CLEAN DEVELOPMENT MECHANISM PROJECT DESIGN DOCUMENT FORM (CDM-SSC-PDD) Version 03 - in effect as of: 22 December 2006 CONTENTS

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1 CLEAN DEVELOPMENT MECHANISM PROJECT DESIGN DOCUMENT FORM (CDM-SSC-PDD) Version 03 - in effect as of: 22 December 2006 CONTENTS A. General description of the small scale project activity B. Application of a baseline and monitoring methodology C. Duration of the project activity / crediting period D. Environmental impacts E. Stakeholders comments Annexes Annex 1: Contact information on participants in the proposed small scale project activity Annex 2: Information regarding public funding Annex 3: Baseline information Annex 4: Monitoring Information Annex 5: Contribution to sustainable development 1

2 Revision history of this document Version Date Description and reason of revision Number January 2003 Initial adoption 02 8 July 2005 The Board agreed to revise the CDM SSC PDD to reflect guidance and clarifications provided by the Board since version 01 of this document. As a consequence, the guidelines for completing CDM SSC PDD have been revised accordingly to version 2. The latest version can be found at < December The Board agreed to revise the CDM project design 2006 document for small-scale activities (CDM-SSC-PDD), taking into account CDM-PDD and CDM-NM. 2

3 CDM Executive Board SECTION A. General description of small-scale project activity A.1 Title of the small-scale project activity: Title of the small-scale project activity: Dom Pedrito Biomass Power Plant Riogrande do Sul, Brazil Version number of the document: 04 Date of the document: April 6 th 2007 A.2. Description of the small-scale project activity: The purpose of the CDM project activity is the establishment and operation of a 12.3 MW biomass power plant in Dom Pedrito. Electricity will be generated by means of a boiler, steam turbine and a generator set. Approximately 96,500 MWh will be generated each year, and approx. 82,200 MWh/yr will be exported to the South-Southeast-Midwest grid of Brazil. The power plant will utilize approx. 102,500 tons rice husks per year from surrounding rice mills 1 that would otherwise have been left for decay. Rice husks will be collected by trucks and would otherwise have been left to anaerobic decay on a disposal site without methane recovery. The start of operation is scheduled for March Hence, the CDM project activity contributes to the reduction of greenhouse gas (GHG) emissions in two ways: avoidance of methane emissions from biomass decay (prevention of decay through controlled burning) and generation of electricity from renewable energy sources. The project activity will contribute to the sustainable development of the host country and the region since it supports Brazil in meeting its increasing energy demand for energy due to economic growth 2 in an environmentally friendly way. It contributes to environmental, social and economic sustainability by increasing the share of renewable energies in electricity generation and consumption. This helps to reduce dependency on fossil fuels and expenditures for oil imports. At the same time, negative environmental impacts from other industrial activities, i.e. waste disposal from rice production, will be reduced. The project activity will imply social benefits, as new job opportunities will be created both with regard to the construction phase and operation of the plant. In technical terms, the project activity will lead to a transfer of modern, highly efficient power plant technology from Germany to the host country. The owner of the biomass power plant will be Dom Pedrito Bionergética S.A., a daughter of Hamburgo Energia Participacoes Ltda.. Finances will be provided by Energiegesellschaft Palmaille mbh (ENERPAL), and operation and management of the installation will be outsourced to the company Cooperative Riograndense de Electricidade Ltda., Porto Alegre (COORECE). 1 The distances between rice mills and power plant are approx 5 km each. 2 According to Brazil s Initial National Communication, the end use of electricity increased from 21.7 TWh in 1990 to TWh in 1999 and TWh in 2000 (MCT 2004, Table 1.3.2, p. 184) 3

4 A.3. Project participants: Name of Party involved (*) ((host) indicates a host Party) Brazil (host) The Netherlands Private and/or public entity(ies) project participants (*) (as applicable) Dom Pedrito Energetica S.A. Rua Santo Guerra, 84 Navegantes Porto Alegre RS; Brazil Hamburgo Energia Participacoes Ltda. Rua Santo Guerra, 84 Navegantes Porto Alegre RS; Brazil Energiegesellschaft Palmaille mbh (ENERPAL) Palmaille Hamburg, Germany Kindly indicate if the Party involved wishes to be considered as project participant (Yes/No) No No The Netherlands have ratified the Kyoto Protocol on 31/05/02 Brazil has ratified the Kyoto Protocol on 23/08/02 A.4. Technical description of the small-scale project activity: Based on negotiations with several German technology suppliers, AREVA T&D Bremen cooperating with its Brazil daughter AREVA DO BRASIL has been selected as the technology provider. An overview of the technical specifications of the biomass power plant is provided in the following. Information regarding the model/types, efficiency of boiler, generator and other equipment has been provided to the Designated Operational Entity. The plant will have a gross output of 12.3 MW e (gross), and 11.1 MW e net 3. The major components of the plant site will be A ward house A truck scale, where the trucks are weighed before and after uploading A fuel uploading station and a fuel handling system with classifiers, conveyors, etc. Silos for rice husk storage (storage capacity of 2-3 days) The boiler, including a water supply system (more detailed description below) The power house, sheltering the generator package, the LV and MV facilities, the staff facilities, the administration and control rooms. Grid connection is designed for a 13,8 kv overhead line MWe (gross) is the installed technical capacity, while 11.1 MWe (net) is the effective capacity after deducting self-consumption of the installation. 4

5 Boiler design: The fuel will be injected into the combustion chamber of the steam boiler by rotary valves. The utilization will take place on a grate-furnace facility, designed as a moving grate and equipped with a combustion control device. The combustion will be fostered through the injection of pre-heated primary air. A secondary injection in the upper part of the chamber assures an excellent burnout of the fuel. The process water will be heated to super-heated steam with a temperature of 420 C and a pressure of 43 bars by the flue gas in the steam boiler (vertical construction). Besides the boiler itself, a high efficiency heater system will be installed, comprising an: Economiser to upraise the water temperature, Air pre-heater to upraise the temperature of the primary air Super heater to dry the steam and to upraise its temperature The process control including temperature selection in the boiler system will minimize the emissions of NOx. The exhaust gas will be filtered by a multi-cyclone filter, guaranteeing emission values lower than 100 mg dust/nm³, and pumped by the mean of a fan into a 25 m stack to the atmosphere. The ash extraction will be realized under the furnace by a screw and the ashes are forwarded into an ash container. Volatiles will be filtered after exiting the boiler by the multi-cyclone and will also be collected in ash containers. Generated electricity will be exported to the grid Sistema Elétrico Interligado Nacional (SIN), which is operated by Operador Nacional do Sistema Eleétrico (ONS). The monitoring of the grid and the accounting for the electricity delivered will be done by the Agencia Nacional de Energia Elétrica (ANEEL). A power purchase agreement is currently being negotiated with Companhia Estadual de Energia Elétrica S.A. (CEEE). A.4.1. Location of the small-scale project activity: Brazil A Host Party(ies): A Riogrande do Sul Region/State/Province etc.: A City/Town/Community etc: City of Dom Pedrito, Riogrande do Sul, Brazil. A Details of physical location, including information allowing the unique identification of this small-scale project activity : The project is located in the most southern state of Brazil, Riogrande do Sul (see Figure 1), about 650 km west of Porto Alegre (see Figure 2). The coordinates are LAT: , LONG: GPS-data of the entrance of the project site: UTM ,32 E / ,0 N. 5

6 Figure 1: Map of Brazil (Source: Maps and boundary data are copyrighted by Figure 2: Map of Riogrande do Sul (Source of MAP: 6

7 The project site is located 5km outside the city centre of Dom Pedrito, a town with 35,000 people. The major part of the site is undulate and based on rocky ground. The north-eastern part of the site is more even and covered with grassland (also see Figure 3). Figure 3: Site area Dom Pedrito is connected to the national highway system through paved roads, capable for truck transports. The fuel for the biomass power plant, rice husks, will be delivered from rice husk disposal sites, fed by local and regional rice mills. A list of the contracted suppliers has been provided to the Designated Operational Entity (DOE). The average transporting distance between rice mills/disposal sites and power plant is approx of 25 km. A.4.2. Type and category(ies) and technology/measure of the small-scale project activity: The project activity consists of two components: 1. Grid connected renewable electricity generation ( Power generation, Scope 1, energy industries [renewable-, non-renewable sources], and 2. Avoidance of methane production from biomass decay through controlled combustion ( Methane emissions avoidance ; Scopes 13 & 15; waste handling and disposal) Component 1: Grid connected renewable electricity generation The project activity complies with type I, category D of the most recent version of the simplified modalities and procedures for small-scale CDM project activities, because: The activity supplies electricity from renewable biomass to a grid (which includes fossil fuel generating units), The installed capacity is 12.3 MW e and thus below the limit 15 MW e for type I projects. Component 2: Avoidance of methane production from biomass decay through controlled combustion The project activity complies with type III, category E of the most recent version of Appendix B to the simplified modalities and procedures for small-scale CDM project activities, since: 7

8 The activity avoids the production of methane from biomass or other organic matter that would have otherwise been left to decay anaerobically in a solid waste disposal site without methane recovery. Anaerobic decay is prevented through controlled combustion (in the biomass power plant). The project activity does not include the recovery or combustion of methane. Anthropogenic emissions of greenhouse gas emissions are reduced (calculations see section B of this document), and The project activity results in emission reductions of less than 60 kt CO 2 equivalent annually in any year over the crediting period. Rice husks are a waste product of rice conditioning as part of the food production process. They are rich of proteins and fat (100% biomass) and account for up to 30% of the weight of an unpolished rice grain. Rice husks have traditionally been and are currently being deposited on officially designated disposal sites. Such disposal sites have to be officially authorized and can be quite large. Figure 4 exemplarily shows a 90-ha disposal site in Rio Grande do Sul. Figure 4: Rice husk disposal site. Transfer of environmentally safe and sound technology The CDM project activity will apply modern German technology, characterized by high efficiency and little flue gases. The following design features allow reaching a high energy efficiency coefficient: Pre-heating of the primary air before injection into the burning chamber; Operation of a modern 6 stage steam turbine processing superheated steam; Operation of an economiser to upraise the water temperature; Operation of a modern condenser system at 0.08 bars negative pressure; 8

9 Super heater to dry the steam and to upraise its temperature. The secondary injection of in the upper part of the burning chamber will assure an excellent burnout of the fuel. In order to minimize emissions of local pollutants, all flue gases will be decontaminated according to the relevant Brazil emissions limits. In fact, all of the technology providers under consideration have broad experiences with the European emission standards as defined in the EU Directive 2001/80/EC - Limitation of emissions of certain pollutants into the air from large combustion plants. All exhaust gases of the biomass power plant will be post-combusted and filtered by a multi-cyclone filter. Flue gas concentrations of carbon monoxide will be minimized through the controlled combustion process, complying with the emission limits of 150 mg/nm³. An electronic control panel (EU standard) allows automatic and full control of the biomass power plant and supervises fuel input, temperature and pressure within the process, and electricity exports to the grid. A.4.3 Estimated amount of emission reductions over the chosen crediting period: The estimated amount of emission reductions over the chosen crediting period (7 years) is summarized in Table 1 below. Year Annual estimation of emission reductions in tons of CO 2 e Year 1 (2008/09) 24,852 Year 2 (2009/10) 28,556 Year 3 (2010/11) 32,151 Year 4 (2011/12) 35,640 Year 5 (2012/13) 39,025 Year 6 (2013/14) 42,310 Year 7 (2014/15) 45,498 Total estimated reductions 248,033 (tonnes of CO 2e ) Total number of crediting years 7 Annual average over the crediting period of 35,433 estimated reductions (tonnes of CO 2e ) Table 1: Estimated amount of project emissions and emissions reductions over the chosen crediting period A.4.4. Public funding of the small-scale project activity: Neither public funding nor official development assistance (ODA) are used in the project activity. No loans from international financial institutions (IFIs) are included. The financing will be realized by Dom Pedrito Bionergética S.A. with a loan from a German bank, mediated by the German technology exporter CCC Machinery GmbH, a Hermes Euler credit insurance and the sale of generated CERs to private investors. Further information is provided in the detailed finance plan, which has been provided to the DOE as a separate document for confidentiality reasons. 9

10 A.4.5. Confirmation that the small-scale project activity is not a debundled component of a large scale project activity: The project activity consists of the construction and operation of one single power plant with an installed capacity of 12.3 MW e. It is not component of another project activity with the same project participants, being registered within the previous 2 years, and whose project boundary is within 1 km of the project boundary of the proposed small scale activity at the closest point. SECTION B. Application of a baseline and monitoring methodology B.1. Title and reference of the approved baseline and monitoring methodology applied to the small-scale project activity: Component 1: Component 2: References: AMS type I, category D Grid connected renewable electricity generation AMS type III, category E Avoidance of methane production from biomass decay through controlled combustion Methodological Tool to determine methane emissions avoided from dumping waste at a solid waste disposal site (EB 26) Appendix B of the simplified modalities and procedures for small scale CDM project activities; Decision -/CMP.2: Further guidance relating to the clean development mechanism B.2 Justification of the choice of the project category: The eligibility conditions for application of the small scale baseline methodologies (Component 1: AMS I.D; and Component 2: AMS III.E) have been summarized and discussed in section A.4.2 of this document. In short, the project conforms to the above small scale conditions in the following ways: The project comprises the use of rice husks, which is a renewable biomass to be used to supply electricity to and/or displace electricity from the electricity distribution system of Rio Grande do Sul. Rio Grande do Sul and its integrated grid contain coal fired power plants. Thus the project activity replaces the use of at least one fossil fuel. The installed capacity of 12.3 MW e is below the eligibility threshold for category I.D projects. Emission reductions due to methane avoidance are clearly below the 60kt threshold of AMS III.E Hence, the project activity is eligible for application of the simplified modalities and procedures for small-scale CDM project activities, categories I.D and III.E. B.3. Description of the project boundary: Component 1: AMS I.D defines the project boundary as the physical, geographical site of the renewable generation source. Consequently, besides the physical project sites as described below ( component 2 ) all installations that provide electricity to the South-Southeast-Midwest grid are considered in the baseline scenario. 10

11 Component 2: Referring to the simplified modalities and procedures for small-scale CDM project activities (Version 10: 23 rd December 2006) the project boundary are the physical, geographical sites, Where the solid waste would have been disposed and the avoided methane emission occurs in absence of the proposed project activity, Where the treatment of biomass through controlled combustion takes place, and In the itineraries between them, where the transportation of wastes and combustion residues occurs. With regard to the planned CDM project activity, this means that the following locations and elements are in the project boundaries: The biomass power plant including its site of operation as described in section A.4.1.4, Additional transport between the existing rice husk disposal sites and the plant, Transport of ashes from the project site to their final destination (industry/cement plants), and Current disposal sites for rice husks (place where methane emissions occur in the absence of the project activity), i.e. the biomass suppliers sites. Since installations for rice production are not under control of the project participants and since their operation mode does not influence baseline emissions, they are not included in the project boundary. B.4. Description of baseline and its development: Component 1: Grid connected renewable electricity generation To estimate the baseline emissions related to grid connected renewable electricity generation, the baseline as defined under category I.D. of Appendix B is applied. The electricity grid to which electricity generated by the project activity is exported does not purely consist of diesel/oil fuelled generators. Hence, the emission coefficient (kg CO 2e /kwh) is calculated as: (i) the combined margin (CM), consisting of the combination of operating margin (OM) and build margin (BM) according to the procedures prescribed in the approved methodology ACM0002. A more detailed description of the application of the baseline methodology is provided in Annex 3 to this document. Component 2: Avoidance of methane production from biomass decay through controlled combustion According to AMS III-E, the baseline scenario is the situation where, in the absence of the project activity, biomass and other organic matter are left to decay within the project boundary and methane is emitted to the atmosphere. The baseline emissions are the amount of methane from the decay of the biomass content of the waste treated in the project activity. 11

12 To estimate the baseline emissions related to the avoidance of methane production from biomass decay through controlled combustion, the formula defined in AMS III.E. are applied on a 1:1 ratio. The Yearly Methane Generation Potential is calculated using the first order decay model based on the discrete time estimate method of the IPCC Guidelines, as described in category AMS III-G, applying the Tool to determine methane emissions avoided from dumping waste at a solid waste disposal site (TME). The average temperature in Dom Pedrito is 17.8ºC and the yearly rainfall is 1710 mm, thus characterizing the area as a sub-temperate wet climate (average of ; data obtained from Brazil Ministry for Agriculture in February 2007). As rice husk have a similar composition as straw, they are classified as wood, wood waste and straw for the purpose to apply the TME (parameters Kj and DOCj). Assumptions of the baseline methodology in the context of the project Parameter Data source (ex-ante figures) Component 1: Grid connected renewable electricity generation Value used for ex-ante baseline calculation 1 Electricity generation/export to Installation planning and 82,239 MWh/yr the grid design 2 Combined margin ONS, ANEEL (2006) Ecoinvest (2006a-c) Econergy also see Annex kg/mwh Component 2: Avoidance of methane production 3 Q y, biomass Installation planning 115,000 tons/yr and design 4 Q y, non-biomass Installation planning 0 tons/yr and design 5 Model correction factor (φ) TME Fraction of methane captured at Project design 0 the SWDS and flared, combusted or used in another manner (f) 7 Oxidation factor (Ox) Project Design 0 8 Fraction of CH 4 in landfill gas TME / IPCC (F) 9 Per cent of rice husks in the deposited waste (j) Disposal site 100% 10 Per cent of degradable organic TME; classification as 0.5 fraction by weight in the waste type j (DOCj) wood, wood waste and straw, wet waste 11 Fraction of DOC that can TME / IPCC decompose (DOC f ) 12 Methane correction factor (MCF) TME; classification as unmanaged-shallow solid waste disposal sites. 13 Amount of organic waste type j Quantification of biomass 102,500 tons/yr

13 Parameter prevented from disposal in the SWDS in the year x (W j,x ) 14 Decay rate for the waste stream type j (kj) 15 Year since the landfill started receiving wastes (x) 16 Year for which LFG emissions are calculated (y) 17 Global warming potential of methane (GWP_CH 4 ) 18 Methane destroyed/removed in year y due to national regulations (Md y,reg ) 19 Truck capacity for waste transportation (CT y ) 20 Average transporting distance of biomass (DAF) 21 CO 2 emissions factor from fuel use for transportation (E y,fuel ) 22 Quantity of combustion residues per year (Q y,ash ) 23 Average transporting distance of ash (DAF Ash ) 24 Truck capacity for waste transportation (CT y, Ash ) 25 Q y, fuel ( for the emergency electricity generator only). Data source Value used for ex-ante (ex-ante figures) baseline calculation that would be left for decay (wet waste) in absence of the project activity TME; classification as 0.03 wood, wood waste and straw, MAT < 20 C, wet/humid climate Baseline scenario 2008 Baseline scenario IPCC 21 Brazil regulations for the operation of disposal sites (including emission standards) - ABNT NBR and Assumption: 40% as pressed commodity, 60% as loose commodity Calculated weighted average distance between rice mills and plant site IPCC default value for US uncontrolled diesel trucks Reference Manual, table 1-32 Expert judgement based on typical fuel ash content and amount of fuel Conservative estimate Planning data Installation planning (conservative estimate) 0 tons/yr 24 t/truck 25km kg CO 2 /km 24,900 t/yr 75 km 24 t/truck 0.5t/yr 4 Table 2: Key information and data used to determine the baseline scenario B.5. Description of how the anthropogenic emissions of GHG by sources are reduced below those that would have occurred in the absence of the registered small-scale CDM project activity: litres/yr, assumed density of kg/l (Maly 2004). 13

14 If the planned CDM project activity was not implemented, the current situation would prevail. More concrete, the current practice of dumping biomass and related methane production from decay would continue. Also, this biomass would not be utilized for renewable electricity generation. Such continuation of current practice seems the only realistic alternative to the project scenario. According to attachment A to Appendix B of the simplified modalities and procedures for small-scale CDM project activities, project participants shall provide an explanation to show that the project activity would not have occurred anyway due to at least one of the following barriers: (a) Investment barrier: a financially more viable alternative to the project activity would have led to higher emissions; (b) Technological barrier: a less technologically advanced alternative to the project activity involves lower risks due to the performance uncertainty or low market share of the new technology adopted for the project activity and so would have led to higher emissions; (c) Barrier due to prevailing practice: prevailing practice or existing regulatory or policy requirements would have led to implementation of a technology with higher emissions; (d) Other barriers (e.g. institutional barriers, limited information, managerial resources, organizational capacity, financial resources, or capacity to absorb new technologies) In the subsequent sections, the additionality of the project will be shown, taking into account the various barriers named in attachment A to Appendix B. In essence, the additionality of the project is given due to the combination of two barriers: First, there is a lack of financial resources and organisational capacity in the host country that obviously prevents locals, e.g. the operators of rice mills, to construct and operate a biomass power plant themselves. This also results from the high interest rates and limited availability of long-term loans in the host country (Instituto Nacional de Eficiencia Energética; A2R. 2001). Second, Hamburgo Energia Ltda. would not take the final investment decision without assurance that there will be additional income in the form of reduction credits. In fact, income from CERsales is an inherent part of the financing/loan structure of the project. Hence, there is a severe investment barrier. Financial resources barrier (Category other barriers ) As a consequence of the historically long period of inflation, the Brazilian Real (BRL) experienced high volatility coupled with strong devaluation, which effectively precluded commercial banks from providing any long-term debt financing to local companies. The lack of a long-term debt market caused a severe negative impact on the financing of energy projects in Brazil in the past decades, regardless the fact that the Brazil government opened the electricity market for private companies (De Araújo, De Oliveira, 2003). Even after implementation of the Real plan in 1994 and the resulting stabilisation of inflation rates, Real interest rates have been high (also see Figure 5). 14

15 Figure 5: Interest rates as annualized Serviço Especial de Liquidaçao e Custódia (SELIC). Source: Latin Focus 2006 / Banco Central do Brazil, The investment costs of the biomass power plant amount to 52,650,000 R$, or 19,500,000 EUR 5 respectively. Total annual running costs are about 5,500,000 R$ without instalments and interest, while the expected annual income from electricity sales is approximately 10,500,000 R$. Comprehensive financial data have been provided to the DOE but are not published for confidentiality reasons. The analysis of the project finances shows that the project activity would not be economically feasible under such high interest rates. Table 3 summarizes the key indicators for interest rates of 15%, 17.5% and 20%. IRR-calculations are done for a period of 20 years, since this is the expected lifetime of the installation. Interest rate Payback period [years] IRR (20 years) 15% % 17.5% % 20% >21-0.8% Table 3: Project finances with interest rates typical for host country Additionally, the availability of long-term loans is very limited. The National Development Bank BNDES is the only supplier of long-term loans (EEVentures, 2002). These two facts practically constitute prohibitive barriers for the investment of 52,650,000 BRL in the project activity by Brazilian companies. 5 Currency exchange rate of 2.7 BRL/EUR; February

16 CDM Executive Board Investment Barrier As has been shown above, the investment in the planned biomass power plant would not be feasible for national investors due to high interest rates and limited availability of long-term loans. The intended financing structure for the Dom Pedrito biomass power plant tries to overcome these barriers by including a foreign investor, Energiegesellschaft Palmaille (ENERPAL), Hamburg/Germany. ENERPAL intends to organise a 7-year loan from German bank, partly secured with a Hermes Euler export credit insurance 6. Under this construction, it might be possible to achieve interest rates of 7-8%. However, even under such improved conditions, the project activity itself would not be an attractive investment option. Even under the conservative assumption that personnel costs will not increase during project s lifetime, the project is characterised by a payback period of approx. 15 years and an Internal Rate of Return (IRR) of % without revenues from CER-sales (also see Table 4). Interest rate Payback period [years] IRR (20 years) 7% % 7.5% % 8% % Table 4: Project finances with reduced interest rates For the German investor, the risks of high inflation and currency devaluation are most fundamental. All income streams are generated in BRL, while the loan is provided in hard currency (EUR). Hence, the investor faces the risk of currency devaluation which can be considered a serious threat in the background of the Brazilian economic history. Even in recent years, both inflation rate and currency exchange rate must be considered relatively high and volatile (see Figure 6). A devaluation of the Brazil Real constitutes a major threat with regard to repayment of the EUR-loan. Figure 6: Inflation in Brazil and volatility of BRL. Source: Bevilaqua (2006) 6 As will be shown below, the availability of those loans are contingent upon CER-generation, as expected income from CER-sales would be a security aspect for the credit. 16

17 Hence, in case the project activity would not generate CERs, the investment was not a viable option for the German investor. As a consequence, the biomass power plant would not be constructed, leading to higher GHG emissions. In order to visualize the impact of CER-generation on the project s financial feasibility, the incremental income through CER-sales is estimated below (scenario: 8.0% interest rate). Calculations are based on the expected annual emission reductions achieved by the project activity and average CER-prices of 8.0 EUR/CER, 10.0 EUR/CER and 12.0 EUR/CER. CER-Price Payback period [years] IRR (20 years) % % % Even more important is the fact CER-sales lead to additional income in hard currency (EUR or US$), which can be used to pay annual instalments and interest. In fact, at a price of 10 EUR/CER, revenues from annual CER-sales during the first 7 years would cover approx. 12% of the instalments and interest rates that have to be covered by the investor. B.6. Emission reductions: B.6.1. Explanation of methodological choices: Component 1: Grid connected renewable electricity generation The formulas as given in AMS I.D are used without deviations. Project emissions related to the electricity consumption when it occurs will be calculated as following: where, PE y,power = EC y * CEF_CO 2,elect PE y,power Project Emissions of electricity consumption (tonnes CO 2e ) EC y CEF_CO 2,elect Electricity consumption by project activity in year y (MWh) Grid Carbon Emission Factor (measured in tonnes CO 2e / MWh) In line with AMS I.D, the combined margin (CM) is calculated on the basis of the operating margin (OM) and build margin (BM) according to the procedures prescribed in the approved methodology ACM0002. Any of the four procedures to calculate the operating margin can be chosen, considering the restrictions as defined in ACM0002. According the recommendations given in ACM0002, for Brazilian projects, the Operating Margin is calculated as the Simple Adjusted Operating Margin (EF_OM adjusted): 17

18 CEF_CO 2,elect = ( ωom * EF_OM adjusted ) + ( ωbm * EF_BM) where, EF_OM adjusted Simple Adjusted Operating Margin emission factor EF_BM Build Margin emission factor ωom = ωbm weights by default = 0.5 The Simple Adjusted Operating Margin (EF_OM adjusted ) is calculated as: where, F i,,y the amount of fuel i (in GJ) consumed by power source j or k in year y; k set of low-cost or must-run plants delivering electricity to the grid j other plants; COEF i,y carbon coefficient of fuel i (tco 2e /GJ); GEN y electricity (MWh) delivered to the grid by source j or k number of hours per year for which low-cost/must-run sources are on margin/8760 hours per year λ y The CO 2 coefficient is estimated as COEF i,j = NCV i * EF CO2,i * OXID i Where NCV i OXID i EF CO2,i is the net calorific value per mass or volume unit of fuel i is the oxidation factor of the fuel i CO 2 emission factor per unit of energy of the fuel i The plant will be connected to the Southeast-South-Midwest interconnected system. Load and values for Lambda (λ), Simple Adjusted Operating Margin and Build Margin emission factors are presented in Annex 3. Component 2: Avoidance of methane emissions The formulas as given in AMS III-E are used without deviations. Concerning the calculation of the methane generation potential MB y, AMS III-E refers to the Methodological Tool to determine methane emissions avoided from dumping waste at a solid waste disposal site (TME). The relevant formula for the calculation of the methane avoidance potential is: where 18

19 In order to reflect the baseline scenario in a realistic way, year x is set as the year 2008 being the first year the disposal site would continue to receive rice husks in the absence of the project activity. Y is the year for which MB y is calculated, i.e. the years after project implementation ( ). Baseline emissions (BE) are calculated as: BE y = MB, y * GWP_CH 4 MD y,reg * GWP_CH 4 Where BEy MB, y MD y,reg CH 4 _GWP Baseline methane emissions from biomass decay (tonnes of CO2 equivalent) Methane generation potential in the year y (tonnes of CH 4 ), estimated by applying the TME. Methane that would be destroyed or removed in the year y for safety or legal regulation GWP for CH 4 (value of 21 is used for the first commitment period) Project emissions for the methane avoidance component according to AMS III.E (version 10: 23 rd December 2006) are calculated as: PE y = PE y,comb + PE y,tansp + PE y,power Where PE y project activity direct emissions in the year y (tonnes CO 2 e) PE y,comb emissions through combustion of non-biomass carbon in the year y (tonnes CO 2 e) PE y,tansp emissions through incremental transportation in the year y (tonnes CO 2 e) PE y,power emissions through electricity or diesel consumption in the year y (tonnes CO 2 e) PE y,comb = Q y,non-biomass * 44/12 + Q y,fuel * E y,fuel 19

20 Where Q y,non-biomass Q y,fuel E y,fuel non-biomass carbon of the rice husks combusted in the year y (tonnes of carbon) quantity of auxiliary fuel used in the year y (tonnes) CO 2 emission factor for the combustion of the auxiliary fuel (tonnes CO 2 per tonne fuel according to IPCC guidelines) PE y,tansp = (Q y / CT y ) * DAF w * EF CO2 (Q y,ash / CT y, ash ) * DAF ash * EF CO2 Where Q y CT y DAF w EF CO2 ** Q y,ash CT y, ash DAF ash quantity of rice husks combusted in the year y (tonnes) average truck capacity for waste transportation (tonnes/truck) average incremental distance for rice husk transportation (km/truck) CO 2 emission factor from fuel use due to transportation (kg CO 2 /km) quantity of combustion revenues produced in the year y (tonnes) average truck capacity for combustion residues transportation (tonnes/truck) average distance for combustion residues transportation (km/truck) ** It may be noted that the fuel consumed by trucks is likely to contain ethanol (CO 2 -neutral). Due to conservativeness reasons, however, it is assumed that the fuel consists of 100% diesel (fossil fuel). It may be noted that approx. 240 tons of fuel wood will be utilized annually to pre-heat the boiler. However, since this is a CO 2 -neutral fuel, no CO 2 -emissions are to be accounted for. B.6.2. Data and parameters that are available at validation: Data / Parameter: φ Data unit: n.a. Description: Model correction factor according to the Tool to determine methane emissions avoided from dumping waste at a solid waste disposal site (TME) Source of data used: AMS III.G and TME Value applied: 0.9 Justification of the Standard default factor choice of data or description of measurement methods and procedures actually applied : Any comment: n.a. Data / Parameter: F Data unit: % Description: Fraction of methane captured at the SWDS and flared, combusted or used in another manner Source of data used: AMS III.G and TME Value applied: 0 Justification of the Project design: no flaring or methane capturing is applicable choice of data or 20

21 description of measurement methods and procedures actually applied : Any comment: n.a. Data / Parameter: F Data unit: % Description: Fraction of CH 4 in landfill gas (F) Source of data used: AMS III.G and TME Value applied: 0.5 Justification of the Standard default factor choice of data or description of measurement methods and procedures actually applied : Any comment: n.a. Data / Parameter: DOCj Data unit: % Description: Per cent of degradable organic fraction by weight in the waste type j (DOCj) Source of data used: TME Value applied: 0.5 Justification of the Classification as wood, wood waste and straw, wet waste choice of data or description of measurement methods and procedures actually applied : Any comment: n.a. Data / Parameter: DOC f Data unit: % Description: Fraction of DOC that can decompose (DOC f ) Source of data used: TME / IPCC 2006 Value applied: 0.5 Justification of the Standard default factor choice of data or description of measurement methods and procedures actually applied : Any comment: n.a. Data / Parameter: MCF 21

22 Data unit: n.a. Description: Methane correction factor Source of data used: TME Value applied: 0.4 Justification of the Classification as unmanaged-shallow solid waste disposal sites. choice of data or description of measurement methods and procedures actually applied : Any comment: n.a. Data / Parameter: kj Data unit: n.a. Description: Decay rate for the waste stream type j Source of data used: TME Value applied: 0.03 Justification of the Classification as wood, wood waste and straw, MAT < 20 C, wet climate choice of data or description of measurement methods and procedures actually applied : Any comment: n.a. Data / Parameter: GWP_CH 4 Data unit: n.a. Description: Global warming potential of methane Source of data used: AMS III.E, IPCC Value applied: 21 Justification of the Standard GWP choice of data or description of measurement methods and procedures actually applied : Any comment: n.a. Data / Parameter: E y,fuel Data unit: kg CO 2 /km Description: CO 2 emissions factor from fuel use for transportation Source of data used: IPCC 1996 default value for US uncontrolled diesel trucks. Ref. Man., table 1-32 Value applied: Justification of the Conservative standard emissions factor. choice of data or description of 22

23 measurement methods and procedures actually applied : Any comment: n.a. B.6.3 Ex-ante calculation of emission reductions: Component 1: Grid connected renewable electricity generation In line with AMS I.D, baseline emissions are calculated as: BEy = (EG y EG baseline ) * EF y Where BE y baseline emission (tonnes CO 2 ) EG y electricity supplied by the project activity to the grid (MWh) EG baseline baseline electricity supplied to the grid in the case of modified or retrofit facilities (MWh) EF y baseline emission factor (tco 2 /MWh) As shown in Annex 3, the baseline emission factor has been determined as t CO 2 /MWh. Hence, baseline emissions are 21,473 t CO 2 e /yr. Project emissions are 0 t CO 2 e/yr. Component 2: Avoidance of methane emissions The baseline emissions are calculated as: BEy = MB,y * GWP_CH 4 MDy,reg* GWP_CH 4 Where BEy MB,y MDy,reg CH 4 _GWP Baseline methane emissions from biomass decay (tonnes of CO 2 equivalent) Methane generation potential in the year y (tonnes of CH 4 ), estimated by applying the TME. Methane that would be destroyed or removed in the year y for safety or legal regulation GWP for CH 4 (value of 21 is used for the first commitment period) The baseline emissions of the methane avoidance component increase over time, also see Table 5. Year MBy [t CH 4 ] BEy [t CO2e] Year ,817 Year ,521 Year ,116 Year ,604 Year ,990 Year 6 1,013 21,275 Year 7 1,165 24,463 Table 5: Methane generation potential and baseline emissions (methane component) Project emissions (PE y,power ) through auxiliary fuel (diesel) consumption in the year y are 1.6 tco 2 e. 23

24 As an annual average, project emissions through incremental transportation (PE y,tansp ) are tco 2 e and project emissions through of non-biomass carbon (PE y,comb ) are estimated 0 tco 2 e 7. [t CO 2-eq ] PE y,comb PE y,power PE y, transp PE Year Non-biomass in fuel Auxiliary fuel (diesel) Transport of biomass+ash Project total Year 1 (2008/09) Year 2 (2009/10) Year 3 (2010/11) Year 4 (2011/12) Year 5 (2012/13) Year 6 (2013/14) Year 7 (2014/15) Total , ,060.7 Annual average PE y,comb emissions through combustion of non-biomass carbon in the year y (tonnes CO 2 e) PE y,tansp emissions through incremental transportation in the year y (tonnes CO 2 e) PE y,power emissions through electricity or diesel consumption in the year y (tonnes CO 2 e) PE total project direct emissions in the year y (tonnes CO 2 e) Hence, total project emissions are t CO 2 e/yr. For both components, emission reductions are measured as the difference between the baseline emissions and the sum of the project emissions and leakage. ER y = BE y (PE y + Leakage) In line with AMS I.D and AMS III.E, leakage is not applicable because no transfer of energy generating equipment is involved in the project activity. 7 This is based on the expectation that delivered rice husk are 100% biomass (no major contaminations with other substances). 24

25 B.6.4 Summary of the ex-ante estimation of emission reductions: [t CO 2-eq] Year Estimation of PE (t CO2e) Estimation of BE (t CO2e) Estimation of leakage (t CO2e) Estimation of ER (t CO2e) Estimation of PE (t CO2e) Estimation of BE (t CO2e) Estimation of leakage (t CO2e) Estimation of ER (t CO2e) Year 1 (2008/09) 0 21, , , ,380 Year 2 (2009/10) 0 21, , , ,084 Year 3 (2010/11) 0 21, , , ,679 Year 4 (2011/12) 0 21, , , ,167 Year 5 (2012/13) 0 21, , , ,552 Year 6 (2013/14) 0 21, , , ,838 Year 7 (2014/15) 0 21, , , ,026 Total in crediting period BE = Baseline Emissions PE = Project Emissions ER = Emission Reductions Component 1: Renewable electricity generation AMS I.D Component 2: Avoidance of methane production AMS III.E 0 150, ,308 3, , ,725 Year Estimation of PE (t CO2e) Estimation of BE (t CO2e) Estimation of leakage (t CO2e) Estimation of ER (t CO2e) Year 1 (2008/09) , ,852 Year 2 (2009/10) , ,556 Year 3 (2010/11) , ,151 Year 4 (2011/12) , ,640 Year 5 (2012/13) , ,025 Year 6 (2013/14) , ,310 Year 7 (2014/15) , ,498 Total in crediting period 3, , ,033 BE = Baseline Emissions PE = Project Emissions ER = Emission Reductions 25

26 B.7 Application of a monitoring methodology and description of the monitoring plan: B.7.1 Data and parameters monitored: Component 1: Data / Parameter: Data unit: Description: Source of data to be used: Value of data Description of measurement methods and procedures to be applied: QA/QC procedures to be applied: Any comment: Data / Parameter: Data unit: Description: Source of data to be used: Value of data EG y MWh Electricity supplied to the grid Electricity metering To be monitored Continuous recording, monthly reporting. Standard electricity metering procedures in accordance with the requirements defined by the Camara de Comeracializacao de Energia Eletrica (CCEE) and/or ANEEL (whichever is relevant at the time of project start). Electricity metering will be conducted with standard metering devices, which are characterized by a high accuracy due to their relevance for invoicing and financial accounting. Only measurement devices accepted by CCEE/ONS will be used (currently: the Standards for Electricity NBR 5410, grid proceedings from ONS). Standards for connection are established by grid companies during licensing. According to the Brazilian regulations on electrical grid, at least two supplementary conventional electronic measurers are to be installed at the outlet cabin: one primary meter, and a backup meter. These metering devices have to comply with the standards of CCEE/ONS; a link of currently accepted devices can be found at: the accepted measurement error class is 0.2 Relevant standards for current transformers as described at will be followed, as well as standards regarding the Installation and adjustment of devices ( In addition, the relevant regulations and manufacturers instructions with regard to the calibration of devices will be adopted. The accepted error class for these monitoring devices is 0.3. Meters will be subject to regular maintenance and testing regime to ensure accuracy. The meter must meet the relevant calibration standards of ONS/ANEEL/CCEE (whichever is relevant at the time of calibration). Calibration records will be kept to show auditors in the verification process, if requested. The consistency of metered electricity will be crosschecked with the quantity of biomass fired (e.g. estimation of efficiency = electricity generation divided by the quantity of utilizes biomass). n.a. EF y t CO 2 / MWh Emission Factor of the Grid ONS; ANEEL To be monitored. For ex-ante calculations, the validated combined margin as the average of grid 26

27 Description of measurement methods and procedures to be applied: QA/QC procedures to be applied: Any comment: Component 2: Data / Parameter: Data unit: Description: Source of data to be used: Value of data Description of measurement methods and procedures to be applied: QA/QC procedures to be applied: Any comment: Data / Parameter: Data unit: Description: Source of data to be used: Value of data Description of measurement methods and procedures to be applied: QA/QC procedures to be applied: Any comment: Data / Parameter: Data unit: Description: Source of data to be used: Value of data Description of data (ONS) is applied. Use of official statistics, application of formulas in AMS I.D. Third party check (verification by DOE). n.a. Q v,fuel Tons/yr Diesel consumption in the power plant Fuel bills, inventory of fuel stock To be monitored Monthly data monitoring, Transformation of volume units into mass units with a diesel density conversion faction of kg/l (Maly 2004). Measurements of annual fuel consumption will be cross-checked with fuel bills as well as a record on the operating hours of the emergency generator. n.a. Q y, non-biomass tons Non-biomass share of utilized biomass Visual control upon delivery of biomass to identify any non-biomass contaminations of the delivered fuel. If contaminations are found, these will be quantified and resulting CO 2 - emissions will be calculated. To be monitored Sampling and weighting if contaminations are found. An accurate and frequent sampling of biomass contamination during the project activity will ensure that any contaminations of non-biomass are identified and quantified in a timely manner. n.a. Q y tons Quantity of rice husks combusted Plant operator, fuel bills To be monitored Fuel consumption will be calculated as 27

28 measurement methods and procedures to be applied: QA/QC procedures to be applied: Any comment: Data / Parameter: Data unit: Description: Source of data to be used: Value of data Description of measurement methods and procedures to be applied: QA/QC procedures to be applied: Any comment: Data / Parameter: Data unit: Description: Source of data to be used: Value of data Description of measurement methods and procedures to be applied: QA/QC procedures to be applied: Any comment: Qy = fuel delivered to project site ± change in fuel stock (silos) - fuel leaving project site (if any). The quantity of fuel stored in the silos in [kg] is determined as Q biomass [m 3 ] x ρ biomass. The density of biomass stored in the silos (ρ biomass ) will be determined in a field test or lab analysis. Fuel delivery will be determined at the entry of the project site (truck weights) and on the basis of fuel bills. While the latter figure is relevant for the financial accounting and is thus the preferred value, there will be a consistency-check between these two parameters. The truck weight will be properly maintained and calibrated. Truck weights typically have a measurement error of 2-7% 8, with new ones at the lower end. Inventories of the fuel stock at the project site can be undertaken with low measurement uncertainty because the rice husks will be stored in silos with known volumes. The density of biomass stored in the silos (ρ biomass ) will be determined as field tests, being conducted at project start and in line with maintenance intervals of the power plant. n.a. Q y, FS tons Origin of supplied biomass (production or disposal site) Biomass suppliers, data gathering by gate keeper To be monitored. Monitoring will be done each time biomass is delivered. Biomass taken from existing disposal sites will not be considered in calculating MBy. Data can be easily checked by gate keeper on the basis of transport logs. In case of doubts at later stages, fuel bills can be taken as reference. n.a. BL BM tons Quantity of biomass that would have been dumped on disposal sites Biomass suppliers To be monitored. Please see Annex 4. Third party validation (DOE) For each biomass supplier, the amount of eligible biomass (tons of biomass that have been left for decay annually) has been determined; see Annex 4. 8 EU COM (2004), COMMISSION DECISION of 29/01/2004, Establishing guidelines for the monitoring and reporting of greenhouse gas emissions pursuant to Directive 2003/87/EC of the European Parliament and of the Council, Table 2, page