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The Biga Peninsula is an important region of geothermal resources, heat mining in Western Anatolia. In this study, the modelling of mineral efficiency in hot waters was made with data envelopment analysis for the first time. Gold, silver, and lithium in the geothermal hot water were defined as the outputs, whereas physical properties of the geothermal resource such as temperature, pH level, electrical conductivity, and salinity were defined as the inputs. The output-oriented Charnes, Cooper, and Rhodes data envelopment analysis model, which measures the total efficiency, and the output-oriented Banker, Charnes, and Cooper data envelopment analysis model, which measures technical efficiency, were used in the study. A total of 50 models were created –25 with the first model and 25 with the second model – to analyse 21 geothermal resources in the Biga Peninsula. As a result of the analysis of the models, nine geothermal resources were found to have a relative efficiency of 100%. The average technical efficiency score in the Banker, Charnes, and Cooper model was 70%, whereas the average total efficiency score in the Charnes, Cooper, and Rhodes model was 68.5%. It was found that data envelopment analysis can be used to model geothermal resources in mineral operations.
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Czasopismo
Rocznik
Tom
Strony
101--113
Opis fizyczny
Bibliogr. 20 poz., rys., tab., wykr.
Twórcy
autor
- University of Maine, Department of Civil and Environmental Engineering, Orono, Me, 04469, United States
- University of Agder ,Department of Mathematical Sciences, Norway
Bibliografia
- [1] R .D. Banker, A. Charnes, W.W. Cooper, Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis. Manage. Sci. 30, 1078-1092 (1984). DOI: https://doi.org/10.1287/mnsc.30.9.1078.
- [2] G . Bi, W. Song, P. Zhou, L. Liang, Does Environmental Regulation Affect Energy Efficiency in China’s Thermal Power Generation? Empirical Evidence from a Slacks-Based DEA Model. Energ. Policy. 66, 537-546 (2014).DOI: https://doi.org/10.1016/j.enpol.2013.10.056.
- [3] A. Charnes, W.W. Cooper, E. Rhodes, Measuring the Efficiency of Decision Making Units. Eur. J. Oper. Res. 2,429-444 (1978). DOI: https://doi.org/10.1016/0377-2217(78)90138-8.
- [4] D .R. Cooke, D.C. McPhail, Epithermal Au-Ag-Te mineralization, Acupan, Baguio District, Philippines: Numerical Simulations of Mineral Deposition. Econ. Geol. 96, 109-131 (2001).D OI: https://doi.org/10.2113/gsecongeo.96.1.109.
- [5] W.W. Cooper, L.M. Seiford, K. Tone, Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software, Springer (2006).
- [6] X. Gao, Y. Qiao, Z. Wang, T. Li, Production Potential Assessment of Enhanced Geothermal System with Thermos-Hydraulic-Mechanical-Chemical Mechanism in Hot Dry Rock. Energ. Convers. Manage. 309, 118410 (2024).DOI: https://doi.org/10.1016/j.enconman.2024.118410.
- [7] https://goldprice.org/ (2025), accessed: 11.02.2025.
- [8] H . Kaasalainen, A. Stefánsson, The Chemistry of Trace Elements in Surface Geothermal Waters and Steam, Iceland. Chem. Geol. 330-331, 60-85 (2012). DOI: https://doi.org/10.1016/j.chemgeo.2012.08.019.
- [9] Z. Karaca, D. Sanliyuksel Yucel, M.A. Yucel, C. Kamaci, Z.E. Cetiner, R.C. Erenoglu, O. Akcay, Canakkale Province (Biga Peninsula) Geothermal Resources and Determination of their Properties, the Biga Peninsula Geothermal Information System, Canakkale, Turkey. https://www.gmka.gov.tr/dokumanlar/yayinlar/Biga-Yarimadasi-Jeotermal-Proje-Kitabi.pdf (2013), accessed: 02.01.2023.
- [10] A. Mardani, D. Streimikiene, T. Balezentis, M.Z.M. Saman, K.M. Nor, S.M. Khoshnava, Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends. Energies 11, 2002-2022 (2018). DOI: https://doi.org/10.3390/en11082002.
- [11] S. Mohebali, S. Maghsoudy, F.D. Ardejani, Application of Data Envelopment Analysis in Environmental Impact Assessment of a Coal Washing Plant: A New Sustainable Approach. Environ. Impact Asses. 83, 106389 (2020).DOI: https://doi.org/10.1016/j.eiar.2020.106389.
- [12] https://www.mta.gov.tr/v3.0/arastirmalar/jeotermal-enerji-arastirmalari (2024), accessed: 11.02.2025.
- [13] N .T. Nassar, X. Du, T.E. Graedel, Criticality of the rare earth elements. J. Ind. Ecol. 19, 1044-1054 (2015).DOI: https://doi.org/10.1111/jiec.12237.
- [14] A. Navarro, X. Font, M. Viladevall, Geochemistry and Groundwater Contamination in the La Selva Geothermal System (Girona, Northeast Spain). Geothermics 40, 275-285 (2011).DOI: https://doi.org/10.1016/j.geothermics.2011.07.005.
- [15] J. Raymond, A.E. Williams-Jones, J.R. Clark, Mineralization Associated with Scale and Altered Rock and Pipe Fragments from the Berlín Geothermal Field, El Salvador; Implications for Metal Transport in Natural Systems.J. Volcanol. Geotherm. Res. 145, 81-96 (2005). DOI: https://doi.org/10.1016/j.jvolgeores.2005.01.003.
- [16] A. Panwar, M. Olfati, M. Pant, V. Snasel, A Review on the 40 Years of Existence of Data Envelopment Analysis Models: Historic Development and Current Trends. Arch. Comput. Method. E. 29, 5397-5426 (2022).DOI: https:// doi.org/10.1007/s11831-022-09770-3.
- [17] H . Scheel, EMS: Efficiency Measurement System User’s Manual. https://www.holger-scheel.de/ems/ (2000), accessed: 11.02.2025.
- [18] https://scrreen.eu/crms-2023/ (2023), accessed: 11.02.2025.
- [19] E. Thanassoulis, M.C. Portela, R. Allen, Incorporating value judgment in DEA, in: W.W. Cooper, L.M. Seiford, J. Zhu (Eds.), Handbook on Data Envelopment Analysis, pp. 99-138. Springer, New York (2011).DOI: https://doi.org/10.1007/978-1-4419-6151-8.
- [20] C .-N. Wang, T.-L. Chao, Evaluating Taiwan’s Geothermal Sites: A Bounded Rationality Data Envelopment Analysis Approach. Mathematics 12, 2477 (2024).
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7ea10219-87b0-4cb6-b9e7-e8b9b6cf471b
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