Development of GHG projections guidelines

1. Development of GHG projections guidelines Melanie Sporer, EEA

2. Background DG CLIMA commissioned contract conducted by TNO, AMEK UK limited, Aether Limited, OekoInstitute.V., Umweltbundesamt GmbH, final report December 2012 Part A: General Guidance (140p)Part B: Sectoral Guidance (272p) http://ec.europa.eu/clima/policies/g-gas/monitoring/studies_en.htm The guidelines do not prescribe a specific projection method to each MS, but guide the MS in a graded methodological approach to reflect different approaches and data situations at MS level and to provide all information on projections’ assumptions, parameters, algorithms and results that allow the Commission to derive EU-wide projections that can be seen as a consolidation of the individual MS national projections.

3. The general guidance on the step-by-step development process of an emission projection is addressed to the national projection compiler Compilation includes the collection of projected activity data (in most cases outputs from projection models), estimation of emissions and removals, checking and verification, uncertainty assessment, sensitivity analysis and reporting. Projection compiler is the person, persons or institutions who put together or develop the projection from materials gathered from several sources.

4. The following aspects of GHG projections are addressed in the guidelines • Data collection -> extremely important that latest historic inventory and associated activity data and assumptions contained therein are used as a base • Key category analysis -> guiding users in their methodological choice for each category • Time series consistency -> ensuring the time series consistency of projections in relation to historic inventory estimates is essential to establishing confidence • Quality Assurance (QA) and Quality Control (QC) -> sector specific quality control checks • Reporting-> providing harmonised reporting tables for the projected GHG emissions

5. General approach

6. How to decide on the ‘Grade’ for AD

7. How to decide on the ‘Grade’ for EF

8. QA/QC similar as applied in emission inventories • Completeness: missing sources/fuels; • Comparability: misallocation of estimates to sub-sectors; • Consistency: inconsistency in the time series (including historic to projected) or between approaches for different pollutants/categories; • Accuracy: errors in application of assumptions or biased assumptions.

9. Comprehensive QA/QC checklist

10. Uncertainty • should not be interpreted in terms of the uncertainty whether or not the projected future will indeed come true; the likelihood of the exogenous assumptions in terms of projected economic growth, technological developments or policy decisions are in this sense not part of the model's uncertainty but discriminate between different scenarios • shouldbe interpreted as the uncertainties in the model originating from uncertainties in the endogenous parameters and algorithms in the model; these include specific energy requirements, emission factors and similar related to specific source categories and technologies

11. Thank you!

12. Definition - Accuracy • Inventory definition: Accuracy is a relative measure of the exactness of an emission or removal estimate. Estimates should be accurate in the sense that they are systematically neither over nor under true emissions or removals, as far as can be judged, and that uncertainties are reduced as far as practicable. Appropriate methodologies conforming to guidance on good practices should be used to promote accuracy in inventories. (FCCC/SBSTA/1999/6 Add. 1) • Statistical definition: Accuracy is a general term which describes the degree to which an estimate of a quantity is unaffected by bias due to systematic error. It should be distinguished from precision. (GPG 2000)

13. Precision-Accuracy-Uncertainty