Understanding CDM Methodologies - SuSanA

Data Availability
Problems in Brazil
and China
Combined Margin Calculation under Data Constraints
The following two cases (see Boxes 16 and 17) describe challenges
encountered in the methodology application. Both cases are related to CM
calculation under data constraints. Some key points are summarized below.
However, it should be noted that these are the alternative approaches
deemed appropriate in the context of Brazil and China. They might not be
valid in other countries.
The project boundary could exclude power plants where necessary data for
emission factor calculation is not publicly available. However, it should be
justified that the project is unlikely to affect the excluded power plants. In
addition, it is also important that the selected grid boundary consists of a
majority share of the total installed capacity in the relevant geographical area.
Data Hierarchy In the absence of plant-specific data (e.g. fuel consumption, power
generation), the following approach could be considered as alternatives for
grid emission factor calculation:
• OM calculation: Calculate the average emission factor for the grid for each
fuel type (based on the average efficiency of the existing power plants);
and
• BM calculation: Apply conservative proxy for power plant efficiency
for each fuel type (e.g. the efficiency level of the best technology
commercially available in the relevant geographical area) to calculate fuel
consumption necessary for the BM calculation. The use of the average
efficiency of existing power plants is unlikely to be accepted because it
would not lead to conservative BM calculation.
In case plant-specific power generation data is not publicly available, more
aggregate data (e.g. capacity addition from one year to another) could
be used as an alternative for the selection of power plants for the BM
calculation.
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