PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1

PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1.

CDM Executive Board

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:

Project Title: “Pelita Agung Agrindustri Biomass Cogeneration Plant”

PDD Version: Version 1.1.0

Completion Date: 18/03/2008

A.2. Description of the project activity:

Pelita Agung Agrindustri (PAA) commenced construction of an integrated palm oil processing complex in early 2005. When

completed, the complex will consist of a palm oil mill, four lines of kernel crushing plants, one crude palm oil refinery unit, two

lines of transesterification (biodiesel), glycerine distillation, as well as a number of storage tanks (tank farms). By the time of

validation, only the mill and (one) kernel crushing plant are in operation with limited load pending to the completion of its

downstream facilities expected to be in mid 2008. At its full operation, the complex will have the capacity to process palm fresh

fruit bunches into various products including cooking oil, stearine, purified fatty acid distillate, bio-diesel, glycerine. The new

complex is located in the Province of Riau, on the Island of Sumatra, Indonesia.

In order to meet the high demand of steam and electricity, PAA implemented renewable energy initiatives covering construction

of (a) co-generation plant powered using biomass generated by its upstream milling activities and (b) biogas extraction project to

treat the complex‟ effluent, diverting from traditional method of relying on fossil fuel. Both projects are implemented with

assistance of CDM although applications are made on under separate PDD. This PDD covers only for the biomass co-generation

project (“the Project”).

The Project consists of three identical parallel trains of combined heat and power (CHP) units each consisting of a boiler and a

turbine. In total, the system will have the capacity to deliver up to 9.2Mwe (gross) of electricity, and 95MWth of steam meeting

almost1 all of PAA‟s complex energy requirements: 75tonnes per hour of low pressure steam, 15 tonnes per hour of medium

pressure steam, and up to 8.5MW to power the complex including its supporting facilities.

In addition to a drastic reduction of solid waste volume from its upstream processing unit (the palm oil mill), the Project provides

renewable steam and electricity for PAA energy-hungry downstream processing facilities which in other situation would have

been generated using fossil fuel. It is projected that at full operation more than half of the energy requirement would have been

self-generated, with the rest are powered using residues from other palm oil producer. Upon the Project completion, PAA facilities

including its offices and staff residents, would be powered by the Project and with no imports from national grid, enabling PAA

be produce fossil-free end-products.

Contribution to Sustainable Development

The Project supports sustainable development in the following ways:

∷ Elimination of oil-based captive power/steam generation typically employed by downstream processing facilities. By

utilizing biomass exclusively, the Project eliminates the need for PAA to generate fossil-based electricity/steam that would

consequently contribute to green-house-gas emission;

∷ Highly efficient operation. The integration of palm oil mill and its downstream processing facilities complemented with

renewable energy technologies increase the overall efficiency of energy consumption and green-house-gas emission per unit

of end-products.

The integration allows energy consumption to be drastically reduced by elimination of transportation of intermediate products

between facilities, such as: transportation of biomass residues from mill to power/heat generation plants, transmission loss,

transportation of CPO from mill to refinery & biodiesel plants.

1 Very high pressure steam for refining is met using methane extracted from the waste-water


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∷ Utilization of unused biomass. The Project consumes entirely all residue generated by the palm oil mill including its empty

fruit bunches, preventing it from emitting methane during its decomposition.

Without the Project, PAA can-not sufficiently meet its large energy demand using its available biomass, and thus must meet its

remaining demand using prevailing fuels.

A.3. Project participants:

Table 1 – Party(ies) Involved

Name of Party Involved Private and/or Public Entity(ies) Project Participants Kindly Indicate if the Party involved wishes to be

considered as Project Participant

Indonesia (host) PT Pelita Agung Agrindustri, Private Entities No

Japan Mitsubishi UFJ Securities Co., Ltd., Private Entities No

PT Pelita Agung Agrindustri (PAA) is wholly owned by PT Permata Hijau Group based in Medan, North Sumatra, Indonesia.

The group operates palm plantations, palm oil mills, refineries, bulk storage terminal, and recently entering bio-fuel industry with

inception of PAA.

Mitsubishi UFJ Securities Co., Ltd. is the CDM consultant of this Project.

A.4. Technical description of the project activity:

A.4.1. Location of the project activity:

A.4.1.1. Host Party(ies):

Indonesia

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

The Province of Riau

A.4.1.3. City/Town/Community etc:

Sebangar Hamlet, Mandau District, Town of Bengkalis

A.4.1.4. Detail of physical location, including information allowing the unique identification of

this project activity (maximum one page):

The Project is located within PAA palm processing complex. The Project geographical location is shown in the following figure.


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PAA is located on KM No. 26 (Simpang Bangko) of the main road connecting the City of Duri and the City of Dumai (Lintas

Duri Dumai) at 1° 25‟ 41.75”N and 101° 11‟ 21.29“ E.

A.4.2. Category(ies) of project activity:

The Project falls under:

Sectoral Scope I, Energy Industry; and

Sectoral Scope II, Waste Handling & Disposal

A.4.3. Technology to be employed by the project activity:

Project Equipment The Project involves the installation of three (3) identical parallel trains of combined heat and power (CHP)

units. The simplified process flow diagram of the units is illustrated in Figure 2 overleaf. Each train consists of a biomass boiler

connected sequentially to a steam turbine and a generator. The installed capacities and annual outputs of each boiler and turbine

are provided in the following Table 2.

Table 2 – Boiler and Turbine Installed Capacity and Output

Train Installed Capacity

Boiler Turbine/Generator

I 35MWth (40TPH) 3.2MWe

II 35MWth(40TPH) 3.2MWe

III 35MWth(40TPH) 2.8MWe

The boilers are manufactured by Vickers-Hoskins (M). Sdn. Bhd. with license from Babcock Energy Ltd. in United Kingdom.

The steam turbines and generators are manufactured by United States based Dresser-Rand and Newage AVK respectively.

The CHP system is equipped with (a) biomass treatment system to pre-treat the biomass and (b) reverse osmosis water treatment

plant to meet the system water demand.

Process Description The biomass boiler obtained energy from the combustion of biomass mixture consisting of palm kernel shell

(shell), mesocarp fibre (fibre) and treated empty fruit bunches (EFB) which has been pre-treated to ensure efficient combustion.

PROJECT

SITE

Figure 1 – Project Location in Riau Province, City of Bengkalis


CDM Executive Board Each boiler is capable to deliver 40tonnes per hour (TPH) of superheated steam at 32barg or 3,300kPaa and will be operated at

3,000kPa(a) with maximum outlet temperature of 320degC. About 10% of this steam are withdrawn as medium pressure steam for

heat exchange applications in the biodiesel and glycerine plant after pressure adjustment in a pressure reducing valve.

The remaining steam from biomass boiler are fed to the steam turbines, each is connected to a power generator. The steam turbine

expands the steam pressure from 3,000kPa to 300kPa driving the attached power generator to produce up to 9.2 MW of electricity.

The generated electricity is sufficient to meet all PAA production needs as well as office use, staff dormitory and lighting within

PAA complex, and thus eliminates the need to purchase electricity from the grid for domestic usages.

Low-pressure steam from the back pressure vessel is distributed to various areas including to pressure-cook the fresh fruit bunches

in the mill, direct usage in the kernel crushing, and glycerine distillation, and general heat exchange processes in all areas. Un-

used low pressure steam are recirculated. Only small portion of the water used for low pressure application can be recovered as

condensate, the rest must be treated in the anaerobic digesters in the waste-water treatment plants.

The biomass fuel feeding system includes pressing and shredding machines to treat EFB and automated using mechanical

conveyor belt system, requiring minimum operator intervention. Prior to feeding, the pressed/shredded EFB are in contact with

hot air from boiler‟s exhaust to adjust its moisture to acceptable level.

There is a future plan to add a new burner parallel to these boilers to recover heat from unused biogas obtained from the bio-

digester and thus reduces flaring. However, implementation of this plan is pending to confirmation that there is sizable excess

biomass2.

2 The biodigester has completed construction but not yet running at the time of PDD writing, pending to the completion of the refinery construction.


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Figure 2 - Simplified Process Flow Diagram of the Cogeneration System

Medium pressure

Steam users

Low pressure

Steam users

Pressur e Reducing

Valve

Back Pressure

Vessel

High Pressure

Steam Header

Feed Water

Tank

circulating water

Turbine

Generator

Turbine

Generator

Turbine

Generator

Biomass

boilers

Biomass

boilers

Biomass

boilers

Make-up water from

Reverse Osmosis

Biomass

Fuel mix

e lectricity


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The proposed power/heat generations represents a considerably more complex set of system than those typically practised by

Indonesian palm oil industry. Typically, palm oil mill and kernel crushing plant (referred hereafter as „upstream facilities‟) is

located in-land closer to palm plantation, whereas the refinery and other more complex chemical productions (referred hereafter as

„downstream facilities‟) are located closer to a maritime access.

With this Project, PAA attempts to take a more holistic approach in its production by combining the residue generating upstream

activity (palm oil mill) and the energy-intensive downstream processing. The Project therefore represents a link of delicate

balance between these two aspects of operations. Interruption in the palm oil mill, for example, influences the production of

biomass fuel and high pressure steam supply to refinery which relies on the biogas extracted from the mill‟s waste water. In order

to ensure success, PAA took caution in implementing this Project by providing buffer of biomass fuel and intermediate-products

to minimize impact.

The combustion of EFB is widely applied in Malaysia with the advent of CDM. However, Indonesia is slow in catching up and

PAA was the first EFB consuming project in Indonesia to apply for CDM assistance but application was delayed due to

unavailability of a suitable methodology.

A.4.4 Estimated amount of emission reductions over the chosen crediting period:

Table 3 – Estimated annual emission reduction over the chosen crediting period

Year Annual Estimation of Emission Reduction

in t-CO2/yr

1 149,686

2 157,229

3 164,512

4 171,545

5 178,336

6 184,893

7 191,225

8 197,339

9 203,242

10 208,943

Total estimated emission reduction (t-CO2/yr) 1,806,950

Total number of crediting years 10

Annual average over the crediting period of estimated reductions (t-CO2/yr) 180,695

A.4.5. Public funding of the project activity:

This Project does not receive any public funding in its financing.


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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:

The approved methodology applicable to this Project is ACM0006 Version 06 (EB33). The title of the methodology is:

“Consolidated Methodology Electricity Generation from Biomass Residue”

Other methodological tools used are:

“Tool to calculate project or leakage CO2 emissions from fossil fuel combustion” Version 01 (EB32)

“Combined tool to identify the baseline scenario and demonstrate additionality” Version 02.1 (EB28)

“Tool to determine methane emissions avoided from dumping waste at a solid waste disposal site” (EB35)

This PDD is completed in accordance with Guideline in Completing CDM-PDD and CDM-NM Version 06.2.

B.2 Justification of the choice of the methodology and why it is applicable to the project activity:

The Project is a cogeneration plant fuelled using biomass residue and is implemented as the utility facility of a new integrated

palm oil processing complex. The Project involves the installation of a new biomass residue power and heat generation plant

where previously no power and heat generation occurs (green-field project), thus meeting the general description of Project under

ACM0006.

The following assessment demonstrates that the Project is applicable to apply ACM0006:

The biomass residue used by the Project (palm kernel shell, mesocarp fibres, and empty fruit bunches) are the by-product,

residue or waste stream from agriculture related industries (palm oil mill) and does not include municipal wastes or other

wastes that contain fossilized or non-biodegradable material. Thus, the biomass residue used by the Project meets the

definition of biomass residue characterized in ACM0006;

The Project was designed to supply PAA complex, which itself is also a new facility with pre-defined capacity and demands.

Its implementation deemed not to increase the processing capacity of the raw input material of the palm oil mill other than the

pre-designated capacity.

The biomass residues used by the Project will not be stored for more than one year. Under normal circumstances, untreated

EFB is expected not to be stored and storage capacity for buffer shell is no more than a few months.

The dry biomasses: shell and fibre do not need additional energy for treatment as it is also used in the baseline. The wet

biomass (EFB) requires pressing, drying and mechanical shredding to reduce its moisture content and ensure smooth feeding

to the boiler. Drying is performed by subjecting the wet biomass to the exhaust of the boiler combustion chamber on a

moving conveyour belt, resulting in no significant increase of energy utilization. However, pressing and mechanical

shredding requires a sizable amount of electricity which is made possible by the co-generation system.

It is pertinent to note that the bio-diesel plant in PAA complex exclusively processes refinery products via esterification.

However, the product of esterification process will not be used as fuel to the Project plants.

It can then be deduced that apart from transportation and mechanical treatment, no significant energy quantity is required to

prepare the biomass residues (EFB, fibre, or shell) for fuel combustion.

It is demonstrated under Section B4, that the baseline Scenario of the Project meets the situation described in Scenario 20 of

Table 2 of ACM0006.

B.3. Description of the sources and gases included in the project boundary

Sources and gases included in the project boundary are summarized in Table 4.

The following sources are excluded:

1. Emissions from storage of biomass This emission source is excluded in the chosen methodology and deemed appropriate as

the storage period of biomass fuel is short.


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2. Pre-treatment of biomass As elaborated under applicability conditions (Section B2), EFB requires pre-treatment to reduce

its moisture content to ensure efficient boiler feeding. The process results in the generation of EFB liquor which is then

processed in a closed bio-digestion system where all methane are captured and used to replace fuel for one of the boiler in the

refinery. The drying is done through evaporation by subjecting shredded biomass on conveyor belt to hot air from boiler

immediately before feeding. Thus, it can be concluded that no additional emissions results from this pre-treatment system.

3. Electricity usages The entire PAA facility, including office & staff dormitory is not connected to external electricity grid.

Any electricity needed will be drawn from the project output – which is entirely generated from renewable energy. For plant

start-up or electricity consumption during project down-time, electricity will be drawn from back-up diesel gen-set, which

emissions are accounted as „on-site fossil fuel usage‟. Thus, electricity usage is not accounted as an isolated emission source

but rather as emission from combustion of on-site fossil fuel.

Table 4 – Sources and gases included in the project boundary

BASELINE SCENARIO ACTIVITY

Source Gas Details

Electricity generation CO2 CO2 emissions from the consumption of diesel oil to generate electricity in the power generator.

Heat generation CO2 CO2 emissions from the combustion of residue oil in the baseline fossil fuel boiler to supplement

energy unable to be met by biomass utilization alone

Decay of biomass CH4 CH4 emissions from the decay of landfilled EFB

PROJECT ACTIVITY

Source Gas Details

Onsite fossil fuel usage CO2 CO2 emissions from on-site utilization of fossil fuel including for electricity generation attributable to the

Project, ie. to start-up project equipments (as defined in Section A.4.3). This does not cover fuel

consumption by the stand-by gensets to generate electricity for the offices, process users, during

project down-time. Co-firing is unforeseen, but included as parameter to be monitored.

Offsite transportation of

biomass residue

CO2 CO2 emission from the transportation of biomass imported to PAA complex.

The remaining biomass is self-generated on-site and movement is done using conveyor belt system

consuming electricity from the project.

Combustion of biomass

residue for Project activity

CH4 CH4 emission in the stack gas of the biomass boiler combustion chambers

Spatial project boundary The spatial extent of the project boundary encompasses the cogeneration plants at the project site, the

means of biomass transportation, the site where preparation and storage of biomass occurs and the site where the biomass would

have been left to decay. With consideration that PAA does not have electrical connection for import or export of electricity, the

project boundary does not include power plants in the public grid.


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B.4. Description of how the baseline scenario is identified and description of the identified baseline scenario:

The following section determines the most likely alternative to the Project and embodied Step 1 (identification of alternative) of

the „Combined tool to determine baseline scenario and demonstrate additionality‟. Subsequent steps of the tool (demonstration of

additionality) are described in Section B.5.

STEP 1 – Identification of alternative Scenarios

Step 1(a) – Define alternative scenarios to the proposed CDM project activity

As prescribed in Section II of the applied methodology, baseline identification process should assess how power and heat

would have been generated, and how the biomass would have been handled in the absence of the Project.

Determination of baseline scenarios for biomass handling

As required by the methodology, the application of Step 1 must take into account the following alternatives into

consideration during baseline determination:

Table 5 – Biomass Baseline Scenarios to be considered as per ACM0006

Scenario Description

B1 The biomass residues are dumped or left to decay under mainly aerobic condition. This applies, for example, to

dumping and decay of biomass residues on fields.

B2 The biomass residues are dumped or left to decay under clearly anaerobic conditions. This applies, for example, to

deep landfills with more than 5m.

B3 The biomass residues are burnt in an uncontrolled manner without utilizing it for energy purposes.

B4 The biomass residues are used for heat and/or electricity generation at the project site.

B5 The biomass residues are used for power generation, including cogeneration, in other existing or new grid-connected

power plants.

B6 The biomass residues are used for heat generation in other existing or new boilers at other sites.

B7 The biomass residues are used for other energy purposes, such as the generation of biofuels

B8 The biomass residues are used for non-energy purposes, e.g. fertilizer or as feedstock in the processes.

As required by the baseline methodology, the baseline analysis of the biomass residues is identified for each type of

biomass. Biomass residue from different sources is considered as different type of biomass residue. The classification

and utilization of biomass in this Project and results of its assessment is summarized in the following table. The

assessment process is described in the next few paragraphs.

Table 6 - Biomass Classification, Projected Utilization, and Baseline Scenarios Considered

Biomass

Type

Description and Note Projected annual consumption Baseline Scenario Evaluation

Tonnes/yr TJ/yr Considered Concluded

K1 Onsite generated, meso-carp fibre 46,230 428 B4, B5, B6 B4

K2 Onsite generated, palm kernel shell 31,050 488 B4,B5,B6 B4

K3 Imported, palm kernel shell used in

both the baseline and project situation

3,126 49 B4,B5,B6 B4


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K4 Imported, palm kernel shell used only

in the project situation

77,229 1,214 B4,B5,B6 B4

K5 Onsite generated, empty fruit bunches

from PAA mills

93,150(untreated) or

64,860 (treated)

549 B1, B2, B3, B8 B2

Note: The term ‘on-site’ referred to biomass generated by PAA palm oil mill, as oppose to biomass ‘imported’ from other mills outside

PAA.

Biomass K1 : mesocarp fibre from PAA

Mesocarp fibre represents the most widely used biomass energy source in the palm oil industry, consequently:

(a) Scenarios involving biomass being dumped (B1, B2) or burnt in uncontrolled manner (B3) are excluded;

(b) Scenarios involving the use of this biomass for other energy purpose such as bio-fuels(B7) or non-energy purposes

such as fertilizer (B8) are non-existent, and thus excluded.

(c) Scenarios involving utilization of fibre as energy source in the baseline [B4, B5, and B6] are credible alternative and

considered for further evaluation.

However, with consideration of PAA large energy demand, it is unlikely that PAA would sell this biomass to other

parties for power/heat generation as described in Scenario B5 and B6. It is likely that this biomass is used by PAA itself

as energy source – as with any other palm oil mill, and thus baseline Scenario B4 is the most credible baseline scenario

for Biomass K1.

Biomass K2 ,K3,and K4 : palm kernel shell

The utilization of kernel shell for palm oil players differs from operator to operator. Traditional palm oil mill which

needs little electricity can meet its energy demand by combustion of fibre, and small amount of shell using low-

efficiency simple co-generation technology. The remaining shells are used for non energy purpose such as plantation-

road reinforcement to reduce slip during wet season, and therefore left to decay aerobically.

Less commonly, minority players operate a kernel crushing facility (like PAA) which requires more electricity than a

mill3. For this type of operator, the kernel shell plays an important energy source to generate steam and electricity which

is typically done by increasing the capacity of the low pressure co-generation system. As such, for palm kernel shell:

(a) Scenarios involving biomass being dumped (B1, B2) or burnt in uncontrolled manner (B3) are excluded;

(b) Scenarios involving the use of this biomass for other energy purpose such as bio-fuels(B7) or non-energy purposes

such as fertilizer (B8) are non-existent, and thus excluded.

(c) Scenarios involving utilization as energy source in the baseline [B4, B5, and B6] are credible alternative and

considered for further evaluation.

Biomass K2, ,on-site palm kernel shell. With consideration that PAA energy demands is higher than typical industry

practice due to its large downstream processing activities; it is unlikely that biomass K2 is sold to other parties for energy

purpose (B5 and B6). Thus, scenario B4 is the only credible alternative for this type of biomass.

Biomass K3, and K4 , shell from other mills. PAA purchased shell from traditional millers who utilized fibre for its

operation and shell partially, and left excess shell unused and decay aerobically (B1). Such millers however is expected

to be aware of shell economic value in future and sold this biomass to industries in need of large energy source like PAA

(B5 and B6). Thus, in all likelihood, biomass K3 and K4 will be used as energy source whether at PAA site (B4), or other

industrial sites (B5 and B6).

At the time of decision making, the utilization of shell for energy purpose outside the upstream palm oil mill & kernel

crushing was not a common practise but becoming more common with the advent of CDM. In terms of calculation of

baseline emission, the use of biomass at any sites (PAA or other industrial site), for whichever purposes (heat or

3 The ratio of kernel crushing facility is about 1:11, 1 kernel crushing plant with typical size of 600TPD services about 10mills with average capacity of 45TPH. However, even for such players, there are still considerable amount of excess shell available.


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electricity) has little influence in determining the baseline emission. As such, for all intent and purposes, this biomass is

considered to have baseline B4.

Biomass K5, empty fruit bunches from PAA mills. The utilization of EFB as energy source was not a common practise

before the advent of CDM. When the project proponent decided to explore this project in 2004, there was no palm oil

mill in Indonesia to implement large scale EFB boilers with or without CDM. Until today, only two EFB power plants in

Indonesia are applying for CDM. Both are not yet registered at the time of PDD writing and are non-cogeneration type.

Others, prefer to use EFB as material for composting with assistance of CDM.

EFB is not commonly used in palm mill power plants for a number of reasons: (a) the pre-treatment process is energy

and capital intensive and (b) a typical non-integrated stand-alone mill hardly needs electricity, and the necessary steam

can be supplied from fibre combustion alone.

For the Project, PAA installed four EFB treatment process with total electrical consumption of 536kWh or nearly 40% of

the electricity needed by the mill itself. Thus, it is clear that without any sufficient and economical electrical output,

utilization of EFB as fuel is not an attractive option. In addition to this, the cost of these treatment plant itself is not

insignificant thus further hindering its utilization as energy source.

As indicated in Table 6, EFB contributes to only 20% of the total fuel mix on energy basis despite the additional capital

requires for treatment plants and considerably large electrical requirement for pre-treating the material. These factors

deem that usage of EFB as fuel is prohibitive whenever system with lower efficiency is employed. Consequently,

alternatives involving the utilization of EFB as energy source (Scenario B4, B5,and B6) are excluded from further

consideration in the baseline.

A number of technical papers cited the potential use of EFB as: (1) potential feedstock for refused derived fuel (Scenario

B7); (2) potential feedstock for pulp and paper industry (Scenario B8); and (3) feedstock for composting (Scenario B8).

Currently, the first two situations are still in research and development and non-existent in Indonesia, and thus both are

excluded from further consideration. However, Scenario 3 is a credible option and will be further assessed.

With the exclusion of some scenarios above, the remaining credible scenarios are scenarios involving the disposal of

EFB (Scenario B1, B2, B3), and scenario involving the use of EFB for composting (B8) and discuss in the following

paragraphs:

A. Scenario B1, biomass disposal in mainly aerobic condition. The disposal of empty fruit bunches in mainly aerobic

condition is associated with the use of the material for mulching. For PAA, this does not provide a long-term

solution to its requirement to manage empty fruit bunch for the following reasons:

(1) Costs incurred for material movement PAA is not bordered by its own plantation, and which means the

use of untreated empty fruit bunch as mulch will incur significant costs for material movement (labour and

transportation). It is unlikely that independent farmers who operate the plantation surrounding PAA facility

compensate for delivery of untreated EFB.

(2) Short-term application The application of mulch is intended to reduce water evaporation due to harsh

tropical climate for new plant or during re-planting. After the tree matures, the tree canopy and its dry leaves can

sufficiently fulfil this function. With a life-cycle of 20 years, the demand for mulch is not continuous and no

longer required as soon as the tree reaches its productive stage and evaporation is sufficiently prevented by its

own canopy.

B. Scenario B8, EFB is used for composting (non-energy purpose). Using EFB as composting has been cited as one of

the most potential eco-friendly way of handling EFB. However, its application remains unimplemented in the region

as it requires not insignificant investment. As such, the use of EFB as composting is only feasible with assistance of

CDM as has been evidence with the numerous CDM applications of composting activities in the region. As PAA

operates a relatively large industrial complex, production of compost is not in-line with its core activity and thus less

likely to be considered as an option.

C. Scenario B3, the biomass residue is burnt for non energy purpose. With no other potential usages, PAA facility and

others surrounding the region are equipped with incinerator to destroy the EFB when unconsumed. This incinerator

is simple incinerator with high stack, but no combustion control.The existing incineration in PAA was set up as


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temporary measure to destroy EFB generated by the mill before the cogeneration plant is fully operational, and will

be decomissioned after the Project is fully operational.

Under the current environmental regulations, the application of incineration is not prevented as long as it meets the

required ambient air quality governed under the ministrial decree for stationary combustion. The applied standard for

combustion of biomass requires the control of the following emissions: particulate matters, sulfur dioxide, nitrogen

oxides, hydrogen chloride, chlorine, ammonia, hydrogen fluoride, and opacity. It does not control the methane

emission from combustion.

However, many environmental agencies voiced concerns over the use of incineration for the handling of waste due

to fear of the formation of dioxin and furan. As consequence, the continuation of such practise may no longer be

compliance with law in not-too-distant future, as with the case with other countries in the region which banned

incineration by law. Consequently, the only long-term solution within law for PAA is to construct a landfill to

contain its 93,000t per year of EFB.

D. Scenario B4, the biomass residue is managed in a sanitary landfill. If the use of existing incineration is prohibited by

law then the only viable option of managing EFB is the construction of a landfill within vicinity of PAA to avoid

transportation/labour costs. This solution is a feasible option as land is available and economical in the area where

PAA is located and away from residential area. In order to avoid complain from surrounding neighbour, the

constructed landfill must be implemented with sanitary standard, where waste must be compacted, covered, with the

collected leachate treated in PAA waste water treatment facility. However, with consideration of the unstable

emission profile and the size of this private landfill, it is unlikely that methane collection facility is implemented

without CDM.

Based on this long-term view, the most plausible baseline scenario for handling EFB is the construction of a managed

landfill (B2). The baseline emission is calculated using multiphase model as described in the „Tool to determine methane

emissions avoided from dumping waste at a solid waste disposal site‟. The choice of parameters and justifications are

explained in Table 10 and Table 11 of this document in Section B6 (p. 26).

Determination of baseline scenario for power and heat

As stipulated in the methodology, baseline scenarios must be determined for both power and heat by considering

scenarios described in the following table.

Description Description

P1 The proposed project activity not undertaken as a CDM

project activity

H1 The proposed project activity not undertaken as a CDM

project activity

P2 The continuation of power generation in an existing biomass

residue fired powered plat at the project site, in the same

configuration, without retrofitting and fired the same type of

biomass residues as co-fired in the project activity

H2 The proposed project activity (installation of a cogeneration

power plant), fired with the same type of biomass residues

byt with a different efficiency of heat generation.

P3 The generation of power in an existing captive power plant

using only fossil fuel.

H3 The generation of heat in an existing captive cogeneration

plant, using only fossil fuel.

P4 The generation of power in the grid H4 The generation of heat in boilers using the same type of

biomass residues

P5 The installation of a new biomass residue fired power plant,

fired with the same type and with the same annual amount of

biomass residues as the project activity, but with a lower

efficiency of electricity generation than the project plant and

H5 The continuation of heat generation in an existing biomass

residue fired cogeneration plant at the project site, in the

same configuration, without retrofitting and fired with the

same type of biomass residues as in the project activity.


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therefore with a lower output than the project case.

P6 The installation of a new biomass residue fired power plant

that is fired with the same type, but higher annual amount of

biomass residues as the project activity and that has a lower

efficiency of electricity generation than the project activity.

Therefore, the power output is the same as the project case.

H6 The generation of heat in boilers using fossil fuel

P7 The retrofitting of an existing biomass residue fired power

plant, that is fired using the same amount of biomass

residues as the project activity, but with a lower efficiency of

electricity generation than the project plant, and therefore

with a lower output than the project case

H7 The use of heat from external sources, such as district heat.

P8 The retrofitting of an existing biomass residue fired power

plant, that is fired using the same type, but higher annual

amount of biomass residues as the project activity, and that

has a lower efficiency of electrical generation than the

project plant.

H8 Other heat generation technologies (eg. Heat pumps or

solar energy).

P9 The installation of new fossil fuel fired captive power plant at

the project site

As the Project is a green-field project where no power or heat is generated previously, any scenarios involving

continuation or retrofitting of existing equipment (P2, P3, P7, P8, H3 and H5) can be immediately excluded.

Scenario involving grid electricity import (P4) can also be excluded as Sumatra electricity grid does not have enough

capacity to supply electricity to a large industry with sufficient reliability at the time of project inception. The prevalent

practise in Sumatra for industry is on-site (captive) generation of electricity. This is evident from reports issued by the

state electricity company, PT PLN and the Directorate General for Electricity and Energy Utilization in 2005 suggesting

that less than 10% of total electricity sold in 2004 in Sumatra is purchased by industry4. The grid situation may change in

the future with many new (coal) power plants are added. However, it will not change the baseline situation, as

commitment to proceed with the Project was made in 2004.

The scenario involving the use of heat from external sources (H7) is also immediately excluded as at the time of PDD

writing PAA is not bordered with other industrial facilities that can procure or supplied excess heat. There are also no

utility company operating within proximity of the Project. With consideration of PAA relatively significant demand,

reliance on heat generation technologies such as heat pumps and solar energy are not a practical option. Thus, Scenario

H8 is also excluded.

Scenarios involving the installation of new biomass power plants (P5/P6) are considered as plausible scenarios. As

elaborated earlier (under biomass handling), the use of fibre is common in a typical stand-alone-mill and shell is used to a

lesser degree. As shown in Table 6, on-site shell (K2) and fibre(K1) can potentially supply the Project with 916TJ of

energy annually without additional transportation or material cost. Thus, these biomasses are considered as the primary

energy source in PAA.

It will be demonstrated in Annex 3, that biomass alone can-not meet the large steam and electricity needs of the complex,

and thus the baseline is likely to be combination of biomass and fossil fuel, either co-fired or in distributed system. Thus,

combination of Scenario H4 and H6 is treated as one option for the purpose of baseline identification assessment.

4 “Rencana Umum Kelistrikan Nasional” or “General Plan for National Electricity”, Directorate General for Electricity and Energy Utilization (DJLPE), Department of Energy and Mineral Resources, April 2005


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From the above eliminations, the remaining credible scenarios are: P1, P5, P6, P9 for power and H1, H2, H4, H6 for

heat.

Outcome of Step 1a

With non-relevant baseline scenarios are eliminated in the above assessment, the remaining possible combination of

baseline scenarios is summarized in the following table and described in paragraphs underneath as outcome to Step 1a.

Table 7 – Remaining combinations of credible baseline scenarios

Heat H1

Project without CDM

H2

Cogeneration

H4/H6

(Heat generation using biomass and fossil fuel) Power

P1 (Project without CDM) Scenario A × ×

P5 (Cogeneration) × Scenario B ×

P6 (Cogeneration) × Scenario C ×

P9 (Captive power generation) × × Scenario D

Scenario A - Installation of a cogeneration plant with same efficiency as the Project

The Project is carried out without CDM

Scenario B - Installation of a cogeneration plant with lower efficiency using the same amount of biomass as the Project

In this Scenario, power and heat are generated simultaneously using co-generation system which is prevalent in

palm oil industry, low pressure and low efficiency using the same amount of biomass as the Project. The lower

efficiency, however, creates a shortfall of output in comparison to the Project and thus must be compensated

with the adoption of fossil fuel technology to meet the remaining demand.

As the use of EFB in lower efficiency system is prohibitive, only biomass K1, K2, K3, and K4 is used.

Scenario C - Installation of a cogeneration plant with lower efficiency using more biomass as the Project

In this Scenario, power and heat are generated simultaneously using co-generation system which is prevalent in

palm oil industry, lower pressure and lower efficiency. In order to compensate the lower efficiency, the boiler is

designed to combust more biomass to recover more energy.

As the use of EFB in lower efficiency system is prohibitive, the plant is fuelled with biomass K1, K2, K3, and

higher amount of K4.

Scenario D – Separate generation of electricity and heat

Steam Demand for Upstream Processes (Mill and Kernel Crushing Plant). The steam demands for upstream

operations are supplied exclusively using biomass (K1, K2, K3).

Unlike an integrated industry, an independent palm oil mill consumes 100% of its fibre and 2% of its shell for

its thermal and electricity requirement. Greater amount of electricity is needed by minority player who owns and

run kernel crushing facility5.

PAA plans to operate greater than normal kernel crushing facility (almost double the typical capacity).

Combined with the mill, the thermal demand of these facilities is 42TPH of low pressure steam, and if generated

5 In the case of PAA (which operates one of the largest mill size), the mill itself can supply only 69t per day of kernel, which is very small compared to PAA designated 4x275tpd or 1100t per day of installed kernel processing capacity


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using biomass boiler with 70% efficiency6, consumes the entire self generated fibre (K1) and shell (K2) with

additional 3,126t/yr of more shell needed to be imported to PAA (K3).

Steam Demand for Downstream Processes (Refinery, Biodiesel, Glycerine Distillation, and Tank Farms)

The combined steam demand of these areas are 32.7TPH of low pressure steam (3bar(g)), and 15TPH of

medium pressure steam (15bar(g)). As stated at earlier section, the common practice is to have these

downstream processes near to a maritime port for ease of distribution away from the upstream processes. In

such case, these processes typically consumes non-biomass fuel.

With highest pressure demand of only 15 bar, the use of cogeneration will not be able to provide sufficient

electricity needed which is in the order of 7.9MW. A simple calculation shows that such system can only

provide less than 6% of the total electricity needed7 and thus is ruled out as possible alternative. Consequently, it

is more likely that the steam requires by the downstream processing facility is generated as per its original

design of the process, supplied by boilers distributed in the individual demand. With consideration of lack of

natural gas pipeline, such boilers is likely to be operated using either residue oil or coal which are considered

more economical than diesel oil. However, the use of coal in distributed boilers system are unlikely due to

impractical fuel feeding system. Based on observation of other operations, it is likely that these boilers would

have been fuelled using residue oil which are more expensive but practical.

Electricity Demand for the Entire Facility With all of its self-generated biomass is concentrated for the use of

steam production in its upstream facility, and the possibility of cogeneration for the downstream steam usage is

ruled out, PAA has only one remaining option: to install a captive power plant to supply its electricity.

The most economical course of option is to install coal power plant due to its economic advantage and access to

fuel8. This is evident by moves initiated by the Indonesian government to reduce consumption of diesel oil as

Indonesia is heading toward a net-oil importing country due to lack of investment in oil exploration. However,

for sake of conservativeness, the baseline is assumed to be diesel oil power plant9.

In all of the above scenarios, biomass K5 (EFB) are not included as energy source and hence landfilled.

Substep 1b Consistency with mandatory applicable laws and regulation

All of the above Scenario A to D are in compliance with applicable legal and regulatory requirement in the host-nation,

including national policy.

Outcome of Step 1b.

Scenario A to D remains as credible alternatives to the Project.

STEP 2 – Barrier Analysis

Substep 2a – Identify barriers that would prevent the implementation of alternative Scenario

This section identify the list of barrier that prevents the implementation of Scenario A-D as described in Step 1

Barrier1 – Relative complexity & practicality of implementation. The alternative is less likely to be executed

than the Project if it represents a less practical option in terms of operation, control and reliability.

6 Maximum efficiency of biomass boiler as cited in Council of Industrial Boiler white paper: “Energy Efficiency & Industrial Boiler Efficiency:

an Industry Perspective” which cited New Biomass Boiler efficiency is in the range of 60% to 70%.

7 The incremental specific enthalpy between medium pressure (2,821 MJ/t) and low pressure steam (2,750 MJ/t) is only 71MJ/t. Thus for

turbine with 97% energy recovery efficiency and the low-pressure steam flowrate of 32.7TPH, the recoverable electricity is 451.4kW or only 5.3% of total electricity demand.

8 Sumatra is the largest coal producing region in Indonesia, and one of the leading coal supplier in Asia Pacific.

9 It is pertinent to note that this decision have several consequences in the barrier analysis, namely that a diesel power plant is more hefty in

operating costs but lower in capital costs compared to a coal power plant. However, the cost-effectiveness of a coal power plant is evident by the apparent proliferation of such technologies in Indonesia.


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Barrier 2 – Less financially attractive than the Project. The alternative is less likely to be executed than the

Project if it represents a less financially feasible option than the Project.

Sub-step 2b – Eliminate alternative Scenarios which are prevented by the identified barriers

Scenario A. This scenario represents the same technological advances as the Project and thus is not prevented by the

barriers identified in Sub-step 2a. Consequently, it remains as credible alternative to the Project.

Scenario B. This scenario represents a biomass co-generation technology with similar arrangement as the project

(boiler+steam turbine+generator) using lower efficiency, consuming the same amount of biomass as the Project (K1 to

K4). It is likely that such low-efficiency system is a result of combination of lower operating pressure, less efficient

boiler/furnace and low intake pressure, less efficient steam turbine than the Project.

The lower overall efficiency means that the boiler generates lower quality of steam in a quantity less than those

that can be supplied by the Project boiler, and subsequently reduces the quantity of recoverable electricity in the

steam turbine. In order to meet end-users demands, installation of such biomass co-generation plant requires

additional investment for the provision of remaining of electricity and steam. The option of adding more burning

more biomass is considered in Scenario C and thus not considered here. As electricity becomes less scarce the

utilization of EFB becomes less likely, and the fuel requirement must be met with import of fossil fuel.

At best, it is likely that this lower efficiency cogeneration and the additional capital investment to meet the

remaining steam/elecricity results in a similar investment cost as the Project. On the other hand, its operating

costs is significantly higher as more fossil fuel are needed to meet the shortfall.

An alternative of similar investment compared to the Project with higher running costs to procure fossil fuel,

represents a less sophisticated and financially less attractive alternative than the Project (Barrier 2). Thus, less

likely to be implemented than the Project.

Scenario C. This scenario represents a biomass co-generation technology with similar arrangement as the project

(boiler+steam-turbine+generator) using lower efficiency. In order to compensate the lower efficiency, more biomass is

burnt in this boiler than the Project situation.

In this scenario, more biomass is burnt to par the electricity/steam output as the Project. The additional biomass

needed to compensate the lower efficiency does not only translate to additional operating costs, but also a bigger

furnace chamber to accomodate combustion of more biomass, and bigger heat exchange surface area to transfer

the same quantity of thermal energy. Subsequently, the turbine must be able to handle lower pressure and more

volume of steam, with the constraint of low recovery efficiency.

The overall lower efficiency system will result in oversize system design that is harder to control with demands

and does not represent good engineering practice (Barrier 1). In order to compensate lack of operability, the

system must be splitted into many smaller systems (more than the Project) and thus elevates capital costs

without additional benefit. Taking into account the additional biomass that must be procured, this is a less

economically attractive option than the Project (Barrier 2).

Note for Scenario B and C: Lower efficiency cogeneration would be a more suitable option to PAA, if the mill

has been implemented independently (a few years before) the rest of the processing facility. In such case, the

mill is served by a typical lower efficiency cogeneration plant, and new utility are added with the

implementation of the downstream processing facility.

In the case of PAA, the mill and the rest of downstream operations are implemented as greenfield project based

on a long-term planning to create an integrated industry. As such, the planning of energy provision takes into

account the total electricity and heat demand of all downstream facilities.


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Scenario D. In this scenario, each individual process units (upstream and downstream facilities) are served by individual

smaller utility system that responds to individual demands.

This option represents an alternative which is easy to control to changing demand and economical as each utility

is designed to meet individual needs or a smaller group of processing plant. In addition to this, exact

quality/quantity of steam can be generated within vicinity of the demand, eliminating the need to compensate

heat loss due to pipeline condensation compared to cogeneration situation including the Project.

In the original design, individual processes of the downstream facilities would have individual utility system

supplying medium pressure and low pressure steam directly to the needing areas. The biodiesel plant for

example, would have installed four small residue oil boilers at different pressure level supplying steam for

glycerine distillation, bleaching, transesterification as well as general heat exchange processes. Similarly the

tank farms, the refineries, and the kernel crushing facility would have had its own, low pressure boilers, whereas

the mill can be powered using its own fibre and shell. Thus, this option is not prevented from implementation by

Barrier 1.

However, without the centralized steam generation system employed by the Project, it is not possible to generate

electricity in-house as by-product of steam generation. Consequently electricity must be provided by way of

captive diesel oil power generators, which is the prevalent practice10

.

It will be demonstrated in Section B.5 that this Scenario is not prevented for implementation by Barrier 2, and is

a more financially attractive option than the Project without CDM (Scenario A).

Outcome of Sub-step 2b

The above evaluation shows that Scenario A and D are the only scenarios that are not prevented for implementation by

both Barrier 1 and 2.

Conclusion to Assessment of Alternatives (Step 1 and 2)

It is demonstrated above that from point of view of large heat demands and electricity required by PAA, the remaining credible

alternative to the Projects are:

Scenario A – the Project is carried out without CDM; and

Scenario D – where (a) electricity is generated using diesel oil generator(s), (b) low pressure steam for upstream facilites

are generated exclusively using biomass, (c) steam for the downstream facilities are generated using residue oil. (c) with

exception of EFB, biomass K1 (on-site fibre), K2 (on-site shell) and K3 (imported shell used in the baseline) are used in

this facility. EFB will continue to be unused for non-energy purpose and landfilled.

Step 2b stipulates that „if there are several alternative scenarios remaining, including the proposed project activity undertaken

without CDM, proceed to Step 3 (Investment analysis)‟. It will be demonstrated using investment analysis in Section B.5, that

Scenario A is less financially attractive than Scenario D concluding that Scenario D is the only credible baseline for the Project.

This scenario falls under the description of Scenario 20 of ACM0006 where;

‘the project activity involves the installation of a new biomass residue fired cogeneration plant at a site where no power

was generated prior to the implementation of the project activity. The project plant is a captive cogeneration plant that

provides electricity and heat to captive users at the project site. In the absence of project activity, a new fossil fuel fired

captive power plant would be installed at the project site instead of the project plant.

The biomass residue would in the absence of project activity be (a) partly be used for heat generation in project site and

(b) partly be dumped or left to decay or burnt in uncontrolled manner without utilizing them for energy purposes.

The heat generated by the project plant would in the absence of project activity be generated using on-site boilers using

(a) the same biomass residues as fired in the project plant, and where applicable (b) partly using fossil fuels’

10 The diesel oil power generators is selected for conservativeness basis for purpose of emission reduction calculation. In practise, coal power plant would have been the most plausible baseline plant


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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):

As prescribed in the methodology, the demonstration of Project‟s additionality is done in compliance with the „Combined tool to

identify baseline scenario and demonstrate additionality‟ Version 02.1 (EB28). Step 1 and Step 2 analysis has been carried out

under Section B.4, and concludes that two scenarios, Scenario A and Scenario D remain credible options. The tool prescribed that

in the case where there are more than one credible scenarios, the baseline is to be determined by which of the two option is the

most economically attractive and thus the most likely to be implemented. Thus, a comparative financial analysis is performed on

the two options to determine its relative financial performance.

Step 3 – Investment Analysis

General Approach of this Investment Analysis The Project capital investment value (Scenario A) is significantly more

expensive than its alternative (Scenario D), which is a simpler but equally reliable processes. From investment point of view, the

incremental capital to carry out Scenario A is justified if it provides investment return in the form of operational saving that meets

an acceptable benchmark. For purpose of demonstrating additionality, the investment comparison analysis is performed by

analyzing the net present value (NPV) of this committed incremental costs , using the following general approach:

Step A. To establish the basic parameters for the investment analysis.

Step B. To analyze the incremental capital investment of the two options;

Step C. To analyze the resulting operational savings gained from making the additional investment;

Step D. To establish the cash-flow of the additional investment, the resulting operational savings, and the additional tax

that must be paid (C) and analyze the net-present-value.

Benchmark selection The selected financial parameter that is deemed suitable is Net Present Value (NPV). The discounting

factor is constructed based on the applicable working capital loan interest rate applicable in first three semester of 2004 which is

13.86%11

, with additional 3% premium deem suitable to cover for risk of implementation due to project relative complexity and

longer than normal construction time.

Interpretation of financial parameter The calculated NPV from this incremental analysis (Step E) represents the NPV of the

Project relative to the NPV of its alternative. A positive NPV thus suggest that the Project Investment is more attractive than the

alternative. A negative NPV does not necessarily means that the Project is not profitable, but a less financially attractive option

compared to its alternative.

Step A Basic Parameters for the Investment Analysis. The basic assumptions used in the investment analysis as well as its

justification are summarized in the following table. For consistencies, all prices used excludes value added tax. With exception of

currency exchange, all of these assumptions have strong impact to the operational savings and thus included as parameter in the

sensitivity analysis.

Table 8 – Basic Parameters Adopted for Investment Analysis

Assumptions Value Assumed Rationale

Currency Exchange IDR 9,159 per USD The value is based on the average mid-rate currency exchange

between USD and Rupiah rate as published by the Bank of Indonesia

for period of 6 months leading to September 2004.

Cost of imported shell,

applicable to both

Scenario A and Scenario

D.

IDR 198,375 per tonnes of shell.

Projected shell imports amounts to 80,355t

per year.

On-site shell usage is not included in this

A study performed in February 2004 indicates costs of shell of

IDR150,000 per tonnes when imported within 200km radius. More

than 50% of this is contributed to cost of material movement.

The project developer projected that the price of shell will increase at

11 Based on information published by Bank of Indonesia for working capital loan for average of 6 months leading to September 2004


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analysis as it will be consumed on both

situations and thus has no impact to

operational saving.

a rate of at least 15% per annum as (a) PAA own consumptions and

demand from other industries will create a market for shell (b) as it is

a labour/transport intensive activities, the price will be influenced by

the country inflation. As such it is appropriate that by the time the

project is at its full operation, the price of biomass has increased

significantly.

Costs of water treatment

system, applicable in both

Scenario A and D

IDR5,953 per tonnes of water

Expected water consumption is 120TPH for

the Project and 97TPH for Scenario A.

PAA used reverse osmosis process to treat its water so that it is

suitable for use for the boiler. The costs of water treatment as

calculated by the supplier including cost of chemical and maintenance

is USD0.65 or IDR5,953 at the assumed exchange rate.

Costs of residue oil for

steam production,

applicable only to

Scenario D.

IDR1,455 per L with density of 0.988kg per

Liter. Calculated consumption is 19,177t/yr

Cost of residue oil is based on PERTAMINA 12 published rate

for’minyak bakar’ for industrial used for 200413. Density of residue oil

is based on information from PERTAMINA.

The expected consumption of residue oil is calculated based on 100%

recovery efficiency of a residue boiler as required for baseline

calculation.

Costs of diesel oil for

electricity production,

applicable only in

Scenario D.

IDR1,864 per L, with electrical fuel

consumption rate of 0.202L per kWh

Expected electrical output is

54,951,600MWh per year. This electrical

output is calculated on net basis based on

the demand of individual processes and net

of electricity to run the project plant).

Cost of residue oil is based on PERTAMINA published rate for’minyak

bakar’ for industrial used for 2004. Density of residue oil is based on

information from PERTAMINA.

The consumption rate of the diesel gen-set is based on fuel

specification of a suitable gen-set provided by a manufacturer to be

0.1865kg/L.

Applicable tax rate 30% of profit (after excluding asset

depreciation)

Based on documents issued by the tax office. Tax rate is progressive,

but due to size, it is reasonable to assume the rate to be flat.

Step B. Incremental Capital Investment Analysis The total project investment values as identified in its feasibility analysis is

IDR168,573million which is significantly higher than its alternative. The breakdown of capital investment is provided in the

enclosed spreadsheet published with this PDD. The summary is provided in the following table.

Table 9 – Comparison of the Investment Values between Scenario A (Project) and its alternative (Scenario D)

Aspect Values in Rupiah

Scenario A Scenario D Increment (Δ)

Equipment Costs IDR 165,077,781,000 IDR 37,433,094,947 IDR 127,644,686,053

Working Capital & Other Costs (2 months) IDR 3,492,317,799 IDR 9,109,783,204 IDR -5,617,465,405

Total Capital Investment Value IDR 168,570,095,799 IDR 46,542,878,151 IDR 122,027,217,648

It is shown above that the commitment to proceed with the project requires an additional capital investment of

IDR122,027million. On the equipment value basis, the incremental investment on asset is identified to be IDR127,027million per

year. From this information, the annual incremental depreciation can be calculated to calculate the impact of the incremental

investment to tax on profit.

12 PERTAMINA: State oil and gas company, the only fuel supplier in Indonesia in 2004

13 Fuel in Indonesia was partially subsidised


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Step C. Incremental Operating costs

Based on the parameters established in Step A, the projected operating costs for both scenarios are calculated below:

Project Installation Project Alternative

Operation Cost to purchase shell (K3): 3,126t IDR 620,121,671 IDR 620,121,671

Cost to purchase shell (K4): 77,229t IDR 15,320,337,979 IDR -

Cost to process water (6,900hr) IDR 4,929,194,400 IDR 3,984,432,140

Costs of fuel

Residue oil IDR - IDR 28,232,037,997

Diesel oil IDR - IDR 21,753,334,510

Maintenance

14

Biomass Boilers IDR 68,772,906 IDR 68,772,906

Turbine IDR 15,461,838 IDR -

Residue Boiler IDR - IDR -

Total Operational & Maintenance (O&M) Costs IDR 20,974,910,495 IDR 54,658,699,224

Incremental O& M (Operational Savings from Project Investment) IDR 33,704,810,430

Step D. Analysis of Cash Flow

With an incremental capital commitment of IDR122,027million, and an operational saving of IDR33,705million, the net present

value of the resulting cash flow is calculated to be –IDR52,165million. As explained earlier, this calculated NPV represents the

NPV of the Project (Scenario A) relative to its alternative (Scenario D), and thus concludes that the Project is less financially

attractive than Scenario D.

In order to asses the robustness of this analyis, a series of sensitivity analysis is performed on all of the critical parameters. The

results are listed in the following table.

Critical

Parameter

Sensitivity Magnitude Result of Sensitivity

Analysis (‘000,000)

Justification of sensitivity magnitude

Equipment

costs

Reduced by 20% IDR (31,708) The project equipment cost is based on quotation from a supplier on a turn-

key basis. However, the Project Participant decided to manage the project

itself, and thus made a considerable savings. The 20% reduction is deemed

appropriate.

Tax on Profit 25% instead of 30% IDR (11,393) The applicable tax rate is applied on progressive basis with maximum tax

rate of 30%. However the maximum tax rate is applied for profit above

IDR100million and thus the magnitude of sensitivity is appropriate.

Imported shell

price

Maintained at 2004

price

IDR (43,168) The shell price in 2004 is Rp150,000 per tonnes, as it is unlikely that the

price of shell will be lower.

The price of shell in 2007 is Rp290,000 per tones, well above the assumed

value in the financial analysis.

Fuel price Increased by 20% IDR (28,090) With hindsight of the current oil price, it is difficult to analyze the appropriate

magnitude for sensitivity analysis for this parameter at the time of decision

making.

14 Maintenance costs for the reverse osmosis plant has been accounted in the water treatment costs. Maintenance cost on the residue boiler is assumed to be insignificant in both cases.


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Although it was generally accepted that the government needs to shave its

oil subsidy at some point in time, increase is historically controlled and

announced overnight to avoid conflict.

The sensitivity magnitude of 20% is based on the evaluation of historical

price increase between January 2003 to January 2004 which is 25% for

diesel oil, but only 2.6% for diesel oil. The price remains constant for the

entire 2004.

Conclusion to the investment analysis The result of the sensitivity analysis shows that the financial analysis is robust to

variations of these critical parameters. The financial analysis concludes that the Project investment without CDM revenue is less

financially attractive than its alternative, and hence are unlikely to be implemented without CDM incentives. This sets Scenario D

as the most financially attractive from the two options, and more likely to be implemented than Scenario A.

Step 4 Common Practice Analysis

This step provides an analysis to which extent „similar activities‟ to the Project have been previously implemented or are currently

underway. „Similar activities‟ is defined as activities that are of similar scale, take place in a comparable environment, inter alia,

with respect to regulatory framework and are undertaken in the relevant geographical area, as defined in sub-step 1a above.

As explained earlier, the prevailing practise in Indonesia is to have palm oil mill located in-land within a palm oil plantation. The

majority of the crude palm oil generated from such mills are exported, a smaller proportion is processed domestically in refineries

to make cooking oil, and even smaller proportion is further processed into higher-value products (oleochemicals or biodiesel).

Typically, the refining and other processing are located in a maritime port closer to the storage terminal prior to being shipped to

its industrial consumers.

By implementing process integration at concept level, PAA deviates from the common practise in the industry. Process integration

is not a new concept in the more sophisticated petrochemical business, but new to the agricultural industries15

.The energy

provision strategy for such an integrated activity can not be compared to non-integrated operation. Along with its benefit, the

integrated utility also exposes PAA operations with additional risk requiring greater expertise. It is clear from this explanation that

PAA situation and subsequently the Project, is not a common practice in palm oil industry in general, and thus further demonstrate

that the Project is additional.

The significance of costs compared to alternative deemed the company to seriously pursue CDM status for this Project. The

company was already in serious discussion with representative from a leading buyer by October 2005. However, the deal stopped

short due to unexpected sensitive political situation beyond the control of the project developer deeming the company to restart

seeking option prior to engagement with Mitsubishi UFJ Securities Co.,Ltd.

B.6. Emission reductions:

B.6.1 Explanation of methodological choices

Baseline Scenario Applicable for the Project

As has been demonstrated in Section B4 and B4, the alternative to the Project falls under the description of Scenario 20, and thus

followed the methods prescribed for this Scenario.

Emission Reduction General Calculation Method

The total emission reduction resulting from the Project activity will be calculated as follow:

15 In April 2006, a research paper by a leading research institution in Indonesia describes the concept as „still needing research from scientist, courage from investors, and incentives from government‟


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𝐸𝑅𝑦 = 𝐸𝑅ℎ𝑒𝑎𝑡 ,𝑦 + 𝐸𝑅𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 ,𝑦 + 𝐵𝐸𝑏𝑖𝑜𝑚𝑎𝑠𝑠 ,𝑦 − 𝑃𝐸𝑦 − 𝐿𝑦

Equation 1

𝐸𝑅𝑦 = Emissions reductions of the Project activity during the year y (tCO2/yr)

𝐸𝑅ℎ𝑒𝑎𝑡 ,𝑦 = Emission reduction due to displacement of fossil-based heat during the year y (tCO2/yr)

𝐸𝑅𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 ,𝑦 = Emission reduction due to displacement of fossil-based electricity during the year y (tCO2/yr)

𝐵𝐸𝑏𝑖𝑜𝑚𝑎𝑠𝑠 ,𝑦 = Baseline emission due to natural decay of biomass residues (biomass K5) during the year y (tCO2e/yr)

𝑃𝐸𝑦 = Project emissions during the year y (tCO2/yr)

𝐿𝑦 = Leakage emissions during the year y (tCO2/yr)

A. Project Emissions, 𝑃𝐸𝑦

As has been elaborated under Section B.3, emission from additional waste-water from biomass treatment (𝑃𝐸𝑊𝑊 ,𝐶𝐻4,𝑦 ) is

excluded and emission from electricity usage from stand-by diesel generators (𝑃𝐸𝐸𝐶 ,𝑦) is accounted as emission from on-site fuel

consumption (𝑃𝐸𝐹𝐹𝑦). Thus, to calculate project emission, Equation 2 of ACM0006 is adapted as follow:

𝑃𝐸𝑦 = 𝑃𝐸𝑇𝑦 + 𝑃𝐸𝐹𝐹𝑦 + 𝐺𝑊𝑃𝐶𝐻4 ∙ 𝑃𝐸𝑏𝑖𝑜𝑚𝑎𝑠𝑠 ,𝐶𝐻4,𝑦

Equation 2

𝑃𝐸𝑇𝑦 = CO2 emissions during the year y due to transport biomass residues to PAA site (tCO2/yr)

𝑃𝐸𝐹𝐹𝑦 = CO2 emissions during the year y due to fossil fuel co-firing and other fossil fuel consumptions attributable to the project

activity (tCO2/yr)

𝐺𝑊𝑃𝐶𝐻4 = Global Warming Potential for methane valid for the relevant commitment period

𝑃𝐸𝑏𝑖𝑜𝑚𝑎𝑠𝑠 ,𝐶𝐻4,𝑦 = CH4 emissions from the combustion of biomass residues during the year y (tCH4/yr)

A1. CO2 Emissions from Biomass Transportation, 𝑃𝐸𝑇𝑦

With consideration of established biomass payment & logging system in all PHG operation, Option 1 is selected to calculate the

CO2 emission from off-site biomass transportation. The emission is applied to the portion of biomass that is transported to the

project site, and calculated using the following equation:

𝑃𝐸𝑇𝑦 = 𝐵𝐹𝑇,𝑘 ,𝑦

𝑘

∙1

𝑇𝐿𝑦

∙ 𝐴𝑉𝐷𝑦 ∙ 𝐸𝐹𝑘𝑚 ,𝐶𝑂2,𝑦

Equation 3

𝑃𝐸𝑇𝑦 = CO2 emissions during the year y due to transport of the biomass residues to the project plant (tCO2/yr)

𝐵𝐹𝑇 ,𝑘 ,𝑦

𝑘

= Quantity of biomass residue type k that has been transported to project site during year y (t-biomass/yr)

𝑇𝐿𝑦 = Average truck load of delivery (t/delivery)


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𝐴𝑉𝐷𝑦 = Average round trip distance (from and to) between the location of supplier and the site of the project plant during the

year y (km)

𝐸𝐹𝑘𝑚 ,𝐶𝑂2,𝑦 = Average CO2 emission factor for the delivery truck(s) measured during the year y (tCO2/km). This is calculated based

on the fuel economy of the delivery truck from supplier s.

k = Types of biomass residues used in the project plant and that have been transported to the project plant in year y. For

conservativeness, this includes biomass type K3 and K4.

A2. CO2 Emissions from Onsite Fossil Fuel Usage, 𝑃𝐸𝐹𝐹𝑦

Fossil fuel is used as auxiliary fuel to the boiler during project plant start-up and shut-down; and as fuel to power the back-up

generator set during project inactivity. No co-firing of fossil fuel in project plant is foreseen. Onsite transportation of biomass

within PAA is via conveyor belt system operated using electricity generated by the Project. Thus, fossil fuel utilization due to on-

site biomass movement is unforeseen.

As specified in the methodology, the CO2 emission from consumption of fossil fuel must be calculated in accordance with Version

01 of „Tool to calculate project or leakage CO2 emission from fossil fuel combustion‟. The tool prescribed that CO2 emission is

calculated based on quantity of fuel used times the CO2 emission coefficient of fuel used.

𝑃𝐸𝐹𝐹𝑦 = 𝐹𝐹𝑝𝑟𝑜𝑗𝑒𝑐𝑡𝑝𝑙𝑎𝑛𝑡 ,𝑖 ,𝑦 + 𝐹𝐹𝑝𝑟𝑜𝑗𝑒𝑐𝑡𝑠𝑖𝑡𝑒 ,𝑖 ,𝑦 ∙ 𝐶𝑂𝐸𝐹𝑖

𝑖

Equation 4

𝑃𝐸𝐹𝐹𝑦 = CO2 emissions from onsite fossil fuel usages in year y (t-CO2/yr)

𝐹𝐹𝑝𝑟𝑜𝑗𝑒𝑐𝑡𝑝𝑙𝑎𝑛𝑡 ,𝑖,𝑦 = Quantity of fossil fuel type i co-fired in the project boiler during year y (t-fuel/yr).

𝐹𝐹𝑝𝑟𝑜𝑗𝑒𝑐𝑡𝑠𝑖𝑡𝑒 ,𝑖,𝑦 = Quantity of fossil fuel type i used at the project site for other purposes that are attributable to the project activity

during the year y.

𝐶𝑂𝐸𝐹𝑖 CO2 emission factor for fossil fuel type i (tCO2/t-fuel)

The Tool prescribed the calculation of CO2 emission factor based on chemical composition of fossil fuel (Option A) or based on

net calorific value of fuel (Option B). With consideration that the most likely fuel to be used in the project situation are fuel oils

with complex assay (residue oil), Option B is the only practical method available to calculate CO2 emission factor.

𝐶𝑂𝐸𝐹𝑖 = 𝑁𝐶𝑉𝑖 ∙ 𝐸𝐹𝐶𝑂2,𝑖

Equation 5

𝐶𝑂𝐸𝐹𝑖 = CO2 emission factor for fossil fuel type i (tCO2/t-fuel)

𝑁𝐶𝑉𝑖 = Net calorific value of fuel type i (TJ/t-fuel)

𝐸𝐹𝐶𝑂2,𝑖 = CO2 emission factor of fuel type i (tCO2/TJ)

A3. CH4 Emissions from Combustion of Biomass Residue, 𝑃𝐸𝐵𝑖𝑜𝑚𝑎𝑠𝑠 ,𝐶𝐻4,𝑦

The combustion of biomass in the project plant releases methane via the stack-gas. As methane is a main emission source in the

baseline, the methodology mandates that this emission source is also included as project emission.


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𝑃𝐸𝑏𝑖𝑜𝑚𝑎𝑠𝑠 ,𝐶𝐻4,𝑦 = ∞ ∙ 𝐸𝐹𝐶𝐻4,𝐵𝐹 ∙ 𝐵𝐹𝑘 ,𝑦 ∙ 𝑁𝐶𝑉𝑘

𝑘

Equation 6

𝑃𝐸𝑏𝑖𝑜𝑚𝑎𝑠𝑠 ,𝐶𝐻4,𝑦 = Project emission from biomass combustion (t-CH4/yr)

∞ = Uncertainty factor (unitless) for uncertainty band of more than 100%.

𝐵𝐹𝑘,𝑦 = Quantity of biomass residue type k combusted in the project plant during the year y (t-yr)

𝑁𝐶𝑉𝑘 = Net calorific value of the biomass residue type k (TJ/tonnes)

𝐸𝐹𝐶𝐻4,𝐵𝐹 = CH4 emission factor for the combustion of biomass residues in the project plant (tCH4/TJ)

B. Emission Reduction Due to Displacement of Fossil Based Electricity, 𝐸𝑅𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 ,𝑦

The Project displaces diesel generator for electricity generation in the baseline. Consistent with the methodology the emission

reduction from this source is calculated by multiplying net quantity of increased electricity generated using biomass residues as a

result of project activity with CO2 baseline emission factor.

𝐸𝑅𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 ,𝑦 = 𝐸𝐺𝑦 ∙ 𝐸𝐹𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 ,𝑦

Equation 7

𝐸𝑅𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 ,𝑦 = Emission reductions due to displacement of electricity during the year y (tCO2/yr)

𝐸𝐺𝑦 = Net quantity of increased electricity generation as a result of the Project activity (incremental to baseline generation)

during the year y (MWh). This is equivalent to the amount of electricity supplied to the users in PAA or net electricity

generation from the Project plant.

𝐸𝐹𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 ,𝑦 = CO2 emission factor for the electricity displaced due to the Project activity during the year y (tCO2/MWh).

Determination of emission factor of the electricity, 𝐸𝐹𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 ,𝑦

For project with Scenario 20 in the baseline, the CO2 emission factor of electricity displaced is calculated in accordance with

Equation 12 of ACM0006.

𝐸𝐹𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 ,𝑦 =𝐸𝐹𝐶𝑂2,𝐹𝐹 ,𝐷𝑂

𝜀𝑒𝑙 ,𝑟𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒 𝑝𝑙𝑎𝑛𝑡

∙ 3.6 × 10−3

Equation 8

𝐸𝐹𝐶𝑂2,𝐹𝐹,𝐷𝑂 = CO2 Emission factor of the diesel oil used in the baseline situation (t-CO2/TJ)

εel ,reference plant = Average net energy efficiency of the diesel generator that would be constructed in the baseline situation

3.6 × 10−3 = Conversion factor in TJ/MWh or 1 MWh = 3.610-3TJ

𝐸𝐹𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 ,𝑦 = Equivalent CO2 emission factor for the electricity displaced due to the project activity (t-CO2/MWh)

C. Emission Reduction Due to Displacement of Fossil Based Heat, 𝐸𝑅ℎ𝑒𝑎𝑡 ,𝑦


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For project with Scenario 20 as baseline, the emission reduction due to displacement of fossil-based heat is calculated in

accordance with Equation 30 of ACM0006.

𝐸𝑅ℎ𝑒𝑎𝑡 ,𝑦 = 𝑄𝑝𝑟𝑜𝑗𝑒𝑐𝑡𝑝𝑙𝑎𝑛𝑡 ,𝑦

𝜀𝐵𝐿 ,𝐵𝑜𝑖𝑙𝑒𝑟

− 𝐵𝐹𝑘 ,𝑦 ∙ 𝑁𝐶𝑉𝑘

𝑘

∙ 𝐸𝐹𝐶𝑂2,𝐵𝐿 ,ℎ𝑒𝑎𝑡

Equation 9

𝐸𝑅ℎ𝑒𝑎𝑡 ,𝑦 = Emission reduction due to the displacement of fossil-based heat during year y (t-CO2/yr)

𝑄𝑝𝑟𝑜𝑗𝑒𝑐𝑡𝑝𝑙𝑎𝑛𝑡 ,𝑦 = Net quantity of heat generated by the project plant from firing biomass residue in year y (TJ/yr)

𝜀𝐵𝐿 ,𝐵𝑜𝑖𝑙𝑒𝑟 = Efficiency of baseline boilers (TJ/TJ).

K = Biomass residue type k, which are used in the project plant, which would (in the absence of project activity)

be used in a boiler for heat generation (B4).

Biomass type k refers to biomass type K1 (on-site generated fibre), K2 (on-site generated shell), K3 (imported

shell in the baseline that are also used in the Project). (see Table 6, p.10).

𝐵𝐹𝑘,𝑦 = Quantity of biomass residue type k used in the project situation in year y (t-biomass/yr)

𝑁𝐶𝑉𝑘 = Net calorific value of biomass residue type k (TJ/t-biomass)

𝐸𝐹𝐶𝑂2,𝐵𝐿,ℎ𝑒𝑎𝑡 = The emission factor of fossil fuel (residue oil) used for heat generation in the baseline (tCO2/TJ).

D. Baseline Emission due to uncontrolled burning of biomass, 𝐵𝐸𝑏𝑖𝑜𝑚𝑎𝑠𝑠 ,𝑦

As indicated in Table 6 (p.10), biomass type K5 (EFB) is not utilized as energy source in the baseline and in the baseline the

material will be handled in sanitary landfill. The methane generated such landfill is calculated using multiphase model specified in

the “Tool to determine methane emissions avoided from dumping waste at solid waste disposal site” outlined below.

𝐵𝐸𝑏𝑖𝑜𝑚𝑎𝑠𝑠 ,𝑦 = 𝛼 ∙ 𝐵𝐹𝑃𝐽 ,𝐾5,𝑦 ∙ 𝐷𝑂𝐶𝐾5 ∙ 𝑒−𝑘𝐾5(𝑦−𝑥) ∙ (1 − 𝑒−𝑘𝐾5 )

𝑦

𝑥=1

Equation 10

𝛼 = 𝜑 ∙ 1 − 𝑓 ∙ 𝐺𝑊𝑃𝐶𝐻4 ∙ (1 − 𝑂𝑋) ∙16

12∙ 𝐹 ∙ 𝐷𝑂𝐶𝐹 ∙ 𝑀𝐶𝐹

Equation 11

The parameter alpha (∝) is expected to remain constant throughout the duration of one credit period but must be reviewed

according to latest IPCC guideline at its renewal.

Table 10 – Parameters and Justification of constant used to determine Alpha, Equation 11

𝛼 (ALPHA)

Variable Description Value used

𝜑 = Model correction factor to account for model uncertainty. Methodology default value is used. 0.9

𝑓 = Fraction of methane captured at the dumpsite that is flared, combusted or used for other manner. It is

unlikely that the landfill has methane captured facility without CDM, and thus 0 is deemed

appropriate.

0


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𝐺𝑊𝑃𝐶𝐻4 = Global Warming Potential of methane. Methodology default value is used. 21

𝑂𝑋 = Oxidation factor of the covering material. The sanitary landfill would have either soil or plastic

covering. For conservativeness, oxidation factor of 0.1 is applied.

0.1

𝐹 = Fraction of methane in the biogas. Methodology default value is used. 0.5

𝐷𝑂𝐶𝐹 = Fraction of degradable organic carbon of organic material that can decompose. Methodology default

value is used.

0.5

𝑀𝐶𝐹 = Methane correction factor representing managed solid waste disposal. 1

Table 11 – Parameters used to determine methane emissions from biomass decay

Variable Description Value used

𝐵𝐹𝑃𝐽 ,𝐾5,𝑦 = The amount of biomass K5 generated by PAA mill (on wet basis) that would have been dispose in the

absence of the Project.

Calculated

𝐷𝑂𝐶𝐾5 = Fraction of degradable organic carbon of Biomass K5 per wet weight that can decompose.

Methodology specified for EFB.

43%

𝑘𝐾5 = Decay rate of biomass K5. Methodology specified for EFB for Tropical region with MAP>1,000mm 0.035

𝑥 = Year during crediting period N/A

𝑦 = Year of which the methane emission is calculated N/A

E. Leakage Emissions, 𝐿𝐸𝑦

The methodology prescribed that biomass with energy generation as the most likely baseline scenario does not need to be

evaluated for leakage as their effect have been accounted for in the baseline reductions. Consequently, leakage emission is

considered only for biomass type K5.

The methodology provides three possible approaches to evaluate leakage effect, and with consideration that biomass K5 is

biomass (EFB) supplied by PAA‟s own mill and will not be sold to market, assessment method L1 is the most appropriate.

The assessment method requires the demonstration that at the site where the project is located (PAA complex), EFB have not been

collected or utilized (for example as fuel, fertilizer, or feedstock) but have been dumped and left to decay prior to implementation

of project activity. This aspect has been sufficiently demonstrated in detail under Section B4 during assessment of baseline

scenario applicable to EFB.

However to provide a perspective of the availability of the biomass, it is perceived necessary to demonstrate that EFB is available

in large excess in the region. This can be demonstrated by evaluating the amount of fresh-fruit-bunches processed in the relevant

region.

Information provided by Agricultural ministry in 1998 suggests that Riau Province alone has 44 installed palm oil mill with total

processing capacity of 2,017t of fresh fruit bunches per hour. With consideration that yield of EFB is approximately 22.5% of

fresh fruit bunch processed this capacity translates to daily generation of 10,440tonnes of empty fruit bunches per day in 1998.

By 2005, news archive published in Riau Province official website suggests that the number of mills has grown to 116, and 34

more are needed to absorb yield from maturing plantations. With average capacity of 45t/hr, the 2005 yield of EFB is

approximated to be 27,014tonnes of material per day, compared to PAA‟s 310t per day. This magnitude of generation is more

than quadruple the amount waste generated by Jakarta municipality in 2004 which is circa 6,000t per day. The picture is even


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bigger if output from other province in Sumatra is considered. Thus, it is clear that a more sophisticated solution (than mulching,

burning or dumping) is needed to resolve the disposal of this material. Similar to municipal SWDS in Indonesia, dumping/burning

remains the most-attractive and within-the-law solution and with such excess, it is unlikely that EFB will become a traded

commodity within the crediting period.

EFB limited utilization coupled with large availability in the region means that EFB utilization as energy source in PAA will not

divert other users to use fossil fuel and thus the resulting leakage emission of project activity is negligible.

B.6.2. Data and parameters that are available at validation:

Data/Parameter 𝑁𝐶𝑉𝑖

Data unit: TJ/t-fuel

Description: Weighted average of net calorific value of fossil fuel type i used on-site in year y

Source of data used: Upper limit of NCV reported in Table 1.2, 2006 IPCC Report

Value applied For diesel fuel, 0.0433TJ/t-fuel

For residual fuel oil, 0.0417TJ/t-fuel

Justification of the choice of data or description

of measurement methods and procedures

actually applied:

Fuel supplier invoice (Option (a) of Tool to calculate project or leakage CO2 emissions from

fossil fuel combustion’) does not provide net calorific value data, and the most recent national

communication (Option (c)) does not cover emission from fossil fuel.

Any comments: 1. Future revision of IPCC guideline must be taken into account

2. This parameter is to calculate project emission from on-site fossil fuel combustion

Data/Parameter 𝐸𝐹𝐶𝑂2,𝑖

Data unit: t-CO2/TJ

Description: Weighted average of emission factor of fossil fuel type i used on-site in year y

Source of data used: Upper limit of effective CO2 emission factor with 95% confidence interval reported in Table 1.4,

2006 IPCC Report

Value applied For diesel fuel, 74.8tCO2/TJ

For residual fuel oil, 78.8tCO2/TJ



actually applied:

Fuel supplier invoice (Option (a) of Tool to calculate project or leakage CO2 emissions from

fossil fuel combustion’) does not provide emission factor data, and the most recent national

communication (Option (c)) does not cover emission from fossil fuel.

Any comments: 1. Future revision of IPCC guideline must be taken into account

2. This parameter is used to calculate project emission from on-site fossil fuel combustion

Data/Parameter ∞

Data unit: Dimensionless

Description: Uncertainty factor of methane emission factor used to calculate methane emission from


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combustion of biomass

Source of data used: Table 4 of ACM0006 Version 06

Value applied 1.37



actually applied:

The value is selected for ‘wood waste’ or ‘other solid biomass residue’, with assumed

uncertainty of 300%

Any comments: This parameter is used to calculate project methane emission from combustion of biomass

residue

Data/Parameter 𝐸𝐹𝐶𝐻4,𝐵𝐹

Data unit: t-CH4/TJ

Description: Methane emission factor for combustion of biomass residue in project plant

Source of data used: Default value provided in ACM0006 version 06

Value applied 0.030t-CH4/TJ



actually applied:

The methodology allows this factor to be derived from (a) measurement or (b) the use of

default value with uncertainty factor applied. With consideration practicality and size of

emision, the project proponent chose to use the latter option.

Any comments: This parameter is used to calculate methane emission from combustion of biomass residue

Data/Parameter 𝐺𝑊𝑃𝐶𝐻4

Data unit: 21

Description: Global warming potential of methane

Source of data used: IPCC default value

Value applied 21 for the first commitment period



actually applied:

In compliance with values prescribed in the chosen methodology

Any comments: This value shall be updated in accordance to future COP/MOP decisions or update of latest

IPCC Report.

Data/Parameter 𝐸𝐹𝐶𝑂2,𝐹𝐹,𝐷𝑂

Data unit: t-CO2/TJ

Description: CO2 emission factor of diesel oil used in the baseline power generator set

Source of data used: Lower limit of effective CO2 emission factor with 95% confidence interval reported in Table 1.4,

2006 IPCC Report

Value applied 72.6tCO2/TJ


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actually applied:

In compliance with method prescribed in the chosen methodology

Any comments: The value shall be updated upon adoption of later IPCC Report.

Data/Parameter 𝜀𝑒𝑙 ,𝑟𝑒𝑓𝑒𝑟𝑒𝑛𝑐𝑒 𝑝𝑙𝑎𝑛𝑡


Description: Electrical generation efficiency of power generation plant in the baseline scenario

Source of data used: Technical specification of equivalent technology that would have been used in the baseline

Value applied 45%



actually applied:

The Project will displace a series of new state-of-the-art fuel economic diesel power generators

with fuel consumption rate of 7,962kJ/kWh or equivalent efficiency of 0.45kJ/kJ according to

manufacturer specification.

Any comments: This parameter is used to calculate emission reduction from diesel oil used for electricity

generation in the baseline.

Data/Parameter 𝐸𝐹𝐶𝑂2,𝐵𝐿,𝐻𝐸𝐴𝑇

Data unit: t-CO2/TJ

Description: CO2 emission factor of residual oil used in the baseline boiler

Source of data used: Lower limit of effective CO2 emission factor with 95% confidence interval reported in Table 1.4,

2006 IPCC Report

Value applied 75.5tCO2/TJ



actually applied:

In compliance with method prescribed in the chosen methodology

Any comments: This parameter is used to calculate emission reduction from residual fuel oil used for steam

generation in the baseline.

Data/Parameter 𝜀𝐵𝐿 ,𝐵𝑜𝑖𝑙𝑒𝑟


Description: Average heat generation efficiency of boilers that would have been used in the baseline

Source of data used: Average values of 2 types of boiler used in the baseline

(a) Biomass boiler with efficiency of 70% to generate 46.6% of steam required

(b) Residual oil boiler with efficiency of 100% to generate 53.3% of steam required

Value applied 86%

Justification of the choice of data or description 1. The maximum efficiency of biomass boiler as cited by Council of Industrial Boiler


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actually applied:

whitepaper as 70%;

2. The efficiency of medium pressure residue boiler is assumed to be 100%

Any comments: N/A

Data/Parameter 𝜑


Description: Model correction factor to account for model uncertainties

Source of data used: Tool to determine methane emissions avoided from dumping waste at a solid waste disposal

site

Value applied 0.9



actually applied:

As prescribed in the methodological tool

Any comments: The adopted parameter must be reviewed upon renewal of credit period against latest IPCC

Guideline.

Data/Parameter 𝑂𝑋


Description: Oxidation factor reflecting the amount of methane from SWDS that is oxidised in the soil or

other material covering waste.


site

Value applied 0.1



actually applied:

It is expected that the EFB will managed in a sanitary landfill with some type of material

covering.


Guideline.

Data/Parameter 𝑓


Description: Fraction of methane captured that is flared.


site

Value applied 0.5





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actually applied:


Guideline.

Data/Parameter 𝐹


Description: Fraction of methane in the biogas (volume fraction)


site

Value applied 0.5



actually applied:



Guideline.

Data/Parameter 𝑀𝐶𝐹


Description: Methane correction factor


site

Value applied 1.0



actually applied:

In the absence of the Project, biomass K5 will be treated in a sanitary landfill to avoid

resistance from surrounding community. Such facilty would be considered as managed

anaerobic solid waste disposal site. Thus, MCF of 1 is deemed appropriate


Guideline.

Data/Parameter 𝐷𝑂𝐶𝐹


Description: Fraction of degradable organic carbon (by weight) that can decompose


site

Value applied 0.5



actually applied:

As prescribed by the methodological tool


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Page 33


Guideline.

Data/Parameter 𝐷𝑂𝐶𝐾5


Description: Fraction of degradable organic carbon (by weight) for material


site

Value applied 43% based on wet-waste



actually applied:

The carbon content of Biomass K5 (EFB) is similar to wood or wood products


Guideline.

Data/Parameter 𝑘𝐾5


Description: Decay rate of biomass K5


site

Value applied 0.035 for slowly degrading material at wet tropical climate



actually applied:

The carbon content of Biomass K5 (EFB) is similar to wood or wood products as prescribed by

the methodology. The mean annual precipitation (MAP) and mean annual temperature (MAT)

at Riau Province is greater than 1,000mm and 20degC respectively.


Guideline.

B.6.3 Ex-ante calculation of emission reductions:

A. Project Emission

A1. CO2 Emissions from Biomass Transportation, 𝑃𝐸𝑇𝑦

As calculated in Annex 3, approximately 80,356t of shell will be transported to the Project site using 28tonnes truck,

equivalent to 2,870 delivery trips. The shell is procured from surrounding mills with various distances. For purpose of ex-

ante calculation, it is assumed that the average return distance is 400km from the Project site.

Based on emission factor for heavy-duty vehicle without emission control of 0.001097t-CO2/km, the resulting emission

from transportation of biomass K3 and K4 is estimated as follow:

𝑃𝐸𝑇𝑦 = 2,870𝑡𝑟𝑖𝑝𝑠

𝑦𝑟∙ 40

𝑘𝑚

𝑡𝑟𝑖𝑝∙ 0.001097

𝑡𝐶𝑂2

𝑘𝑚~1,259

𝑡𝐶𝑂2

𝑦𝑟 3


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A2. CO2 Emissions from Onsite Fossil Fuel Usage, 𝑃𝐸𝐹𝐹𝑦

Based on diesel oil net calorific value of 0.0433TJ/t and emission coefficient of 74.8tCO2/TJ obtained from the upper

limit for diesel oil contained in Table 1.2 and Table 1.4 2006 IPCC report, the emission factor from diesel fuel

consumption is calculated to be 3.24 tCO2 per tonnes of diesel fuel.

𝐶𝑂𝐸𝐹𝑑𝑖𝑒𝑠𝑒𝑙 = 0.0433𝑇𝐽

𝑡𝑑𝑖𝑒𝑠𝑒𝑙∙ 74.8

𝑡𝐶𝑂2

𝑇𝐽= 3.24

𝑇𝐽

𝑡𝑑𝑖𝑒𝑠𝑒𝑙

The amount of diesel oil consumption is not yet known at this stage and depends on the number of down-time of the

Project. However, for purpose of ex-ante estimation, it is assume that 105tonnes of diesel oil per year will be consumed.

This data is estimated based on 12 shut-down per year (for all 3 lines of equipment) and diesel consumption required per

shut-down which is 8.75t for start-up and back-up electrical generation. Material movement within PAA is using

conveyor belt which draw electricity from the Project.

Based on diesel fuel emission factor calculated above, the associated emission from this source is approximated as

follow:

𝑃𝐸𝐹𝐹𝑦 = 0𝑡𝑑𝑖𝑒𝑠𝑒𝑙

𝑦𝑟+ 105

𝑡𝑑𝑖𝑒𝑠𝑒𝑙

𝑦𝑟 ∙ 3.24

𝑇𝐽

𝑡𝑑𝑖𝑒𝑠𝑒𝑙~340

𝑡𝐶𝑂2

𝑇𝐽

A3. CH4 Emissions from Combustion of Biomass Residue, 𝑃𝐸𝑏𝑖𝑜𝑚𝑎𝑠𝑠 ,𝐶𝐻4,𝑦

Based on information provided in Table 17 in Annex 3-2, It is estimated that the Project will consumes over

200,000tonnes of biomass per year yielding 2,728TJ/yr of energy.

Using default methane emission factor of 30kgCH4/TJ provided by the methodology and applying uncertainty factor of

1.37, the resulting methane emission from biomass combustion is estimated as follow:

𝑃𝐸𝑏𝑖𝑜𝑚𝑎𝑠𝑠 ,𝐶𝐻4,𝑦 = 1.37 ∙ 0.030𝑡𝐶𝐻4

𝑇𝐽∙ 2,728

𝑇𝐽

𝑦𝑟~112

𝑡𝐶𝐻4

𝑦𝑟

Total Project Emission, 𝑃𝐸𝑦

Based on the calculated project emissions from transportation, on-site fossil fuel usage, and methane released from combustion

calculated above, the project emissions are totalled to 3,951tCO2 per year.

𝑃𝐸𝑦 = 1,259𝑡𝐶𝑂2

𝑦𝑟+ 340

𝑡𝐶𝑂2

𝑦𝑟+ 21 ∙ 112

𝑡𝐶𝐻4

𝑦𝑟~3,951

𝑡𝐶𝑂2

𝑦𝑟

B. Emission Reduction from the Displacement of Fossil Based Electricity

Emission Factor of Baseline Electricity The Project will displace a series of new state-of-the-art fuel economic diesel power

generators with fuel consumption rate of 7,962kJ/kWh at continuous full load, using diesel oil with LHV of 42,700kJ/kg. Based

on this data, the electrical generation efficiency is calculated to be 45%.

𝜀𝑒𝑙 ,𝑟𝑒𝑓 =𝑘𝑊ℎ

7,962𝑘𝐽=

3,600𝑘𝐽

7,962𝑘𝐽= 0.45

Using lower limit CO2 emission factor for diesel oil in Table 1.4 2006 IPCC Guideline of 72.6tCO2/yr, the emission factor of

baseline electricity is calculated to be 0.5808tCO2/MWh.

𝐸𝐹𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 ,𝑦 =72.6

𝑡𝐶𝑂2𝑦𝑟

45%∙ 3.6 ×

10−3𝑇𝐽

𝑀𝑊ℎ= 0.5808

𝑡𝐶𝑂2

𝑀𝑊ℎ


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Net electricity supplied to PAA The net electricity required in PAA is approximated to be 54,952MWh per year based on

7,964kW demands from downstream facility and 6,900 operating hours per year.

𝐸𝐺𝑦 = 7,964𝑘𝑊 ∙ 6,900ℎ𝑟

𝑦𝑟~54,952

𝑀𝑊ℎ

𝑦𝑟

Emission reduction from fossil based electricity displacement

Based on the calculated emission factor of 0.5808tCO2/MWh, and displaced electricity of 54,952 MWh, the emission reduction

resulting from displacement of fossil based electricity generation is 31,915tCO2/yr

𝐸𝑅𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 ,𝑦 = 0.5808𝑡𝐶𝑂2

𝑀𝑊ℎ∙ 58,945

𝑀𝑊ℎ

𝑦𝑟~31,915

𝑡𝐶𝑂2

𝑦𝑟

C. Emission reduction due to displacement of fossil based heat

Average efficiency of displaced boiler In the baseline situation, steam is provided by operating three types of boilers:

(a) Low pressure biomass boiler to meet the low pressure steam demand from upstream facilities (797TJ/yr). This boiler

would have an efficiency of 70%;

(b) Low pressure boiler residue boiler to meet the demand of low pressure steam from downstream facilities (621TJ/yr).

This boiler would have efficiency of nearly 100%.

(c) Medium pressure boiler residue boiler to meet the demand of medium pressure steam from downstream facilities

(292TJ/yr). This boiler would have efficiency of nearly 100%.

The average efficiency of the above three boilers (𝜀𝐵𝐿,𝐵𝑂𝐼𝐿𝐸𝑅 ) is calculated to be 86%

𝜀𝐵𝐿,𝐵𝑂𝐼𝐿𝐸𝑅 = 0.7 ∙797

1710+ 1 ∙

621

1710+ 1 ∙

292

1710= 0.326 + 0.363 + 0.17 = 86%

Emission reduction from fossil-based heat displacement

It is estimated in Annex 3-2, that combustion of biomass in the project plant (𝑄𝑝𝑟𝑜𝑗𝑒𝑐𝑡𝑝𝑙𝑎𝑛𝑡 ) yields 2,128TJ/yr of heat and requires

2,728TJ/yr of biomass fuel. Out of these, 965TJ/yr is already used in the baseline situation from combustion of biomass K1, K2, K3

(Table 18, Annex 3-5).

Based on the lower limit of residual fuel oil of 75.5tCO2/TJ obtained from Table 1.4 IPCC Guideline, the emission reduction from

fossil-based heat displacement is calculated as follow:

𝐸𝑅ℎ𝑒𝑎𝑡 ,𝑦 = 2,128

𝑇𝐽

𝑦𝑟

86%− 965

𝑇𝐽

𝑦𝑟 ∙ 75.5

𝑡𝐶𝑂2

𝑇𝐽~113,961

𝑡𝐶𝑂2

𝑦𝑟

D. Baseline Emission due to Natural Decay of Biomass

As identified in Annex 3, PAA mills generate 93,150t of wet EFB on annual basis. Using methodological “Tool to determine

methane emissions from solid waste disposal site”, the amount of methane released from accumulation of this biomass (type K5) if

left to decompose can be determined.

The constant parameter alpha is pre-determined to be 5.67 using parameters contained in Table 10 (p. 26). Based on degradable

organic carbon for material with similar carbon content as wood of 0.43 (on wet basis) and decay constant for slowly degrading

material in tropical climate, the projected emission profile from biomass decomposition is averaged to be 38,820tCO2/yr (for 10

years). The emission profile can be seen in the following Section B.6.4.

E. Leakage Emission


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As elaborated under Section B.6.1 (Explanation of methodological choices), the Project activity is not expected to result in

increase of fossil fuel usage outside the Project boundary. Consequently, leakage emission is zero.

F. Effective emission reduction, 𝐸𝑅𝑦

Based on the calculated (a) project emissions of 3,951tCO2/yr, (b) emission reduction from fossil-based electricity generation of

31,915tCO2/yr, (c) emission reduction from heat-based steam of 113,911tCO2/yr and (d) baseline emission from methane avoided

averaged at 38,820tCO2 per year, the total emission reduction from project activity is estimated to be 180,695tCO2 per annum.

B.6.4 Summary of the ex-ante estimation of emission reductions:

Table 12- Estimated Project Emission

Year

Estimated project emission

from transportation of biomass

(tonnes of CO2)


from on-site fossil fuel usages

(tonnes of CO2)


from methane released during

biomass combustion

(tonnes of CO2)

Total estimated project

emission (tonnes of CO2)

1 1,259 340 2,352 3,951

2 1,259 340 2,352 3,951

3 1,259 340 2,352 3,951

4 1,259 340 2,352 3,951

5 1,259 340 2,352 3,951

6 1,259 340 2,352 3,951

7 1,259 340 2,352 3,951

8 1,259 340 2,352 3,951

9 1,259 340 2,352 3,951

10 1,259 340 2,352 3,951

Total 12,590 3,400 23,520 39,510

Table 13 – Estimated Baseline Emission

Year

Estimated emission reduction

from displacement of fossil-

based electricity (tonnes of

CO2)


of fossil-based heat (tonnes of

CO2)


from avoidance of methane

released from biomass

decomposition (tonnes of

CO2)

Total estimated baseline

emission

(tonnes of CO2)

1 31,915 113,911 7,811 153,637

2 31,915 113,911 15,354 161,180

3 31,915 113,911 22,637 168,463

4 31,915 113,911 29,670 175,496

5 31,915 113,911 36,461 182,287

6 31,915 113,911 43,018 188,844

7 31,915 113,911 49,350 195,176

8 31,915 113,911 55,464 201,290

9 31,915 113,911 61,367 207,193

10 31,915 113,911 67,068 212,894

Total 319,150 1,139,109 388,200 1,846,459


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Table 14 – Estimated Emission Reduction

Year Estimation of project activity

emission (tonnes of CO2)

Estimation of baseline

emissions (tonnes of CO2)

Estimation of leakage

emissions (tonnes of CO2)

Estimation of overall emission

reduction (tonnes of CO2)

1 3,951 153,637 0 149,686

2 3,951 161,180 0 157,229

3 3,951 168,463 0 164,512

4 3,951 175,496 0 171,545

5 3,951 182,287 0 178,336

6 3,951 188,844 0 184,893

7 3,951 195,176 0 191,225

8 3,951 201,290 0 197,339

9 3,951 207,193 0 203,242

10 3,951 212,894 0 208,943

Total 39,510 1,846,459 0 1,806,949

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

B.7.1 Data and parameters monitored:

Data / Parameter: 𝐵𝐹𝑇,𝑘 ,𝑦

Data unit: Trips/yr

Description: Quantity of biomass type K3 and K4 transported to Project site

Source of data to be used: Recorded weighing slip at receiving station

Value of data applied for the purpose of

calculating expected emission reductions in

section B.5

Projected to be 80,356t-shell/yr

Description of measurement methods and

procedures to be applied:

All delivery of biomass is recorded and weigh on weighing bridge supplier payment purposes

at biomass receiving station. A weighing slip is issued to supplier for billing purpose.

QA/QC procedures to be applied: Weighing bridge is subjected to regular government calibration with tolerance of less than 1%

Any comment: N/A

Data / Parameter: 𝑇𝐿𝑦

Data unit: t/delivery

Description: Average tonnage of delivery

Source of data to be used: Recorded weighing slip at receiving station



section B.5

Average delivery is approximately 28t based on truck loading capacity.



All delivery of biomass is recorded and weigh on weighing bridge supplier payment purposes

at biomass receiving station. A weighing slip is issued to supplier for billing purpose.

QA/QC procedures to be applied: Weighing bridge is subjected to regular government calibration with tolerance of less than 1%

Any comment: N/A

Data / Parameter: 𝐴𝑉𝐷𝑦


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Data unit: Km/trip

Description: Average roundtrip distance performed by biomass supplier

Source of data to be used: Information obtained from official sources



section B.5

400km/trip (approximation)



The name of the supplier is identified at the receiving station and delivery source from

individual supplier is identified by the supplier address

QA/QC procedures to be applied: The distance of delivery should be verified using official-issued road map.

Any comment: N/A

Data / Parameter: 𝐸𝐹𝑘𝑚 ,𝐶𝑂2,𝑦

Data unit: t-CO2/km

Description: Average CO2 emission factor for the trucks during the year y

Source of data to be used: Literature



section B.5

0.001097 t-CO2/km representing the emission factor of a heavy-duty truck without emission

control measure from 1996 IPCC Revised Guideline



1. Conduct sample measurements of fuel type, fuel consumption and distance travelled by a

representative truck types to identify its specific fuel consumption per distance travelled

(volume of fuel/km) from 2 suppliers.

2. Determine CO2 emission factor is using the collected data (1) and the following fuel specific

information.

(a) Net calorific value (LHV) of fuel used (based on local supplier data, or if not

available upper limit provided in Table 1.2 2006 IPCC Guideline) in MJ/tfuel.

(b) Density of fuel (based on local supplier data, or if not available use 0.9kg/L

(c) CO2 emission factor of fuel used based on upper limit provided in Table 1.4 2006

IPCC Guideline)

QA/QC procedures to be applied: Compared the calculated data with the ex-ante value. The applicable CO2 emission factor is

the higher between the two values.

Any comment: N/A

Data / Parameter: 𝐹𝐹𝑝𝑟𝑜𝑗𝑒𝑐𝑡𝑝𝑙𝑎𝑛𝑡 ,𝑖,𝑦

Data unit: t-fuel/yr

Description: Quantity of fossil fuel type i used for project boiler co-firing during year y (t-fuel/yr)

Source of data to be used: Measurement of fossil fuel fed to the boiler



section B.5

N/A



All fossil fuel co-fired in the biomass boiler must be recorded either using weighing bridge (if

solid fuel), or meters (if gas or liquid is used).

QA/QC procedures to be applied: Measuring device(s) must be calibrated at least once per year with maximum error level of

4%.


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Any comment: Co-firing with fossil fuel is not foreseen.

Data / Parameter: 𝐹𝐹𝑝𝑟𝑜𝑗𝑒𝑐𝑡𝑠𝑖𝑡𝑒 ,𝑖,𝑦

Data unit: t-fuel/yr

Description: Quantity of fossil fuel type i used for activity attributed to Project during year y (t-fuel/yr)

Activity attributed to Project that consumes fossil fuel is the operation of diesel power

generator set to provide electricity to cold-start power plants or emergency situation where the

biomass plants are not able to supply electricity.

Source of data to be used: Fuel metering device to the stand-by power generator set.



section B.5

105 t of diesel oil per year



On-line metering device is logged on at least once per month

QA/QC procedures to be applied: Measuring device is calibrated by standard laboratory at least once per year with maximum

error level of 4%.

Any comment: N/A

Data / Parameter: 𝑁𝐶𝑉𝑘

Data unit: MJ/t

Description: Net calorific value of all biomasses relevant to the project (shell, fibre, EFB)

Source of data to be used: Sampling and laboratory analysis



section B.5

Biomass Type Calorific Value in MJ/t

Fibre (K1) 𝑁𝐶𝑉𝐾1 9,257

Shell (K2,K3,K4) 𝑁𝐶𝑉𝐾2,𝑁𝐶𝑉𝐾3 , 𝑎𝑛𝑑 𝑁𝐶𝑉𝐾4 15,715

EFB (K5) 𝑁𝐶𝑉𝐾5 8,468



Sample is taken once per year and send to internationaly accredited laboratory for testing of

low heating value.

QA/QC procedures to be applied: N/A

Any comment: N/A

Data / Parameter: 𝐵𝐹𝐾1,𝑦

Data unit: Tonnes/yr

Description: Quantity of biomass residue K1 (onsite-generated fibre) feed to the project plant

Source of data to be used: Direct measurement of fibre generated by PAA mill using screw conveyour system



section B.5

46,230t-fibre per year



Fibre generated by the mill is loaded into screw conveyour system destined to the boiler. The

screw conveyour system has constant loading capacity (kg of fibre per minute). By monitoring

the operation time of the screw conveyour belt the amount of fibre fed to the boiler can be

accurately measured.

QA/QC procedures to be applied: The loading capacity of the screw convenyour must be tested once per year during verification


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by taking the following approach:

(a) the conveyour is operated for 10 minutes, and the amount of biomass conveyed is

collected and measured using weighing bridge;

(b) the conveyour loading capacity per minute is calculated and compared against the pre-set

value. The lowest loading capacity between the two values is adopted to calculate the amount

of shell fed to the boiler.

Any comment: Stock changes does not need to be considered as this biomass is the first in the dispatch

order, not stocked-up and directly fed to the boiler.



Description: Quantity of biomass residue K2 (onsite-generated shell) feed to the project plant

Source of data to be used: Direct measurement of shell generated by PAA mill using screw conveyour system



section B.5

31,050 t/yr



Shell generated by the mill is loaded into screw conveyour system destined to the boiler. The

screw conveyour system has constant loading capacity (tonnes of shell per minute). By

monitoring the operation time of the screw conveyour the amount of shell fed to the boiler can

be accurately measured.

QA/QC procedures to be applied: The loading capacity of the screw convenyour must be tested once per year during verification

by taking the following approach:

(a) the conveyour is operated for 10 minutes, and the amount of shell conveyed is collected

and measured using weighing bridge;

(b) the conveyour loading capacity per minute is calculated and compared against the pre-set

value. The lowest loading capacity between the two values is adopted to calculate the amount

of shell fed to the boiler.

Any comment: Stock changes does not need to be considered as this biomass is the second in the dispatch

order, not stocked-up and directly fed to the boiler.

Data / Parameter: 𝐵𝐹𝑃𝐽 ,𝐾5,𝑦


Description: Quantity of biomass residue K5 (onsite-generated untreated EFB) generated by the mill and

diverted from landfill by using it as fuel.

Source of data to be used: Direct measurement of material fed into the EFB treatment system



section B.5

93,150t/yr



Generated EFB is dumped into a storage area before being loaded into the conveyour belt

destined to the EFB treatment plant. EFB will be measured either using manual or on-line

balance before manually loaded into the conveyour belt.

QA/QC procedures to be applied: Balance must be calibrated with maximum error level of 4%.

Any comment: Stock changes is considered by ensuring that EFB at the storage area to be zero before the


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Page 41

monitoring period start and zero (fully consumed) at the end of the monitoring period.

Data / Parameter: 𝑚𝐾5

Data unit: %

Description: Percentage of moisture removal by EFB treatment system or moisture removed per raw EFB

Source of data to be used: Moisture test of raw EFB and treated EFB



section B.5

30.4%



The following procedure are followed twice per year at the beginning of monitoring period and

at the mid-terms of the monitoring period:

(a) sample of fresh EFB is taken, and tested for its % water content (𝑚𝐴) in PAA laboratory

(b) sample of treated EFB (taken before boiler feeding) is tested for its water content (𝑚𝐵) in

PAA laboratory;

(c) the percentage of moisture (𝑚𝐾5) removed is calculated using the following formula:

𝑚𝐾5 =𝑚𝐴 − 𝑚𝐵

1 − 𝑚𝐵

QA/QC procedures to be applied: The testing of moisture content must follow internationally accepted standard.

Any comment: This parameter is measured to calculate the amount of (treated) EFB combusted into the

boiler.



Description: Quantity of biomass residue K5 (onsite-generated treated EFB) generated by the mill and fed

into the boiler

Source of data to be used: Combination of direct measurement and moisture adjustment



section B.5

64,860t/yr



Calculated from measured 𝐵𝐹𝑃𝐽 ,𝐾5,𝑦 and 𝑚𝐾5 using the following relationship:

𝐵𝐹𝐾5,𝑦 = 𝐵𝐹𝑃𝐽 ,𝐾5,𝑦 ∙ (1 − 𝑚𝐾5)

QA/QC procedures to be applied: N/A

Any comment:

Data / Parameter: 𝐵𝐹𝐾3,𝑦 and 𝐵𝐹𝐾4,𝑦


Description: 𝐵𝐹𝐾3,𝑦 is the amount of shell imported in the baseline situation and used in the project plant;

𝐵𝐹𝐾4,𝑦 is the amount of ‘additional shell’ imported in the project situation in addition to 𝐵𝐹𝐾3,𝑦

Source of data to be used: Combination of direct measurement (𝑀𝐿𝑃), steam-table and heat and material balance

calculation;



64,860


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Page 42

section B.5



1. Measurement of low pressure steam is elaborated in the relevant table;

2. Calculate the amount of 𝐵𝐹𝐾3,𝑦 using the following relationship:

𝐵𝐹𝐾3,𝑦 =1

𝑁𝐶𝑉𝐾3

∙ 𝑀𝐿𝑃 ∙ (𝐻𝐿𝑃 − 𝐻𝐻2𝑂)

𝜀𝐵𝐿 ,𝐵𝑜𝑖𝑙𝑒𝑟

− 𝐵𝐹𝑘 ,𝑦 ∙ 𝑁𝐶𝑉𝑘

𝐾2

𝐾1

3. Calculate 𝐵𝐹𝐾4,𝑦 using the following relationship:

𝐵𝐹𝐾4,𝑦 = 𝐵𝐹𝑇,𝐾,𝑦 − 𝐵𝐹𝐾3,𝑦

QA/QC procedures to be applied: See QA/QC for 𝑁𝐶𝑉𝑘 , 𝑀𝐿𝑃, and 𝐵𝐹𝑇,𝑘 ,𝑦

Any comment: N/A

Data / Parameter: 𝑀𝐻𝑃

Data unit: t/yr

Description: (Mass) Quantity of high pressure steam generated by the boiler equivalent to the amount of

water fed to the boiler

Source of data to be used: Direct flowrate measurement of water fed to individual boiler or single measurement of steam

entering High Pressure steam header



section B.5

120t/hr



Continuous on-line flow-meter

QA/QC procedures to be applied: Flowmeter is subject to annual calibration with maximum error of up to 4%

Any comment: N/A

Data / Parameter: 𝑀𝐿𝑃

Data unit: t/yr

Description: (Mass) Quantity of low pressure steam delivered to the users

Source of data to be used: Flowmeter



section B.5

75t/hr



1. Direct measurement of steam recirculated to the boiler (𝑄𝐶) from back pressure vessel

(BPV).

2. The low pressure steam delivered to the user is calculated as 𝑄𝐿𝑃 = 𝑄𝐻𝑃 − 𝑄𝐶

QA/QC procedures to be applied: Flowmeter is subject to annual calibration with maximum error of up to 4%

Any comment:

Data / Parameter: 𝑄𝑝𝑟𝑜𝑗𝑒𝑐𝑡 𝑝𝑙𝑎𝑛𝑡

Data unit: TJ/yr

Description: Net (heat) quantity of steam generated by the project plant by firing biomass residue

Source of data to be used: Combination of direct measurement (flowmeter, temperature and pressure) and calculation



2,128TJ/yr


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section B.5



1. Hourly measurement of temperature and pressure at the boiler outlet to determine specific

enthalpy of steam generated by the biomass boiler 𝐻𝐻𝑃 in MJ/t

2. Calculate heat generated by the project plant using the following relationship:

𝑄𝑝𝑟𝑜𝑗𝑒𝑐𝑡 𝑝𝑙𝑎𝑛𝑡 = 𝑀𝐻𝑃 ∙ (𝐻𝐻𝑃 − 419) ∙ 10−6

QA/QC procedures to be applied: All quantity measuring device (flowmeter, temperature, and pressure) must be calibrated with

maximum error of up to 4%.

Any comment: N/A

Data / Parameter: 𝐸𝐺𝑦

Data unit: MWh

Description: Net electricity supplied by the Project to PAA

Source of data to be used: Electricity meters of the following:

(a) Electricity meters measuring electricity generated by all turbines;

(b) Electricity meters measuring electricity consumed by biomass power plant including

reverse osmosis plant



section B.5

57,960MWh



Individual meters are logged on daily basis.

Net electricity supplied is the difference between generation (a) and consumption (b)

QA/QC procedures to be applied: Individual electricity meters is calibrated annually with maximum error of 4%

Any comment: N/A

B.7.2 Description of the monitoring plan:

Management Structure of CDM in PAA

In order to meet the CDM monitoring and reporting requirements as outlined above, PAA will appoint its Plant Manager as the

CDM Coordinator reporting directly to a member of the Board of Director at the Nagamas‟ parent company Permata Hijau Group

(PHG).

The CDM Coordinator will supervise the following activities:

Data collection and instrument calibration by the PAA‟s technical department;

Consolidation of results from various departments; and

Issuance of emission reduction and monitoring reports for the purpose of verification.

The CDM Coordinator will also be responsible to ensure that data has been collected as per the requirements of this PDD and

contain no errors.

Monitoring equipment & Calibration Procedure

All monitoring equipment is installed by experts using standard methods. All concerning equipments will be calibrated to the

highest standards prior to start of credit period and regularly maintained by the project operator. Any irregularities or problems

with the equipment will be reported to the management and rectified as soon as possible. A thorough instrument calibration will

be conducted at the start of the crediting period.

A calibration report status is maintained for CDM purpose. The report identifies all instrumentations mandatory for calibration, its

historical maintenance and calibration report. Calibration is performed minimum annually and timed during Plant maintenance


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shut-down or if any irregularities are identified. The calibration status report will be checked for validity and compliance during

audits prior to the release of six-monthly Emission Reduction Delivery Report (ERDP).

PHG will train the power plant personnel to operate the equipment and to record all the data necessary for monitoring the Project

activity as specified in the monitoring plan. This data will be directly used for calculation of project emissions.

Archiving, Reporting, and Auditing Structure

All data required to be logged on regular basis will be recorded in the Operator Journal system. At the end of the day, the operator

log sheet will be transferred to a CDM Report covering all CDM-related instrumentation record.

This report will cover day-to-day data of:

a. Number of biomass delivery and distance covered by supplier;

b. Amount of fossil fuel consumed for power generation;

c. Amount of biomass generated and combusted;

d. Amount of net electricity delivered to PAA processing facilities;

e. Amount of heat output from the biomass boiler;

f. Amount of low pressure/medium pressure steam delivered to users

On six-monthly basis, the Technical Department at PHG will issue an Emission Reduction Delivery Report (ERDP) containing a

consolidated CDM Daily Report, estimated (delivered) emission reduction, calibration status report and an audit report verifying

the accuracy of the CDM Daily Report. The ERDP is signed and approved by PHG‟s Technical Director and will make part of the

monitoring report for annual verification. Annually monitored parameters such as the biomass net calorific values and obligation

to measure fuel consumption of delivery truck will be performed and the results are reported in the ERDP.

The hard copy of the daily report will be stored locally at Nagamas‟ site and an electronic copy is sent to PHG‟s headquarter in

Medan on daily basis to prevent data loss. Both electronic and hard copy will be archived for at least 2 years after the end of the

last crediting period.

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)

Clean Energy Finance Committee, Mitsubishi UFJ Securities Co. Ltd.

Mitsubishi Building, 2-5-2 Marunouchi, Chiyoda-ku,

Tokyo 100-0005, Japan

Ph. +81 (3) 6213 6860

Fax. +81 (3) 6213 6175

Email: [email protected]

Mitsubishi UFJ Securities is the CDM advisor to the Project, and is also a participant in this Project

Date of completion of baseline and monitoring assessment is 18/03/2008


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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:

14/09/2004, representing date when the Project enters agreements with equipment suppliers.

C.1.2. Expected operational lifetime of the project activity:

30 years

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:

N/A

C.2.1.2. Length of the first crediting period:

N/A

C.2.2. Fixed crediting period:

C.2.2.1. Starting date:

01/05/2008 or immediately after registration

C.2.2.2. Length:

10 years and 00 months

SECTION D. Environmental impacts

D.1. Documentation on the analysis of the environmental impacts, including transboundary impacts:

In accordance with regulation issued by the Minister of Environment of the host-nation, (No. 11/2006), PAA facilities does fall

into category of facility that needs an Environmental Impact Statement, but mandated to provide “Efforts for Environmental

Management and Monitoring”, which contains approved monitoring plan and actions that must be carried out.

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:

The project activity does not pose any significant environmental impact. Nevertheless, it is required to comply with the national

regulation in air quality from biomass combustion in stationary sources. The regulation requires PAA to maintain air emission

quality to be below standard applied in the Ministerial Decree No. 7/2007 which requires control of particulate emissions, and

other gases.


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SECTION E. Stakeholders’ comments

E.1. Brief description how comments by local stakeholders have been invited and compiled:

The first stakeholder consultation meeting was conducted at PAA on 09 January 2006. This meeting was attended by 26 members

of communities living in Sebangar, Simpang Bangko and Bumbung. This meeting combined information of both PAA Biomass

and Biogas Projects in a single information & consultation session. During the

meeting, a member of community suggests invitation be extended to wider audience

than the three villages already invited.

Based on this concern, a second consultation session was held in 18 June 2007, at

PAA office in Simpang Bangko. Formal invitations were extended to members of

communities of Sebangar, Simpang Bangko, Kesumbo Ampai, Suka Jadi, Suka

Tamba, and Sidomulyo villages, which are located adjacent to PAA via the individual

village heads (Kepala Desa). 21 community representatives and PAA member of

staff attended the meeting.

Comments and concerns during both meetings are summarized in Section E.2.

E.2. Summary of the comments received:

First session, 09 January 2006

Mr. Naksir Sakban the Village Chief of Sebangar inquires the extent of efforts placed by PAA to contain its waste. Mr. Sakban

also recommended that villagers be involved in managing PAA‟s waste. PAA explained that palm oil mill, including PAA,

generates a lot of waste. However, PAA is taking measure to converts its waste by using them as main energy source, replacing

fuel oils typically used for similar facility.

PAA also plans to treat its effluent such that it will no longer liberate the unpleasant smells currently observed. PAA explained

that the company has obtained permit from environmental regulators to carry out such efforts, and the Project will be carried out

in accordance with guidelines sets under the environmental documents.

Mr. Mulyono from Sebangar Village concerns about impact of global warming to farmers. PAA clarifies that the global warming

change global climate and results in extreme season variations. For farmers this means it is harder to predict period of rainy or dry

seasons, affecting planting and harvest time. On extreme case, it may reduce harvest, frequent flash flood and other environmental

problems.

Mr. Mulyono is further inquiring the hazards posed by the residue generated from the Project. PAA explains that any residue

would be handled in accordance to guideline sets by the environmental agency (BAPPEDAL). PAA is working together with local

authorities and consultants to report its industrial activities and its remaining waste to the related authorities.

Mr. Amrizal, the village Secretary of Kesumbo Ampai expressed appreciation for PAA‟s efforts to socialize the Project to

concerning parties, and express hope that consultation are conducted with larger audience, PAA appreciates the input from Mr.

Amrizal and will discuss with management if this suggestion can be implemented.

Mr. Yudelwan, a community leader of Simpang Bangko hopes that PAA will provide consultation sessions for member of

community to learn planting, maintaining, and harvesting palm oil trees. It is noted that there are 30,000ha of land can potentially

be used for plantation. PAA explained to Mr. Yudelwan that such input is appreciated and the local Plantation and General Affair

will in future design such session for benefit of community.

Second Session, 18 June 2007

Mr. Mariono stated that the use of shell and empty fruit bunches as source of energy generates exhaust during combustion. He

inquired if this is any different from the combustion of diesel and residue which also generates exhaust. PAA explained that the

use of mineral fuel (diesel and residue) contains pollutants such as sulphur which are not found in biomass combustion. This

means that exhaust from biomass combustion is cleaner than exhaust from fossil fuel combustion and thus less hazardous.

Mr. Syarifuddin asks if the residue from the boiler can be used by the community. PAA explains that the solid waste generated by

the boiler is small and contains very little nutrient. Residue from combustion can sometimes be used as building material,

however, qualities of such material is unknown.


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Mr. Naksir Saban noted that at the start of mill operation there was an increased of fly population in his area, however, he

acknowledged that these flies are no longer around. Mr. Naksir asked if the decline of the fly population has anything to do with

the Project. PAA explained that before the Project started, the empty fruit bunches accumulates as the incinerator is not allowed to

be operated. Bacteria proliferate on this material and releases strong odour, which then attracts flies and other pests. Now that the

Project is implemented, all of these empty fruit bunches are combusted and thus population of flies are noticeably low.

Mr. Syahrial inquires of the potential impact that may be experienced by surrounding community if PAA does not implement the

Project. PAA explained that in addition to the reduction of pest population as noted by Mr. Saban, the Project avoided the use of

large amount of fossil fuel that is needed to continue PAA‟s activity. Without the Project, community will experience reduction of

air quality.

It is further explained that the Project contributes to global action to mitigate global warming. Without the Project,

industrial/economic activities continue to release green house gases which are harmful to our existence and future generation.

E.3. Report on how due account was taken of any comments received:

No due account was due from the stakeholder meetings.


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Annex 1

CONTACT INFORMATION ON PARTICIPANTS IN THE PROJECT ACTIVITY

Organization: PT Pelita Agung Agrindustri

Street/P.O.Box: Jl. Iskandar Muda No. 107

Building:

City: Medan

State/Region: Sumatra Utara

Postfix/ZIP: 20154

Country: Indonesia

Telephone: +62 (61) 457 7777

FAX: +62 (61) 456 9755

E-Mail: [email protected]

URL: www.permatagroup.com

Represented by:

Title: Asst. Managing Director

Salutation: Mr.

Last Name: Virgo

Middle Name:

First Name: Jhonny

Department:

Mobile:

Direct FAX:

Direct tel:

Personal E-Mail:

Organization: Mitsubishi UFJ Securities Co., Ltd.

Street/P.O.Box: 2-5-2 Marunouchi

Building: Mitsubishi Building

City: Chiyoda-ku

State/Region: Tokyo

Postfix/ZIP: 100-0005

Country: Japan

Telephone: +81 (3) 6213 6860

FAX: +81 (3) 6213 6175

E-Mail: [email protected]

URL: www.sc.mufg.jp

Represented by:

Title: Chairman

Salutation: Mr.

Last Name: Hatano

Middle Name:

First Name: Junji

Department: Clean Energy Finance Committee

Mobile:

mailto:[email protected]

http://www.permatagroup.com/

mailto:[email protected]

http://www.sc.mufg.jp/


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Annex 2

INFORMATION REGARDING PUBLIC FUNDING

The Project does not involve any public funding


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Annex 3

BASELINE INFORMATION

The followings provide an elaborated explanations of the heat and material balance calculation provided in the spreadsheet.

ANNEX 3-1, Total energy demand by the captive user(s)

1. 74.7TPH of Low Pressure Steam (3bar, 143degC). The steam specific enthalpy at this condition is 2,750MJ/tonnes. The

energy equivalent is calculated as follow:

74.7𝑡

ℎ𝑟∗ 6,900

ℎ𝑟

𝑦𝑟∗ 2,750

𝑀𝐽

𝑡∗

𝑇𝐽

106𝑀𝐽~1,418

𝑇𝐽

𝑦𝑟

2. 15TPH of Medium Pressure Steam withdrawn directly from boiler output with condition of 15bar, 210degC. The specific

enthalpy at this condition is 2,821MJ/tonnes.

15𝑡

ℎ𝑟∗ 6,900

ℎ𝑟

𝑦𝑟∗ 2,821

𝑀𝐽

𝑡∗

𝑇𝐽

106𝑀𝐽~292

𝑇𝐽

𝑦𝑟

3. 7,964kW of electricity

7,964𝑘𝐽

𝑠∗ 3,600

𝑠

ℎ𝑟∗ 6,900

ℎ𝑟

𝑦𝑟∗

𝑇𝐽

109𝑘𝐽~198

𝑇𝐽

𝑦𝑟

Total steam requirement (demand) by captive user:

1,418𝑇𝐽

𝑦𝑟+ 292

𝑇𝐽

𝑦𝑟= 1,710

𝑇𝐽

𝑦𝑟

ANNEX 3-2 – Project Energy Supply Requirement

In the project situation, energy is consumed at the boiler for heating feedwater from 100degC to300degC at 3,000kPa.In order to

obtain the theoretical amount of fuel required, mass and energy balance is performed around the boiler.

For conservative approximation, it is assumed that feedwater enters the project plant already at elevated temperature of 100degC.

In practice, significant amount of water is unrecovered during usage and thus make-up water must be added. The make-up water

temperature must be raised from ambient temperature to 100degC.

Feed water enthalpy For conservative approximation, it is assumed that feedwater enters the project plant already at

elevated temperature of 100degC and elevated pressure of 3,100kPa(g), slightly higher than the boiler operating pressure.

In practice, significant amount of water is unrecovered during usage and thus make-up water must be added. For suitable

boiler feeding, the make-up water temperature must be raised from ambient temperature to 100degC. The specific

enthalpy of water at 100degC and 3,100kPa(g) is 421MJ/t. For 3 boilers and operating hours of 6,900hrs per year, the

annual enthalpy of feedwater is:

= 120𝑡

ℎ𝑟∗ 421

𝑀𝐽

𝑡∗ 6,900

ℎ𝑟

𝑦𝑟∗

𝑇𝐽

106𝑀𝐽~348.9

𝑇𝐽

𝑦𝑟

Steam outlet enthalpy The biomass boiler process 120t/hr of water into superheated steam at 3,000kPa(g) or 31bar(a) at

300degC. The specific enthalpy of water at this condition is 2,991MJ/t. The total enthalpy of the product is thus:

= 120𝑡

ℎ𝑟∗ 6,900

ℎ𝑟

𝑦𝑟∗ 2,991

𝑀𝐽

𝑡∗

𝑇𝐽

106𝑀𝐽~2,477

𝑇𝐽

𝑦𝑟

Boiler fuel requirement The boilers heats feedwater with total enthalpy of 348.9TJ/yr to 2,477TJ/yr, thus the amount of energy

transferred to the water is equivalent to the quantity of heat generated from firing biomass fuel (𝑄𝑝𝑟𝑜𝑗𝑒𝑐𝑡 𝑝𝑙𝑎𝑛𝑡 ,𝑦) and calculated as

the difference betwen these enthalpy values or 2,128TJ/yr.

According to its manufacturer specification, the boiler can achieved maximum efficiency of 78% with its efficiency descreases

with the use of EFB. For conservativeness, this efficiency is adopted as project boiler efficiency, and the required energy is

calculated as follow:


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= 2,477𝑇𝐽

𝑦𝑟− 348.9

𝑇𝐽

𝑦𝑟 ÷ 78%~2,728 𝑇𝐽/𝑦𝑟

ANNEX 3-3 – PAA On-site Biomass Production

The palm oil mill at PAA has the capacity to process 60TPH of fruit fresh bunch (FFB). Based on material balance established by

PHG, the residual output from palm oil mill is linearly proportional to the FFB processed (x). The hourly annual output of

biomass fuel in terms of mass is shown in Table 15 and its net calorific value and energy equivalent in shown in Table 16.

Table 15 - Annual Biomass Production at PAA

Biomass Material Balance Correlation Hourly Production in TPH Annual production based on mill operation

hour of 6,900 tonnes per year

Fibre (K1) 0.1223x + 0.0083 6.7 46,230

Shell (K2) 0.102x -1.53 4.5 31,050

EFB (K5) Untreated 0.225x+0.0017 13.5 93,150

Treated** 0.1573x+0.01 9.4 64,860

Total annual untreated biomass production (t-biomass/yr) 170,430

Total annual treated biomass (t-biomass/yr) 142,140

**equivalent to 33% moisture adjustment

Table 16 - Energy from on-site generated biomass

Biomass Calorific Value Annual Amount Energy Contribution

(kcal/kg) (MJ/t) (t/yr) (TJ/yr)

Fibre (K1) 2,213 9,257 46,260 428

Shell (K2) 3,756 15,715 31,050 488

Treated EFB (K5) 2,024 8,468 64,860 549

Total energy from dry biomass (Fibre & Shell) 916

Total energy derived from on-site generated biomass 1,465

Annex 3-4 – PAA Projected Biomass Consumption

As elaborated in Annex 3-6, in addition to the on-site fibre and shell, the project alternative imports 49TJ/yr of shell to meet its

steam demand or equivalent to 3,126t of shell. As shown in Table 16, the on-site biomasses (shell, fibre, and EFB) contributes

1,465TJ/yr of energy.

However, the Project requires 2,728TJ/yr of energy (see Annex 3-2). Thus, there is a shortfall of 1,214TJ/yr of energy, which

must be met by importing more shell. With calorific value of 15,715MJ/t, this equivalent to additional 77,229t per year of shell

import.

The amount of biomass fuel used in the Project boiler is summarized in the following table.

Table 17 – Biomass Consumption for the Project

Biomass Type Energy Equivalent Mass Equivalent Fuel Mix

According to dispatch order TJ/yr TPY (% Energy) (% Mass)

Onsite

Generation

Fibre, K1 428 46,230 16% 24%

EFB, K5 549 64,860 20% 34%

Shell, K2, Produced on-site 488 31,050

64% 50% Estimated

Shell Imports

Shell, K3, Imported in Baseline (see Annex 3-6) 49 3,126

Shell, K4, Additional Import 1,214 77,229

Total Fuel Requirement = Total Fuel to Project Boiler (TJ/yr) 2,728 222,496


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Annex 3-5 – Energy derived from dry biomass in the Project & Baseline situation

The amount of dry biomass that are used in the Project and baseline situation is shown in Table 18 below.

Table 18 - Dry Biomass Used in the Project

Biomass Annual amount (t/yr) Calorific Value (MJ/t) Energy (TJ/yr)

Fibre, K1 46,230 9,257 427.9

Shell, K2 31,050 15,715 487.9

Imported Shell, K3 3,126 15,715 49

Total energy derived from combustion of dry biomass in the Project 965

Annex 3-6 – Estimated amount of shell imported in the baseline situation

As steam is the biggest form of energy required in PAA (1,715TJ/yr), its provision is of prominent importance compared to

electricity (209TJ/yr). In the baseline situation, PAA can meet its 1,715TJ/yr of steam requirement by installing two types of

boiler:

(a) A biomass boiler to generate the low pressure steam requirement of the upstream facility (42TPH);

(b) Residue-oil fired boilers to generate the remaining low pressure (32.7TPH) and medium pressure steam (15TPH) for the

downstream processing facilities;

Low pressure biomass boiler generates 42TPH of low pressure steam required from burning fibre (K1), shell generated the on-

site mill (K2) and imported shell (K3). The amount of imported biomass K3 is calculated using the following balances.

Without electricity generation, this biomass boiler heats up 75t/hr of feedwater with specific enthalpy of 419MJ/t

(100degC,450bar(a)) to 2,750MJ/t(143degC,350bar(a)). With assumption that the baseline boiler has efficiency of 70%, the

amount of energy required for this purpose is calculated as follow:

= 42𝑡

ℎ𝑟× 6,900

ℎ𝑟

𝑦𝑟× 2,750

𝑀𝐽

𝑡− 419

𝑀𝐽

𝑡 ×

𝑇𝐽

106𝑀𝐽÷ 70% ~ 965

𝑇𝐽

𝑦𝑟

As shown in Annex 3-3, fibre and shell generated by PAA contributes 428TJ/yr and 488TJ/yr respectively or totalled to 915.9

TJ/yr. Thus, the remaining shortfall of 49TJ/yr must be met by importing shell (K3). With calorific factor of 15,715MJ/t, the

amount of shell that must be imported is calculated as follow:

= (965 − 915.9)𝑇𝐽

𝑦𝑟 ×

106𝑀𝐽

𝑇𝐽÷ 15,715

𝑀𝐽

𝑡~ 49

𝑡

𝑦𝑟

Annex 4

MONITORING INFORMATION

Please refer to Section B.7.1

- - - - -

Documents

PROJECT DESIGN DOCUMENT FORM (CDM PDD) - Version 03.1