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Title: Application of climate modelling to aid climate risk management in the mining industry
Author: Kirby, I.
ISNI:       0000 0004 7654 5699
Awarding Body: University of Exeter
Current Institution: University of Exeter
Date of Award: 2018
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Abstract:
There is now an overwhelming amount of scientific evidence that suggests that climate change is happening and the global climate system is warming up. This evidence includes observed increases in average atmospheric & oceanic temperatures, widespread melting of snow and ice, and rising sea levels. If the global climate system continues to change, as it is predicted to, there will be greater variability in temperature and precipitation in the years to come. As the atmosphere warms up, its ability to hold water increases as there is more energy and more water available in the atmosphere. As a result, we can also expect to see more extreme weather conditions such as intense storms, flooding and drought conditions. Global and regional climate models suggest increasing temperatures and changes to precipitation regimes which will inevitably alter the frequency, magnitude, and distribution of such climate related hazards. The damaging nature of these extreme events means that this should be an issue of considerable concern, particularly to mining operations which can be located within high risk areas. Whilst climate change has been a well-researched subject for many years, it is only very recently that the subject has appeared on the radar of the international mining industry and much of this has been related to the impacts of the mining industry on climate change and mitigation through emissions targets and policy changes. Climate Change has already started to cause implications to mining operations throughout the world. Considering how important the mining industry is to economies and the modern way of life, there is a distinctive lack of research and understanding on how such changes in climate will affect mining operations and also how mining operations can evaluate the risk and implications caused by such changes. This study has used available Global Circulation Models (GCM's) and Regional Circulation Models (RCM's) to develop climate simulations in order to identify current and future impacts on mines from climate change. Standard risk assessment techniques, commonly used at mines, were utilised in order to demonstrate how iii mining operations could adopt such a methodology within their existing safety, health & environmental management systems. In order to get a general idea which geographical regions may be most at risk from climate change, initial modelling was carried out using GCM's to produce two global projection maps of temperature and precipitation. These used the climate emissions scenario A1B, which assumes that emissions will continue to rise, but some action will be taken to reduce emissions in the future. This analysis allowed the identification of the main mining regions that were at most risk based on pronounced changes in temperature and precipitation. From this analysis, three regions (Canada, Brazil and South Africa) were identified from which to produce more in-depth case studies, and specific operating mines were identified within each region. For each of these regions, downscaled Regional Climate Models were developed to show projected changes in climate compared to an historical baseline. These projections were then used to identify the impacts at mine level. Whilst the overall methodology within these three studies was similar, the specifics of each methodology improved throughout, based on the findings of the previous one. The first study was on a diamond mine in the Northwest Territories in Canada. One GCM was used for modelling purposes and the main climate issue identified for the region was the projected rise of temperature. Increasing temperatures will lead to degrading of the permafrost and ice roads melting, this could cause significant problems to get supplies to the mine, as well as serious geotechnical issues. The second study looked at mines in Southern Brazil. Here four GCM's were used in order to improve the quality of the models produced. Climate projections for Brazil were highly variable but showed that rainfall is projected to decrease slightly. As mining operations are heavily dependent on hydropower for energy supplies, less rainfall and longer periods of drought could cause energy shortages in the future. The final case study is that of a mine in the Limpopo Province of South Africa. The climate models that were produced for this case study showed that the operation is iv projected to observe significant increases in temperatures and less rainfall in future years, although extreme rainfall events would continue to occur every decade. The exact extent or intensity of each rainfall event is impossible to predict as the projected values were calculated over a month, but as rainfall in the region tends to be short intense events that last hours, rather than days, this presents a significant risk. From the modelling, a baseline risk assessment was undertaken to identify specific impacts associated with increasing temperatures, periods of drought and extreme precipitation. In conjunction with stakeholders at the mine, two specific impacts were prioritised and subject to a more detailed issue based risk assessment using the BowTie process. These were i) reduced water availability due to higher temperatures & lower precipitation and ii) Flooding of the open pit by an extreme rainfall event. Here, 'on the ground" based causes and consequences were identified for each, and existing adaptation & control measures were assessed for their effectiveness in reducing the associated risk. These have provided useful guidance into what climate risk the mine may face in the future. It is concluded that potential climate change impacts can be readily identified through the use of climate models, be it a high resolution analysis of a particular area, or over a larger region. Such impacts can have significant consequences for mining operations in the future and mines should incorporate such analysis within their risk management processes going forward.
Supervisor: Foster, P. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.768554  DOI: Not available
Keywords: Climate Risk Management ; Climate Modelling ; Mining Industry
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