Global Scan of Disruptions to the Mine Life Cycle: Price, Ownership, and Local Impact.

Criticality and supply risk models seek to address concerns of potential disruption to global metal supply. These models need to incorporate disruption events that arise from within the mining industry's market structure. In this paper, we review what we refer to as events of "mine life cycle disruption". These include project abandonments, premature closures, care and maintenance, and ownership changes. Life cycle disruptions not only cause production disruptions but also embed social and environmental risks in global metal markets. They arise from the highly variable business environment in which the resources sector operates. Changing commodity prices directly influence mining revenues and drive decisions on whether to halt or push forward a project. While some disruptions are involuntary and induced by external economic conditions, others are purposefully triggered by certain mining companies that use them to their advantage. We examine the frequency of these disruptions based on a contemporary global inventory of 35,000 mining projects and present the findings against recent developments in the research literature. We conclude that life cycle disruption events are an important consideration in balancing the demand for metals and the social and environmental impacts of mining and propose pathways for managing these events and their effects.

Tailings facility disclosures reveal stability risks.

Tailings facility failures represent a significant risk to the environment and communities globally, but until now little data was available on the global distribution of risks and characteristics of facilities to ensure proper governance. We conducted a survey and compiled a database with information on tailings facilities disclosed by extractive companies at the request of institutional investors. Despite limitations in the data, this information disclosure request represents the most comprehensive survey of tailings facilities ever undertaken. The compiled dataset includes 1743 tailings facilities and provides insights into a range of topics including construction method, stability, consequence of failure, stored volume, and the rate of uptake of alternative technologies to dewater tailings and reduce geotechnical risk. Our analysis reveals that 10 per cent of tailings facilities reported notable stability concerns or failure to be confirmed or certified as stable at some point in their history, with distinct trends according to construction method, governance, age, height, volume and seismic hazard. Controversy has surrounded the safety of tailings facilities, most notably upstream facilities, for many years but in the absence of definitive empirical data differentiating the risks of different facility types, upstream facilities have continued to be used widely by the industry and a consensus has emerged that upstream facilities can theoretically be built safely under the right circumstances. Our findings reveal that in practice active upstream facilities report a higher incidence of stability issues (18.3%) than other facility types, and that this elevated risk persists even when these facilities are built in high governance settings. In-pit/natural landform and dry-stack facilities report lower incidence of stability issues, though the rate of stability issues is significant by engineering standards (> 2 per cent) across all construction methods, highlighting the universal importance of careful facility management and governance. The insights reported here can assist the global governance of tailings facility stability risks.

Governing deep sea mining in the face of uncertainty.

Progress towards deep sea mining (DSM) is driven by projected demands for metals and the desire for economic development. DSM remains controversial, with some political leaders calling for a moratorium on DSM pending further research into its impacts. This paper highlights the need for governance architectures that are tailored to DSM. We conceptualise DSM as a type of complex orebody, which encompasses the breadth of environmental, social and governance (ESG) risks that make a mineral source complex. Applying a spatial overlay approach, we show that there are significant data gaps in understanding the ESG risks of DSM. Such uncertainties are compounded by fact that there are no extant commercial DSM projects to function as a precedent - either in terms of project design, or the impacts of design on environment and people. Examining the legislation of the Cook Islands and International Seabed Authority, we demonstrate how regulators are defaulting to terrestrial mining governance architectures, which cannot be meaningfully implemented until a fuller understanding of the ESG risk landscape is developed. We argue that DSM be approached as a distinct extractive industry type, and governed with its unique features in frame.

Renewable energy production will exacerbate mining threats to biodiversity.

Renewable energy production is necessary to halt climate change and reverse associated biodiversity losses. However, generating the required technologies and infrastructure will drive an increase in the production of many metals, creating new mining threats for biodiversity. Here, we map mining areas and assess their spatial coincidence with biodiversity conservation sites and priorities. Mining potentially influences 50 million km2 of Earth's land surface, with 8% coinciding with Protected Areas, 7% with Key Biodiversity Areas, and 16% with Remaining Wilderness. Most mining areas (82%) target materials needed for renewable energy production, and areas that overlap with Protected Areas and Remaining Wilderness contain a greater density of mines (our indicator of threat severity) compared to the overlapping mining areas that target other materials. Mining threats to biodiversity will increase as more mines target materials for renewable energy production and, without strategic planning, these new threats to biodiversity may surpass those averted by climate change mitigation.

The social and environmental complexities of extracting energy transition metals.

Environmental, social and governance pressures should feature in future scenario planning about the transition to a low carbon future. As low-carbon energy technologies advance, markets are driving demand for energy transition metals. Increased extraction rates will augment the stress placed on people and the environment in extractive locations. To quantify this stress, we develop a set of global composite environmental, social and governance indicators, and examine mining projects across 20 metal commodities to identify the co-occurrence of environmental, social and governance risk factors. Our findings show that 84% of platinum resources and 70% of cobalt resources are located in high-risk contexts. Reflecting heightened demand, major metals like iron and copper are set to disturb more land. Jurisdictions extracting energy transition metals in low-risk contexts are positioned to develop and maintain safeguards against mining-related social and environmental risk factors.

Source Risks As Constraints to Future Metal Supply.

Rising consumer demand is driving concerns around the "availability" and "criticality" of metals. Methodologies have emerged to assess the risks related to global metal supply. None have specifically examined the initial supply source: the mine site where primary ore is extracted. Environmental, social, and governance ("ESG") risks are critical to the development of new mining projects and the conversion of resources to mine production. In this paper, we offer a methodology that assesses the inherent complexities surrounding extractives projects. It includes eight ESG risk categories that overlay the locations of undeveloped iron, copper, and aluminum orebodies that will be critical to future supply. The percentage of global reserves and resources that are located in complex ESG contexts (i.e., with four or more concurrent medium-to-high risks) is 47% for iron, 63% for copper, and 88% for aluminum. This work contributes to research by providing a more complete understanding of source level constraints and risks to supply.