CDM-CPA-DD-FORM Version 09.0 Page 1 of 70

CDM-CPA-DD-FORM

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Component project activity design document form

(Version 09.0)

Complete this form in accordance with the instructions attached at the end of this form.

BASIC INFORMATION

Title of the CPA MicroEnergy Credits PoA – CPA 24 – Clear Sky Partners

Scale of the CPA Large-scale

Small-scale

Version number of the CPA-DD 2

Completion date of the CPA-DD 25/11/2019

Title and UNFCCC reference number of the registered CDM PoA

MicroEnergy Credits – Microfinance for Clean Energy Product Lines – India, 9181

Title and reference number of the corresponding generic CPA

Title - MicroEnergy Credits POA – [Partner Organization name]__

Identification/reference number – 9181-0000

Coordinating/managing entity Micro Energy Credits Corporation Private Limited

Host Party India

Applied methodologies and standardized baselines

AMS-I.A “Electricity generation by the user” (Version 14)

AMS-II.G “Energy efficiency measures in thermal applications of non- renewable biomass” (Version 3)

Sectoral scopes 1 - Energy industries (renewable - / non-renewable sources)

3 – Energy demand

Estimated amount of annual average GHG emission reductions 158,248 tCO2

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SECTION A. Description of component project activity (CPA)

A.1. Purpose and general description of CPA

>> In the rural areas in India, the predominant means of cooking are traditional cook stoves that use woody biomass as fuel. The smoke and fumes from these traditional inefficient stoves contribute heavily to indoor air pollution, which overall claim approximately 400,000 lives per year in India1. In rural areas of India, households are either not connected to the grid or in households even with grid connectivity, there are frequent power outages and low voltage so rural households use kerosene for indoor lighting, which also contributes to indoor air pollution and GHG emissions. The proposed small-scale CDM project activity (SSC-CPA) involves marketing, education, distributing, and financing improved cookstoves and solar lighting systems, for low-income households and microentrepreneurs in India. Micro Energy Credits Corporation Private Limited is the Coordinating and Managing Entity of this PoA and coordinates efforts of CPA implementers to distribute Clean Energy Products in India. Clear Sky Partners LLC (Registration number: 124415-0000416; address: 506(2), 47, Gimpohangang 9-ro, 76ben-gil, Gimpo-si, Gyeonggi-do, Republic of Korea), Byeol Gihu Bojon Yuhan Hoesa (Registration number: 110114-0240545 and address: (Cheongwon Building, 2th Floor, Yeoksam-dong) 33, Teheran-ro 8-gil, Gangnam-gu, Seoul) and other Partner organizations play the role of CPA implementers. Clear Sky Partners LLC will provide all project costs for this CPA. Clear Sky Partners LLC will provide a subsidy to make Improved Cook stoves (ICS) and Solar lighting systems (SLS) affordable to households. Clear Sky Partners LLC will also provide for the operation & maintenance costs of ICS and SLS and also finance the costs associated with the distribution of the ICS and SLS to the clients, to enable the CPA to operate in a financially sustainable condition. Sales may happen in any state but within the geographic boundary of the PoA i.e. the country of India. However, it will be ensured at all times that the threshold for SSC projects is not exceeded and the PoA eligibility criteria are met. These products provide clean energy for cooking and renewable energy for lighting. The cookstoves distributed under the proposed SSC-CPA replace traditional cookstoves thereby reducing the amount of fuelwood used for cooking in the baseline by households and thus reducing GHG emissions corresponding to the fuelwood saving by the project activity. The solar lighting systems replace kerosene-based lamps in households, which would have resulted in GHG emissions due to burning of fossil fuel i.e. kerosene. Table A.1.1 Total stoves in operation over the crediting period

Year Sales

Year 1 21,0002

Year 2 21,000

Year 3 21,000

Year 4 21,000

Year 5 21,000

Year 6 21,000

Year 7 21,000

Table A.1.2 Estimated Solar Lighting system in Operation

1 http://www.pciaonline.org/sierra-club

2 These are the cookstove sales anticipated in the first year of the crediting period. At time of CPA inclusion, 0 sales have been made. Sales shall happen in any state (based on demand from customers) but in any case, all sales will be restricted to the geographical boundary of the PoA i.e. India.

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Year Sales3

Year 1 75,0004

Year 2 155,000

Year 3 200,000

Year 4 270,000

Year 5 320,000

Year 6 1,000,000

Year 7 1,200,000

Sales in this CPA for solar lighting devices can happen in any Indian state. It will be ensured that threshold for Type 1 SSC projects is not exceeded and all requirements of the applied methodology AMS.I.A. v14 and the PoA eligibility criteria are met. ERs shall be calculated at actual sales numbers complying with relevant methodological requirements The program is a voluntary initiative coordinated by Micro Energy Credits Corporation Private Limited (MEC), the CME of the PoA, and implemented by Clear Sky Partners LLC and other Partner Organizations (PO). The improved cookstoves are implemented by Shri Kshetra Dharmasthala Rural Development Project (SKDRDP)5 and Greenway Appliances (GGI)6 and solar lighting system are implemented by Evangelical Social Action Forum (ESAF)7, SKDRDP8. The exact number of solar lighting systems implemented will be made available at the time of verification as deployment of these systems is done in a phased manner depending on demand from clients. Under the proposed SSC-CPA, MEC works with project partners to develop a successful and diversified clean energy-lending program. The clean energy program addresses typical barriers for low-income clients including education, price, finance, and supply and aftersales service. MEC trains project partners to implement the clean energy lending program, as well as a robust and transparent carbon credit monitoring and tracking system to quantify and record the volume of carbon emission reductions created through the clean energy program. The carbon finance is used to expand and sustain the clean energy program through:

1. Client education and marketing 2. Internal training and capacity building 3. On lending funds to local SMEs producing the clean energy products 4. Aftersales service and maintenance 5. Lowering the interest or principal cost to the client

The goal of the proposed SSC-CPA is to use carbon finance to enable installations of solar lighting systems, and improved cook stoves in India, resulting in the following sustainable development benefits:

• Education benefits: Households will have less air pollution along with better and more reliable lighting. This will reduce the risk of air pollution-related diseases for the families and enable people to work and/or study for longer hours without straining their eyes.

3 Sales shall happen in any state (based on demand from customers) but in any case, all sales will be restricted

to the geographical boundary of the PoA i.e. India and be in line with all requirements of the methodology AMS.I.A v14 and PoA eligibility criteria

4These are the solar lighting system sales anticipated in the first year of the crediting period. At time of CPA inclusion, 0 sales have been made

5http://skdrdpindia.org/

6http://greenwayappliances.com

7https://www.esafbank.com/

8http://skdrdpindia.org/

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• Economic benefits: o Households and micro-entrepreneurs will achieve energy savings from reduced

spending on biomass fuel and kerosene o The expansion of the clean energy supply chain to rural regions will generate jobs, at

clean energy product suppliers

• Health benefits: It will reduce health hazards from fumes and kerosene. There will also be lesser fire risks from kerosene for families and micro-entrepreneurs

• Environmental benefits: It will reduce emissions of greenhouse gases from usage of kerosene

The CME has approved the inclusion of the proposed SSC-CPA in the registered PoA and also confirms that the proposed SSC-CPA will not be part of another PoA or any single CDM project activity. The technologies/measures employed by the CPA - POs offers loans for a suite of Clean Energy Products (“CEP”) including improved cookstoves, and solar lighting systems.

The project boundary – The POs included in this CPA will be working in branches located in India (Coordinates: 20.5937°N 78.9629°E)

The baseline scenario – SOLAR: This SSC-CPA involves the introduction of solar lighting systems into households in several states in India to replace the main baseline fuel, kerosene. IMPROVED STOVES: The cookstoves distributed under the proposed SSC-CPA replace traditional cookstoves thereby reducing the amount of fuelwood used for cooking in the baseline by households

The estimates of annual average and total GHG emission reductions for the chosen crediting period - The annual average GHG emission reductions for the chosen crediting period are 158,248 t CO2e and total GHG emission reductions are 1,107,738 tCO2e

A.2. Location of CPA

>> The products sold will be restricted to the boundary of the Republic of India. The SSC-CPA project activities will involve households in many states of the host country. The location of each clean energy installation as per a GPS location or verified address will be recorded in MicroEnergy Credit’s Credit Tracker Platform.

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The location of each clean energy installation9 as per a GPS location or verified address will be recorded in MicroEnergy Credit’s Credit Tracker Platform, which has been designed specifically for accelerating microfinance access to clean and efficient energy. These locations will define the more precise boundary of the project activities. The Credit Tracker Platform is used to collect and store the information related to the unique identification number, location, installation date, and usage status of each clean energy product in the CPA, making it easy to identify, locate and verify any or all of the installations that pertain to the CPA. The MEC Credit Tracker Platform is a hosted internet service, limiting the risk of loss of data.

A.3. Technologies/measures

>> There will be two models of improved cook stoves disseminated under the proposed SSC-CPA. In the absence of the project activity, the households with improved cook stoves would have continued to use inefficient traditional cook stoves, including three-stone fires and conventional stoves built of mud/clay lacking a chimney and grate to provide energy for cooking. These stoves use firewood as the fuel. The efficiencies of these conventional stoves are low and are of the order of 10%10. The technical specifications11 of the clean energy products are as follows -

9Location is defined by one of the following sets of information:

A. Precise GPS location of the household that purchases/installs clean energy product. B. GPS location within one mile of the household and credible address for household. C. Three of the following identifiers: purchaser name, household address, phone number, bank ID

number, national ID number, product serial number, household GPS location, or GPS location within one mile of household.

10Jagadish, K.S. (2004). The development and dissemination of efficient domestic cook stoves and other devices in Karnataka. Current Science, Vol. 87, No.7.

11Manufacturer’s certificate on specifications

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The Greenway Smart Stove (GSSV3) is a single burner, high efficiency cook stove that delivers fuel savings up to 70% and minimizes harmful emissions of CO, CO2 and Particulate Matter. The rated thermal efficiency is 25.19%12.

Grameen Greenway Smart Stove (GSSV3) –

Stove Body Size – 9.8’’ x 7.6’’ x 11.7’’

Net weight: 2.5 kg

Average Life span under standard use conditions: 5 years

The Greenway Jumbo Stove (GJS) is a single burner, high efficiency cook stove that delivers fuel savings up to 70% and minimizes harmful emissions of CO, CO2 and Particulate Matter. The rated thermal efficiency is 31.17%13.

Grameen Jumbo Stove (GJS) –

Stove Body Size – 12.4" x 10.6" x 11.6"

Net weight: 5 kg

Average Life span under standard use conditions: 5 years

A variety of solar lighting systems will be offered under the proposed SSC-CPA. Households receiving these solar lighting systems are either not connected to the grid or have intermittent electricity supply from the grid resulting in use of kerosene for lighting in the baseline scenario. Some of the models that will be distributed, including their technical specifications14 are –

1. Selco Eco Home 1 HLS (Model Number – EH1HLS): Solar panel Wattage: 12W Total Light system wattage: 5W Luminous intensity (Lumens/Wattage): 76 Lifetime of product (in years) – Module – 15 years Battery – 8 years Electronics – 5 years Battery: Lead Acid Tubular, 15 Ah, 12V

2. Selco Eco Home 2 HLS (Model Number – EH2HLS): Solar panel Wattage: 12W Total Light system wattage: 3.6W Luminous intensity (Lumens/Wattage): 111 Lifetime of product (in years) – Module – 15 years Battery – 8 years Electronics – 5 years Battery: Lead Acid Tubular, 15 Ah, 12V 3. Selco Eco Home 4 HLS (Model Number – EH4HLS):

12As per stove testing results

13As per stove testing results

14As per manufacturer’s product information sheet

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Solar panel Wattage: 18W Total Light system wattage: 9.6W Luminous intensity (Lumens/Wattage): 109 Lifetime of product (in years) – Module – 15 years Battery – 8 years Electronics – 5 years Battery: Lead Acid Tubular, 20 Ah, 12V

4. Selco Smart Home 4 HLS (Model Number – SH4HLS): Solar panel Wattage: 30W Total Light system wattage: 16.8W Luminous intensity (Lumens/Wattage): 85 Lifetime of product (in years) – Module – 15 years Battery – 8 years Electronics – 5 years Battery: Lead Acid Tubular, 30 Ah, 12V 5. Selco Super Bright HLS (Model Number – SB4HLS): Solar panel Wattage: 40W Total Light system wattage: 30W Luminous intensity (Lumens/Wattage): 78 Lifetime of product (in years) – Module – 15 years Battery – 8 years Electronics – 5 years Battery: Lead Acid Tubular, 60 Ah, 12V 6. Selco Shankara 2 Light (Model Number – SKD2L): Solar panel Wattage: 12W Total Light system wattage: 9W Luminous intensity (Lumens/Wattage): 102 Lifetime of product (in years) – Module – 15 years Battery – 8 years Electronics – 5 years Battery: Lead Acid Tubular, 20 Ah, 12V 7. Selco Shankara 3 Light (Model Number – SKD3L): Solar panel Wattage: 18W Total Light system wattage: 12W Luminous intensity (Lumens/Wattage): 100 Lifetime of product (in years) – Module – 15 years Battery – 8 years Electronics – 5 years Battery: Lead Acid Tubular, 20 Ah, 12V

8. RAL Duron Mitwa MS 16B solar lantern: Solar panel Wattage: 0.35W Total Light system wattage: 0.5W Luminous intensity (Lumens): 50 Average Lifetime: 5 years Battery: Li-ion Phosphate, 550mAh, 3.2V

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All products contain a solar panel, lights as shown in the photograph –

Other models of solar lighting systems may also be offered under the SSC-CPA as long as they meet all the requirements of the methodology AMS.I.A v14. and the PoA eligibility criteria in the registered PoA-DD.

A.4. Coordinating/managing entity

>> Micro Energy Credits Corporation Private Limited (MEC) is the coordinating/managing entity (“CME”) for the proposed SSC-PoA. MEC is a registered company in India. The CME will communicate with the Executive Board and/or the pertinent Designated Operational Entity (“DOE”) on all matters, including submission of the PoA and making arrangements for the distribution of certified emission reductions.

A.5. Parties and CPA implementers

Parties involved CPA implementers Indicate if the Party involved

wishes to be considered as CPA implementer (Yes/No)

Republic of Korea Clear Sky Partners LLC No

India Micro Energy Credits Corporation Private Limited

No

Republic of Korea Byeol Gihu Bojon Yuhan Hoesa No

India Shri Kshetra Dharmasthala Rural Development Project (SKDRDP)

No

India Greenway Appliances (GGI) No

India Evangelical Social Action Forum (ESAF)

No

A.6. Public funding of CPA

>> The proposed SSC-CPA does not receive any funding from Annex I parties to the Convention therefore there is no risk that public funding could result in diversion of ODA. Affirmation of this is available in the form of a statement from the CME and PO.

A.7. History of CPA

>> The CME confirms that –

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a. The proposed CPA is neither registered as a CDM project activity nor included in another registered CDM PoA. b. The proposed CPA is not a project activity that has been deregistered Further, the CME declares that – 1. The proposed CPA is a CPA that has not been excluded from a registered CDM PoA; 2. A registered CDM project activity or a CPA under a registered CDM PoA whose crediting period has or has not expired (hereinafter referred to as former project) does exist in the same geographical location as the proposed CPA. However, in line with paragraph 168 of the CDM project standard for Programme of Activities v2.0, the CME declares that proposed CPA will not lead to the discontinuation or modification of the former project and does not decrease the GHG emission reductions or net anthropogenic GHG removals by the former project, and that the

proposed CPA complies with the following conditions:

Requirement as per CDM project Standard for Programme of Activities V2.0

Water Purification Devices15

Solar Lighting systems

Improved cookstoves

It utilizes both a different measure and a different technology from those of the former project

A registered CDM project activity (Reference number – 9432) exists, however, the technology type used by this registered PoA (membrane based filter) is different from the technology (HUL-Pureit Classic 23L and EFL Aquasure Nakshatra) used in the proposed CPA (Gravity based filter) in CMEs PoA.

A registered CDM project activity (Reference number – 2699) exists, however, the technology (specifically the solar lamp models) used in this project are different from the solar lamp models used in the proposed CPA16. Also, the solar models mentioned in the registered CDM project have been discontinued by the manufacturer and also have different technical specifications than the models included in the proposed CPA.

There are multiple CDM Projects and Programme of Activities for improved cookstoves in India. However, the technology type used by these registered PAs and PoAs is different from the technology (Grameen Greenway manufactured cookstoves – Smart stove and Jumbo Stove) used in the proposed CPA.

It does not share or utilize any of the assets of the former project

The registered existing project activity solely utilizes the network of distributors and retailers to disseminate the products. However, the proposed CPA



15Please note that while the table mentions Water Purifiers, there are no water purifiers included in this CPA.

16Associated evidence (product technical specifications) is submitted to the validating DOE to substantiate that the models are different.

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relies extensively on microfinance channel to disseminate the products.



It utilizes a different resource type compared to the former project

While the resource type is water for both, the existing registered CDM project as well as the proposed CPA, however, the resource (solar energy) is available in abundance and hence is not shared.

While the resource type is solar energy for both, the existing registered CDM project as well as the proposed CPA, however, the resource (solar energy) is available in abundance and hence is not shared.

While the resource type is woody biomass for both, the existing registered CDM project as well as the proposed CPA, however, the resource is available in abundance and hence is not shared.

The CME also confirms that the POs have the CME’s approval for inclusion in the registered PoA

A.8. Debundling

>> In accordance with paragraph 9 of Annex 32 to the EB47 Report, “Guidance for determining the occurrence of de-bundling under a Programme of Activities (PoA),” if each independent subsystem/measures included in the CPA of a PoA is no greater than 1% of the small-scale threshold defined by the methodology applied, than that CPA of PoA is exempted from performing the debundling check, i.e. considered as being not a de-bundled component of a large-scale activity. For Cookstoves: The small-scale threshold, as defined by AMS II.G version 3, is for a maximum energy saving of 180 GWhth/year. The calculation in the table A.8.1 below shows that a single cookstove does not exceed 1% of the SSC threshold i.e. 1.8 GWhth. Each cookstove deployed has a maximum energy saving of 0.0083 GWhth, i.e. 0.005% of the small-scale limit.

Table A.8.1

Parameter Unit Value Reference/Source

Baseline Stove efficiency % 10 As per SSC methodology AMS.II.G v3

Project stove efficiency % 31.17

Performance testing report for Grameen Greenway Jumbo Stove given by Indian Institute of Technology, School of Materials Science and Technology, Banaras Hindu University, dated 17/12/2015

Baseline Fuel consumption

T/family/year 2.81

Calculated from Forest Survey of India, State of Forest's 2011 report. Maximum Possible value(Meghalaya) is considered for conservative design

Fuelwood savings T/family/year 1.91 Calculated

Calorific value of biomass TJ/T 0.016

IPCC default value cited in and AMS-II.G version 3

Energy savings per year

TJ/family/year 0.030 Calculated

Conversion factor TJ/GWh 3.6

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Energy savings per improved cookstove GWhth 0.0083 Calculated

Total number of cookstove till 180GWhth threshold is reached 21,765

The above calculation is for cookstoves sold in the state of Meghalaya and also highest possible energy savings for a single cookstove in this project. Reference for above calculation is provided in the emission reduction excel sheet titled “9181-0024 ER Calculation Ex ante”. For Solar Lighting:

Parameter Unit Value Reference/Source

Average Wattage of solar device W 10.81

Average capacity of the model amongst the different types of solar lighting systems to be distributed under the proposed CPA

Total number of solar devices till 15 MWe threshold is reached 1,387,283

Each device as a percentage of the threshold 0.0001%

The reference for above calculation is provided in the emission reduction excel sheet titled “9181-0024 ER Calculation Ex ante”

Therefore, the proposed SSC-CPA is exempted from the de-bundling check.

SECTION B. Application of methodologies and standardized baselines

B.1. References to methodologies and standardized baselines

>> The proposed SSC-CPA applies the following methodologies in line with the registered PoA17 – For solar lighting and solar electric/PV systems, the SSC-CPA will use the approved small-scale methodology AMS-I.A “Electricity generation by the user” (Version 14)18 in accordance with the

registered PoA-DD under which SSC-CPA shall be included. For the thermal displacement technologies (improved cookstoves), the SSC-CPA will use the approved small- scale methodology AMS-II.G “Energy efficiency measures in thermal

17http://cdm.unfccc.int/ProgrammeOfActivities/poa_db/B46TH0V2GLIZK1UPWJ3SMNA8QRX7FY/view

18 http://cdm.unfccc.int/filestorage/A/R/X/ARX0JK3B48L2Z9M5VNP67QTUDOEC1Y/EB54_repan08_AMS-I.A_ver14.pdf?t=NWt8b2Y4c253fDDRBxj7vqpqJYL-oiaefc8C

http://cdm.unfccc.int/ProgrammeOfActivities/poa_db/B46TH0V2GLIZK1UPWJ3SMNA8QRX7FY/view

http://cdm.unfccc.int/filestorage/A/R/X/ARX0JK3B48L2Z9M5VNP67QTUDOEC1Y/EB54_repan08_AMS-I.A_ver14.pdf?t=NWt8b2Y4c253fDDRBxj7vqpqJYL-oiaefc8C

http://cdm.unfccc.int/filestorage/A/R/X/ARX0JK3B48L2Z9M5VNP67QTUDOEC1Y/EB54_repan08_AMS-I.A_ver14.pdf?t=NWt8b2Y4c253fDDRBxj7vqpqJYL-oiaefc8C

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applications of non- renewable biomass” (Version 3)19in accordance with the registered PoA-DD under which SSC-CPA shall be included.

B.2. Project boundary, sources and greenhouse gases (GHGs)

>> The project boundary – The sales included in this CPA will be within geographic boundary of the PoA i.e. Republic of India (Coordinates: 20.5937°N 78.9629°E) SOLAR:

Source GHG Included? Justification/Explanation

Baseli

ne

Combustion of kerosene fuel used for light;

CO2 Yes Primary source of emissions

CH4 No Minor source

N2O No Minor source

Pro

ject

acti

vit

y

Renewable energy source solar lighting systems used for light

CO2

No Project activity does not involve consumption of fossil fuels or electricity therefore no CO2 emissions are generated

CH4 No Minor source

N2O No Minor source

IMPROVED COOKSTOVES:

Source GHG Included? Justification/Explanation

Baseli

ne

Combustion of non-renewable biomass for cooking or heating

CO2 Yes Important source of emissions

CH4 No Not required by methodology, only CO2 Emission Factor for fossil fuels is considered.

N2O No Not required by methodology, only CO2 Emission Factor for fossil fuels is considered.

Pro

ject

Acti

vit

y Combustion of non-renewable biomass

for cooking or heating CO2 Yes Important source of emissions

CH4 No Not required by methodology, only CO2 Emission Factor for fossil fuels is considered.

N2O No Not required by methodology, only CO2 Emission Factor for fossil fuels is considered.

19 https://cdm.unfccc.int/filestorage/M/L/D/MLDN960OH41VWJPCZ23ERFUQT5BAGX/EB60_repan21_AMS-

II.G_ver03.pdf?t=TW18b2Z2eDJ3fDC14o2F1N8SHw4UMCpjFALK

https://cdm.unfccc.int/filestorage/M/L/D/MLDN960OH41VWJPCZ23ERFUQT5BAGX/EB60_repan21_AMS-II.G_ver03.pdf?t=TW18b2Z2eDJ3fDC14o2F1N8SHw4UMCpjFALK

https://cdm.unfccc.int/filestorage/M/L/D/MLDN960OH41VWJPCZ23ERFUQT5BAGX/EB60_repan21_AMS-II.G_ver03.pdf?t=TW18b2Z2eDJ3fDC14o2F1N8SHw4UMCpjFALK

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FLOW DIAGRAM: For improved cookstoves – For solar lighting systems -

Woody biomass consumed in the baseline scenario

Use of traditional cookstove with low

efficiency

CO2 emissions produced

Woody biomass consumed in the project scenario

Use of improved cookstove with

higher efficiency


Baseline scenario

Project scenario

Efficiency improvement by upgrading to improved cookstove

Baseline scenario

Project scenario

Use of kerosene based lamps for

lighting


Use of solar lighting systems

No CO2 emissions produced

Switch from kerosene based lamps to solar lighting system

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B.3. Establishment and description of baseline scenario

>>

BASELINE DESCRIPTION – STOVES

A summary of baseline information for India is provided in this Section. Parameters for the baseline scenario are established using data primarily from the Ministry of Environment and Forest report titled, “India State of the Forest Report” by the Forest Survey of India (FSI)14, as well as supporting sources identified below. The baseline scenario identified in this PoA-PDD will serve to calculate the emission reductions creditable from the introduction of improved biomass cookstoves to replace traditional unimproved stoves used for cooking and heating water for drinking purposes at the household level.

According to CDM Methodology AMS-II.G, “It is assumed that in the absence of the project activity, the baseline scenario would be the use of fossil fuels for meeting similar thermal energy needs”. The baseline scenario for this project activity is derived using data from the above-mentioned study, including the calculation of ƒNRB,y, the fraction of woody biomass saved by this project activity that can be established as non-renewable.

This project applies a default value of 0.1 for parameter Nold (efficiency of the system being replaced) because the systems being replaced are either three-stone fires or conventional systems with no improved combustion air supply or flue gas ventilation system. For other types of systems a default value of 0.2 shall be used, unless evidence can be provided to justify an alternate value.

Objectives and Reliability Requirements

The objective of the 2011 FSI report was to assess fuelwood and small timber requirements at the state and national level by analyzing the growing stock of various Indian forests and village wood consumption surveys. Households were specifically surveyed about fuel sources and consumption. The sample size for estimating household wood consumption was established by referencing the 1995 FSI survey, “Wood Consumption Study of Haryana”.

Target Population

The target population for the PoA consists of the beneficiary households in India using traditional cookstoves for cooking and heating water. These households collect wood from forests and other common property resources, which is to a large extent non-renewable. The FSI study targeted consumption points of wood across India by State, including industries, households and other sectors such as hostels and jails.

Sample Size

According to the 2011 FSI report, a total of 1,800 households were surveyed in 100 villages and 50 UFS blocks in India.

Baseline Sampling Design

Sampling Method

The 2011 FSI study used stratified random sampling to survey the target population. In order to achieve a representative sample, it was determined that 62 districts needed to be included in the study, but in actuality 75 districts were randomly selected and included. The villages and UFS blocks surveyed were equally distributed within these districts. Households were categorized and stratified based on economic status (i.e. “affluent, “less affluent”, and “others”). Two “affluent”, five “less affluent”, and 5 “other class” households were surveyed in each village or UFS block.

Sampling Frame

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The 2001 FSI study established a sampling frame by dividing the entire country of India into 23 clusters, based on large states or group of states/Union territories. The primary sampling frame for this project activity was fuel sources and biomass consumption of households.

Quality Assurance/Quality Control

The Forest Survey of India is administered by the government of India and was responsible for quality assurance and quality control measures.

Baseline Data Analysis

The 2011 “India State of the Forest Report” was used to estimate the fraction of woody biomass saved by this project activity that can be established as non-renewable biomass (ƒNRB).

As per SSC methodology AMS II.G paragraph 10, the non-renewable woody biomass (NRB) is defined as the quantity of woody biomass used in the absence of the project activity (Bold) minus the DRB component, as long as at least two of the following supporting indicators are shown to exist:

I. A trend showing an increase in time spent or distance travelled for gathering fuel-wood by users (or fuel-wood suppliers), or alternatively, a trend showing an increase in the distance the fuel-wood is transported to the project area;

a. A 2006 study found that the average time taken to collect one bundle of firewood

currently is 3.84 hours, as against 2.36 hours a quarter century ago. Distance to the

forest increased from 2.06 to 2.31 km, which indicates greater time spent within the

forest due to degradation.

b. A recent 2011 study based on surveys covering 4,296 individuals in Himachal

Pradesh found that on average, women walk 30 km each month taking 2.7 h per trip

for fuel wood collection over hilly terrain, often at high altitudes and undergo stress

like stiff-neck, backache, headache and loss of work days

II. Survey results, national or local statistics, studies, maps or other sources of information, such as remote-sensing data, that show that carbon stocks are depleting in the project area;

a. The India State of the Forest Report 2011 conducted an assessment of forest cover

of the entire country which was carried out at an interval of two years by interpretation

of remote-sensing satellite data. The study found that between 2009 and 2011, the

actual national forest cover reduced by 36,700 hectares. The FSI noted that the main

reasoning behind this reduction is the decrease in forest cover in certain states due

to illicit felling, forest clearances in encroached areas, shortening of shifting cultivation

cycle and biotic pressure.

III. Increasing trends in fuel wood prices indicating a scarcity of fuel-wood;

a. The wholesale price of wood and wood products in India has increased 25% in the

past ten years. The Ministry of Statistics and Programme implementation reports that

the price of wood in 2000 was $180 and has since increased to $239 in 2010 (price

measured in $RPS/0.173 units of wood).

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IV. Trends in the types of cooking fuel collected by users that indicate a scarcity of woody biomass.

a. Not applicable

NRB Conclusion: The woody biomass used in the absence of the project activity meets three of the four supporting indicators for NRB (only two are required). Therefore, the NRB is the total fuelwood consumed by households in India, minus the biomass that is considered demonstrably renewable.

Qualitative Assessment of Demonstrably Renewable Biomass (DRB)

As established in the AMS II.G methodology, the principle of Demonstrably Renewable Biomass should be considered when establishing the fraction of non-renewable biomass used in the project activity. The biomass used in India for cooking comes from woody biomass originating from trees in forests and trees outside of forests (TOF).

Woody biomass is “renewable” if the following conditions are satisfied:

The woody biomass is originating from land areas that are forests where:

I. The land area remains a forest;

a. According to the FAO Forest Resource Assessment India Country Report 2010, the area of forest has increased 7% from 63.939 million hectares in 1990 to 68.434 million hectares in 2010. However, while there has been improvement in significantly reducing and controlling the rate of deforestation, forest degradation appears to be continuing, as evidenced by the fall in the average growing stock of wood and bio mass volume per ha. Declining production of timber and fuel wood is also indicative of continuing forest degradation.

II. Sustainable management practices are undertaken on these land areas to ensure, in particular, that the level of carbon stocks on these land areas does not systematically decrease over time (carbon stocks may temporarily decrease due to harvesting); and

a. Although 29% of India’s forest area is designated as protected, there is no forest area under sustainable forest management.

b. India’s forest management program adopts a silviculture system influenced by sustained yield forestry principles, in which wood should be harvested at an average rate, which is not greater than the forest can regenerate. However, the forest productivity in India is low compared to the global average. The Mean Annual Increment (MAI), which is a measure of forest productivity, is 0.7 cu m/ha for Indian forests as against the world average of 2.1 cu m/ha. This has resulted in a demand-supply

gap in various forest products, especially fuelwood, which has led to forest degradation.

The biomass is woody biomass and originates from non-forest areas (e.g., croplands, grasslands) where:

I. The land area remains as non-forest or is reverted to forest; and

a. The Non-Forest area in India has remained constant from 1990 to 2004, while the non-forest area with tree cover increased 11% from 2000 to 2004.

II. Sustainable management practices are undertaken on these land areas to ensure in particular that the level of carbon stocks on these land areas does not systematically decrease over time (carbon stocks may temporarily decrease due to harvesting); and

a. There is no evidence or reports that indicate that sustainable management practices are undertaken on trees outside the forest.

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III. Any national or regional forestry, agriculture and nature conservation regulations are complied with.

a. There is no evidence or reports that indicate that there are any national or regional forestry conservation regulations for the area of trees outside the forest.

DRB Conclusion: The woody biomass used in the project activity originating from trees within forests and non-forest areas do not meet all of the requirements to be considered demonstrably renewable.

Assessment of baseline technology – Studies conducted by organizations like GIZ20 and the Global Alliance for clean cookstoves21 show that majority of rural Indians use traditional (inefficient) wood-based stoves like the three-stone fired for cooking. Assessment of Fraction of non-renewable biomass (fNRB) – Although the woody biomass used in the project activity did not meet all the qualitative requirements to be considered demonstrably renewable, DRB is still accounted for by assessing the sustainable extraction rate of fuelwood in forests and trees outside of forests (TOF). The total sustainable yield from forests in India is estimated by taking the percent of each forest cover type from the FSI 2011 report and applying it to the total forest area (68,434,000 hectares) presented in FAO’s India Forest Resource Assessment Country Report 201022 to yield the total area of each forest cover type. Sustainable extraction rates for specific forest cover types from a 2001 forestry and carbon sequestration study23 were then applied to each forest cover type area to find the sustainable yield of forests and plantations/TOF (26,315,679 tons/year). To account for fuelwood extracted from outside the forest, the ratio of sustainable fuelwood produced to the total area of the forest (0.38 sustainable tons/forest ha) was applied to the total area of other wooded land, 3,267,00024: For example: fNRB calculation for Meghalaya:

Parameter Unit Value Reference

Amount of non-renewable woody biomass

Million Tonnes/year 5.042 FSI State of Forests, 2011 report

Total quantity of fuelwood (Renewable +Non-renewable)


Fraction of non-renewable biomass

- 0.9560 Calculated

20http://www.giz.de/en/downloads/giz2014-en-kaleidoscope-of-cooking-india.pdf

21http://cleancookstoves.org/resources_files/india-cookstove-and-fuels-market-assessment.pdf

22 Food and Agriculture Organization. (2010). Forest Resource Assessment India Country Report. Table T1 – Extend of Forest and Other Wooded Land.

23 Ravindranath, N.H., et al. (2001). Forestry for Sustainable Biomass Production and Carbon Sequestration in India. Mitigation and Adaptation Strategies for Global Change, 6:233-256. Table AI. Projected and sustainable rates of extraction from forests and plantation, pg. 254. See India NRB Report (Table 2) for a complete summary of sustainable fuelwood extraction estimates for India’s forests.

24FAO, 2010.

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Calculated Fraction of non-renewable biomass = 5.042/5.274 = 0.9560 Calculation 1 3,267,000 ha x 0.38 = 1,256,295 tons Therefore, the total DRB from both forest and non-forest areas in India is 27,571,974 tons/year. The woody biomass used in the absence of the project activity in India meets the CDM requirements for non-renewability, and therefore the NRB is calculated as the total household fuelwood demand minus the DRB. NRB for this project activity is calculated as follows: Calculation 2 NRB = Bold – DRB 188,849,029 tons = 216,421,000 tons – 27,571,974 tons The fraction NRB for India is calculated accordingly: Calculation 3 fNRB = NRB/ (NRB + DRB) 0.8726 = 188,849,029 tons / (188,849,029 tons + 27,571,974 tons) Since the stoves in this CPA are distributed in several states in India, the fNRB,y value is calculated individually for all states. The values are mentioned in Section B.4.2. of the CPA-DD. For the calculation of emission reductions, as mentioned in the PoA-DD, the lower value between state level fNRB,y and India level fNRB,y will be used. Assessment of Quantity of woody biomass consumed in the absence of the project activity (Qbiomass) – As required by AMS-II.G “Energy efficiency measures in thermal applications of non- renewable biomass” (Version 3), Qbiomass is calculated based on historical data. For the purpose of calculating Qbiomass, CME refers to the Forest Survey of India (FSI)’s State of Forests, 2011 report. Cookstoves within the proposed SSC-CPA are deployed in Several Indian states. The Qbiomass values for all states are mentioned in Section B.4.2 For example: Qbiomass calculation for Meghalaya:

Parameter Unit Value Reference

Number of persons using fuel wood

Million 9.383 FSI State of Forests, 2011 report

Total quantity of fuelwood used for cooking


Number of people in a household for the State of Meghalaya

5 Census of India, 2011

Total Biomass consumption in the

Tonne/family/year 2.81 Calculated

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absence of the project activity (Qbiomass)

Qbiomass = (5.274/9.383)* 5 = 2.81 Hence, it can be established that for cookstoves, the baseline is use of conventional (inefficient) wood-based stoves like the three-stone fired for cooking.

BASELINE DESCRIPTION – SOLAR LIGHTING

The project activity involves the introduction of solar lighting systems into households throughout India. Solar lighting systems replace the main baseline fuel, kerosene. Baseline parameters for this project activity were primarily derived from data presented in India’s National Sample Survey Organisation’s (NSSO) 2007 report, “Energy Sources of Indian Households for Cooking and Lighting, 2004-05”. It reports information from the national Household Consumer Expenditure survey conducted from July 2004 to June 2005, and contains the most recent data on household lighting consumption in India. Other supporting studies were used for non-India specific parameter values, such as luminous efficiency and the net calorific value of kerosene. Households in India use kerosene, gas, candle, electricity, and other oil for lighting. Among these, kerosene and electricity are most commonly used. At a national level, kerosene and electricity is used by 99% of the households in both rural and urban areas. The use of kerosene as the primary source of lighting is common in rural areas where nationally 44% of the rural population consumes kerosene for lighting, as compared to 7% in urban areas. According to Methodology AMS-I.A (version 14), the energy baseline is: the fuel consumption of the technology in use or that would have been used in the absence of the project activity to generate the equivalent quantity of energy, estimated using one of three options. This project activity will use Option 3, a trend-adjusted projection of historic fuel consumption in situations where an existing technology is replaced, to calculate emissions baseline in year y (BECO2), as outlined in the methodology. Data from the 2007 NSSO report is used to calculate this projection. The baseline scenario identified in this PDD will serve to calculate the emission reductions creditable from the installation of renewable energy lighting applications, and the replacement of kerosene lanterns. Objectives and Reliability Requirements

The 2004-05 Household Consumer Expenditure survey presents the distribution of rural and urban households by primary source of energy used for cooking and lighting in all of the states and Uts of India. The survey sampling design and instruments, as well as the preparation of the 2007 report, were developed by NSSO’s Survey Design and Research Division. The field work was conducted by the Field Operations Division and the data processing and table generation by the Data Processing Division. Target Population The target population for this project activity consists of households throughout India where the CME’s partner Microfinance Institutions (MFIs) operate. NSSO survey sample was collected to represent all Indian states and different socio-economic categories. NSSO data is used to calculate historic consumption rates of kerosene for the baseline of this project activity. Sample Size

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The 2004-05 NSSO survey covered all the States and Uts in India. The data was collected from a sample of 79,298 rural and 45,346 urban households spread over 7,999 villages and 4,602 urban blocks, respectively.

BASELINE SAMPLING DESIGN

Sampling Method Clustered random sampling was used to select villages and urban blocks included in the survey. Each district within a state or ut was divided into two clusters that were comprised of all rural areas and all urban areas within a district. The number of villages or blocks sampled within a state or ut was determined based on the proportion of population as per the 2001 Census, and was subject to the availability of investigators to ensure a uniform workload. The allocation of the sample between the rural and urban sectors was determined by the proportion of the population as per the 2001 Census with a 1.5 weighting for the urban sector. Households were selected using simple random sampling without replacement with respect to rural/urban location, income, and monthly per capita expenditure.25 Sampling Frame The sampling frame was comprised of two different sources: For households in rural areas, a list of villages from the 2001 national census constituted the sampling frame. For households in the urban sector, the latest available list from the Urban Frame Survey (UFS) blocks was used as the sampling frame. Quality Assurance/Quality Control Technical guidance from the governing council NSSO and survey working group was provided at every stage of the survey. Since surveying was conducted over four rounds, an equal number of villages/blocks were sampled in each to ensure a uniform spread.

BASELINE DATA ANALYSIS

According to Methodology AMS-I.A (version 14), the energy baseline is: the fuel consumption of the technology in use or that would have been used in the absence of the project activity to generate the equivalent quantity of energy. The technology that would have been used in the absence of the project activity is determined as a simple wick-based kerosene lantern. PARAMETER: BECO2,y

Calculation Definitions

To calculate the energy baseline, this project activity will use Option 3 (which is specifically recommended for lighting devices) listed in AMS.I.A, a trend-adjusted projection of historic fuel consumption in situations where an existing technology is replaced. The fuel consumption trend of India shows the average level of kerosene consumption for lighting in the target households over the years. The trend extrapolation is used to ensure that no carbon credits can be claimed for a lighting service which exceeds the general lighting service that people could obtain from their average kerosene consumption. The specific equivalent level of lighting service is calculated for each improved lamp model, to ensure that in the end only the actual lighting service which is provided by an improved lamp will be converted into carbon credits.

25See Appendix B of “Energy Sources of Indian Households for Cooking and Lighting, 2004-5” for detailed description of

sampling procedures.

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As defined by AMS.I.A., paragraph 11, emissions in the baseline (BECO2,y)is calculated using the following equation: Equation 1

Where: Table 1

Parameter Unit Project Calculation

BECO2,y tCO2

Emissions in the baseline in year y

FCj,y kg Amount of kerosene consumption in year y

NCVj GJ/kg Net calorific value of kerosene

EFCO2,j tCO2/GJ CO2 emission factor of kerosene

J Kg Kerosene

Step 1: Baseline Technology Applying a conservative approach we assume the kerosene lamp model in the baseline is a hurricane lamp, which is conservative because it has a glass cover making it more efficient than most homemade lanterns. This baseline lantern has an average efficiency of 0.13 lumen/watt (Louineau et al, 1994)26. This again is conservative, as the World Bank has reported an efficiency of 0.1 lumen/Watt for this model. Step 2: General Energy Baseline: The most recent kerosene consumption volume of households that use kerosene for lighting in all of rural India is 6.98 L/month (NSSO data, 2004; see Table 3 below). Table 2

Year Kerosene usage (L/month)

1987 3.85

1993 5.48

1999 8.1

2004 6.98

Source: NSSO, 1987, 1993, 1999, and 2004. The following values were calculated based on the following formula: Equation 2 KChh = KCcapita * HHsize / P(ker all India)

26 Jean-Paul Louineau, Modibo Dicko, Peter Fraenkel, Roy Barlow and Varis Bokalders, “Rural Lighting: A

Guide for Development Workers, Intermediate Technology (IT)” publications in association with The Stockholm Environment Institute 1994.

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Figure 1: Kerosene Consumption in Rural India (based on historic NSSO data)

Step 3: Specific equivalent level of lighting service: As a next step, the energy baseline calculated in Step 2 will be adjusted according to the actual level of lighting service provided by the improved lamps, in lumen*hours. The units of kerosene consumption per month per household will be adjusted to lumen*hours per month per household in the following way:

1. Calculate the lighting service provided to a household using the volume of kerosene consumption established in Step 2.

2. Compare the calculated lighting service in the previous step to the lighting service provided by the project lamps

3. Ensure carbon credits for project lamps per household do not surpass the lighting service of the energy baseline

4. Calculate the actual baseline emissions per project lamp based on the actual specific lighting service provided

The above steps are followed with detailed calculations below. As mentioned in Step 1, the luminous efficiency of the baseline technology = .13 lumens / watt (using a conservative value as described above). Using the parameters below, the equivalent level of lighting service of the kerosene consumed by households in the baseline can be calculated: Table 3

Parameter Unit Description Value Source

LS(month) Lumen*hr/month Lighting per month 9021.4 Calculated

KC(HH) Liter/ month Household Kerosene consumption per month

6.98 NSS0 511

LE(ker) Lumen / W Luminous efficiency of kerosene with baseline lantern

0.13 Louineau et al, 1994

NCV(ker) TJ/Gg Net calorific value of kerosene

43.8 IPCC 2006

Dens (ker) KG/L Density of kerosene 0.81715 www.simetric.co.u

y = 0.216x - 424.96

0

1

2

3

4

5

6

7

8

9

1985 1990 1995 2000 2005

Mo

nth

ly

Ke

rso

sen

e C

on

sum

pti

on

(L)

Kerosene Consumption for Lighting

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1. Methodology AMS-I.A. allows for a default daily lighting usage of 3.5 hours in the baseline. The calculation below represents the average light output that households get from the kerosene consumed. This value will be used to compare the lighting output of the new technology from this project.

The Lighting per month can be calculated using the following formula: Equation 3

The lighting per month based on 2004 kerosene usage = 9021.4 Lumen hr / month. The reference cap can then be calculated using the formula: Equation 4 RC = LS (month) * 12/ 365*h

The reference cap equals 84.7, based on 2004 data, and will be extrapolated to future years as new data arises on usage. The reference cap for possible carbon savings is defined such that in a single household it shall not be allowed more emission reductions claimed than those that arise from the general baseline lighting service.

2. The possible carbon savings in a single household has a reference cap as defined by the

baseline light output. According to AMS-I.A, it shall not be allowed that for a single household more emission reductions are claimed than those that arise from the general baseline lighting service. The reference cap values for all years of the crediting period are presented in the table below:

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Table 4: Extrapolated monthly kerosene consumption per household, equivalent lighting service and reference cap values

Year

Extrapolation of Kerosene Consumption (L/month)

Equivalent lighting service (lumen*hours/month)

Reference Cap (lumens)

2012 9.632 12448.96 116.9374

2013 9.848 12728.14 119.5598

2014 10.064 13007.31 122.1821

2015 10.28 13286.48 124.8045

2016 10.496 13565.65 127.4268

2017 10.712 13844.82 130.0492

2018 10.928 14123.99 132.6715

2019 11.144 14403.16 135.2939

2020 11.36 14682.33 137.9162

2021 11.576 14961.5 140.5386

2022 11.792 15240.68 143.1609

3. The baseline emissions for the lighting systems that are being distributed under this project

are calculated as the emissions corresponding to the specific equivalent level of lighting service in the baseline.

The following equation is used to calculate baseline emissions for a solar lamp (n) in period (v); the emissions that would have been generated by the burning of kerosene in the baseline to generate that same lighting as provided by n lamp over period v: Equation 5

The values are defined as follows:

Table 5

Parameter Unit Description Value Source

l(n) Lumen Lumen output of solar lamp, n

Variable (see table)

Technical specs (see references)

D Days Number of days in period v

365 -

h Hours / day Average operating hours of kerosene lamps in the baseline

3.5 Meth AMS I.A. Default value

LE(ker) Lumen/W Specific luminous efficiency of kerosene when burnt in kerosene lantern

.13 Louineau et al 1994

EF(ker) TCO2/GJ Specific CO2 emissions of kerosene

.0719 IPCC 2006

For the solar lighting component, baseline scenario is the use of fossil fuel to provide lighting in the households in the project boundary as per AMS-I.A. “Electricity generation by the user” (Version 14).

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Rural households in India rely on kerosene for lighting. As per the “Energy sources of Indian Households for cooking and lighting” report (dated September 2012) of the Government of India’s National Sample Survey Office, 44% of households in rural India use kerosene for lighting. Since, the solar lighting systems are implemented in a phased manner, the baseline scenario for individual solar lighting system will be identified in line with the guidelines given in AMS-I.A version 14. A representative sample survey (90% confidence interval, +/- 10% error margin) was also carried out in the project population to determine their pre-project fuel. To ensure that the baseline requirements of the methodology and the registered PoA-DD are complied with by the CPA, the CME also carried out a baseline survey to determine the baseline at time of CPA inclusion. This survey was carried out through a random representative approach by considering end-users that have expressed an interest in buying the solar products from PO – GGI. A representative sample survey (90% confidence interval, +/- 10% error margin) was carried out in the anticipated project population to determine their pre-project fuel. All respondents said that they used kerosene in wick lamps in the baseline scenario and are not connected to the grid. Methodology for the sample survey:

1. The total sample size required to meet (90% confidence interval, +/- 10% error margin) was calculated using http://www.raosoft.com/samplesize.html.

2. The number of final samples taken i.e. 70 was more than the sample size required (68 samples as per http://www.raosoft.com/samplesize.html calculation) to meet 90% confidence interval, +/- 10% error margin to cover for contingencies like residents not being in the house, residents not willing to talk etc.

3. A questionnaire was prepared in consultation with PO’s for conducting the survey. The questionnaire includes the name of the product owner, address and ask questions on what their baseline fuel was. The questions are designed to make sure that they are not leading and ensure that the respondents are not asked questions with bias.

4. MEC enumerators visited the selected households during the day (between 9 AM and 6 PM) to ask them the questions and collect the answers

As an additional measure, since solar sales in this CPA will be made in a phased manner across several states in India, and to ensure that the baseline requirements of the applied methodology AMS.I.A. v14 and registered PoA-DD are met, the baseline is also one of the monitoring parameters in Section B.5.1 of the CPA-DD. As part of the monitoring, it will be recorded whether or not households being given the solar lighting system used kerosene in the pre-project scenario. Only those households that used kerosene for lighting in the baseline scenario are included in the CPA for crediting. Hence, it can be established that for households with solar lighting systems in the proposed SSC-CPA, the baseline is use of kerosene.

B.4. Estimation of emission reductions

B.4.1. Explanation of methodological choices

>> The methodological choice and emission reduction equations used in the proposed SSC-CPA is based on the methodological choice approved in the PoA and mentioned in Section B.6.1. PoA-DD. The methodological choice is in line with the applied methodologies – AMS-I.A. “Electricity generation by the user” (Version 14) and AMS-II.G. “Energy efficiency measures in thermal applications of non- renewable biomass” (Version 3).

http://www.raosoft.com/samplesize.html

http://www.raosoft.com/samplesize.html

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For solar lighting: Total baseline emissions for period v are calculated as the sum of the baseline emissions of each lamp type i in the period:

BEv=

Parameter Unit Type Value

BEv tCO2 Calculated Emissions generated in the absence of the project activity in period v by all lamps

BEi,v tCO2 Calculated Emissions generated in the absence of the project activity in period v by all lamps of type i

Ex post baseline emission for each lamp type i is calculated with the following equation:

BEv= )*li*h*1

LEker*EFker*10-6*3.6*CFi,v,LFR


BEv tCO2 Calculated Emissions generated in the absence of the project activity in period v by all lamps of type i

Ni,a Number Monitored The total number of solar lamps of type i deployed in period a

di,a,v Days Monitored/calculated

Average number of days lamps of type i that have been deployed in period a were operating in period v

li Lumen Monitored (once per lamp type)

Nominal lumen output of solar lamps of the type I deployed as part of the project activity

h Hours/day Fixed Average operating hours of kerosene lamps in the baseline

LEker Lumen/W Fixed The specific light output of kerosene when burnt in a kerosene lantern

EFker tCO2/GJ Fixed The specific CO2-emissions of kerosene

CFi,v,LFR - Monitored/Calculated

This factor corrects the total number of lamps of type i by the share of these lamps that were found to be operational according to the sampling in period v. The statistical error is included in this parameter (confidence level 90%).

Where:

𝐶𝐹𝑖,𝑣,𝐿𝐹𝑅 = 1 − (𝐿𝐹𝑅𝑖,𝑣 + 𝑧 ∗ √𝐿𝐹𝑅𝑖,𝑣∗(1−𝐿𝐹𝑅𝑖,𝑣)

𝑛𝑖,𝑣,𝑡𝑜𝑡𝑎𝑙)


CFi,v,LFR - Calculated This factor corrects the total number of lamps of type i by the share of these lamps that were found to be operational according to the sampling in period v. The statistical error is included in this parameter (confidence level 90%).

LFRi,v % Monitored Share of lamps of lamp type i in checked sample group gi,v not operational in period v.

z - Given Standard normal for a confidence level of 90%

ni,v,total - Monitored Total number of lamps checked for which a valid result was obtained.

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In line with the applied methodology and the registered PoA, project emissions and leakage emissions are not present and hence not included. For cookstoves: ERy = By,savings * fNRB,y * NCVbiomass * EFprojected_fossilfuel Where: ERy = Emission reductions during the year y in tCO2e By,savings = Quantity of woody biomass that is saved in tonnes f NRB,y = Fraction of woody biomass saved by the project activity in year y that can be

established as non-renewable biomass NCV biomass = Net calorific value of the non-renewable woody biomass that is substituted

(IPCC default for wood fuel, 0.015 TJ/tonne) EFprojected_fossilfuel = Emission factor for the substitution of non-renewable woody biomass by

similar consumers. Use a value of 81.6 tCO2/TJ In the typical case in which a single sample is used, quantity of woody biomass saved will be calculated using Option 2 from AMS II.G version 3:

Where: Bold = Quantity of woody biomass used in the absence of the project activity in tonnes

old = (1) A default value of 0.10 may be optionally used if the replaced system is a three-stone fire, or a conventional system with no improved combustion air supply or flue gas ventilation system, i.e. without a grate or a chimney; (2) for other types of systems a default value of 0.2 may be optionally used

new = Efficiency of the system being deployed as part of the project activity (fraction), as determined using the Water Boiling Test (WBT) protocol. Use weighted average values if more than one type of system is being introduced by the project activity

2) Determination of the Share of Non-Renewable Biomass The value used for the proposed CPA is the country level value of 0.8726 or state level values whichever is lower. 3) Leakage The methodology requires that project proponents investigate multiple sources of leakage. In the case of the project activities included in this PoA, leakage risks are very low as explained here for each of the areas of leakage risk discussed in Section 13(a) of the methodology:

)

new

old old y,savings η

η (1- B B =

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a) The use/diversion of non-renewable woody biomass saved under the project activity by non-project households/users that previously used renewable energy sources.

• The baseline technologies being displaced in the typical project activity areas included in this PoA are very simple technologies such as 3-stone stoves, very primitive cookstoves, and kerosene lamps. These technologies are commonly available and used only to meet the basic needs of households. The fuel costs for such technologies are greater than those for lower emitting technologies, which are perceived as more desirable both because of fuel savings and other development benefits, such as reduced smoke. Consequently, it would be extremely unusual for someone outside the project boundary to use a displaced baseline technology in place of a lower emitting technology. Furthermore, the drivers of usage for such stoves are basic needs and the amounts of fuel users can afford, rather than availability of the baseline technologies themselves. Therefore, availability of a displaced baseline technology will not drive increased usage. In the low number of cases in which a displaced baseline technology is used by a different household it would be more likely be more efficient and higher quality than the one it replaces, so is more likely to reduce fuel usage while increasing the level of service within a context of meeting basic needs.

• As described above, in the typical areas of the project activities, most people do not have access to lower-emitting energy sources and, those that do have no incentive to switch to non-renewable biomass or fossil fuels. Therefore, the risk of this type of leakage is very low

However, to take the conservative approach, a leakage adjustment of 95%, as per AMS II.G. ver. 03, has been applied to ER calculations.

B.4.2. Data and parameters fixed ex ante

For solar lighting products:

Data / Parameter LEker

Data unit Lumen/W

Description The specific luminous efficiency of kerosene when burnt in a kerosene lantern

Source of data Jean-Paul Louineau, Modibo Dicko, Peter Fraenkel, Roy Barlow and Varis Bokalders; Rural Lighting: A Guide for Development Workers, Intermediate Technology (IT) Publications in association with The Stockholm Environment Institute 1994

Value(s) applied 0.13

Choice of data or Measurement methods and procedures

Louineau et al (1994) state an efficiency range of 0.05 to 0.21 lumens/W for hurricane kerosene lanterns. Another study by the World Bank states an efficiency of 0.1 lumen/W for hurricane lanterns. Values for the widely used homemade wick lamps are scarcely available as designs vary. Anyway, these lamps have much lower efficiencies than hurricane lanterns. It is assumed that the kerosene lamp model in the baseline is a hurricane lamp. This is conservative since the vast majority of households use self-made kerosene lanterns without a glass cover, which are less efficient due to wind disturbance and very basic design. The average efficiency value of 0.13 lumen/watt for hurricane lamps from Louineau et al (1994) is chosen, being conservative with respect to the lower value of 0.1 lumen/W provided by the World Bank.

Purpose of data Calculation of baseline emissions

Additional comment GS approved the use of this parameter and value applied for D.Light project. This value is also approved in the registered PoA-DD Section page 45 to 46. The parameter is fixed for the entire crediting period.

Data / Parameter EFker

Data unit tCO2/GJ

Description The specific CO2 emissions of kerosene

Source of data 2006 IPCC guidelines for National Greenhouse Gas inventories


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The default value of other kerosene in 2006 IPCC guidelines for National Greenhouse Gas Inventories is 71.900 tCO2/TJ.


Additional comment The parameter is fixed for the entire crediting period.

Data / Parameter z

Data unit n/a

Description Standard normal for a confidence interval of 90%

Source of data Köhler, Schachtel, Voleske, 2002; Biostatistik, Springer Verlag Berlin Heidelberg; Tafel 2, p. 279

Value(s) applied 1.290 1.645; 1.96


This is the statistical standard value for standard normal for a confidence level of 90% for a one-sided test, and 90% and 95% for a two-sided test, respectively.


Additional comment

For improved cook stoves:

Data / Parameter fNRB,y

Data unit Fraction

Description Fraction of woody biomass saved by project activity in year y that can be established as non-renewable biomass

Source of data Forest Survey of India. (2011). India State of Forests Report. Government of India, Ministry of Environment & Forests. Chapter 2 Forest Cover and Chapter 7 Production & Consumption of Forest Resources. Food and Agriculture Organization. (2010). Forest Resource Assessment India Country Report. Ravindranath, N.H., et al. (2001). Forestry for Sustainable Biomass Production and Carbon Sequestration in India. Mitigation and Adaptation Strategies for Global Change, 6:233-256. Table AI. Projected and sustainable rates of extraction from forests and plantation.

Value(s) applied The fNRB values (lowest value between State level and national level) to be used for different states in India is as follows – Andhra Pradesh - 0.8726 Arunachal Pradesh - 0.1045 Assam - 0.8726 Bihar - 0.8726 Chattisgarh - 0.7746 Gujarat - 0.7796 Haryana - 0.4465 Himachal Pradesh - 0.7611 Jammu and Kashmir - 0.7238 Jharkhand - 0.8637 Karnataka - 0.8726 Kerala – 0.8726 Madhya Pradesh - 0.8726 Maharashtra - 0.8314 Orissa - 0.8726 Punjab- 0.7252 Rajasthan - 0.8726 Tamil Nadu - 0.8726 Uttaranchal - 0.8726 Uttar Pradesh - 0.8726 West Bengal - 0.8726 Meghalaya – 0.8726 The fNRB,y value for India is 0.8726 (This value is used for ex-ante calculation)

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All data used in the fNRB calculation is the most recently published government data available. Household woody biomass demand was estimated by the Forest Survey of India (FSI) using a national survey whose findings were reported in the 2011 India State of Forests Report. FSI also conducts an assessment of the forest cover of the entire country, which is carried out at an interval of two years by interpretation of remote-sensing satellite data. The sustainable fuelwood extraction rates used are based on a study by N.H. Ravindranath, P. Sudha, and S. Rao, which was published by the Mitigation and Adaptation Strategies for Global Change journal in 2001.


Additional comment In line with the PoA-DD, the lower value between state level fNRB,y and India level fNRB,y is used for the CPA. As mentioned in the PoA-DD, the state of implementation within the boundary of India and fNRB,y values will be calculated and fixed for the crediting period of the CPA at the time of its inclusion. Along with other states mentioned in the PoA-DD, the fNRB,y value for the State of Meghalaya is presented in this CPA-DD. The PoA-DD mentions that the most recent FSI report will be referred to at the time of CPA inclusion. The FSI reports for 2013, 2015, 2017 are referred to and they don’t contain the information (i.e. amount of non-renewable woody biomass and amount of demonstrably renewable biomass) required to calculate the fraction of non-renewable biomass for this CPA. Hence, the 2011 FSI report is referred to. The State level fNRB,y values for the States are Andhra Pradesh (0.9578), Arunachal Pradesh (0.1045), Assam (0.9691), Bihar (0.9176), Chhattisgarh (0.7746), Gujarat (0.7796), Haryana (0.4465), Himachal Pradesh (0.7611), Jammu and Kashmir (0.7238), Jharkhand (0.8637), Karnataka (0.9553), Kerala (0.9692), Madhya Pradesh (0.9136), Maharashtra (0.8314), Orissa (0.9165), Punjab (0.7252), Rajasthan (0.9153),Tamil Nadu (0.9691),Uttaranchal (0.8811), Uttar Pradesh (0.8792) ,West Bengal (0.9624) and Meghalaya (0.9560). The Indian country level value of fNRB,y is 0.8726. For the purpose of calculating the ex-ante emission reductions, the country level fNRB value is being used. The reason is that there is a phased implementation of CEPs in this CPA. The states of future sales are determined based on demand from customers. For calculation of emission reductions at time of issuance, the lower value between fNRB,y at state level and fNRB,y at country level (in line with the state level values given in the table above), will be used.

Data / Parameter NCVbiomass

Data unit TJ/tonne

Description Net calorific value of non-renewable woody biomass that is substituted (IPCC default for wood fuel, 0.015 TJ/tonnes)

Source of data The net calorific value of woody biomass is as given in 2006 IPCC Guidelines Reference: 2006 IPCC Guidelines for National Greenhouse Gas Inventories Volume 2: http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol2.html



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Data / Parameter EFprojected_fossilfuel

Data unit tCO2/TJ

Description Emission factor: substitution of non-renewable biomass by similar consumers

Source of data AMS-II.G. Version 3


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Data / Parameter Qbiomass

Data unit Tonnes/household/year

Description Quantity of woody biomass per appliance used in absence of project activity in tonnes

Source of data Forest Survey of India (FSI), State of Forests 2011 report

Value(s) applied

The state level Qbiomass values to be used are –

Andhra Pradesh - 1.46 Arunachal Pradesh - 2.37 Assam - 2.39 Bihar - 0.96 Chattisgarh- 0.98 Gujarat- 1.24 Haryana- 1.00 Himachal Pradesh- 0.97 Jammu and Kashmir- 0.97 Jharkhand- 1.18 Karnataka- 2.21 Kerala- 2.07 Madhya Pradesh- 1.26 Maharashtra- 0.91 Orissa- 1.16 Punjab- 1.28 Rajasthan- 1.75 Tamil Nadu- 1.14 Uttaranchal- 1.72 Uttar Pradesh- 0.65 West Bengal- 1.24 Meghalaya – 2.81 Average Qbiomass value – 1.44 (Used for ex-ante ER calculation)


Detailed calculation of this parameter for different states is given in Section B.3 and Emission reduction calculation sheet.


Additional comment This parameter is fixed for the entire crediting period. For cookstove sales, the value for Qbiomass is calculated using the FSI, State of Forests 2011 report. As mentioned in the PoA-DD, the state of implementation within the boundary of India and Qbiomass values will be calculated and fixed for the crediting period of the CPA at the time of its inclusion. Alongwith other states mentioned in the PoA-DD, the Qbiomass value for the State of Meghalaya is presented in this CPA-DD. The FSI 2011 report is the latest report with the information on household woody biomass demand. FSI has released two further reports in 2013, 2015 and 2017, however, these do not have the information on socio-economic contribution of forests: production and consumption of forest resources in India. More specifically, these subsequent reports do not contain information on the ‘number of persons using fuelwood’, ‘total quantity of fuelwood used for cooking’. Also, the number of people in a household in each state is taken from 2011 census data as the next India wide census will be conducted only in 2021.

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For the purpose of calculating the ex-ante emission reductions, the average value (1.44) of all states is being used. The reason is that there is a phased implementation of CEPs in this CPA. The states of future sales are determined based on demand from customers and hence the average value is used to calculate ERs for inclusion. For calculation of emission reductions at time of issuance, the actual state level values given in this table above will be used.

Data / Parameter LAF

Data unit Fraction

Description Net to gross adjustment factor

Source of data AMS-II.G. version 03



Default value as prescribed by methodology applied.


Additional comment This parameter is fixed for the entire crediting period. According to the methodology, default factor of 0.95 can be used to account for leakage related to the non-renewable woody biomass saved by the proposed SSC-CPA.

B.4.3. Ex ante calculation of emission reductions

>> For solar lighting products: As explained above, the emissions reductions for solar projects under AMS-I.A. are determined to be the same as the baseline emissions. Therefore, the equations for calculating the emissions reductions are: The per-lamp baseline emissions are calculated in Baseline Step 3. To calculate total emission reductions, these must be aggregated across all lamps in use in the period under consideration. This is done using the following equations, as per methodology approved for use in D.Light PDD, GS448: Total baseline emissions for period v are calculated as the sum of the baseline emissions of each lamp type i in the period:

(Eq. 2)


𝐵𝐸𝑣 tCO2 Calculated Emissions generated in the absence of the project activity in period v by all lamps

𝐵𝐸𝑖,𝑣 tCO2 Calculated Emissions generated in the absence of the project activity in period v by all lamps of type i

Ex post baseline emission for each lamp type i is calculated with the following equation:

(Eq. 3)


𝐵𝐸𝑖,𝑣 tCO2 Calculated Emissions generated in the absence of the project activity in period v by all lamps of type i

𝑁𝑖,𝑎 - Monitored The total number of solar lamps of type i deployed in period a

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𝑑𝑖,𝑎,𝑣 Days Monitored/calculated

Average number of days lamps of type i that have been deployed in period a were operating in period v

𝑙𝑖 Lumen Monitored (once per lamp type)

Nominal lumen output of solar lamps of the type I deployed as part of the project activity

ℎ Hours/day Fixed Average operating hours of kerosene lamps in the baseline

𝐿𝐸𝑘𝑒𝑟 Lumen/W Fixed The specific light output of kerosene when burnt in a kerosene lantern

𝐸𝐹𝑘𝑒𝑟 tCO2/GJ Fixed The specific CO2-emissions of kerosene

𝐶𝐹𝑖,𝑣,𝐿𝐹𝑅 - Monitored/Calculated

This factor corrects the total number of lamps of type i by the share of these lamps that were found to be operational according to the sampling in period v. The statistical error is included in this parameter (confidence level 90%).

Where:

𝐶𝐹𝑖,𝑣,𝐿𝐹𝑅 = 1 − (𝐿𝐹𝑅𝑖,𝑣 + 𝑧 ∗ √𝐿𝐹𝑅𝑖,𝑣∗(1−𝐿𝐹𝑅𝑖,𝑣)

𝑛𝑖,𝑣,𝑡𝑜𝑡𝑎𝑙) (Eq. 4)


𝐶𝐹𝑖,𝑣,𝐿𝐹𝑅 - Calculated This factor corrects the total number of lamps of type i by the share of these lamps that were found to be operational according to the sampling in period v. The statistical error is included in this parameter (confidence level 90%).

𝐿𝐹𝑅𝑖,𝑣 - Monitored Share of lamps of lamp type i in checked sample group 𝑔𝑖,𝑣 not operational in period v.

𝑧 - Given Standard normal for a confidence level of 90%

𝑛𝑖,𝑣,𝑡𝑜𝑡𝑎𝑙 - Monitored Total number of lamps checked for which a valid result was obtained.

In line with the applied methodology and the registered PoA, project emissions and leakage emissions are not present and hence not included. Emission reduction calculation:

Parameter Symbol Definition Value Unit Source

Ni,a The total number of solar lamps of type i deployed in period a 1 Number

To be monitored

di,a,v

Average number of days lamps of type i that have been deployed in period a were operating in period v 365 Days

Assumption for ex-ante emission reduction calculation

li

Nominal lumen output of solar lamps of the type I deployed as part of the project activity 116.9 Lumen

The PoA-DD prescribes a cap of 116.9 Lumens for individual household with solar lighting systems implemented under the PoA and hence a Lumen value of 116.9 is applied. For all

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solar lighting systems, the Lumen value will be capped at 116.9 for individual households.

h Average operating hours of kerosene lamps in the baseline 3.5 hrs/day

Methodology default

LEker

The specific light output of kerosene when burnt in a kerosene lantern 0.13

Lumen/Watt

Jean-Paul Louineau, Modibo Dicko, Peter Fraenkel, Roy Barlow and Varis Bokalders; Rural Lighting: A Guide for Development Workers, Intermediate Technology (IT) Publications in association with The Stockholm Environment Institute 1994

EFker The specific CO2 emission factor of kerosene 0.0719 tCO2/GJ

2006 IPCC guidelines for National Greenhouse Gas inventories

CFi,v,LFR

This factor corrects the total number of lamps of type i by the share of these lamps that were found to be operational according to the sampling in period v. The statistical error is included in this parameter (confidence level 90%). 100% Estimate

Emission Reduction per solar lighting system

Emissions reductions generated by 1 solar lighting system 0.2973 Calculated

Total emission reductions for solar lighting for all 75,000 installations projected for Year 1= 75,000 X 0.2973 = 22,301 tCO2 For improved cook stoves: 1) Emissions Reductions ERy = By,savings * fNRB,y * NCVbiomass * EFprojected_fossilfuel Where: ERy = Emission reductions during the year y in tCO2e

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By,savings = Quantity of woody biomass that is saved in tonnes f NRB,y = Fraction of woody biomass saved by the project activity in year y that can be

established as non-renewable biomass NCV biomass = Net calorific value of the non-renewable woody biomass that is substituted

(IPCC default for wood fuel, 0.015 TJ/tonne) EFprojected_fossilfuel = Emission factor for the substitution of non-renewable woody biomass by

similar consumers. Use a value of 81.6 tCO2/TJ In the typical case in which a single sample is used, emission reductions will be calculated using Option 2 from AMS II.G: By,savings = Bold * (1 - ƞold / ƞnew) Where: Bold = Quantity of woody biomass used in the absence of the project activity in tonnes

old =1. Efficiency of the system being replaced, measured using representative sampling methods or based on referenced literature values (fraction), use weighted average values if more than one type of system is being replaced;

2. A default value of 0.10 may be optionally used if the replaced system is a three-stone fire, or a conventional system with no improved combustion air supply or flue gas ventilation system, i.e. without a grate or a chimney; for other types of systems a default value of 0.2 may be optionally used

new = Efficiency of the system being deployed as part of the project activity (fraction), as determined using the Water Boiling Test (WBT) protocol. Use weighted average values if more than one type of system is being introduced by the project activity

2) Determination of the Share of Non-Renewable Biomass The lower value between state level fNRB,y and India level fNRB,y will be used as per the PoA-DD to calculate the emission reductions for issuance. In the calculation of the ex-ante emission reductions at time of inclusion, country level fNRB,y of 0.8726 is used as the states in which sales under this CPA will be made is based on demand from customers and cannot be determined at this stage. 3) Leakage The methodology requires that project proponents investigate multiple sources of leakage. In the case of the project activities included in this PoA, leakage risks are very low as explained here for each of the areas of leakage risk discussed in Section 13(a) of the methodology:

a) The use/diversion of non-renewable woody biomass saved under the project activity by non-project households/users that previously used renewable energy sources.

• The baseline technologies being displaced in the typical project activity areas included in this PoA are very simple technologies such as 3-stone stoves, very primitive cookstoves, and kerosene lamps. These technologies are commonly available and used only to meet the basic needs of households. The fuel costs for such technologies are greater than those for lower emitting technologies, which are perceived as more desirable both because of fuel savings and other development benefits, such as reduced smoke. Consequently, it would be extremely unusual for someone outside the project boundary to use a displaced baseline technology in place of a lower emitting technology. Furthermore, the drivers of usage for such

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stoves are basic needs and the amounts of fuel users can afford, rather than availability of the baseline technologies themselves. Therefore, availability of a displaced baseline technology will not drive increased usage. In the low number of cases in which a displaced baseline technology is used by a different household it would be more likely be more efficient and higher quality than the one it replaces, so is more likely to reduce fuel usage while increasing the level of service within a context of meeting basic needs.

• As described above, in the typical areas of the project activities, most people do not have access to lower-emitting energy sources and, those that do have no incentive to switch to non-renewable biomass or fossil fuels. Therefore, the risk of this type of leakage is very low.

However, to take the conservative approach, a leakage adjustment of 95%, as per AMS II.G ver 03, has been applied to ER calculations: Grameen Greenway Smart stove:

Parameter Symbol Definition Value Units Source

Qbiomass

Baseline fuelwood consumption in each household in the project boundary 1.44

Tonnes/year

The data derives from historical data obtained from the Forest Survey of India, State of Forests Report 2011. Average Qbiomass of all Indian States

nold Baseline stove efficiency 0.1 -

A default value of 0.10 may be optionally used if the replaced system is a three-stone fire, or a conventional system with no improved combustion air supply or flue gas ventilation system, i.e. without a grate or a chimney (value cited in AMS-II.G. version 3)

nnew Project stove efficiency 25.19 %

Performance testing report for Grameen Greenway Jumbo stove given by Biomass Cookstove Testing Centre, Department of Renewable Energy Engineering, College of Technology and Engineering, Maharana Pratap University of Agriculture and Technology dated 24/05/2013

fNRB,y Fraction of non-renewable biomass 0.8726 Fraction

Country level fNRB,y (calculated from the Forest Survey of India, State of Forests Report 2011) used for inclusion

NCVBiomass Net calorific value of biomass 0.0156

TJ/Tonnes

IPCC default value cited in AMS-II.G version 3

Conversion Factor 0.00417

GWh/Tonnes

Default

EFprojected fossil fuel

Emission factor for the substitution of non-renewable woody biomass by similar consumers. 81.6 tCO2/TJ

As per AMS-II.G version 3

LAF Net to gross adjustment factor 0.95 Fraction


By,Saving Quantity of woody biomass that is saved

0.87 Tonnes/year Calculated

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ER per household 0.9175

tCO2/cookstove Calculated

Emission reductions for first year projection from Grameen Greenway Smart stove = 2,000 * 0.9175 =1,835 tCO2 Grameen Greenway Jumbo stove:

Parameter Symbol Definition Value Units Source

Qbiomass

Baseline fuelwood consumption in each household in the project boundary 1.44

Tonnes/year

The data derives from historical data obtained from the Forest Survey of India, State of Forests Report 2011. Average Qbiomass value of all Indian States

nold Baseline stove efficiency 0.1 -

A default value of 0.10 may be optionally used if the replaced system is a three-stone fire, or a conventional system with no improved combustion air supply or flue gas ventilation system, i.e. without a grate or a chimney (value cited in AMS-II.G. version 3)

nnew Project stove efficiency 31.17 %

Performance testing report for Grameen Greenway Jumbo Stove given by Indian Institute of Technology, School of Materials Science and Technology, Banaras Hindu University, dated 17/12/2015

fNRB,y Fraction of non-renewable biomass 0.8726 Fraction

Country level fNRb,y (calculated from the Forest Survey of India, State of Forests Report 2011) used for inclusion.

NCVBiomass Net calorific value of biomass 0.0156

TJ/Tonnes

IPCC default value cited in AMS-II.G version 3

Conversion Factor 0.00417

GWh/Tonnes

Default

EFprojected fossil fuel

Emission factor for the substitution of non-renewable woody biomass by similar consumers. 81.6 tCO2/TJ


LAF Net to gross adjustment factor 0.95 Fraction


By,Saving Quantity of woody biomass that is saved

0.9793 Tonnes/year Calculated

ER per household 1.0334

tCO2/cookstove Calculated

Emission reductions for first year projection from Grameen Greenway Jumbo stove = 19,000 * 1.0334 = 19,634 tCO2 Total Emission reductions for first year projections from Improved cookstove = 1,835+19,634= 21,469 tCO2 Leakage No leakage emissions from solar lighting systems

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Emissions reductions Emissions reductions will be calculated as: ERy = By,savings * fNRB,y * NCVbiomass * EFprojected_fossilfuel Hence, total emission reductions from this CPA in the first year = 43,770 tCO2

B.4.4. Summary of ex ante estimates of emission reductions

SOLAR:

Year Baseline

emissions (t CO2e)

Project emissions (t CO2e)

Leakage (t CO2e)

Emission reductions

(t CO2e)

Year 1 22,301 - - 22,301

Year 2 46,089 - - 46,089

Year 3 59,469 - - 59,469

Year 4 80,284 - - 80,284

Year 5 95,151 - - 95,151

Year 6 297,347 - - 297,347

Year 7 356,816 - - 356,816

Total 957,457 - - 957,457

Total number of crediting years

7

Annual average over the crediting period

136,780 - - 136,780

IMPROVED COOKSTOVES:

Year Baseline

emissions (t CO2e)


Leakage (t CO2e)

Emission reductions

(t CO2e)

Year 1 21,469 - - 21,469

Year 2 21,469 - - 21,469

Year 3 21,469 - - 21,469

Year 4 21,469 - - 21,469

Year 5 21,469 - - 21,469

Year 6 21,469 - - 21,469

Year 7 21,469 - - 21,469

Total 150,280 - - 150,280


7


21,469 - - 21,469

TOTAL:

Year Baseline

emissions (t CO2e)


Leakage (t CO2e)

Emission reductions

(t CO2e)

Year 1 43,770 - - 43,770

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Year 2 67,557 - - 67,557

Year 3 80,938 - - 80,938

Year 4 101,752 - - 101,752

Year 5 116,620 - - 116,620

Year 6 318,816 - - 318,816

Year 7 378,285 - - 378,285

Total 1,107,738 - - 1,107,738


7


158,248 - - 158,248

B.5. Monitoring plan

B.5.1. Data and parameters to be monitored

Solar lighting system parameters to be monitored

Data / Parameter ln

Data Unit Lumens

Description Lumen output of each solar lamp n deployed as part of project activity

Source of data Product manufacturer specification

Value(s) applied 116.9 Lumen

Measurement methods and procedures

Will be recorded at time of sale/installation in MEC Credit Tracker system

Monitoring frequency Annual

QA/QC procedures Each light installation will be geocoded (GPS coordinate or other specific location data) or provide address/location of household in the MEC Tracker System. Associated data will reside in the MEC Tracker Database, allowing each installation to be monitored on a regular basis.

Purpose of data To calculate baseline emissions

Additional comment If lamp types allow for different settings of light intensity, the conservative value shall be chosen unless an accurate average value is substantiated through a representative sample survey (90% confidence interval +/- 10% error). A variety of solar lighting systems will be offered under the proposed SSC-CPA. The lumen output for the models sold under the proposed SSC-CPA will be used for calculating the final emission reduction. In line with the information given in the eligibility criteria section in this CPA-DD, the lumen value for solar lighting systems in this CPA will be capped at 116.9 Lumen for individual households. In Section B.4.3 formula for emission reduction calculation, this parameter is mentioned as “li”.

Data / Parameter Ni,a

Data Unit Lamps

Description Total number of solar lamps of type i that have been deployed in period a

Source of data Primary data collected by PO/CPA implementer and recorded in Credit Tracker

Value(s) applied 75,000 for Year-1


Target population: all solar lamps of type i that have been deployed Objective: Establish the number of solar lamps of type i deployed during period a as part of the proposed SSC-CPA. Description and Reliability Requirements: Primary data collection

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No sampling is applied to this parameter. All deployed solar lamps of type i will be recorded. Ni,a is adjusted according to actual operational days during a given monitoring period y. The sales date for each solar lamp of type i listed in Credit Tracker for proposed SSC-CPA signifies the start of operation for each solar lamp. The operational days of each solar lamp is divided by the total number of days of the current monitoring period to determine the adjusted Ni,anumber of solar lamps of type i in operation.


QA/QC procedures Each light installation will be geocoded (GPS coordinates or other specific location identifiers) in the MEC Tracker System. Associated data will reside in the MEC Tracker Database, allowing each installation to be monitored on a regular basis. The data in MEC tracker system can be crosschecked with the MIS system of the PO.


Additional comment -

Data / Parameter di,a,v

Data Unit Days

Description Average number of days lamps of type i that have been deployed in period a were operating in period v

Source of data Monitoring partner, Credit Tracker

Value(s) applied 365


Exact date of sale (in the case of solar lights) and installation (in the case of solar lighting systems) for all clean energy products is tracked by monitoring partners and recorded in Credit Tracker. For products newly sold/installed in period v, the date of sale or installation will be used to calculate total days of operation in period v. For products sold/installed prior to period v, di,a,v will be equal to the total number of days in period v. Target population: all solar lamps of type i that have been deployed Objective: Establish the number of days solar lamps of type I that have been deployed in period a were operating in period v. Description and Reliability Requirements: Primary data collection No sampling is applied to this parameter.


QA/QC procedures Results will be checked by contracted verifier


Additional comment The date in MEC tracker system can be crosschecked with the MIS system of the PO. Contracted verifier will check results.

Data / Parameter h

Data Unit Hours/day

Description Average operating hours of kerosene lamps in the baseline

Source of data Based on field survey results in baseline population.

Value(s) applied 3.5 (default value)


AMS I.A version 14 par.8(c) states: For the specific case of lighting devices a daily usage of 3.5 hours shall be assumed, unless it is demonstrated that the actual usage hours adjusted for seasonal variation of lighting is different based on representative sample survey (90% confidence interval +/-10% error) done for minimum of 90 days. In practice, usage of more than 3.5 hours/day is expected. A representative sample survey (90% confidence interval +/- 10% error) within the baseline population may be conducted. The results of the survey shall be checked during the following

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periodic verification by the contracted verifier and shall afterwards permanently replace the default value used for the relevant CPA.


QA/QC procedures Results will be checked by contracted verifier



Data / Parameter LFRi,v

Data Unit %

Description Lamp failure rate: Share of lamps of lamp type i in checked sample group gi,v operational in period v


Value(s) applied 0% (Ex-ante estimate). The real LFR shall be determined during annual monitoring


CME/PO/Monitoring partner will track usage status of all lamps (or solar lighting systems) from each quarterly of the year with results recorded in Credit Tracker. Any lamps that are non-operational (due to failure or disuse by owner) will be recorded as “failed” lamps. Lamp failure rate will be calculated as: LFR = (Number of failed lamps/Total number of lamps monitored)


QA/QC procedures The lamp failure rate will also be checked by the verifier. The LFR measure in use based on regular monitoring for the full portfolio of lamps will be down-rated as appropriate according to the verifier rating.



Data / Parameter CFi,v,LFR

Data Unit %

Description This factor corrects the total number of lamps of type i by the share of these lamps that were found to be operational according to the sampling in period v. The statistical error is included in the parameter (confidence level 90%) when 90/10 precision is not met. Otherwise, the mean value of LFR will be used.

Source of data LFRi,v

Value(s) applied 100%


The value is calculated using the recorded value for LFRi,v –

𝐶𝐹𝑖,𝑣,𝐿𝐹𝑅 = 1 − (𝐿𝐹𝑅𝑖,𝑣 + 𝑧 ∗ √𝐿𝐹𝑅𝑖,𝑣 ∗ (1 − 𝐿𝐹𝑅𝑖,𝑣)

𝑛𝑖,𝑣,𝑡𝑜𝑡𝑎𝑙

)


QA/QC procedures This value is calculated based on the results of other monitored parameters. Calculation results will be checked by the CME to confirm accuracy.



Data / Parameter n,i,v,total

Data Unit Lamps

Description Total number of lamps checked for which a valid result was obtained.


Value(s) applied 30


CME/PO/Monitoring partner will randomly and representatively track households contacted and reached for monitoring lamp usage status for each lamp type i in the monitoring period, p. This data will be recorded in Credit Tracker. Survey methods will be used.


QA/QC procedures Results will be checked by contracted verifier.


Additional comment As per the sampling procedure, a minimum of 30 samples is required to be checked for obtaining a valid result as this is a proportion based parameter.

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However, for some state/model combinations this could be lower as the total sales could be less than 30.

Data / Parameter Kerosene Usage in the Baseline

Data Unit n/a

Description Determination of whether or not the end user used kerosene for lighting prior to the project activity

Source of data Primary data collected by PO/CME/monitoring partner and recorded in Credit Tracker

Value(s) applied 100% For all sales made under this proposed SSC-CPA will provide data on the number of end users who confirmed using kerosene in the absence of the project activity.


Target population: all end users who purchased a solar lamp under a CPA included in this PoA Objective: Confirm whether or not the end user used kerosene for lighting prior to the project activity Description and Reliability Requirements: Primary data collection No sampling is applied to this parameter. All end users who purchased a solar lamp will be tracked.


QA/QC procedures Each light installation will be geocoded (GPS coordinates or other specific location identifiers) in the MEC Tracker System. Associated data will reside in the MEC Tracker Database, allowing each installation to be monitored on a regular basis.


Additional comment

Improved cookstove parameters to be monitored

Data / Parameter Nall

Data Unit Number

Description Total number of stoves disseminated

Source of data Credit Tracker Platform of stove installation records

Value(s) applied 21,000 for Year-1


Target population: All stoves disseminated (therefore all target populations). Objective: Establish the number of stoves disseminated Description and Reliability Requirements: Primary data collection, weighted average if multiple models. No sampling is applied to this parameter. All stoves disseminated, weighted average if more than one type. Each PO shall maintain these records in the Credit Tracker Platform


QA/QC procedures The CME will supervise the activities of the PO, providing training, guidelines and templates to facilitate accurate record keeping in the Credit Tracker Platform.



Data / Parameter CE

Data Unit Number of households

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Description Check of household contact information to ensure that no household is in more than 1 CPA under the PoA.

Source of data Credit Tracker Platform

Value(s) applied 0


The PoA restricts CPAs from implementing both AMS-III.AV and AMS-II.G. in order to eliminate cross-effects between cookstoves and water filters. The CME shall ensure that no household receives a cookstove under one CPA and a water filter under another CPA. Checking the household contact information contained in the Credit Tracker Platform to determine whether the same household is present in more than 1 CPA shall ensure this.


QA/QC procedures In the event that a household is found to have received a cookstove and water filter under different CPAs, the CME shall remove the household from the emission reductions calculations for one CPA.


Additional comment This parameter is only applicable if AMS-II.G. and AMS-III.AV. are implemented under different CPAs within the PoA.

Data / Parameter nnew

Data Unit %

Description Efficiency of the new efficient stoves

Source of data Water Boiling test

Value(s) applied Smart Cookstove (GSSV3) - 25.19% Jumbo Cookstove (GJS) - 31.17%


A Water Boiling Test will be carried out for a sample of that type of cookstoves in operation and only cookstove with rated efficiency of .2 or higher will be included in the proposed SSC-CPA. Target population: Systems deployed by model. Objective: Establish the thermal efficiency of the system/s deployed per stove model. Description and Reliability Requirements: Primary data collection (by means of the WBT), weighted average if multiple systems. Sampling Frame: Credit Tracker of each CPA as defined by sales date, appliance type, CEP unique identifier number, and end-user information. Sample Size and Desired Precision: Cross-CPA sampling will meet 95/10 Implementation: For the proposed SSC-CPA CPA, a standard test (water boiling test) by a dedicated expert team at minimum every two years that measures aging stove efficiency per stove type. A weighted average of stove sales for each vintage will be applied. This value will be used for ex-post emission reduction calculations. All data will be kept for 2 years following the crediting period or the last issuance of the CERs of the project activity.

Monitoring frequency Biennial

QA/QC procedures The CME/PO conducts water-boiling tests with expert assistance. Training will be provided to enumerators and testers or an expert third party is contracted to carry out tests.

Purpose of data For emission reduction calculation

Additional comment This parameter nnew is applicable only when AMS-II.G. step-6 option-2 is chosen for a given CPA.

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Data / Parameter POF

Data Unit Fraction

Description Product Operation Fraction

Source of data Survey

Value(s) applied 1


This is measured ex-post by investigation of the number of cookstove installations within the sampled cookstoves, which are operational. The PO maintains within the MEC Credit Tracker Platform a monitoring record of surveyed cookstoves on an annual basis. Then a sample of the CEPs is chosen for participation in the survey. If for example, the survey reveals that 90% of the sample is only found to be operational, then POF is 90%. Target population: Cookstoves disseminated through project activity Objective: Establish the product operation fraction of stoves disseminated through the project activity Description and Reliability Requirements: Primary data collection Sampling method: Field survey by a dedicated team at minimum every two years. Ex-post monitoring and surveys will determine the number of appliances still in operation. Multi-stage sampling technique will be used and a weighted average of stove sales for each vintage and appliance type will be applied. EB 67 Annex 6 Best Practices Examples Focusing on Sample Size and Reliability Calculations will be followed to determine sample size. Sampling Frame: Credit Tracker of proposed SSC-CPA as defined by sales date, appliance type, CEP unique identifier number, and end-user information. Sample Size and Desired Precision: This will be calculated in line with Guidelines on sampling and surveying for CDM PoAs and project activities Implementation: Field survey by a dedicated team at minimum every year. Ex-post monitoring and surveys will determine the number of appliances still in operation. All data will be kept for 2 years following the crediting period or the last issuance of the CERs of the project activity.


QA/QC procedures CME/PO provides guidance and training for conducting surveys and testing with expert party assistance.


Additional comment

Data / Parameter µold

Data Unit tonne wood/ year

Description Quantity of woody biomass used in the project activity by traditional stoves per household

Source of data Primary data collection through survey of household behaviour and/or field testing

Value(s) applied 0


According to AMS II.G v03 paragraph 2 (b), If baseline stoves continue to be used, monitoring shall ensure that the fuel-wood consumption of those stoves is excluded from Bold. Target population: Residential biomass users Objective and description: Establish the quantity of woody biomass used in the project activity by traditional stoves per household for each target population. Sampling Frame: Credit Tracker Database of proposed SSC- CPA as defined by sales of cookstoves.

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Sample Size and Desired Precision: Mean value determination, see PoA-DD Section B.7.2 Sample Method: Multi-stage sampling technique will be used and a weighted average of stove sales for each vintage and appliance type will be applied. EB 67 Annex 6 Best Practices Examples Focusing on Sample Size and Reliability Calculations will be followed to determine sample size. Implementation: The CPA shall measure changes in Bold displaced by the proposed SSC-CPA. A survey or field test will be conducted to determine the amount of fuel-wood still used in the project activity by traditional stoves. Survey questionnaires administered to a random sample of end users will elicit self-reported estimates of the amount of non-renewable biomass used per day in traditional stoves in parallel to the improved stove. The quantity of woody biomass still used by traditional stoves (µold) will be excluded from Bold. Alternatively, field-testing may measure fuel consumption by traditional stoves. A weighted average of stove sales for each vintage will be applied. This value will be used for ex-post emission reduction calculations. Once applied to a single SSC-CPA, all applicable future SSC-CPAs within the same PoA may choose to use such data to define the value if applying a single sampling design.


QA/QC procedures CME/PO provides guidance and training for conducting surveys and testing with expert party assistance.


Additional comment

Data / Parameter Ubaseline

Data Unit Fraction

Description Efficiency of system being replaced

Source of data End-User surveys

Value(s) applied 0.1 (methodological default for conventional system without improved combustion air supply), based on Jagadish, K.S. (2004). The development and dissemination of efficient domestic cook stoves and other devices in Karnataka. Current Science, Vol. 87, No.7.


Target population: all end users who purchased an improved stove under a CPA included in this PoA Objective: Confirm whether or not the end user used an unimproved stove prior to the project activity Description and Reliability Requirements: Primary data collection No sampling is applied to this parameter. The baseline system of all end users who purchase a stove will be tracked and recorded in the Credit Tracker. If the replaced system is a three-stone fire, or a conventional system with no improved combustion air supply or flue gas ventilation system, i.e. without a grate or a chimney, then the parameter value shall be .1. For other types of systems, a default value of 0.2 shall be used, unless evidence can be provided to justify an alternate value.


QA/QC procedures Each stove installation will be geocoded (GPS coordinates or other specific location identifiers) in the MEC Tracker System. Associated data will reside in the MEC Tracker Database, allowing each installation to be monitored on a regular basis.

Purpose of data Calculation of baseline emission

Additional comment

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B.5.2. Sampling plan

>> To reduce monitoring efforts a single sample is drawn based on which all of the parameters determined via sampling shall be monitored. The CME will determine the number of users/appliances monitored during sampling for each of the parameters separately. The reason is that the variation within the values obtained will be different for each parameter. Since the precision of a sampled parameter depends on the variation of its values, the necessary number of users/appliances to be monitored in order to achieve the 5% or 10% precision will also depend on the variation of values. Therefore, although the monitoring team will undertake monitoring of various parameters simultaneously and on the same sample, the PP may decide to stop monitoring of a particular parameter during the campaign once the required precision for this parameter is achieved. The monitoring team will continue to monitor appliances in the sample with respect to the remaining parameter(s) until again the required precision for these parameters is achieved. The following steps will be carried out for representative sampling, in consideration of the General Guidelines27 for sampling and surveys for small-scale CDM project activities. The monitoring team will continue to monitor appliances in the sample with respect to the remaining parameter(s) until again the required precision for these parameters is achieved. Statistical sampling using a random number generated will be used to select samples from sampling frames drawn from Credit Tracker for monitored parameters. Multi-stage sampling equations are provided below, but alternative sampling approaches may be used in accordance with EB 67 Annex 6 Best Practices Examples Focusing on Sample Size and Reliability Calculations, Paragraph 40. Multistage sample size is determined for Mean Values using28:

Where:

• (c) Minimum required number of clusters to be sampled.

• Confidence: o 90% = 1.645 (as indicated in the formula above) o 95% = 1.96 (1.645 in formula will be replaced)

• Precision: o 10% = 0.1 (as indicated in the formula above) o 5% = 0.05 (0.1 in formula will be replaced)

• (M) Total number of clusters (i.e. villages) = TBD from project database

• (N) Average number of units (HH) per a cluster = TBD from project database

• (u) Number of units that have been pre-specified per a cluster = TBD according to M and N.

• (Overallmean) Mean per unit from all clusters in the sample =

(𝛴 𝑀𝑒𝑎𝑛 𝑝𝑒𝑟 𝑢𝑛𝑖𝑡 𝑖𝑛 𝑎 𝑐𝑙𝑢𝑠𝑡𝑒𝑟)

𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑢𝑛𝑖𝑡𝑠 𝑖𝑛 𝑠𝑎𝑚𝑝𝑙𝑒

27http://cdm.unfccc.int/Reference/Guidclarif/ssc/methSSC_guid20.pdf

28 EB69 Annex05, Example 18.

http://cdm.unfccc.int/Reference/Guidclarif/ssc/methSSC_guid20.pdf

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• (Clustermean) Mean for all units (in other words, per cluster) from all clusters in the sample =

(𝛴 𝑀𝑒𝑎𝑛 𝑝𝑒𝑟 𝑐𝑙𝑢𝑠𝑡𝑒𝑟 𝑖𝑛 𝑡ℎ𝑒 𝑠𝑎𝑚𝑝𝑙𝑒)

𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑙𝑢𝑠𝑡𝑒𝑟𝑠 𝑖𝑛 𝑠𝑎𝑚𝑝𝑙𝑒

• (SDB) Standard deviation between clusters =

Therefore: SDB = √(SDB)2

Where:

o y = Total for the units sampled per cluster (TBD from the field, and according to N) o n = Number of clusters (TBD from the field, and according to M)

• (SDw) Average within clusters standard deviation =

√∑ (𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑢𝑛𝑖𝑡𝑠 𝑖𝑛 𝑐𝑙𝑢𝑠𝑡𝑒𝑟 ∗ (𝑆𝑡 𝐷𝑒𝑣 𝑏𝑒𝑡𝑤𝑒𝑒𝑛 𝑢𝑛𝑖𝑡𝑠 𝑖𝑛 𝑐𝑙𝑢𝑠𝑡𝑒𝑟)2)

𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑢𝑛𝑖𝑡𝑠 𝑎𝑐𝑐𝑟𝑜𝑠𝑠 𝑎𝑙𝑙 𝑐𝑙𝑢𝑠𝑡𝑒𝑟𝑠

Multi-stage sample size is determined for Proportional Values using29:

Where:

• (c) Minimum required number of clusters to be sampled.

• Confidence: o 90% = 1.645 (as indicated in the formula above) o 95% = 1.96 (1.645 in formula will be replaced)

• Precision30: o 10% = 0.1 (as indicated in the formula above) o 5% = 0.05 (0.1 in formula will be replaced)

• (M) Total number of clusters (i.e. villages) = TBD from the project database

• (N) Average number of units (HH) per a cluster = TBD from the project database

• (u) Number of units that have been pre-specified per a cluster = TBD according to M and N.

• (p) Mean for all units (in other words, per cluster) from all clusters in the sample =

(𝛴 𝑀𝑒𝑎𝑛 𝑝𝑒𝑟 𝑐𝑙𝑢𝑠𝑡𝑒𝑟 𝑖𝑛 𝑡ℎ𝑒 𝑠𝑎𝑚𝑝𝑙𝑒)

𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑐𝑙𝑢𝑠𝑡𝑒𝑟𝑠 𝑖𝑛 𝑠𝑎𝑚𝑝𝑙𝑒

29 EB69 Annex05, Example 14.

30According to the 69 Annex05, Page04, Paragraph 11 “Precision of 10 percent i.e. ±10% in this standard shall be interpreted as a proportion can describe either of the two possible scenarios of the success rate or the failure rate – for example (i) cook stove still operational or (ii) cook stove no longer operational. Project proponents may use the larger of the two proportions in the sample size calculation, that is p or (1-p), in any of the monitoring periods during the crediting period without having to revise the monitoring plan. The check on meeting the reliability requirement should be based on the larger of the two proportions.

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• (SDB) Standard deviation between clusters =

Therefore: SDB = √(SDB)2

Where:

o p = Mean for each unit sampled per cluster (calculated above) o n = Number of clusters (TBD from the field, and according to M)

• (SDw) Average within clusters standard deviation =

√∑(𝑉𝑎𝑟𝑖𝑎𝑛𝑐𝑒 𝑤𝑖𝑡ℎ𝑖𝑛 𝑒𝑎𝑐ℎ 𝑐𝑙𝑠𝑢𝑡𝑒𝑟)

𝑁𝑢𝑚𝑏𝑒𝑟 𝑐𝑙𝑢𝑠𝑡𝑒𝑟𝑠

A sample size calculation tool31 has been designed to describe step by step the method in place and to estimate the minimum sample needed to satisfy statistical requirements for each monitoring parameter according to its sampling approach. Thus, the sample size calculation tool to be used has been developed for each monitored parameter. Actual survey results will inform whether fewer or greater surveys will be needed to meet the required confidence/precision. Although the monitoring team will undertake monitoring of various parameters simultaneously and on the same sample, the CME may decide to stop monitoring of a particular parameter during the campaign once the required precision for this parameter is achieved. The monitoring team will continue to monitor appliances in the sample with respect to the remaining parameter(s) until the required precision for these parameters is achieved again. The coefficient of variation is estimated from recent monitoring data. In the case of parameters monitored for the first time the expected variation for that measure in the sample may be based on results from similar studies, pilot studies, or from the project planner’s own knowledge of the data. The sampling procedure may either consist of a single-stage process which randomly samples households across all the CPAs, or it may consist of a two-stage process whereby a sample of CPAs are randomly selected and within these, a random selection is made of installations. The required confidence/precision may be achieved through different combinations of across-CPA sample size and within-CPA household sample sizes; if less CPAs are surveyed, more houses within the CPAs will need to be surveyed to achieve the required precision, and vice versa. The relative costs and practicalities of surveying across several CPAs will be balanced against the relative costs and practicalities of household surveys and a decision taken as to the most efficient balance between across-CPA surveying and within-CPA surveying. For each monitoring period the following sampling procedures will be followed: Multistage sampling from CPA Project Databases Step 1: For each monitoring period contact details from end-users are collected for all, or a subset of, appliances deployed. This is stored in Credit Tracker. Step 2: In order to reflect the different age of the appliance (i.e. the different deployment dates), the relative share of appliance vintages within the total population of appliances deployed as recorded in

31 See Sample Size Calculation Tool provided to the DOE.

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Credit Tracker under the CPAs shall be established. Example: If after the second monitoring period, 75% of all appliances were deployed until the end of the first Monitoring Period, and 25% were deployed until the end of the second Monitoring Period, then the final selection shall also represent that share. Similarly, within each monitoring period, probability weighted sampling will reflect the number of appliance sold per 3-month quarter within a calendar year. Step 3: A sample of administrative clusters (e.g. states) is selected for each monitoring period y from the Credit Tracker by “probability proportional to size”-sampling, i.e. Government state clusters with a higher number of appliances deployed will have a higher chance to be selected than those with a smaller number of appliances. Step 4: A random sample of villages or MFI branches are selected from each selected administrative area. “Probability proportional to size” sampling will be applied, balanced with practical consideration of reaching villages in a cost-effective and timely manner. Step 5: Users within the selected villages will be randomly selected. The number of users to be selected shall be proportional to the size of sales in that administrative area.

B.5.3. Other elements of monitoring plan

>> Monitoring for typical SSC-CPAs is described below. The monitoring activity provides a framework for project preparation and monitoring processes that will be undertaken at the CPA level for each CPA, as required by the CDM rules. This schedule takes into account the key parameters that are needed during the crediting periods of the project. All required monitoring and documentation would be implemented, reported, consolidated and managed by the CME or a qualified expert partner to meet verification requirements. Monitored data will be stored in a suite of monitoring databases. These will be updated each monitoring period: Summary: 1. Each PO keeps a record of all the CEPs it installs in the MEC Credit Tracker Platform. The record includes the name, date of installation, model of CEP and location of the product. All records are screened by the CME and cross-checked with the PO records to confirm the installation record is authentic and no double counting occurs. 2. The values of the two emission reduction parameters required for ex-post ER calculation

(efficiency of CEPs ( ), number of CEPs still operating (POF) are found from sampling of CEP installations 3. The records kept in the MEC Credit Tracker Platform relate to paper copies of title transfer agreements received from individual households. Quality assurance The sampling approaches described above follow the CDM EB General Guidelines For Sampling and Surveys for Small Scale CDM Project Activities. This applies both to single-stage and two-stage approaches. Generalities The CME along with the PO will coordinate all ex-post monitoring activities in the PoA. The CME is ultimately responsible for implementing the monitoring plan, ensuring the quality of data obtained and the use of this data for emissions reduction calculations. The CME will provide the DOE with a single monitoring report for verification purposes for all CPA’s requesting issuance together. However, the actual field measurements to be conducted during monitoring (e.g. testing of ICS selected during sampling) will most likely be performed by third parties contracted to the CME and/or

newη

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PO. In the case of using contractors, however, the CME will still be responsible for setting the procedures and providing oversight and training to the contractors. The choice between conducting the actual monitoring activities itself or employing another organization (for example, local marketing firm, university etc.) will depend on locational, operational factors and financial factors. In any case, a local partner will be important for providing local insight in questionnaire design, interview technique and for gaining physical access to project beneficiaries to obtain accurate results during monitoring. Parameter values shall be estimated by sampling in accordance with the requirements in the applied methodology separately and independently for each of the CPAs included in a PoA except when a single sampling plan covering a group of CPAs is undertaken, in which case 95/10 confidence/precision is applied for the sample size calculation. A single sample plan will combine together the populations of all CPAs, and the sample size is determined and a single survey is undertaken to collect data e.g. if the parameter of interest is daily self-reported fuel consumption, it may be feasible to undertake a single sampling and survey effort spread across geographic regions of several CPAs when either homogeneity of included CPAs relative to the fuel usage can be demonstrated or the differences among the included CPAs is taken into account in the sample size calculation, such as proportional and weighted averages. If a sampling plan is developed for each CPA, and where there is no specific guidance in the applicable methodology, project proponents shall use 90/10 confidence/precision as the criteria for reliability of sampling efforts for small-scale project activities (according to EB 69 Annex 4). Sampling Objective – The sampling objective for each parameter is to determine via survey with statistically significant value for the emission reduction calculations.

Field Measurement Objective and data to be collected – This is defined in the ex-post monitoring tables.

Target population and sampling frame – The target population is the total population served under the PoA, and in the case of multi-stage sampling, the sampling frame is a complete listing of sub-groups of the study area/population which constitutes all the primary sampling units. In developing sampling frames the implementer of the survey effort shall compile a clear description of the target population, including those characteristics of the population, which define membership (as in the diagram below defining sampling frames). From the description and characteristic the implementer can then select a sampling frame appropriate for the study.

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Sample method – Multi-stage random sampling will be used, and detailed calculations are provided below. When project circumstances allow single stage simple random sampling will be applied per CDM guidelines EB 69 Annex 5. One example of a 2-stage random sampling approach would be to provide a first-stage sampling frame consisting of all households serviced across all CPAs categorized by region, methodology combination, end-user type, and CEP model combination – all listed by village. Random sampling of villages from the first-stage frame would provide a subset of areas to sample from. In the second stage, the sampling frame would consist of all households serviced in the randomly selected villages. Random sampling would then be conducted from the second-stage frame. To ensure a random sample selection, random number generators shall be applied. Each CEP in the target population is uniquely identifiable by its Serial ID number. Each CEP within a sampling frame can thus be allocated a Sample Selection Number in each monitoring period, starting at 1 and increasing up to the total number of CEPs in the Credit Tracker Platform for that pre-defined sampling frame. Applying the random number generators, the CEP can then be randomly chosen from the defined population up to the required sample size as calculated by the CME. This will be done for each group of CPAs within a defined sampling frame or for each CPA in the case that CPAs are not grouped up for monitoring.

Desired precision / expected variance and sample size – unless otherwise noted in the measurement methods and procedures section of the monitored parameter table in section B.7.1, and as allowed by applicable methodology, the sample size will be chosen for a 90/10 precision (90% confidence interval and 10% margin of error); except when a single sampling plan covering a group of CPAs is undertaken, in which case 95/10 confidence/precision is applied for the sample size calculation.

During sampling there may be non-response from the target population. Over-sampling by 20% may be used to avoid non-response, however, sampling may be cease once required confidence/precision is met.

Implementation - The sampling for surveyed data will be implemented consistent with the approach described above.

Monitoring shall be carried out by the operating entity of the CPA according to the procedures and monitoring framework established below and will be submitted to the managing entity. The managing entity will store the data in an electronic database. Primary data will be stored by the implementing entities/operators:

The MEC Credit Tracker Platform is used to keep detailed records of all installations under each CPA. Each installation is monitored annually to check usage status. The Project shall monitor a representative sample of households that have received both stoves and water technologies. All monitoring records are maintained in the Credit Tracker Platform. 1. The PO maintains in the Credit Tracker Platform a record of all clean energy products that are installed 2. The PO identifies the exact location of the CEP using GPS location and/or address of the household or organization. 3. The emissions parameters required for ex-post management are also maintained in the Credit Tracker Platform. These include the number of solar lighting systems still in operation, and then performance of the solar lighting systems. These parameters are determined through a sampling study as described above. 4. The CME uses the Credit Tracker Platform to cross-check the new records with the existing Platform in order to confirm that the installation record is authentic and that no double-counting occurs.

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5. The electronic files holding installation records are backed up on the Internet, reducing risk of any loss of data. 6. All monitored data required for verification and issuance will be kept for two years after the end of the crediting period or the last issuance of CERs for the PoA, whichever occurs later. The unique system ID number which is linked to a gps location and/or verified address eliminates any risk of double-counting between CPAs. Organizational Diagram of Monitoring Plan

Quality Assurance/Quality control As the PoA is intended to include multiple regions within India with a high level of cultural diversity as well as different end user groups, there is no “one size fits all” approach for dealing with these issues. However, in order to avoid many of these problems the CME will undertake the following strategies, tailoring the specific approach to the local circumstances: 1) Ensuring end user awareness. At the time of sale, the CEP customer is made aware that they are required to participate in monitoring activities. This will be via training sales personnel to explain the importance of monitoring to each customer, and during regularly scheduled microfinance group meetings for end-users. 2) Questionnaire design. The design of the questionnaire will ensure that the questions are non-intrusive and easy to understand for both the interviewee and interviewer. 3) Drawing on local knowledge. The local contractors to be hired by the CME in each region will play an important role in tailoring the approach to suit local circumstances. For example, in some instances, it may be essential for a local person to conduct the interview in order to obtain accurate results. 4) Quality of contractors. Any third parties hired by the CME to carry out sampling will be required to demonstrate a high level of cultural awareness, local language skills and appropriate experience with data entry and data management. The CME will ensure that contractors are adequately trained for the tasks they are contracted for (e.g. carrying out of WBTs in line with a methodology supported by an appropriate international body such as PCIA). Training will also be provided on how to deal with non-responses, refusals and other problems should these occur.

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SECTION C. Start date, crediting period type and duration

C.1. Start date of CPA

>> 30/11/2019 i.e. date of sale of first clean energy product (Improved cookstove or solar product under the proposed SSC-CPA. (Sales invoice for the first CEP in this CPA will be provided to the verifier at the time of verification) The CME hereby confirms that no CEP have been sold under this CPA before the start date of the PoA.

C.2. Expected operational lifetime of CPA

>> 21 years.

C.3. Crediting period of CPA

C.3.1. Type of crediting period

>> Renewable crediting period

C.3.2. Start date of crediting period

>> The start date of the crediting period will be 30/11/2019 or the date of inclusion of the CPA in the PoA whichever is later.

C.3.3. Duration of crediting period

>> 7 years

SECTION D. Environmental impacts

D.1. Analysis of environmental impacts

>> In accordance with the CDM-SSC-CPA-DD form, this section is not completed since this information is provided at the PoA level.

D.2. Environmental impact assessment

>> No EIA is required as per host country guidelines for the technologies implemented.

SECTION E. Local stakeholder consultation

E.1. Modalities for local stakeholder consultation

>> For solar lighting devices and improved cookstoves: Local holder consultation was held on 04/09/2018 Location of meeting: SKDRDP Head Office, Dharmasthala Stakeholders were invited by email to attend one of two telephonic conference calls (arranged at different times to accommodate various time zones on the same day). Stakeholders also had the option to submit comments by email. Stakeholders were notified of the meeting 15 days before the date of the meeting. Physical stakeholder consultation meetings were held by PO in Dharmasthala on 04/09/2018.

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The invited stakeholders included representatives from NGOs, development agencies, and businesses working in issues of sustainable development, household-level clean energy, microfinance, and gender among low income populations in India. Minutes were recorded for both consultations that occurred by conference call, and additional feedback submitted by email was also recorded in the Local Stakeholder Consultation template.32 For improved cookstoves: Local holder consultation was held on 06/09/2018 Location of meeting: Hotel Ramyas, Trichy Stakeholders were invited by email to attend one of two telephonic conference calls (arranged at different times to accommodate various time zones on the same day). Stakeholders also had the option to submit comments by email. Stakeholders were notified of the meeting 15 days before the date of the meeting. Physical stakeholder consultation meetings were held by PO in Trichy on 06/09/2018. The invited stakeholders included representatives from NGOs, development agencies, and businesses working in issues of sustainable development, household-level clean energy, microfinance, and gender among low income populations in India. Minutes were recorded for both consultations that occurred by conference call, and additional feedback submitted by email was also recorded in the Local Stakeholder Consultation template.33

E.2. Summary of comments received

>> Overall, in all meetings and in email communications, the project received significant interest from stakeholders and positive feedback. The stakeholders generally felt that the project offered significant environment, development, and empowerment impacts by making proven clean energy products affordable and accessible to low-income households and micro-entrepreneurs. Multiple stakeholders spoke enthusiastically about the potential for such technologies to have a transformative and empowering impact on the lives of people living in extreme poverty. The stakeholders believed the project was positive on most sustainable development indicators and neutral on a couple. No one expressed major concerns about the project. The minor concerns expressed were about end use disposal of products, avoiding market distorting subsidies, and avoiding conflicts of interest for MFI reporting, but all stakeholders agreed with the mitigation measures MEC planned to implement. More detailed information on the comments received is included in the Local Stakeholder Consultation report.

E.3. Consideration of comments received

>> All clarification requested by local attending stakeholders were addressed during the debate after the initial presentation and a detailed summary of comments by stakeholder group is available upon request.

32The complete Local Stakeholder Consultation Report was provided to the DOE during validation.

33The complete Local Stakeholder Consultation Report was provided to the DOE during validation.

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SECTION F. Eligibility for inclusion

No. Eligibility criterion –

Category Eligibility criterion - Required condition

Supporting evidence for inclusion

Description of this CPA in relation to the

criterion and supporting evidence

1 Boundary and location of the CPA

The CPA is located within India.

Statement of CME that the location and boundary is within India with supporting GPS coordinates (: 20.5937oN, 78.98629oE).

Location and boundary is specified in the specific CPA-DD stating that the location is limited to India and supported with GPS coordinates.

2 No Double counting of CEP

A unique numbering or identification system for the CEP installed is applied. This shall ensure no double counting of CEPs within the PoA and ensure that stoves can be identified as belonging to this PoA and not to a PoA managed by any other CME.

-Sales receipt -Programme logo displayed on the CEPs.

The unique numbering or identification regime is included in the specific CPA-DD and consistent with the PoA-DD For first CPA, document provided: Credit Tracker sale receipt showing CME and PO information, end user details including name and address and CEP ID number. For all subsequent CPAs, in addition to the sales receipt the programme logo shall be displayed on the CEPs and verifiable by the DOE.

3 CER ownership End users receiving CEP under the specific CPA contractually cede their rights to claim and own emission reductions under the Clean Development Mechanism of the UNFCCC to the CME of the PoA

1. Default Booking Record

The default CEP Booking Record provided for end users is including the provision that emission reductions generated by the CEP are owned by the CME.

4 No Double counting of CPA

The CPA is exclusively bound to the PoA. Confirmation that the programme activity has not been and will not be registered either as a single CDM project activity or as a CPA under another PoA.

Check on UNFCCC website with date of access (April 14th, 2012) and contract between the CME and MFI.

A statement by the CME is included in the CPA-DD section A.7. that the specific CPA will not be part of another single CDM project activity or CPA under another PoA. In addition, declaration from CPA operators as part of their contract with the CME, stating that they activities are not registered as part of another single CDM

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project activity of CPA under another PoA.

5

Awareness and agreement of those operating a CPA on PoA subscription

Contractual provisions to ensure that those operating the CPA are aware and have agreed that their activity is being subscribed to the PoA. In the case that the CME is not responsible for implementing the CPA, the organization responsible for CPA implementation, known as the Distributing Organisation (DO), has signed a contractual agreement with the CME to participate in the PoA. This agreement:

- Defines the ownership of the carbon emission reduction rights

- Covers the DO’s distribution and monitoring related responsibilities

- Confirms that the ICS to be distributed under the CPA have not and will not be distributed under any other carbon project (CDM project, PoA or voluntary carbon market project)

Cedes the DO’s rights to the carbon credits generated from CPAs under the PoA to the CME

Contractual agreement with CPA operator

Contractual agreement for PO, stating that they are aware and have agreed that their activity is being subscribed to the PoA. CPA Operator in this CPA is: MEC, Clear Sky Partners LLC, Byeol Gihu Bojon Yuhan Hoesa, SKDRDP, GGI, ESAF and other PO’s that will be finalized at the time of verification based on the distribution schedule. Statement from CME that they provide access for the proposed SSC-CPA in their PoA and statement from PO’s stating that they are aware that their proposed SSC-CPA is being included in the registered PoA.

6 Non-diversion of ODA in case of Public funding

The CME and the CPA operator (in case of being different from the CME) shall confirm that there is no public funding or in the case of public funding, the Annex 1 party will confirm that funding is not a diversion of Official

Statement from CME that there is no public funding involved.

Section A.7 contains a statement from the CME and the CPA operator (in case of being different from the CME) confirming there is no public funding involved

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Development Assistance.

7 CPA Start Date

CPA start date shall not be before PoA webhosting date, i.e. 18/01/2012. Please note that not all CEP installations may have been deployed at CPA inclusion stage, however the CEP start date can also be checked during verification. In the event that any deployed CEP is found not in line with CPA start date, those CEP will not be counted in the emission reduction calculation

1. Statement from CME that no CEP under the CPA were sold before 18/01/2012 2. First CEP Booking Record of CPA

Starting date of the CPA i.e. 30/11/2019 is after the PoA start date i.e. 18/01/2012. Statement from CME that no CEP under the proposed SSC-CPA was sold before the PoA webhosting date, i.e. 18/01/2012.

8 CPA Crediting Period

CPA crediting period not to exceed the PoA end date and the start date of the crediting period of a CPA shall be on or after: (i) The date of registration of the PoA, if the corresponding CPA-DD is submitted together with the request for registration;

(iii) The date when the CPA was included in accordance with the Project cycle procedure;

Section C.3.2. of the CPA-DD refers to the CPA crediting period start date.

CPA-DD Section C.3.2. states that the start date of the crediting period will be 30/11/2019 or the date of inclusion of the CPA in the PoA whichever is later. Also, the CPA crediting period will not exceed PoA end date.

9 Approval of CPA by CME

CME approved each CPA to be included into its registered PoA.

Statement in CPA-DD and approval letter from CME.

Statement of CME in CPA-DD section A.7 giving approval for the CPA to be included into its registered PoA

10 Additionality of CPAs

Additionality will be demonstrated in accordance with EB 68 Annex 27: Guideline on the Demonstration of Additionality of Small-Scale Project Activities Version 09, Paragraph 2(c) which states that a barriers analysis is not required to document Additionality for:

1. Description of CPA activity as documented in CPA-DD Sections A.3

2. CPA-DD Section A.8 demonstrating that the size of each unit is no larger than 5% of the small-scale CDM threshold

1. Description of CPA activity specifying types and the size of CEP units is found in CPA-DD Section A.3. 2. CPA-DD Section A.8 demonstrates that the size of each unit is no larger than 5% of the small-scale CDM threshold

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c) Project activities solely composed of isolated units where the users of the technology/measure are households or communities or Small and Medium Enterprises (SMEs) and where the size of each unit is no larger than 5 per cent of the small-scale CDM thresholds

3. Manufacturer’s specifications showing that solar lighting products are less than the 5% of the 15 mw cap.

Manufacturer’s specifications showing that improved cookstoves are less than the 5% of the 180 GWhth cap

11 Application of Methodologies

The methodologies that can be applied to a CPA include:

- AMS-I.A (version 14)

- AMS-II.G (version 3)

- AMS-III.AV (version 2)

Each CPA can implement these methodologies in isolation. In addition, the following combinations of methodologies are eligible under the PoA:

- AMS-I.A (version 14) and AMS-II.G (version 3)

- AMS-I.A (version 14) and AMS-III.AV (version 2)

Section B.1 outlines the methodologies that are applied in this CPA.

As stated in section B.1 above, this CPA shall deploy AMS-II.G. (version 3) and AMS-I.A (version 14)

12 End User Group

The CPA is either aimed at households, community organisations (e.g. schools) or small/medium enterprises.

CPA-DD Section A.1. and Section B.3.

The CPA-DD describes the target end-user group and the appropriate baseline in sections A.1.

13 Baseline parameters to be established at CPA level

Each CPA shall demonstrate how the baseline parameters for baselines not established at the PoA level (that applies for baselines and options not applicable at the first CPA at the time of PoA registration) that are to be calculated at the CPA

CPA-DD Section B.3.

CPA-DD Section B.3. outlines the approach and provide supporting documents used for determining parameters. If local surveys or representative sampling are used then copies of questionnaires,

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level have been determined. Parameters to be monitored are listed in CPA-DD B.6.1.

sampling design etc. shall be provided.

14 LSC

Local stakeholder consultation for CPA to be conducted prior to CPA inclusion.

LSC report The LSC report is provided.

Solar lighting and solar electric/PV systems (solar lighting systems)

15 Technical Requirement

The CPA consists of distribution of solar lighting and solar electric/PV systems, product type defined in the CPA-DD, and hence appliances involving the renewable electricity generation that supply individual households/users or groups of households/ users as per AMS I. A, ver. 14. Please note that not all solar lighting systems may have been deployed at CPA inclusion stage, the ‘type and number of solar lighting systems deployed’ will however also be checked during verification, and in case any deployed solar lighting systems type will be found not in line with the methodology requirement, those solar lighting systems will not be counted for emission reduction calculation

Product data sheets or specification or product information sheets from manufacturer.

Specification of solar lighting system type and compliance with the technological requirements of AMS I A as described in Section A.3 of the specific CPA-DD. The Solar lighting systems to be deployed are the EH1HLS, EH2HLS, EH4HLS, SB4HLS, SH4HLS, SKD2L, SKD3L, MS 16B and other models, hence are appliances involving the renewable electricity generation that supply individual households/users or groups of households/ users as per AMS I. A, ver. 14

16 Technical Requirement

The emissions reduction per solar lighting system included in the CPA is less than 5 tonnes of CO2e a year

Product data sheets or specification or product information sheets from manufacturer.

Specification of solar lighting system type and compliance with the technological requirements of AMS I A are described in the CPA-DD Section A.3.

17 Technical Requirements

The PO must prove that fossil fuel, specifically kerosene, is used in the absence of the project activity as demonstrated by:

As per the official statistics from the host country published National Sample Survey Organization, 2007. “Energy Sources of Indian Households for Cooking and Lighting,

CPA-DD Section B.3.

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A representative sample survey (90% confidence interval, ±10% error margin) of target households; or Official statistics from the host country government agencies

2004-05”. Report No. 511(61/1.0/4). The use of kerosene as the primary source of lighting is common in rural areas where nationally 44% of the rural population consumes kerosene for lighting, as compared to 7% in urban areas.

18 De-bundling

In accordance with paragraph 9 of Annex 32 to the EB47 Report, “Guidance for determining the occurrence of de-bundling under a Programme of Activities (PoA)”, if each independent subsystem/measures included in the CPA of a PoA is no greater than 1% of the small-scale threshold defined by the methodology applied, than that CPA of PoA is exempted from performing de-bundling check, i.e. considered as being not a de-bundled component of a large-scale activity Please note that not all solar lighting systems may have been deployed at CPA inclusion stage, but the 1% threshold however can also be checked during verification, and in case any deployed solar lighting systems type will be found not in line with the De-bundling requirement, those solar lighting systems will not be counted for emission reduction calculation.

CPA-DD Section A.8. And Manufacturer specifications showing that the wattage of the solar lighting distributed under the CPA are no greater than 1 % of the small-scale threshold.

Demonstrated in line with Section A.8 of the CPA-DD and the manufacturer’s specifications

19 SSC Limit of CPAs

The installed capacity of the CPA will not increase beyond 15 megawatt (MW) (threshold as per EB 61 Annex 1) throughout the

Manufacturer’s specification

The estimated maximum number of solar lighting systems is to be defined in the CPA-DD according to the equation provided in

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crediting period of the CPA. If a CPA exceeds the applicable limit in any year, the claimable emission reduction shall be capped based on the estimated GHG reductions in the CPA-DD34). Please note that not all solar lighting systems may have been deployed at CPA inclusion stage, the SSC limit for CPAs can however also be checked during verification, and in case any deployed solar lighting systems will be found not in line with CPA SSC Limit for CPAs requirement, those solar lighting systems will not be counted for emission reduction calculation

PoA-DD Section B.6.3 (Part 2 in generic-CPA section of PoA-DD) Solar Lighting: The renewable energy systems introduced in this CPA have a capacity of approximately 10.81 W (average wattage amongst the solar products initially planned to be included in this CPA). The project would need to reach over 1,387,283 installations before exceeding the CDM small-scale cap. This is beyond the expected scope of the CPA. The coordinating entity will track installations and ensure that the SSC-CPA does not go beyond the limit of 15MW. Each unit is therefore 0.0001% of the small-scale limit. This is proven in the ex-ante ER calculations excel sheet provided. If a CPA exceeds the applicable limit in any year, the claimable emission reduction shall be capped based on the estimated GHG reductions in the CPA-DD35).

Thermal Displacement Technologies- Improved Cookstoves (ICS)

20 Technological requirements

The CPA consists of replacement of conventional firewood cookstoves for biomass fired ICS as defined in section A.4.2.1 of the PoA-DD. Conventional stoves replaced will be any of the types identified by each baseline scenario and

Manufacturer specifications

Specification of ICS type and compliance with the technological requirements of AMS II G are described in the Section A.3 in the specific CPA-DD. The two models of ICS to be deployed are the Grameen Greenway

34 As per EB 65, Annex 5, paragraph 83.


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as applied by the specific CPA. Stove types replaced and implemented will be defined in the CPA-DD, and hence appliances involving the efficiency improvements in the thermal applications of non-renewable biomass as per AMS II. G, ver. 3. Please note that not all ICS may have been deployed at CPA inclusion stage, the ‘type and number of ICS deployed’ will however also be checked during verification, and in case any deployed ICS type will be found not in line with the methodology requirement, those ICS will not be counted for emission reduction calculation.

Smart stove, a single pot, portable domestic cookstove and the Grameen Greenway Jumbo stove. Hence, both are appliances involving the efficiency improvements in the thermal applications of non-renewable biomass as per AMS II. G, v03.

21 Efficiency of the ICS

The ICS disseminated under the CPA will be single pot, multi pot or in-situ cookstoves that have a specified efficiency of at least 20%

Manufacturer specifications for Grameen Greenway Jumbo stove and Grameen Greenway Smart stove shows a single pot stove with a thermal efficiency of 31.17% and 25.19% respectively.

The ICSs implemented under the proposed CPA are single pot cookstoves with efficiencies of 25.19% and 31.17% which is line with AMS.II.G version 3 Document: Cookstove performance test report is provided. The agencies that carried out the tests are 1) Biomass Cookstove Testing Centre, Department of Renewable Energy Engineering, College of Technology and Engineering, Maharana Pratap University of Agriculture and Technology which is an approved cookstove testing agency as per India’s Ministry of New and Renewable Energy (MNRE); 2) the Indian Institute of Technology,

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School of Materials Science and Technology, Banaras Hindu University

22 Technical Requirements

The PO must monitor the baseline stove that is being replaced to ensure that only the displacement of traditional unimproved stoves is credited.

Section B.3. of the CPA-DD.

As stated in section B.3., the baseline stove of each end-user will be recorded at the point of sale.

23 Technical requirement Only new ICS will be disseminated

1. Statement from CME that only new stoves will be disseminated under the CPA

Specification of stove type and compliance with the technological requirements of AMS II G are described in Section A.3 of the specific CPA-DD.

24 Non-renewability of biomass

In accordance with methodology AMS IIG: Project participants are able to show that non-renewable biomass has been used since 31 December 1989, using survey methods

http://www.corecentre.co.in/Platform/Docs/DocFiles/population_pressure.pdf (Page 5)

The report shows that historical record of forest decline has occurred since 1989, which has been compounded by population growth that further places pressure on NRB as a household fuel.

25 De-bundling

In accordance with paragraph 9 of Annex 32 to the EB47 Report, “Guidance for determining the occurrence of de-bundling under a Programme of Activities (PoA)”, if each independent subsystem/measures included in the CPA of a PoA is no greater than 1% of the small-scale threshold defined by the methodology applied, than that CPA of PoA is exempted from performing de-bundling check, i.e. considered as being not a de-bundled component of a large-scale activity Please note that not all ICS may have been deployed at CPA inclusion stage, but the

CPA-DD Section A.8.

CPA-DD Section A.8., clearly shows that each solar/stove device is less than 1 %of the small-scale threshold defined by the methodology applied i.e. AMS.I.A. v14 and AMS.II.G. v3.

http://www.corecentre.co.in/Database/Docs/DocFiles/population_pressure.pdf




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1% threshold however can also be checked during verification, and in case any deployed ICS type will be found not in line with the De-bundling requirement, those ICS will not be counted for emission reduction calculation.

26 SSC Limit for CPAs

The CPA will remain under the thermal threshold of 180 GWhth/a thermal energy savings (threshold as per clarification request SSC_233) throughout the crediting period of the CPA. If a CPA exceeds the applicable limit in any year, the claimable emission reduction shall be capped based on the estimated GHG reductions in the CPA-DD36). Please note that not all ICS may have been deployed at CPA inclusion stage, the SSC limit for CPAs can however also be checked during verification, and in case any deployed ICS will be found not in line with CPA SSC Limit for CPAs requirement, those ICS will not be counted for emission reduction calculation.

Section A.3. of the CPA-DD

The estimated maximum number of ICSs is defined in Section A.3. of the CPA-DD according to the equation provided in Section B.6.3 (Part 2 in generic-CPA section of PoA-DD) Cookstoves: For this CEP each household represents about 0.005% (0.0083 GWhth/180 GWhth) of the energy saving limit. According to this calculation, each CPA can have up to 21,765 GGI Jumbo cookstoves installed before it reaches the SSC limit of 180 GWh(thermal) [21,765 households would yield energy savings of 180 GWh(thermal)]. This value will be updated annually based on the number of stoves actually distributed. The threshold is indicative and may change based on the actual implementation states, but will not exceed 180GWhth


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Appendix 1. Contact information of CPA implementers

Organization name Micro Energy Credits Corporation Private Limited

Country India

Address 22A Waterwoods, Main Varthur Road, Whitefield, India

Telephone +91-8076844056 +91 9884273950

Fax -

E-mail [email protected] [email protected]

Website www.microenergycredits.com

Contact person Sriskandh Subramanian Anantha Karthik Rajagopalan

Organization name Byeol Gihu Bojon Yuhan Hoesa

Country Republic of Korea

Address (Cheongwon Building, 2th Floor, Yeoksam-dong) 33, Teheran-ro 8-gil, Gangnam-gu, Seoul

Telephone +827071134713

Fax -


Website -

Contact person April Suzanne Allderdice Narendra Prajapati

Organization name Clear Sky Partners LLC

Country Republic of Korea

Address 506(2), 47, Gimpohangang 9-ro, 76ben-gil, Gimpo-si, Gyeonggi-do, Republic of Korea

Telephone +821051070265

Fax -


Website -

Contact person Hae Sung Sally Yoo Narendra Prajapati

Organization name Greenway Appliances (GGI)

Country India

Address Lodha Supremus 2, Senapati Bapat Marg, Lower Parel, Mumbai – 400003, India

Telephone +91-22-24902164

Fax -

E-mail [email protected]

Website https://www.greenwayappliances.com/

Contact person Neha Juneja

Organization name Shri Kshetra Dharmasthala Rural Development Project (SKDRDP)

Country India

mailto:[email protected]


http://www.microenergycredits.com/








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Address Dharmashri Building, Dharmasthala – 574216, Belthangadi Block, Dakshina Kannads District

Telephone +91-8256-277215

Fax


Website www.skdrdpindia.org

Contact person Dr. L.H. Manjunath

Organization name Evangelical Social Action Forum (ESAF)

Country India

Address Hepzibah Complex, Mannuthy P.O. Thrissur, Kerala 680651, India

Telephone +91-4872373813

Fax -


Website www.esafmicrofin.com

Contact person K.V. Christudas

Appendix 2. Affirmation regarding public funding

The proposed CPA does not receive any funding from Annex I parties to the Convention therefore there is no risk that public funding could result in diversion of ODA.

Appendix 3. Further background information on ex ante calculation of emission reductions

NA – left blank intentionally.

Appendix 4. Further background information on monitoring plan

NA – left blank intentionally.

Appendix 5. Summary report of comments received from local stakeholders

For solar lighting system and improved stoves:

Date of meeting: 04/09/2018

Location of meeting: SKDRDP Head Office, Dharmasthala

The physical meeting was done by SKDRDP and MEC in Dharmasthala for solar lighting system and improved cookstoves. The invited stakeholders included representatives from NGOs, development agencies, and businesses working in issues of sustainable development, household-level clean energy, microfinance, and gender among low income populations in India. Additionally, video conferencing was also organized through which customers and other stakeholders from other parts of the country.


http://www.skdrdpindia.org/


http://www.microenergycredits.com/

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STAKEHOLDER NAME QUESTION RESPONSE FROM CME/PO

Rukmini How does stove help in reduction of smoke level? It will help in improving health of family

The representatives explained about working principles of stove and how to use it. The project will contribute to reducing disease risks related to indoor air pollution and improve the users’ health and well-being

Sundari Product specific questions about warranty and product life cycle, etc.,

Information was provided on product warranty and durability.

For improved stoves:

Date of meeting: 06/09/2018

Location of meeting: Hotel Ramyas, Trichy

The physical meeting was organized by GGI and MEC in Trichy for improved cookstoves. The invited stakeholders included representatives from NGOs, development agencies, and businesses working in issues of sustainable development, household-level clean energy, microfinance, and gender among low income populations in India. Additionally, video conferencing was also organized through which customers and other stakeholders from other parts of the country.

Questions raised by the stakeholders were satisfactorily addressed during the consultation.

STAKEHOLDER NAME QUESTION RESPONSE FROM CME/PO

Vijaya How do you convert sales of clean energy product into emission reductions?

The process of conversion of sales to ER has multiple steps. There are UN defined methodologies which uses statistical ways to make these conversions. Along with the tools, physical visits to the customer households are made by UN certified auditors to physically verify the claims.

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Appendix 6. Summary of post-registration changes

NA – left blank intentionally

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- - - - -

Document information

Version Date Description

09.0 31 May 2019 Revision to:

• Ensure consistency with version 02.0 of the “CDM project standard for programmes of activities” (CDM-EB93-A07-STAN);

• Make editorial improvements.

08.1 20 October 2017 Editorial revision to remove appendix “Applicability of methodologies and standardized baselines” from the main part of the form which had been mistakenly kept in the previous version.

08.0 28 June 2017 Revision to:

• Remove appendix “Applicability of methodologies and standardized baselines” as the appendix is not relevant at the CPA level;

• Make editorial improvement.

07.0 7 June 2017 Revision to:

• Improve consistency with the “CDM project standard for programmes of activities” and with the PDD and PoA-DD forms;


06.0 24 May 2017 Revision to:

• Ensure consistency with the “Standard: CDM project standard for programme of activities” (CDM-EB93-A07-STAN) (version 01.0);

• Incorporate the “Component project activity design document form for small-scale component project activities” (CDM-SSC-CPA-DD-FORM);


05.0 15 April 2016 Revision to ensure consistency with the “Standard: Applicability of sectoral scopes” (CDM-EB88-A04-STAN) (version 01.0).

04.0 9 March 2015 Revision to:

• Include provisions related to statement on erroneous inclusion of a CPA;

• Include provisions related to delayed submission of a monitoring plan;

• Provisions related to local stakeholder consultation;

• Provisions related to the Host Party;


03.0 25 June 2014 Revisions to:

• Include the Attachment: Instructions for filling out the component project activity design document form for CDM component project activities (these instructions supersede the "Guidelines for completing the component project activity design document form" (Version 01.0));

• Include provisions related to standardized baselines;

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Version Date Description

• Add contact information on a CPA implementer and/or responsible person/ entity for completing the CDM-CPA-DD-FORM in A.13. and Appendix 1;

• Add general instructions on post-registration changes in paragraph 4 and 5 of general instructions and Appendix 6;

• Change the reference number from F-CDM-CPA-DD to CDM-CPA-DD-FORM;


02.0 13 March 2012 Revision required to ensure consistency with the "Guidelines for completing the component project activity design document form" (EB 66, Annex 16).

01.0 27 July 2007 EB 33, Annex 42

Initial adoption.

Decision Class: Regulatory Document Type: Form Business Function: Registration Keywords: component project activity, project design document

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