1. Summary on Prague workshop QUANTIFY Workshop, De Bilt, 8-9 november 2005 dimitri.caro@cea.fr LSCE, CNRS/CEA, Gif sur Yvette, France

2. ACTIVITY 2 WP 2.1.1 Road traffic CERC, IVL, NIMH WP 2.1.2 Ship plumes (small scale) IVL, CERFACS WP 2.1.3 Ship plumes (meso scale) IVL, CUNI, NIMH WP 2.2.1 Aircraft wakes (small scale) IVL, ONERA WP 2.2.2 Aircraft wakes (meso scale) CERFACS WP 2.3 Ship measurement DLR,UYO,PSI,HA,CUNI WP 2.4 Effective emission indices CERFACS,CERC,NMA,NIMH, CUNI

3.  Intensive review of modeling and computational methods for Effective Emission Indices  Review paper submitted before the end of the year: Paoli, Caro, Meijer and Sausen  definition of chemistry and aerosol chemistry schemes for new plume simulations  comparison with 10 plume measurements already available (Hans Schlager)  simulations for the lowermost stratosphere with Br and Cl chemistry  consideration of effect of plume processes by a modification of reaction rates (CERFACS) Aircraft plumes (small and meso scales) WP 2.2.1, 2.2.2, 2.4 CERFACS: Roberto.Paoli@cerfacs.fr CERFACS: Benedicte.Cuenot@cerfacs.fr

4.  box NO x (t)  plume NO x (t)  NO x (t=0)+  NO x (t=0) = NO x ambient + NO x emissions  NO x (t=0)  Approach of Kraabol et al. (2000, 2002) and Meijer (2001): Emission Conversion Factors  Approach of Petry et al. (1998): Effective Emission Indices Parameterizations of aircraft plumes t0 15h 18h  Plumb et al. (2003): Comparison of the two approaches ? plume grid box NO x ambient NO x ambient + NO x emissions  NO x (t=0)  NO x (t) plume

5. GCM results including aircraft plume processes Kraabol et al. (2002) Maximum reduction of  NO x January20%8 to 22 pptv May25% to 35%15 to 25 pptv Maximum reduction of  O 3 January15% to 20%0.4 to 0.6 ppbv May15% to 18%0.8 to 1 ppbv Meijer (2001) Maximum reduction of  NO x January20% to 30%15 to 30 pptv July20% to 40%10 to 35 pptv Maximum reduction of  O 3 January0% to 5%0 to 0.1 ppbv July-5% to 10%-0.1 to 0.2 ppbv  Disagreement for O 3 results between Kraabol et al. et Meijer ?  Plumb et al. (2003): - similar results with the two plume parameterizations - small impact of plume processes on O 3 as in Meijer (2001)  Shortcomings of these results: - consideration of one plume for the total emissions of a grid box ! - no interaction of plumes  overestimation of the plume effects on NO x and O 3

6. Parameters controlling the chemical conversion of aircraft emissions in a dispersing plume Calculations of ECFs or EEIs Dynamical variables for dispersion of plumes :  Diffusion coefficients (M -)  Wind shear (M ±,Pl ±) Location of emissions :  Latitude (K +, M +, Pl +)  Altitude (M +, Pl +) Composition of background atmosphere :  air masses (Pl +)  clean air vs corridor conditions (K +, Pe +)  NO x and O 3 background conditions (K +, M +) Time of year of emissions :  Months (K +, M +, Pl +)  Seasons (K +, M +, Pl +) Emission time (K +, M +, Pe +, Pl -) Plume models : single or multishell plume (K +, Pe -) Meteorological parameters :  T (K +, M ±)  Humidity (M +)  Photolysis (K ±, M ±) Heterogeneous chemistry (K -, M -) Type of aircraft (K ±, M ±) K : Kraabol et al. (2000, 2002), M : Meijer (2001), Pe : Petry et al. (1998), Pl : Plumb et al. (2003)  A lot of parameters, a lot of uncertainties compared to a possibly small impact ! - : negligeable effect (<< 10%) ± : moderate effect (~ 10%) + : strong effect (>> 10%)  Plumb et al. (2003): importance of emission time depends on the end time of the plume  need for a precise definition of end time of the plume  relation between end time of plume and grid box resolution ?

7.  Measurement pre-campaign in July 2006 and campaign in spring 2007  Need to define the parameter fields that should be measured for a global modelling  necessity for pre-simulations of ship plume processes with a detailed plume model to identify the essential parameters  Need for the development of ship plume simulations  importance of sea wake for initial NO x emissions through humidification of air wake (plume) Ship plumes (small and meso scales) WP 2.1.2, 2.1.3, 2.3, 2.4 CERFACS: Roberto.Paoli@cerfacs.fr DLR: hans.schlager@dlr.de

8. Modeling the chemical effects of ship exhausts Glasow et al. (2002)  Box model: plume and background reservoirs  Dilution of plume: expansion of the plume + entrainment of background air  Expansion of the single plume: Constant parameters (≠gaussian plume)  Mixing of concentrations:  Chemical lifetime of the ship plume: 2 days  Effects of emissions of several ships and plume overlap: - Calculations of an «average ship» emission and a «ship density» - Homogeneous distribution of ships and all ship routes parallel - Specific aera : 1730 x 1730 km (length of plume after 2 days)  Plume overlap if more than 40 ships  mean time lag between 2 ships  interaction between 2 plumes  Background/background+plume comparison: - Important increase in NO x and SO 2 - Negligeable impact on O 3  Expanding plume (EP)/instantaneous dispersion (ID) comparison: - Twice less with the EP for O 3, OH, NO x, SO 2 Disagreement still exists between these calculations and the measurements !  Lot of uncertainties in the estimate of ship emissions  Lot of uncertainties regarding this averaging approach

9. Surface transport emission WP 2.1.1, 2.4 Stéphanie Gray (CERC): steph@cerc.co.uk  review paper on emission data from road traffic partly done (draft available from CERC)  estimation of emissions, availability of emission data, evolution of emissions in the atmosphere  modelling with IVL (for heterogeneous processes) and NIMH (for mesoscale modelling)  Required work: - investigation to understand which processes are important for the dispersion of road traffic emissions onto scale of climate models - small-scale output from ADMS-Urban (CERC) to be used as input to larger scale modelling  preliminary modelling: study of effect of modelling road traffic emissions on different scales  future work: further preliminary modelling, improvement of chemistry, selection of modelling configurations for mesoscale models