Spatial data approaches for assessing the environmental and socioeconomic impacts of mining activities
Summary
The growing human population, economic expansion, urbanisation, and rising affluence have driven global resource consumption to unprecedented levels. Metals and minerals have experienced particularly rapid growth, and mining activities are projected to intensify due to higher demand in emerging economies, the global energy transition, and declining ore grades. While mining increasingly encroaches on vulnerable ecosystems, systematic global assessments remain scarce. Research often focuses on specific regions or materials. Moreover, metals and minerals supply chains remain opaque, hindering comprehensive analysis. Key data gaps, including the precise locations of mines and the commodities they extract, exacerbate this challenge. However, recent advances in spatial data, such as global datasets on mining areas, present new opportunities to explore the regional and global implications of mining activities.
Structured around three research articles, this dissertation examines the spatial distribution of global mining activities, their local and regional impacts, and their linkages to global consumption. The first paper investigates the global spatial distribution of metal mining projects between 2000 and 2019. Drawing on data from 2,935 mining sites and intersecting these with biodiversity, protected areas, and water stress indicators, the analysis reveals that the surge in global metal mining poses significant threats to vulnerable ecosystems. For instance, in 2019, 79% of metal ore extraction occurred in five of the six most biodiverse biomes, and mining volumes in tropical forests doubled since 2000. Notably, half of all global metal mining takes place within 20 kilometres of protected areas. These findings underscore the environmental risks of expanding mining activities, highlighting hotspots in several world regions.
The second paper centres on Brazil, examining mining's regional economic and environmental impacts, with a particular focus on GDP growth and forest loss. Using spatial econometric models and data from 5,262 municipalities, the analysis reveals that industrial mining can generate economic benefits, including spillovers to neighbouring regions, but these gains are transient and depend on global commodity prices. Meanwhile, informal mining (“garimpo”) is associated with significant deforestation. The findings challenge the assumption of a simple trade-off between economic growth and environmental conservation, revealing a nuanced and context-dependent picture.
The third paper links mining-related deforestation to global consumption patterns, focusing on the European Union (EU). Using satellite imagery and environmentally extended input-output modelling techniques, the study reveals that 12% of global mining-related deforestation is linked to EU consumption, with 89% of these impacts occurring outside the EU. The analysis identifies key industrial sectors driving these impacts, offering insights to inform initiatives such as the EU Corporate Sustainability Due Diligence Directive.
By combining spatial data, econometric analysis, and supply chain modelling, this dissertation advances understanding of mining’s environmental and socioeconomic dimensions. The findings underscore the need for a global, integrated approach, as local environmental and social impacts are directly tied to global consumption patterns and inherent inequalities. By bridging sub-national and global perspectives, this dissertation provides a roadmap for identifying priority areas for further research, promoting ecosystem conservation and pathways toward responsible resource governance.
