Model Simulations Of Ozone Formation Model Simulations Of Ozone Formation Over Israel, The West Bank, And JordanOver Israel, The West Bank, And Jordan

E. Weinroth, M. Luria, A. Ben-Nun, C. Emery, J. Kaplan, M. PelegE. Weinroth, 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

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

S. Kasakseh, Applied Research Institute JerusalemS. Kasakseh, Applied Research Institute JerusalemBethlehem, West bankBethlehem, West bank

2727thth NATO/CCMS/ITM NATO/CCMS/ITMBanff Center, Banff, Alberta, CanadaBanff Center, Banff, Alberta, Canada

24-29 Oct 200424-29 Oct 2004  

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

OUTLINEOUTLINE• PROJECT OBJECTIVES

• METEOROLOGICAL PATTERNS

• RAMS AND MM5 RESULTS

• EMISSION PATTERNS

• CAMx RESULTS

• CONCLUSIONS

Specific 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 RAMS & MM5 and CAMx to (5) Apply RAMS & MM5 and CAMx to increase understanding of current & increase understanding of current & future air quality problemsfuture air quality problems

Results show

• spatial & temporal variations in met factors & air quality concentrations

• temporal & spatial emission patterns that reflect land use patterns

• RAMS winds reproduce observed transport patterns

• CAMx ozone fields reproduce transboundary transport patterns observed by aircraft

Topo map of study area

Land-use map

Emission Inventory: 1997- 8

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

• 400 Medium Stationary (point) sources (6.6%)• Small Stationary (area) sources (12.2%)• Solvents (area) sources• Biogenic Stationary (area) sources (isoprene

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

aerial

0

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4

6

8

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12

Percentage of pollution

00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00

Time

Average daily distribution of motor vehicle emissions in Israel

Weather Conditions: Preview

• Pre-episode: subtropical H slow speeds, low mixing depth

• Episode: shallow Persian thermal trough penetrates H withdraws increased surface HPG

augmented westerly sea breeze front inland elevated ozone concentration

EPA uMM5 at SJSU • As close as possible to RAMS set-up

• 3 nested grids on 96 CPU cluster

• 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

CAMx: version 3.10

• Map projection: Polar Stereographic

• Grid area: 270 x 370 km2. Cells 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 used for main stationary sources. Maturity parameters 2500 m or 12hr.

CAMx model

Jerusalem

Jerusalem

Flight Path

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Camx Results vs Airborne Measurements

CAMx model

Jerusalem

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7.8.97 14:00

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Flight Path

Camx Results vs Airborne Measurements

Measurments versus Model results

y = 0.8591x - 9.3931

R2 = 0.3644

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model ( o3 ppb)

mea

surm

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Camx Results vs Measurements

8 Emission Input Scenarios

1. All emission sources

2. All Industry sources

3. Main (large) Industry sources

4. Medium and small (low) industry

5. Without Industry = Vehicles, Solvents & Vegetation

6. Vehicles only

7. Without vehicles = All Industry, Solvents & Vegetation

8. Without emissions (initial and boundary conditions)

All emission sources

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Without emission sources

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%

Future Plans:

GIS/RS from TAU, ARIJ, an EPRI to determine gridded fields of sfc characteristics (e.g., z0, ε, α, LU/LC) for uMM5 and CAMx  

Urbanized EPA MM5 meso-model (uMM5xx) will simulate additional flow cases on the 106 CPU SJSU cluster

CAMx will be run with current precursor emissions using output from the RAMS and uMM5xx simulations

 ARIJ, EPRI, & HUJI planners will identify future emission scenarios from 2010 & 2020 population conditions (when regional populations will be 2 x present values) to test in CAMx

 Jordanian scientists will become part of project

FIRST CALL: ASAAQ2005

THE 2005 ATMOSPHERIC SCIENCES AND AIR QUALITY CONF WILL BE HELD ON

27-29 APRIL 2005 IN DOWNTOWN SAN FRANCISCO CALIFORNIA, USBA.

ABSTRACT SUBMISSION INFO CAN BE FOUND AT THE AMERICAN METEOR-OLOGICAL SOCIETY WEB PAGE: AMETSOC.ORG OR

FROM BOB BORNSTEIN AT PBLMODEL@HOTMAIL.COM

OR FROM GREG CARMICHAEL AT GCARMICH@ENGINEERING.UIOWA.EDU