Statistical testing of availability for mining technological systems with air quality constraints

Abstract

We develop a mining technology statistical model showing that even environmentally sustainable mining can be still very profitable. We put constraints on mining activities for elevated levels of particulate matters (eg, PM2.5 and PM10) in the air. We show that upper quantiles (eg, 95%) of productivity slightly decrease with respect to maximal number of failures, and this high-productivity feature is robust with respect to variation of underlying statistical parameters. We illustrate the model on two currently active mining sites, the Chuquicamata copper mine in Chile and the opencast coal mine Libouš in the Czech Republic. Two generic working scenarios have been obtained. We show that, under very realistic conditions for both countries, the Czech Republic and Chilean mining companies can regulate mining activities for high thresholds of air pollutants without a substantial loss of productivity. Sensitivity analysis with respect to parameters is provided.