The growing demand for increased production has resulted in the need to develop deeper underground mines to extract more resources. However, the mining process becomes less economically attractive as the ventilation and ore transportation costs drastically increase when operating at large depths. This has led to the industry investigating automated battery-electric and biodiesel fueled machinery instead of diesel machines to reduce emissions, and hence ventilation costs, as well improve productivity and thereby, the economic viability of deep mine projects.

A life cycle assessment (LCA) approach has been developed to evaluate the environmental impact from introducing automated equipment in underground copper mines. This is a novel application for an LCA, and as a gauge of model accuracy, it was found that calculated greenhouse gas (GHG) emissions for an underground mine site in Canada were within 5.6% of their reported emissions. The model was then expanded using data collected from automation trials at a Canadian mine to predict changes due to the introduction of various levels of automation with regards to the impact potentials of global warming, acidification, eutrophication and human toxicity. All impact levels were quantified and found to decrease due to automation. Data from this site study was then used to further develop the LCA model to predict changes in environmental impacts for underground copper mine sites in Australia, Canada, Poland, USA and Zambia. Site specific parameters and processes that contribute to their overall environmental impacts were identified, and the calculated CO2 emissions were within 4.2-5.6% of the reported values.

The mining industry is moving toward introducing significantly more technology to enhance both productivity and safety. This thesis investigates using an LCA approach to add a third dimension;​ improved environmental impacts that contribute to more sustainable mining