Simulations of ozone over Simulations of ozone over Israel, West Bank, and JordanIsrael, West Bank, and Jordan

E. WeinrothE. Weinroth, M. Luria, A. Ben-Nun, C. Emery, J. Kaplan, M. Peleg, M. Luria, A. Ben-Nun, C. Emery, J. Kaplan, M. Pelegand Y. Mahrerand Y. Mahrer

Seagram Center for Soil and Water Sciences Faculty of AgricultureSeagram Center for Soil and Water Sciences Faculty of AgricultureThe Hebrew University Rehovot 76100 IsraelThe Hebrew University Rehovot 76100 Israel

weinroth@agri.huji.ac.ilweinroth@agri.huji.ac.il

S. KasaksehS. Kasakseh, Applied Research Institute Jerusalem, Applied Research Institute JerusalemBethlehem, West BankBethlehem, West Bank

J. Safi, Environmental Protection Research InstituteJ. Safi, Environmental Protection Research InstituteGaza City, Gaza Gaza City, Gaza

R. BornsteinR. Bornstein, Dept. of Meteorology, San Jose State University, , Dept. of Meteorology, San Jose State University, San Jose, CA, USASan Jose, CA, USA

Atmospheric Sciences and Air Quality ConferenceAtmospheric Sciences and Air Quality Conference27–29 April 2005, San Francisco, California 27–29 April 2005, San Francisco, California

OUTLINEOUTLINE• PROJECT OBJECTIVES

• METEOROLOGICAL PATTERNS

• RAMS & MM5 RESULTS

• EMISSION PATTERNS

• CAMx RESULTS

• CONCLUSIONS

Specific project objectives:

(1) Install environmental monitoring sites

(2) Prepare environmental databases

(3) Prepare regional climatology

(4) Conduct field campaigns during periods conducive to poor regional AQ

(5) Apply (5) Apply RAMS & MM5 toRAMS & MM5 to CAMxCAMx to increase to increase understanding of current & future air understanding of current & future air quality problemsquality problems

Topo map of study area Land-use map

Emission Inventory: 1997- 8

• 15 Large Stationary (point) sources (58% fuel consumption)

• 400 Medium Stationary (point) sources (7%)• Small Stationary (area) sources (12%)• Solvents (area) sources• Biogenic Stationary (area) sources (isoprene

and monoterpene)• Mobile (area) sources, both ground based and

aerial (22%)

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Percentage of pollution

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Time

Average daily distribution of motor vehicle emissions in Israel

Weather Conditions

• Pre-episode: weak Persian trough slow V & low mixing depth high NOx

O3 titration (costal) • Episode:

trough strengthens increased surface HPG

augmented westerly sea breeze front

high inland O3 concentration

Med Sea

900Km

900 Km

270 Km

360 Km

180 Km

270 Km

Cell 20X20 Km2

Cell 5X5 Km2

1.25X1.25Km2

RAMS • Non hydrostatic meso-met model

• 3 nested grids

• Initialized & updated every 6 h with ECMWF output

• Topography from GTOPO30 project, horizontal grid spacing of 30 sec (approx 1 km2)

• Local land-use and DTM data

(25 x 25 m2) for 2nd and 3rd grids.

• RAMS met input to CAMx

RAMS

5 m/s

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Elyakim StationOr Akiva Station

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New MM5 at SJSU • Close as possible to RAMS set-up

• 3 two-way nested grids

• Initialized & updated every 6 hr with ECMWF fields

• Topography from GTOPO30 project, horizontal grid spacing of 30 sec (approx 1 km2)

• Land-use & DTM (25 x 25 m2) for 2nd & 3rd grids

• MM5 Met fields will also be used as input to CAMx • Meso wind convention: flag is 5 m/s & full barb is 1 m/s

1.8.97 19:001.8.97 7:00

MM5

CAMx

• Map projection: Polar Stereographic

• Grid area: 270 x 370 km2 cells at 5 X 5 km2

• Transport algorithm: area preserving flux-form advection solver (Bott 1989)

• CBM-IV: Carbon Bond Mechanism + CMC fast solver

• Plume-in-grid: sub model for main stationary sources; maturity parameters 2500 m or 12 h

CAMx model

Jerusalem

Jerusalem

Flight Path

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מקראO3 ppb

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RAMS/Camx Results vs Airborne Measurements: 300 m AGL

Measurments versus Model results

y = 0.8591x - 9.3931

R2 = 0.3644

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RAMS/Camx O3: Results vs Measurements

All emission sources

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LegendO3 ppb

All industry sources Without industry sources

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1. All emission sources

2. All Industry sources

3. Main (large) Industry sources

4. Medium and small (low) industry

5. Without Industry; only Vehicles, Solvents & Vegetation

6. Vehicles only

7. Without vehicles = All Industry, Solvents & Vegetation

8. Without emissions (initial and boundary conditions)

8 Emission Input Scenarios

1.8.97 15:00

Ozone Peaks for all Scenarios: 1 Aug ‘97

SourceO3 Peak(ppb)

Comparison to “All Sources” Peak in %(discounting initial 45 ppb)

All sources 116 100%

Without emissions 56 15%

Industry low 58 18%

All industry 98 75%

Industry large 97 73%

Without Industry 82 51%

Without vehicles 103 81%

Vehicles 80 49%

Summary of results: • Temporal & spatial emission patterns reflect

land use patterns

• Spatial & temporal variations in met factors & air quality concentrations were reproduced

• RAMS & MM5 reproduce observed transport patterns

• CAMx ozone reproduces transboundary transport patterns observed by aircraft

Current Efforts:• CAMx + current emissions + RAMS or MM5

• ARIJ, EPRI, & HUJI planners to identify future emission scenarios for CAMx from 2010 & 2020 population conditions (when regional populations will have doubled present values)

• Jordanian scientists joined project

Acknowledgment

• Israel Ministry of Infrastructure • Israel Ministry of Environment • HUJI: H. Leshner, Prof. A. Danin,

Dr. R. Kadmon, I. levy• SJSU: T. Michaels, J. Wilkinson • Israel CBS: Dr. R. Shishinski,

S. Kats, O. Stone • INNPPA: Y.Magal, Y. Taober-

FUNDING: USAID/MERC PROGRAMFUNDING: USAID/MERC PROGRAM