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Comprehensive evaluation of green mine construction level considering fuzzy factors using intuitionistic fuzzy TOPSIS with kernel distance.

Authors :
Luo, Dejiang
Huang, Jie
Liang, Yuan
Cheng, Long
Source :
Environmental Science & Pollution Research; Mar2024, Vol. 31 Issue 11, p16884-16898, 15p
Publication Year :
2024

Abstract

With increasing concerns about climate change and resource-environmental limitations, the green development of the mining industry has become mainstream and gained much support. Driven by the concept of sustainable and green development, China has made the advancement of green mine construction a crucial part of establishing an eco-society and has put forward the overall goal of green mines. An important future strategy is to evaluate a large number of mines. However, developing scientific, reliable, and comprehensive index systems and evaluation methods is extremely difficult because of the objective complexity of green mine evaluation and the fuzziness of some indicators. The kernel method and intuitionistic fuzzy set can effectively handle these problems. This study proposed a comprehensive evaluation index system and a hybrid evaluation method based on the kernel distance measure and intuitionistic fuzzy TOPSIS method. The index system contains 22 indicators considering six aspects: mining area environment, resource development mode, comprehensive utilization of resources, energy saving and emission reduction, technical innovation, and corporation management. The hybrid evaluation method was applied to the practical assessment of ten green mines in Panxi, China. Comparative analyses were carried out to demonstrate its applicability and sensitivity. The results verify that the hybrid method can fully depict the construction achievements of green mines in all aspects with strong reliability and stability. This approach is a valuable reference for evaluators and decision-makers in government departments. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09441344
Volume :
31
Issue :
11
Database :
Complementary Index
Journal :
Environmental Science & Pollution Research
Publication Type :
Academic Journal
Accession number :
175633683
Full Text :
https://doi.org/10.1007/s11356-023-31812-x