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대기질 및 배출 모델링 Air Quality and Emission Modeling

대기질 및 배출 모델링 Air Quality and Emission Modeling. 2000/8/15 황령산에서 바라본 연제 / 동래 일대. 2002.4. 김 동 영. Outline.  Air Quality Management Process Air Quality Management Cycle Roles of Air Quality Model  Air Quality Modeling Evolution of Air Quality Modeling System

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대기질 및 배출 모델링 Air Quality and Emission Modeling

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  1. 대기질 및 배출 모델링Air Quality and Emission Modeling 2000/8/15 황령산에서 바라본 연제/동래 일대 2002.4 김 동 영

  2. Outline  Air Quality Management Process Air Quality Management Cycle Roles of Air Quality Model  Air Quality Modeling Evolution of Air Quality Modeling System USEPA’s Third-Generation “One-Atmosphere” Modeling Tool: Models-3/CMAQ System Applications of Models-3/CMAQ System  Air Pollutant Emission Modeling Methodology of Emission Estimation Emission Inventory Database and Emission Modeling Applications

  3. Air Quality Management Process

  4. Air Quality Management Cycle Establish Goals What Reductions Are Necessary? ⇒ Science(Criteria) ⇒ Law(NAAQS) ⇒ Monitoring ⇒ Inventories ⇒ Modeling ⇒ Risk and Econ. Analysis Evalualte Results How to Achive ⇒ Monitoring ⇒ Modeling ⇒ National Rules & Programs ⇒ States Plan Implement ⇒ States & Local Rules ⇒ Permits ⇒ Compliance & Enforcement

  5. Air Quality Management Process under CAA/NAAQS(U.S) Air Quality Monitoring Rulemaking & Implementation Air Quality Modeling Assement Emission Inventory Control Strategy & Risk Assessment Cost/Benefit analysis & Optimizaiton

  6. 대기오염관리와 대기질모델링Schematic Diagram of Air Quality Management Goal (Ozone, Acid rain, ...) $ Policy Decision Control Strategy Evaluation Modeling Performance Evaluation MODLEING MONITORING Emission - Meteorology - Chemistry - Deposition

  7. Components of a Modeling Systemfor Air Quality Management Emissions input data Meteorological input data Emission Model Meteorological Model Emission Changes Air Quality Model Decision Support System Socio- Economic Factors Air quality input data Decision support input data Dong Young Kim

  8. Air Quality Modeling

  9. Roles of Air Quality Models • Research tool • Understanding of pollution formation process • Regulatory tool Current AQ Assessment & future AQ projection Control strategy development • Required by Law in the U.S Clean Air Act Amendments (CAAA) of 1990 U.S. EPA’s Regulatory Models

  10. Air Qaulity Management - The Tool :Mathematical Modeling Physical model : small scale, lab. presentations of the phenomena (wind tunnel, water tank ...) Mathmatical model : a set of anlytical/numerical algorthms that describe the physical and chemical aspects of the problem Deterministic models based on the fundamental mathematical descriptions of atmpospheric precesses, in which effects(i.e., air pollution) area generated by cause(i. e., emission) Statistical models based upon semiemperical statistical relations among available data and measurements Eulerian model Laglangian model Gaussian model Dong Young Kim

  11. Dimensions of Atmospheric Dynamics A. Henderson-Sellers, KMcGuffie A Climate Modeling Primer, John Wiley & Sons, 1987 p. 2 Dong Young Kim

  12. Temporal and Spatial Scale of Chemical Lifetime and Transport minite day month week 3 month hour year 10-3 10-2 10-1 100 101 102 103 104 105 106 107 108 109 Lifetime(sec) 10-2 10-1 10-0 101 102 103 104 105 106 107 108 109 1010 HONO OH HO2 Photostationary state NO3 NO2 NO PAN O3 Methanol CO Acetone Benzene Isoprene Propene Acetaldehyde Methane SO2 troposphere H2O2 Transport(m) (Advection at 4m/s) Robin L. Dennis, Daewon W. Byun, Joan H. Novak, Kenneth J. Galluppi, Carlie J. Coats, The next generation of integrated air quality modeling: EPA's Models-3, Atmos. Environ. 30(12): 1925-1938(196) Dong Young Kim

  13. Scale of Known Meteorological Phenomena VII. -plane approximation VI. neglecting the Coliolis force V. quasi-geostrophic assumption IV. hydrostatic assumption III. incompressible assumption II. anelastic assumption I. Navier-Stokes Eqa. meso-  meso- micro- micro-  micro- meso- macro LONG WAVES Rossby waves baroclinic waves SYNOPTIC WEATHER fronts hurricanes Power spectrum of horizontal wind speed cloud clusters inertial waves sec low level jet 100 101 102 103 104 105 106 107 108 squall line deep convection thunderstorms short gravity waves GRAVITY WAVES SMALL SCALE TURBULENCE tornados plumes dust devils SOUND WAVES 100 101 102 103 104 105 106 107 108 m Robin L. Dennis, Daewon W. Byun, Joan H. Novak, Kenneth J. Galluppi, Carlie J. Coats, The next generation of integrated air quality modeling: EPA's Models-3, Atmos. Environ. 30(12): 1925-1938(196) Dong Young Kim

  14. AtmosphericDynamics A. Henderson-Sellers, KMcGuffie A Climate Modeling Primer, John Wiley & Sons, 1987 p. 135 Dong Young Kim

  15. Governing Equation of Air Quality Dynamics A. Henderson-Sellers, KMcGuffie A Climate Modeling Primer, John Wiley & Sons, 1987 p. 135 Dong Young Kim

  16. Air Quality Diffusion Equation : Conservation of mass Source & Sink Rxns Advection Diffusion C : Concentration(ML-3) t : Time(T) u, v, w : Wind vector(LT-1) Ex, Ey, Ez : Diffusion coefficient vector(L2T-1) R : Reaction rate(ML-3T-1) S : Source and sink(ML-3T-1) (emission and deposition) Dong Young Kim

  17. MM5The Fifth-Generation NCAR/Penn State Mesoscale Model • Prognostic vs Diagnostic • GCM and … http://www.mmm.ucar.edu/mm5/ Dong Young Kim

  18. CSU RAMSColorado State University Regional Atmospheric Modeling System http://rams.atmos.colostate.edu/ Dong Young Kim

  19. Evolution of Air Quality Models • 1st-generation AQM (1970s - 1980s) Dispersion Models (e.g., Gaussian Plume Models-ISC) Photochemical Box Models (e.g. OZIP/EKMA) • 2nd-generation AQM (1980s - 1990s) Photochemical Grid Models (e.g., UAM, RADM) • 3rd-generation AQM (1990s - 2000s) Community-Based ‘One-Atmosphere’ Modeling System (e.g., U.S. EPA’s Models-3/CMAQ)

  20. First-GenerationAir Quality Models Gaussian Dispersion Model ISC3, CALPUFF, AERMOD (for primary pollutants) Photochemical Box Model OZIP/EKMA (for ozone)

  21. 2nd-GenerationAir Quality Models Eulerian Grid Models UAM, RADM, REMSAD, ROM

  22. 3-D Modeling Scheme Grid sheme and treatment of atmospheric processs of UAM U. S. EPA, User’s guide for the Urban Airshed Model(CB-IV), EPA-50/4-90-007A, 1990 Dong Young Kim

  23. 3-D Modeling Scheme A. Henderson-Sellers, KMcGuffie A Climate Modeling Primer, John Wiley & Sons, 1987 p. 138 Dong Young Kim

  24. Examples of 2nd-Generation Air Quality Models UAM Photochemical Grid Models

  25. Modeling Atmospheric ChemistryCBM-IV, RADM2 CBM-IV Carbon Bond Mecanism, Version 4 Gas phase chemisrty for Ozone Lumped approach (23 species, 80 rxn eq.) RADM2 Regional Acid Deposition Model Multi-phase chemistry Explicit approach

  26. Third-Generation Air Quality Models:U.S.EPA’s Models-3/CMAQ “Open-Access” Community-Based Models : User-friendly, Modular, Common modeling framework for scientists and policy-makers. Advanced Computer Technologies : High performance hardware and software technologies (Cross-platform, GUI, distributed computing, visualization tools, etc.). “One-Atmosphere” Modeling : Multi-pollutant (Ozone, PM, visibility, acid deposition, air toxics, etc.) Multi-scale.

  27. One-Atmosphere Modeling: Models-3/CMAQ Mobile Sources Ozone NOx, VOC, PM, Toxics (Cars, trucks, planes, boats, etc.) PM Industrial Sources Acid Rain Chemistry Meteorology NOx, VOC, SOx, PM, Toxics Visibility (Power plants, refineries/ chemical plants, etc.) Air Toxics Atmospheric Deposition Area Sources Climate Change NOx, VOC, PM, Toxics (Residential, farming commercial, biogenic, etc.)

  28. Smog = Ozone + PM(fine)

  29. NOx-Related Air Quality Issues (NO3-, NH4+) PM (NOx + VOC + hv) --> Ozone NOx Acid Rain (NO3- deposition) Visibility (Fine PM) Water Quality (Nitrogen deposition, Lake Acidification)

  30. SOx-Related Air Quality Issues (SO42-, NH4+) PM (Fine PM) Visibility SOx Acid Rain (SO42-deposition) Water Quality (Lake acidification, Toxics deposition)

  31. .OHRole in Pollutants Formation : One-Atmosphere PM2.5 SOx [or NOx] + NH3 + OH ---> (NH4)2SO4 [or NH4NO3] VOC + OH ---> Orgainic PM One Atmosphere Ozone One Atmosphere Visibility Fine PM (Nitrate, Sulfate, Organic PM) .OH NOx + VOC + OH + hv ---> O3 Acid Rain Water Quality SO2 + OH ---> H2SO4 NOx + SOx + OH (Lake Acidification, Eutrophication) NO2 + OH ---> HNO3 OH <---> Air Toxics (POM, PAH, Hg(II), etc.) Air Toxics

  32. Models-3/CMAQ Technology Transfer & Applications Models-3/CMAQ Release (annual since 1998) Version : Cray Supercomputer and Unix Workstations PCs (Linux OS): recommended Technology Transfer & User Support Help Desk & Model-3 User E-mail List Server Training & User Workshop CMAS Modeling Support Center http://www.epa.gov/asmdnerl/models3/

  33. Models-3/CMAQ System Framework or RAMS Meteorology Processor or SMOKE Emission Processor Air Quality Model PAVE

  34. Science Process Components in Models-3/CMAQ (Courtesy of Daewon Byun, USEPA/ORD)

  35. Science Modules Flow Charts in Models-3/CMAQ (Courtesy of Daewon Byun, USEPA/ORD)

  36. U. S. EPA, Models-3 conceptsAdaptability

  37. Models-3/CMAQ Demo Simulation :PM 2.5 Fine PM Species (PM2.5) Sulfate, Nitrate, Ammonium, Secondary anthropogenic & biogenic organics, Primary elementary carbon, Unspeciated primary aerosols Coarse PM Species (PM10) Fugitive dust Sea salt Unspeciated anthropogenic aerosols

  38. Models-3/CMAQ Demo Simulation :Visibility Visual Range Parameters: Deciview (dv) : dV = 10 ln (b / 0.01), b [km-1] : extinction coeff. Koschmieder Visual Range : Vr = 3.91 / b [km] dV Vr [km] b [km-1] 60 1.0 4.0 40 7.2 0.55 20 53 0.07 10 144 0.03 0 391 0.01

  39. Models-3 Future CMAQ CMAS MIMS • Community Multiscale • Air Quality (CMAQ) • Modeling System : • First release 07/1998; • Recent release 06/2001; • Ready to use for O3, PM, • visibility, acid rain; • Currently undergoing • PM evaluation and • air toxics development; • Community Modeling • and Analysis System • (CMAS) : • Year 2001 - 2004 plan : • Outreach to user community • Provide support to users • through Training & Support • Center • Hold Models-3 training • and workshop • Multi-Media • Integrated Modeling • System (MIMS): • Year 2000 - 2008 plan : • Include Multi-media and • cross-media pollutants; • Common framework for • airshed and watershed • modeling;

  40. Schematic Diagram of Multi-Media Environmental Modeling Dong Young Kim

  41. Dry Deposition Modeling F = -vdC 1/vd = rt = ra + rb + rc F : the vertical dry deposition flux(M/L2) vd : the deposition velocity(L/T) C : the concentration of air(M/L3) Dong Young Kim

  42. Dry Deposition Sampling Deposition plate : a 13 inch greased(L-Apiezon) Mylar strip, which is mounted on to a clean PVC plate. have a sharp leading edge(to induce laminar flow). are kept pointing into the wind(to avoid reentrainment). should be covered whenever it rains or snows(used the moisture sensors for automation). Sampling time Short-term samples : 8~72 hrs Long-term samples : 1~4 weeks Dong Young Kim

  43. Arerosol Samplers polar zone Automated aerosol sampler TSP, High volumn sampler PM10, High volumn sampler Dichotonous PM sampler Dong Young Kim

  44. Deposition Velocity &Particle Size Dong Young Kim

  45. Computing Resource of NCSC Dong Young Kim

  46. Air Pollutants Emission Modeling

  47. 배출목록의 활용 • 대기질 관리 정책의 수립 및 평가 • 기존 배출원 관리 및 신규 배출원 평가 • 대기질 모형체계의 운영 • 오염 예보체계 운영 • 환경영향평가 • 측정망 설계 및 평가 • 규제 이행여부 평가 • 배출부과금 산정

  48. U.S. EPA’s NEI & AIRS • NEI(national emission inventory) • input from State and local air agencies • National Emission Trends (NET) database, Criteria pollutant emissions data (1985 ~ ) • National Toxics Inventory (NTI) database, Hazardous air pollutants emissions data (1993 ~) http://www.epa.gov/airs/

  49. AIRS Arerometric Information Retrieval System U.S. EPA’s AIRS GCS Geo-common Subsystem AQS Air Quality Subsystem AMS Area/Mobile Subsystem AFS Facility Subsystem Emissions Data Compliance Data Permitting Enhancements AG Graphics http://www.epa.gov/airs/

  50. http://www.epa.gov/ttn/chief/ U.S. EPA’sCHIEF Emission Factor and Inventory Group Factor and inventory contact News & general information Report AP-42 and Other Estimation references AP-42 L&E documents(air toxics) Source classification code Emission Estimation Software Area source analysis program DESPERATE(Air toxics model) FIRE Fugitive dust emissions Inventory projection software SPECIATE PC-BEIS TANKS others National Inventory Data & Projection Ozone transport Emission trend procedure Emission Inventory Improvement Program Point source Area source Mobile source Biogenic source Data management Coding Quality assurance State/Local interaction Emission Inventory Guidance General inventory guidance Air toxics Criteria pollutants Greenhouse gas

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