The mining industry’s social and economic importance in Africa cannot be understated. In South Africa, mining contributes approximately 8% of GDP and provides direct employment to roughly half a million people. Mining accounts for more than 90% of export earnings for Algeria, Equatorial Guinea, Libya, and Nigeria, and 80% for Botswana, Congo, Gabon, Guinea, Sierra Leone and Sudan. Given this dependence, the mining industry’s impact on climate change – and potential for contributing to climate change resilience – must be harnessed if climate adaptation in Africa is to succeed.
Climate change is not an environmental issue but rather a global economic risk, and Africa is already heavily affected. Africa is one of the lowest contributors to greenhouse gas emissions that cause climate change, yet key development sectors are already experiencing widespread losses and damages attributable to human-induced climate change. Biodiversity loss, water shortages, reduced food production, loss of lives and reduced economic growth (high confidence IPCC AR6) are all clearly evident across the continent. Climate change has reduced economic growth across Africa, increasing income inequality between African countries and those in temperate northern hemisphere climates.
The impacts can be seen across sectors. Africa’s agricultural productivity growth has been reduced by 34% since 1961 due to climate change - more than any other region. Future warming will negatively affect food systems in Africa by shortening growing seasons and increasing water stress. Exposure of people, assets and infrastructure to climate hazards is also increasing, compounded by rapid urbanisation, the infrastructure deficit, and a growing population in informal settlements. But the continent is facing major technological, institutional and financial barriers to climate adaptation, and climate-related research in Africa faces severe data constraints, as well as inequities in funding and research leadership that reduces adaptive capacity.
The mining industry faces significant impacts, too. In context, a target global temperature increase of 1.5°C translates to 3°C in Southern Africa, which results in exacerbated socioeconomic impacts including implications for mine site water balances, mining infrastructure and surrounding communities. The direct impact of climate change in mining cannot be ignored. For instance, extreme precipitation resulting in flood damage to infrastructure - including mine waste residues - can have significant consequences and must be accounted for in mine planning and ongoing operations. But more than that, indirect impacts such as the health and safety of personnel onsite or of people in the surrounding communities, legal liability, and reputational consequences, also contribute to the pressurised environment mining houses find themselves facing.
Climate information services that are demand driven and context specific, combined with climate change literacy, can be the difference between coping and informed adaptation responses. The mining industry can lead the way – and many instances already is. To respond to these challenges and build resilience to climate change into mining operations, undertaking a climate risk assessment is critical. Generally, these assessments rely on global climate models (GCMs) which simulate the earth’s climate to capture continental scale climatological patterns. The limitations of using this data in raw form are that the resolution is coarse in spatial scale (approximately 100kms) and contains persistent biases. To overcome these limitations, we undergo a process of statistical downscaling in which datasets are spatially and temporally tuned for site specific climate projections.
Statistical downscaling involves modelling the statistical relationship between a GCM and an observational dataset over a historical period, and then applying that model to generate future predictions. Firstly, a climate baseline is developed from available climate station data and reanalysis data is used to infill the series. We used reanalysis data from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA5). A complete time series data set of chosen climate variables is then prepared that will show the correlation between the data sources and is representative of the site conditions.
Next, climate projections provided by NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP), is used to characterise potential future conditions in line with the IPCC scenarios from their sixth assessment report. The data is comprised of GCM outputs, which are statistically downscaled using the Bias-Correction Spatial Disaggregation Method.
Inherent uncertainties exist in projecting future climate conditions, which is why we apply an ensemble approach to help quantify the uncertainties using a percentiles approach. This helps in decision-making processes as it allows multiple scenarios to be considered from within the range of available projections.
Downscaled climate modelling is crucial for mines because it provides site-specific and localised information about future climate conditions. The granularity of the results is useful for mine sites to develop effective response strategies, from engineered solutions and future-informed design decisions to water balance scenario analysis and bespoke site closure plans.
Traditional GCMs offer valuable insights into large-scale climate patterns but lack the resolution required to capture the unique characteristics of a specific mining site. Downscaled climate modelling has the potential to build an uncertainty advantage around climate change risk for mining companies. Developing climate-conscious, scenario-based business strategies and climate-proofing operations with engineering solutions is an important way to future-proof mining operations.
