Minimization of CO2 Emissions in Openpit Mines by Using Stochastic Simulations
摘要
Modifications in European environmental legislation requiring the minimization of the environmental footprint of mining operations have resulted in increased environmental costs and fewer investments in new surface mines. Due to the significant dependence of the global economy on mining, which provides raw materials and energy for most industries, it is essential to develop the necessary technologies for reducing pollutant emissions and exploitation costs. In open pit or underground mining operations, the highest cost comes from loading and hauling the extracted ore. Hence, the optimal combination of loading and hauling equipment has a significant impact on the production rate of the mine/quarry. The primary aim of this research is to improve the production of a surface mining operation by modifying the operational parameters (different dumping positions of materials) of the loading-hauling equipment in such a manner as to reduce fuel consumption and emitted pollutants. This aim is achieved by optimizing the hauling cycle by examining different scenarios utilizing stochastic simulation based on queue theory. The queue theory is a stochastic method commonly used to simulate the shovel-truck haulage system of a mine operation. This method has been implicated to estimate pollutants emitted in the atmosphere and propose alternative scenarios for reducing emissions normalized with the hauled material. The method is validated against actual data from a large open pit. The implementation of queue theory and estimating fuel consumption and greenhouse gas (GHG) emissions are derived from the