Part 1

Monte Carlo uncertainty evaluationof emission reduction scenarios

constrained by observations from the ESQUIF campaign

M. Beekmann (LISA), C. Derognat (Aria-Technologies)

Part 2

Extension of CHIMERE to Eastern Europe and evaluation with surface

and satellite data

I. Konovalov (Institute of Appplied Physics, Nizhny Novgorod) M. Beekmann (LISA)

R. Vautard (LMD/IPSL)A. Richter (IUP, University of Bremen)

J. Burrows (IUP, University of Bremen),

What is the uncertainty in the simulation of emission reduction scenarios ?

Case of Paris agglomeration

Monte Carlo uncertainty analysis

Model output uncertainty due to uncertainty in input parameters

Constraint by measurements (ESQUIF campaign)

(Bayesian Monte Carlo uncertainty analysis)

Reduced uncertainty

METHODOLOGY (1)SET-up of the CHIMERE model for the Paris region (version 2002)

Domain 150 km x 150 km with 6 km horizontal resolution

5 vertical levels from surface to ~3 km

Forced by ECMWF first guess or forecast

Gas phase chemistry: MELCHIOR with 82 compounds, 338 reactions

Emissions, refined for regional scale from AIRPARIF, also biogenic

Boundary conditions: from CHIMERE at continental scale

OX, NOy 16/7/99 14h POI6

METHODOLOGY (2)Definition of the probability density function for input parameters

EMISSIONS : anthropogenic VOC 40 % (log.,1) Hanna et al, 1998 anthropogenic NOx 40 % (log.,1) as for VOC biogenic VOC 50 % (log.,1) Hanna et al, 1998, 2001

RATE CONSTANTS : NO + O3 10 % (log.,1) Atkinson et al, 1997 NO2 + OH 10 % (log.,1) Atkinson et al, 1997 NO + HO2 10 % (log.,1) Atkinson et al, 1997 NO + RO2 30 % (log.,1) Atkinson et al, 1997 HO2 + HO2 10 % (log.,1) Atkinson et al, 1997 RO2 + HO2 30 % (log.,1) Atkinson et al, 1997 RH + OH 10 % (log.,1) Atkinson et al, 1997 CH3COO2 + NO 20 % (log.,1) Atkinson et al, 1997 CH3COO2 + NO2 20 % (log.,1) Atkinson et al, 1997 PAN + M 30 % (log.,1) Atkinson et al, 1997

PHOTOLYSIS FREQUENCIES + RADIATION :

actinic flux 10 % (log.,1) see text J(O3 -> -> 2 OH) 30 % (log.,1) DeMore et al, 1997 J(NO2->NO+O3) 20 % (log.,1) DeMore et al, 1997 J(CH2O->CO+2 HO2) 40 % (log.,1) DeMore et al, 1997 J(CH3COCO-> ....) + 50 % (one sided, 1) S 95, RM 96 J(carbonyl compound from o-xylene) 40 % (log.,1 Atkinson al, 1997

METEOROLOGICAL PARAMETERS:

zonal wind speed 1 m/s (absolute,1) see text meridional wind speed 1 m/s (absolute,1) see text mixing layer height 20 % (log.,1) see text temperature 1.5 K (absolute,1) Hanna et al, 1998 relative humidity 20 % (log.,1) after Hanna et al, 1998/2001 vertical mixing coefficient 50 % (log.,1) see text deposition velocity 25 % (log.,1) Hanna et al, 1998/2001

METHODOLOGY (3) Constraints from ESQUIF observations

From circular flights (DIMONA, MERLIN) OX, NOy, NOx, (VOC)

C = C (plume) – C (background)

From airquality network (AIRPARIF)OX = OX (urban) – OX (background)

Flight tracks around the Paris agglomeration during ESQUIF

METHODOLOGY (3) Constraints from ESQUIF observations

From circular flights (DIMONA, MERLIN) OX, NOy, NOx , (VOC)

C = C (plume) – C (background)

METHODOLOGY (4)mathematical formulation of the constraint

For each Monte Carlo simulation k:

Likelihood L for model output Yk to be correct for observations Oi (Bayesian Monte Carlo analysis Bergin and Milford, 2000):

1 (Oi – Yk,i)

2

L(YkY | Oi) = _____________ EXP [ -0.5 _______________ ] (2 ii

2

L(Yk | O) = L(Yk,,1 | O1) * L(Yk,2 | O2) * …….

Measurement errors i of observations Oi are assumed as normally distributed independent They stem from instrumental errors uncertainty in representativity for model grid

METHODOLOGY (5) Simulations performed

For 3 days in POI’s 2 and 6: August7, 1998 and July 16,17

500 Monte Carlo simulations with base line emissions

500 Monte Carlo simulations with reduced emissions

- 50 % anthropogenic VOC - 50 % anthropogenic. NOx - 50 % anthro. VOC + NOx

RESULTS (1)

• Cumulative probability plots

Surface O3 maxima for baseline and 50% reduced emissions

With (____) and without (- - - -) constraint

RESULTS (2)

Surface O3 maxima for baseline and 50% reduced emissions

RESULTS (3)Chemical regime averaged over the pollution plume:

Difference in surface O3 between a

NOx emissions –50 % and a

VOC emissions –50% scenario

Positive values : VOC limited chemical regime

Average over 1998/1999 :

VOC sensitive or intermediate chemical regime (thesis C. Derognat)

RESULTS (4)

OH averaged over the pollution plume

at 14 UT (layer 2 50-600 m):

RESULTS (5)

A posteriori

and a priori

probability of

input parameters :

NOx and VOC

emissions

CONCLUSIONS

Uncertainty in simulated max. ozone (for baseline and reduced emissions) reduced by a factor 1.5 to 3 due to measurement constraint

Uncertainty in VOC limited regime is reduced for two days, shift from slightly VOC limited to slightly NOx limited for anaother day

For OH, the uncertainty is less reduced, but very low values are rejected, remaining uncertainty factor 1.5 – 2.5

Weighting procedure through likelihood function changes distribution in input parameters namely NOx emissions

Limitations of this study:

Uncertainty in model formulation is neglected (transport, model chemistry)

Uncertainty in the definition of pdf’s for input parameters

Uncertainty in error distribution of observations (covariance always zero ?)

Perspectives :

Application to continental scale

Application to air quality forecast

Part 2

Extension of CHIMERE to Eastern Europe and evaluation with surface and

satellite data

I. Konovalov (Institute of Appplied Physics, Nizhny Novgorod) M. Beekmann (LISA)

R. Vautard (LMD/IPSL)A. Richter (IUP, University of Bremen)

J. Burrows (IUP, University of Bremen),

Model set up

Domain covering EU to Ural + Mediterranean regions with 0.5 ° horizontal resolution

8 vertical levels from surface to 500 hPa

Forced by NCEP forecast (2.5°) and MM5 (1° res.)

Gas phase chemistry: MELCHIOR reduced

Emissions from EMEP and EDGAR, if needed

Boundary conditions: from MOZART

Time series

Error statistics

Comparison between GOME and CHIMERE derived tropospheric NO2 columns,

June – August 1997

University of Bremen,GOME version V2 320 * 40 km resolution

I. B. Konovalov, M. Beekmann, R. Vautard, J. P. Burrows, A. Richter, H. Nüß, N. Elansky, ACP, 2005

CHIMERE tropospheric NO2 columns versus

GOME tropospheric NO2 columns

Average June – August 1997 Western Europe Eastern Europe

Slope = 0.75R = 0.91

Slope = 0.70R = 0.77

differences in GOME / CHIMERE tropospheric NO2 columns versus

tropospheric NO2 columns (1015mol.)

Random error in monthly mean (in a spatial sens) is mainly of multiplicative nature (25-30%), no attribution to GOME or CHIMERE possible

Western Europe

differences in GOME / CHIMERE tropospheric NO2 columns versus

tropospheric NO2 columns (1015mol.)

Random error in monthly mean (in a spatial sens) is less clearly of multiplicative nature for Eastern Europe than for Western Europe

Eastern Europe

CONCLUSIONS

CHIMERE domain has been extended to Eastern EU and Mediteranean region

Correlation with surface O3 obs. larger in WE (>80%) than in Central and EE <60-70%)

Comparison with GOME tropospheric NO2 :* No bias* slope 0.70-0.75* multiplicative spatial random error 15% EE – 30% WE