1 1 INDUSTRIAL PROCESS SECTOR Hands on Training Workshop of the CGE on NGGI for NAI Parties to the UNFCCC, Africa Region Pretoria, South Africa 18-22 September.

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Presentation transcript:

1 1 INDUSTRIAL PROCESS SECTOR Hands on Training Workshop of the CGE on NGGI for NAI Parties to the UNFCCC, Africa Region Pretoria, South Africa September 2006 GHANA CASE STUDY

2 2 OUTLINE- GHANA CASE STUDY RE96GL APPROACH AND STEPS Country sources and subsource categories identified Summary of Process Descriptions of source categories and estimated missions Methodological Choices Collection of AD IPCC Default and CS-EF GPG 2000 approaches for selected source categories

3 3 OUTLINE- GHANA CASE STUDY SECTION B Potential problems with the use of Re96GL, effects, and suggested approaches regarding: AD and CBI Data Sources Lack of AD and EFs Institutional Arrangements

4 4 OUTLINE- GHANA CASE STUDY SECTION C ESTIMATION AND REPORTING -Using country source worksheets and other countries reported data to complete the electronic software

5 5 Re96GL Approach and Steps Country Sources identified 2A-Mineral Production  2A2-Lime production, Pg  2A3-Soda ash production and Use Pg B Chemical Industry  2B1-Calcium Carbide use Pg C Meta Production  2C1-Iron and Steel Pg  2C2- Aluminum Pg

6 6 Re96GL Approach and Steps Choice of Activity Data Plant level measurements or direct emissions reports with documented methodologies Where direct measurements are not available, estimations are based on calculation with plant-specific data

7 7 Re96GL Approach and Steps Choice of Default Emission Factors Process reaction-based EFs (Stoichiometric Ratios) Production-based emission factors Technology-specific emission Factors Reported Country/Region-specific plant-level measurements

8 8 Re96GL Approach and Steps Sample Tiers by Sub-source Categories 2C5-Calcium Carbide Use in Steel Melting plants CO2) T1a -Consumption of Carbide in acetylene production (tonne carbide) and EF (tone CO2/tonne carbide (Default)

9 9 Re96GL Approach and Steps Tiers by Sub-source Categories 2C-Metal production (Iron and Steel) Tier 1a-consumption of reducing agent (tonne) and EF (tonne C/tonne reducing agent) Tier 1b-production of the metal (tonnes) and EF (tonne CO2/tonne metal)

10 Key source analysis and prioritization Demonstrate Key source Analysis by Level using the Ghana Inventory Results

11 Country-Specific Methodology and good practice plant-level EF and AD The case of Aluminum production inventory in Ghana

12 Good practice Activity Data (Plant-level EF based on Tier 1a Method)

13 Consumption of reducing agent (anode carbon)

14 Net carbon consumption

15 Comparability of good practice plant level and IPCC Default Process Parameter Country Specific (Plant level Tier 2) 7-year average IPCC Default including baking emissions (5%) Net Carbon consumption assuming 98% purity of anode carbon tonne C/tonne Emission factor (tonne CO2/tonne Al.) % Difference +3.5%

16 Emissions Estimation and Reporting Use of IPCC Electronic Inventory Software Hand-on using the various country data for different source categories

17 REPORTING TABLES Long Summary and Short summary (Reference : IPCC Inventory Software)

18 Emissions Estimation and Reporting- Selected country reviews Discussion of the identified problems with reporting and methodological choices of selected countries identified in the IP sector of the INC

19 Lack of Activity Data and Emissions Factors encountered in the use of Re96GL GPG 2000 Tier1 good practice Options Notes: Annex 2 - Table 2 gives the methodological choices and GHG estimation for Tier 1 methods based on national circumstances where EFs and certain types of ADs are not available.)

20 GPG 2000 DECISION TREE APPROACH TO ESTIMATIONS SAMPLE ILLUSTRATIONS 2.A.1Cement Production 2.C1 Iron and Steel 2.C.2 Aluminum production Handbook Annex 3 Table 3 presents detailed estimations of Emission factors of the source categories above based on the various GPG 2000 Tier level methods

21 UNCERTAINTY ESTIMATION GPG 2000 OPTIONS Table 3.2 of GPG2000 illustrates the use of default factors in estimating uncertainties based on the various Tier level methods