PASODOBLE

Progress on the development of local and regional downstream services

Martijn Schaap, Thilo Erbertseder & PASODOBLE consortiumFAIRMODE 4th plenary meeting

SMHI, June 16, 2011, Norrköping, Sweden

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

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

PASODOBLE - Concept

Interface to Core and Inputs

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Health Community Support

Public Forecasting Support

Compliance Monitoring Support

Local Model Evaluation Support

Air Quality Service Cluster1

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In situ & Satellite Data

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

Scale and Application of Current AQ Projects

Source: FAIRMODE

Towards harmonised nesting of models

Global (Reactive and Greenhouse Gases, Aerosol)

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Local / Urban

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Harmonised Nesting via MACC ENS and Airsheds

Intermediateairsheds at~ 7x7km resolution

Bridge gap between MACC ENS and local nests

covering most of the local/urban services within PASODOBLE

Nesting within MACC air quality ensemble

• 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

NO2 conc at 06:00 for July 16, 2007 EURAD-IM IC-AIRSHED forecast system

Data Extraction Tool for NestingSelect 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

Data Extraction Tool for NestingSelect 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

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

Need for considering local scales – Brussels NO2, 2005

PROMOTE IAQMACC ENS

Limit value

Need for considering local scales – Brussels NO2, 2005

Population density weighted concentration (i.e., exposure) for a 64 64 km2 sub-domain, as a function of spatial resolution

).

4 8

1x1km²:342.000 inhabitants above limit value

16x16km²:none above limit value

Compliance Monitoring Support Services• Collaboration with agencies with AQ

Directive compliance duties to facilitate their reporting

• Provide explanation of exceedance of 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

Quantification of dust loadings Utilizing thermal characteristics of MODIS/TerraDust mass loading (g/m-2) covering the Canary islands

NILU infrared camera for in-situ validation

Improved PM analysis and forecasting over the Netherlands

Sea salt at PM10 ~50 ug/m3

Venlo

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

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

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

User Interface

Goal: allow interoperable access to data in a simple and harmonized wayCentral Pasodoble system allows access to information from de-central service

providers

Collab with FP7 GENESIS

Collected information consists of:concentration mapsin-situ measurementstime series

Functionalities (WMS, WPS, CSW):Display / Comparison / Time SeriesExposure CalculationData FusionGoogle Earth FunctionalitiesOGC and INSPIRE compliance

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

www.myair-eu.org

Contact: thilo.erbertseder@dlr.depasodoble@dlr.de

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, DERIVM National Institute for Public Health and the Environment, NL

Improving PM Forecasts by Satellite Data Assimilation

Forecast withoutsatellite data

Comparison of forecastwith gb measurementsat 10 dust outbreaks

July-Nov 2003

Schroedter-Homscheidt et al, 2010

Forecast inlcudingENVISAT/SCIA/AATSR

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

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

Compliance monitoring support for PM for Northrhine-Westphalia

Emission cataster (PM10) PM10 Annual Mean 2008 (ENVISAT, SYNAER)from LANUV for 2000/2008 satellite map (0.1° x 0.1 °)

< 800 800 – 24002400 – 64006400 – 32000> 32000

kg/a 16km² - raster 4x4 km2

0.0 25.0 50.0PM10 [µg/m³]

Improved PM analysis and forecasting over the Netherlands

Sea salt at PM10 ~50 ug/m3

Venlo