10 october 2008, cavtat (croatia) – first planery meeting fairmode1 ies - institute for...

10 October 2008, Cavtat (CROATIA) – First Planery Meeting FAIRMODE 1

IES - Institute for Environment and SustainabilityIspra - Italy

http://ies.jrc.ec.europa.eu/

http://www.jrc.ec.europa.eu/

Joint Research Centre (JRC)

WG2 Scoping Paper on Quality Assurance...

Scoping Paper on Quality Assurance of Models in Relation to the new EU Air Quality Directive (WG2 - FAIRMODE)

E.Georgieva, P.Dilara



Purpose of the Scoping Paper:

• Provide background information on compliance related aspects of the models quality assurance procedures

• Define the aims of WG2 activities

• Propose methodologies and relevant issues to be discussed at the kick-off meeting

• At present the document has a “open questions” character



Modelling in the context of the new EU AQD:

1. Assessment of ambient air quality

2. Planning and mitigation strategies (e.g. emission scenarios)

3. Assessment of the contribution of natural sources, road dust and winter sanding/salting (source apportionment)

4. Short term forecast for exceedances of information and /or alert thresholds

2. 3. 4.Modelling: implicitely referred

as most like methodology

1.- In all zones and agglomerations, depending on pollution levels with respect to LT, UT and LV



Assessment (AQD)

: modelling shall be sufficient

: combination of modelling and measurements

: measurements may be supplemented by modelling

LAT

UAT

LV

Limit value, Upper and Lower assess. Threshold

SO2, CO, NO2, NOx, PM, lead, benzene



Models in support of the AQD should be reliable and trustful

Model Quality Assurance is a crucial stage andhas to be tailored to different type of models use(explicitly or implicitly mentioned in the Directive)



Model Quality Objectives (MQO)

Relevant to AQ assessment

Defined as modelling uncertainty with regard to hourly, 8h avg.,daily or annual values

WG1:

Relative Directive Error

Pollutant Quality Indicator Modelling uncertainty

SO2, NO2, NOx, CO

Hourly 50 %

8-hour averages 50 %

Daily averages 50 %

Annual averages 30 %

PM10, PM2.5, PbDaily averages Not yet defined

Annual averages 50 %

Ozone and related NO and NO2

Hourly 50%

8-hour averages 50%

Benzene Annual averages 50%



The uncertainty concept ( …remind) e.g. Britter,94; Borrego, Miranda

et al.,2008

essential for models supporting political decision

Can be determined by statistical evaluation comparing observations with model results

TOTALuncertainty

MODELuncertainty

INPUT DATAuncertainty Variability= ++

Emissions, meteorology, chemistry

Stochastic atm. + anthropog. processes

Parameterizations, numerical, grid



Uncertainty and model quality assurance

AQD criteria for acceptability of modelling results:

• Modelling uncertainty

Model evaluation (fitness- for- purpose):• scientific evaluation• verification• validation• model intercomparison• sensitivity analysis• uncertainty analysis• operational evaluation

If generally accepted Model Evaluation Protocol is missing, model validation and intercomparison usually address the model assessment



Open questions 1/2:

Representativeness of stationsstations – compound specific?

Quality of monitored data data (data coverage, comparability of PM instruments, treatments of small concentrations)

Uncertainties of the single modulessingle modules of the modelling system (emission, meteorology, chemical transport model)

Uncertainty of nested modelsnested models (multiscale model cascades) (different spatial scales in emission inventory top/down and bottom/up, nesting in the meteorological and chemical transport model)



Open questions 2/2:Uncertainty for combination of monitoring and combination of monitoring and modellingmodelling (data assimilation), uptake of Kopernikus (GMES) Atmospheric Service

Identify complimentary quality indicators (statistical statistical indexesindexes) for different type of model applications, compound specific ?

Communication Communication of model uncertainty to decision makers (uncertainty spatial mapping, reporting for further use in health and environmental applications)

The model’s model’s user as a source of uncertainty – how to evaluate and how to overcome it



AIMS of WG2 activities:

Overall goal: To develop methodology for quality assurance of models in support of the new EU – AQD

(i) Develop and recommend an EU wide standard procedure for uncertainty evaluation and model performance indicators in support of AQ assessment according the AQD



AIMS of WG2 activities - continued:

(ii) Create a European Framework for Model Validation for different type of models (from hotspot to regional scale) and different purposes (assessment, scenario calculations, forecast of exceedances, contribution from natural sources and winter sanding/salting)

(iii) Steer any potential modifications of the AQD



WG2 participation:

• All EU national experts (bring their needs and expectations, practical test cases)

• DG-ENV (collaborate with respect implementation of the AQD)

• JRC- Ispra: chair for the beginning (meetings, workshops)

• EEA-ETC/ACC: contribute

• External experts if needed

• Others?



Activities of WG2 (tentative list):

a) Organisation of intercomparison exercises for the purposes of the AQD.

b) Uncertainty analysis

c) Characterisation of monitoring stations



a) Organisation of intercomparison exercises for the purposes of the AQD.

Models will be evaluated in two ways:

How well are the models able to reproduce current air pollution ? (AQ assessment)

How well do the models respond to emission changes? (scenario calculations)

JRC experience with CityDelta, EuroDelta



….Intercomparison exercise – possible objectives/activities

• Study the impact of different modules of an AQ system on hourly, daily and annual concentrations

• Study and develop appropriate statistical parameters (indexes) in addition to the AQD parameter

• Propose and test benchmarks

• Develop/adopt appropriate graphical representation (compound specific?)



b) Uncertainty analysis:

• Develop/adopt and regularly update datasets(make use of databases by ACCENT, COST728/732, JRC-DAM, EU – INSPIRE Initiative)

• Uncertainty/sensitivity due to individual physical and chemical processes

• Sensitivity analysis to input parameters (IC/BC, meteo, land use etc.)

• How to define uncertainty for Ensemble Means?

• Address contribution of stochastic variability



c) Characterisation of monitoring stations:

Representativeness, both for AQ and Meteo

Number and types

Analyse if compound specific or not



Concluding remarks:

The Scoping paper is very general

We invite participants to share their needs and expectations

SIGN UP in FAIRMODE web site for WG2

Questionnaire

Meeting in January 09 on definition of the framework, topics and first exercises

10 october 2008, cavtat (croatia) – first planery meeting fairmode1 ies - institute for...

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