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Urban PM and the integrated assessment.

Jean-Marc BRIGNONInstitut National de l ’Environnement Industriel et des RisquesDirection des Risques ChroniquesUnité Modélisation et Analyse Économique pour la Gestion des RisquesTél. 03 44 55 61 29jean-marc.brignon@ineris.fr

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Urban PM exposure and integrated assessment Important benefits expected from reduction in urban PM

exposure.

IAM will help set priorities for the repartition of efforts between regional and local policies for PM.

=> Necessity to take account of the diversity of urban situations regarding PM in the IAM work : high number of cities to be taken into account.

=> Underestimation of PM by regional-scale dispersion model : how can we compute correction factors for many cities in Europe ?

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Two similar approaches are possible

IIASA (Rains Review 2004 report) : correction factor based on PM emission density in cities.

This approach : correction factors based on NOx concentrations in cities and SO4 concentrations in rural background around the city.

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Origin of PM in cities

Distance from city centre0

PM Concentration

Local PM

PM for regional background

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Statistical assessment of origin of PM in cities

PM10 = A * [NOx urban] (surrogate for PM from local combustion)

+ B * [SO4 rural] (surrogate for regional PM)

+ C (other PM : crustal material, marine aerosol,

resuspended)

Data from local monitoring networks (from City-Delta database for this trial)

Data from EMEP network

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An example of detailed results : Milan

Milan : comparison between observed and modelled PM10

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µg

/m3

Mesures(moyenneLimito/Meda/Vimercate)Modèle

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An example of detailed results : Milan

Milan : contribution of local combustion sources and regional background to PM concentration

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µg

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Observed PMconcentration

PM from localcombustion sources

PM from regionalbackground

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Realtive share of local combustion sources in PM 10 concentrations

0

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Mean value

Higher limit (95%confidence interval)

Lower limit (95%confidence interval)

Par

is

Par

is P

M 2

.5

Lond

on

Mar

seill

e

Mila

n

Ber

lin

Pra

gue

Kat

owic

e

Cle

rmon

t-F

erra

nd

Cae

nHigher share for PM2.5 than for PM 10

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Qualitative use of PM apportionment results in the Integrated Assessment.

=> build a typology and range european cities in categories according to the strenght of the share of local sources in PM concentration.

=> test scenarios with RAINS in which emission controls on mobile sources (PM filter, fuel switches in public transports,...) and other local sources are differentiated in each city type ?

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Hybrid model to compute PM in cities.

Local contribution

computedas % of regional

contribution

Observed PM concentration in urban background

Hybrid modelEMEP Model

Regionalcontribution

computed with EMEP model

The % factor is given by the statistical PM apportionment

modelsAssumes that the % factor is not dependant from the scenario being analysed

Rigorously, for each city, the regional contribution should be computed zeroing the local urban emissions in the EMEP model

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Interannual variability of the share of local emissions.

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Date

01/02/99

05/03/99

06/04/99

08/05/99

09/06/99

11/07/99

12/08/99

13/09/99

15/10/99

16/11/99

18/12/99

Milan

Londres

Paris

Berlin

Prague

Marseille

Katowice

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Conclusions.

Contribution of local emissions is highly variable between european cities : need to adopt a method able to include a high number of cities : statistical models combined with dispersion models can be part of a solution.

Data availability problems : local PM emissions, PM 2.5 concentrations.

Uncertainties : variability of the “urban signal “ over time and under different emission scenarios.

What can be done for urban ozone ?