FAIRMODE Update Fairmode Steering Group

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

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

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

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?

About the PILOT exercise A new working group in FAIRMODE

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

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.

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

Stockholm city/region Current Pilots Country Pilot city/region General Contact point Sweden Stockholm city/region Matthew.Ross-Jones@Naturvardsverket.se helene.alpfjord@smhi.se kristina.eneroth@slb.nu Italy Emilia Romagna region mstortini@arpae.it gabriele.zanini@enea.it mihaela.mircea@enea.it Milan city marco.bedogni@amat-mi.it Ireland Dublin city K.Delaney@epa.ie Slovenia Country/Ljubljana Rahela.Zabkar@gov.si Poland Malopolska Region Piotr.Lyczko@umwm.pl joanna.struzewska@pw.edu.pl pawel.durka@ios.gov.pl Croatia sandra.krmpotic@mzoe.hr vidic@cirus.dhz.hr Greece Athens vasiliki@noa.gr Finland Helsinki anu.kousa@hsy.fi Germany Hessen state Stephan.Nordmann@uba.de Florian.Pfaefflin@ivu-umwelt.de

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

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

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

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

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

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 https://eucompositemaps.marvin.vito.be/emissions/ Would you contribute?

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

Local emissions Emission modellers The emissions composite mapping platform: a meeting point National emissions Air quality modellers Local emissions Emission modellers http://fairmode.jrc.ec.europa.eu/ecmaps/

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?

Thank you