PASODOBLE

1. PASODOBLE Progress on the development of local and regional downstream services Martijn Schaap, Thilo Erbertseder & PASODOBLE consortium FAIRMODE 4th plenary meeting SMHI, June 16, 2011, Norrköping, Sweden

2. PASODOBLE – Service Domains • Focus on regions and cities, complementary to MACC  Focus on regions and cities, complementary to MACC  35 downstream AQ services to support local actors

3. PASODOBLE - Goal Develop and demonstrate user-driven services for the regional and local air quality sector by combining space-based data, in-situ data and models in 4 service lines: • Health community support for people at risk, hospitals, pharmacies and doctors • Public forecasting and assessment support for agencies, tourist industries and sport event organizer Compliance monitoring support on particulate matter for regional environmental agencies Local forecast model evaluation support for local authorities and city bodies … embeded in a generic, harmonised technical infrastructure

4. PASODOBLE - Concept User Needs GMES Core Services In situ & Satellite Data Other Inputs Interface to Core and Inputs Air Quality Service Cluster 1 Quality Management Marketing and Business Planing Health Community Support Compliance Monitoring Support Public Forecasting Support Local Model Evaluation Support Interface to Users User feedback cycle Marketing cycle 2 Users and Market

5. PASODOBLE - Objectives • Development and demonstration of AQ services for European regions/cities, based on documented needs and demonstrated capabilities of the ESA GSE PROMOTE user federation and service providers Development and testing of a sustainable generic service infrastructure for efficient and effective implementation of (future) services and user access. Utilization of multiple cycles of delivery, use, assessment vs. requirements including market intelligence assessment wrt to self-supportiveness and sustainability Promotion of use of best/good practise and harmonization

6. Scale and Application of Current AQ Projects Source: FAIRMODE

7. Towards harmonised nesting of models Global (Reactive and Greenhouse Gases, Aerosol) Quality Management MACC European / Regional Regional PASODOBLE Quality Management Local / Urban Use and Application

8. Harmonised Nesting via MACC ENS and Airsheds Intermediate airsheds at ~ 7x7km resolution Bridge gap between MACC ENS and local nests covering most of the local/urban services within PASODOBLE

9. Nesting within MACC air quality ensemble NO2 conc at 06:00 for July 16, 2007 EURAD-IM IC-AIRSHED forecast system • Currently airsheds nested into single MACC ensemble members • Currently tests are being performed using the MACC ensemble data as boundary conditions • Issues: • Currently available O3, NO2, PM10, SO2 and CO. • More species and vertical levels are required • Timeliness: two nesting steps require availability of MACC data very early in morning

10. Data Extraction Tool for Nesting • Select any sub domain, species, layers, dates and directly get the data: • OGC compliant web coverage service (WCS) to access airsheds and soon MACC ENS • Via metadata all available species can be browsed • Example: TNO/KNMI-LOTOS Airshed:http://wdc.dlr.de/cgi-bin/airsheds_tno • Example: Surface NO2 for SW-Germany on 2011-04-19request=getcoverage&time=2011-04-19&coverage=o3,no2&elevation=1&bbox=6.9528750,47.4687533,9.5778750,49.2187533

11. Data Extraction Tool for Nesting • Select any sub domain, species, layers, dates and directly get the data: • OGC compliant web coverage service (WCS) to access airsheds and soon MACC ENS • Via metadata all available species can be browsed • Example: TNO/KNMI-LOTOS Airshed:http://wdc.dlr.de/cgi-bin/airsheds_tno • Example: Surface NO2 for Germany on 2011-04-19request=getcoverage&time=2011-04-19&coverage=o3,no2&elevation=1&bbox=5.0,46.4,15.5,54.5

12. Public Information and Assessment Support Services • Improvement of existing AQ services in 25 regions and cities • Regional harmonisation w.r.t INSPIRE and FAIRMODE guidance • Thematic integration (physical, chemical and biological weather forecasting) • Examples: • Harbour Management Support Antwerp • Road traffic management (NL) • Olympic Games London 2012 • Tourism Information Systems

13. Need for considering local scales – Brussels NO2, 2005 Limit value MACC ENS PROMOTE IAQ

14. ). 4 8 Need for considering local scales – Brussels NO2, 2005 1x1km²:342.000 inhabitants above limit value 16x16km²: none above limit value Population density weighted concentration (i.e., exposure) for a 64  64 km2 sub-domain, as a function of spatial resolution

15. Compliance Monitoring Support Services • Collaboration with agencies with AQ Directive compliance duties to facilitate their reporting • Provide explanation of exceedanceof local emissions or advected dust • Use satellite data complementary to ground-based data • Improve upon existing desert dust services to provide daily quantitative analysis of dust (not forecasting) • Develop a satellite-based mapping tool for PM threshold exceedances

16. Quantification of dust loadings • Utilizing thermal characteristics of MODIS/Terra • Dust mass loading (g/m-2) covering the Canary islands NILU infrared camera for in-situ validation

17. Improved PM analysis and forecasting over the Netherlands Sea salt at PM10 ~50 ug/m3 Venlo

18. Local Model Evaluation Support Service • Target: city bodies and authorities • Develop and demonstrate a toolbox • Set standard criteria and protocols for performance evaluation • Promote good practice wrtFAIRMODE and AQME II • Standardize interfaces • Support accountability/apportionment studies • Test cases with city authorities Sofia, Bratislava, Prague, Athens,Thessaloniki, London, Rotterdam • Demonstration during the next months

19. What will it be like? • Methodology • Web based, structured advice and a toolbox • Evaluation of model output with respect to satellite and in situ measurements • Aspects • basic criteria/fitness for purpose check list e.g. is model resolution consistent with application? • scientific assessment • model evaluation methodologies (concentrations) based on FAIRMODE guidance and AQME II • forecast accuracy criteria (metrics) e.g. AQ index, number of episodes correctly forecast, systematic/unsystematic etc

20. Difference to existing approaches • Focus on the local and urban scale • Focus on air quality forecasting • Focus on evaluation of operational models (probabilistic and operational) • Online Evaluation Support Service

21. UserInterface • Goal: allow interoperable access to data in a simple and harmonized way • Central Pasodoble system allows access to information from de-central service providers • Collab with FP7 GENESIS • Collected information consists of: • concentration maps • in-situ measurements • time series • Functionalities (WMS, WPS, CSW): • Display / Comparison / Time Series • Exposure Calculation • Data Fusion • Google Earth Functionalities • OGC and INSPIRE compliance

22. Summary • PASODOBLE builds on the achievements of PROMOTE and MACC and utilizes guidance from FAIRMODE • Develops a number of targeted and sustainable air quality services throughout Europe to support local actors • Develops a modular, generic and harmonized service infrastructure for efficient implementation of (future) services and user access • Follows a combined approach (modelling, in-situ, remote sensing) • Contributions to FAIRMODE on harmonised nesting, local model evaluation support, source attribution • Service prototypes have been developed, next step validation

23. www.myair-eu.org • Contact: • thilo.erbertseder@dlr.de • pasodoble@dlr.de

24. PASODOBLE - Consortium DLR Deutsches Zentrum für Luft- und Raumfahrt (coordinator), DE ACRI ACRI – ST, FRAEA AEA Technology, UKAUTH Aristotle University of Thessaloniki, ELBMT BMT ARGOSS, NLIASB Institut d’Aeronomie Spatiale de Belgique, BEBAS Bulgarian Academy of Sciences, GPhI, BGCERC Cambridge Environmental Research Consultants, UKCGS Carlo Gavazzi Space, ITCHU Centre Hospitalier Universitaire Nice, FRMUW Medical Uni Vienna / European Aeroallergen Network, ATEMA European Medical Association, INTFMI Finish Meteorological Institut, FIKNMI Koninklijk Nederlands Meteorologisch Instituut, NLNILU Norsk Institutt for Luftforskning, NORIU Rheinisches Institut für Umweltforschung, DETAS-F Thales Alenia Space France, FRTNO Ned. Org. v. Toegepast Natuurwetenschappelijk Onderzoek, NLVITO Vlaamse instelling voor technologisch onderzoek, BENowcasting International, IEOutdoor Concepts, DE RIVM National Institute for Public Health and the Environment, NL

25. Improving PM Forecasts by Satellite Data Assimilation Comparison of forecast with gb measurements at 10 dust outbreaks July-Nov 2003 Forecast inlcuding ENVISAT/SCIA/AATSR Forecast without satellite data Schroedter-Homscheidt et al, 2010

26. Need for considering local scales – Brussels NO2, 2005 Simulated annual mean NO2 concentration field for Brussels and surroundings with VITOAURORA model. Population density expressed as number of residents per km2 for

27. PASDOBLE: Compliance Monitoring DS COMP 3.3 Monitoring PM 2.5 Exceedances in Italy 2005 average PM2.5 [µg/m³] 2005 % exceedances above 25 µg/m³ PM retrieved from MODIS/Terra satellite-data

28. < 800 800 – 2400 2400 – 6400 6400 – 32000 > 32000 kg/a 16km² - raster 4x4 km2 Compliance monitoring support for PM for Northrhine-Westphalia Emission cataster (PM10) PM10 Annual Mean 2008 (ENVISAT, SYNAER) from LANUV for 2000/2008satellite map (0.1° x 0.1 °) 0.0 25.0 50.0 PM10 [µg/m³]

29. Improved PM analysis and forecasting over the Netherlands Sea salt at PM10 ~50 ug/m3 Venlo