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DMI Modeling Systems And Plans For CEEH Activities

C. Energy Environment Health. DMI Modeling Systems And Plans For CEEH Activities. Gross, A. Baklanov, U. S. Korsholm, J. H. Sørensen, A. Mahura & A. Rasmussen. Content:. Off-Line Air Pollution Modeling On-Line Air Pollution Modeling

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DMI Modeling Systems And Plans For CEEH Activities

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  1. C Energy Environment Health DMI Modeling Systems And Plans For CEEH Activities • Gross, A. Baklanov, U. S. Korsholm, • J. H. Sørensen, A. Mahura & A. Rasmussen Content: • Off-Line Air Pollution Modeling • On-Line Air Pollution Modeling • Emergency Preparednes & Risk • Assessment • Urban Modeling Kick-off. d. 23-25/1 2007

  2. C Energy Environment Health Chemical Solvers Aerosol Module UTLS Trans. Models Air Pollution Modeling At DMI • PSC aerosols • Tropospheric • aerosols • Approaches: • Normal distribution, • Bin approach • Physics: • Condensation • Evaporation • Emission • Nucleation • Deposition • Gas Phase • Aqueous phase • Chemical equil. • Climate Modeling • Approaches: • RACM, CBIV, • ISORROPIA Lagrangian transport, 3-D regional scale Eulerian trans- port 0..15 lat-lon grid, 3-D regional scale ECMWF DMI-HIRLAM Met. Models Eulerian trans- port 0.2-0.05 lat-lon, 25-40 vert. layer, 3-D regional scale Stochastic Lagrangian transport, 3-D regional scale Tropo. Trans. Models City-Scale Obstacle Resolved Modelling TSU-CORM Emergency Pre- parednes & Risk Assess- ment. DERMA Off-Line Chemical Aerosol Trans. CAC On-Line Chemical Aerosol Trans. ENVIRO-HIRLAM Regional (European) scale air pollution: smog and ozone, pollen. Nuclear, veterinary and chemical. Regional (European) to city scale air pollution: smog and ozone.

  3. C Energy Environment Health • Currently nested versions of HIRLAM: • T – 15x15 km2, 40 vertical layers. • S – 5x5 km2, 40 vertical layers. • Q – 5x5 km2, 40 vertical layers. • Test version of 1.5x1.5 km2 of DK. DMI-HIRLAM Q A forecast integration starts out by assimilation of meteorological observations whereby a 3-d state of the atmosphere is produced, which as well as possible is in accordance with the observations. S T A numerical weather prediction system consists of pre-processing, climate file generation, data-assimilation and analysis, initialization, forecast, post-processing and verification.

  4. C Energy Environment Health Modeling Area Simulation period: Year 2000 to 2100 Climate Change Scanarios Modeling By HIRHAM • Horizontal resolution 25x25 km2. • Vertical resolution 19 levels. Output of meteorological parameter: From 3-6 hours to once a day depend on the parameter.

  5. C Energy Environment Health Off-Line modelling with CAC T:0.15º×0.15º Simulation domain Horizontal resolution 0.2º×0.2º. S: 0.05º×0.05º CAC Model Area

  6. C Energy Environment Health ENSEMBLE JRC project exp. nr. 11 (Off-Line)

  7. Ensemble: DK3, DE1, FR2, CA2

  8. Ozone C Energy Environment Health 36 hour forecast 48 hour forecast ppbV 0 15 30 60 90 120 150 “Semi”-operational forecasts 4 times a day of O3, NO, NO2, CO, SO2, Rn, Pb, “PM2.5”, “PM10”. (Off-Line)

  9. On-line coupling Only one grid; No interpolation in space No time interpolation Physical parameterizations are the same; No inconsistencies Possibility of feedbacks bewte-en air pollution and meteoro-logy All 3D met. variables are ava-ilable at the right time (each time step); No restriction in variability of met. fields Does not need meteo- pre/postpro-cessors Off-line Possibility of independent parame-terizations Low computational cost; More suitable for ensembles and oprational activities Independence of atmospheric pol-lution model runs on meteorolo-gical model computations More flexible grid construction and generation for ACT models C Energy Environment Health Advantages of On-line & Off-line modeling

  10. C Energy Environment Health Examples of feedbacks

  11. C Energy Environment Health On-Line Modeling With ENVIRO-HIRLAM U, V, W, T, q, U*, L Emission Transport Dispersion Clouds Precipitation Radiation DMI-HIRLAM Gas phase chemistry Aerosol chemistry Aerosol physics Deposition Concentration/Mixing ratio

  12. C Energy Environment Health Chernobyl Simulation 0.15°x0.15°, d. 7/5-1986, 18.00 UTC Dry deposition (kBq/m2) Total deposition statistics: Corr = 0.59, NMSE 6.3

  13. Difference (ref – perturbation) in Accumulated dry deposition [ng/m2] Accumulated (reference) dry deposition [μg/m2] +48 h

  14. C Energy Environment Health Emergency Preparednes & Risk Assessment Using the 3-D Stochastic Lagragian Regional Scale Model DERMA Examples: • Probabilistic Risk Assessment. • Source Determination by Inverse Modelling. • Chemical Emergency Preparednes. • Urban Meteorology Effects.

  15. C Energy Environment Health Probabilistic Risk Assessment Risk atlas of potential threats from long-range atmospheric dispersion and deposition of radionuclides. Sellafield nuclear fuel reprocessing plant Yearly deposition Yearly time-integrated concentration

  16. C Energy Environment Health Source Determination by Inverse Modelling Hypothetical release of 100 g Anthrax spores Determination of source location by adjoint DERMA using monitoring data. No a priori assumption about source (point, area, …). Inhalation dose calculated by DERMA based on DMI-HIRLAM. Monitoring stations

  17. C Energy Environment Health Aalborg Portland, 23 October 2005 Accidental fire in waste deposit Accidental fire in waste deposit.

  18. C Energy Environment Health Aalborg Portland, 23 October 2005 Accidental fire in waste depositDERMA calculations

  19. Wake diffu-sion Radiation Drag C Energy Environment Health Wall Roof Momentum Turbu-lence Heat Street Urban Features

  20. C Energy Environment Health Urban Effects The ABL height calculated from different DMI-HIRLAM data (left: urbanized, right: operational T). Main cities and their effect on the ABL height are shown by arrows.

  21. C Energy Environment Health Urban Effects Local-scale RIMPUFF plume corresponding to a hypothetical release calculated by using DMI-HIRLAM data. Cs-137 air concentration for different DMI-HIRLAM versions(left: urbanized 1.4-km resolution, mid: operational 5 km, right: operational 15 km).

  22. C Energy Environment Health Streamlines and air pollution conc City-Scale Obstacle-Resolved Modeling (TSU-CORM) 3 d. fluid dynamic air pollution model Resolution: Horizontal: 1x1 m2 Vertical: from 1m Will be implemented spring 2007 at DMI and linked with DMI-HIRLAM, CAC and /or ENVIRO-HIRLAM.

  23. C Energy Environment Health DMIs Possible Modeling Activities In CEEH Modeling of the environmental impact of energy production/consumption • Long-term simulations: • ENVIRO-HIRLAM and/or CAC. • Episodes: • ENVIRO-HIRLAM. Climate change impact on air pollution and population health • Long-term simulation of ENVIRO- HIRLAM and/or CAC using HIRHAM Meteorology. Kick-off. d. 23-25/1 2007

  24. C Energy Environment Health DMIs Possible Modeling Activities In CEEH Optimization modeling of environmental risk/impact studies • Modify DERMA or CAC for sensitivi- ty, risk/impact minimization and optimization studies. • Sensitivity studies for environmen- tal risk/impact assessments. Human exposure modeling • City scale modeling using TSU- CORM. • Link the air pollution prediction from ENVIRO-HIRLAM or CAC to population activity (human expo- sure modeling). Kick-off. d. 23-25/1 2007

  25. C Energy Environment Health FUMAPEX integrated population health impact study © Helsingin kaupunki, Kaupunginmittausosasto 576§/1997, ©Aineistot: Espoon, Helsingin, Kauniaisten ja Vantaan mittausosastot The predicted exposure of population to NO2 (g/m3 *persons). Environmental Office

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