MONITORING REPORT v06 18/03/2014. QoriQ oncha Improved Cookstoves Diffusion Programme in Peru VPA 3 GS 1365

Transcription

1 MONITORING REPORT v06 18/03/2014 QoriQ oncha Improved Cookstoves Diffusion Programme in Peru VPA 3 GS st MP 14/05/ /05/2013 (first and last days included) Title of the VPA Reference number of the project activity GS 1365 Title of the PoA Reference number of the PoA Version number of the monitoring report 6 QoriQ oncha ImprovedCookstoves Diffusion Programme in Peru VPA 3 QoriQ oncha ImprovedCookstoves Diffusion Programme in Peru GS1005 Completion date of the monitoring report 18/03/2014 Registration date of the project activity 15/11/2013 Monitoring period number and duration of this monitoring period Project participant(s) Host Party(ies) Sectoral scope(s) and applied methodology(ies) Estimated amount of GHG emission reductions or net anthropogenic GHG removals by sinks for this monitoring period in the registered PDD Actual GHG emission reductions or net anthropogenic GHG removals by sinks achieved in this monitoring period Actual GHG emission reductions achieved during the first commitment period Actual emission reductions achieved during the period from 1 January 2013 onwards 1 st monitoring period: 14/05/ /05/2013 (first and last days included) Duration of the monitoring period: 731 days - Instituto Trabajo Y Familia (ITYF) - Gobierno Regional de Arequipa (GRA) - Gobierno Regional de La Libertad (GRLL) - Gobierno Regional de Tacna (GRT) - MICROSOL Peru Sectoral scope: Energy demand Applied methodology: Gold Standard Cook stove methodology: Methodology for Improved Cook-stoves and Kitchen Regimes V ,

2 Contents A. Description of the project activity A.1. Purpose and general description of the project activity A.2. Location of the projectactivity A.3. Parties and project participant(s) A.4. Reference of appliedmethodology A.5. Crediting period of the project activity B. Implementation of the projectactivity B.1. Description of implemented registered project activity B.2. Post registration changes C. Description of the monitoring system D. Data and parameters D.1. Data and parameters fixed ex ante or at renewal of crediting period D.2. Data and parametersmonitored D.3. Implementation of sampling plan E. Calculation of emission reductions or GHG removals by sinks E.1. Calculation of baseline emissions or baseline net GHG removals by sinks E.2. Calculation of project emissions or actual net GHG removals by sinks E.3. Calculation of leakage E.4. Summary of calculation of emission reductions or net anthropogenic GHG removals by sinks E.5. Comparison of actual emission reductions or net anthropogenic GHG removals by sinks with estimates in registered VPA-DD E.6. Remarks on difference from estimated value in registered VPA-DD E.7. Actual emission reductions or net anthropogenic GHG removals by sinks during the first commitment period and the period from 1 January 2013 onwards Annex 1 - LPP ITYF 1. Project Survey 1.1 Project Survey description 1.2 Project Survey Matrix 2. SustainableDevelopmentIndicators 2.1 SustainableDevelopmentmatrix 2.2 Do No HarmAssessmentDeclaration Annex 2 - LPP GRA 1. Project Survey 1.1 Project Survey description 1.2 Project Survey Matrix 2. SustainableDevelopmentIndicators 2.1 SustainableDevelopmentmatrix 2.2 Do No HarmAssessmentDeclaration 2

3 Annex3 - LPP GRLL 1. Project Survey 1.1 Project Survey description 1.2 Project Survey Matrix 2. SustainableDevelopmentIndicators 2.1 SustainableDevelopmentmatrix 2.2 Do No HarmAssessmentDeclaration Annex4 - LPP GRT 1. Project Survey 1.1 Project Survey description 1.2 Project Survey Matrix 2. SustainableDevelopmentIndicators 2.1 SustainableDevelopmentmatrix 2.2 Do No HarmAssessmentDeclaration 3

4 SECTION A. Description of the project activity A.1. Purpose and general description of the project activity This Voluntary Project Activity (VPA) is part of the PoA QoriQ oncha - Improved Cookstoves Diffusion Programme in Peru (GS1005). In Peru, where a large part of the population relies on wood for cooking, inefficient cooking practices are a major cause of deforestation. Besides, the poorest populations of the country have a very low access to basic needs and one of the most urgent issues is the health-related issue of cooking combustion habit. This VPA intends to be part of the solution. It aims at disseminating, within the defined processes of the PoA, improved cookstoves that will enable the beneficiaries to reduce significantly their wood consumption and will decrease their exposure to indoor air pollution. Indeed, the improved cookstoves design optimizes the internal combustion, the isolating materialsused (such as adobe or clay) in the construction optimize the heat efficient use and the chimney draws the toxic smokes outside the house 1. This VPA, the third of this PoA, includes project activities in four regions of Peru implemented by four LPPs (Local Project Participant). The project activities are the dissemination and transfer of 49,823 improved cookstoves in Huanuco, Arequipa, La Libertad and Tacna in Peru. Project activities will take place between 2010 and 2018 at least (the actual dissemination and transfer of technology was held between but follow up and maintenance will last until 2018 at least). Four main actors, the LPPs, are implementing the project activities that lead to the request of issuance of credits in this first monitoring period: - InstitutoTrabajo Y Familia (ITYF): Local Project Participant n 3 (LPP3) of this PoA. It is a national NGO. ITYF is implementing project activities in Huanuco region during the period Gobierno Regional de Arequipa (GRA): Local Project Participant n 6 (LPP6) of this PoA. It is a public organization. It is implementing project activities in Arequipa regionduring the period Gobierno Regional de La Libertad (GRLL): Local Project Participant n 7 (LPP7) of this PoA. It is a public organization. It is implementing project activities in La Libertad regionduring the period Gobierno Regional de Tacna (GRT): Local Project Participant n 8 (LPP8) of this PoA, It is a public organization. It is implementing the project activities in Tacna region during the period MICROSOL, the Managing entity, coordinates the carbon related activities. It is a French company dedicated to help local actors of Peru to implement voluntary actions of cookstove diffusion. MICROSOL participates in the investment of project activities developing deep knowledge on social, cultural and environmental impact of cookstove, adequate dissemination mode of cookstove and carbon engineering. It also finances and organizes the writing of carbon market related documents, coordination of information production and monitoring activities, stakeholders consultations, discussions with the Gold Standard and DOEs. For the analysis of this VPA the following methodological tool is used: Gold Standard Cook stove methodology: Methodology for Improved Cook-stoves and Kitchen Regimes V The detailed list of materials used for the construction of the ICS is presented in section B.1. 4

5 As a result of the pre-feasibility assessment, the Gold Standard declared the project eligible for inclusion and retroactive crediting. The inclusion of the VPA was successfully conducted by TUV NORD and the Gold Standard officially included the VPA when the 2-week review period ended, that is to say on 13 th May The registration of the PoA as a Gold Standard project with the project ID GS 1005 was realized on 14 th November This monitoring report covers ERs generated during the monitoring period by all the stoves disseminated from the beginning of project activities. This is the first monitoring period of this VPA: it goes from 14/05/2011 until 13/05/2013, both days included. The total emission reductions achieved in this monitoring period by the LPPs are tCO2e, as in the following table. Table A1: ICS volumes and Emission reductions of this 1 st monitoring period ITYF GRA GRLL GRT TOTAL Number of ICS installed 3,533 6,781 13,679 5,029 29,022 Emission reductions (tco2) A.2. Location of the project activity Peru is a km 2 coordinates: Huánuco Latitude Longitude Arequipa Latitude Longitude La Libertad Latitude Longitude Tacna Latitude Longitude country with 24 regions. Project activities are located in the following Geographic Coordinates 9 55' 46" S 76 14' 23" W Geographic Coordinates 16 23' 55" S 71 32' 12" W GeographicCoordinates S " W GeographicCoordinates " S " W 5

6 Table A2: Maps Project activities take place in four regions: - The Huánuco region on central mountainous area. - The Arequipa region on the Pacific Coast south. - The La Libertad region on the pacific coast north, - The Tacna region on the Pacific Coast south. The Huánuco region ( Departamento ) has 11 provinces ( provincia ). The project activity takes place in 1 western province: - Dos de mayo The Arequipa region ( Departamento ) has 8 provinces ( provincias ). The project activity takes place in the 8 provinces: - Caylloma - Caraveli - Camaná - Islay - Castilla - Condesuyos - Arequipa - La Unión 6

7 The La Libertad region ( Departamento ) has 12 provinces( provincias ) The project activity takes place in 4 provinces: - Bolivar - Gran Chimu - Pataz - Sanchez Carrion The Tacna region ( Departamento ) has 4 provinces ( provincias ) The project activity takes place in the 4 provinces: - Candarave - Jorge Basadre - Tarata - Tacna A.3. Parties and project participant(s) Party involved ((host) indicates a host Party) Private and/or public entity(ies) project participants (as applicable) Indicate if the Party involved wishes to be considered as project participant Peru (host country) - Instituto Trabajo Y Familia (Privateentity) - Gobierno Regional de Arequipa (Publicentity) - Gobierno Regional de La Libertad (Publicentity) - Gobierno Regional de Tacna (Publicentity) France (involved party) MICROSOL S.A.R.L.(Privateentity) No No 7

8 A.4. Reference of applied methodology The approved baseline and monitoring methodology applied to each VPA is the Gold Standard approved: Methodology for Improved Cookstoves and Kitchen Regimes V.01. It is available on the Gold Standard website: gies/gs_methodology_cookstove.pdf A.5. Crediting period of project activity The selected crediting period is a 7-year crediting period renewable twice, as stated in section A.9 of VPA-DD 3. The starting date of the crediting period is: 14/05/2011 (DD.MM.YYYY) Indeed, the first stove of this VPA has been built during the month of January However, as of Gold Standard rules, the crediting period cannot start before two years prior to the final inclusion date of the VPA. The inclusion of VPA 3 was officially finished on 13 th May 2013, therefore the official starting date of the crediting period of VPA 3 is the 14 th May

9 SECTION B. Implementation of the project activity B.1. Description of implemented registered project activity LPPs included in this MR started the implementation of their activities as follows: Table B1: Number of ICS installed per year ITYF GRA GRLL GRT 2010 ICS number ,269 3, ICS number - 4,201 8,392 1, ICS number 3,533 1,950 4, ICS number TOTAL OF ICS INSTALLED 3,533 6,781 13,679 5,029 They will continue the implementation of the ICS until the end of 2014, except for GRT which will stop at the end of The specific models of improved cookstoves can be different from one LPP to another but some points do not vary in all the stoves technology being disseminated: - It respects basic physics rules in the technology design, in order to optimize internalcombustion and practical use of the stove; - Isolating materials are used, in order to optimize heat efficient use; - The cookstove is at least partially closed and has a chimney that draws the toxic smokes outside the house. The improved cookstoves implemented by the LPPs have the following characteristics: Table B2: Materials used for ICS construction ITYF GRA Parts Materials Lifeexpectanc y (years) Parts Materials Lifeexpectanc y (years) Chimney Meltedsteel 10 Chimney Steel 10 Combustionchamb er Steel 7 Combustionchamb er Fireclay 5 Platform Adobe 3 Platform Metal / clay 4 to 7 Structure block Adobe 5 Structure block Estimated stove life expectancy if appropriate usage and maintenance 7 Adobe / Brick Estimated stove life expectancy if appropriate usage and maintenance 5 to 10 7 GRLL GRT Parts Materials Lifeexpectanc y (years) Parts Materials Lifeexpectanc y (years) Chimney Steel 10 Chimney Steel 10 Combustionchamb er Fireclay 5 Combustionchamb er Fireclay 5 9

10 Platform Metal / clay 4 to 7 Platform Metal / clay 4 to 7 Structure block Adobe 5 Structure block Adobe / brick 5 to 10 Estimated stove life expectancy if appropriate usage and maintenance 7 Estimated stove life expectancy if appropriate usage and maintenance 7 B.2. Post registration changes B.2.1. Temporary deviations from registered monitoring plan or applied methodology No temporary deviations from the registered monitoring plan or the methodology have been applied to this monitoring period. B.2.2. Corrections No correction occurred in this Monitoring period. B.2.3. Permanent changes from registered monitoring plan or applied methodology No changes have occurred on the monitoring plan or the applied methodology. B.2.4. Changes to project design of registered project activity No changes have occurred to the project design of the registered project activity. B.2.5. Changes to start date of crediting period No changes have been applied to the start date of the crediting period. B.2.6. Types of changes specific to afforestation or reforestation project activity Not applicable. 10

11 SECTION C. Description of monitoring system The monitoring plan applicable for a VPA is based on the Methodology for Improved Cookstoves and Kitchen Regimes V.01. First of all, a final list (installation record) of the families having received an improved cookstove is compiled by each LPP and centralized by MICROSOL. The LPP is due to frequently update this list and communicate changes to MICROSOL. This list will help in identifying stove owners for applying monitoring surveys and will serve as a basis for total population emission reductions calculation. Trainings are performed at various levels to guarantee correct application of PoA rules and efficiency of the projects: - For each LPP,MICROSOL makes various trainings corresponding to each key step of the carbon process. Usually, when a LPP enter in the PoA, it receives two trainings: one on the eligibility documents to produce and the PoA rules, one on the monitoring process. Depending on the content, the training can last from one to three days. After first verification, MICROSOL reproduces training whenever needs are identified (new rules, new people, etc.) - Each beneficiary is trained by the LPP s staff during the stove implementation. The capacity building covers the stove construction and reparation, sensitization on the benefits and risks of stove utilization, good practices and tricks for good utilization. These trainings usually take place during the installation of the stove, in the house of the beneficiary. Every two years at least, a general update of cluster differentiation and corresponding total emission reductions will be carried out with basically the same methodology as that used for initial emission reductions measurement combining qualitative and quantitative surveys described in section B.6. of VPA-DD. A monitoring report will then be produced. Finally, other aspects such as leakage, SD matrix, NRB and eventual DNH mitigation parameters analysis will be monitored every two years in a general update so as to take into account the influence of its eventual evolution on total emission reductions. Corresponding assessment will be presented in the monitoring report produced in this occasion. Quality control and analysis will be performed by MICROSOL in Lima. All data generated will be centralized by MICROSOL in general comprehensive databases so as to be easily accessible and for analysis to be more accurate. MICROSOL s leadership of the process, its permanent control of data and its capacity building to LPPs act as a guarantee for data quality. Nevertheless, whenever possible, independent analysis could be considered so as to reinforce confidence in data. All data and documentation related to the VPAs will be archived at least for a period of 2 years after the end of the crediting period. So, for the monitoring reports: - The LPPs perform KS and KT according to the Monitoring Plan under supervision of MICROSOL; - MICROSOL compiles a report for each cluster; - MICROSOL submits the report to the DOE for verification. All the key documentation related to the PoA is archived electronically on a specific web site called Dropbox. To avoid unexpected deletion of files back-up are saved each month by MICROSOL s IT department. This archiving system prevents from potential loss of documents due to destruction or loss of MICROSOL sstaff computers. To make this monitoring system more efficient and reliable, MICROSOL continuously works on improvements of tools and procedures. The key tools and procedures of MICROSOL are: 11

12 - Emission reduction calculation tool; - Training LPPs on carbon documentation and processes; - Sampling tool to provide guidelines to the LPPs concerning the place to perform surveys; - Quality control of the documentation provided by the LPPs; 12

13 SECTION D. Data and parameters D.1. Data and parameters fixed ex ante or at renewal of crediting period Data / Parameter: Unit: Description: Source of data: EF bl.bio,co2 tco 2 /t_biomass CO 2 emission factor arising from use of wood fuel in baseline scenario 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Tables 1.2/1.4 Value(s) applied): tco2/t wood (=112.0 tco2/tj * TJ/ t ) Purpose of data: Baseline scenario emissions. Data / Parameter: Unit: Description: Source of data: EF pj.bio,co2 tco 2 /t_biomass CO 2 emission factor arising from use of wood fuel in project scenario 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Tables 1.2/1.4 Value(s) applied): tco2/t wood (=112.0 tco2/tj * TJ/ t ) Purpose of data: Project scenario emissions. Data / Parameter: Unit: Description: Source of data: Value(s) applied): Purpose of data: EF bl.bio,non-co2 tco2/t_wood Non-CO2 emission factor arising from use of wood fuel in baseline scenario 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Vol.2 Energy, Chapter 2, Stationary Combustion, Table tco2eq/t wood = ( tCO2eq/t wood (CH4 emission) tCO2eq/t wood (N2O emission)) Baseline scenario emissions. Data / Parameter: Unit: Description: Source of data: Value(s) applied): Purpose of data: EF pj.bio,non-co2 tco2/t_wood Non-CO2 emission factor arising from use of wood-fuel in project scenario 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Vol.2 Energy, Chapter 2, Stationary Combustion, Table tco2eq/t wood = ( tCO2eq/t wood (CH4 emission) tCO2eq/t wood (N2O emission)) Project scenario emissions. 2 This value has been validated, see PoA DD, page This value has been validated, see PoA DD, page

14 D.2. Data and parameters monitored Data / Parameter: B bl,y Unit: kg/day/stove 4 Description: Measured/ Calculated/ Default: Source of data: Value(s) of monitored parameter: Mass of woody biomass combusted per stove in the baseline in year y Measured Measurements of sample of cluster population (KT). Cluster ITYF dry : Cluster GRA dry : Cluster GRLL dry : Cluster GRT wet *: kg/day/stove kg/day/stove kg/day/stove kg/day/stove Monitoring equipment: Measuring/ Reading/ Recording frequency: Calculation method (if applicable): QA/QC procedures: Purpose of data: *Last PSKT realized in dry season by GRT showed wood consumption higher than the ones of wet season and no wood saving. We considered that the wood saving equals to 0 for all the months of dry season. As the ER calculation method used does not allow a null wood saving for dry season, we proceeded to a switch and used wet data instead of dry data. This only impacts the presentation of the calculation tables, but has no consequences on the final ER results. Clock type balance calibrated (with a screw moving the pointer to zero) for each measurement. Fixed baseline is chosen at VPA level. The data is calculated from Baseline Kitchen Tests and will stay the same in future verifications. The following procedures are implemented: 1 ) The mass of the considered woody biomass is measured on a 3-day basis, excluded Sunday when specific occasions may increase the consumption. The proportional extrapolation of results to the whole year will therefore be conservative as it will not consider Sunday s higher consumptions. 2 ) The measurement is made directly with the considered customers, the balance used for the weighting must have a precision of no less than 50g. 3 ) Information shall be presented in a monitoring report. 1 ) Monitored beneficiaries are clearly identified for allowing further verifications. 2 ) Sound capacity building was made with surveys responsible including ethic dimensions of the process and adequate techniques for ensuring confidence of results. 3 ) MICROSOL realizes quality control test in digitations of the surveys. 4 ) A conservative approach and GS statistics guidelines are systematically followed. Baseline scenario emissions. 4 As a seasonality factor is applied in the ER calculations, the mass of woody biomass combusted per stove in baseline and project scenarios are presented per kg/day instead of t/year. 14

15 Data / Parameter: Unit: kg/day/stove 5 Description: Measured/ Calculated/ Default: Source of data: Value(s) of monitored parameter: Monitoring equipment: Measuring/ Reading/ Recording frequency: Calculation method (if applicable): Mass of woody biomass combusted per stove aged of less than one year in the cluster in year y Measured. Measurements of sample of cluster population (KT). Cluster ITYF dry,k=1, : Cluster GRA dry,k=1 : Cluster GRLL dry,k=1 : Cluster GRT wet,k=1 **: kg/day/stove* kg/day/stove kg/day/stove kg/day/stove *At the moment of the PSKT dry in September 2013, there were no stoves of 1 year-old anymore. We thus indicate here the consumption for the youngest stoves at the moment of the last dry PSKT that is to say 2 years old. **Last PSKT realized in dry season by GRT showed wood consumption higher than the ones of wet season and no wood saving. We considered that the wood saving equals to 0 for all the months of dry season. As the ER calculation method used does not allow a null wood saving for dry season, we proceeded to a switch and used wet data instead of dry data. This only impacts the presentation of the calculation tables, but has no consequences on the final ER results. Clock type balance calibrated (with a screw moving the pointer to zero) for each measurement. B pj,y was defined for this cluster in 2013 and a new measurement will be due in 2015 as data should be measured biennially. See Description of measurement methods for the parameter. QA/QC procedures: See Description of QA/QC procedures for the parameter. Purpose of data: Project scenario emissions. 5 As a seasonality factor is applied in the ER calculations, the mass of woody biomass combusted per stove in baseline and project scenarios are presented per kg/day instead of t/year. 15

16 Data / Parameter: Unit: Description: Measured/ Calculated/ Default: X NRB,bl,y Fraction Non-renewability status of woody biomass fuel in year y in baseline scenario Calculated Source of data: See Annex 4 of VPA-DD 3. Value(s) of monitored parameter: Monitoring equipment: Measuring/ Reading/ Recording frequency: Calculation method (if applicable): QA/QC procedures: Purpose of data: Cluster ITYF: 69.63% Cluster GRA: 70.32% Cluster GRLL: 69.29% Cluster GRT: 70.32% N/A Data were newly calculated for this monitoring period and they will be updated at the time of the next verification (at least biennially). See the details of measurements processes in Appendix4 of VPA-DD 3. See the details of QA/QC procedures to be applied in Appendix4 of VPA- DD 3. Baseline scenario emissions. Data / Parameter: Unit: Description: Measured/ Calculated/ Default: X NRB,pj,y Fraction Non-renewability status of woody biomass fuel in year y in project scenario Calculated Source of data: Study See Appendix4 of the VPA DD 3. Value(s) of monitored parameter: Monitoring equipment: Measuring/ Reading/ Recording frequency: Calculation method (if applicable): QA/QC procedures: Purpose of data: Cluster ITYF: 69.63% Cluster GRA: 70.32% Cluster GRLL: 69.29% Cluster GRT: 70.32% N/A Data were newly calculated for this monitoring period and they will be updated at the time of the next verification (at least biennially). See the details of measurements processes in Appendix4 of VPA-DD 3. See the details of QA/QC procedures to be applied in Appendix4 of VPA- DD 3. Project scenario emissions. 16

17 Data / Parameter: Unit: Description: Measured/ Calculated/ Default: Source of data: Value(s) of monitored parameter: Monitoring equipment: Measuring/ Reading/ Recording frequency: Calculation method (if applicable): QA/QC procedures: Purpose of data: I i,y Stove installed/cluster/month Represents the number of stoves installed in month i by each LPP whose effective installation and date of installation can be evidenced. Date of installation shall be used for calculating each stove crediting period. Measured Documents provided by LPPs at VPA level. Please refer to section E.4 of the Monitoring report for detailed values of parameter I i,y. N/A Installation was realized in years , it was measured once and remains fixed thereafter. Signed documents by community representative preferably with list of final beneficiaries. Whenever possible documents signed by each beneficiary should be preferred. Data are collected by the LPPs and then verified by MICROSOL (double counting, random cross-check with installation evidences). Emission reductions calculation. The I i,y parameter is used to calculate the CWCP k,y parameter. 17

18 Data / Parameter: U y Unit: Fraction (%) Description: Measured/ Calculated/ Default: Source of data: Value(s) of monitored parameter: Monitoring equipment: Measuring/ Reading/ Recording frequency: Represents the drop-off rate in stove usage each yearin each cluster. This parameter represents the number of stoves that are getting out of utilization within the cluster each year. Measured Data included in Kitchen surveys (KS). Cluster ITYF: 0.41% Cluster GRA: 1.60% Cluster GRLL: 0.48% Cluster GRT: 3.21% N/A The drop off rate is calculated from the PSKS. All beneficiaries surveyed declaring they don t use the stove on a daily basis are integrated in the calculation of the indicator. The Drop-off rate in stove (of a certain age) usage in year y is calculated from the results of PSKS and can be expressed as follows: Where: Proportion of the improved cookstoves which are not used on a daily basis within the ones surveyed Average age of improved cookstovessurveyed(in years) Calculation method (if applicable): QA/QC procedures: Purpose of data: Data was defined for each cluster in 2013 and a new measurement will be due in 2015 as data should be measured biennially. Surveys with beneficiaries. 1 ) Sound capacity building was made with surveys responsible including ethic dimensions of the process and adequate techniques for ensuring confidence of results. 2 ) MICROSOL realized quality control test in digitations of the surveys. 3 ) A conservative approach was systematically followed. Emission reductions calculation. 18

19 Data / Parameter: Unit: Description: Measured/ Calculated/ Default: Source of data: Value(s) of monitored parameter: A k,y Fraction (%) for a one year period. Represents the 'aging factor' of stove age category k for each cluster in year y. It will be used so as to determine the decrease or increase of potential emission reductions, taking into account the age of the improved cookstoves. A decrease in improved cookstoves efficiency is expected theoretically throughout the years but the opposite can occur for example when the LPP implements sustainability activities, such as additional capacity building or maintenance activities. Measured Measurements of sample of stove model (KT) Cluster ITYF 1 : 0.00% Cluster ITYF 2 : 0.00% Cluster GRA 1 : 0.00% Cluster GRA 2 : % Cluster GRA 3 : % Cluster GRLL 1 : 0.00% Cluster GRLL 2 : % Cluster GRLL 3 : -4.91% Cluster GRLL 4 : 51.25% Cluster GRT 1 : 0.00% Cluster GRT 2 : % Cluster GRT 3 : % Cluster GRT 4 : % Monitoring equipment: Measuring/ Reading/ Recording frequency: Calculation method (if applicable): QA/QC procedures: Purpose of data: N/A Biennial (as stated in the PoA monitoring plan). See the details of calculations in section E.4 of the Monitoring report. 1 ) Sound capacity building was made with surveys responsible including ethic dimensions of the process and adequate techniques for ensuring confidence of results. 2 ) MICROSOL realized quality control test in digitations of the surveys. 3 ) A conservative approach and Gold Standard statistics guidelines were systematically followed. Emission reductions calculation. 19

20 Data / Parameter: O y Unit: Fraction (%) Description: Measured/ Calculated/ Default: Source of data: Value(s) of monitored parameter: Monitoring equipment: Measuring/ Reading/ Recording frequency: Calculation method (if applicable): QA/QC procedures: Purpose of data: Additional comment: Represents the removal rate of the baselinestovesin each cluster. Measured Data included in Kitchen surveys (KS) Cluster ITYF: 86.08% Cluster GRA: 60.76% Cluster GRLL: 93.17% Cluster GRT: 73.84% N/A Biennial (as stated in the PoA monitoring plan). Surveys with beneficiaries. 1 ) Sound capacity building was made with surveys responsible including ethic dimensions of the process and adequate techniques for ensuring confidence of results. 2 ) MICROSOL realized quality control test in digitations of the surveys. 3 ) A conservative approach was systematically followed. Leakage calculation. The LPPs GRA and GRT will be asked to implement additional sensitization activities to encourage beneficiaries to remove their baseline stoves (but it cannot make it compulsory). 20

21 Data / Parameter: Unit: % Description: Measured/ Calculated/ Default: Source of data: Value(s) of monitored parameter: DNH parameter Corruption Percentage of carbon revenues subject to corruption or suspicion of corruption if the LPP does not comply with the principles of the Do Not Harm Declaration. The LPP commits itself to provide this information in the LPP Eligibility form (see Appendix3 of VPA-DD 3). Measured Carbon revenues use report prepared by LPPs, one year after receiving carbon revenues. No carbon revenues were received until now so the parameter is not available. Monitoring equipment: Measuring/ Reading/ Recording frequency: Calculation method (if applicable): N/A Annual after first issuance. The LPP provides a detailed report on how they have used carbon revenues with references to evidences available for consultation. QA/QC procedures: Purpose of data: MICROSOL revises LPPs reports and their consistency with the evidences as well as the validity of those. N/A Data / Parameter: Unit: Description: Measured/ Calculated/ Default: Source of data: Value(s) of monitored parameter: AF bl,i,y t_fuel/unit-year Mass of alternative fuel i combusted in the baseline scenario in year y Alternative fuels are not monitored in this VPA. N/A All Clusters: 0 t/year/stove Data / Parameter: Unit: Description: Measured/ Calculated/ Default: Source of data: Value(s) of monitored parameter: AF Pj,,i,y t_fuel/unit-year Mass of alternative fuel i combusted in the project scenario in year y Alternative fuels are not monitored in this VPA. N/A All Clusters: 0 t/year/stove 21

22 D.3. Implementation of sampling plan QoriQ onchapoa-dd sets the general framework and guidelines for sampling methods, but precise operational methodology is evolving since the beginning of the programme. The latest improvements made on sampling can be summarized as follows: A multistage random sampling for all monitoring surveys has been designed in order to cover all the geographical areas of the project activities and to ensure a random selection of the subjects. Different stages corresponding to the territorial organization of Peru are taken into consideration while defining the sample. These are the province, the district and the community. Province level: In order to cover all geographical parts of the project activity, all the provinces of implementation of the project activity are selected and the sample size is split among all of them 6, according to their weights in terms of ICS volumes (number of stoves installed). District level: In order to avoid situations where the LPP needs to visit few households in different remote districts of the selected provinces, between 1 and 8 districts (depending on the sample size of each province) are randomly selected among the districts with the largest number of ICS implemented in each selected province. The sample size is split among all of them, according to their weights in terms of stoves volumes. Community level: Once the sample size corresponding to each district is defined, between 1 and 8 communities (depending on the sample size of each district) are selected randomly in each selected district among communities with more than sixteen beneficiaries. Eight surveys will be conducted per community, but in order to anticipate the possible absence of some beneficiaries, two sample lists will be randomly defined per community, one as the priority list of beneficiaries to be surveyed and the other one as a back-up list 7. 6 If the sample obtained in one province is smaller than eight, this province is removed from the sample and the sample size is reweighted again among the remaining provinces. 7 If the complete list of beneficiaries is not available at the moment of the Baseline surveys sample definition (in any case, the volumes of ICS per community will be available), the multistage random sampling rules described above will be followed except the last step when defining the list of beneficiaries to be visited. In this case, MICROSOL will provide the LPP with a list of communities to be monitored and the LPP, once in the field, will be in charge of selecting randomly the beneficiaries to be surveyed. 22

23 SECTION E. Calculation of emission reductions or GHG removals by sinks E.1. Calculation of baseline emissions or baseline net GHG removals by sinks In this VPA, we do not consider emissions during production of the fuel neither emissions related to alternative fuels consumption (other than woody biomass). The equation to calculate the baseline emissions is the following: ( ) Where: Dailymass of woody biomass combusted per stove in baseline scenario in dry 8 season in year y Seasonality factor 9 in year y Fraction of non-renewable biomassin baseline scenarioin year y CO 2 emission factor for biomass Non-CO 2 emission factor for biomass The table E1 presents the Baseline emissions per stove for each LPP: Table E1: Baseline emissions per stove ITYF GRA GRLL GRT* kg/day/stove 11,778 5,635 11,916 10, ,00 365,00 365,00 365,00 69,63% 70,32% 69,29% 70,32% tco2/t bio 1,7472 1,7472 1,7472 1,7472 tco2e/t bio 0, , , ,11762 per stove tco2e/year 5,74 2,77 5,78 5,09 *Last PSKT realized in dry season by GRT showed wood consumption higher than the ones of wet season and no wood saving. We considered that the wood saving equals to 0 for all the months of dry season. As the ER calculation method used does not allow a null wood saving for dry season, we proceeded to a switch and used wet data instead of dry data. This only impacts the presentation of the calculation tables, but has no consequences on the final ER results. 8 Except for the case of GRT for which we used the wet data 9 The calculation method of the parameter is presented in section E.4 23

24 E.2. Calculation of project emissions or actual net GHG removals by sinks In this VPA, we do not consider emissions during production of the fuel neither emissions related to alternative fuels consumption (other than woody biomass). The equation to calculate the project emissions is the following: ( ) Where: Dailymass of woody biomass combusted per stove of age category 1 in project scenarioindry 10 season in year y Seasonality factor 11 in year y Fraction of non-renewable biomassinprojectscenarioin year y CO 2 emission factor for biomass Non-CO 2 emission factor for biomass The table E2 presents the project emissions per stove of age category 1 for each LPP. Indeed, the seasonality factor is applied on the wood savings, therefore it is not possible to include it in those calculations. Please refer to section E.4 for detailed emission reductions calculations. Table E2: Project emissions per stove of age category 1 ITYF* GRA GRLL GRT** kg/day/stove 4,896 4,197 6,182 5, ,00 365,00 365,00 365,00 69,63% 70,32% 69,29% 70,32% tco2/t bio 1,7472 1,7472 1,7472 1,7472 tco2e/t bio 0, , , ,11762 per stove k=1 tco2e/year 2,38 2,06 3,00 2,79 **At the moment of the PSKT dry in September 2013, there were no stoves of 1 year-old anymore. We thus indicate here the consumption for the youngest stoves at the moment of the last dry PSKT that is to say 2 years old. **Last PSKT realized in dry season by GRT showed wood consumption higher that the ones of wet season and no wood saving. We considered that the wood saving equals to 0 for all the months of dry season. As the ER calculation method used does not allow a null wood saving for dry season, we proceeded to a switch and used wet data instead of dry data. This only impacts the presentation of the calculation tables, but has no consequences on the final ER results. 10 Except for the case of GRT for which we used the wet data 11 The calculation method of the parameter is presented in section E.4 24

25 E.3. Calculation of leakage As specified in the Gold Standard Methodology for Improved Cook-stoves and Kitchen Regimes V.01, six types of leakage have to be considered. This is done as mentioned below: L1: Increasing consumption of GHG emitting fuels by the project population, consecutively to the project activities (rebound effect). This potential leakage source is intrinsically included in KTs as KTs consider general house fuel consumption. Whenever a necessity would occur because of project activity its corresponding fuel use will then be included into KTs. Thus, no specific monitoring of the leakage is done and this leakage can be considered as: L1=0 L2: Increasing use of GHG emitting fuels outside the project boundary. An increased use of GHG emitting fuels outside of project boundary due to project activity could be thought to as a result of a decrease in prices provoked by a decrease in demand due to stoves fuel savings. Nevertheless, this is very unlikely in the Peruvian context as stove fuel savings are very likely to be insignificant in the wood market 12. Therefore this leakage can be considered as: L2=0 L3: Purchase of the improved stove by population whose baseline is less GHG emitting than the emissions linked to the use of the improved stove. In the Peruvian context cleaner stoves than the improved stoves would be LPG stoves that have been demonstrated to represent high costs and refer then to a certain sector of population. Unless gas prices would increase very significantly (should be more than the simple opportunity cost as switching back form gas to wood can be considered as very uncomfortable), it would not happen. Whenever this would occur, it should be considered as an evolving baseline and not leakage. Therefore: L3=0 L4: Adoption of a new device specifically dedicated to heating, or adoption of a new practice specifically dedicated to heating, consequently to the project activities (ex: due to lack of heating ability of the disseminated stoves). When doing KTs, the use of a cooking device for heating is assessed and, if it is demonstrated it is due to the project activity, the corresponding fuel use is included in the KTs so that this leakage is intrinsically included into KTs and, as well as L1 can be considered as: L4=0 L5: Reuse of the old stoves inside or outside the boundary, and more important use of these unimproved stoves than in the baseline situation: The traditional unimproved stoves cannot usually be moved from a house to another and have to be rebuilt. So that reuse is very unlikely and considered null outside the project boundary. As far as the inside project boundary is concerned, even if old stove destruction is strongly recommended, beneficiaries can keep using their old stove. Thus, no leakage has to be considered here as KTs do take this into account: wood consumption in project scenario corresponds to general consumption including eventual remaining stoves or other stove use. The LPP is asked by MICROSOL to remove the old stove but cannot make it compulsory. The carbon mechanism is per se an incentive as, because the kitchen tests are made with all wood 12 More explanations are presented in section E.6.1 of the PoA-DD. 25

26 consumption of the house, whenever the old stove is still used, wood consumption will be higher and then emission reductions lower. So whenever the old stove is still in use, carbon incomes will be lower but when it is no more in use, carbon incomes will be higher. Whenever data show that less than 80% of the old stoves have been removed from inside the kitchen after two years of project activity, the LPP will be asked for to implement a direct incentive scheme so as to ensure removal of old stoves up to 80% by the fourth year. After this date restrictive actions shall be taken against corresponding LPP including reduction of ERs. As GRA and GRT removal rates are lower than 80% (60.76% and 73.84%), the LPPs will be asked to implement additional sensitization activities to encourage beneficiaries to remove their baseline stoves (but they cannot make it compulsory). L5=0 L6: Significant emissions linked to stove transport or fuel transport: Calculations have been made with basis on the first VPA and it has been demonstrated that stove or fuel transport emissions are inferior to 1% of total emission reductions so that they can be considered as not significant. In this respect, it has been agreed with the Gold Standard to considerer that: L6=0 E.4. sinks Summary of calculation of emission reductions or net anthropogenic GHG removals by a) ER equations The equation to calculate the emission reductions in year yin the entire cluster is the following: { [ ] } Where: Cumulated weighted crediting period in age category k in year y Aging factorfor age category k in year y Daily wood savingsin dry 13 season for less than one year-old ICS in year y Seasonality factor in year y Fraction of non-renewable biomass in year y CO 2 emission factor for wood Non-CO 2 emission factor for wood Eligibility factor of the stoves implemented in year y Leakage in year y 13 Except for the case of GRT for which we used the wet data 26

27 Some of these parameters need to be presented in more details: Cumulated weighted crediting period The Cumulated Weighted Crediting Period in year y can be expressed as follows: Where: asfollows: Cumulated weighted crediting period in age category k in year y. It can be expressed Where: Total improved cookstoves volume implemented in campaign j in age category k in year y. It can be expressed as follows: Where: Improved cookstoves volume from campaign j in month i in age category k in year y. it can be expressed, without loss of generality, as follows: Where: Initial improved cookstoves volume implemented in campaign j (a campaign j being defined by the volume of ICS implemented in month i and year y). Drop-off rate in stove (of a certain age) usage in year y. Drop-off rate The Drop-off rate in stove (of a certain age) usage in year y is calculated from the results of PSKS and can be expressed as follows: Where: Proportion of the improved cookstoves which are not used within the ones surveyed. Average age of improved cookstovessurveyed(in years) 27

28 Wood savings A statistical analysis is conducted in combinationonbaseline and project scenarioswood consumption data to determinethe90% confidence interval of the wood savings. If the confidence interval leads to an error of less than 30%, the daily wood savings in dry season for less than one year-old ICS (k = 1) in year ycan be expressed as follows: Where: Average daily mass of woody biomass combusted per stove in baseline scenario in dry season in year y Average daily mass of woody biomass combusted per stove of age category 1 in project scenarioin dry season in year y If the confidence interval leads to an error superior or equal to 30%, the daily wood savings in dry season for less than one year-old ICS (k = 1) in year y are estimated by the lower bound of the confidence interval and can be expressed as follows: { } Where: Critical value from the Student table Sample variance of wood consumption in baseline scenario in dry season in year y Sample size of wood consumption in baseline scenario in dry season in year y Sample variance of wood consumption in project scenario of stove age category 1 in dry season in year y Sample size of wood consumption in project scenario of stove age category 1 in dry season in year y Aging factor The Aging factor of a stove age category kin year y can be expressed as follows: Where: Daily wood savings for the stove age category k in year y As the wood savings parameter is used in the Aging factor calculation, a statistical analysis is conducted to determinethe90% confidence interval: here the comparison is made between the baseline and each stove age category wood consumptions. If the confidence interval leads to an error 28

29 of less than 30%, the wood savings can be estimated by the difference between the fuel consumption means. If the confidence interval leads to an error superior or equal to 30%, the wood savings can be estimated by the lower bound of the confidence interval. Seasonality factor The Seasonality factor in year y can be expressed as follows: [ ( ) ] Where: Length of the dry season Length of the rainy season Average seasonal variation of daily wood saving The average seasonal variation of daily wood savingin year y can be expressed as follows: Where: Average daily wood savingin rainy season in year y Average daily wood savingin dry season in year y Eligibility factor The eligibility factor was designed by MICROSOL to exclude in a statistical way the part of the beneficiaries that are not eligible for emission reduction calculation. Such exclusion is related to eligibility criteria of the PoA or to cluster differentiation of the VPA: - The improved cook stoves without chimney are not eligible to that PoA and are excluded from emission reductions calculation (as defined in the LPP Eligibility form presented in PoA-DD Annex 3); - Beneficiaries not using wood as main fuel should be monitored in separated clusters. Whenever it would not be possible to perform such a specific monitoring (as it would be complicated and costly), MICROSOL would exclude this population from the emission reductions calculation (see Annexes 1-4 section 1.2); - Beneficiaries who did not use a traditional cookstove in baseline scenario should be monitored in separated clusters. Whenever it would not be possible to perform such a specific monitoring (as it would be complicated and costly), MICROSOL would exclude this population from the emission reductions calculation (see Annexes 1-4 section 1.2). The Eligibility factor of the stoves implemented in year ycan be expressed as follows: Where: 29

30 Sample size of PSKS in year y Proportion of non-eligible beneficiaries. b) ER calculations Cumulated weighted crediting period First of all, here are the volumes of improved cookstoves implemented by month by each LPP: Table E4.1: Volume of ICS implemented per LPP ITYF GRA GRLL GRT January February-10 2 March-10 1 July August September October November December January February March April May June July August September October , November ,675 December , January ,888 February March April May June July August September October November-12 2,032 1 December-12 3 January TOTAL 3,533 6,781 13,679 5,029 30

31 And here is the drop-off rate calculated per LPP: Table E4.2: Drop-off rate per LPP ITYF GRA GRLL GRT Drop off rate (U y ) 0.41% 1.60% 0.48% 3.21% With these two parameters, it is possible to calculate the CWCP k,y of each LPP: Age categories Table E4.3a: CWCP k,y of ITYF CWCP 2011 CWCP 2012 CWCP Age categories Table E4.3b: CWCP k,y of GRA CWCP 2011 CWCP 2012 CWCP Age categories Table E4.3c: CWCP k,y of GRLL CWCP 2011 CWCP 2012 CWCP Age categories Table E4.3d: CWCP k,y of GRT CWCP 2011 CWCP 2012 CWCP

32 Wood savings Here are presented the results of the statistical analysis conducted per LPP to calculate the daily wood savings in dry season for less than one year-old ICS (k = 1). Table E4.4: Wood savings in dry season for less than one year-old ICS per LPP ITYF GRA GRLL GRT** BLKT dry PSKT k=2*,dry BLKT dry PSKT k=1,dry BLKT dry PSKT k=1,dry BLKTwet PSKT k=1,wet Sample size Sample average 11,78 4,90 5,64 4,20 11,92 6,18 10,36 5,67 Sample standard deviation 4,73 1,79 2,51 1,97 2,93 5,92 3,95 1,80 Average Lower bound of the confidence interval Upper bound of the confidence interval Error Value to use for daily wood savings in dry season for less than one year-old ICS Wood savings 6,88 6,16 7,60 10,45% 6,88 Wood savings 1,44 0,79 2,08 44,73% 0,79 Wood savings 5,73 4,22 7,25 26,44% 5,73 Wood savings 4,69 3,91 5,47 16,68% 4,69 *At the moment of the PSKT dry in September 2013, there were no stoves of 1 year-old anymore. We thus indicate here the values for the youngest stoves at the moment of the last dry PSKT that is to say 2 years old. **Last PSKT realized in dry season by GRT showed wood consumption higher that the ones of wet season and no wood saving. We considered that the wood saving equals to 0 for all the months of dry season. As the ER calculation method used does not allow a null wood saving for dry season, we proceeded to a switch and used wet data instead of dry data. This only impacts the presentation of the calculation tables, but has no consequences on the final ER results. Aging factor Here are presented the results of the statistical analysis conducted to calculate the Aging factor of each stove age category per LPP. 32

33 Table E4.5a: Aging factors by stove age categories for ITYF Comparison between groups 0 1* Sample size Sample average 11,78 4,90 Sample standard deviation 4,73 1,79 Comparison of the BL and each age category N/A BL vs 1* BL vs 2 BL vs 3 BL vs 4 Average difference of daily wood consumption N/A 6,88 Lower bound of the confidence interval N/A 6,16 Upper bound of the confidence interval N/A 7,60 Error N/A 0 Value to use for the difference of daily fuel consumption Dry season N/A 6,88 7 ICS age category N/A Aging factors in dry season N/A 0,00% 0,00% Wet season Comparison between groups Sample size Sample average 10,36 6,49 Sample standard deviation 3,95 1,49 Comparison of the BL and N/A BL vs 1 BL vs 2 BL vs 3 BL vs 4 each Average age difference category of daily wood N/A 3,87 consumption Lower bound of the confidence interval N/A 3,21 Upper bound of the confidence interval N/A 4,53 Error N/A 16,99% Value to use for the difference of daily fuel N/A 3,87 consumption ICS age category N/A Aging factors in wet season N/A 0,00% Global aging factors ICS age category N/A Global Aging factors N/A 0,00% 0,00% *At the moment of the PSKT dry (sept-2013) there were no ICS left of age category 1. Thus, to be able to calculate the ageing factor, we estimated the dry season consumption of cat 1 from the rainy KT using the seasonality factor. 33

34 Table E4.5b: Aging factors by stove age categories for GRA Comparison between groups 0 1 2* 3 4 Sample size Sample average 5,64 4,20 5,45 4,40 Sample standard deviation 2,51 1,97 1,60 1,27 0,00 Comparison of the BL and each age category Average difference of daily wood consumption Lower bound of the confidence interval Upper bound of the confidence interval Dry season N/A BL vs 1 BL vs 2* BL vs 3 BL vs 4 N/A 1,44 0,18 1,23 N/A 0,79 NA 0,78 N/A 2,08 NA 1,69 Error N/A 44,7% NA 36,94% Value to use for the difference of daily fuel consumption N/A 0,79 NA 0,78 ICS age category N/A Aging factors in dry season N/A 0,00% N/A 2,22% Wet season Comparison between groups Sample size Sample average 6,87 5,43 4,96 5,45 Sample standard deviation 4,23 1,56 2,50 1,32 Comparison of the BL and N/A BL vs 1 BL vs 2 BL vs 3 BL vs 4 each Average age difference category of daily N/A 1,44 1,91 1,42 wood Lower consumption bound of the confidence N/A 0,38 1,13 interval 0,47 Upper bound of the confidence N/A 2,50 2,68 interval 2,36 Error N/A 73,46% 40,77% 66,81% Value to use for the difference of daily fuel N/A 0,38 1,13 0,47 consumption ICS age category N/A Aging factors in wet season N/A 0,00% -195,33% -22,96% Global aging factors ICS age category N/A Global Aging factors N/A 0,00% -195,33% -10,37% *The data found for the age category 2 doesn't follow at the trend lead by the age categories 1 and 3. The results of this age category seems to be wrong as it is not consistent with the of field observations and the results of KS. Moreover, the statistical analysis suggest a deeper problem since it doesn't reject the T-test hypothesis testing if the two population can be compared. 34

35 To avoid taking into account a erroneous data, we'd rather not use this figure for the ageing analysis. Table E4.5c: Aging factors by stove age categories for GRLL Comparison between groups Sample size Sample average 11,92 6,18 6,08 5,21 Sample standard deviation 2,93 5,92 2,96 1,24 Comparison of the BL and each age category N/A BL vs 1 BL vs 2 BL vs 3 BL vs 4 Average difference of daily wood consumption N/A 5,73 5,83 6,70 Lower bound of the confidence interval N/A 4,22 5,09 6,22 Upper bound of the confidence interval N/A 7,25 6,57 7,19 Error N/A 26,44% 12,69% 7,21% Value to use for the difference of daily fuel N/A 5,73 5,83 6,70 consumption ICS age category N/A Aging factors in dry season N/A 0,00% -1,71% -16,89% Comparison between groups Sample size Sample average 11,12 7,59 9,31 9,26 Sample standard deviation 2,76 2,89 1,80 3,73 Comparison of the BL and each age category Average difference of daily wood consumption Lower bound of the confidence interval Upper bound of the confidence interval Dry season Wet season N/A BL vs 1 BL vs 2 BL vs 3 BL vs 4 N/A 3,53 1,81 1,86 N/A 2,45 1,31 0,95 N/A 4,61 2,32 2,76 Error N/A 30,58% 27,90% 48,77% Value to use for the difference of daily fuel consumption N/A 1,95 2,45 1,81 0,95 ICS age category N/A Aging factors in wet season N/A 0,00% -25,56% 7,08% 51,25% Global aging factors ICS age category N/A Global Aging factors N/A 0,00% -13,64% -4,91% 51,25% 35

36 Table E4.5d: Aging factors by stove age categories for GRT* Comparison between groups Sample size Sample average 5,38 8,17 6,64 6,48 7,98 Sample standard deviation 2,69 2,30 2,69 3,28 2,79 Comparison of the BL and each age category N/A BL vs 1 BL vs 2 BL vs 3 BL vs 4 Average difference of daily wood consumption N/A -2,79-1,26-1,11-2,60 Lower bound of the confidence interval N/A -3,73-2,34-2,03-3,50 Upper bound of the confidence interval N/A -1,85-0,17-0,19-1,70 Error N/A -33,70% -86,25% -83,23% -34,58% Value to use for the difference of daily fuel N/A N/A N/A N/A N/A consumption ICS age category N/A Aging factors in dry season N/A N/A N/A N/A N/A Comparison between groups Sample size Sample average 10,36 5,67 5,07 4,48 Sample standard deviation 3,95 1,80 1,64 1,74 Comparison of the BL and each age category Average difference of daily wood consumption Lower bound of the confidence interval Upper bound of the confidence interval Dry season Wet season N/A BL vs 1 BL vs 2 BL vs 3 BL vs 4 N/A 4,69 5,29 5,88 N/A 3,91 4,48 5,19 N/A 5,47 6,10 6,58 Error N/A 16,68% 15,34% 11,84% Value to use for the difference of daily fuel consumption N/A 4,69 5,29 5,88 ICS age category N/A Aging factors in wet season N/A 0,00% -12,87% -25,48% Global aging factors ICS age category N/A Global Aging factors N/A 0,00% -12,87% -25,48% -38,26% *Last PSKT realized in dry season by GRT showed wood consumption higher that the ones of wet season and no wood saving. We considered that the wood saving equals to 0 for all the months of dry season. 36

37 Seasonality factor The values of the Seasonality factor per LPP are as follows: Table E4.6: Seasonality factor per LPP Season Dry Wet Dry Wet Dry Wet Dry Wet SDy used in this method Length of the season Seasonality factor (S y ) ITYF GRA GRLL GRT 0,00% 0,00% 0,00% ,00% 365 Eligibility factor The values of the Eligibility factor per LPP are as follows: Table E4.7: Eligibility factor per LPP ITYF GRA GRLL GRT Eligibility factor (E y ) 86.26% 94.41% 99.50% 83.11% Emission reductions Once all these parameters have been calculated, it is possible to obtain the annual emission reductions realized by the LPPs project activities and requested in this monitoring period, that are 53,784 tco 2. 37

38 Table E.4.8. Summary of total emission reductions for the VPA ITYF GRA GRLL GRT TOTAL 2010 ICS number ,269 3,047 4, ICS number - 4,201 8,392 1,618 14, ICS number 3,533 1,950 4, , ICS number TOTAL ICS VOLUME 3,533 6,781 13,679 5,029 29,022 ER 2011 (t/year) ER 2012 (t/year) ER 2013 (t/year) TOTAL CUMULATED ER Table E.4.9: Summary of calculation of emission reductions per LPP Item Baseline emissions or baseline net GHG removals by sinks Project emissions or actual net GHG removals by sinks Leakage Emission reductions or net anthropogenic GHG removals by sinks (t CO 2 e) (t CO 2 e) (t CO 2 e) (t CO 2 e) LPP ITYF LPP GRA LPP GRLL LPP GRT Total E.5. Comparison of actual emission reductions or net anthropogenic GHG removals by sinks with estimates in registered VPA-DD Item Emission reductions or GHG removals by sinks (t CO 2 e) Values estimated in ex-ante calculation of registered VPA-DD Actual values achieved during this monitoring period 70, During issuance review, the Goldstandard concluded that the method used by Microsol ER calculation is not fully compliant with the Methodology for Improved Cook-stoves and Kitchen Regimes V.01 (see issuance report). Moreover wet season kitchen tests of GRLL appeared to be invalid. In that context, a correction on the total emission reduction of VPA3: instead of tons, tons. 38

39 E.6. Remarks on difference from estimated value in registered VPA-DD The gap between VPA-DD estimation and ERs calculated for that crediting period can be explained by: 1) Lower wood consumptions than in previous VPAs In the VPA-DD, ER estimations were based on an average wood saving of 3.58kg/day/stove. For GRT (dry season), GRLL (wet season) and GRA, wood savings monitored are much lower than the one used in the VPADD estimation. Also, the statistical analysis of GRT and GRA led us to use the lower bound of the confidence interval, which was not taken into account in the VPADD estimation. E.7. Actual emission reductions during the first commitment period and the period from 1 January 2013 onwards Item Actual values achieved up to 31 December 2012 Actual values achieved from 1 January 2013 onwards Emission reductions or GHG removals by sinks (t CO 2 e)

40 ANNEXES Before the end of the verification review, additional KTs and surveys have been done by the LPPs. Those were revealed to be useful for the ERs calculation and were therefore integrated to the process, with the approbation of the GS. The following annexes only display the results before the inclusion of those new surveys. ANNEX 1. LPP ITYF 1. Project survey As it is stated in VPA-DD 3, baseline scenario KS were used to determine whether another Cluster differentiation was needed inside the ITYF cluster. Conclusion was no, for further details see section D.2 of VPA-DD 3. For the verification stage, project scenario KS have been performed under the same methodology to test possible changes in factors assessment.no need of further cluster differentiation appeared with ITYF. 1.1 Project survey description Table 1.1: Population description PSKS SURVEYS LPP ITYF Survey dates February 2013 Sample size 158 Family size average - Total 4.16 Children (<10) 1.22 Adults (>10) 2.94 % of people using wood as first fuel 96% % of ICS with a chimney 100% % of people using a traditional cookstove in baseline 88% % of removal of the baseline cookstove 86% 1.2 Project survey matrix Table 1.2: Cluster differentiation factors assessment Cluster differentiationfactors Sub-factor Information Criteria ITYF Type of cookstoves Baseline cookstove Type of cookstove used in baseline scenario % of nontraditional baseline stove 11.90% 40

41 Type of household Commercial or institutional use of stove Number of people that use their stove for commercial or institutional purposes % of users with commercial or institutional use >= 30% or <=70% 0.00% Fuel use Main fuel Number of people that do not use wood as first fuel % of users whose main fuel is not wood 3.80% CONCLUSION 3 clusters Based on the BLKS results, there is a need to define specific clusters for beneficiaries who were not using a traditional stove in baseline scenario VS those who are using a traditional stove in baseline scenario. The population of the cluster beneficiaries who were not using a traditional stove in baseline scenario is significant (11.90%) butbecause the implementation of a specific monitoring for it would be costly, it was decided to exclude it from the monitoring and the emission reductions calculations (through the eligibility factor E y ). This approach is conservative. Based on the PSKS results, there is a need to define specific clusters for beneficiaries for whom wood is not the main fuel used VS the ones for whom wood is the main fuel used. The population of the cluster beneficiaries not using wood as first fuel is not significant (3.80%) and because the implementation of a specific monitoring for it would be costly, it was decided to exclude it from the monitoring and the emission reductions calculations (through the eligibility factor E y ). This approach is conservative. The remaining cluster beneficiaries having a traditional baseline and using wood as main fuel is monitored normally. 2. Sustainable development indicators 2.1 Sustainable development matrix Table 2.1 Sustainable Development Matrix 41

42 2.2 Do No Harm Declaration The following documentisthe DNH Declaration signed by ITYF. 42

43 43

44 ANNEX 2. LPP GRA 1. Project survey As it is stated in VPA-DD 3, baseline scenario KS were used to determine whether another Cluster differentiation was needed inside the GRA cluster. Conclusion was no, for further details see section D.2 of VPA-DD 3. For the verification stage, project scenario KS have been performed under the same methodology to test possible changes in factors assessment.no need of further cluster differentiation appeared with GRA. 1.1 Project survey description Table 1.1: Population description PSKS SURVEYS LPP GRA Survey dates January-February 2013 Sample size 158 Family size average - Total 3.5 Children (<10) 0.8 Adults (>10) 2.7 % of people using wood as first fuel 90% % of ICS with a chimney 100% % of people using a traditional cookstove in baseline 98% % of removal of the baseline cookstove 61% 1.2 Project survey matrix Table 1.2: Cluster differentiation factors assessment Cluster differentiationfactors Sub-factor Information Criteria GRA Type of cookstoves Baseline cookstove Type of cookstove used in baseline scenario % of nontraditional baseline stove 1.90% Type of household Commercial or institutional use of stove Number of people that use their stove for commercial or institutional purposes % of users with commercial or institutional use >= 30% or <=70% 0.00% Fuel use Main fuel Number of people that do not use wood as first fuel % of users whose main fuel is not wood 10.13% CONCLUSION 3 clusters 44

45 Based on the PSKS results, there is a need to define specific clusters for beneficiaries who were not using a traditional stove in baseline scenario VS those who are using a traditional stove in baseline scenario. The population of the cluster beneficiaries who were not using a traditional stove in baseline scenario is not significant (1.90%) and because the implementation of a specific monitoring for it would be costly, it was decided to exclude it from the monitoring and the emission reductions calculations (through the eligibility factor E y ). This approach is conservative. Based on the PSKS results, there is a need to define specific clusters for beneficiaries for whom wood is not the main fuel used VS the ones for whom wood is the main fuel used. The population of the cluster beneficiaries not using wood as first fuel is significant (10.13%) butbecause the implementation of a specific monitoring for it would be costly, it was decided to exclude it from the monitoring and the emission reductions calculations (through the eligibility factor E y ). This approach is conservative. The remaining cluster beneficiaries having a traditional baseline and using wood as main fuel is monitored normally. 2. Sustainable development indicators 2.1 Sustainable development matrix Table 2.1 Sustainable Development Matrix 45

46 2.2 Do No Harm Declaration The following documentis the DNH Declaration signed by GRA. 46

47 ANNEX 3. LPP GRLL 1. Project survey As it is stated in VPA-DD 3, baseline scenario KS were used to determine whether another Cluster differentiation was needed inside the GRLL cluster. Conclusion was no, for further details see section D.2 of VPA-DD 3. For the verification stage, project scenario KS have been performed under the same methodology to test possible changes in factors assessment.no need of further cluster differentiation appeared with GRLL. 1.1 Project survey description Table 1.1: Population description PSKS SURVEYS LPP GRLL Survey dates February 2013 Sample size 205 Family size average - Total 5.0 Children (<10) 1.5 Adults (>10) 3.5 % of people using wood as first fuel 100% % of ICS with a chimney 100% % of people using a traditional cookstove in baseline 98% % of removal of the baseline cookstove 93% 1.2 Project survey matrix Table 1.2: Cluster differentiation factors assessment Cluster differentiationfactors Sub-factor Information Criteria GRLL Type of cookstoves Baseline cookstove Type of cookstove used in baseline scenario % of nontraditional baseline stove 0.00% Type of household Commercial or institutional use of stove Number of people that use their stove for commercial or institutional purposes % of users with commercial or institutional use >= 30% or <=70% 0.00% 47

48 Fuel use Main fuel Number of people that do not use wood as first fuel % of users whose main fuel is not wood 0.00% CONCLUSION 1 cluster Based on the PSKS results, there was no need to define more than one cluster for GRLL as all the parameters respect the criteria pre-defined. 2. Sustainable development indicators 2.1 Sustainable development matrix As stated in section D.7 of VPA-DD 3, the following sustainability indicators are monitored. Table 2.1 Sustainable Development Matrix 48

49 2.2 Do No Harm Declaration The following document is the DNH Declaration signed by GRLL. 49

50 50

51 ANNEX 4. LPP GRT 1. Project survey As it is stated in VPA-DD 3, baseline scenario KS were used to determine whether another Cluster differentiation was needed inside the GRT cluster. Conclusion was no, for further details see section D.2 of VPA-DD 3. For the verification stage, project scenario KS have been performed under the same methodology to test possible changes in factors assessment.no need of further cluster differentiation appeared with GRT. 1.1 Project survey description Table 1.1: Population description PSKS SURVEYS LPP GRT Survey dates April 2013 Sample size 172 Family size average - Total 3.6 Children (<10) 0.8 Adults (>10) 2.8 % of people using wood as first fuel 81% % of ICS with a chimney 99% % of people using a traditional cookstove in baseline 99% % of removal of the baseline cookstove 74% 1.2 Project survey matrix Table 1.2: Cluster differentiation factors assessment Cluster differentiationfactors Sub-factor Information Criteria GRT Type of cookstoves Baseline cookstove Type of cookstove used in baseline scenario % of nontraditional baseline stove 1.16% Type of household Commercial or institutional use of stove Number of people that use their stove for commercial or institutional purposes % of users with commercial or institutional use >= 30% or <=70% 0.00% Fuel use Main fuel Number of people that do not use wood as first fuel % of users whose main fuel is not wood 18.60% CONCLUSION 3 clusters 51

52 Based on the PSKS results, there is a need to define specific clusters for beneficiaries who were not using a traditional stove in baseline scenario VS those who are using a traditional stove in baseline scenario. The population of the cluster beneficiaries who were not using a traditional stove in baseline scenario is not significant (1.16%) and because the implementation of a specific monitoring for it would be costly, it was decided to exclude it from the monitoring and the emission reductions calculations (through the eligibility factor E y ). This approach is conservative. Based on the PSKS results, there is a need to define specific clusters for beneficiaries for whom wood is not the main fuel used VS the ones for whom wood is the main fuel used. The population of the cluster beneficiaries not using wood as first fuel is significant (18.60%) butbecause the implementation of a specific monitoring for it would be costly, it was decided to exclude it from the monitoring and the emission reductions calculations (through the eligibility factor E y ). This approach is conservative. The remaining cluster beneficiaries having a traditional baseline and using wood as main fuel is monitored normally. 2. Sustainable development indicators 2.1 Sustainable development matrix Table 2.1 Sustainable Development Matrix 52