IMPACT OF SURFACE COST ON LIGNITE MINING PROJECT

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Michał W. DUDEK*, Leszek JURDZIAK*, Witold KAWALEC*, Zbigniew JAGODZIŃSKI Land acquisition, pit optimization, mineral assets valuation, DCF methods, lignite project IMPACT OF SURFACE COST ON LIGNITE MINING PROJECT ABSTRACT The paper deals with impact of surface cost on lignite mining project. Not only profitability is discussed but also relations between land owners and a Mine Company. Land acquisition is analyzed and statistics are presented. Surface cost as term is introduced. Investigations are conducted on real data obtained from an already closed pit. Geological data is processed and economic block model is built. Lignite quality parameters are estimated with the use of kriging. Surface cost map of deposit area is generated as average measures for purchase/sale of real estate transactions. Ultimate pits with the use of Lerchs-Grossmann algorithm are generated and results are discussed. Additional spatial relation as increase in required land area for operation due to ultimate pits cases is shown. Time factor in land buyout is discussed. Over or underestimating surface cost may have significant impact on viability of lignite mining project. 1. INTRODUCTION Mineral rights, the legal rights to exploit and enjoy the benefits of extraction of minerals located below the surface as country specific issue are subject to government control around the world. Following the Polish law, mineral rights are automatically granted to land owner if only these minerals are not listed in Polish Geology and Mining Act (since 2011) like sand and gravel deposits. Otherwise a concession must be granted. Due to the Polish Geology and Mining Act granting concession for extractive activities to proponent in case of lignite deposits does not require land ownership essential for commencement of operation. There are no straight acquisition regulations so in the event of any legal dispute between land owners and mining or energy company, parties should go to court. Surface costs, considered as costs of land acquisition and management, mine/milling site clearing, payment of ownership, taxes, costs of reclamation and giving or selling land back to previous owners or government, in developed countries became an important topic because of rising costs of land acquisition due to urban area density growth, increasing value of real properties, rising taxes and costs of fulfillment of environmental regulations. In mineral assets valuation three main approaches are used. The Market Approach, the Income Approach and the Cost Approach. Within each approach there are various methods that have evolved and that are used in different markets. In 2005 the IVSC (International Valuation Standards Council) issued Guidance Note 14, Valuation of Properties in the Extractive Industries but it was withdrawn in 2010 by the IVSB [1] (International Valuation Standard Board) but there are attempts for new regulation to be developed. Mineral assets valuations are subjected to national valuation codes such as: VALMIN Code, CIMVal Code, * Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370 Wroclaw, Poland. e-mail: [michal.dudek leszek.jurdziak witold.kawalec]@pwr.wroc.pl KWB Konin Kleczew SA

SAMCODE. In 2008, POLVAL Code - the Polish Code for Mineral Assets Valuation based upon world s best practice was developed in which Fair Market Value of mineral assets is introduced. The Income Approach uses indirect measure of the market value taking into account future income that can be derived from the mineral assets over its entire economic life. Integrated General Approach for mineral assets valuation suggests application of Discounted Cash Flow analysis for projects that are expected to be economically viable. However still there is a problem regarding time factor in commencement of operation. If the project is not expected to be economically viable or time factor is included, IGA (Integrated General Approach) recommends using ROA - Real Option Analysis with e.g. an Option to Delay. Because of ability to choose proper time for commencement NPV of mining project is increased by decision elasticity bonus [2]. ROA approach will be a subject of separate studies. The aim of research presented include impact of surface costs on profitability of mining opencast lignite project treated as the investment of vertically integrated tandems of a lignite mine and a power plant. To illustrate surface costs scale it is worth to mention that Mine Company from the beginning of its operation has bought about 133 Mm 2 of lands and sold or gave back about 81 Mm 2 what gives about 52 Mm 2 in current disposition. With high fixed costs optimal surface costs management became very important issue to sustain profitability of lignite based energy projects. 2. SURFACE COST IDENTIFICATION THROUGH MINE PROJECT VALUATION Mineral asset valuation is often a team effort. This paper focuses on isolating surface cost from mining opencast lignite project and measures its impact. Checklist of required data for valuation purposes depends upon approach chosen, nevertheless in sales comparison approach this dataset may look as follows [3]: Agreement/transaction date, Buyer/acquirer s name, Effective date of appraisal, Price paid per unit, (average) product price at agreement/transaction date, Long-term product price expected at agreement date, (Long-term) product price at effective date of appraisal, Minority interest, Project development status, Deposit grade, Deposit/project size, Property control and security of tenure, Capital investment requirement, Operating cost/net operating income, Production loss/recovery/metallurgical complexity, Product quality, Product market stability, Discovery and expansion potential, Location and access, Infrastructure, Permitting issues, Reclamation, Country risk, Project risk, Taxes, royalties, levies. There are other approaches that may be used for valuation purposes but careful cash flow calculation for individual project still remains a key. For cash flow analysis following steps should be considered [4]. a) Calculation of daily production rate for ore, waste and production schedule. b) Main mine equipment selection and production rate for each type of equipment estimation. c) Supplementary equipment selection. d) Number of production and support employees required. e) Calculation of owning and operating cost for the equipment. f) Calculation of other costs g) Overall cost per tonne calculation. h) Capital cost and the ownership cost for the equipment determination. i) Other capital expenditures (mine). j) Mineral processing cost calculation. k) Expression of the mining costs l) Mine ownership costs per ton. m) Total mining cost. n) Profitability estimation.

While developing geological reserves one may give into consideration many possible opencast mining scenarios from which all have impact on the surface. The influence of lignite base price on the size of ultimate pit (lignite supply) and decrease of lignite quality (decrease of calorific value and increase of sulphur and ash content) has already been analyzed [5]. Additional analysis regarding surface cost and ultimate pit size will be conducted. Considering overlaying parcels as mineral property implicates fact that it refers to a property that contains a mineral deposit of such quantity and quality that it is profitable for extraction as highest and best land use [6]. For the cost estimation purposes in mining projects land acquisition may be significant as well. Without legal acquisition rules all transactions should be taken under free market conditions. By law, mineral deposit (like cooper, lignite and other) listed in Polish Geology and Mining Act (from 2011) are not a part of real estate in terms of ownership and should not have influence on its value, which is arguable. Land parcels that include sand and gravel mineral rights were investigated with Comparable Sales Approach use in Wroclaw County considered as local market in Poland. Estimated price per 1m 2 of those mineral rights (as possible mining land use) was compared to agricultural lands and vacant lots for residential use. In first case sand and gravel mineral property price was approx. 200% of agricultural lands price, whereas it was only 23% of vacant lots for residential use price [7]. Some mineral property valuation used in real estate appraisals in Poland reflects methodology used in mining projects [8]. With the difference that Cost Approach is not well developed in comparison to mining project valuation where Cost Approach may be applicable to Mineral Assets at prospecting stage or at scaling down and closure [9]. Surface cost is not limited only to acquisition. Additional surface cost might be mine site clearing and property taxes. Mine site clearing (clearing land from trees, plants, topsoil) and access roads costs may be expressed as a function of T p tons of ore and waste mined per day (by O`Hara & Suboleski, 1992, found in [4]). =0.0173 (1) Where: required area for the pit in acres (approx. 1ac = 4046.9m²). Total clearing cost is given by following formula: $1600 for 20% slopes with light tree growth = $300 for lat land with shrubs and no trees $2000 for 30% slopes with heavy trees (2) Additional soil and/or waste rock stripping to expose an amount of deposit to sustain four to six months deposit production, then the estimated cost of waste stripping will be Soil stripping cost =$3.20 for soil not more than 20 ft deep (3) Waste stripping cost =$340 for soil not more than 20 ft deep (4) Where: is tons of soil, is tons of waste rock.

As for Polish market, average price of soil removal with stockpiling based upon current civil engineering quotations is estimated to be approx. 7.5 PLN/m 3. With average weight density 2.65 Mg/m 3 and currency exchange 1USD = 3.08PLN soil stripping cost (with stockpiling) in Poland may be expressed simply as follows. Where: is tons of soil. =$0.92 (5) Applied to mining industry this number is only rough estimate. It does not include trees removal and other services though some general conclusions can be made. Closure and reclamation cost. It is believed that legal condition in the scope of mine closure and post-mining land reclamation are unsatisfactory [10]. Closure and reclamation fund must be created and not less than 10% of the required exploitation charge shall be allocated. Entrepreneurs in Poland are obligated to pay operating fees. Royalty rate for lignite is 1.66 PLN/Mg [11]. Average measures for purchase/sale transactions of lands and buildings in Mine Company area (Province) are expressed in following tables as two time frames 2005 and 2012 year. Tab. 1. Polish Real Estate Turnover in 2005 (Province of Mine area) [12]. Developed land (land with buildings) Of which Average Average Description price Urban area Rural area price PLN/m 2 PLN/m 2 PLN/m 2 PLN/m 2 Agricultural land Of which Urban area PLN/m 2 Rural area PLN/m 2 1 2 3 4 5 6 7 Mine area 23.70 64.10 7.90 1.20 10.90 1.00 Tab. 2. Purchase/sale transactions of properties built up with residential buildings in 2012 [13]. Specification Location Province of Mine area A number of Urban areas transactions Of which cities with County status B value, Total Rural C area, m 2 Total More than Less than areas D average price Total 200 thous. 200 thous. PLN/m 2 Inhabitants Inhabitants 1 2 3 4 5 6 7 A 3486 1600 629 467 162 1886 B 1160990 584716 342902 283837 59065 576274 C 4428415 1729701 690059 523573 166486 2698714 D 262.17 338.04 496.92 542.12 354.77 213.54 Tab. 3. Purchase/sale transactions of residential buildings in 2012 [13]. Specification Location Province of Mine area A number of Urban areas transactions Of which cities with County status B value, Total Rural C area, m 2 Total More than Less than areas D average price Total 200 thous. 200 thous. PLN/m 2 Inhabitants Inhabitants 1 2 3 4 5 6 7 A 32 22 - - - 10 B 8645 7006 - - - 1639 C 4363 3320 - - - 1043 D 1981.43 2110.24 - - - 1571.43

Tab. 4. Purchase/sale transactions of built-up agricultural land in 2012 [13]. Specification Location Province of Mine area A number of Urban areas transactions Of which cities with County status B value, Total Rural C area, m 2 Total More than Less than areas D average price Total 200 thous. 200 thous. PLN/m 2 Inhabitants Inhabitants 1 2 3 4 5 6 7 A 664 55 3 - - 589 B 224761 6933 1040 - - 217828 C 33583597 326390 37939 - - 33257207 D 6.69 21.24 27.41 - - 6.55 Tab. 5. Average measures for purchase/sale transactions of agricultural land in Province of Mine in 2012 [13]. Specification Average value of A total Average area sold in Average transaction B urban areas single transaction, m 2 single transaction in Price, PLN/m 2 C rural areas 1 2 3 4 A 17484.4 210.60 12.05 B 3960.7 165.40 41.76 C 19190.4 216.30 11.27 Real Estate Tax as surface cost is also a subject of optimization. Lignite deposit may have area of 7 630 000 m 2. Assuming Land Tax for business purposes approx. 0.79-0.85 PLN/m 2 may give annually 6.4 million PLN. Other surface cost may vary worldwide. Building and development may be treated as sunk cost. In United States special tax consideration for depletion of deposit is given [4]. While developing mineral project valuation useful cost information may be derived from many costs reference guides. For an instance acquisition as surface cost (Canadian Exploration Expense) may be fully deducted in the year incurred to the extent of income from any source for the corporation. Any balance not currently deductible may be carried forward indefinitely in a pool called the Canadian Exploration Expense (CCEE) pool. Alternatively, exploration expenses may be transferred through flow-through-shares that are a means of obtaining financing for mining exploration and development in Canada by sale of the right to claim the specific expenditures as a tax deduction. Money received from sale of flow-through-shares is considered as capital gain from half of which is taxable as income [14]. 3. OPENCAST LIGNITE MINE CASE Investigation of impact of surface cost on mining opencast lignite project was conducted on existing data collected from already closed pit. For the multi-pit Mine Company it is crucial to choose best possible scenario based upon variant analysis for cost optimization. Collected data can be divided into three parts: geology, financial information and land management. Cost structure from 17 years of operation (1995-2011) was analyzed. Several changes of lignite production unit cost, total production cost, revenue and production rate were observed.

% 200 180 160 140 120 100 80 60 40 20 0 Lignite production unit cost, PLN/Mg Revenue, thous.pln Lignite unit price, PLN/Mg Total production cost, thous.pln Production rate, Mg/year Year of production Fig. 1. Changes of: lignite production unit cost, total production cost, revenue, production rate, lignite unit price from last 17 years of operation to closure, real values. Year 1995 = 100% (due to confidential data). Block model development While building block model David (1977) claims that the size of blocks should not be less than ¼ of average drilling interval. Currently lack of computing power is hardly an issue. One may consider blocks no smaller then the selected mining unit [4]. The smaller the blocks the error may increase [15]. Based on 2558 drillholes, deposit parameters were estimated with the use of ordinary kriging (ISATIS by Geovariances) and interpolated into the structural block model (CAE Mining Studio). Investigated lignite deposit has stripping ratio 6.9. Deposit quality parameters such as ash and sulphur content and calorific value were integrated into one Quality Index that differentiates lignite quality while the base price for the standard quality lignite is set to 57.65 PLN/Mg (later 80 PLN/Mg from which previous base price 57.65 PLN/Mg is equal approx. to 70% of new base price). The block model consists of overburden and lignite blocks with the prototype block size 50x50x5 m, whereas the deposit block size was 25x25x1 m. For further processing of the quality block model NPV Scheduler software was used. Mining cost 4 PLN/m 3, discount rate 8% (without inflation) and the general slope angle 15 o as well as the surface costs map as real estate price layer were applied. Basing upon the created economic block model, four ultimate pits (phases) were generated with the use of Lerchs - Grossmann algorithm with 10% of lignite base price incremental change (70-100%). Land acquisition Land acquisitions follow established Mine Company regulations. Buyout and land price negotiation usually starts 3 years before pit advancing. Actual land use regarding agricultural activities does not necessarily follow Land and Buildings Registration. To focus on surface cost impact, area of interest was divided into three main forms of land use nearby deposit area: residential, agricultural-residential and agricultural and then price map of Mine area was estimated. Estimation was conducted with Polish Real Estate Turnover In 2012, Statistical Information and Elaborations use. It is an objective statistical data based upon Notarial Acts and includes average measures for purchase/sale transactions of lands and buildings in Mine

Company area (Province) selected for this research. This model is quite simple but misses many over estimations and subjectivity made by other researchers. Fig. 2. Map of Mine area with estimated price of land use. Estimation based upon Real Estate Turnover 2012. Land buyout. For this research 23 cases of land buyout were investigated between years 1993 2004. Each negotiation was followed by competent person (appraiser) valuation report to estimate market value and then Mine Company made an offer to land owner. % 500 400 300 200 100 0 100 Transaction price as % of estimated value from valuation report (one transaction - one bar) mean = 158% 490 306 251 257 132 134 110 100 129 100 100 122 115 135 173 190 140 107 100 100 127 114 1993 1994 1994 1994 1995 1995 1995 1995 1996 1998 1998 1998 1998 1999 2000 2000 2001 2002 2002 2004 2004 2004 2004 Year Fig. 3. Ratio (%) of transaction price to estimated value from valuation report of each property (one transaction - one bar) mean = 158%. Sometimes owners agreed to close to market value price but in few cases there were court cases and counter valuation reports. For few transactions it took longer than 3 years to accomplish. As a rule that could be seen Mine Company and owners started to negotiate from different positions and tend to meet in the middle. In many cases nearly 150% of first valuation report contract was agreed (Fig. 3).

A B C Fig. 4. Fitted variograms. (A) STR sulphur, (B) AR Ash, (C) QIR lignite calorific value. QIR, kj/kg STR, % AR, % QI, - Max 10086 1.54 12.21 1.130 Min 7533 0.49 3.81 0.813 Mean 9339 1.07 5.68 1.039 Std. Dev. 324 0.12 1.30 0.045 Variance 104682 0.01 1.70 0.002 Fig. 5. Deposit basic parameters. From top: (QIR) calorific value, (STR) sulphur, (AR) ash. ( light dark scale). Lignite price formula used in estimations is calculated as multiplication of lignite base price and the Quality Index (QI). Values of the standard coal are set usually as average values for which the parameters of power plant burners have been adjusted [16]. Price formula used by Mining Company is expressed by following equation. = Where: is base lignite price, PLN,, is calorific value of a standard, actual lignite ( =8850, kj/kg,, is ash content in standard, actual lignite ( =12, %,, is sulphur content in standard, actual lignite ( =0.6, %. (6)

Two scenarios were investigated. First case - market value estimated of surface cost map and second case - surface cost map model multiplied by 2.5 as for extreme cases. In the second case pits were not generated due to high surface cost. In the first case four ultimate pits with 10% increment of the base lignite price were generated. To meet market value based surface cost, lignite base price was set to 80 PLN/Mg although ultimate pit 1 with base price of 70% represents original lignite base price (57.65 PLN/Mg). 4. RESULTS Tab. 6. Results. % of base price Rock, thous. Mg Rock thous. Mg Lignite averaged quality, thous. Mg Lignite averaged quality, thous. Mg Revenue, Revenue Pit 1 70% 414 200 414 200 33 800 33 800 2 704 400 2 704 400 Pit 2 80% 37 000 451 200 2 600 36 400 211 100 2 915 400 Pit 3 90% 56 600 507 800 3 800 40 200 303 500 3 219 000 Pit 4 100% 30 000 537 800 1 800 42 000 141 600 3 360 600 Total 537 800 42 000 3 360 600 % of base price Mining Cost, Mining Cost Capital Costs, Capital Costs NPV, thous. PLN NPV Pit 1 70% 1 635 200 1 635 200 103 800 103 800 48 200 48 200 Pit 2 80% 145 900 1 781 100 8 700 112 500 13 900 62 000 Pit 3 90% 224 100 2 005 200 24 700 137 200 10 100 72 100 Pit 4 100% 118 700 2 123 900 15 400 152 600 1 100 73 200 Total 2 123 900 152 600 73 200 % of base price Pit Area thous. m2 Pit area, thous. m2 Land Tax, land area, acres Total Clearing Cost TCC, M PLN Total Clearing Cost, TCC, M MLN Pit 1 70% 5 800 5 800 4 930 1433 3.41 3.41 Pit 2 80% 6 300 500 425 1557 0.38 3.68 Pit 3 90% 7 100 800 680 1754 0.57 4.10 Pit 4 100% 7 500 400 340 1853 0.31 4.30 Total 7 500 6 375 120 000 100 000 80 000 60 000 40 000 20 000 103 800 48 200 5 800 8 700 6 300 62 000 7 100 7 500 24 700 72 100 15 400 73 200 8 000 6 000 4 000 2 000 thous. m2 0 0 Pit 1 70% Pit 2 80% Pit 3 90% Pit 4 100% Capital Costs NPV, Pit Area thous. m2 Fig. 6. Ultimate pits. Left axis: Capital costs (surface costs), NPV. Right axis: Pit Area.

Fig. 7. Ultimate pits, 10% cumulative lignite base price change, bottom side view (from top: ultimate pit 1 4). 5. CONCLUSIONS Assuming the 8% discount rate few conclusions can be made. Required pit area for the mining operation depending on ultimate pit case (1-4) is estimated to be approx. 5 800, 6 300, 7 100 and 7 500 thous. m 2. One may consider if it is better to purchase all mining lands at once or with pit advancing. Without any special Tax consideration it is better to proceed with progressive land buyout. Two scenarios compared indicated that buying lands at the beginning of operation may lead to extra expenditures regarding Taxes. Ratio of surface cost paid at the beginning to progressive buyout is estimated to be approx. 1.57. As expected, overestimation of surface costs (more than 2.5 times than estimated market value) did not generate ultimate pits. Surface cost may be decreased by granting shares of Mine Company to land owners in exchange for land/mineral rights (even if deposit below the surface is not a legal part of real estate owner but postponing may undermine mining project). Transaction data compared to Mine Company negotiation reports showed the advantage that land owners have over the Mine Company. Without any clear buyout regulation such situation will not change. The average free market transaction price was nearly 150% of first valuation report. It is important to notice that only 23 transaction data from 1993-2004 were analyzed. It can be observed (fig. 3.) that distribution in time is quite even and may suggest that progressive buyout did not generate progressive land prices (though 150% is high ratio itself), however more research will be conducted to support or discard this statement. Granting lands to Mine Company (then government owned) at low price from Country Agricultural Office as not market transactions were not taken into account. As shown in fig. 6. Achieving one million NPV increase in pit 4 compared to pit 3 will require investment of 15 million PLN in land and also 400 000 m 2 to proceed with operation. Such low NPV should raise the question whether the lignite project is economically viable, not to mention unexpected stops that generates additional costs. Despite of the economic issue this example shows that careful surface cost analysis regarding land may lead to social, environmental protection and sustainable land development consideration. Implementation of the Lerch-Grossmann pit optimization algorithm for the surface mining projects allows to evaluate optional scenarios of the pit size with regard to both mining and surface costs.

ACKNOWLEDGMENT This work has been financed from the subsidy B40112 for scientific research contributed to the development of young researchers and PhD students by Polish Ministry of Science and Higher Education executed at the Faculty of Mining, Geoengineering and Geology of the Wroclaw University of Technology. REFERENCES [1] Ellis, T. R., A Review of the Many Cost Approach Methods for Minerals Valuation, presented at SME/CMA/AIMA 2011 Annual Meeting, Denver, CO, 28.02 02.03 2011, SME Paper 151 156 [2] Saługa P, Elastyczność decyzyjna w procesach wyceny projektów geologicznogórniczych, IGSMiE PAN Kraków, 2011 [3] Ellis T. R., Sales Comparison Valuation of Development and Operating Stage Mineral Properties, Mining Engineering, Vol. 63, No. 4, 2011, 89 104. [4] Hustrulid W., Kuchta M., Open pit mine planning & design. Vol. 1, Fundamentals, 2006 [5] Jurdziak L., Kawalec W., Sensitivity analysis of lignite ultimate pit size and its parameters on change of lignite base price (in Polish,) Prace Naukowe Instytutu Górnictwa Politechniki Wrocławskiej. Górnictwo i Geologia vol. VII, ISSN 0370-0798, 2004 (now Mining Science ISSN 2300-9586) [6] Cartwright M., An Overview of Mineral Property Appraising, 1994, 1 16 [7] Dudek M., Attempt to estimate the value of sand and gravel mineral rights using the transaction prices analysis of mineral properties in Wroclaw County, 10th Students' Science Conference, Wałbrzych, 12-15 July 2012. Oficyna Wydawnicza Politechniki Wrocławskiej, 2012, 413-418 [8] Jasiński J., Specyfika i metodologia wyceny nieruchomości gruntowych położonych na złożach kopalin. Część II. Biuletyn Stowarzyszenia Rzeczoznawców Majątkowych Województwa Wielkopolskiego, ISSN 1731-1829, 2013 [9] Polish Code for the Valuation of Mineral Assets (The POLVAL Code), Cracow, 2008 [10] Uberman R., Analysis and assessment of amendments of the provisions concerning mine closure and post-mining areas reclamation in the draft Geological and Mining Law, Prace Naukowe Instytutu Górnictwa Politechniki Wrocławskiej. Górnictwo i Geologia vol. XV, ISSN 0370-0798, 2011 (now Mining Science ISSN 2300-9586) [11] Polish ACT of 9 June 2011, Geological and Mining Law [12] Real Estate Turnover In 2005, Statistical Information and Elaborations, Warsaw, 2006 [13] Real Estate Turnover In 2012, Statistical Information and Elaborations, Warsaw, 2013 [14] CostMine, 2009. Coal cost guide: A subscription cost data service, Spokane Valley, WA, InfoMine USA Inc. [15] Rudenno V., The Mining Valuation Handbook: Mining and Energy Valuation for Investors and Management, 3th Edition, ISBN: 9780731409839, 2009 [16] Jurdziak L., Kawalec W., Influence of power station efficiency and carbon costs on lignite resources and energy consumption in Poland. proceedings of the 11th International Symposium of Continuous Surface Mining, 25-27th June, 2012, 125-135.