Determining the Method of Reclamation of Surface Mines Based on Renewable Energies Using A New Hybrid Approach

Document Type : Research - Paper

Authors

1 M.Sc Student, Dept. of Mining Engineering, Tarbiat Modares University, Tehran, Iran

2 Assistant Professor, Dept. of Mining Engineering, Urmia University of Technology, Urmia, Iran

Abstract

Mines as non-renewable resources have a significant role in the economic and social development of countries. However, at the end of the mine's life, to achieve sustainable development, the mine's pits reclamation is vital. Due to the situation of most mines that are located in remote areas, mine's reclamation based on renewable energies can be an appropriate strategy. In this study, a new hybrid method using the Fuzzy Cognitive Mapping (FCM) method, grey Complex Proportional Assessment (COPRAS-G), and Z-theory reliability is introduced for prioritization and selecting of the mine's reclamation strategies. The proposed method, for reclamation of an open-pit lead-zinc mine by considering several criteria and strategies is applied. The results of the FCM show that the average wind speed criterion has the highest weight. Also, the prioritization of the strategies showed that "closing the mine and building wind turbines" is the best strategy for reclamation of the investigated mine. Therefore, considering the windy situations in the study area, building a wind farm to supply electricity is a suitable strategy to achieve sustainable development in the region.

Keywords

Main Subjects

References

  1. پورمیرزائی، ر.؛ 1396؛ "بررسی نقش صنعت معدنکاری و منابع معدنی در توسعه پایدار کشور". مهندسی منابع معدنی، دوره دوم، شماره 3، ص 81-92.
  2. Amirshenava, S., and Osanloo, M. (2018). “Mine closure risk management: an integration of 3D risk model and MCDM techniques”. Journal of Cleaner Production, 184: 389-401.
  3. Mborah, C., Bansah, K. J., and Boateng, M. K. (2016). “Evaluating alternate post-mining land-uses: A review”. Environment and Pollution, 5(1): 14-22.
  4. Bakhtavar, E., Aghayarloo, R., Yousefi, S., Hewage, K., and Sadiq, R. (2019). “Renewable energy based mine reclamation strategy: a hybrid fuzzy-based network analysis”. Journal of Cleaner Production, 230: 253-263.
  5. Heikkinen, P., Noras, P., Salminen, R., Mroueh, U-M., Vahanne, P., Wahlström, M., Kaartinen, T., Juvankoski, M., Vestola, E., Mäkelä, E., Leino, T., Kosonen, M., Hatakka, T., Jarva, J., Kauppila, T., Leveinen, J., Lintinen, P., Suomela, P., Höyry, H., … and Tolla, P. (2008). “Mine Closure Handbook: Environmental Techniques for the Extractive Industry”. Geological Survey of Finland.
  6. Laurence, D. (2011). “Establishing a sustainable mining operation: an overview”. Journal of Cleaner Production, 19(2-3): 278-284.
  7. Bascetin, A. (2007). “A decision support system using analytical hierarchy process (AHP) for the optimal environmental reclamation of an open-pit mine”. Environmental Geology, 52(4): 663-672.
  8. George-Laurentiu, M., Florentina-Cristina, M., and Andreea-Loreta, C. (2016). “The assessment of social and economic impacts associated to an abandoned mining site case study: Ciudanovita (Romania)”. Procedia Environmental Sciences, 32: 420-430.
  9. Clemente, A. S., Werner, C., Máguas, C., Cabral, M. S., Martins-Loução, M. A., and Correia, O. (2004). “Restoration of a limestone quarry: effect of soil amendments on the establishment of native Mediterranean sclerophyllous shrubs”. Restoration Ecology, 12(1): 20-28.
  10. Yavuz, M., and Altay, B. L. (2015). “Reclamation project selection using fuzzy decision-making methods”. Environmental Earth Sciences, 73(10): 6167-6179.
  11. Palogos, I., Galetakis, M., Roumpos, C., and Pavloudakis, F. (2017). “Selection of optimal land uses for the reclamation of surface mines by using evolutionary algorithms”. International Journal of Mining Science and Technology, 27(3): 491-498.
  12. Çoban, V., and Onar, S. Ç. (2017). “Modelling solar energy usage with fuzzy cognitive maps”. Intelligence Systems in Environmental Management: Theory and Applications, 159-187.
  13. حسینی، ش.، پورمیرزائی، ر.؛ 1396؛ "استفاده از انرژی خورشیدی در معادن، بعنوان رویکردی مناسب جهت بازسازی معادن". ششمین کنفرانس انرژی های تجدید پذیر و تولید پراکنده ایران، تبریز، ص 714-710.
  14. Pavloudakis, F., Galetakis, M., and Roumpos, C. (2009). “A spatial decision support system for the optimal environmental reclamation of open-pit coal mines in Greece”. International Journal of Mining, Reclamation and Environment, 23(4): 291-303.
  15. Sweigard, R. J., and Ramani, R. V. (1988). “Evaluation of postmining land use plans using fuzzy set analysis”. In Transactions of SME-AIME Annual Meeting, New Orleans, LA, 282: 1854-1859.
  16. Soltanmohammadi, H., Osanloo, M., and Aghajani Bazzazi, A. (2009). “Deriving preference order of post-mining land-uses through MLSA framework: application of an outranking technique”. Environmental Geology, 58(4): 877-888.
  17. Soltanmohammadi, H., Osanloo, M., Rezaei, B. A. H. R. A. M., and Aghajani Bazzazi, A. (2008). “Achieving to some outranking relationships between post mining land uses through mined land suitability analysis”. International Journal of Environmental Science and Technology, 5(4): 535-546.
  18. Isalou, A. A., Zamani, V., Shahmoradi, B., and Alizadeh, H. (2013). “Landfill site selection using integrated fuzzy logic and analytic network process (F-ANP)”. Environmental Earth Sciences, 68(6): 1745-1755.
  19. Masoumi, I., Naraghi, S., Rashidi-nejad, F., and Masoumi, S. (2014). “Application of fuzzy multi-attribute decision-making to select and to rank the post-mining land-use”. Environmental Earth Sciences, 72(1): 221-231.
  20. Τsolaki-Fiaka, S., Bathrellos, G. D., and Skilodimou, H. D. (2018). “Multi-criteria decision analysis for an abandoned quarry in the Evros Region (NE Greece)”. Land, 7(2): 43.
  21. Kraujalienė, L. (2019). “Comparative analysis of multicriteria decision-making methods evaluating the efficiency of technology transfer”. Business, Management and Education, 17(1): 72-93.
  22. Zadeh, L. A. (1965). “Fuzzy set theory”. Information and Control, 8(3): 338-353.
  23. Chen, S. M. (1994). “Fuzzy system reliability analysis using fuzzy number arithmetic operations”. Fuzzy Sets and Systems, 64(1): 31-38.
  24. Zadeh, L. A. (2011). “A note on Z-numbers”. Information Sciences, 181(14): 2923-2932.
  25. Song, C., Wang, J. Q., and Li, J. B. (2020). “New framework for quality function deployment using linguistic Z-numbers”. Mathematics, 8(2): 224.
  26. Abbaspour Onari, M., Yousefi, S., and Jahangoshai Rezaee, M. (2021). “Risk assessment in discrete production processes considering uncertainty and reliability: Z-number multi-stage fuzzy cognitive map with fuzzy learning algorithm”. Artificial Intelligence Review, 54(2): 1349-1383.
  27. Kang, B., Zhang, P., Gao, Z., Chhipi-Shrestha, G., Hewage, K., and Sadiq, R. (2020). “Environmental assessment under uncertainty using Dempster–Shafer theory and Z-numbers”. Journal of Ambient Intelligence and Humanized Computing, 11(5): 2041-2060.
  28. Bakhtavar, E., Hosseini, S., Hewage, K., and Sadiq, R. (2021). “Green blasting policy: simultaneous forecast of vertical and horizontal distribution of dust emissions using artificial causality-weighted neural network”. Journal of Cleaner Production, 283: 124562.
  29. Kosko, B. (1986). “Fuzzy cognitive maps”. International Journal of Man-Machine Studies, 24(1): 65-75.
  30. Jahangoshai Rezaee, M., Yousefi, S., and Hayati, J. (2018). “A decision system using fuzzy cognitive map and multi-group data envelopment analysis to estimate hospitals’ outputs level”. Neural Computing and Applications, 29(3): 761-777.
  31. Papageorgiou, K., Singh, P. K., Papageorgiou, E., Chudasama, H., Bochtis, D., and Stamoulis, G. (2019). “Fuzzy cognitive map-based sustainable socio-economic development planning for rural communities”. Sustainability, 12(1): 305.
  32. Zavadskas, E. K., and Kaklauskas, A. (1996). “Determination of an efficient contractor by using the new method of multicriteria assessment”. In International Symposium for “The Organization and Management of Construction”. Shaping Theory and Practice, Bury St. Edmunds, Suffolk, UK: St. Edmudsbury Press, 2: 94-104.
  33. Park, K. (2017). “A grey-based risk selection model using fuzzy information of a supply chain”. Multimedia Tools and Applications, 76(17): 18083-18097.
  34. Zavadskas, E. K., Kaklauskas, A., Turskis, Z., and Tamošaitiene, J. (2008). “Selection of the effective dwelling house walls by applying attributes values determined at intervals”. Journal of Civil Engineering and Management, 14(2): 85-93.
Journal of Mineral Resources Engineering
Volume 7, Issue 3 - Serial Number 25
October 2022
Pages 77-100

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History

  • Receive Date: 12 June 2021
  • Revise Date: 12 August 2021
  • Accept Date: 25 August 2021

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