Charles University in Prague Faculty of Mathematics and Physics Department of Atmospheric Physics V Holešovičkách 2, Prague 8, Czech Republic Jan Karlický, Peter Huszár, and Tomáš Halenka Validation of gas phase chemistry modules used in WRF/chem model on domain including Europe E-mail: Jan.Karlicky@mff.cuni.cz 1. Objectives O3 [μg/m3] in Suburban stations O3 [μg/m3] in Urban stations Evaluate the ability of atmospheric model WRF/chem to capture temporal and spatial distribution of short-lived gas concentrations Compare gas-chemistry modules CBMZ and RADM2 Study links between emissions, amount, and concentrations of some gases 2. Methods a) Model setup Model: WRF/chem v. 3.5.1, simulation year 2008, 5-days spin-up Domain: ENSEMBLES 190x206 points, 25 km resolution, 30 vertical levels Boundary conditions: ERA-interim data, MOZART-4/GEOS-5, Clim. UBC Parameterization: Radiation RRTM(LW) + Goddard(SW), Morrison double-moment scheme (Microphysics), Noah Land Surface Model, MM5 surface layer, PBL – Yonsei University scheme, convection – Grell-Freitas scheme Emission inputs: TNO MACC-II anthropogenic emission data, MEGAN biogenic emissions, FINN SAPRC99 biomass burning emissions Chemical modules: CBMZ and RADM2 (gas only) BIAS, CC, and SLOPE for all gases and st. types b) Reference data E-OBS v.11 (physical part of model), gridded data with 0.25° resolution AirBase database – The European air quality database (v. 7, chemical part), European station data c) Links between biogenic emission of Isoprene, total column of Formaldehyde, and NOx total column Isoprene is the main component of biogenic emissions for Formaldehyde production But there is not direct relation between Isoprene and Formaldehyde amount, NOx is needed for decomposition of Isoprene [Wolfe et al., 2015] The resulting images are composed by localities with prevailing biogenic emissions (less NOx) and urban emissions (more NOx and Formaldehyde, but less Isoprene) Chosen AirBase background stations in 2008 (Rural – green, Suburban – orange, Urban – red) O3 NO2 Relation between biogenic em. of Isoprene (moles/km2), Formaldehyde total column (1019 molec/m2), and NOx total column (1019 molec/m2) (Blue – CBMZ, Red – RADM2; in the middle and on the left – CBMZ only) CO SO2 4. Summary, Discussion Differences between simulation with CBMZ and RADM2 modules in terms of meteorology are negligible – there is only low impact from gas-phase chemistry to meteorology (direct to radiation transfer) Impact of higher precipitation or lower daily amplitude of temperature to chemistry could be stronger – through wet scavenging or less sunshine From presented gases, simulated Ozone concentrations make the best results. Probably reason is that Ozone is secondary pollutant, so it is not directly emitted by sources and its spatial distribution is not as strongly varying near emission sources as in term of CO or SO2, so it could be captured by model with 25 km resolution much better than primary pollutants CO or SO2 Formaldehyde total amount depends strongly on NOx total column, which could be seen on middle image, except urban NOx localities we can see ‘triangle’ with base of low and top of higher NOx total column. c) Statistical quantities BIAS = Model deviation from measurement normalized by reference state (%) CC – Standard Correlation Coefficient SLOPE – Standard Regression Coefficient 3. Results a) Validation of Physical state of model WRF/chem Full-domain season average biases for temperature and precipitation Average biases for temperature (°C) and rainfall (mm) 5. References Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones, M. New. 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. Peckham, E., et al., 2013: WRF/Chem Version 3.5 User’s Guide Wolfe, G.M. et al., 2015: Formaldehyde production from isoprene oxidation across NOx regimes b) Correlation between model and station gas concentrations Scatter plot of model and station daily O3 values over 2008 (rural background st.) CBMZ v. RADM2 O3 [μg/m3] in Rural stations Acknowledgement This work is supported by the project GAUK No. 115-10/227184. Authors wish to express their thanks to WRF team community for their development of the model WRF and chemistry modules used in the study. Further, our thanks go to the ECA&D team for E-OBS gridded data and European Environment Agency for AirBase data used for validation and result analysis. Authors also thanks to MACC organisation for TNO emission data, and also to NCAR for MOZART-4/GEOS-5 and Biomass Burning emission data, which are all used in model simulations.