When managing a carbon project, there are parameters which need to be recorded and monitored on an ongoing basis throughout the duration of the project. This is necessary in order to attribute emission reductions to certain activities, and to demonstrate fulfillment of social/other environmental goals when a social carbon standard is applied (e.g. the Gold Standard, SocialCarbon Standard and Women’s Carbon Standard). This section provides details on:
- The parameters to monitor throughout the programme
- How to manage and store data
- How to gather data using different sampling approaches
Each carbon project has a monitoring plan that defines the procedures for measuring and reporting parameters. The monitoring plan is part of the programme design documents (PDD) and undergoes third-party validation prior to registration of the carbon project. When the project is verified, a third party will assess if the project did monitor all parameters in accordance with the monitoring plan of the PDD.
1. Parameters to monitor
The parameters to be monitored will depend on the methodology and standard applied (e.g. a CDM plus Gold Standard project will have parameters to monitor from the CDM methodology and the Gold Standard). An overview of the CDM and Gold Standard carbon accounting methodologies is available here.
The parameters used to determine the baseline are established before the start of the project and remain fixed for the duration of the crediting period. As they remain fixed, these parameters are not monitored.
The project operation parameters are recorded throughout the lifetime of the project. Depending on the parameter, they are either continuously recorded for every stove that is distributed/sold as and when this occurs or monitored annually or once every two years. Monitoring involves locating distributed stoves and users and collecting information from them.
|Baseline Parameters||Project Operation Parameters|
|type of stove used before project implementation||none||end user info||fraction of new stoves in operation|
|quantity of woody biomass used in old stoves||location||stove efficiency and quantity of biomass/fuel used in new stoves|
|fraction of non-renewable biomass (fNRB)||serial numbers||continued use of old stoves|
|efficiency of old stoves||technology type||leakage|
|number of stoves distributed||sustainability criteria, co-benefits|
The parameters to be monitored under the CDM and Gold Standard methodologies are often steeped in jargon and difficult to follow. Here, some of the most common parameters to monitoring are outlined in simple language, including tips for how to monitor them.
Project operation parameters: Recorded parameters
Common parameters to be recorded once at the point of sale or distribution of each stove include:
Type of technology – Useful if more than one cookstove type is distributed under the project, and to later prove that the cookstoves distributed are eligible for inclusion under the project during verification (e.g. if project documentation states that only solar cookers are eligible under the programme, then inclusion of a rocket stove would not be permitted).
Type of end-user – Useful if only certain types of end-users are eligible to be included in the project (e.g. a CDM micro-scale project may only allow the end-user to be households, communities or small/medium enterprises).
Name of user, address and contact details – The end-user’s name, address and contact details are required in order to ensure that the cookstove can be located and identified during monitoring. These details can be recorded at sale of the cookstove along with the serial number and forwarded to the entity managing the centralized project database.
Location of the product – In addition to recording the address, or in situations where establishing an address is difficult, the GPS coordinates of the stove can be recorded. This will require physically visiting the site of cookstove use to record GPS coordinates.
Serial numbers of product – To avoid double counting of emission reductions it is recommended that each product be issued with a unique identification, or serial number. This allows each cookstove to be identified as belonging to the programme or carbon project. The serial numbers of each installed cookstove are recorded in a centralized project database, which can be programmed to either not allow for repeat entries to be made or to facilitate checking for repeat entries. For an example case study of how serial numbers are generated and applied see SimGas’s Biogas Programme.
Whilst recording the serial number, user name, address, contact details and GPS coordinates in person is the most reliable method of recording information at installation (especially since this provides the opportunity to give proper use and maintenance training to the cookstove user) it may not always be possible to do so. Alternatives include:
- Providing user incentives to leave their personal details: Incentives could include a discount on the technology, one year’s free warranty or free mobile phone credit for users that provide their personal details via text message or phone to the carbon project developer. This requires setting up an automated text message system which asks the user a series of questions (e.g. their name, address etc.) or having a phone line open to receiving information.
- Partnering with distribution centers: involves forming partnerships with local retailers, NGOs and small businesses that will have direct contact with users and will sell cookstoves on behalf of the programme. In this situation, the carbon project developer would train partners on how to collect the required information and transfer it for entry into a centralized project database. Impact Carbon’s Ugastove Project, for example, collects user information through cooperating with distribution centers.
- Using advanced technology solutions: user and technological data is recorded electronically, allowing the transfer of data directly to the database. This reduces input errors and saves time. Proyecto Mirador’s cookstove project, for example, uses a computerised record-keeping system via smartphones.
Project operation parameters: Monitored parameters (annually/once every two years)
In addition to the parameters to be recorded when a cookstove is installed or sold, a carbon project is required to monitor certain parameters throughout the project’s lifetime on an annual or biannual basis.
In order to estimate emissions reductions that will occur in future, monitored parameters need to be estimated before the start of the project. This is referred to as establishing parameters ‘ex-ante’. True parameters are then applied after the project has started during the first round of monitoring, known as ‘ex-post’ parameters. Accurately determining parameters before the project has started can be challenging, as illustrated by CO2Balance’s Efficient Cook Stove Programme in Kenya.
Fraction of new stoves operating
Only those stoves that are operating can be counted towards achieving emissions reductions, or earning carbon credits. Stoves which are broken or simply not used cannot be included. In order to determine the fraction of stoves that are operating, sampling can be employed to determine this figure after or during the first year of operation. Users can be asked whether they still use the stove or not. The number of negative responses is used to estimate the percentage of cookstoves that are likely not used over the entire population of distributed stoves
Stove efficiency and quantity of biomass used
Determining the efficiency of your cookstove, and the quantity of biomass used, is essential for calculating emissions reductions and the quantity of fuel saved by the project. It can also be an important factor in determining if your cookstove can be included in an existing carbon project or PoA. The efficiency of your cookstove can be determined in one of three ways, depending on the carbon methodology applied in the project and how emissions reductions are calculated, as follows:
Kitchen performance test (KPT): a field test used to evaluate stove performance in real-world settings. It is designed to assess actual impacts on household fuel consumption. The KPT includes quantitative surveys of fuel consumption and qualitative surveys of stove performance and acceptability. Since the KPT is not lab-based, it produces the most realistic assessment of efficiency with the local cooking practices out of the three options provided here. Since the KPT requires conducting studies in households it is, however, also the most time-consuming option. Guidance approved by the CDM on how to perform the Kitchen Performance Test is available here.
Water boiling test (WBT): a laboratory-based test that evaluates stove performance while completing a standard task, which is boiling and simmering water, in a controlled environment to investigate the heat transfer and combustion efficiency of the stove. Guidance on how to perform the Water Boiling Test is available here.
Controlled Cooking Test (CCT): a field test that measures stove performance in comparison to traditional cooking methods when a cook prepares a local meal. The CCT is designed to assess stove performance in a controlled setting using local fuels, pots, and practice. It reveals what is possible in households under ideal conditions but not necessarily what is actually achieved by households during daily use. Guidance approved by the CDM on how to perform the Controlled Cooking Test is available here.
For an example of how fuel usage is assessed see a case study of the National Biodigester Programme in Cambodia.
Continued use of old stoves
You may be required to ensure that the replaced, low efficiency, cookstoves used prior to the project are disposed of and not used within the project boundary. Alternatively, if disposal of old stoves does not occur you can choose to exclude fuel wood consumption used in the old stoves from the project.
The difficulty here is that when starting a project you will not know how often end-users will use their old stove, if at all, so an ex-ante assumption must be made in order to estimate emissions reductions from the project before it has started.
To do this, you will need to know the quantity of fuel used for cooking per year and the number of meals cooked per day or month in the project area. It is then possible to conservatively estimate whether users will cook one or more meal(s) per day, week or month using the old stoves and multiply this by the total annual quantity of fuelwood used, as follows:
Since this figure is estimated ex-ante, it will need to be monitored and established ex-post (i.e. after the project has been operational for one year). This can be done by asking end-users ‘How many meals per day are cooked meals?’ and ‘How many meals per day/week/month do you prepare using the old stoves?’
Leakage refers to the effect of the project’s activities that occur outside the boundary of the project itself. For example, distributing cookstoves on one village may lead to a reduction in fuel wood usage in that village, but an increase in fuel wood usage in a neighbouring village due to the increased availability of fuel wood that the project village is no longer using.
The easiest, and therefore most common, approach is to apply a default adjustment factor of 0.95 to account for leakage. This is, however, only applicable under the CDM’s AMS-III.G methodology and the Gold Standard’s ‘Simplified methodology for Efficient Cookstoves’. The leakage factor is applied to the baseline fuel usage and requires no further monitoring of leakage.
Some carbon standards, such as the Gold Standard, Social Carbon and Women’s Carbon Standard, require that certain sustainability criteria are monitored in order to certify that the project contributes positively, or avoids negatively affecting, social and environmental factors. These criteria vary greatly depending on the project in question and, in the case of the Gold Standard, are not pre-defined but selected by the project developer. Criteria could include monitoring the income earned by employees of the programme, the perceived impact the project has on the lives of end-users, keeping a record of any training conducted for employees and skills gained, among other things. In order to demonstrate progress towards sustainability criteria, the following records can be used:
- Training program records – for training and capacity building of the project implementer personnel, maintenance personnel and end-users
- Employment records – employment registers, employee profiles, pay rolls and pay-slips for the personnel employed for the project, salaries paid, as well as ensuring that there is no forced or compulsory labor employed or child labour employment.
- Test reports – for various emissions from the cookstoves, like particulate matter
2. Record keeping
Keeping verifiable records of project data is essential for successfully passing verification and having carbon credits issued for your project/programme. This is particularly relevant both for the management of a project database and for the storing of hard copies of all agreements with end-users and partners. An example of how this can be organized is provided for the Biogas Programme Nicaragua.
Managing a Project Database
During verification, the validator will assess the accuracy and reliability of the project database, which stores all the information required for the carbon components of the programme in a centralized location. A project database can be designed in Microsoft Excel or any other database programme that allows for the automated calculation of totalled figures. For example, the database must allow for determining the total size of a CPA/project/cookstove. Usually the carbon methodology applied to a project will require that total emissions reductions achieved under one CPA/project/cookstove remains below a certain size e.g. the small-scale CDM cookstove methodology AMS-II.G requires that the aggregate energy savings of a single project activity does not exceed the equivalent of 60 GWh per year or 180 GWh thermal per year in fuel input.
At a minimum, a good project database should allow entry of the following:
- Serial number
- User name (first and surname)
- Address (including country, region, city, street, house number and postcode)
- GPS coordinates (if measured)
- Contact details of buyer (phone and email)
- CPA number (only relevant for PoAs)
- Distributor/installation partner (to trace the individual who implemented the system and created the database entry)
- Product model/stove type
In order to minimize the occurrence of errors the following should be integrated into the project database:
- Maximise use of auto-calculated/auto-filled cells
- Maximise use of drop-down menus
- Restrict type of values that can be entered into certain cells
- Restrict ability to enter two of the same values (e.g. useful for serial numbers, where each number must be unique)
- Automatic flagging of the same entries (e.g. useful for reducing errors in the entry of contact phone numbers where each number should be unique but in some cases the same number may apply twice, such as when a single household has two cookstoves).
Data records for the parameters monitored and other project documents should be archived in hard copy and/or electronic format for the duration of the carbon project and an additional two years.
All standardized forms (e.g. for collecting user details at dissemination of the stove) and agreements (e.g. with partners) should be stored as hard copies, with electronic copies also scanned and organized per CPA if a PoA is developed. This allows referencing back to original documents if, for example, an error is found in the project database or a verifier wishes to see original documents.
3. Sampling approaches
Sampling is a useful approach where many dispersed technologies (cookstoves) are concerned. Since a cookstove project consists of a large number of individual systems aggregated under the project/programme, employing sampling during monitoring avoids the need to measure the performance of each and every installation. An efficient cookstove project, for example, may install tens of thousands of cookstoves. Rather than needing to visit each and every household at which a cookstove is installed, sampling allows only a representative portion of these to be monitored. This is much more cost effective and logistically manageable.
In order to design an appropriate sampling method for a project, the CDM have produced comprehensive guidance on the types of sampling available and when each approach can be used. The guidance introduces five sampling methods.
|Simple Random Sampling|
Involves taking a random sample from the whole population
|Simplest sampling method, easy to use.|
Suitable if the units being sampled are similar with respect to the parameter being studied.
|Requires knowing the entire population before a sample can be selected.
Sampling can become costly if the population to be sampled is spread over a wide geographical area.
|Stratified Random Sampling|
Involves randomly sampling a different number of units from each strata according to the weight of each strata in the population (e.g. proportional representation)
|Improves the precision of the estimate (compared to simple random sampling) if there are differences between the strata.||Complicated to calculate.
Determining what the stratification factors should be can be difficult (e.g. in ‘Buildings’, the strata could include offices, households and shops).
Involves taking a sample every nth unit
|A simple sampling method, easy to use.||Sampling can become costly if the population to be sampled is spread over a wide geographical area.|
Sampling every unit within a sample of clusters from the population
|The most economical sampling method if the population is spread over a large geographic area, since the sampling units can be grouped based on their location. |
Can save time where the entire population is not known (e.g. if only a list of villages is known, sampling can be done within villages without having to have a list of each household when planning the sampling effort).
|Standard errors can be high with cluster sampling, since each subgroup tends to be similar. Taking a larger sample size can help to overcome this.|
Randomly sampling a number of units within a number of randomly selected clusters
|Enables a sampling approach at two levels: both the clusters and units. |
Allows for a cost-efficient design to suit the needs of the CME.
|Analysis and the sample size calculation are more complex.|
Adapted from Table 1 presented in EB 69, Annex 5. ‘Guidelines for sampling and surveys for CDM project activities and Programme of Activities’ (Version 02)
The first is Simple Random Sampling, in which a random sample is taken from a relatively homogeneous population. This kind of sampling works when the population of units from which the sample will be taken are homogenous, of limited size or concentrated in a small geographical area, or when they are easily accessible. For example, if one type of clean cookstove is distributed to one target group, such as households which were all previously using a three-stone fire, located within the same geographical area simple random sampling might be most appropriate.
The second method is Stratified Random Sampling, which is applied when a population to be sampled consists of several sub-populations which vary, and are more similar within groups than across groups. It involves selecting strata or homogeneous subpopulations and sampling within these. In a cookstove the different types of groups might be, for example, different types of users such as households and institutions (e.g. hospitals, schools).
The third method is Systematic Sampling, which is most commonly applied to determine quality assurance within the output of a product. An example is a production line where you can test every tenth product. This could include assessing the nthunit to determine the quality of bricks in a manufacturing process or the efficiency of cookstoves from the factory. When designing a sampling plan under this approach, it is important to ensure that the population to be sampled is ordered randomly.
The fourth method is Cluster Sampling, which applies when there are natural groupings within the population. In contrast with Stratified Random Sampling, sampling here occurs at group level rather than on the individual units: the population is divided into subgroups, which are then randomly selected. All units within each sub-group are sampled. A clear example of a population in which Cluster Sampling works well is a population that is geographically dispersed.
And finally, Multi-stage Sampling can be applied. Multi-stage Sampling is a more complex form of Cluster Sampling, in which the population is sub-divided as in Cluster Sampling above, but not all the units within a sub-group need to be measured. Instead, samples of sub-group units are measured.