Environmental Modeling & Assessment

, Volume 24, Issue 5, pp 517–531 | Cite as

An Integrated Multicriteria Decision Analysis System for Reducing Air Emissions from Mining Process

  • Zunaira Asif
  • Zhi ChenEmail author


The selection of a best alternative method to minimize air pollution and energy consumption for mine sites is a critical task because it encompasses evaluation of different techniques. The aim of this paper is to select most suitable technology for mining system which helps in reducing air pollution and carbon footprints by implementing the multicriteria decision analysis (MCDA) method. The existing methods or frameworks in the mining sector, which have been used in the past to select the sustainable solution, are lacking aid of MCDA, and there is a need to contribute more in this field with a promising decision system. The MCDA method is applied as a probabilistic integrated approach for a mine site in Canada. The analysis involves processing inputs to the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) method which assists in identifying the alternatives, defining the criteria, and thus outranking of the final choice. Moreover, criteria weighting has been determined using analytical hierarchical process (AHP) method. Three categories: reduction of dust/fugitive emission control strategies, reduction in fuel consumption to minimize carbon footprint, and cyanide destruction methods are selected. The probability distributions of criteria weights and output flows are defined by performing uncertainty analysis using the Monte Carlo simulation (MCS). The sensitivity analysis is conducted using Spearman’s rank correlation method and walking criteria weights. The results indicate that the integrated framework provides a reliable way of selecting air pollution control solutions and help in quantifying the impact of different criteria for the selected alternatives.


Multicriteria decision analysis PROMETHEE AHP Air pollution Carbon footprints Mining 


Supplementary material

10666_2018_9647_MOESM1_ESM.docx (104 kb)
ESM 1 (DOCX 104 kb)


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Building, Civil and Environmental Engineering (BCEE), Faculty of Engineering and Computer SciencesConcordia UniversityMontrealCanada
  2. 2.Institute of Environmental Engineering and ResearchUniversity of Engineering and TechnologyLahorePakistan

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