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URBAN POLLUTION MODELING IN WINTER – JAPAN EXPERIENCE Toshimasa Ohara (Shizuoka University)

URBAN POLLUTION MODELING IN WINTER – JAPAN EXPERIENCE Toshimasa Ohara (Shizuoka University) Yuki Otsuka (Shizuoka University) Seiji Sugata (National Inst. for Environ. Studies)

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URBAN POLLUTION MODELING IN WINTER – JAPAN EXPERIENCE Toshimasa Ohara (Shizuoka University)

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  1. URBAN POLLUTION MODELING IN WINTER – JAPAN EXPERIENCE Toshimasa Ohara (Shizuoka University) Yuki Otsuka (Shizuoka University) Seiji Sugata (National Inst. for Environ. Studies) Tatsuko Morikawa (Petroleum Energy Center )

  2. Trends of air quality in Tokyo Significant improvement Small improvement Background High wintertime concentrations of aerosol particles are serious atmospheric environment problem in Japan, especially in the Tokyo Metropolitan Area (TMA). In the past three decades, the urban air pollution in Japan has gradually improved due to a series of emission control. Still however, the TMA experiences unacceptable air quality with high levels of particle matter during winter.

  3. Objectives ●To clarify the mechanism of urban pollution formation in the TMA, an intensive field study was conducted in December 1999 covering the TMA by the Japan Clean Air Program (JCAP)*. These observations were successful in detecting typical episodes of urban pollution in the TMA during winter. * Japan Clean Air Program (JCAP), which was launched in 1997 by the Petroleum Energy Center, in collaboration with automobile and oil industries in Japan. ●This presentation focused on the current application results of regional three-dimensional model to the JCAP field campaign in December 1999 in order to analyze the formation mechanism of the heavy air pollution of the aerosol particles and those precursors in winter in the TMA.

  4. Characteristics of urban pollution in the TMA • Complicated meteorology by terrain complexitiesThe terrain complexities generate complex local wind circulation such as land/sea and mountain/valley flows, and these wind circulation system play a significant role for the urban air quality. • Trans-boundary pollution The trans-boundary pollution from Asian countries influence urban pollution. • Major emission is automobile Major emission source is related in automobiles likewise in many mega-cities in the world.

  5. Characteristic of the urban pollution in the TMA (1) The terrain complexities generate complex local wind circulation such as land/sea and mountain/valley flows, and these wind circulation system play a significant role for the urban air quality. Meso-front Strong inversion layer Mizuno and Kondo, 1992 Calm Tsukuba Kanto Plain Meso-front Tokyo Topography around the TMA Ohara and Uno, 1997

  6. Characteristic of the urban pollution in the TMA (2) The trans-boundary pollution from Asian countries influence urban pollution. Ammonium Nitrate EC OC Annual spatial distribution for surface sulfate (μg/m3) Average surface aerosols in spring, 2001

  7. Characteristic of the urban pollution in the TMA (3) Major source is the automotive emission likewise in many mega-cities in the world. Line sources from automobile emissions Contribution of emissions related in automobiles Emission map around the TMA

  8. 2. JCAP field campaign in winter, 1999

  9. Surface observations Upper Observations Overview of observations To clarify the mechanism of urban pollution formation in the TMA, an intensive field study, including aircraft flights and continuous surface measurements of aerosol mass at 18 sites, was conducted in December 1999 covering the TMA by the JCAP. Intensive study days: 7 to 11, December

  10. Time variations for surface NO2 0600 JST 1200 JST 1800 JST 1500 JST 0900 JST 2100 JST Two typical pattern of severe pollution (a) Meso-front type Northern part of the front ・ Stagnation and inversion layer ・ Heavy pollution . Southern part of the front ・ Strong wind ・ Clean (b) Wide stagnation type Over the wide area of TMA ・ Weak wind ・ Heavy pollution 09 December, 1999 (a) Meso-front type Meso-front 10 December, 1999 (b) Wide stagnation type

  11. F F O O K K Y Y Typical heavy pollution episodes (a) Meso-front type airflow SPM Aerosol composition 1800 JST 9 Dec., 1999 Polluted Clean Meso-front Y K O1 O2 F (b) Wide stagnation type South Front North airflow SPM 2100 JST 10 Dec., 1999 Aerosol composition Calm Y K O1 O2 F Heavy pollution in the wide area 75 m height

  12. 3. Model and simulation conditions

  13. To simulate the urban pollution in the TMA • (1) Complicated meteorology by terrain complexities • Coupled modelof RAMS and CMAQ with horizontal and vertical nesting • (2) Trans-boundary pollution • Three nested grids ( East Asia + Japanese Island + TMA ) • (3) Major emission is automobile • Emission inventory for automobile source developed by the • JCAP

  14. ModelDomains East Asia (Grid1) Central Japan (Gird2) Kanto Plain (Grid3) Height above S.L. (m) ＴＭＡ < Number of grid points > 66(x)×58(y)×20(z) 50(x)×50(y)×20(z) 40(x)×50(y)×26(z) < Horizontal grid interval > 44.8 km (x, y) 11.2 km (x, y) 5.6 km (x, y) < Depth of 1st layer > 100 m 100 m 20 m Top of vertical level : 10 km Simulation period : December 6 to 11, 1999 Evaluation area ：Tokyo Metropolitan Area (TMA)

  15. Simulation model Regional Met. Model (CSU-RAMS 4.3) ECMWF Met. data FDDA Input Parameters（SST, Topography ・・） 3-D High Frequency Met. Data Set Emission Data NOx, SO2, CO, NH3, EC, OC,NMVOC (including biogenic) Chemical Transport Model (CMAQ) Grid 1: Carmichael & Streets (2001) etc. Grid 2, 3 : JCAP Boundary Concentrations Initial Concentrations Gases, Aerosols

  16. Description of meteorological model CSU-RAMS Ver.4.3 （Colorado State University - Regional Atmospheric Modeling System) ・ Map projection: Polar-stereographic ・ Vertical coordinate system: σz terrain-following ・ Non-hydrostatic ・ Cloud: Kuo-type scheme ・ Surface layer: Louis scheme ・ Vertical diffusivity: Mellor & Yamada scheme (2.5level) ・ Four-dimensional data assimilation: ECMWF Data Sets (Analysis, Lon.-Lat.=0.5deg, Δt=6 hours) ・ Two-way nesting

  17. Description of Chemical Transport Model Models-3/CMAQ（Models-3 Community Multiscale Air Quality) developed by Byun and Ching (1999) of U.S. EPA ・Advection with piece-wise parabolic method (PPM) ・Vertical diffusion with K-theory parameterization ・Deposition flux as bottom boundary condition for the vertical diffusion ・Mass conservation adjustment scheme ・Horizontal diffusion with scale dependent diffusivity ・Carbon Bond 4 (CB-4) chemistry mechanism with isoprene chemistry ・QSSA gas-phase reaction solver ・Emissions injected in the vertical diffusion module ・Aqueous-phase reactions and convective cloud mixing ・Modal approach aerosol size distribution and dynamics ・One-way nesting

  18. Aerosol species in Models-3/CMAQ 16 components ASO4J Sulfate (Accumulation mode) ASO4I (Aitken mode) ANH4J Ammonium (Accumulation mode) ANH4I (Aitken mode) ANO3J Nitrate (Accumulation mode) ANO3I (Aitken mode) AORGAJ Anthropogenic secondary organic (Accumulation mode) AORGAI (Aitken mode) AORGPAJ Primary organic (Accumulation mode) AORGPAI (Aitken mode mode) AORGBJ Secondary biogenic organic (Accumulation mode) AORGBI (Aitken mode) AECJ Elemental carbon (Accumulation mode) AECI (Aitken mode) A25J Unspecified anthropogenic mass (Accumulation mode) A25I (Aitken mode)

  19. 4. Results and discussion 4-1 Comparison with observations 4-2 Vertical SPM structure 4-3 Aerosol composition 4-4 OC formation processes

  20. Comparison with observations (Meteorological fields) ○：Observation 　　 ：model 12/9 1800 JST 12/10 2100 JST Meso-front Calm Calm Thin regularly spaced: model Thicker: observation RAMS with the data nudging using ECMWF reanalysis data set could reproduce well the meteorological fields in the TMA through the field campaign. However, it was difficult to simulate exactly the wind field, for example, the location of meso-front and the strong stagnant air condition.

  21. Comparison with observations (Air quality) CMAQ with RAMS could reproduce reasonably well the temporal variations of the observed concentrations of the aerosol particles and their precursor gases.

  22. Comparison with observations (SPM distribution) 2000 JST 10 Dec. 1800 JST 9 Dec. Observation Model Observation Model (1) CMAQ with RAMS could reproduce reasonably well the observed spatial distribution. (2) However, the model failed to simulate accurately the high concentration area and also the simulated concentration tends to be low. This situation may be explained by ・ Lack of reproduction of the meteorological field simulated by the RAMS ・ Underestimation of anthropogenic emissions (3) Especially, it was very important to reproduce the details of meteorological fields by a meteorological model.

  23. Comparison with observations (Average particle composition for two-day period) South（sea） North(inland) Observation Model ・ The model can calculate only the fine particles, sulfate, nitrate, ammonium, EC, and OC. ・ For five fine components, modeled compositions are almost similar to observations. ・ Model tends to underestimate the observed concentrations for components except EC. ・ Contribution of EC and OC to the total particles is very high.

  24. Spatial distribution of SPM (a) Meso-front type Horizontal (surface) N-S vertical section along the line L 1800 JST 9 Dec. Modeled meso-front Modeled meso-front Polluted air mass < horizontal > 50 km < vertical > 250 m Very shallow by the surface inversion layer. Flight observation: below 300 m Clean Polluted South（Sea） North（Inland） L1 (b) Wide stagnation type 2000 JST 10 Dec. Polluted air mass < horizontal > 100 km < vertical > 900 m Flight observation: below 900 m L2 North（Inland） South（Sea） Modeled depth of vertical polluted layer accorded with the flight observations.

  25. Average fine particle composition (for two-day period) EC (%) OC (%) NO3- (%) SO4 2- (%) NH4+ (%) 34% 16.1% 19.6% 18.2% 12.0% 9.1% 6.4% 17.8% 49.3% 15.9% Surface Average in a whole domain Column(below 2000 m height) (1) Percentage of Carbonaceous particles (EC+OC) is 50% at surface. They mainly caused by the primary fine particles emitted from automobiles in the TMA. (2) NO3- and NH4+ percentages around the TMA is higher than that in the TMA.

  26. Average composition of fine particles at surface in the TMA (for two-day period) (1) Modeled composition is agreement with the observations except the ratio of EC and OC. (2) At surface, the total carbonaceous particles content (EC+OC) reaches to 66%. (3) At aloft, the contributions of carbonaceous particles decrease with the altitude because the effect of surface emissions is smaller; instead, the contribution for NO3- and SO42- increase because they are secondary particles.

  27. Average OC components (for two-day period) Primary OC Anthropogenic Secondary OC Biogenic Secondary OC (POC) (ASOC) (BSOC) OC μg/m3 TMA At surface, <Primary OC> 80% <Anthropogenic secondary OC> Small fraction (almost 5%) <Biogenic secondary OC>Higher in the mountainous area; 15% ; important component of OC in this area despite the low reactivity in winter.

  28. Conclusions • RAMS can reproduce qualitatively the meteorological fields. However, it is difficult to simulate the exact wind field, for example, the location of meso-front and the strong stagnation. • CMAQ with RAMS can reproduce reasonably well the particles and gases. However, the model fails to simulate accurately the high concentration because of lack of RAMS performance. • The local wind systems play an important role in controlling the formation of heavy particle pollution. Particularly important factors are the meso-front and the strong stagnant air condition. • The urban aerosol particles near surface in the TMA are dominated by EC and primary OC. • The secondary biogenic organic carbon is an important OC component despite the low reactivity in winter.

  29. Next steps Improvement of model performance Important tasks are To reproduce the details of meteorological field by a meso-scale meteorological model. To improve the emission inventory, especially for carbonaceous particles from automobiles. To estimate uncalculated particles, for example, chloride and coarse particles. Sharing lots of results and experiences of urban modeling in many cities over the world in order to improve the urban air quality

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