Manual for Monitoring of CDM Afforestation and Reforestation Projects

Transcription

1 Manual for Monitoring of CDM Afforestation and Reforestation Projects Part II - Data Collection and Calculations Alvaro Vallejo Rama Chandra Reddy Marco van der Linden

2 Manual for Monitoring of CDM Afforestation and Reforestation Projects Part II - Data Collection and Calculations Alvaro Vallejo Rama Chandra Reddy Marco van der Linden Version

3 Disclaimer This Manual is intended to promote knowledge sharing on monitoring of afforestation and reforestation projects implemented under the CDM. The views expressed in this Manual are those of the authors and do not necessarily reflect the views of the World Bank. The World Bank does not accept the liability for the consequences of actions taken on the basis of information presented in this document. The users of this Manual are responsible for interpretation and application of the information presented in this document. Evolving Document The goal of the BioCarbon Fund is to present up to date information pertaining to climate change mitigation activities in land use sector. In this context, this document seeks to provide guidance on regulatory and operational aspects of afforestation and reforestation activities implemented under the clean development mechanism. The guidance presented in this document is also relevant for monitoring of afforestation and reforestation project activities implemented under the voluntary market regimes. This document is intended for knowledge sharing and the information presented in the document may not necessarily be comprehensive in covering all regulatory requirements. Periodic updates will be made to the Manual. The users are expected to refer to the most recent version of this Manual. We hope that this document is useful in providing relevant information for monitoring of afforestation and reforestation projects. We look forward to your inputs for improving the document. Feedback on any aspect of the Manual may be communicated to: Rama Chandra Reddy; Marco van der Linden; Acknowledgements The information presented in this document has evolved from a series of training programs conducted for the personnel implementing CDM afforestation and reforestation projects of the BioCarbon Fund in several countries. The authors wish to thank the participants of training programs for sharing their insights, field experience, and raising thought provoking questions. The authors acknowledge the support of Mirko Serkovic, Zenia Salinas, and Paola Colla of BioCarbon Fund in the organization of the workshops. The authors also acknowledge the contributions of BioCarbon Fund Manager, Ellysar Baroudy; and Deal Managers of BioCarbon Fund, André Rodrigues Aquino, Adrien de Bassompierre, Franka Braun, Neeta Hooda, Daigo Koga, Monali Ranade, Saima Qadir and Nuyi Tao in preparation and dissemination of this document. 2

4 Contents 1 Introduction Strategy for data collection Organization of data collection Schedule of data collection Data collection team Training on data collection Data collection process Forms used for data collection SMART Forms Quality assurance procedures related to data collection Use of sample data Consistency checks of data Data reconciliation Checks of field data collection Data entry and archival Data archival Calculations Organization of data in SMART Calculation of emission reductions using SMART Annex 1. Smart Forms

5 Abbreviations and Acronyms A/R AFOLU BEF CDM CER CPA-DD DBH DOE DOP EB GHG GIS GPS IPCC LULUCF PDD PDOP PoA-DD QA/QC SOP UNFCCC Afforestation and Reforestation Agriculture, Forestry and Other Land Uses Biomass Expansion Factor Clean Development Mechanism Certified Emission Reduction (of greenhouse gases) CDM Program Activity Diameter at Breast Height (of a tree) Designated Operational Entity Dilution of Precision (of a GPS receiver) Executive Board (of the CDM) Greenhouse gas Geographical Information System Global Positioning System Intergovernmental Panel on Climate Change Land Use, Land-Use Change and Forestry Project Design Document Positional Dilution Of Precision (of a GPS receiver) Program of Activities Design Document Quality Assurance/Quality Control Standard Operational Procedure United Nations Framework Convention on Climate Change 4

6 Organization of the Manual This Manual is designed for personnel involved in monitoring and verification of afforestation and reforestation (A/R) projects implemented under CDM. The information presented in the Manual is also relevant for the projects implemented under the voluntary market regimes. The Manual is divided into three parts. Part I - focuses on monitoring of afforestation and reforestation projects. It is organized into ten sections. Section 1 presents an overview of the CDM A/R project cycle with focus on monitoring and verification, Section 2 focuses on standard operating procedures, Section 3 covers the monitoring of project boundary. Section 4 outlines the procedures in the collection of species data. Section 5 focuses on project implementation. Section 6 covers procedures on monitoring of carbon stocks. Section 7 outlines procedures on monitoring of project emissions. Section 8 describes procedures on monitoring of leakage. Section 9 covers other important monitoring elements and, finally, Section 10 presents some references and links relevant to monitoring of afforestation and reforestation projects. Part II covers the procedures to be followed in collection of data, its organization, and archival in secure format; and calculations to be implemented with the data collected using simplified monitoring afforestation and reforestation tool (SMART), a web based tool for monitoring and calculation of GHG removals by sinks for projects in BioCarbon Fund Portfolio. This part is organized into six sections. Section 2 covers the strategy to be followed in data collection, Section 3 outlines the aspects related to resource requirements of data collection, Section 4 outlines the formats used in data collection. Section 5 discusses the quality assurance and quality control procedures of data collection, Section 6 covers the data entry and data archival procedures and finally, Section 7 outlines the procedures in the use of data collected for calculation of emissions reduction. Part III focuses on the guidance for preparation of monitoring report for the purpose of conducting verification of the project activity and for issuance of CERs. 5

7 1 Introduction Data collection is an important step in monitoring of afforestation and reforestation projects. The project management has to organize resources, adopt procedures and prepare appropriate formats to collect data on aspects of project that influence carbon stock change during the monitoring period. A project needs to clearly outline a strategy for collection of data, organize monitoring team(s), assemble resources, and implement steps to ensure collection of data in timely manner. The data collection procedures followed in A/R projects should also confirm to the good practices of forest inventory so to ensure the data collected is of high quality. A companion document, The Manual on Monitoring of Afforestation and Reforestation projects (Part I) describes standard operating procedures (SOP) for monitoring of A/R projects. The guidance in this Manual (Part II) assumes that projects participants follow the SOP outlined in Part I in collection of project data. Proper documentation of procedures and strategy for data collection should also be ensured so that the procedures get institutionalized over the project period and add credibility to the monitoring report. 1.1 Objective The objective of this manual on data collection and calculations is to present best practice guidance relating to data collection procedures in order to generate consistent and accurate data for calculation of emissions reduction in A/R projects. 2 Strategy for data collection The afforestation and reforestation projects are implemented and monitored over a long period; therefore, establishing a strategy for data collection that facilitates consistency in the methods followed in data collection. Major elements of the data collection strategy are: - Defining the use of data collected. The end use of the data collected in terms of its specific use in the emission reduction calculations need to be outlined at the early stage of the project, which is expected to optimize the costs of data collection and facilitates the consolidation of data for calculation of emission reductions and in preparation of monitoring report for verification. - Organization of data collection tasks. For every parameter that is mandated to be recorded, step-by-step instructions on how the data should be measured, logged, consolidated and archived shall be provided to these personnel. - Organization of equipment. The instruments used for monitoring, should be identified and a procedure for compliance of the monitoring plan. - Defining quality assurance procedures. Procedures of quality assurance need to be outlined in order to operationalize the project level checks of the data collected in order to ensure accuracy and consistency of the data collected. - Mechanisms for data reconciliation. The monitoring team also needs adopt procedures for reconciliation of the project data collected and organized at different levels. - Archiving data and reports. In general, CDM requires data to be maintained for a minimum of 2 years after the crediting period. In order to meet this obligation, the project entities must establish procedures for data archival for the required period. 6

8 Implementing training and procedures. The project entity should identify training required to ensure that the data collection tasks can be carried out smoothly. For example, the person in charge of carbon stock sampling should have a good understanding on sampling procedures and statistical knowledge to perform the tasks within the confidence level required by the monitoring plan. Section 3 presents how data collection should be organized for an effective monitoring of a CDM A/R project. 3 Organization of data collection Data collection involves a series of steps to be followed in order to facilitate systematic collection of data monitored for A/R projects. The steps of data collection process are briefly described below. 3.1 Schedule of data collection The monitoring plan of a project presents the frequency with which project data needs to be collected and recorded. The schedule of data collection is developed taking into account the frequency of data collection and recording and the time needed to collect the data. 3.2 Data collection team Personnel with adequate knowledge of silvicultural activities, CDM procedures and appropriate capabilities should be included in the data collection team. The total number of personnel for data collection will depend on the nature, complexity and size of project activities. In general, a team for monitoring carbon stocks is composed by a leader and two or three additional persons. The most efficient number of persons in the team will depend on the carbon pools to be monitored and measured in project, the location and size of sample plots, and the density of bushes and small vegetation inside sampling plots. The monitoring team(s) may also have to interact with others units with regard to the collection of data and for cross checking data on forest establishment, forest activities and emissions. 3.3 Training on data collection Training of personnel in data collection procedures should be done so that they are aware of relevant procedures and the importance of accurate collection of data. Training should also cover procedures to be followed by qualified personnel for checking field measurements so as to identify and correct any errors in field data collection. 3.4 Data collection process Data collection of a project should cover the carbon pools, project emissions and leakage specified in the methodology. 7

9 4 Forms used for data collection The forms used for data collection are important in monitoring of A/R projects as well designed forms facilitate cost effective collection of data, its organization and storage, and calculation of emission reductions based on data collected. The Simplified Monitoring Afforestation and Reforestation Tool (SMART) 1 developed by BioCarbon Fund for monitoring of A/R projects in BioCarbon Fund portfolio includes forms for collection of data on project activities as per the guidelines of the methodology applicable to specific A/R project. 4.1 SMART Forms As part of the SMART system, 43 different forms were designed for data collection. All these forms are available in Microsoft Word, Adobe Acrobat and Microsoft Excel formats 2. The forms are designed to complain with specific methodologies. Where there exist differences among approved methodologies, different variations of the same format were developed. The forms designed for collection of data on project activities for use in SMART are grouped into the following categories. Discreet area data Species data, Sample plot data, Project emission data Leakage data. Table 1 presents a list of SMART forms and their corresponding Monitoring Report sections. SMART forms are clearly labeled in terms of in the methodologies to which the forms are applicable. Therefore, projects need to use the SMART forms that cover the data collection requirements of the project activities covered by the relevant A/R CDM methodology. The forms are enclosed in Annex 2 of this Manual. Table 1. List of SMART forms and their corresponding Monitoring Report sections. Code Name Monitoring Report Section SOP (See Section II) Comments 02 Discrete areas 02.1 General discrete areas D.4. 1 Basic data of discrete areas used for several tasks and calculations Boundaries D.2., D.4. 1,2 Used for calculation of areas, plots location and reporting. 1 The details of SMART are presented in section 7. 2 Different format versions of the same form have the same fields and projects may choose the most appropriated format for their circumstances. 8

10 Code Name Monitoring Report Section SOP (See Section II) Comments 02.3 Site preparation D.4. 4 Some methodologies require implementation of Standard Operational Procedures for site preparation to minimize soil erosion and disturbance and the monitoring of site preparation Baseline and project stratification criteria D Project stratification D Stratification is a procedure for optimizing carbon stocks sampling and it is reflected in carbon stocks calculations Forest establishment D.4. 5 Monitoring of these elements is 02.7 Survival plots D.4. 6, 9-12 required to ensure that forests will grow in planted areas but it is not 02.8 Silvicultural activities D.4. 7 used for calculations Disturbances D.2. Disturbances may affect carbon stocks and its monitoring may be reflected in calculations. 03 Species data forms 03.1 Species D.2. 3 Species data is required for carbon stocks calculation Additional data D Biomass sample plots data forms 04.1 Field data checks D.4. Field data checks are monitored for QA/QC. 04.2a Trees data form (live trees) D These data are used for carbon 04.2b Trees data form (alive and D stocks calculations. standing dead) 04.3 Non trees (shrubs) D.2. 15,16 05 Lying deadwood sample plots data forms 05.1 Field data checks D.4. are monitored for QA/QC Lying dead wood D.2. 17,18 Used for carbon stocks calculation Lying dead wood density samples 06 Litter sample plots data form D.2. 17,18 Used for carbon stocks calculation Litter sample plots D Used for carbon stocks calculation. 07 Soil carbon sample data form 07.1a Soil samples data from field D Used for carbon stocks calculation. 07.1b Soil carbon sample laboratory D Used for carbon stocks calculation. 08 Emissions data forms 08.2a Emissions by fossil fuel burning D.2., D These elements must be monitored 08.2b Emissions by fossil fuel burning D.2., D in some methodologies. Data are used for calculation of project 08.3a Biomass burning D emissions. 08.3b Biomass burning D c Biomass burning D d Biomass burning D e Biomass burning D Fertilizers ID D

11 Code Name Monitoring Report Section SOP (See Section II) 08.5 Fertilization data D Leakage data Comments 09.1a Fuels data D These elements must be monitored 09.1b Fuels data D in some methodologies. Data are used for calculation of emissions by 09.2 Grazing displacement D leakage. a a2 Grazing displacement D b1 Grazing displacement to D unidentified areas 09.2b2 Grazing displacement to D grassland areas 09.2b3 Grazing displacement to forest D areas 09.3a1 Conversion to cropland D a2 Conversion to cropland D a Fuelwood collection displacement 09.4b Fuelwood collection displacement 09.5a Non-renewable wood for fencing 09.5b Non-renewable wood for fencing D D D D Quality assurance procedures related to data collection In this section, general guidance on quality assurance for data collection is presented. Quality assurance for specific monitoring elements is given in the corresponding SOPs and sections. 5.1 Use of sample data In the case of A/R projects, most monitored parameters require statistical sampling for measurement. The monitoring plan takes into account the uncertainty in sampling by a certain error of level (typically 10%) and confidence level (typically 90 %). The sample plot measurements, used to calculate confidence levels of the GHG removals by sinks and for meeting the target levels. If target levels are not obtained after measuring the predefined number of plots, additional sample plot measurements would be required. 5.2 Consistency checks of data After data collected in the field, personnel that were not part of the data collection should review data forms for completeness and consistency. This includes reviewing that all required fields on forms are filled appropriately, measurement units, Sample ID and Discrete Areas ID are used consistently. It is a good practice to check minimum and maximum values and assess if they are reasonable for the sample measurements. 10

12 5.3 Data reconciliation The list of variables that are to be assessed in relation to other variables in order reconcile the two measurements need to be defined. For example, number of seedlings surviving relative to number of seedlings planted to estimate the survival percent. In general, a shorter time interval for reconciliation period represents lesser risk for project operator to lose any data, a greater prediction in the accuracy, and an opportunity to make a correction should any data seem to deviate from calculation. 5.4 Checks of field data collection To check that plots have been installed and the measurements taken correctly, a fixed percentage of plots should be randomly selected and re-measured independently by the personnel not involved in the data collection. The name and signature of the personnel conducting field data checks and the date(s) of field data checks should be recorded on the data collection forms. Key re-measurement elements include the location of sample plots, DBH and tree height on sample plots. The re-measurement data shall be compared with the original measurement data. Errors discovered should be expressed as a percentage of all plots that have been rechecked to provide an estimate of the measurement error. In case the error exceeds certain threshold (e.g., 10%), the data collection procedures should be repeated. 6 Data entry and archival 6.1 Data entry The data collected in the field on paper based SMART formats are transferred to electronic spreadsheet formats paper based data entry and record keeping system, there must be clarity in terms of the procedures and protocols for collection and entry of data, so that compliance with requirements can be assessed without ambiguity by a third party. Stand-by processes and systems, e.g. paper-based systems, must be outlined to provide backup functions in the event of system failures. The record keeping must provide the paper trail that can be audited. Collected data can be stored in an electronic database, however, care must be taken that the data is read out for each monitoring and calculation period and achieved together with calculation results. Data entry should occur as soon after data collection so that field crews keep current with data entry tasks, and identify errors at the time of data collection. As data are being entered, the person entering the data should visually review each data form to make sure that the data on screen match the field forms. This should be done for each record prior to moving to the next form for data entry. At regular intervals and at the end of the field season the Field Lead should inspect the data that have been entered to check for completeness and perhaps catch avoidable errors. The Field Lead may periodically run check for logical inconsistencies and data outliers. 6.2 Data archival Because of the long-term nature of the A/R CDM project activity, data shall be archived and maintained safely. Data archiving shall take both electronic and paper forms, and copies of all data shall be provided to each project participant. All electronic data and reports shall also be 11

13 copied on durable media such as CDs and copies of the CDs are stored in multiple locations (The SMART developed by BioCarbon Fund is one such location). The archives shall include: - Copies of all original field measurement data, laboratory data, data analysis spreadsheet; - Estimates of the carbon stock changes in all pools and non-co2 GHG and corresponding calculation spreadsheets; - GPS coordinates and GIS products; - Copies of field measurements and Monitoring Reports. 7 Calculations 7.1 Organization of data in SMART The data collected on project activities using SMART forms is organized into three categories data collected from the field to be as input data in SMART, output of calculations based on input data collected on SMART forms, and preparation of report on the calculations based on the data collected on the activities implemented in a project Input data The data collected on the SMART forms during the monitoring period are checked for consistency and stored in electronic and paper formats Output data The equations of the relevant methodology are used calculate the GHG removals by sinks, project emissions and leakage Reporting The reports prepared as a result of calculations based on field data are relevant in the preparation of monitoring report covering the monitoring period. 7.2 Calculation of emission reductions using SMART Using the data collected on SMART forms, the SMART online system uses the equations of the relevant A/R methodology to calculate the net GHG removals by sinks of a project following the required calculation steps. The calculations conducted in SMART can be checked or their accuracy and the resulting values and tables can be copied to fill the corresponding tables and sections of the Monitoring Report. 12

14 Annex 1. Smart Forms 13

15 The World Bank Bio Carbon Fund SMART A tool for monitoring afforestation / reforestation project activities SMART Discrete areas data forms SMART Discrete areas data forms For collecting information of discrete areas that are part of a CDM A/R project activity Version Álvaro Vallejo, 2011 (for the World Bank Bio Carbon Fund) Reviewed by: Marco van der Linden Last edition date: Last review date: Objective The purpose of SMART is to facilitate the implementation and monitoring of CDM afforestation and reforestation projects of the Bio-CF portfolio following approved methodologies. The purpose of this form is the pickup of discrete areas information of a CDM A/R project activity for the purpose of further monitoring of the project according to the rules of the corresponding A/R methodology. This information includes discrete areas general data, site preparation data, stratification, planting schedule, survival check, silvicultural activities, events and boundaries. Disclaimer The World Bank accepts no liability for the content of this tool, or for the consequences of any actions taken on the basis of this tool and the information provided in it, unless that information is subsequently confirmed in writing. Any interpretation of the approved CDM-AR methodologies presented in this tool are solely those of the authors and do not necessarily represent those of the World Bank. The user of this holds the liability for the use, interpretation, and application of this tool. Finally, the recipient should check these files and any attachments for the presence of viruses. The World Bank accepts no liability for any damage caused by any virus transmitted by downloading this tool and the files linked to it. Certification We have done our best effort to provide a reliable tool. However, this version of SMART (V1.0) has not yet been certified and may contain errors, misconceptions and misinterpretations.

16 SMART - 02 Discrete areas SMART Discrete areas - General discrete areas data form SMART Discrete areas - General discrete areas data form Sheet 1/2 For collecting basic information of discrete areas that are part of a CDM A/R project activity that uses AR-AM0001/V2, AR-AM0002/V1, AR- AM0002/V3, AR-AM0003/V4, AR-AM0004/V3, AR-AM0009/V4, AR-AM0010/V3 and AR-ACM0001/V1,V2,V3 methodologies. Version 2.0 (See instructions back) Project ID: Project name: Location level: Sub-location 1 level: Sub-location 2 level: Sub-location 3 level: Sub-location 4 level: Discrete area ID (unique code) Location (most general area. e.g. province) Sub-location 1 (e.g. town) Sub-location 2 Sub-location 3 Sub-location 4 (most specific area. e.g. farm) Plot delineation/ coordinates Ownership (Continues on next page) Page:

17 SMART - 02 Discrete areas SMART Discrete areas - General discrete areas data form Sheet 2/2 For collecting basic information of discrete areas that are part of a CDM A/R project activity that uses AR-AM0001/V2, AR-AM0002/V1, AR- AM0003/V4, AR-AM0004/V3, AR-AM0009/V4, AR-AM0010/V3 and AR-ACM0001/V1,V2,V3 methodologies. Version 2.0 (Continued) Project ID: Discrete area ID (same as in previous page) Area (ha) Previous land use Ex-ante stratification values Criterion 1 Criterion 2 Criterion 3 Criterion 4 Criterion 5 Stratum (same as in stratification form) Comments Sheet 2/2 Page:

18 SMART - 02 Discrete areas Instructions Project ID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Discrete area ID: Use a unique code to identify each track of land which conforms the project area. Project name: Write down the name of the project. Location level: Identify the most general subdivision that will be used to specify a given location, e.g. province, state or department. A given area hierarchy is only required if discrete areas are located in more that one of these hierarchies. E.g. use province as location level only if there are discrete areas in more than one province. Country name is not usually required. Do not write here any proper name for a specific location. Names of specific places (e.g. Tarija -which is a department-) will be stated in the Location column. Sub-location 1 level: Identify a subdivision that will be used to specify a given location located inside the more general division defined at Location level. E.g. if province or state was used at Location level, then you could use municipality or town as sub-location. Do not write here any proper name for a specific location. Names of specific places (e.g. Santa Rosa ) will be stated in the Sub-location 1 column. Sub-location 2 level: Identify a subdivision that will be used to specify a given location located inside the more general subdivision defined at Sub-location 1 level. E.g. if municipality or town was used at Sublocation 1 level, then you could use farm or neighborhood as sublocation. Do not write here any proper name for a specific location. Names of specific places (e.g. State Ranch ) will be stated in the Sublocation 2 column. Similar reasoning is applied for Sub-location levels 3 and 4. Leave blank those levels that are not required. Discrete area ID (DID): Discrete areas are separate portions of land that are part of an A/R CDM project and must have a code. They are called plots in some PDDs but this can lead to confusion, since plots also represent sampling units. This code must be unique at project level. DID codes can have any alphanumeric format, but it is recommended that codes follow a fixed pattern and that enough numbers are reserved to represent all the possible discrete areas of the project. Location: Write the specific name of the area where the current discrete area is located. E.g., if the Location level is department, then a specific location could be Tarija (which is a department). Sub location 1: Write the name of any subdivision of current location that is useful for locating discrete areas. E.g. if town represents the sub location level 1, then a specific sub location 1 could be Santa Rosa (the name of a given town). Sub location 2-4: Write the name of any subdivision of previous sub location that is useful for locating discrete areas. E.g. if farm represents the sub location level 2, then a specific sub location 2 could be State Ranch (the name of a given farm). Use as many sub locations as needed. Plot delineation/coordinates: Record coordinates of every point of the discrete area polygon. If there is an electronic registry of these coordinates or land units, just write down the name of such file(s) in the comments line at the end of the form. If there is no enough room for all coordinates of a given discrete area, use following rows and leave blank all other columns in these rows. Use the format N/S xx x' xx', E/W xx xx' xx''. E.g. N 11 5' 30'', W 84 32' 47''. Use decimals of seconds if you wish. Ownership: Write down the name and/or ID of the owner(s) of current discrete area. Area (ha): Record the total area of the discrete area. Previous land use: Record previous land use(s) of current discrete area. (e.g. cropland, grassland). Ex-ante stratification values: Write down the values of the criteria used for stratification for the specific discrete area (e.g., if soil is the highest level of stratification, type soil type A for criterion 1, if previous vegetation is the second stratification level, type pastures for criterion 2, etc.). Stratum: Write down the specific stratum to which belongs the current discrete area. Comments: Use this field to record any observation related to the discrete area that you consider relevant for the monitoring process.

19 SMART - 02 Discrete areas SMART 02.1b Stands data - General stands data form Sheet 1/2 For collecting basic information of discrete areas that are part of a CDM A/R project activity that uses AR-AM0001/V2, AR-AM0002/V1, AR- AM0002/V3, AR-AM0003/V4, AR-AM0004/V3, AR-AM0009/V4, AR-AM0010/V3 and AR-ACM0001/V1,V2,V3 methodologies. Version 2.0 SMART 02.1b Stands data General stands data form (See instructions back) Project ID: Project name: Location level: Sub-location 1 level: Sub-location 2 level: Sub-location 3 level: Sub-location 4 level: Sub-location 5 level: Discrete area ID (unique code) Stand ID (unique code) Location (most general area. e.g. province) Sub-location 1 (e.g. town) Sub-location 2 Sub-location 3 Sub-location 4 Sub-location 5 (most specific area. e.g. farm) Plot delineation/ coordinates (Continues on next page) Page:

20 SMART - 02 Discrete areas SMART 02.1b Stands data - General stands data form Sheet 2/2 For collecting basic information of discrete areas that are part of a CDM A/R project activity that uses AR-AM0001/V2, AR-AM0002/V1, AR- AM0002/V3, AR-AM0003/V4, AR-AM0004/V3, AR-AM0009/V4, AR-AM0010/V3 and AR-ACM0001/V1,V2,V3 methodologies. Version 2.0 (Continued) Project ID: Discrete area ID (same as in previous page) Area (ha) Previous Land use Stratum (same as in stratification form) Erosion class Site class Comments Sheet 2/2 Page:

21 SMART - 02 Discrete areas Instructions Project ID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project. Discrete area ID: Use a unique code to identify each track of land which conforms the project area. Stand ID: Use a unique code to identify each continuous, homogeneous group of trees planted in part or a whole discrete area. Location level: Identify the most general subdivision that will be used to specify a given location, e.g. province, state or department. A given area hierarchy is only required if discrete areas are located in more that one of these hierarchies. E.g. use province as location level only if there are discrete areas in more than one province. Country name is not usually required. Do not write here any proper name for a specific location. Names of specific places (e.g. Tarija -which is a department-) will be stated in the Location column. Sub-location 1 level: Identify a subdivision that will be used to specify a given location located inside the more general division defined at Location level. E.g. if province or state was used at Location level, then you could use municipality or town as sub-location. Do not write here any proper name for a specific location. Names of specific places (e.g. Santa Rosa ) will be stated in the Sub-location 1 column. Sub-location 2 level: Identify a subdivision that will be used to specify a given location located inside the more general subdivision defined at Sub-location 1 level. E.g. if municipality or town was used at Sublocation 1 level, then you could use farm or neighborhood as sublocation. Do not write here any proper name for a specific location. Names of specific places (e.g. State Ranch ) will be stated in the Sublocation 2 column. Similar reasoning is applied for Sub-location levels 3 and 4. Leave blank those levels that are not required. Discrete area ID (DID): Discrete areas are separate portions of land that are part of an A/R CDM project and must have a code. They are called plots in some PDDs but this can lead to confusion, since plots also represent sampling units. This code must be unique at project level. DID codes can have any alphanumeric format, but it is recommended that codes follow a fixed pattern and that enough numbers are reserved to represent all the possible discrete areas of the project. Location: Write the specific name of the area where the current discrete area is located. E.g., if the Location level is department, then a specific location could be Tarija (which is a department). Sub location 1: Write the name of any subdivision of current location that is useful for locating discrete areas. E.g. if town represents the sub location level 1, then a specific sub location 1 could be Santa Rosa (the name of a given town). Sub location 2-4: Write the name of any subdivision of preivous sub location that is useful for locating discrete areas. E.g. if farm represents the sub location level 2, then a specific sub location 2 could be State Ranch (the name of a given farm). Use as many sub locations as needed. Plot delineation/coordinates: Record coordinates of every point of the discrete area polygon. If there is an electronic registry of these coordinates or land units, just write down the name of such file(s) in the comments line at the end of the form. If there is no enough room for all coordinates of a given discrete area, use following rows and leave blank all other columns in these rows. Use the format N/S xx x' xx', E/W xx xx' xx''. E.g. N 11 5' 30'', W 84 32' 47''. Use decimals of seconds if you wish. Area (ha): Record the total area of the discrete area. Previous land use: Record previous land use(s) of current discrete area. (e.g. cropland, grassland). Stratum: Write down the specific stratum to which belongs the current discrete area. Erosion class: If erosion class is used as a criterion for stratification, please record the erosion class corresponding to the discrete area. Site class: If site class is used as a criterion for stratification, please record the site class corresponding to the discrete area. Comments: Use this field to record any observation related to the discrete area that you consider relevant for the monitoring process.

22 SMART Discrete areas data form SMART Discrete areas - Boundaries SMART Discrete areas - Boundaries For collecting information of boundaries of discrete areas that are part of a CDM A/R project activity that uses AR-AM0001/V2, AR-AM0002/V1, AR-AM0003/V4, AR-AM0004/V3, AR-AM0009/V4, AR-AM0010/V3 and AR- ACM0001/V1,V2,V3 methodologies. Version 2.0. (See instructions back) Project ID: Project name: Discrete area ID (unique code) Measuring date GPS coordinates Comments Page

23 SMART - 02 Discrete areas Instructions Methodologies AR-AM0001, AR-AM0003, AR-AM0004, AR-AM0009 and AR-AM0010 require periodical monitoring of project boundaries through the crediting period. Although periodicity of this monitoring is not stated in approved methodologies, it is recommended to do it for each verification period (i.e., every five years). Important: All methodologies used in the Bio-CF portfolio (AR-AM0001, AR-AM0002 Methodologies AR- AM001, AR-AM0002, AR-AM0004, AR-AM0005,, AR-AM0009, AR-AM0010 and AR-ACM0001) allow the use of remote sensing for recording and reporting discrete areas boundaries. Methodology AR-AM0002 requires also periodic field surveys to verify that permanent markers used to delineate the project boundary and various geographic units can be located on the ground. Project ID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project. Discrete area ID (DID): DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. Measuring date: Fill out the date of measuring of discrete area boundaries in the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or GPS coordinates: If the event affected a part of the discrete area, please fill out the coordinates of the affected area. If the event affected the whole area, state it as whole area. Comments: Use this field to record any observation related to boundaries that you consider relevant for the monitoring process.

24 SMART Discrete areas data form SMART Discrete areas - Site preparation data form SMART Discrete areas - Site preparation data form For collecting information of site preparation of discrete areas that are part of a CDM A/R project activity that uses AR-AM0001/V2, AR- AM0002/V1, AR-AM0003/V4, AR-AM0004/V3 and AR-AM0010/V3 methodologies. Version 2.0. (See instructions back) Project ID: Project name: Discrete area ID (unique code) Stand ID (unique code) Start date (dd/mm/yyyy) End date (dd/mm/yyyy) Activity (from predefined list) Area affected (ha) or dig size (cm x cm x cm) Machinery used Comments Page

25 SMART - 02 Discrete areas Instructions Project ID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project. Discrete area ID (DID): DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. Stand ID: Use a unique code to identify each continuous, homogeneous group of trees planted in part or a whole discrete area. Start date: Starting date of activity. Use the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or End date: End date of activity. Use the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or Activity: Name of the activity generating GHGs emissions, from a predefined list at project level. Common activities that generate GHGs are: biomass burning, site cleaning, plowing, bedding, pits digging. Add to this list if there are other activities generating GHGs. When there is biomass burning you must also fill the corresponding form for biomass burning (08.3 Biomass burning data). Area affected (ha): Area affected by the activity. This may differ from the total area of the discrete area. For example, manual holes digging does not affect the total stand area, but just a small fraction. E.g. if holes have 30 x 30 cm each, and a given plantation has 1000 trees per hectare, then affected area is 0.3 x 0.3 m = 0.09 m ² x 1000 = 90 m². Or, alternatively, when recording pits digging, record pit area (in m²) or dimensions (in cm) and pits distance (in m). E.g. 30x30 cm, 3x3m. Machinery used: Use this field to record the machines used for site preparation. Comments: Use this field to record any observation related to the activity that you consider relevant for the monitoring process.

26 SMART Discrete areas data form SMART 02.4 Baseline and project stratification criteria SMART Baseline and project stratification criteria For defining stratification criteria used to stratify the baseline and project scenarios of a CDM A/R project activity. Suitable for all methodologies. Version 2.0. (See instructions) Project ID: Project name: Stratification level Level 01 Level 02 Level 03 Level 04 Level 05 Project stratification criterion Comments Instructions Project ID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project. Stratification level: There are always key factors influencing carbon stocks in the considered pools. These factors may include soil features, micro-climate, landform (e.g., elevation, slope gradient), tree species to be planted, year to be planted, human management, etc. Stratification must be conducted in a hierarchical order that depends on the significance of key factors on carbon stock changes or the extent of difference of the key factors across the project area. Only once higher level stratification is complete shall commence the stratification at the next level down. At each level in the hierarchy, stratification must be conducted within the strata determined at the upper level. Then Level 01 represents the highest level of stratification and the biggest extent of that factor and Level 05 represents the most specific or local factor affecting carbon stocks. Stratification is done separately for both the baseline scenario and the project scenario, using frequently different stratification criteria. For example, in the baseline scenario, the main stratification criteria could be land use and soil type. At project level, stratification criteria could be productive system and species planted. Comments: Use this field to record any observation related to baseline and stratification criteria that you consider relevant for the monitoring process. Page

27 SMART Discrete areas data form SMART Discrete areas Forest establishment SMART Discrete areas Forest establishment For collecting information of planting schedule of discrete areas that are part of a CDM A/R project activity that uses AR-AM0001/V2, AR- AM0002/V1, AR-AM0003/V4, AR-AM0004/V3, AR-AM0009/V4, AR-AM0010/V3 and AR-ACM0001/V1,V2,V3 methodologies Version 2.0 (See instructions back) Project ID: Project name: Discrete area ID (unique code) Stand ID (unique code) Method of establishment Planting start date Species planted Spacing Number of plants End date Comments Page

28 SMART - 02 Discrete areas Instructions Project ID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project. Discrete area ID (DID): DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. Stand ID: Use a unique code to identify each continuous, homogeneous group of trees planted in part or a whole discrete area. Method of establishment: Record the method used to establish the trees. E.g. direct seeding or manual planting. Planting start date: Please specify planting start date using the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or Species planted: Please use the species that are registered in the corresponding form for species (03 - Species data). If planting several species in the same DID, use a separate row for each of them. In this case, fill just species and number of plants and leave all other cells of row blank. If you have many species planted in the same stand, you can group similar species into species groups. Spacing: Register spacing among plants in the stand. (E.g. 3x4m, 3x3 triangle). Number of plants: Record the total number of plants planted. If several species are planted in the same stand, use a separate row for each species. In this case, fill just species and number of plants and leave all other cells of row blank. If you have many species planted in the same stand, you can group similar species into species groups. End date: Record the date when plantation was finished. Comments: Use this field to record any observation related to the forest establishment that you consider relevant for the monitoring process.

29 SMART Discrete areas data form SMART Discrete areas - Survival plots SMART Discrete areas - Survival plots For collecting information of plants survival of discrete areas that are part of a CDM A/R project activity that use AR-AM0001/V2, AR- AM0002/V1, AR-AM0003/V4 and AR-AM0004/V3 methodologies. Version 2.0 (See instructions back) Project ID: Project name: SID Discrete area ID (unique code) Stand ID (unique code) Date of survey Year of survival survey Survival rate (%) Replanting date Number of plants replanted Comments Page

30 SMART - 02 Discrete areas Instructions Project ID: Unique project identification code. Project name: Fill out the name of the project. SID: Sample plot ID. SIDs must be unique at project level. SID codes can have any alphanumeric format. Discrete area ID (DID): DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. Stand ID: Use a unique code to identify each continuous, homogeneous group of trees planted in part or a whole discrete area. Survey date: Record the date when the survival survey field data collection was finished. Year of Survival survey: Record the year (age) of plantation to which the survival survey corresponds. E.g. 2 (if plantation is on its second year of growth). Survival rate: Record the calculated survival rate expressed in percentage. Replanting date: Record the date the replanting of missing trees was finished. Number of plants replanted: Record the total number of plant per hectare replanted to replace missing trees. Comments: Use this field to record any observation related to survival check that you consider relevant for the monitoring process.

31 SMART Discrete areas data form SMART Discrete areas - Silvicultural activities SMART Discrete areas - Silvicultural activities For collecting information of silvicultural activities that are part of a CDM A/R project activity that uses AR-AM0001/V2, AR-AM0002/V1, AR-AM0003/V4, AR-AM0004/V3, AR-AM0009/V4, AR-AM0010/V3 and AR-ACM0001/V1,V2,V3 methodologies. Version 2.0. (See instructions back) Project ID: Project name: Discrete area ID (unique code) Stand ID (unique code) Date Activity Comments Page

32 SMART - 02 Discrete areas Instructions Project ID: Unique project identification code. Project name: Fill out the name of the project. Discrete area ID (DID): DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. Stand ID: Use a unique code to identify each continuous, homogeneous group of trees planted in part or a whole discrete area. Date: Record the end date of accomplishing the corresponding silvicultural activity. Activity: Fill out the name of the silvicultural activity. You do not need to record any other data related to the activities in this form. GHGs emissions are accounted in separate forms (08.x - Project emissions - xxxx). Emitting activities identified in methodologies are: Biomass burning, Fossil fuels burning (for transportation, site preparation, stationary machinery -such as water pumps- and portable machinery -such as chain saws-), fertilization and fencing with wood from non renewable sources. Comments: Use this field to record any observation related to GHGs emitting silvicultural activities that you consider relevant for the monitoring process.

33 SMART - 02 Discrete areas SMART Discrete areas - Disturbances SMART Discrete areas - Disturbances For collecting information of natural/random events that cause GHGs emissions in discrete areas of a CDM A/R project activity that uses AR-AM0001/V2, AR-AM0002/V1, AR-AM0003/V4, AR-AM0004/V3, AR- AM0009/V4, AR-AM0010/V3 and AR-ACM0001/V1,V2,V3 methodologies. Version 2.0. (See instructions back) Project ID: Project name: Discrete area ID (unique code) Stand ID Date (dd/mm/yyyy) Type of event Geographic coordinates Latitude Longitude Area affected (ha) Comments Page

34 SMART - 02 Discrete areas Instructions Project ID: Unique project identification code. Project name: Fill out the name of the project. Discrete area ID (DID): DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. Stand ID: Use a unique code to identify each continuous, homogeneous group of trees planted in part or a whole discrete area. Date: Fill out the date of the event occurrence in the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or Type of disturbance or event: Record the type of the event that can affect present or future stand stocking or generate GHGs emissions such as fire, drought, flooding, pest, etc. You do not need to record any other data related to the activities in this form. GHGs emissions are accounted in separate forms (08.x - Project emissions - xxxx). Geographic coordinates: Fill out the corresponding geographic coordinates in N/S xx x' xx', E/W xx xx' xx'' format. E.g. N 11 5' 30'', W 84 32' 47''. Use decimals of seconds if you wish. Area affected (ha): If the event affected a part of the discrete area, please fill out area affected. If the event affected the whole area, state it as whole area. Comments: Use this field to record any observation related to GHGs emitting activities that you consider relevant for the monitoring process.

35 The World Bank Bio Carbon Fund SMART A tool for monitoring afforestation / reforestation project activities SMART Species data forms SMART Species data forms For collecting information of species used or existing in a CDM A/R project activity Version 2.0. Álvaro Vallejo, (for the World Bank) Reviewed by: Marco van der Linden Last edition date: Last review date: Objective The purpose of SMART is to facilitate the implementation and monitoring of CDM afforestation and reforestation projects of the Bio-CF portfolio following approved methodologies. The purpose of this form is the pickup of basic information of species being used in a CDM A/R project activity for the purpose of further monitoring of the project according to the rules of the corresponding A/R methodology. Disclaimer The World Bank accepts no liability for the content of this tool, or for the consequences of any actions taken on the basis of this tool and the information provided in it, unless that information is subsequently confirmed in writing. Any interpretation of the approved CDM-AR methodologies presented in this tool are solely those of the authors and do not necessarily represent those of the World Bank. The user of this holds the liability for the use, interpretation, and application of this tool. Finally, the recipient should check these files and any attachments for the presence of viruses. The World Bank accepts no liability for any damage caused by any virus transmitted by downloading this tool and the files linked to it. Certification We have done our best effort to provide a reliable tool. However, this version of SMART (V.1.0) has not yet been certified and may contain errors, misconceptions and misinterpretations.

36 SMART Species data form SMART Species data form Sheet 1/2 For collecting basic information of species used or existing in a CDM A/R project activity that uses AR-AM0001/V2, AR-AM0002/V1, AR- AM0003/V4, AR-AM0004/V3, AR-AM0009/V4, AR-AM0010/V3 and AR-ACM0001/V1,V2,V3 methodologies. Version 2.0. (See instructions back) Project ID: Project name: Species (Latin name) Species (common name) Type (shrub or tree) Calculation method (BEF or allometric) Standing dead wood Wood density class 2 Wood density class 3 Wood density class 4 (Continues on next page) Page:

37 SMART Species data form SMART Species data form Sheet 2/2 For collecting basic information of species used or existing in a CDM A/R project activity that uses AR-AM0001/V2, AR-AM0002/V1, AR- AM0003/V4, AR-AM0004/V3, AR-AM0009/V4, AR-AM0010/V3 and AR-ACM0001/V1,V2,V3 methodologies. Version 2.0. (Continued) Project ID: Species (Latin name) Sound wood density Lying dead wood Intermediate Rotten wood wood density density Carbon fraction (CF) Root/shoot ratio or equation Source / references Comments Sheet 2/2 Page:

38 SMART Species data form Instructions Project ID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project. Species: Please fill out the Latin (or botanic or scientific ) name of all important species existing in the baseline or future species to be planted as part of the project activities. E.g. Tabebuia rosea. Tree and shrub species existing in the baseline should also be included in this list. If a complex mix of species is used, give a unique name to the mix and type the name of this group here. E.g. Species mix 1. Species common name: Write down the corresponding common name of the species as known in the project or the region where the project is located. Type (shrub or tree): Please fill out if the species is a shrub or a tree. Calculation method: Select the method to be used for biomass calculations, either BEF (using biomass expansion factor) or Allometric (using allometric equations). When using BEF method, the following is required: 1) a volume equation (usually merchantable volume, but also total stem volume equations can be used); 2) biomass expansion factor; 3) wood density; 4) root to shoot ratio (R/S) or equation; 5) carbon fraction. Note that BEF and R/S for a given species vary with local conditions and age, and depend also from the type of volume equation used (calculated BEF is different when using total or merchantable volume). When using allometric equations, the following is required: 1) an allometric equation (this type of equations allow to calculate total biomass directly from field measurements such as diameter at breast height or total tree height); 2) root to shoot ratio (R/S) or equation (this will be required if the allometric equation is only for above ground biomass); 3) carbon fraction. Note that these equations are also specific for species and local environmental conditions. Wood density (g/cm³): Please write down wood density to be used for calculations for current species. Methodologies AR-AM0001, AR-AM0003, AR-AM0004, AR-AM0010 and AR-ACM0001 should use data from literature/local/national/ or See IPCC GPG-LULUCF, 2003: default Table 3A.1.9. Methodology AR-AM0009 recommends GPG-AFOLU, IPCC 2006 default Table Standing dead trees wood density classes 2 to 4. Standing deadwood is classified in 4 classes: 1) Tree with branches and twigs that resembles a live tree (except for leaves); 2) Tree with no twigs but with persistent small and large branches; 3) Tree with large branches only; 4) Bole only, no branches. For Class 1, wood density of live trees is used. For the rest classes, specific wood densities must be determined for each species. In the case of mixed plantations or assisted natural regeneration, an average for all the species may be used. Lying dead wood density classes 1 to 3. Lying deadwood is classified in 3 classes: Sound wood (1), intermediate wood (2) and rotten wood (3). Carbon fraction (tonne C/tonne d.m.): Write down the carbon fraction to be used for calculating carbon contents of the species. Please use a decimal format (e.g. 0.48). GPG-LULUCF national GHG Inventory recommends a default value of 0.5. Tables 3A.1.15 and 3A.1.16 of IPCC GPG-LULUCF can be used. Root/shoot ratio*: Write down the root to shoot ratio to be used for calculating root biomass. Please use a decimal format (e.g. 0.28). Methodologies AR- AM0001 to AR-AM0005, AR-AM0010 and AR-ACM0001should use data from literature/local research/ecological studies of the region or Annex 3.A1, Table 3A1.8 of GPG-LULUCF 2003, Methodologies AR-0009, 0010 y AR- ACM 0001 recommends use data from national GHG inventory, local survey per species or Table 4.4., GPG AFOLU of IPCC Source / references**: Please use a unique number or code to identify each source or reference used for defining all factors and or equations. Use always the same number or code for the same reference, and then give a more complete description of the reference in the references table of the 03.2 Species additional data form. Comments: Use this field to record any observation related to species (both used for afforestation/reforestation and existing in baseline) that you consider relevant for the monitoring process. Variable names: Use the following variable names: vt = total stem volume; vm = merchantable volume; dbh = diameter at breast height; ht = total stem heigh; hm = merchantable height. Bt = total tree biomass; Ba = aboveground biomass. Please explain any other variables used (if any) in the comments column. * Use several rows for the same species if you have different factors (such as BEF or R/S) that can be applied to the same species under different conditions. E.g. you could have three BEFs for different age ranges. Please explain in comments the differences among factors. ** Use one row for every different source/reference used. E.g. if BEF and wood density data come from two different sources, then separate them in two rows.

39 The World Bank Bio Carbon Fund SMART A tool for monitoring afforestation / reforestation project activities SMART Biomass sample plots data forms SMART Biomass sample plots data forms For collecting information of biomass sampling made in CDM A/R project activities Version 2.0. Álvaro Vallejo, (for the World Bank) Reviewed by: Marco van der Linden Last edition date: Last review date: Objective The purpose of SMART is to facilitate the implementation and monitoring of CDM afforestation and reforestation projects of the Bio-CF portfolio following approved methodologies. The purpose of this form is the pickup of required information of biomass sample plots data being used in a CDM A/R project activity for the purpose of further monitoring of the project according to the rules of the corresponding A/R methodology. Disclaimer The World Bank accepts no liability for the content of this tool, or for the consequences of any actions taken on the basis of this tool and the information provided in it, unless that information is subsequently confirmed in writing. Any interpretation of the approved CDM-AR methodologies presented in this tool are solely those of the authors and do not necessarily represent those of the World Bank. The user of this holds the liability for the use, interpretation, and application of this tool. Finally, the recipient should check these files and any attachments for the presence of viruses. The World Bank accepts no liability for any damage caused by any virus transmitted by downloading this tool and the files linked to it. Certification We have done our best effort to provide a reliable tool. However, this version of SMART (V.1.0) has not yet been certified and may contain errors, misconceptions and misinterpretations.

40 SMART 04.0 Sampling design SMART Sampling design For collecting information of live trees (measured in a trees sample plot in CDM A/R project activities that uses AR-AM0001/V2, AR-AM0002/V1, AR-AM0003/V4, AR-AM0004/V3, AR-AM0009/V4, AR-AM0010/V3 and AR-ACM0001/V1,V2,V3 methodologies. Version 2.0. (See instructions back) Project ID: Project name: Stratum as per PDD Plot shape Plot area (m²) Number of plots in stratum Comments Page

41 SMART Biomass sample plots data Instructions Project ID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Stratum as per PDD: Please record the name of the stratum as defined in the PDD. Plot shape: Please describe the form of the plot. E.g. circular or square or rectangle. Plot area: Please write down the area of plot in square meters. Number of plots in stratum: Please record the number of sampling plots established in the corresponding stratum. Comments: Use this field to record any observation related to the sampled tree that you consider relevant for the monitoring process.

42 SMART Biomass sample plots data SMART Sample plots - verification data SMART Sample plots - verification data For collecting verification data of all sample plots in CDM A/R project activities that use AR-AM0001/V2, AR- AM0002/V1, AR-AM0003/V4, AR-AM0004/V3, AR-AM0009/V4, AR-AM0010/V3 or AR-ACM0001/V1,V2,V3 methodologies. Version 2.0. (See instructions back) Project ID: Project name: Discrete area ID (unique code) Stand ID (unique code) SID (unique code) Latitude Coordinates Longitude Area from coordinates (ha) Comments Page

43 SMART Biomass sample plots data Instructions Project ID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project. Discrete area ID (DID): DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. Stand ID: Use a unique code to identify each continuous, homogeneous group of trees planted in part or a whole discrete area. SID: Use a unique code to identify the plot. SIDs must be unique at project level. SID codes can have any alphanumeric format. Coordinates: Please type the coordinates of plot. In case of a circular plot, type the coordinates of the central plot. In the case of a rectangular plot, type coordinates of the four corners. Use the format N/S xx x' xx', E/W xx xx' xx''. E.g. N 11 5' 30'', W 84 32' 47''. Use decimals of seconds if you wish. Area from coordinates (ha): Please type plot area. Comments: Use this field to record any observation related to verification data of biomass sample plots that you consider relevant for the monitoring process.

44 SMART Biomass sample plots data SMART 04.2b Trees data from (alive and standing dead) SMART b Trees data form (alive and standing dead) For collecting information of trees (alive and standing dead) measured in trees sample plots in CDM A/R project activities that uses AR- AM0002/V1, AR-AM0009/V4 and AR-ACM0001/V1,2,3 methodologies. Version 2.0. (See instructions back) Project ID: SID: Stratum: Stand ID: Measurement date: Person in charge: Discrete area ID (unique code) TID Dead? Species dbh (cm) h (m) hc or rh (m) Decomposition class Top diameter (cm) Comments Page

45 SMART Biomass sample plots data Instructions Attention: Although live trees and standing dead trees represent different pools, they are both sampled simultaneously using the same trees plots for the sake of simplicity. Deadwood is measured in AR/CDM AR-AM0002, AR-AM0007, AR-AM0009 and AR- ACM0001 approved methodologies. Project ID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project. Discrete area ID (DID): DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. Stratum: Write down the specific stratum to which belongs the current sampling plot. Stand ID: Use a unique code to identify each continuous, homogeneous group of trees planted in part or a whole discrete area. SID: Sample plot ID. SIDs must be unique at project level. SID codes can have any alphanumeric format. TID: Tree identification. Usually, it corresponds to the tree number. Measurement date: Please type the date when plot was measured in the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or Person in charge: Type the name of the person responsible for the measurement. Dead?: Write a check mark if tree is dead. In this case, you must fill also Decomposition class. Attention: If you are using methodology AR-AM0002, you must also measure remaining height and top diameter of broken dead trees. Species: Type the corresponding species. All species listed here must be registered in the 03 - Species data form. dbh (cm): Type the diameter at breast height of tree, in centimeters. h (m): Type the total height of tree, in meters. Frequently, total height is only measured for a subsample of plot trees. In this case, leave all other cells blank.this field can be left blank if total height is not used for calculations when, for example, an allometric model based in dbh only is used. hc or rh (m): Commercial height (hc) or remaining height (rh). For live trees, register hc if there are allometric models using commercial height that will be used for calculations. For dead standing trees, register rh if tree is broken. Leave blank this field otherwise. Decomposition class: Select a number (from 1 to 4) representing the following decomposition classes: 1) Tree with branches and twigs that resembles a live tree (except for leaves); 2) Tree with no twigs but with persistent small and large branches; 3) Tree with large branches only; 4) Bole only, no branches. Top diameter: For dead, standing, broken trees, please record the top diameter of stem. Top diameter is estimated as the ratio of the top diameter to the basal diameter (between 0 and 1). E.g.: 0.5 if top diameter is half of dbh. Comments: Use this field to record any observation related to the sampled tree that you consider relevant for the monitoring process.

46 SMART Biomass sample plots data SMART Non trees (shrubs) data form SMART Non trees (shrubs) data form For collecting information of shrubs measured in a trees sample plot in CDM A/R project activities that uses AR-AM0001/V2, AR-AM0002/V1 and AR-AM0009/V4 methodologies. Version 2.0. (See instructions back) Project ID: DID: Stratum: Stand ID: Sample plot ID: Measurement date: Person in charge: ShID Species DB (cm) Crown diameter (m) H (m) N of stems Comments Page

47 SMART Biomass sample plots data Instructions Project ID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project. Stratum: Write down the specific stratum to which belongs the current sampling plot. Discrete area ID (DID): DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. Stand ID: Use a unique code to identify each continuous, homogeneous group of trees planted in part or a whole discrete area. SID: Sample plot ID. SIDs must be unique at project level. SID codes can have any alphanumeric format. Measurement date: Please type the date when plot was measured in the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or Person in charge: Type the name of the person responsible for the measurement. ShID: Shrub identification number. Use an integer beginning in 1. Species: Type the corresponding species. All species listed here must be registered in the 03 - Species data form. E.g. Cordia alliodora. DB (Diameter at base, cm): Type the diameter at the base of the shrub, in centimeters. Crown diameter (m): Diameter of shrub crown, in meters. You can calculate this by using two orthogonal measurements. This field can be left blank if crown diameter is not used for calculations when, for example, an allometric model based in diameter at base only is used. H (m): Type the total height of tree, in meters. Frequently, total height is only measured for a subsample of plot shrubs. In this case, leave all other cells blank. This field can be left blank if total height is not used for calculations when, for example, an allometric model based only in diameter at the base of the shrub is used. N of stems: Number of stems. If the shrub has multiple stems, please count them and type its number. This field can be left blank if the number of stems is not used for calculations when, for example, an allometric model based in diameter at base only is used. Comments: Use this field to record any observation related to sample plots shrubs data that you consider relevant for the monitoring process.

48 The World Bank Bio Carbon Fund SMART A tool for monitoring afforestation / reforestation project activities SMART Lying deadwood sample plots data form SMART Lying deadwood sample plots data form For collecting information of lying deadwood in CDM A/R project activities Version 2.0. Álvaro Vallejo, (for the World Bank) Reviewed by: Marco van der Linden Last edition date: Last review date: Objective The purpose of SMART is to facilitate the implementation and monitoring of CDM afforestation and reforestation projects following approved methodologies of the Bio-CF portfolio. The purpose of this form is the pickup of required information of lying deadwood sample plots data being used in a CDM A/R project activity for the purpose of further monitoring of the project according to the rules of the corresponding A/R methodology. Disclaimer The World Bank accept no liability for the content of this tool, or for the consequences of any actions taken on the basis of this tool and the information provided in it, unless that information is subsequently confirmed in writing. Any interpretation of the approved CDM-AR methodologies presented in this tool are solely those of the authors and do not necessarily represent those of the World Bank. The user of this holds the liability for the use, interpretation, and application of this tool. Finally, the recipient should check these files and any attachments for the presence of viruses. The World Bank accepts no liability for any damage caused by any virus transmitted by downloading this tool and the files linked to it. Certification We have done our best effort to provide a reliable tool. However, this version of SMART (V.1.0) has not yet been certified and may contain errors, misconceptions and misinterpretations.

49 SMART Lying deadwood sample plots data SMART Deadwood sample plots - Lying dead wood SMART Deadwood sample plots - Lying dead wood For collecting basic information of dead lying wood in CDM A/R project activities using AR-AM0002/V1, AR- AM0009/V4 and AR-ACM0001/V1,V2,V3 methodologies. Version 1.0. (See instructions back) Project ID: DID: Stand ID: Stratum: SID: SID Coordinates (central, bisecting point): Person in charge: Measurement date: Bisecting line 1 Bisecting line 2 Dead wood piece number dead wood diameter (cm) Density state (S/I/R) Dead wood piece number dead wood diameter (cm) Density state Comments Page:

50 SMART Lying deadwood sample plots data Instructions Lying dead wood should be sampled using the line intersect method. Two 50-meter lines are established bisecting each plot (Bisecting lines 1 and 2) and the diameters of the lying dead wood ( 5 cm diameter) intersecting the lines are measured. Project ID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Discrete area ID (DID): DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. Stratum: Write down the specific stratum to which belongs the current sampling plot. Stand ID: Use a unique code to identify each continuous, homogeneous group of trees planted in part or a whole discrete area. SID: Sample plot ID. SIDs must be unique at project level. SID codes can have any alphanumeric format. Please assign SIDs to every plots, even if they are temporal plots. Date of measurement: Please type the date the plot was measured, in the format dd.mm.yyyy. You can use any valid date separator instead of., e.g ; 12/10/2008; Bisecting lines orientation: Bisecting lines are always located one in North to South direction and the other West to East direction. Use a compass to determine this orientation. Line 1 direction: Please record the direction (i.e. the cardinal point or azimuth) of the Line 1. Line 2 direction: Please record the direction (i.e. the cardinal point or azimuth) of the Line 1. Line length (m): Record the total length of transect (E.g. if each line has 50 m. then write down 50). Coordinates central point: Fill out the geographic coordinates of the bisecting point in N/S xx x' xx', E/W xx xx' xx'' format. E.g. N 11 5' 30'', W 84 32' 47''. Use decimals of seconds if you wish. Person in charge: Type the name of the person responsible for the measurement. Dead wood piece number: Assign a consecutive number for wood pieces of each bisecting line. Dead wood diameter (cm): Please record the diameter in centimeters of all those pieces of wood intersecting the bisecting line that are more than 5 cm diameter at the bisection point. Density state: For each piece of deadwood, assign a one letter code (S, I, R) representing the density state of the piece of wood. Strike the wood with a machete. If the blade bounces off, it is sound (S), if it enters slightly is it intermediate (I), and if it causes the wood to fall apart it is rotten (R). Comments: Use this field to record any observation related to verification data of dead wood sample plots that you consider relevant for the monitoring process. Attention: In order to assign wood densities to the three considered density states (sound, intermediate or rotten), a sufficient number of logs in each class must be sampled to represent the wood densities present. It is good practice to sample at least 10 logs of each different density class (IPCC Good Practice Guidance).

51 The World Bank Bio Carbon Fund SMART A tool for monitoring afforestation / reforestation project activities SMART - 06 Litter sample plots data form SMART - 06 Litter sample plots data form For collecting information of Litter plots in CDM A/R project activities Version 2.0. Álvaro Vallejo, (for the World Bank) Reviewed by: Marco van der Linden Last edition date: Last review date: Objective The purpose of SMART is to facilitate the implementation and monitoring of CDM afforestation and reforestation projects following approved methodologies of the Bio-CF portfolio. The purpose of this form is the pickup of required information of litter sample plots data being used in a CDM A/R project activity for the purpose of further monitoring of the project according to the rules of the corresponding A/R methodology. Attention: Litter is measured in AR/CDM AR-AM0002, AR-AM0007, AR-AM0009 and AR-ACM0001 approved methodologies only. You do not require monitoring litter if your project does not use one of these methodologies. Disclaimer The World Bank accept no liability for the content of this tool, or for the consequences of any actions taken on the basis of this tool and the information provided in it, unless that information is subsequently confirmed in writing. Any interpretation of the approved CDM-AR methodologies presented in this tool are solely those of the authors and do not necessarily represent those of the World Bank. The user of this holds the liability for the use, interpretation, and application of this tool. Finally, the recipient should check these files and any attachments for the presence of viruses. The World Bank accepts no liability for any damage caused by any virus transmitted by downloading this tool and the files linked to it. Certification We have done our best effort to provide a reliable tool. However, this version of SMART (V.1.0) has not yet been certified and may contain errors, misconceptions and misinterpretations.

52 SMART Litter sample plots SMART Litter sample plots For collecting basic information of litter in CDM A/R project activities using AR-AM0002/V1, AR-AM0009/V4 and AR-ACM0001/V1,V2,V3, methodologies. Version 2.0. (See instructions back) Project ID: Project name: Person in charge: Discrete area ID (unique code) Stand ID SID Stratum Date Sampling frame area (m²) Number of samples taken Mixed sample fresh weight (kg) Sub-sample wet weight (g) Subsample dry weight (g) Carbon fraction Comments Page:

53 SMART Litter sample plots data Instructions Four litter samples in sampling frames of 1 m² shall be collected per trees sample plot and well mixed into one composite sample. A sub-sample of approximately 0.5 kg from the composite sample of litter is taken, oven dried and weighed to determine the dry weight. The dry to wet weight ratio of the subsample is calculated and used for estimations of the litter dry weight. Litter samples shall be taken at the same time of the year in order to account for natural and anthropogenic influences on the litter accumulation and to eliminate seasonal effects. PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. Person in charge: Type the name of the person responsible for the measurement. If different persons are in charge of different plots, you can type their names in the comments column. Discrete area ID (DID): DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. Stand ID: Use a unique code to identify each continuous, homogeneous group of trees planted in part or a whole discrete area. Stratum: Write down the specific stratum to which belongs the current sampling plot. SID: Sample plot ID. SIDs must be unique at project level. SID codes can have any alphanumeric format. Please assign SIDs to every plots, even if they are temporal plots. Date: Please type the date of samples collection in the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or Sampling frame area ( m²): Please record the area of the sampling frame in square meters. Number of samples taken: Please record how many litter samples are taken in each sampling site. Mixed sample fresh weight (kg): Please record the fresh weight in kg of total litter biomass from the four samples (mixed in one composite plot) taken in each trees sample plot. Sub-sample wet weight (g): Take approximately 05. kg of litter from the composite litter sample. Record the fresh weight of the sub-sample in grams. Sub- sample dry weight (g): Oven dry the litter sub-sample at 105 for 24 hours and record the dry weight of sub-sample in grams. Carbon fraction: Please record the carbon fraction to be applied to litter samples. Comments: Use this field to record any observation related to verification data of litter sample plots that you consider relevant for the monitoring process.

54 The World Bank Bio Carbon Fund SMART A tool for monitoring afforestation / reforestation project activities SMART - 07 Soil carbon sample data form SMART - 07 Soil carbon sample data form For collecting information of soil carbon in CDM A/R project activities Version 2.0. Álvaro Vallejo, (for the World Bank) Reviewed by: Last edition date: Last review date: Objective The purpose of SMART is to facilitate the implementation and monitoring of CDM afforestation and reforestation projects following approved methodologies of the Bio-CF portfolio. The purpose of this form is the pickup of required information of soil carbon data in a CDM A/R project activity for the purpose of further monitoring of the project according to the rules of the corresponding A/R methodology. Attention: Soil organic carbon is monitored in AR/CDM AR-AM0002, AR-AM0006 and AR-ACM0001 approved methodologies only. Soil organic carbon can also be considered in AR-ACM0002, but it is determined ex-ante and no ex-post monitoring is required. Disclaimer The World Bank accept no liability for the content of this tool, or for the consequences of any actions taken on the basis of this tool and the information provided in it, unless that information is subsequently confirmed in writing. Any interpretation of the approved CDM-AR methodologies presented in this tool are solely those of the authors and do not necessarily represent those of the World Bank. The user of this holds the liability for the use, interpretation, and application of this tool. Finally, the recipient should check these files and any attachments for the presence of viruses. The World Bank accepts no liability for any damage caused by any virus transmitted by downloading this tool and the files linked to it. Certification We have done our best effort to provide a reliable tool. However, this version of SMART (V.1.0) has not yet been certified and may contain errors, misconceptions and misinterpretations.

55 SMART 08 Project emissions data SMART a Soil carbon sample field data SMART a Soil carbon sample field data For collecting field basic information of soil carbon in CDM A/R project activities that uses AR-AM0002/V1 and AR-ACM0001/V1,V2 methodologies. Version 2.0. (See instructions back) Project ID: Project name: Person in charge: Discrete area ID (unique code) SID SSID BSID Stratum Date of soil sampling Sample depth (cm) Comments Page:

56 SMART - 07 Soil organic carbon data Instructions For each trees plot, take soil samples using soil corer at each corner of trees plot, and one at the center of the plot (five samples in total), taking samples at the same soil depth. 30 cm depth is recommended. Mix them thoroughly and take a sub sample roughly equivalent to the volume of the soil corer. Bag and label it with the corresponding soil sample ID (SSID) and send it to the laboratory for further processing. Record soil depth at which soil samples were collected. Take an additional soil sample for bulk density determination, bag and label it with the corresponding bulk sample ID (BSID) and send it to the laboratory for further processing. Attention: All sample plots in a given trees sample plot shall be collected to the same depth throughout the entire crediting period. However, the depth may vary among the sample plots. PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. Person in charge: Type the name of the person responsible for the measurement. If different persons are in charge of different plots, you can type their names in the comments column. Discrete area ID (DID): DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. SID: Sample plot ID. SIDs must be unique at project level. SID codes can have any alphanumeric format. Please assign SIDs to every plots, even if they are temporal plots. SSID: Soil Sample ID for Soil Organic Carbon determination. Assign a unique sample ID, using any alphanumeric format. Please clearly identify soil sample to be sent to the laboratory with this ID. BSID: Soil Sample ID for Bulk Density determination. Assign a unique sample ID, using any alphanumeric format. Please clearly identify soil sample to be sent to the laboratory with this ID. Stratum: Write down the specific stratum to which belongs the current sampling plot. Date of soil sampling: Please type the date of samples collection in the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or Sample depth: Record sample depth in cm used to take all samples in the trees plot. Five soil samples must be collected in each trees biomass plot, all at the same depth. 30 cm depth is recommended. Comments: Use this field to record any observation related to soil samples collection that you consider relevant for the monitoring process.

57 SMART - 07 Soil organic carbon data SMART b Soil carbon sample laboratory data SMART b Soil carbon sample laboratory data For collecting laboratory information of soil carbon samples in CDM A/R project activities using AR- AM0002/V1 and AR-ACM0001/V1,V2 methodologies. Version 2.0. (See instructions back) Project ID: Project name: Person in charge: DID SID Soil organic carbon Bulk density Comments SSID C_SOC sample (g C/100 g soil) FC BSID Sample volume (cm³) Sample dry weight (g) Page:

58 SMART - 07 Soil organic carbon data Instructions Two kinds of samples are taken in the field for soil organic carbon sampling in every trees plot: one mixed sample for soil organic carbon concentration and one for bulk density. Samples must be sieved in a 2mm sieve, to remove soil coarse fraction and oven dried. Samples volume can be determined by water displacement using a graduated cylinder. PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. DID: Discrete area ID. DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. SID: Sample plot ID. SIDs must be unique at project level. SID codes can have any alphanumeric format. Please assign SIDs to every plot, even if they are temporal plots. SSID: Soil Sample ID for Soil Organic Carbon determination. Assign a unique sample ID, using any alphanumeric format. Please clearly identify soil sample to be sent to the laboratory with this ID. C_SOC sample: Soil organic carbon concentration of the sample (grams of carbon for each 100 g of soil). FC: Correction factor to adjust the fraction of sample occupied by coarse fragments bigger than 2mm. FC is calculated as 1 (% volume of coarse fragments/100). BSID: Soil Sample ID for Bulk Density determination. Assign a unique sample ID, using any alphanumeric format. Please clearly identify soil sample to be sent to the laboratory with this ID. Sample volume (cm³): Volume of the bulk density sample discounting the volume of coarse particles bigger than 2mm diameter. Sample dry weight (g): Record sample dry weight, discounting the volume of coarse particles bigger than 2mm diameter. Comments: Use this field to record any observation related to soil samples laboratory processing that you consider relevant for the monitoring process.

59 SMART 08 Project emissions data The World Bank Bio Carbon Fund SMART A tool for monitoring afforestation / reforestation project activities SMART Emissions data forms SMART Emissions data forms For collecting information of GHG emissions in CDM A/R project activities Version 2.0. Álvaro Vallejo, (for the World Bank) Reviewed by: Last edition date: Last review date: Objective The purpose of SMART is to facilitate the implementation and monitoring of CDM afforestation and reforestation projects following approved methodologies of the Bio-CF portfolio. The purpose of this form is the pickup of basic project level information of a CDM A/R project activity for the purpose of further monitoring of the project according to the rules of the corresponding A/R methodology. Attention: Emissions from fossil fuels combustion, fertilizers, nitrous oxide (N2O) emissions from Nitrogen fixing trees and fencing with wood from non-renewable sources may be neglected according to decisions of the EB42 and EB44 meetings. Only those projects validated with methodology versions approved before these meetings should monitor these sources of emissions. Disclaimer The World Bank accept no liability for the content of this tool, or for the consequences of any actions taken on the basis of this tool and the information provided in it, unless that information is subsequently confirmed in writing. Any interpretation of the approved CDM-AR methodologies presented in this tool are solely those of the authors and do not necessarily represent those of the World Bank. The user of this holds the liability for the use, interpretation, and application of this tool. Finally, the recipient should check these files and any attachments for the presence of viruses. The World Bank accepts no liability for any damage caused by any virus transmitted by downloading this tool and the files linked to it. Certification We have done our best effort to provide a reliable tool. However, this version of SMART (V.1.0) has not yet been certified and may contain errors, misconceptions and misinterpretations.

60 SMART 08 Project emissions data SMART a - Emissions - Emissions by fossil fuel burning data form SMART a - Emissions - Emissions by fossil fuel burning data form For collecting field basic of GHGs emissions due to fossil fuel burning in CDM A/R project activities that use AR-AM0001/V2, AR-AM0002/V1, AR-AM0003/V4 and AR-AM0004/V3. Version 2.0. (See instructions back) Project ID: Project name: Person in charge: Date of report Consumption year Consumed diesel (l) Diesel emission factor (kg- CO2/l) Consumed gasoline (l) Gasoline emission factor (kg- CO2/l) Comments Page:

61 SMART 08 Project emissions data Instructions Attention: Emissions from fossil fuels combustion may be neglected according to decisions of the EB44 meeting. Only those projects validated with methodology versions approved before this meeting should monitor this source of emissions. PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. Person in charge: Type the name of the person responsible for the measurement. Date of report: Please record the date the record refers to. Consumption year: Please record the year when the consumption happened. Consumed diesel: Please report the amount of consumed diesel in liters, since the last report. Diesel emission factor (kg-co 2 /l): Please record the corresponding emission factor for diesel 1. Consumed gasoline: Please report the amount of consumed diesel in liters, since the last report. Gasoline emission factor (kg-co 2 /l): Please record the corresponding emission factor for diesel. Comments: Use this field to record any observation related to fossil fuel burning that you consider relevant for the monitoring process. 1 There are three possible sources of emission factors: National emission factors: These emission factors may be developed by national programs such as national GHG inventory; Regional emission factors; IPCC default emission factors provided that a careful review of the consistency of these factors with the country conditions has been made. IPCC default factors may be used when no other information is available.

62 SMART 08 Project emissions data SMART b - Emissions - Emissions by fossil fuel burning data form SMART b - Emissions - Emissions by fossil fuel burning data form For collecting basic information of GHGs emissions due to fossil fuel consumption in CDM A/R project activities using methodologies AR- AM0010/V3, AR-ACM0001/V1, AR-ACM0001/V2. Version 2.0. (See instructions back) Project ID: Project name: Vehicle type Load capacity Distance (km) Equipment Hours of use Own/ hired Fuel type DID Date of use Operation Vehicle SEC (lt/km)/ef (km/lt Equipment SEC-t (lt/tonne-km) EF (tco2/gj) NCV (GJ/lt, GJ/kg) Comments Page:

63 SMART 08 Project emissions data Instructions Attention: Leakage from fossil fuels combustion may be neglected according to decisions of the EB44 meeting. Only those projects validated with methodology versions approved before this meeting should monitor this source of emissions. PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. Vehicle type: Please write down every kind of vehicle being used in the A/R CDM project. Following some vehicle types: Cars: two door, four door, pickup truck, sport utility, convertible, wagon. Trucks: tractor truck, solo truck, dump truck, tows truck. Buses: minivan, van, minibus, omnibus. Coaches: single deck, double deck. Load capacity: Please write down load capacity of the vehicle being described in terms of number of passengers or load weight (in kg or tonnes). Distance: Record the distance traveled by the vehicle, in kilometers in the recorded date. Equipment type: In case of mechanical equipment that consumes fossil fuels, register the type of equipment (e.g. portable equipment such as chain saws or stationary equipment such as, water pumps) required by the A/R CDM project activity. Hours of use: In case of mechanical equipment that consumes fossil fuels, please record the number of hours of use. Own/ hired: Select the appropriated option, according to the ownership of the equipment: O for owned by project developers or H for owned by third parties. Fuel type: Select the type of fuel used: gasoline, diesel, alcohol. In case of mix, please give a description (E.g. gasohol 90% gasoline ). Discrete area ID (DID): Discrete areas are separate portions of land that are part of an A/R CDM project and must have a code. This code must be unique at project level. DID codes can have any alphanumeric format, but it is recommended that codes follow a fixed pattern and that enough numbers are reserved to represent all the possible discrete areas of the project. Date of use: Record date of use in dd-mm-yyyy format. Use any valid date separator symbol (like., /, - ). Operation: Record the operation for which the vehicle or equipment was used for. E.g. seedlings transportation. Vehicle SEC (lt/km): Specific energy consumption of vehicle, Equipment SEC-t In case of mechanical equipment that consumes fossil fuels write down the specific energy consumption, either in lt/tonne, in lt/m³ or in lt/km, according to the nature of task. E.g. for a chain saw, it could be 1.53 lt/m³. EF (tco2/gj): CO2 emission factor from fuel consumption 2. NCV (GJ/lt, GJ/kg): Net caloric value of fuel, for stationary or portable equipment 1. Comments: Use this field to record any observation related to fossil fuel burning area that you consider relevant for the monitoring process. 2 This value can be obtained in the 2006 IPCC Guidelines for National Greenhouse Gas Inventories - Volume 2 Energy: Chapter 3, Mobile Combustion and in the IPCC Emission Factor Database (EFDB)

64 SMART 08 Project emissions data SMART-08.3a - Emissions - Biomass burning data SMART-08.3a - Emissions - Biomass burning data For collecting information of biomass burning of discrete areas that are part of a CDM A/R project activity that uses AR-AM0001/V2 methodology. Version 2.0. (See instructions back) Project ID Project name DID Date Area (ha) Non-trees biomass (tond.m./ha) Combustion efficiency N/C ratio Carbon fraction (ton C/tonne d.m.) N2O emissions ratio (t-co2) CH4 emission factor Comments Page

65 SMART 08 Project emissions data Instructions DID: Discrete area ID. DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. PID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Date: Please type burning date. Area (ha): Please type area affected by burning. Non-trees biomass (tonne-d.m./ha): Please type the pre-existing non tree biomass in the burned area. Note that this form is not suitable for areas to be burnt with existing standing trees. Combustion efficiency: Combustion factor values (proportion of prefire biomass consumed) for fires in a range of vegetation types.the combustion efficiencies may be chosen from Table 3.A.1.12 of GPG- LULUCF. If no appropriate combustion efficiency can be used, the IPCC default of 0.5 should be used. N/C ratio: According to the IPCC GPG-LULUCF, it is approximated to be about This is a general default value that applies to leaf litter, but lower values would be appropriate for fuels with greater woody content, if data are available. Carbon fraction (tonne C/tonne d.m.): The carbon fraction is the proportion of carbon in dry matter. If there are no local values available, data from Tables 3A.1.15 and 3A.1.16 of IPCC GPG-LULUCF can be used. N2O emissions ratio (t-co2): N2O emission from biomass burning in slash and burn. IPCC GPG-LULUCF default value: CH4 emission factor: CH4 emission from biomass burning in slash and burn, tonnes CO2-e/yr. IPCC GPG-LULUCF default value is Table 2.5 of the AFOLU Guidelines 2006 has also emission factors for some land uses: Savanna and grassland: 2.3 ± 0.9 Agricultural residues: 2.7 Tropical forest: 6.8 ± 2.0 Extra tropical forest: 4.7 ± 1.9 (Includes all other forest types). Note: For monitoring purposes, the upper limit must be used. E.g.: for grassland burning, use = 3.8. Comments: Use this field to record any observation related to burning of a discrete area that you consider relevant for the monitoring process.

66 SMART 08 Project emissions data SMART-08.3b - Emissions - Biomass burning data SMART-08.3b - Emissions - Biomass burning data For collecting information of biomass burning of discrete areas that are part of a CDM A/R project activity that uses AR-AM0002/V1, AR- AM0002/V3, AR-AM00003/V4 and AR-AM0010/V3 methodologies. Version 1.1. (See instructions back) PID DID Date Area (ha) Aboveground biomass (t-d.m./ha) Combustion efficiency Carbon fraction (t-c/td.m.) C/N ratio N2O emissions ratio (t-co2) CH4 emission factor Comments Page

67 SMART 08 Project emissions data Instructions PID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. DID: Discrete area ID. DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. Date: Please type burning date. Area (ha): Please type area affected by burning. Aboveground biomass (tonne-d.m./ha): Please type the average stock in aboveground biomass prior to burn in tonne of dry matter/ha. Combustion efficiency: Combustion factor values (proportion of prefire biomass consumed) for fires in a range of vegetation types (dimensionless). Tables 3A.1.12 and 3A.1.14 of GPG-LULUCF. If no appropriate combustion efficiency can be used, the IPCC default of 0.5 should be used. Carbon fraction (tonne C/tonne d.m.): The carbon fraction is the proportion of carbon in dry matter. If there are no local values available, data from Tables 3A.1.15 and 3A.1.16 of IPCC GPG-LULUCF can be used. but lower values would be appropriate for fuels with greater woody content, if data are available. N2O emissions ratio (t-co2): N2O emission from biomass burning in slash and burn. IPCC GPG-LULUCF default value: Attention: Although ARAM uses , correct value is CH4 emission factor: CH4 emission from biomass burning in slash and burn, tonnes CO2-e/yr. IPCC GPG-LULUCF default value is Table 2.5 of the AFOLU Guidelines 2006 has also emission factors for some land uses: Savanna and grassland: 2.3 ± 0.9 Agricultural residues: 2.7 Tropical forest: 6.8 ± 2.0 Extra tropical forest: 4.7 ± 1.9 (Includes all other forest types). Note: For monitoring purposes, the upper limit must be used. E.g.: for grassland burning, use = 3.8. Comments: Use this field to record any observation related to burning of a discrete area that you consider relevant for the monitoring process. C/N ratio: According to the IPCC GPG-LULUCF, it is approximated to be about This is a general default value that applies to leaf litter,

68 SMART 08 Project emissions data SMART-08.3c - Emissions - Biomass burning data SMART-08.3c - Emissions - Biomass burning data For collecting information of biomass burning of discrete areas that are part of a CDM A/R project activity that uses the simplified approach of the A/R Methodological Tool Estimation of emissions from clearing, burning and decay of existing vegetation due to implementation of a CDM A/R project activity : AR-ACM001/V2 methodology. Version 2.0. (See instructions back) Trees burnt fraction: 0.6 Shrubs burnt fraction: 0.95 Herbs burnt fraction: 1 (IPCC GPG-LULUCF) PID DID Date Area (ha) Vegetation factors Vegetation type Units CH4 emission factor Aboveground biomass Root-shoot ratio Carbon fraction Aboveground biomass Root-shoot ratio Carbon fraction Aboveground biomass Root-shoot ratio Carbon fraction Aboveground biomass Root-shoot ratio Carbon fraction Aboveground biomass Root-shoot ratio Carbon fraction Aboveground biomass Root-shoot ratio Carbon fraction Aboveground biomass Root-shoot ratio Carbon fraction Aboveground biomass Root-shoot ratio Carbon fraction Trees Shrubs Herbs (t-d.m/ha) (t-c/t-d.m.) (t-d.m/ha) (t-c/t-d.m.) (t-d.m/ha) (t-c/t-d.m.) (t-d.m/ha) (t-c/t-d.m.) (t-d.m/ha) (t-c/t-d.m.) (t-d.m/ha) (t-c/t-d.m.) (t-d.m/ha) (t-c/t-d.m.) (t-d.m/ha) (t-c/t-d.m.) Comments

69 SMART 08 Project emissions data Instructions DID: Discrete area ID. DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. PID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Date: Please type burning date. Area (ha): Please type area affected by burning. Above-ground biomass (tonne-d.m./ha): Please type the pre-existing biomass in the burned area for each type of vegetation (trees, shrubs and herbs). Page ARACM0001 doesn t recommend developing local values, because it is highly probable that this will not be cost-efficient. CH4 emission factor: CH4 emission from biomass burning in slash and burn, kg C as CH4 (kg C burned). IPCC GPG-LULUCF default value is Consult Table 3A.1.15, Annex 3A.1, GPG-LULUCF (IPCC 2003) and Table 2.5 of the AFOLU Guidelines 2006 for specific values. Comments: Use this field to record any observation related to burning of a discrete area that you consider relevant for the monitoring process. Root-Shoot ratio: - Tree root:shoot ratio: values should be selected from Table 3A.1.8 of the GPG-LULUCF (IPCC 2003), or equivalently Table 4.4 of the AFOLU Guidelines (IPCC 2006). - Shrubs: if not better values, use 0.4 from AFOLU Guidelines (IPCC 2006). - Herbs: values should be selected from Table of the GPG LULUCF (IPCC 2003) or equivalently from Table 6.1 of the AFOLU Guidelines (IPCC 2006), by choosing a climate zone that most closely matches the project circumstances. Carbon fraction (t-c/t-d.m.): Carbon fraction is the proportion of carbon in dry matter. If there are no local values available, IPCC the following default values can be used: 0.50 for trees, 0.49 for shrubs and 0.47 for herbs. Burnt fraction: Conservative default factors for the biomass fraction that is bunt can be derived from Table 3A.1.12 of GPG-LULUCF (IPCC 2003) and Table 2.6 of AFOLU Guidelines (IPCC 2006): Trees: 0.6, Shrubs: 0.95, Herbaceous vegetation: 1

70 SMART 08 Project emissions data SMART-08.3d - Emissions - Biomass burning data SMART-08.3d - Emissions - Biomass burning data For collecting information of biomass burning of discrete areas that are part of a CDM A/R project activity that uses the generalized approach of the A/R Methodological Tool Estimation of emissions from clearing, burning and decay of existing vegetation due to implementation of a CDM A/R project activity : AR-ACM001 methodology. Version 2.0. (See instructions back) PID Trees decay fraction DID Shrubs decay fraction Date Herbs decay fraction Planted area ha Trees carbon fraction Burnt area ha Shrubs carbon fraction Herbs carbon fraction Sp N Tree species factors Shrub species factors Herb species factors Comments Species Species Species ABB ABB ABB R/S R/S R/S Decay time Decay time Decay time Species Species Species ABB ABB ABB R/S R/S R/S Decay time Decay time Decay time Species Species Species ABB ABB ABB R/S R/S R/S Decay time Decay time Decay time Species Species Species ABB ABB ABB R/S R/S R/S Decay time Decay time Decay time Species Species Species ABB ABB ABB R/S R/S R/S Decay time Decay time Decay time Comments Page

71 SMART 08 Project emissions data Instructions DID: Discrete area ID. DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. PID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Date: Please type burning date. Planted area (ha): Please type total planted area of the discrete area. Burnt area (ha): Please type burnt area. It is possible a partial burning of vegetation of a given discrete area (e.g., because forest is only being established in strips to allow silvopastoral activities, or to avoid erosion). Decay fractions (trees, shrubs and herbs): Conservative default factors for the biomass fraction that is bunt (and thus, unburnt remaining fraction) can be derived from Table 3A.1.12 of GPG-LULUCF (IPCC 2003) and Table 2.6 of AFOLU Guidelines (IPCC 2006): Trees: 0.4, Shrubs: 0.05, Herbaceous vegetation: 0. ARACM0001 doesn t recommend developing local values, because it is highly probable that this will not be cost-efficient. Root-Shoot ratio: - Tree root:shoot ratio: values should be selected from Table 3A.1.8 of the GPG-LULUCF (IPCC 2003), or equivalently Table 4.4 of the AFOLU Guidelines (IPCC 2006). - Shrubs: if not better values, use 0.4 from AFOLU Guidelines (IPCC 2006). - Herbs: values should be selected from Table of the GPG LULUCF (IPCC 2003) or equivalently from Table 6.1 of the AFOLU Guidelines (IPCC 2006), by choosing a climate zone that most closely matches the project circumstances. CH4 emission factor : CH4 emission from biomass burning in slash and burn, kg C as CH4 (kg C burned). IPCC GPG-LULUCF default value is Consult Table 3A.1.15, Annex 3A.1, GPG-LULUCF (IPCC 2003) and Table 2.5 of the AFOLU Guidelines 2006 for specific values. Comments: Use this field to record any observation related to burning of a discrete area that you consider relevant for the monitoring process. Carbon fractions (trees, shrubs and herbs) (t- C/t-d.m.): Carbon fraction is the proportion of carbon in dry matter. If there are no local values available, IPCC the following default values can be used: 0.50 for trees, 0.49 for shrubs and 0.47 for herbs. Species factors (for trees, shrubs and herbs): Up to five species of each type (trees, shrubs and herbs) can be included in burning calculations. If more than five species are present in the burnt area, please group similar species until having five or less groups of each type. Species: please specify species name. Species must Above-ground biomass (tonne-d.m./ha): Please type the pre-existing biomass in the burned area for each type of vegetation (trees, shrubs and herbs).

72 SMART 08 Project emissions data SMART-08.3e - Emissions - Biomass burning data SMART-08.3e - Emissions - Biomass burning data For collecting information of biomass burning of discrete areas that are part of a CDM A/R project activity that uses AR-AM0004/V3 methodology. Version 0.7. (See instructions back) N/C ratio: N2O emissions ratio (t-co2): CH4 emission factor: PID DID Date Area (ha) Biomass (t-d.m./ha) Proportion burnt Combustion efficiency Carbon fraction (t-c/t-d.m.) Comments

73 SMART 08 Project emissions data Instructions N/C ratio: Nitrogen-carbon ratio (IPCC default = 0.01); dimensionless. N2O emissions ratio (t-co2): Emission ratio for N2O, dimensionless (IPCC default factor = 0.07). CH4 emission factor: Emission factor for CH4, t CH4/(t C) IPCC default emission ratio for CH4 = Table 2.5 of the AFOLU Guidelines 2006 has also emission factors for some land uses: Savanna and grassland: 2.3 ± 0.9 Agricultural residues: 2.7 Tropical forest: 6.8 ± 2.0 Extra tropical forest: 4.7 ± 1.9 (Includes all other forest types). Page Combustion efficiency: Average biomass combustion efficiency (IPCC default = 0.1); dimensionless. The combustion efficiencies may be chosen from Table 3.A.1.12 of GPG-LULUCF. If no appropriate combustion efficiency can be used, the IPCC default of 0.5 should be used. Carbon fraction (tonne C/tonne d.m.): The carbon fraction is the proportion of carbon in dry matter. If there are no local values available, data from Tables 3A.1.15 and 3A.1.16 of IPCC GPG-LULUCF can be used. Comments: Use this field to record any observation related to burning of a discrete area that you consider relevant for the monitoring process. Note: For monitoring purposes, the upper limit must be used. E.g.: for grassland burning, use = 3.8. DID: Discrete area ID. DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. PID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Date: Please type burning date. Area (ha): Please type area affected by burning. Biomass (tonne-d.m./ha): Please type the pre-existing biomass before burning in the burned area. Proportion burnt: The proportion of biomass burnt can be estimated by sampling after burning.

74 SMART Organic and synthetic fertilizers identification SMART Organic and synthetic fertilizers identification For collecting identification of fertilizers used in CDM A/R project activities that uses AR- AM0001/V2 (See instructions back) Project ID: Project name: Person in charge: Fertilizer ID (use unique identifier) Organic/ synthetic (O/S) NC_f (nitrogen content. %) Description and comments Page:

75 SMART 08.4 Fertilization data Instructions PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. Person in charge: Type the name of the person responsible for the measurement. Fertilizer ID. For each kind of fertilizer that has a different chemical composition, assign a unique identification code. Assign new fertilizer ID if new fabrication batches of organic fertilizer differ from previous ones. Organic/ synthetic: write O if registering an organic fertilizer. Write S for synthetic fertilizers. NC_f (nitrogen content %): Nitrogen content as percentage of total fertilizer. Description and comments: Give a short description of fertilizer (source, chemical composition, producer, etc) and any other relevant comments.

76 SMART 08.4 Fertilization data SMART Fertilizer purchases and fabrication batches SMART Fertilizer purchases and fabrication batches For collecting data of fertilizers used in CDM A/R project activities that uses AR-AM0001/V2 (See instructions back) Project ID: Project name: Person in charge: Date Invoice code Fertilizer ID Fertilizer type Fertilizer quantity Units (kg or tone) Comments Page:

77 SMART 08.4 Fertilization data Instructions PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. Person in charge: Type the name of the person responsible for the measurement. Date: Register purchase or fabrication date. Use dd.mm.yyyy format. Invoice code: Write Id of purchase receipt or leave blank if registering a fabrication batch of organic fertilizer. Fertilizer ID: Select fertilizer ID from the registered fertilizer ID list (form in Annex 1.1) or Registered table in Excel file SMART - 14-Fert A Tool (fertilization).xls Fertilizer type: Write S if referring to a synthetic fertilizer or O for an organic fertilizer. Fertilizer quantity: Write the amount of fertilizer purchased. Units: Write kg if fertilizer amount is given in kilograms or tonne if given in tonnes. Comments: Write down any relevant comment.

78 The World Bank Bio Carbon Fund SMART A tool for monitoring afforestation / reforestation project activities SMART Leakage data form SMART Leakage data form For collecting information of GHGs emissions by leakage in a CDM A/R project activity Version 2.0. Álvaro Vallejo, (for the World Bank) Reviewed by: Last edition date: Last review date: Objective The purpose of SMART is to facilitate the implementation and monitoring of CDM afforestation and reforestation projects following approved methodologies of the Bio-CF portfolio. The purpose of this form is the pickup of information on GHGs emissions by leakage in a CDM A/R project activity for the purpose of further monitoring of the project according to the rules of the corresponding A/R methodology. Attention: Leakage from fossil fuels combustion and fencing with wood from nonrenewable sources may be neglected according to decisions of the EB44 meeting. Only those projects validated with methodology versions approved before this meeting should monitor these sources of leakage. Disclaimer The World Bank accept no liability for the content of this tool, or for the consequences of any actions taken on the basis of this tool and the information provided in it, unless that information is subsequently confirmed in writing. Any interpretation of the approved CDM-AR methodologies presented in this tool are solely those of the authors and do not necessarily represent those of the World Bank. The user of this holds the liability for the use, interpretation, and application of this tool. Finally, the recipient should check these files and any attachments for the presence of viruses. The World Bank accepts no liability for any damage caused by any virus transmitted by downloading this tool and the files linked to it. Certification We have done our best effort to provide a reliable tool. However, this version of SMART (V.1.0) has not yet been certified and may contain errors, misconceptions and misinterpretations.

79 SMART 09 Leakage data forms SMART a - Leakage - Leakage by fossil fuel burning data form SMART a - Leakage - Leakage by fossil fuel burning data form For collecting field basic of GHGs emissions due to fossil fuel burning in CDM A/R project activities that use AR-AM0001/V2, AR-AM0002/V1, AR-AM0003/V4 and AR-AM0004/V3 methodologies. Version 2.0 (See instructions back) Project name: PID Date of report Consumption year Consumed diesel (l) Diesel emission factor (kg- CO2/l) Consumed gasoline (l) Gasoline emission factor (kg-co2/l) Comments Page:

80 SMART 09 Leakage data forms Instructions Attention: Leakage from fossil fuels combustion may be neglected according to decisions of the EB44 meeting. Only those projects validated with methodology versions approved before this meeting should monitor this source of emissions. PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. Person in charge: Type the name of the person responsible for the measurement. Date of report: Please record the date the record refers to. Consumption year: Please record the year when the consumption happened. Consumed diesel: Please report the amount of consumed diesel in liters, since the last report. Diesel emission factor (kg-co 2 /l): Please record the corresponding emission factor for diesel 3. Consumed gasoline: Please report the amount of consumed diesel in liters, since the last report. Gasoline emission factor (kg-co 2 /l): Please record the corresponding emission factor for diesel 4. Comments: Use this field to record any observation related to fossil fuel burning that you consider relevant for the monitoring process. 3 There are three possible sources of emission factors: National emission factors: These emission factors may be developed by national programs such as national GHG inventory; Regional emission factors; IPCC default emission factors provided that a careful review of the consistency of these factors with the country conditions has been made. IPCC default factors may be used when no other information is available. 4 There are three possible sources of emission factors: National emission factors: These emission factors may be developed by national programs such as national GHG inventory; Regional emission factors; IPCC default emission factors provided that a careful review of the consistency of these factors with the country conditions has been made. IPCC default factors may be used when no other information is available.

81 SMART b - Leakage - Leakage by fossil fuel burning data form SMART b - Leakage - Leakage by fossil fuel burning data form For collecting basic information of GHGs emissions due to fossil fuel consumption in CDM A/R project activities using methodologies AR- AM0010/V3 and AR-ACM0001/V1. Version 2.0. (See instructions back) Project ID: Project name: Vehicle type Load capacity Distance (km) Equipment Hours of use Own/ hired Fuel type DID Date of use Operation Vehicle SEC (lt/km)/ef (km/lt Equipment SEC-t (lt/tonne-km) EF (tco2/gj) NCV (GJ/lt, GJ/kg) Comments Page:

82 SMART 09 Leakage data forms Instructions Attention: Leakage from fossil fuels combustion may be neglected according to decisions of the EB44 meeting. Only those projects validated with methodology versions approved before this meeting should monitor this source of emissions. Vehicle type: Please write down every kind of vehicle being used in the A/R CDM project. Following some vehicle types: Cars: two door, four door, pickup truck, sport utility, convertible, wagon. Trucks: tractor truck, solo truck, dump truck, tows truck. Buses: minivan, van, minibus, omnibus. Coaches: single deck, double deck. Load capacity: Please write down load capacity of the vehicle being described in terms of number of passengers or load weight. (kg or tonnes). Distance (km): Record the distance traveled by the vehicle, in kilometers in the recorded date. Equipment type: In case of mechanical equipment that consumes fossil fuels, register the type of equipment (e.g. portable equipment such as chain saws or stationary equipment such as, water pumps) required by the A/R CDM project activity. Hours of use: In case of mechanical equipment that consumes fossil fuels, please record the number of hours of use. it is recommended that codes follow a fixed pattern and that enough numbers are reserved to represent all the possible discrete areas of the project. Date of use: Record date of use in dd-mm-yyyy format. Use any valid date separator symbol (like., /, - ). Operation: Record the operation for which the vehicle or equipment was used for. E.g. seedlings transportation. Vehicle SEC (lt/km): Specific energy consumption of vehicle. Equipment SEC-t: In case of mechanical equipment that consumes fossil fuels write down the specific energy consumption, either in lt/tonne, in lt/m³ or in lt/km, according to the nature of task. E.g. for a chain saw, it could be 1.53 lt/m³. EF (tco2/gj): CO2 emission factor from fuel consumption. 5 NCV (GJ/lt, GJ/kg): Net caloric value of fuel, for stationary or portable equipment 1. Comments: Use this field to record any observation related to the discrete area that you consider relevant for the monitoring process. Own/ hired: Select the appropriated option, according to the ownership of the equipment: O for owned by project developers or H for owned by third parties. Fuel type: Select the type of fuel used: gasoline, diesel, alcohol. In case of mix, please give a description (E.g. gasohol 90% gasoline ). Discrete area ID (DID): Discrete areas are separate portions of land that are part of an A/R CDM project and must have a code. This code must be unique at project level. DID codes can have any alphanumeric format, but 5 This value can be obtained in the 2006 IPCC Guidelines for National Greenhouse Gas Inventories - Volume 2 Energy: Chapter 3, Mobile Combustion and in the IPCC Emission Factor Database (EFDB)

83 SMART- 09.2a1 Leakage Grazing displacement Initial stock SMART- 09.2a1 Leakage Grazing displacement Initial stock For collecting information of initial livestock in discrete areas that are part of a CDM A/R project activity that uses AR-AM0003/V4, AR-AM0004/V3 or AR-AM0004/V4 methodology. Version 1.1. (See instructions back) Project ID: Project name: DID Date of survey Number of grazing animals Comments Ovine Bovine Equine Page

84 SMART 09 Leakage data forms Instructions Attention! : The survey of initial stock must be completed during the first year of project implementation. PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. DID: Discrete area ID. DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. This initial livestock survey must be completed for all existing DIDs. If a given DID was not used for livestock, please register it with zeros. Date of survey: Please type the date of the livestock survey using the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or Number of grazing animals: Please record the average number of grazing animals present in the current discrete area. This number represents the annual average stock in the area. If livestock flows from/to other areas, calculate a weighted annual average. E.g., if there are 8 cows in a given discrete area during 7 months of the year, then the number of grazing animals is 8*7/12 = Please record each kind of livestock separately (ovine = sheeps, goats; bovine = cows, buffalos, water buffalos, bisons; equine = horses, asses, mules). I.e., consider all kinds of ovines as the same group. Comments: Use this field to record any observation related to the initial livestock present in the current discrete area that you may consider relevant for the monitoring process.

85 SMART 09 Leakage data forms SMART- 09.2a2 - Leakage - Grazing displacement - Existing stock SMART- 09.2a2 - Leakage - Grazing displacement - Existing stock For collecting information of existing livestock in discrete areas that are part of a CDM A/R project activity that uses AR-AM0003/V4, AR-AM0004/V3 or AR-AM0004/V4 methodology. Version 1.1. (See instructions back) Project ID: Project name: DID Date of survey Number of grazing animals Comments Ovine Bovine Equine Page

86 SMART 09 Leakage data forms Instructions Attention! : Monitoring of leakage due to conversion of land to grazing land will not be necessary 5 years after actual date of the last measure taken to control animal grazing, because any conversion of land to grazing land would not be reasonably attributable to the A/R CDM project activity. PID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. DID: Discrete area ID. DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. This initial livestock survey must be completed for all existing DIDs. If a given DID was not used for livestock, please register it with zeros. Date of survey: Please type the date of the livestock survey using the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or Number of grazing animals: Please record the average number of grazing animals present in the current discrete area. This number represents the annual average stock in the area. If livestock flows from/to other areas, calculate a weighted annual average. E.g., if there are 8 cows in a given discrete area during 7 months of the year, then the number of grazing animals is 8*7/12 = Please record each kind of livestock (ovine = sheeps, goats; bovine = cows, buffalos, water buffalos, bisons; equine = horses, asses, mules) separately, i.e., consider all kinds of ovines as the same group. Comments: Use this field to record any observation related to the initial livestock present in the current discrete area that you may consider relevant for the monitoring process.

87 SMART 09 Leakage data forms SMART- 09.2b1 - Leakage - Animal grazing displacement to unidentified areas SMART- 09.2b1 - Leakage - Animal grazing displacement to unidentified areas For collecting information of livestock displacement to unidentified areas outside project limits in CDM A/R project activities that uses the A/R methodological tool Estimation of GHG emissions related to displacement of grazing activities in A/R CDM project activity (Version 01), used in AR-AM0005/V4 and ACM0001/V1,V2,V3 methodologies. Version 1.1. (See instructions back) Project ID: Project name: Date of survey Animal type DMI_g (kg d.m /head/day) Animal heads ANPP (t-d.m/ha) Unidentified area (ha) Comments Page

88 SMART 09 Leakage data forms Instructions PID: Use a unique code to identify the project. Project ID codes can have any alphanumeric format. DID: Discrete area ID. DIDs must be the same used in the 02.1 General discrete areas data form to identify each discrete area. This initial livestock survey must be completed for all existing DIDs. If a given DID was not used for livestock, please register it with zeros. Date of survey: Please type the date of the livestock survey using the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or Animal type: Select the corresponding animal type from the following list: Cattle - Africa - mature female; Cattle - Africa - mature male; Cattle - Africa - young; Cattle - Asia - mature female; Cattle - Asia - mature male; Cattle - Asia - young; Cattle - India - mature female; Cattle - India - mature male; Cattle - India - young; Cattle - Latin America - mature female; Cattle - Latin America - mature male; Cattle - Latin America - young; Sheep - mature female; Sheep - mature male; Sheep - young. DMI_g (kg dry matter/head/day): Daily dry matter intake per grazing animal of animal type. H: Number of heads of animal type g that are displaced to unidentified lands in year t and/or number of head of animals type g that are fed by the fodder collected from unidentified lands in considered year. ANPP (t d.m./ha/yr): Above-ground net primary productivity of corresponding parcel in tonnes dry biomass. ANPP values can be taken from table of IPCC GPG guidance, also provided in Appendix A of the A/R methodological tool Estimation of GHG emissions related to displacement of grazing activities in A/R CDM project activity (Version 01). Alternatively, if local data for ANPP of grasslands are available, it can be used instead. Unidentified area (ha): Area of unidentified land required to feed animals that are displaced in corresponding year. Comments: Use this field to record any observation related to animal grazing displacement to unidentified areas that you may consider relevant for the monitoring process.

89 SMART- 09.2b2 - Leakage - Animal grazing displacement to grassland areas SMART- 09.2b2 - Leakage - Animal grazing displacement to grassland areas For collecting information of livestock displacement to grassland areas outside project limits in CDM A/R project activities that uses the A/R methodological tool Estimation of GHG emissions related to displacement of grazing activities in A/R CDM project activity (Version 01), used in AR-AM0005/V4 and ACM0001/V1,V2,V3 methodologies. Version 1.1. (See instructions back) Project ID: Project name: Parcel ID Date of survey Animal type DMI_g (k d.m/day) H_exist H_displ ANPP (td.m/ha) Parcel area (ha) DMI_t (ton d.m /head/yr) Area required (ha) Parcel SOC (t- C/ha) Comments Page

90 SMART 09 Leakage data forms Instructions PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. Date of survey: Please type the date of the livestock survey using the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or Animal type: Select the corresponding animal type from the following list: Cattle - Africa - mature female; Cattle - Africa - mature male; Cattle - Africa - young; Cattle - Asia - mature female; Cattle - Asia - mature male; Cattle - Asia - young; Cattle - India - mature female; Cattle - India - mature male; Cattle - India - young; Cattle - Latin America - mature female; Cattle - Latin America - mature male; Cattle - Latin America - young; Sheep - mature female; Sheep - mature male; Sheep - young. DMI_g (k d.m/day): Daily dry matter intake per grazing animal of corresponding animal type. H_exist: Number of heads of the corresponding animal type existing on corresponding parcel and/or being fed by fodder produced on that parcel before displacement of animals in the corresponding survey year. H_displ: Number of heads of the corresponding animal type displaced and/or fed by fodder for which production is displaced to the corresponding parcel in the corresponding survey year. ANPP (t d.m./ha/yr): Above-ground net primary productivity of corresponding parcel in tonnes dry biomass. ANPP values can be taken from table of IPCC GPG guidance, also provided in Appendix A of the A/R methodological tool Estimation of GHG emissions related to displacement of grazing activities in A/R CDM project activity (Version 01). Alternatively, if local data for ANPP of grasslands are available, it can be used instead. Parcel area (ha): The area of each identified parcel of grassland that receives displaced grazing activities in the survey year. DMI_t (ton d.m /head/yr): Total dry matter intake of grazing animal on the corresponding parcel in the survey year. Please calculate this value using the following equation: DMI _ g *( H _ exist H _ displ ) DMI _ t * Area required (ha): Total area of land required for the survey year to sustain the grazing activities displaced to the corresponding parcel. Please calculate this value using the following equation: DMI _ t Area required ANPP If Area required is bigger than Parcel area, please fill the value of Parcel SOC. Parcel SOC (t- C/ha): Reference soil organic stocks for corresponding parcel. Comments: Use this field to record any observation related to animal grazing displacement to unidentified areas that you may consider relevant for the monitoring process.

91 SMART- 09.2b3 - Leakage - Animal grazing displacement to forest areas SMART- 09.2b3 - Leakage - Animal grazing displacement to forest areas For collecting information of livestock displacement to forest areas outside project limits in CDM A/R project activities that uses the A/R methodological tool Estimation of GHG emissions related to displacement of grazing activities in A/R CDM project activity (Version 01), used in AR-AM0003/V4, AR-AM0004/V3 and ACM0001/V1,V2,V3 methodologies. Version 2.0. (See instructions back) Project ID: Project name: Date of survey Unidentified area (ha) Total forest area (ha) B_ab (td.m./ha) B_Litter (td.m./ha) B_dead (td.m./ha) R_ave Comments Page

92 SMART 09 Leakage data forms Instructions PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. Date of survey: Please type the date of the livestock survey using the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or Unidentified area (ha): Area of unidentified land required to feed animals that are displaced in year of survey, taken from SMART- 09.2b - Leakage - Animal grazing displacement to unidentified areas. Total forest area (ha): Total area of identified forest land deforested to feed animals displaced in survey year. B_ab (t-d.m./ha): Average above-ground woody biomass of forest land to which animals are displaced. B_Litter (t-d.m./ha): Average litter on forest land to which animals are displaced. B_dead (t-d.m./ha): Average dead wood on forest land to which animals are displaced. R_ave: Average biomass-weighted root-to-shoot ratio appropriate for biomass stock of forest land to which animals are displaced. Comments: Use this field to record any observation related to animal grazing displacement to forest areas that you may consider relevant for the monitoring process.

93 SMART- 09.3a1- Leakage - Conversion to cropland - Household level Before project activities SMART- 09.3a1- Leakage - Conversion to cropland - Household level Before project activities For collecting information at household level of leakage due to conversion of land to crop land as a consequence of the implementation of a CDM A/R project activity that use AR-AM0004/V3 methodology. Version 0.7. (See instructions back) Project ID: Project name: Date of survey: Total number of households occupying land inside the project boundary: Random selected households (10% of the households, or a minimum of 30) Survey Household CS_AD CS_b date head name (t-co2e/ha) (t-co2e/ha) Sample household ID Total displaced area (ha) Comments Page

94 SMART 09 Leakage data forms Instructions Leakage through land conversion due to activity displacement should be monitored through sampling the households and communities displaced from land by the project. However, leakage due to conversion of land is not attributable to the AR CDM project activity if the conversion of land occurs 5 or more years after the displacement of the activity to areas outside the project boundary. Leakage estimation includes monitoring households with identifiable areas of land conversion and conservatively applying a deforestation area to households with unidentifiable areas of land conversion. PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. Date of survey: Please type the date of the livestock survey using the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or TNHH - Total number of households occupying land inside the project boundary: Please record the total number of households occupying land inside the project boundary that will lead to activity displacement outside project area. Household head name: Please record the name of the person in charge of the household. Sample household ID: Please record a unique ID for the household. CS_AD (t-co2e/ha): Locally derived carbon stock (including all the five eligible carbon pools) of area of land on which activities shifted. If for the same household there is more than one area to which activities shifted, please record the average value. CS_b (t-co2e/ha): Carbon stock of the baseline (including all the five eligible carbon pools) of area of land surveyed from which activities shifted. Total displaced area (ha): Total area of land within project boundaries each sampled household will be displaced from due to project activities. Comments: Use this field to record any observation related to activities displacement that you may consider relevant for the monitoring process.

95 SMART 09 Leakage data forms SMART- 09.3a2- Leakage - Conversion to cropland - Household level One year/five years after displacement SMART- 09.3a2- Leakage - Conversion to cropland - Household level One year/five years after displacement For collecting information at household level of leakage due to conversion of land to crop land as a consequence of the implementation of a CDM A/R project activity that use AR-AM0004/V3 methodology. Version 2.0. (See instructions back) Project ID: Project name: Date of survey: Land conversion outside project area Survey Sample IAC (ha) TACP date household ID (ha) Preconverted land stratum CS (t- CO2e/ha) CSU (t- CO2e/ha) Comments Page

96 SMART 09 Leakage data forms Instructions - Classify sampled households as either having identifiable or unidentifiable converted lands. Households which have moved from the area or which cannot be found should be placed in the unidentifiable households category; - Measure area of identifiable land each household has converted since displacement of pre-project activities (IAC); - Classify each area of identifiable converted land into a pre-conversion land cover stratum; - Measure the carbon stock (including all 5 pools) in each land cover stratum using methods from IPCC GPG-LULUCF chapter 4.3; - Determine the mean conservative forest biomass stock for the project region (CS ), if no mean regional stock data exists, use mean national stock reported in IPCC GPG-LULUCF (Table 3A.1.4). PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. Date of survey: Please type the date of the livestock survey using the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or Sample household ID: Please record the unique ID for the household. IAC (ha): Identifiable areas converted by household in corresponding stratum. TACP (ha): Total area of cropland planted that is owned by household Pre-converted land stratum: Please record the baseline stratum of the converted track of land. CS (t-co2e/ha): Mean conservative forest biomass stock for the project region. CSU (t-co2e/ha): Locally derived carbon stock of identified lands (including all the five eligible carbon pools) of corresponding stratum. Comments: Use this field to record any observation related to activities displacement to forest areas that you may consider relevant for the monitoring process.

97 SMART 09 Leakage data forms SMART- 09.4a- Leakage - Displacement of fuel wood collection SMART- 09.4a- Leakage - Displacement of fuelwood collection For collecting information of leakage due to displacement of fuelwood collection as a consequence of the implementation of a CDM A/R project activity that use AR-AM0003/V4, AR-AM0004/V3 and AR-ACM0001/V1,V2 Version 2.0. (See instructions back) Project ID: Project name: Year FG_BL (m³/year) FG_AR (m³/year) FG_NGL (m³/year) D BEF CF Comments Page

98 SMART 09 Leakage data forms Instructions For each verification period, estimate the average fuel-wood collection in the project area to estimate the volume of fuelwood gathering displaced outside the project boundary. Monitoring can be done by periodically interviewing households, through a Participatory Rural Appraisal (PRA) or field-sampling. PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. Date of survey: Please type the date of the livestock survey using the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or FG_BL (m³/year): Average pre-project annual volume of fuelwood gathering in the project area estimated ex-ante and specified in the AR-CDM-PDD. FG_AR (m³/year): volume of fuelwood gathered in the project area according to monitoring results determined interviewing households, through a Participatory Rural Appraisal or field-sampling. FG_NGL (m³/year): Fuelwood gathered in new grassland areas. In the NGL areas specified in the AR-CDM-PDD for monitoring of displaced animal grazing, monitor the volume of fuelwood gathering that is supplied to preproject fuelwood collectors or charcoal producers. Monitored volume of fuelwood gathering in NGL areas and supplied to pre-project fuelwood collectors or charcoal producers. D (tones of dry matter/m³): Basic wood density. See IPCC GPG-LULUCF - Table 3A.1.9. BEF: Biomass expansion factor for converting volumes of extracted round-wood to total above-ground biomass (including bark). See IPCC GPG-LULUCF - Table 3A.1.10 CF (tones of C/tones of dry matter): Carbon fraction of extracted fuelwood (default = 0.5). Comments: Use this field to record any observation related to fuel-wood collection displaced outside the project boundary that you may consider relevant for the monitoring process.

99 SMART 09 Leakage data forms SMART- 09.5a - Use of non-renewable wood for fencing SMART- 09.5a - Use of non-renewable wood for fencing For collecting information of leakage due to the use of non-renewable wood for fencing as a consequence of the implementation of a CDM A/R project activity that use AR-AM0003/V4, AR-AM0004/V3 and AR-ACM0001/V1,V2 methodologies. Version 2.0. (See instructions back) Project ID: Project name: Date PAR (m) DBP (m) FNRP (%) AVP (m³) D (t d.m./m³) BEF_2 CF Comments Page

100 SMART 09 Leakage data forms Instructions If wooden posts from non-renewable sources are used due to project activities, this source of leakage must be monitored periodically, measuring the lengths of the perimeters that are fenced, average distance between wood posts and the fraction of posts that is produced off-site from non-renewable sources. PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. Date: Please type the date of the survey of non-renewable wood used for fencing using the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or PAR (m): Perimeter of the areas fenced in the monitoring year. DBP (m): Average distance between wood posts. FNRP (%): Fraction of posts from off-site non-renewable sources. AVP (m³): Average volume of wood posts estimated from sampling. D (t d.m./m³): Basic wood density. See IPCC GPG-LULUCF - Table 3A.1.9. BEF_2 : Biomass expansion factor for converting volumes of extracted round-wood to total above-ground biomass (including bark). See IPCC GPG-LULUCF Table 3A.1.10 for default values. CF: Carbon fraction of dry matter. IPCC default value = 0.5. Comments: Use this field to record any observation related to the use of wood from non-renewable sources for fencing that you may consider relevant for the monitoring process.

101 SMART 09 Leakage data forms SMART- 09.5b - Use of non-renewable wood for fencing SMART- 09.5b - Use of non-renewable wood for fencing For collecting information of leakage due to the use of non-renewable wood for fencing as a consequence of the implementation of a CDM A/R project activity that use AR-AM0009/V3 methodology. Version 2.0. (See instructions back) Project ID: Project name: Monitoring date Stratum PAR (m) DBP (m) AVP (m³) W_p (%) D CEF R CF Comments Page

102 SMART 09 Leakage data forms Instructions If wooden posts from non-renewable sources are used due to project activities, this source of leakage must be monitored periodically, measuring the lengths of the perimeters that are fenced, average distance between wood posts and the fraction of posts that is produced off-site from non-renewable sources. PID: Project ID. Use a unique code to identify the project. Project ID codes can have any alphanumeric format. Project name: Write down the name of the project as it is used every day. Date: Please type the date of monitoring using the format dd?mm?yyyy, where? represents any valid date separator such as., / or -. E.g or 12/10/2008 or Stratum: PAR (m): Linear meters for fencing in corresponding stratum during the corresponding monitoring year. DBP (m): Distance between wood posts in fences for stratum. AVP (m³): Average volume of each wood post for fences. W_p (%): Waste fraction of unsustainable logging to extract wood posts D (t/m³): Basic wood density for corresponding tree species. CEF: Crown expansion factor: the ratio of crown and stem biomass to stem biomass for corresponding tree species. R: Root-shoot ratio appropriate for biomass stock for corresponding species. CF: Carbon fraction of biomass for corresponding tree species. Comments: Use this field to record any observation related to the use of wood from non-renewable sources for fencing that you may consider relevant for the monitoring process.

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