The challenge of estimating parameters to calculate expected carbon credits

The Efficient Cook Stove Programme in Kenya is a CDM PoA that involves the distribution of domestic fuel-efficient cooking stoves by co2balance, a UK based carbon project developer, to rural households in Kenya. Stoves are distributed free-of-charge to users in exchange for the rights to the generated emissions reductions. Revenues from the sale of emission reductions are used to fund installation of the cookstoves, cover (part) of the cost of the stove and provide on-going maintenance services.

Monitoring for the first two CPAs commenced after one year of operation. During this process, parameters estimated ex-ante (i.e. before the programme was implemented) were tested against actual project conditions.  Under the CDM, the emission reduction potential of a programme is estimated before project implementation to determine the quantity of carbon credits expected from the activity. The results of the monitoring effort indicated that the emission reduction potential had been overestimated in the first place, with only 30% of the volume of CERs expected at the start of the programme being put forward for issuance. Whilst this was partly due to less cookstoves being distributed than foreseen under the two CPAs, other factors also played an important role, including:

  • The continued use of baseline stoves was not envisaged in the PDD. Monitoring results revealed that the baseline stove continued to be used for almost a third of the cases.
  • The original PDD assumed that all stove owners would use the stove. In reality 4% of surveyed owners did not use the new stove.
  • The project stove efficiency was expected to be the same as the initial laboratory test but the actual figure was up to 10% lower, partly due to owners tampering with the design of the stove.
  • The CDM default figure for Kenya’s fNRB value was applied to the CPAs, which is more conservative than the calculated value in the PDD.

The above factors illustrate the difficulty of accurately estimating parameters during the PDD writing process to obtain a precise estimate of the revenues that can be expected from carbon credits in the future.