1. FAIRMODE
Update
Fairmode Steering Group

2. Technical meeting (Athens, June 2017)
About 70 participants and 80 contributions!
Composite mapping exercise
Model quality objectives
Source apportionment exercise
Emission benchmarking
SHERPA applications
Spatial representativeness …
On-going
Composite mapping for emissions
Towards spatial source apportionment
Distinguishing between source app. and planning methodologies
Towards
Pilot exercise
On the use of sensors to support air quality modeling applications
New

3. A full day workshop on spatial representativeness
A FAIRMODE – AQUILA exercise

4. Spatial representativeness: Intercomparison exercise
The Antwerp dataset
At start:
No common definition of spatial representativeness
A large variety of methods to estimate it

5. Conclusions and way forward
Spatial representativeness: Intercomparison exercise
Conclusions and way forward
This study was the first attempt to investigate systematically the differences in spatial representativeness (SR) estimates.
The considerable spread of the results concerns the extent and position of the SR area perimeters, but also the technical procedures and the extent of input data effectively used.
The diversity of results requires the experts community to take further efforts towards a harmonized definition of the concept of “the area of representativeness”
Would it be advisable to have at disposal a set of transparent definitions and practical guidelines, while maintaining the freedom of choosing the most appropriate procedure for a given purpose or application?

6. About the PILOT exercise
A new working group in FAIRMODE

7. WG1 WG2 WG3 WG4 Assessment Emissions Source App. planning
WG5: Pilot on Air Quality management Practices
WG1
Assessment
WG2
Emissions
WG3
Source App.
WG4
planning
WG5: Improved air quality management practices
Chair: E. Pisoni (JRC)
Co-chair: C. Guerreiro (NILU)
Support: All other WG chairs and co-chairs

8. WG5: Pilot on Air Quality management Practices
Context
Guidance, methodologies and supporting tools have been developed in the past years and are available to MS, AQ managers and more generally to the AQ modeling community.
Objectives of the “pilot”
Tune FAIRMODE Methodologies/Guidance/Tools to better fit air quality management needs.
Means
Increase the efficiency of the FAIRMODE QA/QC process by focusing on specific areas where all data are consistently linked.
Strengthen bilateral interactions between FAIRMODE and the pilots to support data preparation, application of tools and interpretation of results.

9. PILOT Increase the efficiency of the FAIRMODE QA/QC
Guidance, methodologies and supporting tools have been developed and are available in the different WGs
Each of these tools/methodologies is supported by a group of users/participants
PILOT
Limited intersection do exist, preventing a consistent process
Pilot interacts with most WG topics in a consistent way

10. Stockholm city/region
Current Pilots
Country
Pilot city/region
General Contact point
Sweden
Stockholm city/region
Italy
Emilia Romagna region
Milan city
Ireland
Dublin city
Slovenia
Country/Ljubljana
Poland
Malopolska Region
Croatia
Greece
Athens
Finland
Helsinki
Germany
Hessen state

11. Pilot: 1st objective
Improving our (modelled) understanding and representation of the current situation (base case)?
Comparison with other data
Quality assessments
Bring in local knowledge
Air quality
BaseCase
Emissions
mapping
Benchmark
Concentration
Model Quality
Objectives
WG1
WG2
WG1
WG2

12. Model Dynamic indicators
2nd objective: improved planning tools based on local knowledge
Improve planning practices (scenarios)?
Comparison with top-down EU data
Bring in local knowledge
Local Knowlegde
Emissions
BU vs. TD
Source apportionment
Model Dynamic indicators
WG2
SHERPA
Top-Down
SHERPA
Bottom-up
WG3
WG4
WG4
WG4

13. Fairmode wheel, process and timing
Phase I Emissions (to be finalized by plenary 2018)
Phase II Assessment (WG1)
Phase III Source apportionment (WG3)
Phase IV Planning (WG4)
2 to 3 years

14. Phase I: Emissions
Overall objective: Assess and (possibly) improve the quality of pilot emission inventories with FAIRMODEs WG2 tools
Pilots are asked to:
respond to an on-line survey.
The survey is a documentation effort to reflect on emission processes (traffic and domestic combustion are first focus)
2) screen emission totals using the Δ-emission tool.
The goal is to identify possible inconsistencies with other inventories
3) Evaluate the spatial distribution of the inventory with the emission composite mapping tool .
The goal is to identify differences in terms of spatial allocation
With full support of FAIRMODE

15. The composite mapping platform adapted for emissions
A follow-up activity with WG1 (Assessment)

16. https://eucompositemaps.marvin.vito.be/emissions/
A few words about the emissions composite mapping platform
Is it a good idea?
Is it helpful?
First results
Would you contribute?

17. A few words about the emissions composite mapping platform
Objectives
How do we move from benchmarking to permanent improvements?
Which use for the new EMEP 0.1x0.1 reported country gridded emissions?
How do we secure further involvement of local emission expertise in FAIRMODE?
Composite mapping for emissions
launched at the technical meeting in Zagreb
WG1 Experience  AQ composite mapping exercise
FAIRMODE national and local estimates vs. data from EMEP CEIP

18. Local emissions Emission modellers
The emissions composite mapping platform: a meeting point
National emissions
Air quality modellers
Local emissions
Emission modellers

19. FAIRMODE recommendations (by WG)
Towards FAIRMODE recommendations
Summarize findings
FAIRMODE recommendations (by WG)
Benchmarking
Regional & local exp.
Inter-comparisons
Guidance
Recommendations
Training
Tools & methods
Datasets…
What is the purpose?
Is my approach fit for the purpose?
Do I apply it in the appropriate way?
Are my results of sufficient quality for policy?

20. Thank you