1. 26.10. 2006 | Folie 1 Classification and Assessment of Representativeness of Air Quality Monitoring Stations La Rochelle, 26.10.2006 Wolfgang Spangl

2. 26.10. 2006 | Folie 2 Service contract to the Commission for the Development of the methodologies to determine representativeness and classification of air quality monitoring stations Contractor to DG ENV: Umweltbundesamt Austria Subcontracts with TNO (Dick van den Hout) Central Institute for Meteorology and Geodynamics, Vienna

3. 26.10. 2006 | Folie 3 Contents Purpose of Classification Purpose of Assessment of Representativeness Classification methods Test of Classification Definition of Representativeness Method for Determination of Representativeness Validation of the method for the Determination of Representativeness

4. 26.10. 2006 | Folie 4 Purpose of Classification Classification of Air Quality Monitoring Stations (AQMS) is a key instrument for the interpretation and assessment of AQ data – especially for large data-sets covering large areas with a wide variety of types of locations – providing the following information: Basic information about (different) causes/sources of air pollution (primarily emissions); Basic information about the affected receptors such as humans (related to exposure); Support of spatial AQ assessment, including the determination of the area of representativeness.

5. 26.10. 2006 | Folie 5 Assessment of Representativeness AQ monitoring data are available at certain locations, but it is of major interest to know the spatial distribution of air quality. Assessment of representativeness means the “extension” of point (measurement) information to “spatial information”. For this task it is necessary to delimitate areas of the concentration field with “similar characteristics” as specific monitoring stations.

6. 26.10. 2006 | Folie 6 Purpose of Assessment of Representativeness Compliance assessment based on data from monitoring stations Delimitation of areas where limit or target values (incl. margin of tolerance) are exceeded or not Exposure assessment (human health, ecosystems, specific plant species …) Delimitation of areas with homogeneous concentrations with respect to the exposure relevant limit/target values – in areas where the respective receptor is located Information of the publicDelimitation of areas with homogeneous concentrations with respect to the relevant limit/threshold/alert values, including maps

7. 26.10. 2006 | Folie 7 Purpose of Assessment of Representativeness Analysis of causes of air pollution: Emissions, dispersion conditions, atmospheric chemistry, deposition, … Delimitation of areas where AQ is influenced/triggered by similar parameters – emission sources (i.e. with similar temporal variations and triggered by common legal regulations) and other similar influencing factors – important for the development of abatement measures Model validation and input Selection of monitoring stations representative for geographical areas related to the spatial model resolution Monitoring network design Identification of geographical areas which are not sufficiently covered by monitoring stations or which are covered by several redundant monitoring stations. Monitoring network design, of course, serves the other purposes listed above.

8. 26.10. 2006 | Folie 8 Classification methods Classification methods for the following parameters are developed: Emissions – specific for different pollutants Population

9. 26.10. 2006 | Folie 9 Classification according to Emissions The classification criterion is the absolute contribution of emissions from the sectors Road traffic Domestic heating Industry/commercial emissions The classification of AQ MS is pollutant-specific in any case for industrial emissions, it is recommended to classify also domestic heating and traffic emissions pollutant-specifically.

10. 26.10. 2006 | Folie 10 Classification of Road traffic emissions The classification parameter is the Emission (g/km.year) divided by the root of the distance road - monitoring station. This parameters is to be summed up for all streets of relevance. The root of the distance is an approximation of the concentration distribution assessed by simple modelling (MISKAM, ADMS). To deal with buildings between monitoring site and road, the respective emissions are weighted with 0 for close buildings, and 0.5 for almost close buildings or locations in narrow cross lanes.

11. 26.10. 2006 | Folie 11 Classification of Road traffic emissions Levels of sophistication for assessment of road traffic emissions LevelApproximation of emissions 0Total vehicle number, uniform emission factor, estimate of share of HDV 1Vehicle number for passenger cars and HDVs, emission factors for each 2Vehicle number for passenger cars and HDVs, specific emission factors for different traffic situations (highway, stop&go, ….) 3Complete emission inventory

12. 26.10. 2006 | Folie 12 Classification of Road traffic emissions This classification parameter (level 1) covers – for Austrian AQ MS – a range between 0 and 60 000(g/km.year).m -1/2. Example for 181 Austrian AQ MS: Three classes are separated by boundaries at 4000(g/km.year).m -1/2 and 10 000(g/km.year).m -1/2, which comprise 135, 60 and 35 stations, resp.  Class boundaries are in any case deliberate

13. 26.10. 2006 | Folie 13 Classification of Austrian AQ MSs according to Road traffic emissions

14. 26.10. 2006 | Folie 14 Relation between NO and NOx concentrations and “Traffic parameter” Deviations from a linear relation are partly caused by different local or regional) dispersion conditions.

15. 26.10. 2006 | Folie 15 Classification of Domestic heating emissions The classification of domestic heating emissions is based upon the emissions in a surrounding of 1 km radius and 5 km radius around the monitoring site. The emissions within 5 km circle are weighted by 0.1% (derived from dispersion profiles for Switzerland, SAEFL, 2003) Swiss Agency for the Environment, Forests and Landscape (2003): Modelling of PM10 and PM2.5 ambient concentrations in Switzerland 2000 and 2010.

16. 26.10. 2006 | Folie 16 Classification of Domestic heating emissions Levels of sophistication for assessment of road traffic emissions LevelApproximation of emissions 0Population at administrative units 1Population within 1 km and 5 km derived from GIS data 2Population within 1 km and 5 km derived from GIS data, emission factors for specific heating structure and fuel use 3Complete emission inventory

17. 26.10. 2006 | Folie 17 Classification of Domestic heating emissions This classification parameter (level 1) covers – for Austrian AQ MS – a range between 0 and 143 000 inh. Example for 181 Austrian AQ MS: Three classes are separated by boundaries at 5000 inh. and 20 000 inh., which comprise 108, 41 and 32 stations, resp. Class “high” comprises most stations in towns with >100 000 inh., class “medium” suburban sites (related to those large towns) and medium towns.

18. 26.10. 2006 | Folie 18 Classification of Industrial emissions The classification of industrial emissions (including commercial areas and power plants) can be either based upon modelling or on expert judgement. No classification method based upon surrogate information can be given.

19. 26.10. 2006 | Folie 19 Classification of Population The classification scheme according to the population distribution gives information about population and ecosystems in the vicinity of the AQ MS which can be used for exposure assessment. It is orientated by “common” classification schemes used e.g. in AirBase. It can be used as a surrogate for the classification of domestic heating emissions.

20. 26.10. 2006 | Folie 20 Classification of Population Classification scheme according to the population distribution: Agglomeration (>250 000 inh.)Central urban Suburban Large town (50 000 – 250 000 inh.) Central urban Suburban Small town (10 000 – 50 000 inh.) RuralNear city regional remote

21. 26.10. 2006 | Folie 21 Test of Classification The proposed Classification method will be tested by application on selected AQ MSs in Austria, the Netherlands and Mediterranean France (to cover different climatic and topographic situations). The availability of required emission data or surrogate data will be investigated.

22. 26.10. 2006 | Folie 22 Definition of Representativeness The area of representativeness is defined by the criteria: 1. The pollution level – described by statistic parameters related to EC AQ regulation – is within a certain range 2. The pollution level is determined by similar reasons.

23. 26.10. 2006 | Folie 23 Definition of Representativeness Statistic parameters related to EC AQ regulations to determine representativeness: PM10: Annual mean, 93.2-percentile of daily mean values (equivalent to 35 days per year above 50µg/m³) NO 2 : Annual mean (The exceedances of 200µg/m³ as 1-hour mean are too “rare” and statistically not significant) Ozone: 90.4-percentile of daily maximum 8- hour mean values

24. 26.10. 2006 | Folie 24 Definition of Representativeness The concentration in the area of representativeness of a certain AQ MS shall be within a range of +10% of the total concentration range observed in Europe. PM10: Annual mean: 4µg/m³, 93.2-percentile of daily mean values: 7µg/m³ NO 2 : Annual mean: 4µg/m³, which shall also be applied to NOx Ozone: 90.4-percentile of daily maximum 8- hour mean values: 4µg/m³ (Preliminary numbers derived from Austrian data)

25. 26.10. 2006 | Folie 25 Example: Ozone 90.4 percentile - concentration range in Austria

26. 26.10. 2006 | Folie 26 Definition of Representativeness Further criteria for Representativeness: The area of representativeness is constant over time (for several years) A certain number of years (proposal: 3 years) must fulfil the concentration range criterion - in order to take into account inter-annual variations of the pollution level by meteorological influences. The area of representativeness may change over time (after several years) due to changes in emissions.

27. 26.10. 2006 | Folie 27 Definition of Representativeness Reasons for similar concentrations: Emissions – similar to the classification of AQ MS Regional background level – derived from measurement or modelling Dispersion conditions – depending on topographic and climatic conditions

28. 26.10. 2006 | Folie 28 Methods to determine the area of Representativeness The spatial concentration pattern necessary to determine the area of representativeness can be derived by: Additional (temporal) measurement Modelling Surrogate information & Expert assessment (based on emissions, background concentration and dispersion conditions)

29. 26.10. 2006 | Folie 29 Methods to determine the area of Representativeness Criteria for the determination of representativeness based upon surrogate information: Emissions: same class related to road traffic, domestic heating and industrial emissions Regional background: Concentration range related to definition of Representativeness

30. 26.10. 2006 | Folie 30 Methods to determine the area of Representativeness Dispersion Conditions: Local (<1km): flat; slope; exposed (summit, ridge ….) Regional (some 10km): Flat terrain; hilly terrain; valley (parallel or cross to mountain ridge); basin Large-scale (some 100km): “Dispersion climate” to differentiate e.g. Alps, Po-Valley, Pre-Alpine Lowlands, Pannonian Plane, Massif Central, Central Iberian Meseta, ….

31. 26.10. 2006 | Folie 31 Methods to determine the area of Representativeness To develop operational methods for the determination of the area of representativeness, appropriate data sources (GIS data-bases) are investigated.

32. 26.10. 2006 | Folie 32 Validation of the Methods to determine the area of Representativeness The validation of the methods for the determination of representativeness will cover a thorough test with selected AQ MSs from Austria, the Netherlands and Mediterranean France (to cover different climate and topographic conditions). The validation will include a sensitivity analysis of “definition parameters”, i.e. the concentration range for each pollutant and statistical parameter, and the criteria for emissions and dispersion conditions.