1. Possible use of Copernicus MACC-II modeling products in EEAs assessment work Leonor Tarrasón, Jan Horálek, Laure Malherbe, Philipp Schneider, Anthony Ung, Bruce Denby, Linton Corbet and Peter de Smet 18tn EIONET workshop on Air Quality Assessment and Management Dublin, Ireland, 24 th and 25 th October 2013

2. Outline 1.Mapping assessments at EEA 2.Use of MACC-II ensemble products 3.Results for PM10 and O3 4.The role of spatial resolution 5.Conclusions and recommendations

3. Outline 1.Mapping assessments at EEA 2.Use of MACC-II ensemble products 3.Results for PM10 and O3 4.The role of spatial resolution 5.Conclusions and recommendations

4. Approaches to AQ assessments Three different approaches to air quality status assessments: 1.Mapping based on air quality observations 2.Mapping based on air quality modelling 3.Mapping based on a combination of models and measurements Increasing accuracy in the description of the extent of exceedances in a certain area

5. Why mapping? Support to national assessments PM 2.5 source contribution in Oslo

6. Mapping for regulatory purposes Different mapping approaches in different countries The recent ETC/ACM report contains an overview of situation on the use of models for regulatory purposes in 2010 and European composite maps http://acm.eionet.europa.eu/reports/docs/ET CACM_TP_2013_3_CompAQModMaps_v2. pdf

7. Current Mapping at ETC/ACM Unified methodology to estimate background concentrations in Europe in 10x10 km 2 Useful for population exposure analysis Includes an analysis of uncertainties and probability of exceedance of limit values

8. EEAs current mapping methodology Airbase background rural and urban stations EMEP model calculation in 50x50km 2 Meteorological and site parameters Residual kriging for rural and urban maps Merging Rural and Urban kriging results PM10, O3 annual averages PM10 36st highest daily average O3 26 th highest daily max 8-h avg SOMO35, AOT40 Combined rural and urban concentration map.

9. PM10 – 36th maximum daily average values, year 2009 Resolution: 10x10 km. Probability of exceedance of limit value based on standard interpolation error.

10. Outline 1.Mapping assessments at EEA 2.Use of MACC-II ensemble products 3.Results for PM10 and O3 4.The role of spatial resolution 5.Conclusions and recommendations

11. Possible improvements of background mapping: example for NO 2 1. Airbase station data 2. Ordinary kriging of Airbase station data 3. Residual kriging of Airbase station data using OMI satellite obs. OMI NO2 satellite data from NASA Godard GESC DISC 2012 ETC/ACM Task 1.0.2.8

12. Possible improvements through use of Copernicus MACC-II products MACC –II ensemble Operational products with 25x25 km 2 and 10x10 km 2 http://macc-raq.gmes-atmosphere.eu/som_ensemble.php

13. MACC-II ensemble performance

14. Background model requirements Model requirements EMEPMACC-II ensemble SustainabilityLong term UNECELong Term Copernicus DocumentationScientific reviews AvailabilityEvery year Y-2 Every Year Y-2 ( Y-1 interim) Model validationYearly evaluation reports daily evaluation of forecasts Yearly evaluation reports, daily evaluation of forecasts Robustness10 years experience with Unified model Ensemble approach with EMEP model included Accuracy CTM state of artData assimilation approach implies significantly increased accuracy Adequate spatial resolution 50x50 km 2 25x25 km 2 10x10 km 2 from 2010 Model requirements EMEPMACC-II ensemble Sustainability == Documentation == Availability + Model validation == Robustness + Accuracy + Adequate spatial resolution + for urban background status assessments

15. Indicator maps evaluated Rural and urban background maps For years 2009 and 2010

16. Outline 1.Mapping assessments at EEA 2.Use of MACC-II ensemble products 3.Results for PM10 and O3 4.The role of spatial resolution 5.Conclusions and recommendations

17. Evaluation of EEA mapping results with use of different background models Identification of meaningful comparisons from available data, avoiding data assimilation issues 2009 1.Residual kriging using EMEP model background (50x50 km 2 ) 2.Residual kriging using EC4MACS hindcast (50x50 km 2 ) 3.Residual kriging using MACC-II ensemble hindcast (25x25km 2 ) 4.Residual kriging using EC4MACS hindcast (7x7 km 2 ) 2010 1.Residual kriging using EMEP model background (50x50 km 2 ) 2.Residual kriging using MACC-II ensemble hindcast (10x10km 2 ) … and allowing for an evaluation of the effect of scale

18. ETC/ACM residual kriging Evaluation of CTM models used EMEPMACCens hindcast Similar mapping results both for O3 and PM10 indicators, with different background model used

19. Kriging driven by observations Larger differences between rural and urban kriged maps independently of the models used EMEP MACC_ens_hindcast RURAL URBAN

20. PM 10 - rural areas -2009 Significant improvement in performace inherent to residual kriging as the method is developped to optimize RMSE

21. PM10- urban background - 2009 Significant improvement in performace inherent to residual kriging as the method is developped to optimize RMSE

22. model vs DA vs kriged Largest differences in areas with few observations, kriging driven by observations

23. Is residual kriging better than DA ? Not really, there are caveats in the comparison Caveats in the present comparison !!! MACC-II DA does not use the same stations

24. Not all stations are in MACC-II data DA but all are included in ETC/ACM kriging

25. Outline 1.Mapping assessments at EEA 2.Use of MACC-II ensemble products 3.Results for PM10 and O3 4.The role of spatial resolution 5.Conclusions and recommendations

26. SOMO35 –rural 2009 50x50 km 2 25x25 km 2 7x7 km 2

27. SOMO35 –urban background 2009 50x50 km 2 25x25 km 2 7x7 km 2

28. PM 10 – rural areas -2010 MACC-II ensemble in 2010 with 10x10 km2 Improvement with MACC-II ensemble Both in rural and urban areas Effect of increased resolution

29. PM 10 general performance Finer resolution improves the results MACC generally better results for PM10 in 2010 because of incresed resolution

30. Ozone general performance MACC general better performance, specially in 2010 with finer resolution

31. Conclusions  Residual kriging results largely driven by observations  Therefore there are larger differences in the urban vs rural maps than between models used  and differences between mapping results are larger where we have fewer stations! Similar mapping results independently of the models used although in the analysed cases the MACC-II ensemble shows general better performance MACC-II ensemble appears to be better when used in 10 x 10 km 2, specially for urban background mapping

32. Recommendations 1.ETC/ACM mapping activities will benefit from the regular use of MACC-II ensemble products both for rural and urban background assessments 2.MACC-II ensemble has long-term sustainability, can be available regularly (yearly assessments) and can provide accurate model results with increased spatial resolution. However, the capabilities of MACC-II ensemble data assimilation results have not been assessed in this context. 3.It is recommended to carry out a dedicated study of the capabilities of the DA data assimilated products from MACC-II ensemble in comparison with EEAs urban and rural background assessment mapping routines.

33. Thank you for your attention!