Waste Clay , Amir Eskanlou

Optimization of Operating Conditions and Design Parameters on Coal Ultra-Fine Grinding Through Kinetic Stirred Mill Tests and Numerical Modeling , Francisco Patino

The Effect of Natural Fractures on the Mechanical Behavior of Limestone Pillars: A Synthetic Rock Mass Approach Application , Mustafa Can Süner

Evaluation of Various Separation Techniques for the Removal of Actinides from A Rare Earth-Containing Solution Generated from Coarse Coal Refuse , Deniz Talan

Geology Oriented Loading Approach for Underground Coal Mines , Deniz Tuncay

Various Operational Aspects of the Extraction of Critical Minerals from Acid Mine Drainage and Its Treatment By-product , Zhongqing Xiao

Theses/Dissertations from 2020 2020

Adaptation of Coal Mine Floor Rating (CMFR) to Eastern U.S. Coal Mines , Sena Cicek

Upstream Tailings Dam - Liquefaction , Mladen Dragic

Development, Analysis and Case Studies of Impact Resistant Steel Sets for Underground Roof Fall Rehabilitation , Dakota D. Faulkner

The influence of spatial variance on rock strength and mechanism of failure , Danqing Gao

Fundamental Studies on the Recovery of Rare Earth Elements from Acid Mine Drainage , Xue Huang

Rational drilling control parameters to reduce respirable dust during roof bolting operations , Hua Jiang

Solutions to Some Mine Subsidence Research Challenges , Jian Yang

An Interactive Mobile Equipment Task-Training with Virtual Reality , Lazar Zujovic

Theses/Dissertations from 2019 2019

Fundamental Mechanism of Time Dependent Failure in Shale , Neel Gupta

A Critical Assessment on the Resources and Extraction of Rare Earth Elements from Acid Mine Drainage , Christopher R. Vass

Time-dependent deformation and associated failure of roof in underground mines , Yuting Xue

Theses/Dissertations from 2018 2018

Parametric Study of Coal Liberation Behavior Using Silica Grinding Media , Adewale Wasiu Adeniji

Three-dimensional Numerical Modeling Encompassing the Stability of a Vertical Gas Well Subjected to Longwall Mining Operation - A Case Study , Bonaventura Alves Mangu Bali

Shale Characterization and Size-effect study using Scanning Electron Microscopy and X-Ray Diffraction , Debashis Das

Behaviour Of Laminated Roof Under High Horizontal Stress , Prasoon Garg

Theses/Dissertations from 2017 2017

Optimization of Mineral Processing Circuit Design under Uncertainty , Seyed Hassan Amini

Evaluation of Ultrasonic Velocity Tests to Characterize Extraterrestrial Rock Masses , Thomas W. Edge II

A Photogrammetry Program for Physical Modeling of Subsurface Subsidence Process , Yujia Lian

An Area-Based Calculation of the Analysis of Roof Bolt Systems (ARBS) , Aanand Nandula

Developing and implementing new algorithms into the LaModel program for numerical analysis of multiple seam interactions , Mehdi Rajaeebaygi

Adapting Roof Support Methods for Anchoring Satellites on Asteroids , Grant B. Speer

Simulation of Venturi Tube Design for Column Flotation Using Computational Fluid Dynamics , Wan Wang

Theses/Dissertations from 2016 2016

Critical Analysis of Longwall Ventilation Systems and Removal of Methane , Robert B. Krog

Implementing the Local Mine Stiffness Calculation in LaModel , Kaifang Li

Development of Emission Factors (EFs) Model for Coal Train Loading Operations , Bisleshana Brahma Prakash

Nondestructive Methods to Characterize Rock Mechanical Properties at Low-Temperature: Applications for Asteroid Capture Technologies , Kara A. Savage

Mineral Asset Valuation Under Economic Uncertainty: A Complex System for Operational Flexibility , Marcell B. B. Silveira

A Feasibility Study for the Automated Monitoring and Control of Mine Water Discharges , Christopher R. Vass

Spontaneous Combustion of South American Coal , Brunno C. C. Vieira

Calibrating LaModel for Subsidence , Jian Yang

Theses/Dissertations from 2015 2015

Coal Quality Management Model for a Dome Storage (DS-CQMM) , Manuel Alejandro Badani Prado

Design Programs for Highwall Mining Operations , Ming Fan

Development of Drilling Control Technology to Reduce Drilling Noise during Roof Bolting Operations , Mingming Li

The Online LaModel User's & Training Manual Development & Testing , Christopher R. Newman

How to mitigate coal mine bumps through understanding the violent failure of coal specimens , Gamal Rashed

Theses/Dissertations from 2014 2014

Effect of biaxial and triaxial stresses on coal mine shale rocks , Shrey Arora

Stability Analysis of Bleeder Entries in Underground Coal Mines Using the Displacement-Discontinuity and Finite-Difference Programs , Xu Tang

Experimental and Theoretical Studies of Kinetics and Quality Parameters to Determine Spontaneous Combustion Propensity of U.S. Coals , Xinyang Wang

Bubble Size Effects in Coal Flotation and Phosphate Reverse Flotation using a Pico-nano Bubble Generator , Yu Xiong

Integrating the LaModel and ARMPS Programs (ARMPS-LAM) , Peng Zhang

Theses/Dissertations from 2013 2013

Column Flotation of Subbituminous Coal Using the Blend of Trimethyl Pentanediol Derivatives and Pico-Nano Bubbles , Jinxiang Chen

Applications of Surface and Subsurface Subsidence Theories to Solve Ground Control Problems , Biao Qiu

Calibrating the LaModel Program for Shallow Cover Multiple-Seam Mines , Morgan M. Sears

The Integration of a Coal Mine Emergency Communication Network into Pre-Mine Planning and Development , Mark F. Sindelar

Factors considered for increasing longwall panel width , Jack D. Trackemas

An experimental investigation of the creep behavior of an underground coalmine roof with shale formation , Priyesh Verma

Evaluation of Rope Shovel Operators in Surface Coal Mining Using a Multi-Attribute Decision-Making Model , Ivana M. Vukotic

Theses/Dissertations from 2012 2012

Calculating the Surface Seismic Signal from a Trapped Miner , Adeniyi A. Adebisi

Comprehensive and Integrated Model for Atmospheric Status in Sealed Underground Mine Areas , Jianwei Cheng

Production and Cost Assessment of a Potential Application of Surface Miners in Coal Mining in West Virginia , Timothy A. Nolan

The Integration of Geomorphic Design into West Virginia Surface Mine Reclamation , Alison E. Sears

Truck Cycle and Delay Automated Data Collection System (TCD-ADCS) for Surface Coal Mining , Patricio G. Terrazas Prado

New Abutment Angle Concept for Underground Coal Mining , Ihsan Berk Tulu

Theses/Dissertations from 2011 2011

Experimental analysis of the post-failure behavior of coal and rock under laboratory compression tests , Dachao Neil Nie

The influence of interface friction and w/h ratio on the violence of coal specimen failure , Simon H. Prassetyo

Theses/Dissertations from 2010 2010

A risk management approach to pillar extraction in the Central Appalachian coalfields , Patrick R. Bucks

The Impacts of Longwall Mining on Groundwater Systems -- A Case of Cumberland Mine Panels B5 and B6 , Xinzhi Du

Evaluation of ultrafine spiral concentrators for coal cleaning , Meng Yang

Theses/Dissertations from 2009 2009

Development of a coal reserve GIS model and estimation of the recoverability and extraction costs , Chandrakanth Reddy Apala

Application and evaluation of spiral separators for fine coal cleaning , Zhuping Che

Weak floor stability in the Illinois Basin underground coal mines , Murali M. Gadde

Design of reinforced concrete seals for underground coal mines , Rajagopala Reddy Kallu

Employing laboratory physical modeling to study the radio imaging method (RIM) , Jun Lu

Influence of cutting sequence and time effects on cutters and roof falls in underground coal mine -- numerical approach , Anil Kumar Ray

Implementing energy release rate calculations into the LaModel program , Morgan M. Sears

Modeling PDC cutter rock interaction , Ihsan Berk Tulu

Analytical determination of strain energy for the studies of coal mine bumps , Qiang Xu

Improvement of the mine fire simulation program MFIRE , Lihong Zhou

Theses/Dissertations from 2008 2008

Program-assisted analysis of the transverse pressure capacity of block stoppings for mine ventilation control , Timothy J. Batchler

Analysis of factors affecting wireless communication systems in underground coal mines , David P. McGraw

Analysis of underground coal mine refuge shelters , Mickey D. Mitchell

Theses/Dissertations from 2007 2007

Dolomite flotation of high magnesium phosphate ores using fatty acid soap collectors , Zhengxing Gu

Evaluation of longwall face support hydraulic supply systems , Ted M. Klemetti II

Experimental studies of electromagnetic signals to enhance radio imaging method (RIM) , William D. Monaghan

Analysis of water monitoring data for longwall panels , Joseph R. Zirkle

Theses/Dissertations from 2006 2006

Measurements of the electrical properties of coal measure rocks , Nikolay D. Boykov

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Informed, Safe and Sustainable Mining

The UA Department of Mining and Geological Engineering is a global leader in research involving mining communication platforms, water conservation in mines, subsurface fluid extraction, concrete alternatives, and health and safety networks.

MGE researchers are working on a wide range of interdisciplinary research projects and commercial products – systems that monitor miners’ health, software for safety training, better methods for mineral separation, and technology to automate mine operations, for example.

Focus Areas

UA mining and geological engineering research focuses on the following  primary areas :

Geophysical sensing techniques

Mine health and safety

Mineral and chemical characterization

Mineral processing, geometallurgy and extractive metallurgy

Mine technology and automation

Rock strength, fracturing and excavation

Sustainable mining and development

Research Centers and Facilities

MGE has two one-of-a-kind resources working to make mining sustainable worldwide and providing industry-level student training. 

First, MGE students and faculty are integral to the university’s globally influential  Lowell Institute for Mineral Resources . Secondly, for research and training, the department operates the UA’s  San Xavier Underground Mining Laboratory , the only underground mining lab with a working vertical shaft in the United States.

See UA College of Engineering-affiliated  Research Centers and Institutes .

Project Highlights

Multidisciplinary Mining

James Werner , assistant director of the San Xavier Mining Laboratory, works at a crossroads of industry, education and high-impact projects.

Gaming for Safety

An interactive mining safety training program promises to keep trainees on their toes. Mary Poulton , retired professor and former department head, was among the inventors.

Conserving Every Last Drop

Professor Moe Momayez , collaborating with Nathan Barba of RePower Design, has invented Hexocover, a technology that prevents evaporation to conserve water in mining tailings ponds.

Taking a Crack at Earth’s Mystery

Isabel Barton , research scientist at the Lowell Institute for Mineral Resources, is on a team studying how underground fluids affect subsurface rocks in the Paradox Basin. UA President Robert C. Robbins says the project is an impressive undertaking.

Featured Videos

Isabel Barton – MGE Associate Professor

MGE chair Kray Luxbacher and Greg Boyce of Rio Tinto/Peabody Energy discuss the state of mining and exciting developments on the horizon

Dave Travis – VP, Freeport-McMoRan Copper & Gold Inc. and Brad Ross – Interim Director, UA School of Mining & Mineral Resources

Wildcat Moon Miners - Aqua Blue

 / 

A system for testing technology to draw minerals from seawater at the Pacific Northwest National Laboratory in Sequim, Washington. Pacific Northwest National Laboratory

In Seawater, Researchers See an Untapped Bounty of Critical Metals

Researchers and companies are aiming to draw key minerals, including lithium and magnesium, from ocean water, desalination plant residue, and industrial waste brine. They say their processes will use less land and produce less pollution than mining, but major hurdles remain.

By Jim Robbins • May 15, 2024

Can metals that naturally occur in seawater be mined, and can they be mined sustainably? A company in Oakland, California, says yes. And not only is it extracting magnesium from ocean water — and from waste brine generated by industry — it is doing it in a carbon-neutral way. Magrathea Metals has produced small amounts of magnesium in pilot projects, and with financial support from the U.S. Defense Department, it is building a larger-scale facility to produce hundreds of tons of the metal over two to four years. By 2028, it says it plans to be operating a facility that will annually produce more than 10,000 tons.

Magnesium is far lighter and stronger than steel, and it’s critical to the aircraft, automobile, steel, and defense industries, which is why the government has bankrolled the venture. Right now, China produces about 85 percent of the world’s magnesium in a dirty, carbon-intensive process. Finding a way to produce magnesium domestically using renewable energy, then, is not only an economic and environmental issue, it’s a strategic one. “With a flick of a finger, China could shut down steelmaking in the U.S. by ending the export of magnesium,” said Alex Grant, Magrathea’s CEO and an expert in the field of decarbonizing the production of metals.

“China uses a lot of coal and a lot of labor,” Grant continued. “We don’t use any coal and [use] a much lower quantity of labor.” The method is low cost in part because the company can use wind and solar energy during off-peak hours, when it is cheapest. As a result, Grant estimates their metal will cost about half that of traditional producers working with ore.

Every day, desalination plants globally produce 37 billion gallons of brine containing copper, zinc, and other metals.

Magrathea — named after a planet in the hit novel The Hitchhiker’s Guide to the Galaxy — buys waste brines, often from desalination plants, and allows the water to evaporate, leaving behind magnesium chloride salts. Next, it passes an electrical current through the salts to separate them from the molten magnesium, which is then cast into ingots or machine components.

While humans have long coaxed minerals and chemicals from seawater — sea salt has been extracted from ocean water for millennia — researchers around the world are now broadening their scope as the demand for lithium, cobalt, and other metals used in battery technology has ramped up. Companies are scrambling to find new deposits in unlikely places, both to avoid orebody mining and to reduce pollution. The next frontier for critical minerals and chemicals appears to be salty water, or brine.

Brines come from a number of sources: much new research focuses on the potential for extracting metals from briny wastes generated by industry, including coal-fired power plants that discharge waste into tailings ponds; wastewater pumped out of oil and gas wells — called produced water; wastewater from hard-rock mining; and desalination plants.

A technician pours a magnesium ingot at the Magrathea Metals facility in Oakland, California. Alex Grant

Large-scale brine mining could have negative environmental impacts — some waste will need to be disposed of, for example. But because no large-scale operations currently exist, potential impacts are unknown. Still, the process is expected to have numerous positive effects, chief among them that it will produce valuable metals without the massive land disturbance and creation of acid-mine drainage and other pollution associated with hard-rock mining.

According to the Brine Miners, a research center at Oregon State University, there are roughly 18,000 desalination plants, globally, taking in 23 trillion gallons of ocean water a year and either forcing it through semipermeable membranes — in a process called reverse osmosis — or using other methods to separate water molecules from impurities. Every day, the plants produce more than 37 billion gallons of brine — enough to fill 50,000 Olympic-size swimming pools. That solution contains large amounts of copper, zinc, magnesium, and other valuable metals.

Disposing of brine from desalination plants has always been a challenge. In coastal areas, desal plants shunt that waste back into the ocean, where it settles to the sea floor and can damage marine ecosystems. Because the brine is so highly concentrated, it is toxic to plants and animals; inland desalination plants either bury their waste or inject it into wells. These processes further raise the cost of an already expensive process, and the problem is only growing as desal plants proliferate globally.

Brine from desalination plants contains an estimated $2.2 trillion worth of materials, including more than 17,400 tons of lithium.

Finding a lucrative and safe use for brine will help solve plants’ waste problems and, by using their brine to feed another process, nudge them toward a circular economy, in which residue from one industrial activity becomes source material for a new activity. According to OSU estimates, brine from desalination plants contains $2.2 trillion worth of materials, including more than 17,400 tons of lithium, which is crucial for making batteries for electric vehicles, appliances, and electrical energy storage systems. In some cases, mining brine for lithium and other metals and minerals could make the remaining waste stream less toxic.

For many decades manufacturers have extracted magnesium and lithium from naturally occurring brines. In California’s Salton Sea, which contains enough lithium to meet the nation’s needs for decades, according to a 2023 federal analysis , companies have drilled geothermal wells to generate the energy required for separating the metal from brines.

And in rural Arkansas, ExxonMobil recently announced that it is building one of the largest lithium processing facilities in the world — a state-of-the-art facility that will siphon lithium from brine deep within the Smackover geological formation. By 2030, the company says it will produce 15 percent of the world’s lithium.

Ingots comprised of magnesium drawn from seawater by Magrathea Metals. Magrathea Metals

Miners have largely ignored the minerals found in desalination brine because concentrating them has not been economical. But new technologies and other innovations have created more effective separation methods and enabled companies to focus on this vast resource.

“Three vectors are converging,” said Peter Fiske, director of the National Alliance for Water Innovation at the Department of Energy’s Lawrence Berkeley National Laboratory in Berkeley. “The value of some of these critical materials is going up. The cost of conventional [open pit] mining and extraction is going up. And the security of international suppliers, especially Russia and China, is going down.“

There is also an emphasis on — and grant money from the Department of Defense, the Department of Energy, and elsewhere for — projects and businesses that release extremely low, zero, or negative greenhouse gas emissions and that can be part of a circular economy. Researchers who study brine mining believe the holy grail of desalination — finding more than enough value in its waste brine to pay for the expensive process of creating fresh water — is attainable.

New technology allows firms to “pick through the garbage piles of wastewater and pick out the high-value items,” says a researcher.

Improved filtering technologies can now remove far more, and far smaller, materials suspended in briny water. “We have membranes now that are selective to an individual ion,” said Fiske. “The technology [allows us] to pick through the garbage piles of wastewater and pick out the high-value items.” One of the fundamental concepts driving this research, he says, “is that there is no such thing as wastewater.”

NEOM, the controversial and hugely expensive futuristic city under construction in the Saudi Arabian desert, has assembled a highly regarded international team to build a desalination plant and a facility to both mine its waste for minerals and chemicals and minimize the amount of material it must dispose of. ENOWA, the water and energy division of NEOM, claims that its selective membranes — which include reverse and forward osmosis — will target specific minerals and extract 99.5 percent of the waste brine’s potassium chloride, an important fertilizer with high market value. The system uses half the energy and requires half the capital costs of traditional methods of potassium chloride production. ENOWA says it is developing other selective membranes to process other minerals, such as lithium and rubidium salts, from waste brine.

The Brine Miner project in Oregon has created an experimental system to desalinate saltwater and extract lithium, rare earth, and other metals. The whole process will be powered by green hydrogen, which researchers will create by splitting apart water’s hydrogen and oxygen molecules using renewable energy. “We are trying for a circular process,” said Zhenxing Feng, who leads the project at OSU. “We are not wasting any parts.”

The Kay Bailey Hutchison Desalination Plant in El Paso, Texas produces waste brine containing gypsum and hydrochloric acid. Jeffrey Phillips via Flickr

The concept of mining desalination brine and other wastewater is being explored and implemented all over the world. At Delft University of Technology, in the Netherlands, researchers have extracted a bio-based material they call Kaumera from sludge granules formed during the treatment of municipal wastewater. Combined with other raw materials, Kaumera — which is both a binder and an adhesive, and both repels and retains water — can be used in agriculture and the textile and construction industries.

Another large-scale European project called Sea4Value , which has partners in eight countries, will use a combination of technologies to concentrate, extract, purify, and crystallize 10 target elements from brines. Publicly funded labs in the U.S., including the Department of Energy’s Ames Laboratory, at Iowa State University, and Oak Ridge National Laboratory, in Tennessee, are also researching new methods for extracting lithium and other materials important for the energy transition from natural and industrial brines.

At the Kay Bailey Hutchison Desalination Plant in El Paso, Texas, which provides more than 27 million gallons of fresh water a day from brackish aquifers, waste brine is trucked to and pumped into an injection well 22 miles away. But first, a company called Upwell Water , which has a facility near the desalination plant, wrings more potable water from the brine and uses the remaining waste to produce gypsum and hydrochloric acid for industrial customers.

As industry faces more stringent regulations, the prospects for brine mining look promising, says an expert.

There are hurdles to successful brine mining projects. Christos Charisiadis, the brine innovation manager for the NEOM portfolio, identified several potential bottlenecks: high initial investment for processing facilities; a lack of transparency in innovation by the water industry, which might obscure problems with their technologies; poor understanding of possible environmental problems due to a lack of comprehensive lifecycle assessments; complex and inconsistent regulatory frameworks; and fluctuations in commodity prices.

Still, Nathanial Cooper, an assistant professor at Cambridge University who has studied metal recovery from a variety of industrial and natural brines, considers its prospects promising as environmental regulations for a wide range of industries become ever more stringent.

“Companies that produce wastewater are going to be required to do more and more to ensure the wastewater they dispose of is clean of pollutants and hazardous material,” he said. “Many companies will be forced to find ways to recover these materials. There is strong potential to recover many valuable materials from wastewater and contribute to a circular economy.”

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Artificial Intelligence and Machine Learning and Data Mining

Computer scientists introduce innovative new work at annual conferences.  The Artificial Intelligence and Machine Learning and Data Mining research community expands the state of the art at these, the field's most prestigious and selective conferences:

Artificial Intelligence (AI) researchers now predict that computers will be able to perform tasks that were once considered the prerogative of human beings.

They include tasks such as driving trucks, translating languages, writing high school essays, creating art, analyzing forensic evidence, and even work as a surgeon.  Although some of these goals are predicted to happen over several decades, AI is concerned with  principles and algorithms that allow researchers to make such bold predictions.  Current methods focus on variants of deep learning — such as convolutional nets, recurrent nets, autoencoders and adversarial networks — as well as on the methods of probabilistic graphical models.

School/University Centers and Institutes

• Center for Unified Biometrics and Sensors (CUBS)
• Center of Excellence for Document Analysis and Recognition (CEDAR)
• UB Artificial Intelligence Institute (AII)
• UB Center for Cognitive Science (CCS)

CSE Research Labs and Groups

• Artificial Intelligence Innovation Lab (A2IL)
• UB Data Science Research Group
• UB Media Forensic Lab
• Visual Computing Lab
• X-Lab@UB: Accelerating AI Systems & Solutions

Affiliated Faculty

113I Davis Hall

Phone: (716) 645-1590

[email protected]

Research Topics: Wireless systems; mobile computing; Internet of Things (IoT); wireless sensing; machine learning

213 Capen Hall

Phone: (716) 645-4747

[email protected]

Research Topics: Big data analytics; anomaly detection

338L Davis Hall

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Research Ranking

UB's institutional reputation in the field of computer science has improved dramatically over the last decade.  By the most valid measure, our national ranking has risen from 50th to 29th .

The Computing Research Association (CRA) is a leading computer science advocacy organization whose mission is to unite industry, academia, and government.  The CRA recommends CSRankings: Computer Science Rankings as the best institutional ranking agency, preferring it over the traditional standard, the US News and World Report Best Graduate Schools report.

The CRA supports the CSRankings report because its evaluative criteria meet the ' GOTO ' standard:

Good data .  Data have been cleaned and curated.

Open .  Data available, regarding attributes measured, at least for verification.  

Transparent .  Process and methodologies are entirely transparent.

Objective .  Based on measurable attributes.

For more details, see Department Rankings , by H.V. Jagadish .

According to CSRankings (2008-2018) , UB's 10-year computer science institutional ranking is #50 in the nation, tied with the University of Central Florida and the University of North Carolina .

According to CSRankings (2015-2018) , UB's three-year computer science institutional ranking is #34 in the nation, making our peer institution the University of Virginia .

According to CSRankings (2017-2018) , UB's one-year computer science institutional ranking is #29 in the nation, putting us in company with Harvard , Johns Hopkins , Ohio State , and Penn State .

Research Highlights

Ken Regan develops algorithms that detect cheating in chess games.  His software compares a player's moves to a database of the player's typical gameplay, then makes an assessment of the statistical likelihood of cheating.  Dr. Regan frequently consults at international chess matches.

Karthik Dantu owns the vision component of the RoboBee Initiative , led by the National Science Foundation and Harvard University.  The "eyes" that Dr. Dantu is integrating are laser-powered sensors that enable the mechanical bees to orient themselves in space.

Wenyao Xu leads an NSF-funded program that detects 3D printing data security vulnerabilities by using smart phones to analyze electromagnetic and acoustic waves.  Kui Ren and Chi Zhou are co-authors.

Proposed software solution could extend battery life, reduce energy consumption.

Professor and Chair Chunming Qiao leads Instrument for Connected and Autonomous Vehicle Evaluation and Experimentation (iCAVE2) —a multidisciplinary academic-industrial partnership that's helping to make self-driving cars safer, cleaner, and more efficient.

Wenyao Xu created AutoDietary — software that tracks the unique sounds produced by food as people chew it.  AutoDietary, placed near the throat by a necklace delivery system developed at China's Northeastern University, helps users measure their caloric intake.

An article on PhysOrg reports UB has received a $584,469 grant from the National Science Foundation to create a tool designed to work with the existing computing infrastructure to boost data transfer speeds by more than 10 times, and quotes Tevfik Kosar , associate professor of computer science.

Recognitions

Multiple faculty members and students from SEAS were nominated by students, faculty and staff for Pillar of Leadership Awards.

Deborah Chung and Venu Govindaraju will receive the UB President’s Medal,   recognizing extraordinary service to the university.

Jinjun Xiong, SUNY Empire Innovation Professor in the Department of Computer Science and Engineering, has been elevated to fellow in the Institute of Electrical and Electronics Engineers. 

Awards acknowledge and provide system-wide recognition for consistently superior professional achievement and the ongoing pursuit of excellence.

Atri Rudra has been named the first Katherine Johnson Chair in Artificial Intelligence, which was established by a generous gift from computer science alums D. Sivakumar, PhD ’96, and Uma Mahadevan, PhD ’98.

• Directories

Mining Geology Research Group

Primary investigator: dr. elizabeth holley.

Everyone deserves access to the natural resources that enable healthy, safe, and fulfilling lives. As the world’s population expands, we must be increasingly creative to find and exploit these resources while minimizing environmental impact and leveraging positive outcomes for communities. Our efforts towards this goal span the mining lifecycle: we utilize geological tools to address technical and socio-technical problems in mineral exploration, mine development, production, and reclamation. We are fortunate to have strong support from industry, federal agencies, and NGOs. Our interdisciplinary team of geologists and mining engineers works in close collaboration with anthropologists, community members, educators, environmental engineers, geographers, and policy-makers around the world. Together we’re tackling some of the most pressing problems of our era.

Publications

View publications by Dr. Elizabeth Holley, her team and colleagues

View our current ongoing projects, and learn more about past projects too.

 Meet some of the current members of our team, as well as past student and faculty members.

Teaching and Outreach

Helping future generations make a difference.

DR. ELIZABETH HOLLEY

– Elizabeth

Campus News

• Mines team comes out on top at All in Steel competitions Colorado School of Mines teams had a great showing at the 2024 All in Steel competitions, taking the top prize in one challenge and runner-up in another.
• Lori Tunstall wins NSF CAREER Award for research on concrete sustainability and durability Lori Tunstall, assistant professor of civil and environmental engineering at Colorado School of Mines, has received a National Science Foundation CAREER Award for her work on improving concrete durabi …
• Mines researchers on two finalist teams for $310M NASA Earth System Explorer mission Geophysics' Bia Villas Bôas and Matthew Siegfried are members of two proposed missions to improve understanding of key Earth science focus areas for the benefit of all. Colorado School of Mines g …

• May 30, 2024 | “Mind-Boggling” – Scripps Scientists Uncover New Molecular Drivers of Alzheimer’s
• May 30, 2024 | Trailblazers in Genetics: Researchers Chase the Cure for Rare Hereditary Diseases
• May 30, 2024 | Sun Struck: NASA Captures Intense X-Class Solar Flares
• May 30, 2024 | Dementia Breakthrough: New AI Solves in Minutes a Challenge That Would Take Neuroscientists Weeks
• May 30, 2024 | Surprising Discovery: Atlantic Cownose Rays in Bermuda Linked to Climate Anomaly

From Black Gold to Green Energy: Mining Rare Earths Alongside Coal

By Brian Maffly, University of Utah May 26, 2024

Michael Vanden Berg, geologist with the Utah Geological Survey, examines a coal outcrop near Utah’s old Star Point mine. Credit: Lauren Birgenheier, University of Utah

New research documents elevated levels of these metals, needed for energy transition, above and below coal seams in Utah and Colorado.

Deposits of designated critical minerals needed to transition the world’s energy systems away from fossil fuels may, ironically enough, be co-located with coal deposits that have been mined to produce the fossil fuel most implicated in climate change.

Now, research led by the University of Utah has documented elevated concentrations of a key subset of critical minerals, known as rare earth elements, or REEs, in active mines rimming the Uinta coal belt of Colorado and Utah.

These findings open the possibility that these mines could see a secondary resource stream in the form of metals used in renewable energy and numerous other high-tech applications, according to study co-author Lauren Birgenheier, an associate professor of geology and geophysics.

“The model is if you’re already moving rock, could you move a little more rock for resources towards energy transition?” Birgenheier said. “In those areas, we’re finding that the rare earth elements are concentrated in fine-grain shale units, the muddy shales that are above and below the coal seams.”

University of Utah geologist Lauren Birgenheier inspects samples at a coal processing waste pile. Credit: Michael Vanden Berg, Utah Geological Survey

A Search for Alternate Sources of Rare Earths

This research was conducted in partnership with the Utah Geological Survey and Colorado Geological Survey as part of the Department of Energy-funded Carbon Ore, Rare Earth and Critical Minerals project, or CORE-CM. The new findings will form the basis for a grant request of an additional $9.4 million in federal funding to continue the research.

While these metals are crucial for U.S. manufacturing, especially in high-end technologies, they are largely sourced from overseas.

“When we talk about them as ‘critical minerals,’ a lot of the criticality is related to the supply chain and the processing,” said Michael Free, a professor of metallurgical engineering and the principal investigator on the DOE grant. “This project is designed around looking at some alternative unconventional domestic sources for these materials.”

The U-led study was published last month in the journal Frontiers in Earth Science . Team members included graduate students Haley Coe, the lead author, and Diego Fernandez, a research professor who runs the lab that tested samples.

What Are Rare Earth Elements? Despite the moniker, rare earth elements (REEs) are not rare in Earth’s crust, but they are rarely found in concentrations high enough to make mining them economical Nearly 90% of the global supply is processed in China, according to the Bipartisan Policy Center . These metallic elements include the 15 within the lanthanide series as well as scandium (Sc) and yttrium (Y), all found in the third column of the Periodic Table. These elements are usually found in their oxide forms. Because they exist in such low concentrations, these minerals are hard to separate from ores and from each other. Rare earths hold special properties that make them essential ingredients in materials associated with high-tech applications . “It’s really rooted in the kinds of compounds that you can form with these rare elements or these critical minerals that make them attractive and more efficient,” said Michael Free, a University of Utah professor of metallurgical engineering. “When you look at the rarer elements, neodymium (Nd) praseodymium (Pr) and dysprosium (Dy), they can be combined with other elements to form high-power magnets.” Many lanthanide compounds are used in glass and catalysts, as well as magnets, superconductors, phosphors, lasers and luminescent materials. Rare earths also found in everyday technology, such televisions and smartphone screens, medical devices, auto- and fluid catalysts. Carbon-neutral energy technology, including wind turbines, solar panels, electric vehicles, rechargeable batteries and energy-efficient lighting, also require these elements. “With turbine blades, for example, in a windmill to generate power, you want to use the higher powered magnets to make them more efficient. It basically helps us in some of this energy transition. It’s about energy efficiency, it’s about energy density for storage,” Free said. “There’s a lot of strategic kinds of things with some of these elements that are critical, that are used in high-end electronic devices and satellite technologies and defense applications.These kind of elements perform much better than the more common elements that we’re familiar with.” The U.S. uses, on average, 8,300 metric tons of rare-earth oxides a year, according to the U.S. Geological Survey. The Mountain Pass mine in California’s Mojave Desert is the nation’s largest producer of rare earth elements, but most of its output is sent overseas for processing. “The supply here is not very established in some cases. It was established to some extent, but then it got shipped overseas because we didn’t want to do the sourcing here. We didn’t want to open up new mines here,” Free said. “So that leaves us vulnerable for a lot of these higher-end technologies and the clean-energy technologies that we’re trying to get more into.

The association between coal and REE deposits has been well documented elsewhere, but little data had been previously analyzed relevant to Utah and Colorado’s once busy coal fields, which have fallen on hard times as domestic demand for coal has shriveled. Among a longer-term decline, however, remaining active coal mines in Utah and Colorado report that they can’t mine fast enough in recent years to meet demand and high coal prices.

“The goal of this phase-one project was to collect additional data to try and understand whether this was something worth pursuing in the West,” said study co-author Michael Vanden Berg, Energy and Minerals Program Manager at the Utah Geological Survey. “Is there rare earth element enrichment in these rocks that could provide some kind of byproduct or value added to the coal mining industry?”

The study targeted the coal-producing region stretching from Utah’s Wasatch Plateau east across the Book Cliffs deep into Colorado. Researchers analyzed 3,500 samples from 10 mines, four mine waste piles, seven stratigraphically complete cores, and even some coal ash piles near power plants.

The study included Utah’s active Skyline, Gentry, Emery and Sufco mines, recently-idled Dugout and Lila Canyon mines in the Book Cliffs, and the historic Star Point and Beaver Creek No. 8 mines. The Colorado mines studied were the Deserado and West Elk.

Analyzing Rock Samples by the Thousands

“The coal itself is not enriched in rare earth elements,” Vanden Berg said. “There’s not going to be a byproduct from mining the coal, but for a company mining the coal seam, could they take a couple of feet of the floor at the same time? Could they take a couple of feet of the ceiling? Could there be potential there? That’s the direction that the data led us.”

To gather samples, the team worked directly with mine operators and examined coal seam outcrops and processing waste piles. In some cases, they analyzed drilling cores, both archived cores and recently drilled ones at the mines. The team entered Utah mines to collect rock samples from the underground ramps that connect coal seams.

Researchers deployed two different methods to record levels of REE’s present, expressed in parts per million, or ppm, in the samples. One was a hand-held device for quick readings in the field, the other used Inductively Coupled Plasma-Mass Spectrometry, or ICP-MS, in the on-campus lab overseen by Fernandez.

“We’re mostly using this portable X-ray fluorescence device, which is an analysis gun that we hold to the rock for two minutes, and it only gives us five or six of the 17 rare earth elements,” Birgenheier said. If samples showed concentrations higher than 200 parts per million, or ppm, they ran a more complete analysis using the mass spectrometry equipment on campus.

The Department of Energy has set 300 ppm as the minimum concentration for rare earth mining to be potentially economically viable. However, for the study, researchers deemed concentrations greater than 200 ppm to be considered “REE enriched.”

The study found the highest prevalence of such concentrations in coal-adjacent formations of siltstone and shale, while sandstone and the coal itself were mostly devoid of rare earths.

The team has analyzed 11,000 samples to date, far more than were used in the published study. The next steps include determining how much rare earth ore is present, likely to be done with colleagues at the University of Wyoming and New Mexico Institute of Mining and Technology.

“We still have results that are ongoing and papers that’ll be coming out soon,” Birgenheier said. “We’re writing a proposal now for phase two. We can’t make resource volume estimates yet because we don’t have that data. This next phase will push us towards answering, ‘how do we actually calculate a volume of rare earths in these deposits?’”

How Did the Elements Get There?

The study did not identify the geological process that enriched the coal-adjacent formations, but Birgenheier has a few theories. Many of the Utah coal-bearing formations were deposited during the Cretaceous period that ended 66 million years ago, a time when the western U.S. was volcanically active.

“There are two models. One is maybe volcanic ash brought rare earths into ancient peat bogs,” she said. “The other is there’s evidence that terrestrial organic material in the peat bog actually takes in heavy rare earths.”

Then, through time, heat and burial, the peat bogs enriched in rare earths became Utah and Colorado coal deposits.

“We think rare earths were in the coals and have migrated into the adjacent mudstones or siltstones above and below the coals,” Birgenheier explained, “probably through a process called diagenesis, basically any fluid movement that happens in the rock after it was deposited.”

Reference: “Rare earth element enrichment in coal and coal-adjacent strata of the Uinta Region, Utah and Colorado” by Haley H. Coe, Lauren P. Birgenheier, Diego P. Fernandez, Ryan D. Gall, Michael D. Vanden Berg and Andrew Giebel, 10 April 2024, Frontiers in Earth Science . DOI: 10.3389/feart.2024.1381152

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