1 / 20

Managing Uncertainty in Road Transport Emissions Inventory

This assessment explores uncertainty in COPERT4 model development and implications on emission factors. The study compares COPERTII and COPERT4, highlighting challenges in meeting emission targets due to real-world behavioral differences. It analyzes NOx emissions of Euro V trucks and the impact of uncertainties on projection accuracy. The document discusses strategies for quantifying uncertainties using new knowledge and updated datasets, emphasizing the importance of accurate activity data. The study suggests improvements in regulations and activity data allocation to bridge the gap between projected and actual emissions.

dmorin
Download Presentation

Managing Uncertainty in Road Transport Emissions Inventory

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. An assessment of uncertainty in COPERT4 & managing differences arising from model development:from COPERTII to COPERT4 Leonidas Ntziachristos ETC/ACM Updated version of: Road transport emission inventory uncertainties – GHGs and APs,EEA, Copenhagen, 18 November 2010 http://www.eionet.europa.eu/events/transport%20uncertainties/

  2. Agenda of the Nov. 18, 2010 meeting TFEIP Stockholm

  3. Projected emission factors • Emission reductions for future vehicle technologies generally follow the rule: • Limitation: • Real-world behaviour does not (always) follow emission standards TFEIP Stockholm

  4. Example: Euro V trucks NOx • Emission Level • EF over ES ratios TFEIP Stockholm

  5. Impacts • Uncertainty of projection increases due to inability to predict real-world behaviour beforehand • Difficulties to meet targets may originate from such uncertainty in setting targets • Best example: NECD TFEIP Stockholm

  6. Towards NECD: Current Assessment Source: Nitrogen oxide (NOx) distance-to-target for EEA member countries, EEA, Oct. 2010. TFEIP Stockholm

  7. Responsible: Model or Regulation? • Model projects what regulations wished to achieve • Reality proves that regulations failed to achieve • Manufacturers followed “letter” not “spirit” of law! • Improvements required to regulations • Different driving profile? • Non-to-exceed approach? TFEIP Stockholm

  8. Quantifying uncertainties • Use new knowledge • Models • Activity data • Compare with • Old models • Old activity data • Objective: Explain uncertainty due to model and activity data differences TFEIP Stockholm

  9. Approach to quantify uncertainty: input data • RAINS activity and emission factor data used to set the NECD targets • Cost-effective Control of Acidification and Ground-Level Ozone. Part A: Methodology and Databases. Sixth Interim Report to the European Commission, IIASA 1998. • Actual excel files received by J. Cofala, Oct. 2010. • FLEETS/EC4MACS data • Updated datasets used by GAINS in the framework of LIFE EC4MACS • Based on original data by individual MSs • Four countries used as examples:DE, FR, IE, NL TFEIP Stockholm

  10. Approach to quantify uncertainty: models • COPERT II (1997) • Used to provide removal efficiencies to RAINS • COPERT 4 v8.0 (Nov. 2010) • Most updated version, implementing HBEFA 3.1 HDV EFs TFEIP Stockholm

  11. Runs executed (Germany) • Run 1: Original RAINS calculation • Run 2: COPERT 2 + RAINS Input • Run 3: COPERT 2 + EC4MACS Input • Run 4: COPERT 4 + RAINS Input • Run 5: COPERT 4 + EC4MACS Input TFEIP Stockholm

  12. DE: Activity TFEIP Stockholm

  13. DE: Technology penetration TFEIP Stockholm

  14. 34% activity 75% EF DE: NOx Emissions TFEIP Stockholm

  15. DE 2010: Technology responsibility TFEIP Stockholm

  16. IE: Activity TFEIP Stockholm

  17. 131% activity 64% EF IE: NOx Emissions TFEIP Stockholm

  18. IE 2010: Technology responsibility TFEIP Stockholm

  19. Summary • Differences between target and reality result from both emission factors and activity data • 65-75% higher emissions due to EFs • 19-131% higher emissions due to activity data • Emission factors • Practically all Euro 3 / III and later diesel EFs • Conventional/E1 GPC! • Activity data: • Misallocation of HD, LD diesel consumption • Relative increase of DPC consumption • Too fast scrappage of old vehicles assumed TFEIP Stockholm

  20. More Info http://acm.eionet.europa.eu/reports/ETCACC_TP_2010_20_Copert2vsCopert4 TFEIP Stockholm

More Related