Bruce Rolstad Denby FAIRMODE 4th Plenary, Norrkjoping Sweden June 2011 The combined use of models and monitoring for applications related to the European air quality Directive: SG1-WG2 FAIRMODE SUMMARY FAIRMODE Forum for air quality modelling in Europe Bruce Rolstad Denby FAIRMODE 4th Plenary, Norrkjoping Sweden June 2011

Content Aim of SG1-WG2 Response to ‘request for information’ Discussion topics inWG2-SG1 Results of discussions Work plan

Aims of SG1 To promote ‘good practice’ when combining models and monitoring (Directive related) To provide a forum for modellers and users interested in applying these methodologies To develop and apply quality assurance practices when combining models and monitoring To provide guidance on station representativeness and station selection

Two major types of ‘combination’ Data fusion The combination of separate data sources to form a new and optimal dataset (e.g. models/ monitoring/ satellite/ land use/ etc.). Statistically optimal but does not necessarily preserve the physical characteristics Fast post processing of model data Data assimilation The active, during model integration, assimilation of observational data (e.g. monitoring/satellite). Physical laws are obeyed Calculation intensive

Request for information SG1 21 responses to the survey Summary tabulation of the information Summary information in figures Will help to plan bench marking activities Will help to understand the state-of-the-science

Discussions in SG1-WG2 Results of the ‘request for information’ concerning data assimilation activities in Europe Methods for quality assurance when combining monitoring and modelling. How to benchmark these? Contribution of SG1 to the revision of the Directive. Defining representativeness of monitoring stations for modelling and data assimilation, implementation in the benchmarking activities

1. ‘Request for information’ The survey was successful and provided a useful overview of methods There are a range of QA indicators used Methods for independent verification include: Leave one out cross validation (usually fusion only) Split assimilation and validation datasets (assimilation) The station classification was the most often used method to determine representativeness but this was quantified in different ways

2. Methods for quality assurance and SG4 Methods that use ‘leave one out’ cross validation can provide results in the same way as models The same indicators can, and should be, used as for models We do not want to look at forecasting (at this stage) We wish to focus on the urban scale But limitted number of stations may be prohibitive We do not think assimilation methods are appropriate (at this stage) for local scale modelling We would like to see the model and assimilation uncertainty also reported and utilised in the delta tool Fusion methods may be applied to other existing model results in the delta tool: allowing assessment of different methods and application to different models The use of model calibration for planning applications was discussed but not completely resolved

3. Contribution of SG1 to the review of the Directive. Prefer to see optimal use of models and monitoring rather than ‘supplemented with’. Incompatibility between the following aspects: You may reduce the number of monitoring stations if you use models You can use modelling below the upper threshold assessment Clarification on what combination/ supplementary is in the Directive. Clarification of model resolution in the Directive Still to be discussed

4. Representativeness Representativeness information provides: Information of the radius of influence of monitoring data for data assimilation Modellers with information concerning the required model resolution for verification studies Modellers with information concerning the usable monitoring data (related to the Directive) No one method is available for assessing this. Future task of SG1 is to provide recommendations on this For the time being a consensual table is required that quantifies this information through Expert elicitation Existing methods for quantification

Example table for NO2 Temporal resolution One hour One day One year Rural background 5 km 20 km 50 km Suburban background 2 km 10 km Urban background 1 km 3 km Traffic 10 m 100 m 250 m Industrial 500 m

Work plan Consolidate and deliver a short report on the ’request for information’ Compile a short report on methods for quality assurance of combination methods Expert elicitation on representativeness to provide a consensual basis Compile a list of methods and recommendations for assessing representativeness for different applications

For information and contributions contact Bruce Rolstad Denby bde@nilu.no and register interest on the website http://fairmode.ew.eea.europa.eu/