PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

CDM – Executive Board page 1

CLEAN DEVELOPMENT MECHANISM PROJECT DESIGN DOCUMENT FORM (CDM-PDD) Version 03 - in effect as of: 28 July 2006

CONTENTS

A. General description of 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 project activity

Annex 2: Information regarding public funding

Annex 3: Baseline information

Annex 4: Monitoring plan

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SECTION A. General description of project activity

A.1 Title of the project activity: >> Coal to Biomass Residues Fuel Switch Project in Suibao Cogeneration Co. ,Ltd Version number of the document: 01 Date: 20/02/2009

A.2. Description of the project activity: >> Heilongjiang Suibao Cogeneration Co., Ltd is located in Acheng , City of Heilongjiang Province, which now has 2 sets of 75t/h coal-fired circulating fluidized bed boiler and 2 sets of 35t/h coal-fired chain grate boiler and is the major source of heat supply for the eastern region of the city as well as of industrial steam supply for the enterprises nearby.

Coal to Biomass Residues Fuel Switch Project in Heilongjiang Suibao Cogeneration Co. Ltd. (hereafter referred to as the Project) involves retrofitting 2 sets of 75 t/h coal-fired circulating fluidized bed boiler having a lifetime of 20 years which were put into operation in Nov. 2004 and Dec. 2004 respectively, and 2 sets of 35t/h coal-fired chain great boiler having a lifetime of 30 years which were put into operation in Dec. 1991. Biomass residues including rice straw, husk and so on will be mixed with coal for combustion in the Project, which will reduce the emission of greenhouse gases(GHG) while achieving the integrated utilization of agricultural waste materials. It is estimated that the project activity will consume 166,540 tons of biomass residues and reduce the consumption of 71,380 tons of standard coal equivalent, thus generating GHG emission reductions of about 146,882 tCO2e per year.

Acheng District, Harbin City of Heilongjiang Province, listed one of the 500 major counties of marketable grain production, has 720.36km2 of arable land, and was once honored “Advanced Unit for Grain Production” and “Rice Hometown of China”. Within a radius of 30km around the Project, there are approximately 400,000 tons of rice straw and husk per year which have not been utilized and are left to decay or burnt in an uncontrolled manner, resulting in serious pollution to the local environment.

The Project clearly fits into the development priority of China, and will not only supply electricity utilizing renewable energy, but also contribute to sustainable development of the local community, the host country and the world by means of:

Š reducing 629 tons of SO2 emission and 150.13 tons of TSP discharge per year via an decrease of coal consumption1; Š mitigating the water pollution, air pollution and landscape pollution resulting from leaving the straw to decay or burning it in an uncontrolled manner; Š creating 60 long term positions for local residents required by the fragmenting and prilling processes of the Project.

A.3. Project participants: >> Participants to the project activity are the following:

1 EIA approval of the Project PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Kindly indicate if the Party Name of Party involved Private and/or public entity(ies) project involved wishes to be considered as (*) ((host) indicates a host participants (*) project participant Party) (as applicable) (Yes/No) Heilongjiang Suibao Cogeneration Co., Ltd. P.R.China (host) No (Project owner) Carbon Capital Management, Inc. (Japan). Japan No (Project buyer)

More detailed contact information on the Participants is provided in Annex 1.

A.4. Technical description of the project activity:

A.4.1. Location of the project activity:

A.4.1.1. Host Party(ies): >> The Host Country is the People’s Republic of China.

A.4.1.2. Region/State/Province etc.: >> Heilongjiang Province

A.4.1.3. City/Town/Community etc: >> Acheng District, Harbin City

A.4.1.4. Detail of physical location, including information allowing the unique identification of this project activity (maximum one page): >> The Project, with the geographical coordinates of east longitude of 126°35′17″and north latitude of 45°19′ 22″, is located in the eastern region of Acheng District, Harbin City of Heilongjiang Province. Figure 1 is a map showing the location of the Project.

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The Project

. Figure 1. Map showing the location of the Project

A.4.2. Category(ies) of project activity: >> This category would fall within sectoral scope 1: energy industries (renewable energy) and sectoral scope 4: Manufacturing industries.

A.4.3. Technology to be employed by the project activity: >> Within a radius of 30km surrounding the project site, biomass residues composed primarily of rice straw and husk amount to 400,000 tons, which are left to decay in the field or burnt in an uncontrolled manner. This not only pollutes the environment, but also wastes a great amount of renewable energy. Heilongjiang Suibao Cogeneration Co., Ltd. currently has 2 sets of 75t/h coal-fired circulating fluidized bed boiler and 2 sets of 35t/h coal-fired chain grate boiler which consume a great deal of coal each year. Consumption of coal will not only emit CO2, but also emit a great amount of SO2 and dust, resulting in serious environmental pollution to the area of the project site. The Project involves making retrofit to the 2 sets of 75t/h coal-fired circulating fluidized bed boiler and 2 sets of 35t/h coal-fired chain grate boiler, enabling the combustion of biomass residues (accounting for 80%) mixed with coal in the 4 boilers.

In order to enhance the efficiency of biomass residues combustion, a set of biomass residues prilling PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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system will be added into the Project, which will prill the rice straw and then mix the rice straw pellet with rice husk and coal according to a certain mass ratio (50% for rice straw pellet, 30% for rice husk and 20% for coal) and delivers them into the boilers for combustion to produce steam. Major technical parameters of the key equipments employed by the Project are illustrated as follows: 75t/h coal-fired 75t/h coal-fired 35t/h chain grate 35t/h chain grate Boiler circulating fluidized circulating fluidized boiler boiler bed boiler bed boiler Type YG-75/3.82-M YG-75/3.82-M YG-35/3.82-M YG-35/3.82-M

Nameplate 85% 85% 83% 83% efficiency Time when the boiler was put into Nov., 2004 Dec., 2004 Dec., 1991 Dec., 1991 operation Operational life of 20 years 20 years 30 years 30 years the boiler Remaining operational life of 16 years 16 years 13 years 13 years the boiler Manufacturer Jinan boiler Co. Ltd Jinan boiler Co. Ltd Jinan boiler Co. Ltd Jinan boiler Co. Ltd

All the equipments employed by the Project are manufactured by domestic manufacturers, thus no technical transfer from abroad is involved.

A.4.4 Estimated amount of emission reductions over the chosen crediting period: >> It is expected that the project activities will generate emission reductions of about 146,882 tCO2e per year over a 10-year fixed crediting period from 1st. Jan, 2010 to 31st. Dec, 2019. Annual estimation of emission Years reductions in tonnes of CO2e 2010 146,882 2011 146,882 2012 146,882 2013 146,882 2014 146,882 2015 146,882 2016 146,882 2017 146,882 2018 146,882 2019 146,882

Total estimated reductions (tonnes of CO2e) 1,468,820 Total number of crediting years 10 Annual average over the crediting period of 146,882 estimated reductions (tonnes of CO2e)

A.4.5. Public funding of the project activity: PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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>> There is no public funding from Annex I Parties for this Project. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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SECTION B. Application of a baseline and monitoring methodology

B.1. Title and reference of the approved baseline and monitoring methodology applied to the project activity: >> Approved baseline and monitoring methodology AM0036 ver 02.1 – “Fuel switch from fossil fuels to biomass residues in boilers for heat generation” is adopted by the Project.

According to methodology AM0036, the following tools are also adopted by the Project: “Tool for the Demonstration and Assessment of Additionality” ver 05.2 “Tool to determine methane emissions avoided from disposal of waste at a solid waste disposal site” ver 04

For more information about the methodology and tools, please refer to: http://cdm.unfccc.int/methodologies/PAmethodologies/approved.html

B.2 Justification of the choice of the methodology and why it is applicable to the project activity: >> According to the Feasibility Study Report, the Project meets all the applicability conditions of the approved baseline and monitoring methodology AM0036, details of which are as follows: Scenario Applicability condition Explanation

1 The methodology is applicable to project activities that switch from use of The Project falls into (a) of Scenario 1 fossil fuels to biomass residues, in existing and, where applicable new, of project activities listed in Table 1 boilers. The methodology is applicable to project activities described in of methodology AM0036 – “Retrofit Table 1 of methodology AM0036. of existing boilers. The project activity is the retrofit of (an) existing boiler(s). The retrofit is made to the boiler(s) to enable (a) the use of biomass residues or (b) an increase in the use of biomass residues beyond historical levels, which would not be technically possible in any of the existing boilers without a retrofit or replacement of the boilers.” 2 The project activity may be based on the operation of (a) heat generation The Project involves a retrofit of heat boiler(s): generation boilers in an independent • In an agro-industrial plant generating the biomass residues, which is cogeneration plant in order to enable used in the activity; or the use of biomass residues in the • In an independent plant where the biomass residues are produced from boilers. The biomass residues are the nearby area or a market. produced from the nearby area or a market. • 3 The heat generated in the boiler(s) is: The heat generated in the boilers is o Not used for power generation; or used for power generation, however, o If power is generated with heat from the boilers, it is not increased as a (a) the power generation capacity result of the project activity, i.e, installed remains unchanged (a) Site, the power generation capacity installed remains unchanged due to throughout the crediting period due to the implementation of the project activity and this power generation the implementation of the project capacity is maintained at the pre-project level throughout the crediting activity; and (b) the annual power PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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period; and generation during the crediting period (b) The annual power generation during the crediting period is not more is not more than 10% larger than the than 10% larger than the highest annual power generation in the most highest annual power generation in recent three years prior to the implementation of the project activity. the most recent three years prior to the implementation of the project activity. 4 The use of biomass residues or increasing the use of biomass residues RMB 22.93 million yuan is invested beyond historical levels is technically not possible at the project site by the Project in retrofitting existing without a significant capital investment in: boilers. o Either the retrofit or replacements of existing boilers or the installation of new boilers; o Or in a new dedicated biomass supply chain established for the purpose of the project (e.g. collecting and cleaning contaminated new sources of biomass residues that could otherwise not be used for energy purposes). 5 Existing boilers at the project site have used no biomass or have used only Existing boilers at the project site biomass residues (but no other type of biomass) for heat generation during have used no biomass for heat the most recent three years prior to the implementation of the project generation during the most recent activity. three years prior to the implementation of the project activity. 6 No biomass types other than biomass residues, as defined above, are used Biomass residues combusted during in the boiler(s) during the crediting period (some fossil fuels may be co- the crediting period of the Project are fired). only those biomass residues abandoned and not utilized, which will be mixed with coal by a ratio of 80:20 for combustion. 7 For projects that use biomass residues from a production process (e.g. Rice husk employed by the Project production of sugar or wood panel boards), the implementation of the comes from the nearby rice project shall not result in an increase of the processing capacity of raw processing factories, and the input (e.g. sugar, rice, logs, etc.) or in other substantial changes (e.g. implementation of the project will not product change) in this process. result in an increase of the processing capacity of rice or in other substantial changes (e.g. product change). 8 The biomass residues used at the project site, where the project activity is The method of FIFO is adopted by the implemented, should not be stored for more than one year. Project for storing the biomass residues to ensure that the biomass residues are not stored for more than one year. 9 No significant energy quantities, except from transportation or mechanical The Project will perform only treatment of the biomass residues, are required to prepare the biomass mechanical treatment of the biomass residues for fuel combustion, i.e. projects that process the biomass residues in the prilling process, so residues prior to combustion (e.g. esterification of waste oils) are not except from transportation or eligible under this methodology. mechanical treatment of the biomass residues, no significant energy quantities are required. 10 The biomass residues are directly generated at the project site or The biomass residues used by the transported to the project site by trucks project activity are transported to the project site by trucks 11 In case of project activities that involve the replacement or retrofit of All the existing boilers prior to the existing boiler(s), all boiler(s) existing at the project site prior to the implementation of the project activity implementation of the project activity should be able to operate until the are able to operate until the end of the end of the crediting period without any retrofitting or replacement, i.e. the crediting period without any remaining technical lifetime of each existing boiler should at the start of retrofitting or replacement. Technical PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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the crediting period be larger than the duration of the crediting period (7 or lifetime of the boilers will be 10 years as applicable). For the purpose of demonstrating this applicability provided by the manufacturers. condition, project participants should determine and document the typical average technical lifetime of boilers in the country and sector in a conservative manner, taking into account common practices in the sector and country. This may be done based on industry surveys, statistics, technical literature, historical replacement records of boilers in the company, etc. The age of the existing boiler(s) and the average technical lifetime of boilers in the country and sector should be documented in the CDM-PDD. 12 Furthermore, this methodology is only applicable if the most plausible The most plausible baseline scenario baseline scenario(s): for the Project is: • For heat generation is either case H2 or case H5; and • For heat generation is case H2; and • For the use of biomass residues is case B1, B2, B3, B4 and/or B5. If • For the use of biomass residues is case B5 is the most plausible scenario, the methodology is only applicable case B1. if: (a) The plant where the biomass residues would be used as feedstock in the absence of the project activity can be clearly identified throughout the crediting periods; (b) The fuels used as substitutes for the biomass residues at that plant can be monitored by project participants. 13 The applicability conditions outlined in the latest available version of the CH4 emissions, from the treatment of “Tool to determine methane emissions avoided from disposal of waste at a biomass residues, are not included in solid waste disposal site”, in addition to the above listed applicability the baseline of the project activity; conditions, apply if: and case B2 is not identified as the

• CH4 emissions, from the treatment of biomass residues, in the baseline most plausible baseline scenario for are included; the use of biomass residues. • Where case B2 is identified as the most plausible baseline scenario for the use of biomass residues.

To sum up, the Project satisfies the applicability conditions of methodology AM0036.

B.3. Description of the sources and gases included in the project boundary >> The project activity is utilizing the biomass residues including rice straw and husk in place of coal, and the baseline scenario is case B1: the biomass residues are dumped or left to decay under mainly aerobic conditions (please refer to B.4 for detailed analysis). According to methodology AM0036, the following emissions sources are considered:

• CO2 emissions from on-site fossil fuel and electricity consumption that is attributable to the project activity. This may include fossil fuels or electricity used for on-site transportation or preparation of the biomass residues, e.g., the operation of shredders or other equipment, but shall not include fossil fuels co- fired in the boiler(s); • CO2 emissions from off-site transportation of biomass residues that are combusted in the boiler(s) to the project site.

For the purpose of determining the baseline, project participants shall include the following emission sources: • CO2 emissions from fossil fuel fired for heat generation in boilers that are displaced by heat generation with biomass residues. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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• Since the most likely baseline scenario for the use of the biomass residues is that the biomass residues would be dumped or left to decay under aerobic conditions (case B1), the project participants have decided to include CH4 emissions in the project boundary.

The spatial extent of the project boundary encompasses: • The boilers and related equipment at the project site; • The means for transportation of biomass residues to the project site (e.g. vehicles).

Sources of GHG emissions included in or excluded from the project boundary when determining the baseline emissions and project emissions are listed in Table 1.

Table 1 Summary of gases and sources included in or excluded from the project boundary source gas Included? Justification/explanation CO Included Main emission source. Fossil fuel 2 Excluded for simplification. This is combustion in CH4 Excluded boilers for heat conservative. Excluded for simplification. This is generation N O Excluded 2 conservative.

It is assumed that CO2 emissions from surplus CO2 Excluded biomass residues do not lead to changes of carbon pools in the LULUCF sector. Baseline Project participants decide to include this Uncontrolled emission source since case B1 is identified as CH Included burning or decay of 4 the most likely baseline scenario for the use of the surplus biomass the biomass residues. residues Excluded for simplification. This is conservative. Note that emissions resulting from N2O Excluded the natural decay of biomass should not be included in the anthropogenic GHG emission list.

Project CO2 Included activity On-site fossil fuel Excluded for simplification. This emissions CH Excluded and electricity 4 source is assumed to be very small. consumption Excluded for simplification. This emissions N O Excluded 2 source is assumed to be very small.

CO2 Included Off-site Excluded for simplification. This emissions CH Excluded transportation of 4 source is assumed to be very small. biomass residues Excluded for simplification. This emissions N O Excluded 2 source is assumed to be very small.

It is assumed that CO2 emissions from surplus biomass residues do not lead to changes of CO2 Excluded carbon pools in the LULUCF sector.

Combustion of Project participants decide to include CH4 biomass residues for emissions from biomass residues left to decay or heat generation CH4 Included burnt in an uncontrolled manner in the baseline scenario, so this emission source should be considered. Excluded for simplification. This emissions N O Excluded 2 source is assumed to be very small. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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It is assumed that CO2 emissions from surplus CO Excluded biomass residues do not lead to changes of 2 carbon pools in the LULUCF sector.

Biomass storage Excluded for simplification. Since biomass CH4 Excluded residues are stored for not longer than one year, this emission source is assumed to be small. Excluded for simplification. This emissions N O Excluded 2 source is assumed to be very small.

Biomass Fuel 2 sets of Purcha Rice straw residues 50% mix 75t/h

sing prilling and circulating Co

station Transportation by system trans fluidized g eneration of trucks porta bed boiler Heat biomas tion and 2 sets s Rice husk 30% syste of 35t/h residue m chain grate s Transportation by trucks boiler

Coal 20% Project boundary

Figure 2. Project boundary

B.4. Description of how the baseline scenario is identified and description of the identified baseline scenario: >> As per the methodology AM0036, the most plausible baseline scenario among all realistic and credible alternatives will be identified by the following steps:

Step 1: Identification of alternative scenarios to the proposed CDM project activity that are consistent with current laws and regulations

Identify all realistic and credible alternatives to the project activity that are consistent with current laws and regulations. Realistic and credible alternatives should be separately determined for the following two components of the project activity: • Heat generation in the absence of the project activity; • What would happen to the biomass residues in the absence of the project activity.

Since the project activity is only retrofit of existing boilers to enable the combustion of biomass residues mixed with coal and is not installation of new boilers fuelled by biomass residues, alternative H5 “Continued operation of the existing boiler(s) using the same fuel mix as in the past AND installation of (a) new boiler(s) that is/are fired with the same fuel type(s) and the same fuel mix as the existing boiler(s) ” should be excluded from analysis.

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According to the baseline alternatives provided in methodology AM0036, the results of analysis and justification of the results are provided in Table 2.

Table 2. Process of identifying plausible alternatives Alternatives Plausible Justification/explanation ? The proposed project activity not Consistent with current laws and H1 undertaken as a CDM project activity Yes regulations. (heat generation with biomass residues); Heat Continued operation of the existing Consistent with current laws and generation H2 boiler(s) using the same fuel mix or less Yes regulations. biomass residues as in the past; Continued operation of the existing Consistent with current laws and H3 Yes boiler(s) using a different fuel (mix); regulations. Improvement of the performance of the Consistent with current laws and H4 Yes existing boiler(s); regulations. Replacement of the existing boiler(s) with Consistent with current laws and H6 Yes new boiler(s). regulations. The biomass residues are dumped or left Common practice for treatment of to decay under mainly aerobic conditions. biomass residues in the area which B1 This applies, for example, to dumping and Yes provides biomass residues for the decay of biomass residues on fields; Project. Consistent with current laws and regulations. The biomass residues are dumped or left to decay under clearly anaerobic conditions. This applies, for example, to Consistent with current laws and B2 deep landfills with more than 5 meters. Yes regulations. This does not apply to biomass residues that are stock-piled or left to decay on fields; Use of Regulation on rural energy biomass administration by Heilongjiang Province The biomass residues are burnt in an residues (Decree of People’s Government of B3 uncontrolled manner without utilizing No Heilongjiang,no. 14)2 forbids the them for energy purposes; burning of biomass residues without utilizing them for energy purposes. The biomass residues are sold to other consumers in the market and the Consistent with current laws and B4 predominant use of the biomass residues Yes regulations. in the region/country is for energy purposes (heat and/or power generation); The biomass residues are used as Consistent with current laws and B5 feedstock in a process (e.g. in the pulp and Yes regulations. paper industry); The biomass residues are used as Rice straw and husk will be used as fertilizer; fertilizer by means of burning them and B6 No returning them to field, Regulation on rural energy administration by Heilongjiang Province (Decree of

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People’s Government of Heilongjiang, no. 14)3 forbids the burning of biomass residues without utilizing them for energy purposes. The proposed project activity not undertaken as a CDM project activity (use Consistent with current laws and B7 Yes of the biomass residues for heat regulations. generation); Any other use of the biomass residues. Uses other than the above B1-B7 are not available. It is assumed here that it is B8 Yes consistent with current laws and regulations.

Outcome of Step 1: based on Table 2, plausible baseline alternatives are identified which are consistent with current laws and regulations.

STEP 2: Barrier analysis to eliminate alternatives to the project activity that face prohibitive barriers

According to the guidance of Step 3 “Barrier analysis” of Tool for the Demonstration and Assessment of Additionality ver 05.2, eliminate the alternatives which have been identified from the outcome of Step 1 but face prohibitive barriers. As required by methodology AM0036, a common set of barriers should be established to evaluate all the alternatives identified in Step 1. Referring to Step 3 of Tool for the Demonstration and Assessment of Additionality ver 05.2, the common set of barriers adopted is as follows:

(a) Investment barriers, other than the investment analysis, inter alia: • For alternatives undertaken and operated by private entities: Similar activities have only been implemented with grants or other non-commercial finance terms. Similar activities are defined as activities that rely on a broadly similar technology or practices, are of a similar scale, take place in a comparable environment with respect to regulatory framework and are undertaken in the relevant country/region; • No private capital is available from domestic or international capital markets due to real or perceived risks associated with investment in the country where the proposed CDM project activity is to be implemented, as demonstrated by the credit rating of the country or other country investments reports of reputed origin. (b) Technological barriers, inter alia: • Skilled and/or properly trained labour to operate and maintain the technology is not available in the relevant country/region, which leads to an unacceptably high risk of equipment disrepair and malfunctioning or other underperformance; • Lack of infrastructure for implementation and logistics for maintenance of the technology (e.g. natural gas can not be used because of the lack of a gas transmission and distribution network); • Risk of technological failure: the process/technology failure risk in the local circumstances is significantly greater than for other technologies that provide services or outputs comparable to those of the proposed CDM project activity, as demonstrated by relevant scientific literature or technology manufacturer information; • The particular technology used in the proposed project activity is not available in the relevant region. (c) Barriers due to prevailing practice, inter alia:

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The project activity is the “first of its kind”.

Process for the barrier analysis is illustrated in Table 3. Table 3. Barrier analysis of alternatives Alternatives Eliminated Barrier analysis ? The proposed project activity not Eliminated from the baseline using the H1 undertaken as a CDM project activity No investment analysis of the Project. (heat generation with biomass residues); Continued operation of the existing Common practice, not facing the above H2 boiler(s) using the same fuel mix or less No barriers. biomass residues as in the past; Using a different fuel mix, including natural gas or fossil fuel; (1) technological barriers will be faced if natural gas is used (natural gas can not be used because of the lack of a gas transmission and distribution network); (2) investment barriers will be faced if Heat fossil fuel is used (net caloric value of generation fossil fuel is 41,816MJ/t, price of fossil fuel is 4,900 yuan RMB/t4, thus MJ price Continued operation of the existing of fossil fuel is 0.1172 yuan RMB; prior H3 Yes boiler(s) using a different fuel (mix); to the implementation of the Project, net caloric value of coal is 16,308 MJ/t, price of coal is 242 yuan RMB/t, thus MJ price of coal is 0.01484, which is 12.63% of that of fossil fuel. Therefore, consumption of fossil fuel will lead to an increase in the unit cost of heat generation to the project owner. So use of fossil fuel can be implemented only with grants or other non-commercial finance terms. Technological barriers are faced (existing 4 boilers at the project site have advanced performance among the same Improvement of the performance of the H4 Yes type of boilers in China, the particular existing boiler(s); specific technology for making improvement of existing boilers is not available in the relevant region). Investment barriers are faced, for additional investment is required to install new boilers having comparable Replacement of the existing boiler(s) performance with existing boilers, H6 Yes with new boiler(s). which, however, will generate no additional revenues, so it can be implemented only with grants or other non-commercial finance terms.

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The biomass residues are dumped or left to decay under mainly aerobic conditions. Common practice, not facing the above B1 No This applies, for example, to dumping barriers. and decay of biomass residues on fields; The biomass residues are dumped or left Investment barriers are faced; for to decay under clearly anaerobic additional investment is required to conditions. This applies, for example, to construct landfills which will not B2 deep landfills with more than 5 meters. Yes generate additional revenues. It can be This does not apply to biomass residues implemented only with grants or other that are stock-piled or left to decay on non-commercial finance terms. fields; Technological barriers are faced, for in the region where the market from which The biomass residues are sold to other the Project procures the biomass consumers in the market and the residues is located, there lacks sufficient B4 predominant use of the biomass residues Yes technological infrastructure for energy in the region/country is for energy production utilizing biomass residues, Use of purposes (heat and/or power generation); resulting in a huge amount of biomass biomass residues not utilized for energy residues purposes. The biomass residues are used as Technological barriers are faced, for in feedstock in a process (e.g. in the pulp the region where the market from which and paper industry); the Project procures the biomass residues is located, there lacks sufficient B5 Yes technological infrastructure for utilizing biomass residues as input materials, resulting in a huge amount of biomass residues not utilized for energy purposes. The proposed project activity not undertaken as a CDM project activity Eliminated from the baseline using the B7 No (use of the biomass residues for heat investment analysis of the Project. generation); Any other use of the biomass residues. Due to prevailing practices, except for B8 Yes the above B1, B2, B4, B5, other uses of biomass residues are not available.

Outcome of STEP 2: based on Table 3, credible alternatives for heat generation of the Project identified include H1 and H2; credible alternatives for use of biomass residues identified include B1 and B7; therefore, the combination of credible alternatives for heat generation or use of biomass residues is: Table 4 Combination of credible baseline scenarios of the Project Combination Heat generation Use of biomass residues of baseline The proposed project activity not undertaken as a The proposed project activity not undertaken as a 1 CDM project activity (heat generation with biomass CDM project activity (B7) residues) (H1) Continued operation of the existing boiler(s) using The biomass residues are dumped or left to decay the same fuel mix as in the past (H2) under mainly aerobic conditions. This applies, for 2 example, to dumping and decay of biomass residues on fields (B1) Combination of baseline 1 is the project activity. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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STEP 3: Investment analysis

Using STEP 2 of Tools for the Demonstration and Assessment of Additionality ver 05.2, analysis will be made on all the combinations of alternatives for heat generation or use of biomass residues not eliminated after Step 2. The most economically attractive combination of alternatives for heat generation or use of biomass residues will be identified as the most credible baseline scenario.

Based on the investment analysis (please see details in B.5), IRR of total investment of combination of baseline 1 (The proposed project activity not undertaken as a CDM project activity) is -0.42%, lower than the benchmark 8%, thus it is clearly not economically attractive and should be eliminated from the combination of baselines.

Outcome of STEP 3: the most credible baseline scenario is combination of baseline 2 “Continued operation of the existing boiler(s) using the same fuel mix as in the past (H2); the biomass residues are dumped or left to decay under mainly aerobic conditions. This applies, for example, to dumping and decay of biomass residues on fields (B1)”.

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 CDM project activity (assessment and demonstration of additionality): >> Evidence and main events on serious CDM consideration

CER sale revenues play a key role on investment decision of the Project. During the Feasibility Study Report preparation phase, the project owner seriously considered and analyzed CER sale revenues and entrusted the organization in charge of compiling the Feasibility Study Report to make an analysis on the impact of CER sale revenues on the Project.

Table 5. Outline of key events for CDM development of the Project Date Event

Nov., 2007 Impact of CER sale revenues on the Project was analyzed in compiling the Feasibility Study Report, which indicated that only with CER sale revenues would cause the Project be financially feasible. Dec., 2007 Heilongjiang Suibao Cogeneration Co. Ltd. made a board resolution on CDM development of the Project. May 9, 2008 Official approval was obtained from Economic & Trade Bureau of Acheng District Harbin City for the Feasibility Study Report of the Project.

May 14, 2008 Official approval was obtained from Environment Protection Agency of Heilongjiang Province for the Environment Impact Assessment of the Project.

May, 2008 Stakeholder comments on the CDM development of the Project were collected.

May 30, 2008 Construction of the Project began. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Demonstration and assessment of additionality

Identify whether the Project has additionality by using the latest Tool for the Demonstration and Assessment of Additionality (v05.2) approved by CDM EB.

Step 1. Identification of alternatives to the project activity consistent with current laws and regulations The objective of the Step 1 is to define realistic and credible alternatives to the project activity that can be (part of) the baseline scenario through the following sub-steps:

Sub-step 1a. Define alternatives to the project activity:

As per the methodology AM0036, define the possible alternative scenarios to the project activity. Please refer to STEP 1 and STEP 2 of B.4 for details of the alternatives. The combination of H2/B1 is defined as the baseline scenario of the Project, shown in the following table: Table 6. Baseline scenario of the Project Heat generation Use of biomass residues Continued operation of the existing boiler(s) using the The biomass residues are dumped or left to decay same fuel mix as in the past (H2) under mainly aerobic conditions (B1)

This scenario and the Project scenario constitute the combination of baseline alternatives of the project activity. Table 7. Combination of baseline alternatives of the Project

Alternative Heat generation Use of biomass residues

The proposed project activity not undertaken as a CDM H1 B7 project activity

Continued operation of the existing boiler(s) using the same H2 B1 fuel mix as in the past; The biomass residues are dumped or left to decay under mainly aerobic conditions.

Sub-step 1b. Consistency with mandatory laws and regulations: Alternative of combination of H1/B7 (The proposed project activity not undertaken as a CDM project activity) meets all the mandatory laws and regulations in China.

Alternative of combination of H2/B1 (Continued operation of the existing boiler(s) using the same fuel mix as in the past; the biomass residues are dumped or left to decay under mainly aerobic conditions) meets all the mandatory laws and regulations in China.

Step 2. Investment Analysis The purpose of investment analysis is to determine whether the Project, without the revenue from the sale of CERs, is economically or financially less attractive than at least one alternative identified in Step 1.

Investment analysis is conducted in the following sub-steps:

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Sub-step 2a. Determine appropriate analysis method Tools for the Demonstration and Assessment of Additionality suggests three analysis methods which are simple cost analysis (Option I), investment comparison analysis (Option II) and benchmark analysis (Option III). Since the alternative of the Project is continued operation of the existing boilers and requires no investment, benchmark analysis method (Option III) will be employed for the analysis according to Guidance on the Assessment of Investment Analysis (clause 14, annex 35 of EB39 meeting report).

Sub-step 2b. Benchmark Analysis Method (Option III) Core business of the project owner is central heating, as per the Economic Evaluation Method and Parameters for Construction Projects (version 03) issued by National Development and Reform Commission (NDRC) and Ministry of Construction (Now Ministry of Housing and Urban-Rural Development), it is determined that 8% is used as the benchmark project IRR of the Project., based on which calculation and comparison of financial indicators of sub-step 2c will be made.

Sub-step 2c. Calculation and comparison of financial indicators Basic parameters for calculation of financial indicators of the Project are shown as follows: Table 8 Basic parameters for calculation of financial indicators parameter Data unit value Source of data Total investment for retrofit RMB 10,000 2401 Annex of the Feasibility Study Report “Economic Analysis for Suibao’s Retrofit” Annual power generation MWh 107,960 Annex of the Feasibility Study Report “Economic Analysis for Suibao’s Retrofit” Annual heat generation TJ 1,945 Annex of the Feasibility Study Report “Economic Analysis for Suibao’s Retrofit” Possible subsidy (VAT Yuan 250 Tentative management measures for price and included) of electricity RMB/MWh sharing of expenses for electricity generation from supply after mixing biomass renewable energy(Document no. TJFGJG[2006]7) residues with coal for combustion Construction period Year 1 Annex of the Feasibility Study Report “Economic Analysis for Suibao’s Retrofit” Operation period Year 15 Annex of the Feasibility Study Report “Economic Analysis for Suibao’s Retrofit” Working staff newly person 60 Annex of the Feasibility Study Report “Economic recruited Analysis for Suibao’s Retrofit” Wage of the workers Yuan 24,000 Annex of the Feasibility Study Report “Economic RMB/year Analysis for Suibao’s Retrofit” Price of coal (net caloric Yuan 2,42 Annex of the Feasibility Study Report “Economic value of 16,308 MJ/t) RMB/ton Analysis for Suibao’s Retrofit” Price of rice straw (net Yuan 2,25 Annex of the Feasibility Study Report “Economic caloric value of 12,545 RMB/ton Analysis for Suibao’s Retrofit” MJ/t) Price of rice husk (net Yuan 2,40 Annex of the Feasibility Study Report “Economic caloric value 12,545 MJ/t) RMB/ton Analysis for Suibao’s Retrofit” Income tax rate 25% New tax law Rate of city maintenance 7% Feasibility Study Report P76 and construction tax Rate of education 3% Feasibility Study Report P76 supplementary tax PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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In accordance with the benchmark analysis (Option III), if the project IRR of the Project is lower than the benchmark, the Project is not considered financially attractive. Calculation based on the above data shows that without the revenue from CERs sales, the project IRR of the Project is -0.42%, lower than the benchmark of 8%. Therefore, the project activity is considered not financially attractive and not commercially feasible.

Calculated by 9 Euro/tCO2e with 10 years fixed crediting period, revenues from CERs sale can enhance the IRR of total investment of the Project to 54.72%, exceeding the benchmark of 8%. This shows that revenues from CERs sale can significantly improve the financial indicators, making the Project financially more competitive compared to the baseline scenario project.

Table 9. Comparison of IRR of total investment of the Project with and without CERs sales revenues Without CERs sales benchmark With CERs sales revenues revenues FIRR -0.42% 8% 54.72%

Sub-step 2d. Sensitivity analysis

For the Project, (1) the possible subsidy of electricity supply is strictly stipulated by Tentative management measures for price and sharing of expenses for electricity generation from renewable energy and the risk that can’t obtained the subsidy is very high5 , so, the subsidy of electricity supply is not considered in the sensitive analysis, this is conservative. (2) The heat price is strictly controlled by the local government6, and will not be increased due to the fuel switch from the coal to biomass, so, the heat price is excluded from the sensitive analysis.

The following financial parameters were taken as uncertain factors for the sensitivity analysis of financial attractiveness: Š Total static investment Š Price of biomass residues Š Price of coal Š Heat supply

Assuming the above 3 parameters fluctuated within a range of -10%~+10%, the corresponding impacts on the project IRRof the Project were analyzed. The results are shown in Table 9.

Table 9. Sensitivity analysis of different financial parameters of the Project (project IRR, without CER sales revenues) Range -10% 0 +10% Parameter Total static investment(%) 1.17 -0.42 -1.82

5 As per the measures, if the biomass accounts for less 80% of fuel consumption ( heat value basis), the RMB 250/Kwh of subsidy will be cancelled. 6 Regulations of urban heat supply in Heilongjiang(Document no. bulletin 24) http://www.hlraohe.gov.cn/Article.aspx?id=5153 PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Price of biomass residues(%) 17.75 -0.42 NA7 Price of coal(%) -31.76 -0.42 11.55

It can be seen that the project activity is very sensitive to the prices of biomass residues and coal, which is uncontrolled by the project owner, so, the project face high investment risks. Now, the husk price in Heilongjiang is between RMB 250/t and RMB 450/t8; the coal price currently is RMB 0.1315/MJ, much lower than RMB 0.1484/MJ of coal price in the FSR of the Project. So, the possibility of IRR deterioration is much higher than that of IRR improvement according the real situation, thus the additionality of the Project is robust.

Investment analysis shows that if undertaken not as a CDM project, the project activity is not financially attractive, thus the case that the project not undertaken as a CDM project is not the baseline scenario.

Step 4 Barrier analysis Not applicable

Step 4 Common practice analysis

Sub-step 4a. Analyze other activities similar to the proposed project activity:

There is currently no cogeneration project utilizing biomass residues in place of coal which has been put into operation and has not been developed as CDM project in China.

Sub-step 4b. Discuss any similar options that are occurring:

There is currently no cogeneration project utilizing biomass residues in place of coal which has been put into operation and has not been developed as CDM project in China, which can to a certain extent demonstrate that the Project has additionality.

B.6. Emission reductions: B.6.1. Explanation of methodological choices: >> The methodology AM0036 is applied in the project, this section includes the following sub-parts: ·Determine the baseline emissions;

·Determine the project emissions

·Leakage analysis;

·Calculate the emission reductions.

I. Determine the baseline emissions

Baseline emissions include CO2 emissions from fossil fuel combustion in the boilers in the absence of the project activity and, CH4 emissions from the treatment of biomass residues in the absence of the project activity:

7 Negative annual cash flow make the IRR unsolved 8 http://www.aptc.cn/news/Content.Asp?ID=58930 PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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BEyHGyBFy=+ BE,, BE (1) where:

BEy =Baseline emissions during the year y (tCO2e/yr);

BEHGy, =Baseline emissions from fossil fuel combustion for heat generation in the boiler(s)

(tCO2e/yr);

BEBF, y =Baseline emissions due to uncontrolled burning or decay of the biomass residues (tCO2e/yr); a) Baseline emissions from fossil fuel combustion in boiler(s) for heat generation

Baseline emissions from fossil fuel combustion in the boiler(s) are determined by multiplying the heat generated with fossil fuels that are displaced by biomass residues with the CO2 emission factor of the least carbon-intensive fossil fuels that would be used in the absence of the project activity and by dividing by the average net efficiency of heat generation in the boiler(s), as follows:

HGPJbiomassy,,× EF FFCO ,2, y BEHG, y = (2) ηboiler, FF where:

BEHGy, =Baseline emissions from fossil fuel combustion for heat generation in the boiler(s)

(tCO2e/yr);

HGPJbiomassy,, =Heat generated with incremental biomass residues used as a result of the project activity during the year y (GJ/yr);

EFFF,2, CO y =CO2 emission factor of the fossil fuel type displaced by biomass residues (tCO2e/GJ); η boiler, FF =Average net efficiency of heat generation in the boiler(s) when fired with fossil fuels.

For the purpose of determining EFFF,2, CO y as a conservative approach, the least carbon intensive fuel type (i.e. the fuel type with the lowest CO2 emission factor per GJ) should be used among the fossil types used in boilers at the project site during the most recent three years prior to the implementation of the project activity and the fossil fuel types used in boilers at the project site during the year y.

The determination of HGPJbiomassy,, depends on whether only fossil fuels would be used for heat generation in the absence of the project activity (case A) or whether along with fossil fuels some biomass residues also would be used in the absence of the project activity (case B).

The project is under case A as followed:

• No fossil fuel has been used for heat generation at the project site during the most recent three years prior to the implementation of the project activity; PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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• The most plausible baseline scenario is that heat would continue to be generated only with fossil fuels.

In case A, HGPJbiomassy,, corresponds to the total quantity of heat generated from firing biomass residues

( HGPJbiomassy,,= HGPJ,,, biomass total y ).

HGPJ,,, biomass total y is determined based on the fraction of biomass residues that are used for heat generation in the boiler(s), taking into account all biomass residue types k and fossil fuel types i fired in the project boilers during a year y, as follows:

∑ BFky, × NCV k k HGPJ,, biomass y=× HG PJ ,, total y (3) ∑∑BFky,,×+ NCV k FC iy × NCV i kk Where:

HGPJ,,, biomass total y = Total heat generated from firing biomass residues in all boilers at the project site during the year y (GJ/yr);

HGPJtotaly,, = Total heat generated in boilers at the project site, using both biomass residues and fossil fuels, during the year y (GJ/yr);

BFky, = Quantity of biomass residue type k fired in all boiler(s) at the project site during the year y (tons of dry matter or liter);

NCVk = Net calorific value of the biomass residue type k (GJ/ton of dry matter or GJ/liter);

FCiy, = Quantity of fossil fuel type i fired in all boiler(s) at the project site during the year y (mass or volume unit);

NCVi = Net calorific value of the fossil fuel type i (GJ/mass or volume unit). b) Baseline emissions due to uncontrolled burning or decay of the biomass residues

Baseline emissions( BEBF, y ) due to uncontrolled burning or decay of the biomass residue is determined as follow steps:

Step 1 Determination of the quantity of biomass residues used as a result of the project activity( BFPJky,, )

No biomass residue has been used for heat generation at the project site during the most recent three years prior to the implementation of the project activity and, the most plausible baseline scenario is that heat would continue to be generated only with fossil fuels, so that, for the total biomass residues type k used in the project plant, there is BFPJ ,k, y = BFk, y .

Step 2: Estimation of methane emissions, consistent with the baseline scenario for the use of biomass residues

In this project, the most likely baseline scenario for the use of the biomass residues is that the biomass residues would be dumped or left to decay under mainly aerobic conditions (B1). According to methodology AM0036, baseline emissions are calculated assuming, for both scenarios viz. natural decay and uncontrolled burning, that the biomass residues would be burnt in an uncontrolled manner.Baseline PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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emissions are calculated by multiplying the quantity of biomass residues that would not be used in the absence of the project activity with the net calorific value and an appropriate emission factor, as follows:

BEBF,4, y=⋅⋅⋅ GWP CH∑ BF k y NCV k EF burning ,4,, CH k y (4) k where:

BEBF, y =Baseline emissions due to natural decay or burning of anthropogenic sources of biomass

residues during the year y (tCO2e/yr);

GWPCH 4 =Global Warming Potential of methane valid for the commitment period (tCO2e/tCH4); NCV k =Net calorific value of the biomass residue type k (GJ/ton of dry matter);

EFburning,CH 4,k, y =CH4 emission factor for uncontrolled burning of the biomass residue type k during the year y (tCH4/GJ); k =Types of biomass residues for which the identified baseline scenario is B1 and for which leakage effects could be ruled out with one of the approaches L1, L2 L3 or L4 described in the leakage section.

Since it is difficult for the project owner to conduct regular measurement of the CH4 emission factor of biomass residues burnt in an uncontrolled manner ( EFburning,4,, CH k y ), the default value of 0.001971 t CH4/t for the product of NCVk and EFburningCH4, k , y from the methodology AM0036 is adopted in this case.

II. Determine the project emissions

According to methodology AM0036, Project emissions include CO2 emissions from on-site fossil fuel and electricity consumption that is attributable to the project activity ( PECO2, FF , y and PECO2, EC , y ), CO2 emissions from off-site transportation of biomass residues that are combusted in the boiler(s) to the project site ( PETR,2, CO y ), and, if included in the project boundary, CH4 emissions from combustion of biomass residues for heat generation ( PECH4, BF , y ): PE=+++⋅ PE PE PE GWP PE y CO2, FF , y CO 2, EC , y TR , CO 2, y CH 4 CH 4, BF , y (5)

Where

PEy = Project emissions during the year y (tCO2e/yr);

PECO2, FF , y = CO2 emissions from on-site fossil fuel combustion attributable to the project activity

(tCO2e/yr);

PECO2, EC , y = CO2 emissions from on-site electricity consumption attributable to the project activity

(tCO2e/yr);

PECO2, TR , y = CO2 emissions from off-site transportation of biomass residues to the project site

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GWPCH 4 = Global Warming Potential of methane valid for the commitment period (tCO2e/tCH4);

PECH4, BF , y = CH4 emissions from combustion of biomass residues in the boiler(s) (tCH4/yr).

Determine the project emissions as follows: a) CO2 emissions from on-site fossil fuel combustion ( PECO2, FF , y )

CO2 emissions from on-site fossil fuel combustion that is attributable to the project activity ( PECO2, FF , y ) are calculated by multiplying the fossil fuels consumption with appropriate net calorific values and CO2 emission factors, as follows:

PECO2, FF , y=××∑ FF on− site , i , y NCV i EF CO 2, FF , i (6) i

Where:

PECO2, FF , y = CO2 emissions from on-site fossil fuel combustion attributable to the project activity (tCO2e/yr);

FCon− site,, i y = Quantity of fossil fuel type i combusted at the project site for purposes other than heat generation as a result of the project activity during the year y (mass or volume unit);

NCV i = Net calorific value of the fossil fuel type i (GJ / mass or volume unit);

EFCO2, FF , i = CO2 emission factor for fossil fuel type i (tCO2e/GJ). b) CO2 emissions from on-site electricity consumption ( PECO2, EC , y )

CO2 emissions from on-site electricity consumption ( PECO2, EC , y ) are calculated by multiplying the electricity consumption by an appropriate grid emission factor, as follows:

PEEC,,, y=× EC PJ y EF grid y (7)

Where:

PECO2, EC , y = CO2 emissions from on-site electricity consumption attributable to the project activity (tCO2e/yr); EC PJ , y = On-site electricity consumption attributable to the project activity during the year y (MWh);

EFgrid, y = CO2 emission factor for electricity used from the grid (tCO2e/MWh). Use last version of approved “Tool to calculate the emission factor for an electricity system (01.1)” to calculate the grid emission factor. The calculation of EFgrid, y , the calculation process and the data were summarized in the annex 3 according to the tool and the Notification on 2008 Baseline Emission Factors for Regional Power Grids in China, issued by China on July 18,2008 (http://cdm.ccchina.gov.cn/web/ NewsInfo.asp?NewsId=3239) PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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c) CO2 emissions from transportation of biomass residues to the project site ( PECO2, TR , y ) In this case, transportation is undertaken by vehicles. According to methodology AM0036, project participants may choose between two different approaches to determine emissions( PECO2, TR , y ): an approach based on distance and vehicle type (Option 1) or on fuel consumption (Option 2). In this case, option 1 was chosen. option 1: Emissions are calculated on the basis of distance and the number of trips (or the average truck load):

PECO2, TR , y=⋅ N y AVD y ⋅ EF km , CO 2, y (8) or

∑ BFky, k PECO2, TR , y=⋅⋅ AVD y EF km , CO 2, y (9) TLy

Where:

PECO2, TR , y = CO2 emissions from off-site transportation of biomass residues to the project electric field

site (tCO2e/yr);

N y = Number of truck trips during the year y;

AVDy = Average round trip distance (from and to) between the biomass fuel supply sites and the site of the project electric field during the year y (km);

EFkm,CO2,y = Average CO2 emission factor for the trucks measured during the year y (tCO2e/km);

BFk,y = Quantity of biomass residue type k used for heat generation as a result of the project electric field activity during the year y (tons of dry matter or liter);

TLy = Average truck load of the trucks used (tons or liter);

d) CH4 emissions from combustion of biomass residues in the boiler(s) ( PECH4, BF , y )

In this case, the source has been included in the project boundary, emissions( PEBiomass,CH 4, y ) are calculated as follows:

PECH4, BF , y=⋅ EF CH 4, BF∑ BF PJ , k , y ⋅ NCV k (10) k

Where:

PECH4, BF , y = CH4 emissions from combustion of biomass residues in the boiler(s) during the year y

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EFCH 4,BF = CH4 emission factor for the combustion of the biomass residues in the project boiler

(tCH4/GJ);

BFPJky,, = Quantity of biomass residue type k used for heat generation as a result of the project activity during the year y (tons of dry matter or liter);

NCVk = Net calorific value of the biomass residue type k (GJ/ton of dry matter or GJ/liter).

III. Leakage analysis

According to methodology AM0036, Option L2 is adopted to demonstrate that the biomass residues used in the plant did not increase fossil fuel consumption elsewhere.

According to the Feasibility Study Report of the Project, the project consumes 166.54kt of rice straw and rice husk per year; the quantity of rice straw and rice husk within 30 km around the project site has reached 0.4 million tons. the quantity of available biomass residues in the region is at about 240% larger than the quantity of straw that are utilized, which satisfy the 25% floor level 9 required by the methodology AM0036. Therefore leakage effects do not need to be addressed according to methodology

AM0036, i.e. LEy = 0 tCO2e.

V.Calculate the emission reductions

Emission reductions are calculated as follows:

ERBEPELEyyyy=−− (11)

Where:

ERy = Emission reductions during the year y (tCO2e/yr);

BEy = Baseline emissions during the year y (tCO2e/yr);

PE y = Project emissions during the year y (tCO2e/yr);

LEy = Leakage emissions during the year y (tCO2e/yr). B.6.2. Data and parameters that are available at validation:

Data / Parameter: ηboiler, FF Data unit: - Description: Average net efficiency of heat generation in the boiler(s) when fired with fossil

9 According to methodology AM0036, project participants should demonstrate that there is an abundant surplus of the biomass residue in the region of the project activity which is not utilized. For this purpose, demonstrate that the quantity of available biomass residue of type k in the region is at least 25% larger than the quantity of biomass residues of type k that are utilized (e.g. for energy generation or as feedstock), including the project plant. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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fuels Source of data used: the highest value of manufacturer’s information on the efficiency among 4 boilers Value applied: 85% Justification of the The data obtained from manufacturer’s information on boilers, satisfying the choice of data or requirement of methodology AM0036. description of measurement methods and procedures actually applied : Any comment: the three most recent years for which data is available at the time of submission of the PDD to the DOE for validation

Data / Parameter: FCin,,1,2// FC in− FC in− Data unit: million tons of coal Description: Quantity of fossil fuel type i fired in all boiler(s) at the project site during the historical year 2005,2006,2007 Source of data used: On-site measurements Value applied: 14.98,15.06, 15.72 Justification of the Cross check with the energy balance sheet and the receipt of fuel purchase. choice of data or description of measurement methods and procedures actually applied : Any comment: the three most recent years for which data is available at the time of submission of the PDD to the DOE for validation

Data / Parameter: EFCO2, FF . i

Data unit: tCO2e/GJ Description: CO2 emission factor of fossil fuel type i for transportation and biomass residues disposal. Source of data used: 2006 IPCC National Greenhouse Gas Inventories Guide Value applied: 0.0946(coal),0.0741(diesel oil) Justification of the National specific default values are unavailable, so IPCC default values are choice of data or used, satisfying the AM0036 requirement description of measurement methods and procedures actually applied : Any comment:

Data / Parameter: - Data unit: MWh Description: Highest historical electricity generation at the project site during the most recent three years prior to the implementation of the project activity Source of data used: On-site measurements PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Value applied: 107,960 Justification of the - choice of data or description of measurement methods and procedures actually applied : Any comment: Required to assess the applicability condition referring to power generation at the project site.

Data / parameter: GWPCH 4

Data unit: tCO2e/tCH4 Description: Global warming potential for CH4 Source of data used: 2006 IPCC Guideline for National Greenhouse Gas Inventories Value applied: 21 Justification of the 21 for the first commitment period. choice of data or description of measurement methods and procedures actually applied : Any comment: -

Data / Parameter: NCVk ⋅ EFburningCH 4,k , y

Data unit: tCH4/ton of dry matter Description: CH4 emission factor of biomass residues burnt in an uncontrolled manner Source of data used: methodology AM0036 Value applied: 0.001971 Justification of the The data is obtained from the methodology AM0036 thus reliable. choice of data or description of measurement methods and procedures actually applied : Any comment: -

Data / Parameter: EFgrid, y

Data unit: tCO2e/MWh Description: CO2 emission factor for electricity used from the grid Source of data used: Notification on 2008 Baseline Emission Factors for Regional Power Grids in China, issued by China on July 18,2008(updated on Dec,30,2008) (http://cdm.ccchina.gov.cn) Value applied: 1.03145 Justification of the Notification on 2008 Baseline Emission Factors for Regional Power Grids in choice of data or China, issued by China on July 18,2008 (http://cdm.ccchina.gov.cn) is reliable description of data source. measurement methods PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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and procedures actually applied : Any comment: Determined ex ante

B.6.3 Ex-ante calculation of emission reductions: >> I. Estimated baseline emissions: a) Baseline emissions from fossil fuel combustion in boiler(s) for heat generation HG BF BF NCV NCV FC NCV Item PJtotaly,, ky, ky, k k iy, i (GJ/yr) (t-straw) (t-husk) (GJ/t straw) (GJ/t straw) (t) (GJ/t) I.D. A B C D E F G Data 1,945,000 104,090 62,450 12.545 12.545 41,630 16.308 Data source or FSR of the FSR of the FSR of the FSR of the FSR of the FSR of the FSR of the calculation Project Project Project Project Project Project Project formula

HG EF η BE Item PJ,, biomass y FF,2, CO y boiler, FF HGy, (GJ/yr) (tCO2e/GJ) (tCO2e/yr) I.D. H I J K Data 1,467,978.808 0.0946 85% 163,377.4061 Data source or H=A×(B×D+C×E)/ Nameplate of calculation IPCC D=A×B/C ((B×D+C×E)+(F×G)) boilers formula

b) Baseline emissions due to uncontrolled burning or decay of the biomass residues GWP NCV ⋅ EF BE Item CH 4 k burningCH 4,k, y BF, y (tCO2e/tCH4) (tCH4/t dry mass) (tCO2e/yr) I.D. L M N Data 21 0.001971 6,893.2571 Data source or IPCC AM0036 N=L×(B+C)×M calculation formula c)Baseline Emission

Item BEy (tCO2e/yr)) I.D. O Data 170,271 Data source or calculation formula O=M+N

II. Estimated the project emissions

a) CO2 emissions from on-site fossil fuel combustion ( PECO2, FF , y ) PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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The Quantity of fossil fuel type i combusted at the project site for purposes other than heat generation as a result of the project activity during the year y was assumed as 0 in the PDD, then FC NCV EF PE Item on− site,, i y i CO2, FF , i CO2, FF , y (t/yr) (GJ/t) (tCO2/GJ) (tCO2e/yr) I.D. P Q R S Data 0 16.098 0.0946 0 Data source or FSR of the 0 IPCC R =P×Q×R calculation Project formula

b) CO2 emissions from on-site electricity consumption ( PECO2, EC , y )

EFgrid, y Item ECPJ , y (MWh/yr) PEEC, y (tCO2e/yr) (tCO2e/MWh) I.D. T U V Data 18,968.87 1.03145 19,565.44 Data source or FSR of the Project China DNA V=T ×U calculation formula

c) CO2 emissions from transportation of biomass residues to the project site ( PECO2, TR , y )

TL AVD EF PE Item y y km,CO2 CO2, TR , y (t dry mass) (km) (tCO2e/km) (tCO2e/yr) I.D. W X10 Y Z Data 5 60 0.001011 2,020.4633 Data source or calculation formula FSR of the Project FSR of the Project IPCC Z=(H+I)/W×J×K

d) CH4 emissions from combustion of biomass residues in the boiler(s) ( PECH4, BF , y )

Item EFCH 4,BF (tCH4/GJ) PECH4, BF , y (tCO2e/yr) I.D. AA AB Data 4.11×10-5 1,803.2268 Data source or calculation formula AM0036 AB=AA×(B×D+C×E) ×L e) Project emissions

Item PE y (tCO2e/yr) I.D. AC Data 23,389 Data source or calculation formula AC=S+V+Z+AB

10 The maximum round distance has been employed in the PDD as a conservative proxy for the average round distance.

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IV. Estimated leakage

As analysed in Section B.6.1., leakage effects do not need to be addressed according to methodology

AM0036, i.e. Ly = 0 tCO2e.

V.Estimated emission reductions

Item LEy (tCO2e/yr) ERy (tCO2e/yr) I.D. AD AE Data 0 146,882 Data source or calculation formula AE=O-AC -AD

B.6.4 Summary of the ex-ante estimation of emission reductions: >> It is expected that the project activities will generate emission reductions for 1,468,820 tCO2e over a 10- year fixed crediting period from 1st. Jan, 2010 to 31st. Dec, 2019.

Estimation of Estimation of Estimation of Estimation of project activity baseline leakage overall emission Year emissions emissions (tonnes of reductions (tonnes of CO2e) (tonnes of CO2e) CO2e) (tonnes of CO2e) 2010 23,389 170,271 0 146,882 2011 23,389 170,271 0 146,882 2012 23,389 170,271 0 146,882 2013 23,389 170,271 0 146,882 2014 23,389 170,271 0 146,882 2015 23,389 170,271 0 146,882 2016 23,389 170,271 0 146,882 2017 23,389 170,271 0 146,882 2018 23,389 170,271 0 146,882 2019 23,389 170,271 0 146,882 Total 233,890 1,702,710 0 1,468,820 (tCO2e)

B.7 Application of the monitoring methodology and description of the monitoring plan:

B.7.1 Data and parameters monitored:

Data / Parameter: EFCO2, FF , y

Data unit: tCO2e/GJ Description: CO2 emission factor of the fossil fuel type displaced by biomass residues for the year y Source of data to be Data used in the PDD is obtained from IPCC default emission factors used: Value of data applied 0.0946 PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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for the purpose of calculating expected emission reductions in section B.5 Description of Review the appropriateness of the data annually. measurement methods and procedures to be applied: QA/QC procedures to Check consistency of measurements and local/national data with default values be applied: by the IPCC. Any comment:

Data / Parameter: HGPJtotaly,, Data unit: GJ/yr Description: Total heat generated in all boilers at the project site, firing both biomass residues and fossil fuels, during the year y Source of data to be Data used in the PDD is obtained from the Project owner of the Project. Actual used: data is to be obtained from continuously on-site measurements. Value of data applied 1,945,000 for the purpose of calculating expected emission reductions in section B.5 Description of Heat generation is determined as the difference of the enthalpy of the steam or measurement methods hot water generated by the boiler(s) minus the enthalpy of the feed-water, the and procedures to be boiler blow-down and any condensate return. The respective enthalpies should applied: be determined based on the mass (or volume) flows, the temperatures and, in case of superheated steam, the pressure. Steam tables or appropriate thermodynamic equations may be used to calculate the enthalpy as a function of temperature and pressure. QA/QC procedures to The consistency of metered net heat generation should be cross-checked with be applied: the quantity of biomass and/or fossil fuels fired (e.g. check whether the net heat generation divided by the quantity of fuel fired results in a reasonable thermal efficiency that is comparable to previous years). Any comment:

Data / Parameter: BFk, y Data unit: tons of dry matter Description: Quantity of biomass residue type k combusted in the project plant during the year y Source of data to be Data used in the PDD is obtained from the Feasibility Study Report of the used: Project. Actual data is to be obtained from on-site measurement. Value of data applied 104,090(straw), 62,450(husk) for the purpose of calculating expected emission reductions in PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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section B.5 Description of Continuously on-site measurements with weight meters and prepare annually measurement methods an energy balance. Adjust for the moisture content in order to determine the and procedures to be quantity of dry biomass. The quantity shall be crosschecked with the quantity applied: of electricity (and heat) generated and any fuel purchase receipts (if available). QA/QC procedures to Crosscheck the measurements with an annual energy balance that is based on be applied: purchased quantities and stock changes. Any comment: The quantity of biomass combusted should be collected separately for all types of biomass.

Data / Parameter: Moisture content of the biomass residues Data unit: % Description: Moisture content of the biomass residues type k combusted in the project plant during the year y. Source of data to be The data is assumed as zero for calculation in PDD. Actual data is to be used: obtained from on-site measurement. Value of data applied 0 for the purpose of calculating expected emission reductions in section B.5 Description of Continuously on-site measurements with mean values calculated at least measurement methods annually. and procedures to be applied: QA/QC procedures to - be applied: Any comment: -

Data / Parameter: FCiy, Data unit: Tons/yr Description: Quantity of fossil fuel type i fired in all boiler(s) at the project site during the year y Source of data to be Data used in the PDD is assumed as zero. Actual data is to be obtained from used: continuously on-site measurements. Value of data applied 41,630 for the purpose of calculating expected emission reductions in section B.5 Description of Continuously on-site measurements with weight meters and record monthly. measurement methods and procedures to be applied: QA/QC procedures to Cross-check the measurements with an annual energy balance that is based on be applied: purchased quantities and stock changes. Any comment: The quantity of fossil fuels combusted should be collected separately for all types of fossil fuels. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Data / Parameter: NCVi Data unit: GJ/t Description: Net calorific value of fossil fuel type i Source of data to be Data used in the PDD is form the FSR of the Project. Actual data is to be used: obtained from continuously on-site measurements. Value of data applied 16.308 for the purpose of calculating expected emission reductions in section B.5 Description of At least every six months, taking at least three samples for each measurement. measurement methods Measurements shall be carried out at reputed laboratories and according to and procedures to be relevant international standards applied: QA/QC procedures to Cross Checked using the NCV of fossil fuel type i provided by the fuel be applied: supplier. Any comment: -

Data / Parameter: NCVk Data unit: GJ/t Description: Net calorific value of biomass residues type k Source of data to be Data used in the PDD is form the FSR of the Project. Actual data is to be used: obtained from continuously on-site measurements. Value of data applied 12.545(straw),12.545(straw) for the purpose of calculating expected emission reductions in section B.5 Description of At least every six months, taking at least three samples for each measurement. measurement methods Measurements shall be carried out at reputed laboratories and according to and procedures to be relevant international standards. Measure the NCV based on dry biomass. applied: QA/QC procedures to Check the consistency of the measurements by comparing the measurement be applied: results with measurements from previous years, relevant data sources (e.g. values in the literature, values used in the national GHG inventory) and default values by the IPCC. If the measurement results differ significantly from previous measurements or other relevant data sources, conduct additional measurements. Ensure that the NCV is determined on the basis of dry biomass. Any comment: -

Data / Parameter: FCon− site,, i y Data unit: Tons/yr Description: Quantity of fossil fuel type i combusted at the project site for other purposes than heat generation as a result of project activity during the year y. Source of data to be Data used in the PDD is assumed as zero. Actual data is to be obtained from used: continuously on-site measurements. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Value of data applied 0 for the purpose of calculating expected emission reductions in section B.5 Description of on-site measurements with weight meters and record monthly. measurement methods and procedures to be applied: QA/QC procedures to be applied: Any comment: The value should not include fossil fuels co-fired in the boiler(s) but should include all other fossil fuel consumption at the project site that is attributable to the project activity, such as for on-site transportation or treatment of biomass residues.

Data / Parameter: AVDy Data unit: km Description: Average round trip distance (from and to) between biomass fuel supply sites and the project site Source of data to be Data used in the PDD is obtained from the Feasibility Study Report of the used: Project. Actual data is to be obtained from the Records by project participants on the origin of the biomass. Value of data applied 60 for the purpose of calculating expected emission reductions in section B.5 Description of Continuously record the origin of the biomass by project participants. measurement methods and procedures to be applied: QA/QC procedures to Check consistency of distance records provided by the truckers by comparing be applied: recorded distances with other information from other sources (e.g. maps). Any comment: If biomass is supplied from different sites, this parameter should correspond to the mean value of km traveled by trucks that supply the biomass plant.

Data / Parameter: EFkm,CO2,y

Data unit: tCO2/km Description: Average CO2 emission factor for the trucks during the year y Source of data to be Data used in the PDD is obtained from 2006 IPCC Guidelines for National used: Greenhouse Gas Inventories. Actual data is to be obtained from measurement. Value of data applied 0.001011 for the purpose of calculating expected emission reductions in section B.5 PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Description of Conduct sample measurements of the fuel type, fuel consumption and distance measurement methods traveled for all truck types. Calculate CO2 emissions from fuel consumption by and procedures to be multiplying with appropriate net calorific values and CO2 emission factors. For applied: net calorific values and CO2 emission factors, use reliable national default values or, if not available, (country-specific) IPCC default values. Measurement should be done at least annually QA/QC procedures to Cross-check measurement results with emission factors referred to in the be applied: literature from reputed researcher/institute. Any comment: -

Data / Parameter: ECPJ , y Data unit: MWh Description: On-site electricity consumption attributable to the project activity during the year y Source of data to be Data used in the PDD is obtained from The Feasibility Study Report of the used: Project. Actual data is obtained from measurement. Value of data applied 18,968.87 for the purpose of calculating expected emission reductions in section B.5 Description of Continuously on-site measurements with electricity meters, aggregated at least measurement methods annually. The quantity shall be cross-checked with electricity purchase receipts. and procedures to be applied: QA/QC procedures to Cross-check measurement results with invoices for purchased electricity if be applied: available. Any comment: -

Data / Parameter: EFCH 4,BF

Data unit: tCH4/GJ Description: CH4 emission factor for the combustion of biomass residues in the project plant Source of data to be Data used in the PDD is obtained from the methodology AM0036 of the used: Project. Actual data is obtained from measurement. Value of data applied 4.11×10-5 for the purpose of calculating expected emission reductions in section B.5 Description of The CH4 emission factor may be determined based on a stack gas analysis using measurement methods calibrated analyzers. At least quarterly, taking at least three samples per and procedures to be measurement. applied: QA/QC procedures to Check the consistency of the measurements by comparing the measurement be applied: results with measurements from previous years, relevant data sources (e.g. values in the literature, values used in the national GHG inventory) and default values by the IPCC. If the measurement results differ significantly from PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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previous measurements or other relevant data sources, conduct additional measurements. Any comment: -

Data / Parameter: - Data unit: Tons Description: Quantity of biomass residues of type k that are utilized (e.g. for energy generation or as feedstock) in the defined geographical region. Source of data to be Data used in the PDD is obtained from the Feasibility Study Report of the used: Project. Actual data is obtained from annually surveys or statistics. Value of data applied 400,000 for the purpose of calculating expected emission reductions in section B.5 Description of Annually surveys or statistics measurement methods and procedures to be applied: QA/QC procedures to - be applied: Any comment: -

B.7.2 Description of the monitoring plan:

Key contents of the monitoring plan for the Project include:

1. Management structure

Project owner

Person in charge of CDM In full charge of issues related to CDM, particularly communication with DNA, EB and DOE.

Other relevant department Production department Financial department Cooperate with CDM Meter calibration, QA/QC, Data verification (by means of monitoring staff with the data archiving and electricity sales receipts, fuel monitoring task in coordination management. purchase receipts and annual

with the person in charge of energy balance sheet and etc). CDM.

Statistician Monitoring and recording the data of electricity generation and auxiliary electricity consumption of the Project. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Figure 3. Management Structure of Monitoring Plan

2. Training Plan Prior to the submission of Project request for registration, the task of training staff in charge of executing the monitoring plan will be completed, with the training contents including basic concepts and operation modality of CDM, methods of data monitoring and archiving for CDM projects, quality control and quality assurance of monitoring, and preparation and improvement of key documents of monitoring and verification. Contents and requirements of the training plan should be supplemented, modified and improved according to DOE’s requirements, and training records should be provided for DOE’s validation.

3. Methods for monitoring Data and parameters required to be monitored will be monitored as per Section B.7.1, and reading records should be readily available for DOE verification.

According to Statistical method of energy balance in enterprises (GB/T16614-1996) and Methods of drawing up energy balance table in enterprises (GB/T16615-1996), ex post monitoring data should be employed to formulate the annual energy balance sheet of the Project.

4. Error disposal procedure Error disposal procedure will be implemented according to the stipulations in the Power Purchase Agreement, Parallel Operation Agreement, fuel purchase agreement, and so on.

5. Calibration of Meters & Metering All meters and instruments should be calibrated regularly as per industry practices. Calibration of Meters & Metering should be implemented according to national standards and rules. And all the records should be documented and maintained by the project owner for DOE’s verification.

6. Improvement of Quality Assurance and Quality Control The quality assurance and quality control procedures for recording, maintaining and archiving data shall be improved as part of this CDM project activity according to CDM EB rules and real practice in terms of the need for verification of the emission reductions on an annual basis according to this PDD.

7. Data Management System ·Specific staff will be appointed by the project owner to take the overall responsibility for monitoring greenhouse gas emission reductions and keeping all the data collected as part of monitoring archived electronically and be kept at least for 2 years after the end of the last crediting period. ·Electronic data and documents, including readings from electric meters connected into the computer central control system, will be regularly copied and archived via optical discs and storage tapes, and kept at least two years after the end of the crediting period. ·Written data and documents, including receipts for cross-checking of data, will be copied and archived with an explanation of the department or company where the original copy is kept, and kept at least two years after the end of the crediting period.

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It is expected that the verification of emission reductions generated from the Project will be done annually. Besides the data and documents required in Section B.7., other documents should be prepared by the project owner for verification include, but not limited to:

·PDD (registration version), including the electronic spreadsheets and supporting documentation (assumptions, estimations, measurement, etc); ·Monitoring Quality Control and Quality Assurance Report; ·The report on qualifications of the persons responsible for the monitoring and calculation. ·Record on maintenance and calibration of metering equipment; ·Project Management Record (including data collection and management system).

B.8 Date of completion of the application of the baseline study and monitoring methodology and the name of the responsible person(s)/entity(ies) >> The application of the baseline study and monitoring methodology of the Project was completed on 10/02/2009 by Dr. Zheng Zhaoning. Email:[email protected] The persons are not project participants listed in Annex 1.

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SECTION C. Duration of the project activity / crediting period

C.1 Duration of the project activity:

C.1.1. Starting date of the project activity: >> 30/05/2008 (construction start)

C.1.2. Expected operational lifetime of the project activity: >> 15y-0m

C.2 Choice of the crediting period and related information:

C.2.1. Renewable crediting period

C.2.1.1. Starting date of the first crediting period: >> Not applicable.

C.2.1.2. Length of the first crediting period: >> Not applicable.

C.2.2. Fixed crediting period:

C.2.2.1. Starting date: >> 01/01/2010

C.2.2.2. Length: >> 10y-0m

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SECTION D. Environmental impacts

D.1. Documentation on the analysis of the environmental impacts, including transboundary impacts: >> The Environmental Protection Agency of Heilongjiang Province gave an official reply to the EIA Report of the Project, approving the implementation of the Project (document No: HHH[2008]5) on May 4, 2008. According to the EIA Report, the environmental impacts arising from the Project are analyzed separately for the construction phase and the operation phase.

Construction Phase

The Project is a technical innovation one, so major work during the construction period is replacement and installation of equipment, which will have little impact on the environment. One straw storage space, one factory building for prilling rice straw, one barn for storing rice straw pellet, and two barns for rice husk need to be built by the Project in the plant area, since scale of the construction is small and period of construction is very short, and impact of construction will be entirely limited within the plant area, construction of the Project will not impact the environment of the surrounding area.

Operation Phase

Waste gas

Compared with the pre-project level, emission of SO2 will be reduced by 587.7 tons per year, and emission of smoke and dust will be 150.13 tons, thus the Project is conductive to the improvement of local environment. Waste gas emissions of the Project meet the requirement of Emission standard of air pollutants for thermal power plants (GB13223-2003) (period III), and the surrounding atmospheric environment satisfies the Standard II of Ambient air quality standard (GB3095-1996).

Noise

The project owner will take measures such as making proper layout, purchasing low-noise equipments, installing sound absorbing walls/sound insulating walls, increasing greening work in the plant area and so on, so as to mitigate impacts of noises on the working staff and surrounding area. Predicted values of noise within the plant area of the Project satisfy the requirements of type II standard of Standard of noise at boundary of industrial enterprises and operation of the Project will not have significantly negative impacts on the acoustic environment of the surrounding area.

Waste water

The amount of discharged waste water of the Project will be small. The principle of “separate the rain from the wastewater” will be followed for treating various types of waste water and for reutilizing them. Waste water discharged after treatment must satisfy the requirement of Integrated wastewater discharge standard (GB8978-1996).

Solid waste

Compared with the pre-project level, discharge of clinker will be reduced by 20,681 tons. Household garbage at the plant area of the Project will be collected at designated sites, and be regularly disposed by environment and sanitary services, thus will have little impact on the environment. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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In conclusion, construction and operation of the Project will not significantly impact the environment.

D.2. If environmental impacts are considered significant by the project participants or the host Party, please provide conclusions and all references to support documentation of an environmental impact assessment undertaken in accordance with the procedures as required by the host Party: >> Environmental impacts arising from this project are considered insignificant; therefore, it is not necessary to make additional explanation here. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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SECTION E. Stakeholders’ comments

E.1. Brief description how comments by local stakeholders have been invited and compiled: >> According to the area possibly affected by the Project, stakeholders identified for the Project include local government and residents living near the project site.

Given the approaches of receiving information from the stakeholders of the Project, in May of 2008, the project owner, by means of posting a public notice, invited local residents interested in the Project to answer the questionnaires of the Project. A total of 52 people received the questionnaires and return them with their responses. Related photographs, registration form and investigation are available for DOE checking. The questionnaires mainly focus on following issues: ·What’s the attitude of the stakeholders on the construction and operation of the Project? ·What positive impacts will be introduced by the implementation of the Project from the view of stakeholders? ·What negative impacts will be introduced by the implementation of the Project from the view of stakeholders? ·What measures should be applied to reduce the negative impacts from the view of stakeholders?

The project owner reported to the local government concerning the plan for CDM development of the Project, which obtained positive support from the local government. The local government issued a support letter for the Project, which is available for DOE validation.

E.2. Summary of the comments received: >> Totally 52 questionnaires returned out of 52 with 100% response rate. The basic structure of the respondents is shown in Table 11. Table 11. Structure of the respondents Structure of gender Structure of educational level Structure of age numbe Percentage Educational Percentage Percentage gender number age number r (%) level (%) (%) University 7 13.46 21~30 7 13.46 Junior college 14 26.92 31~40 35 67.31 Male 33 63.46 Senior high school and technical 23 44.23 41~50 8 15.38 secondary school Junior high Female 19 36.54 6 11.54 51~60 2 3.85 school Elementary 2 3.85 school

It can be seen that people surveyed are representative of the public in terms of gender, age and educational levels. Therefore their attitudes towards the Project can be a comprehensive reflection of the attitudes of the local residents possibly affected by the Project. A summary of the key findings based on 52 returned questionnaires is as follows:

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·23 people surveyed (accounting for 44.23%) have a clear understanding of the Project, 28 people surveyed (accounting for 52.85%) have some knowledge about the Project, and 1 person (accounting for 1.92%) does not know the Project. ·51 people surveyed (accounting for 98.08%) support the construction of the Project, 1 person surveyed (accounting for 1.92%) does not think the construction matters. ·People surveyed considered that positive impacts of the construction of the Project include reduction of atmospheric pollution resulting from coal combustion (78.85%), increase in farmers’ income (78.85%), reduction of pollution resulting from the straw being dumped or left to decay or burnt in an uncontrolled manner (71.15%), reduction in heat price (42.31%), and improvement in living/working environment (51.92%). ·People surveyed considered that negative impacts as a result of the Project construction include noises (36.54%), destruction of the local ecological environment (5.77%), and increase in the price of fuel (1.92%).

E.3. Report on how due account was taken of any comments received: >> Local people and the government at the project site are all very supportive of the implementation of the Project. For the concerns some respondents have about the negative impacts possibly caused by the Project, the project owner has given the following explanations:

(1) Noises of the Project will be controlled within the type II standard limit of Standard of noise at boundary of industrial enterprises and the project owner will further reduce noises by means of increasing greening work in the plant area; (2) All the biomass used by the Project are biomass residues which have not been utilized, thus they will not impact the ecological environment. (3) The Project utilizes biomass residues as the fuel, which can reduce demand for coal at the project site and is conducive to lowering the price of coal.

Based on the comments received from the stakeholders it is not necessary to make modifications to the Project.

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Annex 1

CONTACT INFORMATION ON PARTICIPANTS IN THE PROJECT ACTIVITY

Organization: Heilongjiang Suibao Cogeneration Co, ltd

Street/P.O.Box: Tongcheng Street No 1, Achen District

Building:

City: Harbin

State/Region: Heilongjiang

Postfix/ZIP: 150300

Country: P.R of China

Telephone: +86-451-53966301

FAX: +86-451-53966303

E-Mail:

URL:

Represented by: Xu guoqiang

Title:

Salutation:

Last Name: Xu

Middle Name:

First Name: Guoqiang

Department:

Mobile:

Direct FAX: +86-451-53966303

Direct tel: +86-451-53966301

Personal e-Mail: [email protected] PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Organization: Carbon Capital Management, Inc.(Japan)

Street/P.O.Box: Suenaga Takatu-ku

Building: 146-1-A

City: Kawasaki-shi

State/Region: ----

Postfix/ZIP: 213-0013

Country: Japan

Telephone: ----

FAX: +81-44-877-9517

E-Mail: ----

URL: ----

Represented by: Mr. Kaoru Inoue

Title: ----

Salutation: Mr.

Last Name: Inoue

Middle Name: ----

First Name: Kaoru

Department: ----

Mobile: ----

Direct FAX: ----

Direct tel: ----

Personal e-Mail: [email protected] PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Annex 2

INFORMATION REGARDING PUBLIC FUNDING

There is no public funding from Annex I Parties for this Project. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Annex 3

BASELINE INFORMATION

The combined margin CO2 emissions factor of the Grid( EFgrid,, CM y ) was calculated as per “Tool to calculate the emission factor for an electricity system” (Version 01.1), in the following six steps:

STEP 1. Identify the relevant electric power system In the absence of the project activity, the Northeast China Grid would provide equivalent electricity to the recipient. As per 2008 Baseline Emission Factors for Regional Power Grids in China published by China DNA on July 18, 2008(updated on Dec 30, 2008). The Northeast China Grid includes provincial grids of Liaoning, Jilin, Heilongjiang.

STEP 2. Select an operating margin (OM) method

The “Tool to calculate the emission factor for an electricity system” (Version 01) offers four options for 11 the calculation of the Operating Margin emission factor(s) ( EFgrid,, OM y ). Low-cost/must run resources constitute less than 50% 12of total amount of grid generating output from 2002 to 2006 in Northeast China grid, referred to 2008 Baseline Emission Factors for Regional Power Grids in China published by China DNA on July 18, 2008, Method (a) Simple OM was selected.

According to the methodological tool, following data vintages was selected:

Ex ante option: A 3-year generation weighted average, based on the most recent data available at the time of submission of the CDM-PDD for validation, without requirement to monitor and recalculate the emissions factor during the crediting period.

STEP 3. Calculate the operating margin emission factor according to the selected method

The simple OM emission factor is calculated as the generation-weighted average CO2 emissions per unit net electricity generation (tCO2e/MWh) of all generating power plants serving the Northeast China grid, not including low-cost/must-run power/units. The “Tool to calculate the emission factor for an electricity system”(Version 01) offers three options for the calculating of the Simple OM.

♦ Based on data on fuel consumption and net electricity generation of each power plant/unit (Option A), or ♦ Based on data on net electricity generation, the average efficiency of each power unit and the fuel type(s) used in each power unit (Option B), or ♦ Based on data on the total net electricity generation of all power plants serving the system and the fuel types and total fuel consumption of the project electricity system (Option C).

11 Low-cost/must-run resources are defined as power plants with low marginal generation costs or power plants that are dispatched independently of the daily or seasonal load of the grid. They typically include hydro, geothermal, wind, low-cost biomass, nuclear and solar generation. If coal is obviously used as must-run, it should also be included in this list, i.e. excluded from the set of plants. 12 5.44%, 4.72%, 6.24%, 8.05%, 5.25% from 2002 to 2006 respectively PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Option A should be preferred and must be used if fuel consumption data is available for each power plant/unit. As the fuel consumption data for each power plant/unit is not available in China, neither Option A nor Option B is reasonable. While total net electricity generation of all power plants serving the Northeast China grid and the fuel types and total fuel consumption of the Northeast China grid are available from China Electric Power Yearbook and China Energy Statistical Yearbook. So, the project uses Option C for calculating the simple OM emission factor as follows:

∑ FCiy,,2,,×× NCV iy EF COiy i EFgrid,, OMsimple y = (A1) EGy Where

EFgrid,, OMsimple y Simple operating margin CO2 emission factor in year y (tCO2e/MWh);

FCiy, Amount of fossil fuel type i consumed in the Northeast China grid in year y (mass or volume unit);

NCViy, Net calorific value (energy content) of fossil fuel type i in year y (GJ/mass or volume unit);

EFCO2, i , y CO2 emission factor of fossil fuel type i in year y (tCO2e/TJ);

EGy Net electricity generated and delivered to the grid by all power sources serving the Northeast China grid, not including low-cost/must-run power plants/units, in year y (MWh); i All fossil fuel types combusted in power sources in the Northeast China grid in year y; y the three most recent years for which data is available at the time of submission of the CDM-PDD to the DOE for validation (ex ante option).

EGyy= GEN×−(1 AER y ) (A2) Where:

GEN y electricity generated by all power sources serving the Northeast China grid, not including low- cost/must-run power plants/units, in year y (MWh);

AERy the average auxiliary electricity consumption rate(%) of all power sources serving the Northeast China grid, not including low-cost/must-run power plants/units, in year y.

Referred to 2008 Baseline Emission Factors for Regional Power Grids in China, the Simple operating margin CO2 emission factor( EFgrid,, OMsimple y ) of the Northeast China Grid is 1.2561 tCO2e/MWh.

STEP 4. Identify the cohort of power units to be included in the build margin

According to the methodological tool, the sample group of power units m included in the build margin consists of either: a) The set of five power units that have been built most recently, or b) The set of power capacity additions in the electricity system that comprise 20% of the system generation (in MWh) and that have been built most recently13.

Project participants should use the set of power units that comprises the larger annual generation.

As per the methodological tool, if group of power units, not registered as CDM project activity, identified

13 If 20% falls on part capacity of a plant, that plant is fully included in the calculation. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

CDM – Executive Board page 50 for estimating the build margin emission factor do not include power unit(s) that is(are) built more than 10 years ago, power plant registered as CDM project activities should be excluded from the sample group m.

However, under the current circumstance of China, the power plants take the Build Margin data as important business data and won’t let them published. Therefore, it is difficult to get the data of five power plants that have been put into operation most recently or the newly built power plant capacity additions in the electricity system that comprise 20% of the system generation. In allusion to the situation, CDM EB approves the following methodology deviation14: (1) Estimating power grid’s Build Margin Emission Factor according to the new increasing capacity in the past 1~3 years; (2) Substituting installed capacity with annual power generation to estimating weighted, and suggesting taking the most advanced commercial technology efficiency level of provincial/ regional/ national power grid as a kind of conservative approximation.

As per the methodology deviation, the sample group of power units m can ensure that not including any power unit(s) that is(are) built more than 10 years ago. So, the registered CDM projects in the Northeast China grid can be excluded from build margin calculation.

In terms of vintage of data, the methodological tool provides the following two options for the calculation of EFgrid,, BM y :

Option 1: For the first crediting period, calculate the build margin emission factor ex-ante based on the most recent information available on units already built for sample group m at the time of CDM-PDD submission to the DOE for validation submission of the request for renewal of the crediting period to the DOE. For the second crediting period, the build margin emission factor should be updated based on the most recent information available on units already built at the time of submission of the request for renewal of the crediting period to the DOE. For the third crediting period, the build margin emission factor calculated for the second crediting period should be used. This option does not require monitoring the emission factor during the crediting period.

Option 2: For the first crediting period, the build margin emission factor shall be updated annually, ex- post, including those units built up to the year of registration of the project activity or, if information up to the year of registration is not yet available, including those units built up to the latest year for which information is available. For the second crediting period, the build margin emissions factor shall be calculated ex-ante, as described in option 1 above. For the third crediting period, the build margin emission factor calculated for the second crediting period should be used.

Project participants have chosen Option 1, which requires the project participant to calculate the build margin emission factor EFgrid,, BM y ex-ante based on the most recent information available already built for sample group m at the time of PDD submission.

STEP 5. Calculate the build margin emission factor

14 EB guidance for “Request for guidance: Application of AM0005 and AMS-ID in China, 2005.10.7”: Request for clarification on use of approved methodology AM0005 for several projects in China. http://cdm.unfccc.int/Projects/Deviations PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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The build margin emissions factor is the generation-weighted average emission factor (tCO2e/MWh) of all power units m during the most recent year y for which power generation data is available, calculated as follows:

∑ EGmy,,, EF ELmy m EFgrid,, BM y = (A3) ∑ EGmy, m Where

EFgrid,, BM y Build margin CO2 emission factor in year y (tCO2e/MWh);

EGmy, Net quantity of electricity generated and delivered to the grid by power unit m in year y (MWh);

EFEL,, m y CO2 emission factor of power unit m in year y (tCO2e /MWh); m Power units included in the build margin; y Most recent historical year for which power generation data is available. As per the methodology deviation, China DNA published the BM calculation method as follow:

Because current statistics data can’t separate installed capacity of coal, oil and gas fueled power generation, the method adopted for BM calculation as follow: firstly make use of the latest energy balance data to calculate all sorts of emission scale in total emission from coal, oil and gas fueled power generation; then based on the emission factor under the business best technology, calculated the fueled power emission factor of the grid; last multiply the fuelled power emission factor and fuelled power proportion of the total power, it’s the BM of the grid. Detailed step and formula as follow:

Sub-step 1. Calculation of the share of CO2 emissions from solid, liquid and gaseous fuels

∑ Fijy,,×× NCV iy , EF COijy 2,,, iCOALj∈ , λCoal, y = (A4) ∑ FNCVEFijy,,×× iy , COijy 2,,, ij,

∑ FNCVEFijy,,×× iy , COijy 2,,, iOILj∈ , λOil, y = (A5) ∑ FNCVEFijy,,×× iy , COijy 2,,, ij,

∑ FNCVEFijy,,×× iy , COijy 2,,, iGASj∈ , λGas = (A6) ∑ FNCVEFijy,,×× iy , COijy 2,,, ij,

Fijy,, the consumption of fuel i in province j in year y(unit of mass or volume ); Coal, Oil and Gas is the foot-index for solid fuels, liquid fuels and gas fuels. Sub-step 2. Calculation of the emission factor of thermal power

EFThermal,, y= λ Coal y×+×+× EF Coal ,,,,,,,, Adv yλλ Oil y EF Oil Adv y Gas y EF Gas Adv y (A7) PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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EFCoal,, Adv y , EFOil,, Adv y and EFGas,, Adv y are emission factors of the best efficiency commercial coal-fired, oil-fired and gas-fired generation technologies. . Sub-step 3. Calculation of the BM in the Grid

Δ−CAPThermal,,, y CAP Thermal y CAP Thermal y− N EFgrid,, BM y=×= EF Thermal , y × EF Thermal , y (A8) Δ−CAPTotal,,, y CAP Total y CAP Total y− N

CAPTotal, y is the total installed capacity in the Northeast China grid in year y, CAPThermal, y is the total installed capacity of thermal power in the Northeast China grid in year y. N is the shortest vintage that the added installed capacity nearest to 20% of total installed capacity in the Northeast China grid.

Based on 2008 Baseline Emission Factors for Regional Power Grids in China published by China DNA, the Build Margin Emission Factor ( EFgrid,, BM y ) of the Northeast China Grid could be obtained to be:

0.6687 CO2e/MWh.

STEP 6. Calculate the combined margin emissions factor

The combined margin emissions factor is calculated as follows:

EFgrid,, CM y= EF grid ,, OM y×+ W OM EF grid ,, BM y × W BM (A9)

EFgrid,, CM y Build margin CO2 emission factor in year y (tCO2e/MWh);

WOM Weight of operating margin emissions factor (%); W BM Weight of build margin emissions factor (%).

According to the methodological tool, both the weight wOM and the weight wBM take 0.5 as default in the fixed crediting period. Therefore the combined baseline emission factor:

EFgrid,, CM y =×+×=1.2561 0.5 0.8068 0.5 1.03145 tCO2e/MWh PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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To determine the simple OM emission factor ( EFgrid,, OMsimple y ) and the Build Margin emission factor ( EFgrid,, BM y ) of the Project, data recommended in the 2008 Baseline Emission Factors for Regional Power Grids in China for the Northeast China Grid are adopted.

The following tables summarise the numerical results from the equations listed in the approved methodological tool-Tool to calculate the emission factor for an electricity system (version 01). The information provided by the tables includes data, data sources and the underlying calculations. The emission factors of OM and BM are calculated based on the Tool to calculate the emission factor for an electricity system. The information provided by the tables includes data, data sources and the underlying calculations. Table A1.Thermal Electricity generation of the Northeast China Grid from 2004 to 2006

year 2004 2005 2006 Province EG AER EDG EG AER EDG EG AER EDG (MWh) (%) (MWh) (MWh) (%) (MWh) (MWh) (%) (MWh) Liaoning 84543000 7.21 78447450 83697000 7.03 77813101 96282000 6.62 89,908,132 Jilin 33242000 7.68 30689014 35294000 6.59 32968125 38576000 6.78 35,960,547 Heilongjiang 53482000 7.84 49289011 58000000 7.96 53383200 62964000 7.85 58,021,326 Total 158425475 164164426 183,890,005 Data source: China Electric Power Yearbook 2005-2007 EG- Electricity generation, AER- Auxiliary electricity consumption Rate, EDG-Electricity delivered to the grid. . PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Table A2. Calculation of simple OM emission factor of the Northeast China Grid in 2004

Emission Oxidation Liaonin NCV Emission Jilin Heilongjiang Total fuel factor rate Energy Unit g (MJ/t,km3) (tCO e) (tc/TJ) (%) 2 A B C D=sum(A:C) E F G H15 Coal 104t 4144.2 2310.9 3084.8 9539.9 25.8 100 20908 188689377 Cleaned coal 104t 84.75 1.09 4.88 90.72 25.8 100 26344 2260872 Other washed coal 104t 577.67 14.26 61 652.93 25.8 100 8363 5165589 Coke 104t 0 29.2 100 28435 0 Coke oven gas 108m3 4.83 2.91 7.74 12.1 100 16726 574367 Other gas 108m3 57.33 4.19 61.52 12.1 100 5227 1426677 Crude oil 104t 0 20 100 41816 0 Gasoline 104t 18.9 100 43070 0 Diesel 104t 2.04 1.16 0.24 3.44 20.2 100 42652 108673 Fuel oil 104t 12.81 1.78 2.86 17.45 21.1 100 41816 564536 LPG 104t 2.19 2.19 17.2 100 46055 69305 Refinery gas 104t 9.79 1.14 10.93 15.7 100 46055 289780 Other oil products 104t 0.03 2.53 2.56 15.3 100 38931 559111 Other coke products 104t 0 15.3 100 38931 0 Natural gas 108m3 0 15.3 100 38931 0 Other energy 104tCe 26.97 5.07 32.04 0 100 0 0

Total emission of the Northeast China Grid (tCO2e) 199708287 Total electricity delivered to the Northeast China Grid (MWh) 158425475

Simple OM emission factor of the Northeast China Grid (tCO2e/MWh)) 1.260582

Data sources: China Energy Statistical Yearbook 2005. China Energy Statistical Yearbook 2007 2006 IPCC Guideline for National Greenhouse Gas Inventories, Volume 2

15 If the unit of the fuel is 104 t, then H=D×E×F×G×44/12/104; if the unit of the fuel is 108 m3, then H =D×E×F×G×44/12/103. . PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Table A3. Calculation of simple OM emission factor of the Northeast China Grid in 2005 Emission Oxidation Liaonin NCV Emission Jilin Heilongjiang Total fuel factor rate Energy Unit g (MJ/t,km3) (tCO e) (tc/TJ) (%) 2 A B C D=sum(A:C) E F G H9 Coal 104t 4305.41 2446.13 3383.21 10134.75 25.8 100 20908 200454896 Cleaned coal 104t 0 25.8 100 26344 0 Other washed coal 104t 524.74 19.26 24.16 568.16 25.8 100 8363 4494940 Coke 104t 0 29.2 100 28435 0 Coke oven gas 108m3 1.03 3.57 0.68 5.28 12.1 100 16726 391817 Other gas 108m3 12.62 8.37 20.99 12.1 100 5227 486768 Crude oil 104t 1.16 1.16 20 100 41816 35571 Gasoline 104t 0 18.9 100 43070 0 Diesel 104t 1.18 1.48 0.57 3.23 20.2 100 42652 102039 Fuel oil 104t 9.32 2.46 1.55 13.33 21.1 100 41816 431247 LPG 104t 0.12 0.12 17.2 100 46055 3798 Refinery gas 104t 5.48 1.32 6.8 15.7 100 46055 180284 Other oil products 104t 0.84 2.24 3.08 15.3 100 38931 672681 Other coke products 104t 0 15.3 100 38931 0 Natural gas 108m3 0 15.3 100 38931 0 Other energy 104tCe 16.18 16.18 0 100 0 0

Total emission of the Northeast China Grid (tCO2e) 207254040 Total electricity delivered to the Northeast China Grid (MWh) 164164426

simple OM emission factor of the Northeast China Grid (tCO2e/MWh)) 1.262478

Data sources: China Energy Statistical Yearbook 2006. China Energy Statistical Yearbook 2007 2006 IPCC Guideline for National Greenhouse Gas Inventories, Volume 2

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Table A4. Calculation of simple OM emission factor of the Northeast China Grid in 2006 Emission Oxidation Liaonin NCV Emission Jilin Heilongjiang Total fuel factor rate Energy Unit g (MJ/t,km3) (tCO e) (tc/TJ) (%) 2 A B C D=sum(A:C) E F H H9 Coal 104t 4681.99 2738.24 3698.29 11118.52 25.8 100 20908 219912851 Cleaned coal 104t 0.03 0.03 25.8 100 26344 748 Other washed coal 104t 674.74 17.83 96 788.57 25.8 100 8363 6238691 Coke 104t 3.32 3.32 29.2 100 28435 101075 Coke oven gas 108m3 2.68 0.16 1.44 4.28 12.1 100 16726 317609 Other gas 108m3 55.26 1.43 56.69 12.1 100 5227 1314667 Crude oil 104t 0.49 0.49 20 100 41816 15,026 Gasoline 104t 0 18.9 100 43070 0 Diesel 104t 0.75 0.39 0.3 1.44 20.2 100 42652 45491 Fuel oil 104t 11.73 0.45 1.44 13.62 21.1 100 41816 440629 LPG 104t 0 17.2 100 46055 0 Refinery gas 104t 8.55 4.27 12.82 15.7 100 46055 339888 Other oil products 104t 0.19 2.1 2.29 15.3 100 38931 500143 Other coke products 104t 0 15.3 100 38931 0 Natural gas 108m3 0 15.3 100 38931 0 Other energy 104tCe 12.16 17.6 82.77 112.53 0 100 0 0

Total emission of the Northeast China Grid (tCO2e) 229226818 Total electricity delivered to the Northeast China Grid (MWh) 183890005

Average OM emission factor of the Northeast China Grid (tCO2e/MWh)) 1.246543

Data sources: China Energy Statistical Yearbook 2007 2006 IPCC Guideline for National Greenhouse Gas Inventories, Volume 2

Calculated with the data provided in Table A1~Table A4, the OM emission factor of the Northeast China Grid is calculated as 1.2561 tCO2e/MWh

The following tables summarize the numerical results from the equations listed in 2008 Baseline Emission Factors for Regional Power Grids in China:

Sub-step 1: Calculation of the share of CO2 emissions from solid, liquid and gaseous fuels.

Calculated with the data provided in Table A4, λCoal, y =98.70%, λOil, y =0.22%, λGas, y =1.08%. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Sub-step 2: Calculation the emission factor of thermal power Calculated the emission factor of thermal power based on the emission factors of the best efficient and commercial coal-fired, oil-fired and gas-fired generation technologies as follow:

Table A5. CO2 emission factor for best efficient and commercially available thermal power technologies in China

Thermal Power Technologies variable Electricity supply efficiency Emission factor of fuel(tc/TJ) Oxidation Emission factor(tCO2e/MWh) A B C D=3.6/A/1000*B*C*44/12

Coal fired power plants EFCoal., Adv y 37.28% 25.8 1 0.9135

Gas fired power plants EFGas., Adv y 48.81% 15.3 1 0.4138

Oil fired power plants EFOil., Adv y 48.81% 21.1 1 0.5706 Data sources: Chinese DNA, http://cdm.ccchina.gov.cn/

Then

EFThermal,, y= λ Coal y×+×+× EF Coal ,,,,,,,, Adv yλλ Oil y EF Oil Adv y Gas y EF Gas Adv y =98.70%×0.9135+0.22 %×0.5706+1.08%×0.4138 =0.9074tCO2e/MWh Sub-step 3: Calculation BM in the grid.

Table A6. Installed capacity of the Northeast China Power Grid in 2006 Installed capacity Liaoning Jilin Heilongjiang Total 16721 7039 12456 36216 Thermal power (MW) 1401 3872 853 6126 Hydro power (MW) 00 00 Nuclear power (MW) 216 221 115 552 Wind power and Other (MW) 18338 11132 13424 42894 Total (MW) Data source: China Electric Power Yearbook 2007. PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03

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Table A7. Installed capacity of the Northeast China Power Grid in 2000 Installed capacity Liaoning Jilin Heilongjiang Total 13937.9 4924.7 10069.9 28932.5 Thermal power (MW) 1248.5 3536.7 814.8 5600 Hydro power (MW) 00 00 Nuclear power (MW) 43.9 0 0 43.9 Wind power and Other (MW) 15230.3 8461.4 10884.7 34576.4 Total (MW) Data source: China Electric Power Yearbook 2001.

Table A8. Installed capacity of the Northeast China Power Grid in 1999

Installed capacity Liaoning Jilin Heilongjiang Total 12425.7 4583.1 10128.1 27136.9 Thermal power (MW) 1240.0 3508.2 774.5 5522.7 Hydro power (MW) 00 00 Nuclear power (MW) 22.9 0 0 22.9 Wind power and Other (MW) 13688.6 8091.3 10902.6 32682.5 Total (MW) Data source: China Electric Power Yearbook 2000.

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Table A9. Calculation of BM emission factor of the Northeast China Power Grid Installed capacity Installed capacity Installed capacity Capacity additions Share in total

in 1999 in 2000 in 2006 from 1999 to 2006 capacity additions Unit MW MW MW MW A B C D=C-A

Thermal power 27136.9 28932.5 36216 9079.1 88.91%

Hydro power 5522.7 5600 6126 603.3 5.91%

Nuclear power 0 0 0 0 0.00%

Wind power and Other 22.9 43.9 552 529.1 5.18%

Total 32682.5 34576.4 42894 10211.5 100.00%

Share in total installed capacity of 2006 76.19% 80.61% 100%

EFgrid,, BM y = 0.9074× 88.91% =0. 8068 tCO2/MWh

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Annex 4

MONITORING INFORMATION

The calibration of meters & metering, the QA/QC procedure and others of the monitoring plan should be carried out with reference to the Heat Supply Agreement of the Project, fuel purchase agreement, Analysis Report on Component of Fuel and the checking and testing standard and the specification of the monitoring equipments. No other additional information.

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