Influence of Biomass Burning and Mid-latitude Pollution on the Arctic Atmosphere during the ARCTAS Field Campaign: A Three Dimensional Modeling Analysis Sarika Kulkarni1, Bhupesh Adhikary1, Alessio D’Allura2, Chao Wei1, Gregory R. Carmichael1,Youhua Tang3, David Streets4,Qiang Zhang4, Robert B. Pierce5, Jassim A. Al-Saadi5 , Jack E. Dibb6, Andrew J Weinheimer7, Glenn S Diskin5, Rodney J Weber8, Jose-Luis Jimenez9, and Yutaka Kondo10 1Center for Global and Regional Environmental Research, University of Iowa, Iowa City, 2ARIANET Srl ,Milano, ITALY, 3Meso-scale modeling, NOAA/NCEP/EMC, W/NP2, NOAA, Camp Springs, MD, 4Argonne National Laboratory, IL, 5NASA Langley Research Center,Hampton,VA,6 The University of New Hampshire, Durham, NH, 7NCAR, Boulder, CO, 8Georgia Institute of Technology, Atlanta, GA, 9The University of Colorado, Boulder, CO,10The University of Tokyo, Japan Introduction Research Design Chemical Forecasts in Support of Flight Planning Modeling Description The Arctic Research on the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaign took place during the spring (April 1-21) and summer (June 26-July 12) of 2008. The major objectives of this mission were to study the long range transport pathways of pollution (spring phase) to the Arctic and assess the impact of biomass burning (summer phase) on the Arctic atmosphere. Multiple observations platforms including satellites, aircrafts, and surface stations were deployed during the mission to understand the chemistry and composition of the Arctic atmosphere. The University of Iowa’s Sulfur Transport and dEpostion model (STEM), a comprehensive 3-dimensional regional scale model, provided high resolution chemical weather forecasts to support the intensive aircraft measurements. It is now being used in post analysis to assist in interpreting the observations. Meteorological Output from WRF model Meteorological Preprocessor STEM Model Normal meteorological variables: wind velocities, temperature, pressure, water vapor content, cloud water content, rain water content etc. Dust and Sea Salt emissions Emission Preprocessor Volcanic SO2 Emissions Anthropogenic Area Emissions Large Point Sources Post Analysis Top and Lateral Boundary condition and Biomass Burning Emissions from RAQMS global model Data Flow Chart of U. of Iowa Regional Chemical Transport Model, STEM (Sulfur Transport and dEposition Model) Meteorology model: WRF 60 km x 60 km, GFS Forecast data Model run for two periods : from April 1 to April 30 2008 and June 18 to July 14, 2008 6hr output Dry Deposition: ‘Resistance in Series Parameterization’ for gases and aerosols. Sulfate aerosol calculated, other aerosols scaled to sulfate Wet Scavenging: Precipitation Scavenging for Sulfate calculated, Other aerosols scaled to Sulfate. Hydrophilic and hydrophobic BC emitted. BC conversion using a first order rate constant of 39 hours. Fossil Fuel Emissions: New ARCTAS 2008 Emissions, 2001 NEI emissions for USA. Dust Emissions: Based on the work of Uno et al. (2003). Sea Salt Emissions: Based on the work of S. L. Gong (2003). Biomass Burning Emissions from RAQMS Global model forecast. 2008 ARCTAS Emissions Inventory ARCTAS Spring and Summer Phase DC-8 flights This is a composite data set of global emissions developed by David Streets and Qiang Zhang (Argonne National Laboratory), with the help of Mian Chin (NASA/GSFC), Louisa Emmons (NCAR), and Zig Klimont and Janusz Cofala (IIASA). The latest data available was included so that the most current emissions can be represented. The main objective of this emissions inventory is to support the ARCTAS pre-mission planning. Further details on this emissions can be found at http://www.cgrer.uiowa.edu/arctas/emission.html. For any question please contact : David Streets dstreets@anl.gov; and Qiang Zhang zhangq@anl.gov. The DC8 flight tracks for Spring and Summer phase of the ARCTAS mission are shown here. We have selected two DC8 flights that represent the spring (flight 9) and summer (flight 19) phases of the mission. Illustrative model results are discussed below for these two DC8 flights. Preliminary results of STEM model data comparison with DC8 observations The DC8 flight 9 was a sortie from Fairbanks. The main objectives of this flight were to sample the major Asian biomass burning plumes and Arctic Haze in the troposphere. The calculated five day back trajectories along this flight track show that the air masses are primarily coming from Asia. The model comparison with some selected meteorological observations suggests that the WRF model is able to capture the important features. The modeled BC and biomass CO tracer capture the trend seen in the observed BC and HCN (biomass tracer). The model is able to capture the magnitude of BC aerosol. The model sulfate also compares well with the observed values but misses the peaks. The biomass burning emissions used during the model forecasting period were three days behind. The preliminary results from the post analysis run, which used the updated biomass burning emissions, are shown in the HCN comparison plot. The post analysis biomass CO tracer matches the observed HCN better than the forecast run biomass CO. DC 8 flight 9 Meteorological variables DC 8 flight 9 Aerosols and Chemistry DC 8 flight 19 Meteorological variables The DC8 flight 9 was sortie from Cold Lake. The main objectives of this flight were to investigate the Canadian fire emissions and smoke transport. The calculated five day back trajectories along this flight track show that the air masses are coming mostly from the northwest. The WRF meteorological variables compare well with observations. The model does well in capturing the trend of observed Ozone but overpredicts the peak ozone values. The modeled absorbance at 530 nm also shows similar behavior and misses the peaks. The biomass CO tracer does not capture the features of observed HCN as the biomass burning emissions used in the model forecasting period were three days behind. DC 8 flight 19 Aerosols and Chemistry Summary and Ongoing/Future Work The WRF meteorological model in forecasting mode performs satisfactorily throughout the ARCTAS mission. Evaluate and constrain the model further with observations from other DC-8 and P3 flights. Perform full chemistry model runs with updated biomass burning emission inventory to study the influence of boreal/biomass burning plumes. Evaluate STEM full chemistry model performance for ozone and other photochemistry dependent species. Perform sensitivity analysis to assist interpretation of observations, understand the source-receptor relationships of pollutants in the Arctic. Acknowledgements ARCTAS Measurement Team Funding from NASA CGRER The University of Iowa Author Contact 431 IATL, CGRER, The University of Iowa, IA, 52242. Email : sarika-kulkarni@uiowa.edu