Case study 1

1. Case study 1 Review comments on Baseline Methodology Waste heat use project Prepared by Nguyen Van Hanh Vietnam

2. comments on the description of how the baseline scenario is selected STRENGTHS • Appropriate selection of approach for identifying the baseline scenario: • The Approach selection to meet the requirement of the paragraph 48 of the CDM modalities and procedures • High applicability of the selected approach • Clear identification of two cases of baseline scenario: • Case 1: Baseline – GHG intensity of existing power plant. • Case 2: Baseline – Combined margin grid intensity. • Taking into account national/sectoral policies and circumstances: No national/sectoral policies supporting the use of waste gasses for electricity generation in the present time

3. comments on the description of how the baseline scenario is selected (Continued) Weaknesses: • Inappropriate spatial scope of data used to determine the baseline for small – scale project: unnecessary data availability at national level

4. comments on DESCRIPTION of HOW the PROPOSED cdm project is not the baseline scenario Strengths: • Clear definition of the project boundary in terms of gases and sources Weaknesses • Unclear and inadequate barrier analysis: • On investment barrier: Absence of NPV, IRR and livelized electricity generation cost, excluding only electricity price of 1.94 Rupi/KWh • On impact of proposed CDM project on financial plans: Without financial quantifying the impact of this project • Absence of a small map for the location of proposed CDM project

5. comments on whether information of data sources, vintage, spatial scope has been described in the baseline methodology Strengths • High applicability of the baseline methodology and its generic formulae/algorithms. (They could be used for many other small-scale project categories) • High conservativeness of algorithms/formulae used for determining: • Minimum quantity of waste gas available for supply to power generator Min WGA = Minimum [GA,Y,W]. • Using the combined margin data to estimate the GHG emissions. • Clear information of data sources (national/sectoral), vintage (3 years/5 years) and spatial scope (regional/national).

6. comments on whether information of data sources, vintage, spatial scope has been described in the baseline methodology (Continued) Weaknesses: • Using average operation margin data for identification of baseline scenario instead of the related dispatching - originated data (according to recommended consolidation methodology) • Insufficient vintage of data on electricity generation (April 03 – March 04): one year only instead of 3 years according to CDM modalities and procedures • Absence of must-run and low-cost data sources.

7. comments on transparency and conservativenessof how the project emissions are estimated STRENGTHS • Transparent way was used for developing the baseline methodology • Using the combined margin EF-BLCM,y, the baseline emissions are highest and the marginal plant would give the greatest number of CERs. • Uncertainties presented are reasonable and appropriate in terms of unreliability and instability of BOF waste gas source WEAKNESS • Absence of leakage estimation method for the proposed CDM project.

8. comments on algorithms/formulae used in baseline methodology - Proposed minor changes • Baseline emission factor by average CM in any year “y” should be calculated as follows: EF-BL CM,y = (EF OM, Average, y + EF BM,y)/2 (See original formulas D.2.1.4. (3): EF-BL CM,y = (EF OM, Average, y + EF BM,y) (Possible misprint) - Using the EF-BLCM,y, the baseline emissions are highest and the marginal plant would give the greatest number of CERs. - Absence of energy efficiency values of thermal power plants, consequently, the assumption that the thermal power plants use the same primary energy type (coal or natural gas or oil) having the same IPCC emission factors (tCO2eq/KWh) is unreasonable