Development of open-pit mine reclamation cost estimation models: A regression-based approach

Document Type : Original Article

Authors

1 School of Mining Engineering, Amirkabir University of Technology, Tehran, Iran

2 Department of Industrial Engineering & Management Systems, AmirKabir University of Technology, Tehran, Iran

Abstract

In the recent decade, very few studies have been done on mine reclamation cost estimation and no study has been conducted on proposing mine reclamation cost estimation models based on historical data. This study aims to develop predictor models for mine reclamation costs. To this end, after collecting the historical cost data of 41 open-pit mine reclamation projects, a comprehensive data set of 16 mine reclamation costs groups and the extent of the disturbed mined land corresponding to each group was prepared. Given the advantage of the regression method in developing a reliable predictor model with few data, the proposed cost models are developed based on the regression analysis technique. The R square for all and more than 87% of the developed models was more significant than 85% and 90%, respectively, indicating the proper fits on the data sets. Also, the root mean square error ratio to the standard deviation of observed cost data (RSR) was lower than 0.7 for all developed models, indicating the predictor models' good performance on reliably estimating mine reclamation costs. These efficient and simple general models can help make the right decisions by mine reclamation planners and pave the way to achieve sustainable mining by considering mine reclamation cost in the mine planning and design process.

Keywords

References

  1. Amirshenava, S., and Osanloo, M., “Mine closure risk management: An integration of 3D risk model and MCDM techniques”, Journal of Cleaner Production, Vol. 184, (2018), 389-401, DOI: 1016/j.jclepro.2018.01.186.
  2. Amirshenava, S., and Osanloo, M., “Mined Land Suitability Assessment: A Semi-Quantitative Approach based on a New Classification of Post-Mining Land Uses”, International Journal of Mining, Reclamation and Environment, Published online, (2021), DOI: 10.1080/17480930.2021.1949864.
  3. “US Environmental Protection Agency | US EPA.” https://www.epa.gov/ (accessed Sep. 03, 2021).
  4. Sassoon, M., “Financial Surtey: Guidelines for the Implementation of Financial Surety for Mine Closure,” Extractive Industries for Development Series #7, The World Bank, (2009), Accessed online: https://openknowledge.worldbank.org/handle/10986/18386.
  5. Burgher, K. E., and Erickson, E., “The optimization of coal mine production schedules using linear programming: an example that determines the effects of reclamation costs and interest rates”, Mining Science and Technology, Vol. 2, (1984), 69-78, DOI: 10.1016/S0167-9031(84)90223-8.
  6. Jafarpour, A., and Khatami, S., “Analysis of Environmental Costs’ Effect in Green Mining Strategy Using a System Dynamics Approach: A Case Study”, Mathematical Problems in Engineering, Published online, (2021), DOI: 10.1155/2021/4893776.
  7. Baidowi, N., Rosyidi, C.N., and Aisyati, A, “A Cut-Off Grade Optimization Model in Open Pit Mining Considering Reclamation Cost and Revenue”, IOP Conference Series: Materials Science and Engineering, (2021), DOI: 10.1088/1757-899x/1096/1/012021.
  8. Narrei, N., and Osanloo, M., “Optimum cut-off grade’s calculation in open pit mines with regard to reducing the undesirable environmental impacts”, International Journal of Mining, Reclamation and Environment, Vol. 29, No. 3, 2015, 226-242, DOI: 10.1080/17480930.2014.994734.
  9. Muttaqin, B. I. A., Rosyidi, C. N., and Pujiyanto, E., “A cut-off grade optimization model in the open pit mining considering reclamation and valuable waste materials”, In Proceedings of the IEEE International Conference on Industrial Engineering and Engineering Management, (2018), 45-49, DOI: 10.1109/IEEM.2017.8289848.
  10. Amirshenava, S., and Osanloo, M., “A hybrid semi-quantitative approach for impact assessment of mining activities on sustainable development indexes”, Journal of Cleaner Production, Vol. 218, (2019), 823-834, DOI: 10.1016/j.jclepro.2019.02.026.
  11. Kaźmierczak, U., Malewski, J., and Strzałkowski, P., “The concept of forecasting the reclamation cost in rock mining”, Gospodarka Surowcami Mineralnymi/ Mineral Resources Management, Vol. 35, No. 4, (2019), 163-176, DOI: 10.24425/gsm.2019.128537.
  12. OSMRE (Office of Surface Mining Reclamation and Enforcment), “Handbook for calculation of reclamation bond amounts”, (2000), Accessed online: https://www.osmre.gov/LRG/docs/directive882.pdf.
  13. Sweigard, R.J., and Ramani, R.V., “Economic Aspects of Postmining Land Use Planning”, In Proceedings of the Society of Mining Engineers Fall Meeting Conference, Albuquerque, NM, USA, (1985), 1801-1808.
  14. Nourali, H., and Osanloo, M., “Mining capital cost estimation using Support Vector Regression (SVR)”, Resources Policy, Vol. 62, (2019), 527-540, 10.1016/J.RESOURPOL.2018.10.008.
  15. Gentry, D.W., O’Neil, T.J., “Mine Investment Analysis”, Book (SME), New York, (1984). ISBN: 978-0895204295.
  16. Gilson, N.K., and Vanreyk, A.J., “Review of Cost Estimation Models”, International Journal of Scientific Engineering and Research, Vol. 4, (2014), 42-44, Accessed online: https://www.ijser.in/archives/v4i3/IJSER15714.pdf.
  17. Nourali, H., and Osanloo, M., “A regression-tree-based model for mining capital cost estimation,” International Journal of Mining, Reclamation and Environment, Vol. 34, No. 2, (2020), 88-100, DOI: 10.1080/17480930.2018.1510300.
  18. Nourali, H., and Osanloo, M., “A new cost model for estimation of open pit copper mine capital expenditure,” International Journal of Engineering, Transactions B: Applications, Vol. 32, No. 2, (2019), 184-191, DOI: 10.5829/ije.2019.32.02b.21.
  19. Xu, X.C, Gu, X.W., Wang, Q., Gao, X.W., Liu, G.P., Wang, Z.K., and Wang, X.H., “Production scheduling optimization considering ecological costs for open pit metal mines,” Journal of Cleaner Production, Vol. 180, (2018), 210-221, DOI: 10.1016/j.jclepro.2018.01.135.
  20. Lin, W., Spore, R.L., and Nephew, E.A., “Land Reclamation and Strip-mined Coal Production in Appalachian”, Journal of Environmental Economics and Management, Vol. 3, (1976), 236-252, DOI: 10.1016/0095-0696(76)90023-1.
  21. Gronhovd, D. E., and Scott, D. F., “Reclamation Costs of strip-mined land in Western North Dakota”, Farm Research, Vol. 37, No. 1, (1979), 7-11.
  22. L. Leathers, “Costs of Strip Mine Reclamation in the West,” Technical Report: United States Department of Agriculture, Report No. 19, (1980), Accessed online: https://naldc.nal.usda.gov/download/AGE81916922/PDF.
  23. Misiolek, W. S., and Noser, T. C., “Coal Surface Mine Land Reclamation Costs”, Land Economics, Vol. 58, No. 1, (1982), 67-85, DOI: 2307/3146077.
  24. Baker, K., Sullivan, J., Burger, J. A., and Amacher, G., “Coal mine reclamation in the southern appalachains: costs of forestry versus hayland/pasture”, Journal American Society of Mining and Reclamation, Vol. 2008, No. 1, (2008), 78-96, DOI: 10.21000/JASMR08010078.
  25. Sullivan, J., and Amacher, G. S., “Private and social costs of surface mine reforestation performance criteria,” Environmental Management, Vol. 45, No. 2, (2010), 311-319, DOI: 10.1007/s00267-009-9395-4.
  26. Mishra, S. K., Hitzhusen, F. J., Sohngen, B. L., and Guldmann, J., “Costs of abandoned coal mine reclamation and associated recreation bene fi ts in Ohio,” Journal of Environmental Management, Vol. 100, (202), 52-58, DOI: 10.1016/j.jenvman.2012.01.021.
  27. Catlett L., and Boehlje, M., “Strip-Mine Reclamation Laws and Regional Cost Implications,” Journal of Agricultural and Applied Economics, Vol. 11, No. 1, (1979), 157-161, DOI: 10.1017/S0081305200014898.
  28. Du Plessis, A., and Brent, A. C., “Development of a risk-based mine closure cost calculation model”, Journal of the Southern African Institute of Mining and Metallurgy, Vol. 106, No. 6, (2006), 443-450.
  29. Hutchison, I., and Dettore, R., “Statistical and Probabilistic Closure Cost Estimating,” In Proceedings Tailings and Mine Waste, Vancouver, BC., (2011), DOI: 10.14288/1.0107717.
  30. Pavloudakis, F., Roumpos, C., and Galetakis, M., “Public acceptance of surface mining projects and the determination of the marginal environmental cost”, International Journal of Mining, Reclamation and Environment, Vol. 26, No. 4, (2012), 292-308, DOI: 10.1080/17480930.2011.613568.
  31. Paricheh, M., and Osanloo, M., “A simulation-based framework for estimating probable open-pit mine closure time and cost,” Journal of Cleaner Producti, Vol. 167, (2017), 337-345, DOI: 10.1016/j.jclepro.2017.08.202.
  32. Ignatyeva, M., Yurak, V., and Pustokhina, N., “Recultivation of post-mining disturbed land: Review of content and comparative law and feasibility study”, Resources, Vol. 9, No. 6, (2020), DOI: 10.3390/resources9060073.
  33. “Standardized Reclamation Cost Estimator (SRCE)| NDEP,” 2021. https://nvbond.org/ (accessed Sep. 03, 2021).
  34. “Estimated Rehabilitation Cost (ERC).” https://environment.des.qld.gov.au/ (accessed Sep. 03, 2021).
  35. “RECLAIM Model.” https://www.enr.gov.nt.ca/en (accessed Sep. 03, 2021).
  36. “Construction Economics.” https://www.enr.com/economics (accessed Sep. 05, 2021).
  37. Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D., and Veith, T. L., “Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations,” Transactions of the ASABE, Vol. 50, No. 3, (2007), 885-900, DOI: 10.13031/2013.23153.
International Journal of Engineering
Volume 34, Issue 11
TRANSACTIONS B: Applications
November 2021
Pages 2467-2475

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