Improving regional air quality model results at the city scale : results from the EC4MACS project INERIS : Bertrand Bessagnet, Etienne Terrenoire, Augustin Colette, Laurent Létinois, Laure Malherbe, Laurence Rouïl, Frédéric Tognet, Anthony Ung RSE/INERIS : Guido Pirovano

DCO - 08/09/ titre - 2 CityDelta background  EC4MACS « urban modelling » component : better account for the urban dimension in the integrated assessment modelling  What? : concentration increment (or decrement) due to the city itself  Why? : to correct coarse resolution model used in integrated assessment  How? : Can be defined as δ=C high - C low In the former CityDelta exercice : with a set of CTM results over 7 cities in Europe that lead to a single formula for all European cities CHIMERE high resolution (7 km) simulation over a large part of Europe [ECMWF data + WRF ; EMEP emissions]

DCO - 08/09/ titre - 3 Improving emissions  « residential emissions » (SNAP2) reallocated with population density (+ wood burning share urban vs rural with french data)  « Crops » landuse proxy for Agricultural sector  « built-up » landuse proxy for the other anthropogenic sectors  « roadmap » proxy for road traffic emissions (in progress) PPM2.5 emission before PPM2.5 emission after

DCO - 08/09/ titre - 4 Inluence of vertical resolution  Three simulations performed with CHIMERE over the Paris area C8 : Reference run with 8 levels (first at 40 m) up to 500 Hpa C20 : Simulation with 20 levels (first at 40 m) up to 500 Hpa C9 : Simulation with 9 levels (first at 10 m) up to 500 Hpa

DCO - 08/09/ titre - 5 Inluence of vertical resolution Coll. L. Menut LMD/IPSL-CNRS

DCO - 08/09/ titre - 6 Improving horizontal resolution – why 7 km resolution?  For secondary pollutants like O3, 12 km seems an optimal resolution (Valari and Menut, 2008)  From the POMI exercize, no gain from 6km to 3 km (even for PM)  Computing time…(increase of grid cell number and decrease of time step)

DCO - 08/09/ titre - 7 The simulation domains  A high resolution run is performed over the grey domain (7 km)  A high resolution run is performed over the grey domain  For each small cell (i,j) : the high res. conc : the coarse res. Conc. : the averaged concentration : (i,j) COARSE (50 km) NEST (7km) 300 x 400 grid points! DELTA assumed to be :

DCO - 08/09/ titre - 8 Simulation results  Two simulations performed for the year 2006 : A simulation with only primary particulate matter and low level sources (SNAP 2, 7 and partly 3)  PPM run A full chemistry run Delta PPM2.5 species 2006 µg.m -3 Month

DCO - 08/09/ titre - 9 [PPM based delta] versus [full PM based delta] PPM run: Delta PPM2.5 species FULLCHEM run: Delta PM2.5 species µg.m -3

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DCO - 08/09/ titre - 11 Model underestimations  Usually we have an underestimate of PM SOA formation (  background issue) Wildfires (60% of the total PM10 emissions in Europe! including a part of Russia - AQMEII project) (  background issue) Domestic wood burning in wintertime Road traffic resuspension Resuspension from soil erosion (  background issue) Emission vertical profiles Meteorology (kz calculation, wet deposition)

DCO - 08/09/ titre - 12 PM2.5 Jan 2006 – using EMEP vertical profile for SNAP 2 emissions

DCO - 08/09/ titre - 13 PM2.5 Jan 2006 – putting all SNAP 2 in the first CHIMERE layer

DCO - 08/09/ titre - 14 Impact of emision injection heights of city deltas

DCO - 08/09/ titre - 15 Conclusion  Downscaling method of EMEP emission dataset improved for our high resolution  High resolution run was performed over Europe to compute citydeltas  Improvment of CHIMERE runs at all resolutions (high and low)  Define a strategy to use « deltas » in integrated assessment model

DCO - 08/09/ titre - 16 Extra slides

DCO - 08/09/ titre - 17 About validation…  Pratically, it is not possible to validate a « delta » δ=C high - C low ; C high and C low are comparable with measurements, but δ ??  What is the order of magnitude of PM2.5 deltas? With measurements in 2009, we roughly estimate the delta =1.6 µg.m -3 versus 0.94 µg.m -3 found in our work (for 2006).  Validation on PM2.5 for the “full chemistry run” City

DCO - 08/09/ titre - 18 Box model approximation  Reminder : a coefficient K is defined by city as δ=K.Q  Possible implementation of a box model by city to introduce a sensitivity to meteorological parameter  Box model increment : X city = diameter of the city (m) X bckg = charateristic length of the background (m) (EMEP grid compliant) S city = surface of the city (m²) S bckg = surface of the low resolution cell (m 2 ) Q= city emissions (kg/s) h= ABL height U= Wind speed at 10m (m/s)

DCO - 08/09/ titre - 19 CityDelta background – are observations useful to compute the citydelta?  Main goal is to correct a coarse EMEP simulation We can consider : δ ideal =C real – C low then, δ ideal corrects the model behavior and the lack of sources (using optimal interpolation methods) Then, δ ideal = δ known physics and emissions + δ missing sources & processes And, δ ideal =K.Q + δ missing sources & processes We must correct only what we know, implementing observations in the methodology introduces a bias difficult to handle in GAINS calculations Computed in this work What to do with this term? Nothing!

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DCO - 08/09/ titre - 21 Background O3 (AVERAGE) Background O3 (low resol) ppb

DCO - 08/09/ titre - 22 AQMEII project AreaPointFireTotal CO (50.7%) NOx (6.9%) NMVOC (4.4%) SO (1.2%) PM (59.4%) NH (10.2%) Domain-wide yearly emissions [tons/y]