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Model Simulations Of Ozone Formation Over Israel, The West Bank And Jordan. E. Weinroth, M. Luria, A. Ben-Nun, C. Emery, J. Kaplan, M. Peleg and Y. Mahrer Seagram Center for Soil and Water Sciences Faculty of Agriculture The Hebrew University Rehovot 76100 Israel. - PowerPoint PPT Presentation
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Model Simulations Of Ozone Formation Model Simulations Of Ozone Formation Over Israel, The West Bank And Jordan.Over 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
Model Simulations Of Ozone Formation Over Israel, The West Bank And Jordan.
Project objectives:
• To study, over time, the transport of polluted air masses and the chemical reactions occurring within:
• To quantify the effects of the different emission sources on the ozone peak in the study area
GIS
Stationary emission model & database
Transportation model
(EMME\2)
&
Transportation emission factors
Emission Data
Meteorological model (RAMS)
Photochemical Transport diffusion
model (CAMx)
Models
Result &Analysis
Research Structure
Model Simulations Of Ozone Formation Over Israel, The West Bank And Jordan.
Lecture Structure:• Emission Inventory for Israel • Weather Conditions at Study Area• RAMS• CAMx• Model results versus measurements• Various emission scenarios • Conclusions • Acknowledgments
Emission Inventory for Israel 1997- 8
• Large Stationary (point) sources
• Medium Stationary (point) sources
• Small Stationary (area) sources
• Solvents (area) sources
• Biogenic Stationary (area) sources
• Mobile (area) sources, both ground based and aerial
LARGE STATIONARY (POINT) SOURCES
These sources account for over 58% of total fuel consumption.
MEDIUM STATIONARY (POINT) SOURCES
• Plants which Monitor Emissions
100 plants in this category
• Plants which report Fuel Consumption
Approx 400 plants in this category
• These sources account for over 6.6% of total fuel consumption.
SMALL STATIONARY (AREA) SOURCES
• These sources account for 12.2% of total fuel consumption.
Solvents
• Road asphalt VOC.
• Solvents in urban and industrial areas: paint, aerosol products, household products, adhesives (industrial and non industrial), moth control, space deodorant - distributed by population density.
• Biogenic sources which emit the pollutants Isoprene and Monoterpene
(VOC estimated according to Winer et al 1992; Benjamin et al 1996, 1997, 1998).
Vegetation
Land-use map
MOBILE (AREA) SOURCES
• The emissions from mobile sources were derived from EMME/2 transportation model.
• This model utilizes an emission-vehicle speed curve, derived from measurements taken in tunnels– Jerusalem (Yavin, 1998) – Haifa (Tratakovsky, 1997)
– Fort Mc-Henry (Pierson, 1996)
0
2
4
6
8
10
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
Emission Inventory Results CO mol/hourVOC-
solvents0%
Vegetation0%
Industry (R)1%
Cement factories
0%
IEC1%Refineries
0%
Vehicles97%
Aviation1%
NOx mol/hour
Vehicles26%
Industry (R)14%
Cement factories
2%
IEC56%
Refineries 2%Vegetation
0%
VOC-solvents
0% Aviation0%
SO2 mol/hourAviation
0%
IEC65%
Refineries 4%
Vehicles1%
Cement factories
3%
Industry (R)27%
Vegetation0%
VOC-solvents
0%
Alkane mol/hour
VOC-solvents
89%
Vegetation0%
Industry (R)0%
Cement factories
0%
IEC0%
Refineries 1%
Aviation0%
Vehicles10%
Weather Conditions at Study Area
• The episodes of elevated ozone concentration were found to fall into the “shallow Persian trough “ synoptic category.
• Such synoptic episodes occur mainly at the beginning of summer but can occasionally appear at the middle or the end of summer.
• This synoptic pattern features stagnation conditions that evolve as a result of weak pressure gradient winds.
• A shallow mixed layer capped by subsiding warm and dry air causes a poorly ventilated mixed layer.
RAMS Aspects • RAMS 3bv• Non hydrostatic mesoscale mode. • 3 nested grids.
• The simulations were initialized and updated every 6h with European Center for Medium-Range Weather Forecasts (ECMWF) data fields.
• Topography was obtained from the GTOPO30 project, horizontal grid spacing of 30 seconds (approx 1 km2)
and with local land-use and DTM (25X25 m2) for the second and third grids.
• The meteorological fields produced by RAMS were used as input to drive CAMx.
900Km
900 Km
270 Km
360 Km
180 Km
270 Km
Cell 20X20 Km2
Cell 5X5 Km2
Cell 1.25X1.25Km2
5 m/s
07:001.8.97 7.8.97
13:00
5 m/s
1.8.97 7.8.97
19:00
5 m/s
1.8.97 7.8.97
CAMx Aspects
• CAMx 3.10
• Map projection Polar Stereographic
• Grid 270X370 Km2, cell 5X5 Km2
• Transport algorithm: area preserving flux form advection solver Bott(1989).
• CBM-IV Carbon Bond Mechanism. Using the CMC fast solver.
• “Plume-in-grid” sub model used for the main stationary sources. Maturity parameters 2500m or 12h.
15:00 1.8.97 14:00 7.8.97
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מקראO3 ppb
Camx Results vs Airborne Measurements
CAMx model
Jerusalem
Jerusalem
Flight Path
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1.8.97 15:00
Camx Results vs Airborne Measurements
CAMx model
Jerusalem
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7.8.97 14:00
Jerusalem
Flight Path
Camx Results vs Airborne Measurements
Measurments versus Model results
y = 0.8591x - 9.3931
R2 = 0.3644
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Modin Aug 1997
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Hamapil Aug 1997
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Hamaapil
1.8.97 3.8.97 7.8.97 8.8.97 10.8.97 28.8.97 29.8.97
1.8.97 3.8.97 7.8.97 8.8.97 10.8.97 28.8.97 29.8.97
Ashkelon Aug 1997
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Qiryat Gat Aug 1997
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1.8.97 3.8.97 7.8.97 8.8.97 10.8.97 28.8.97 29.8.97
1.8.97 3.8.97 7.8.97 8.8.97 10.8.97 28.8.97 29.8.97
תחנת ניטור המעפיל
תחנת ניטור מודיעין תחנת ניטור אשקלון
תחנת ניטור קריית גת
Diurnal behavior - ozone concentration 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
0
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105-120
LegendO3 ppb
1.8.97 15:00
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LegendO3 ppb
1.8.97 15:00
All industry sources
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105-120
Legend O3 ppb
1.8.97 15:00
Large industry sources
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LegendO3 ppb
1.8.97 15:00
Low industry sources
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LegendO3 ppb
1.8.97 15:00
Without emission sources
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LegendO3 ppb
1.8.97 15:00
Without industry sources
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LegendO3 ppb
1.8.97 15:00
Vehicle sources
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LegendO3 ppb
1.8.97 15:00
Without vehicle sources
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1.8.97 15:00
All industry sources
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LegendO3 ppb
1.8.97 15:00
Without emission sources
Comparison of Ozone Peak for all Scenarios 1.8.97
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%
Comparison of Ozone Peak for all Scenarios 7.8.97
SourceO3 Peak(ppb)
Comparison to “All Sources” Peak in %(discounting initial 45 ppb)
All sources 113 100%
Without emissions 52 11%
Industry low 55 14%
All industry 99 80%
Industry large 98 78%
Without Industry 78 49%
Without vehicles 105 88%
Vehicles 76 46%
29.8.97 28.8.97 10.8.97 8.8.97 7.8.97 3.8.97 1.8.97 Source
100 % 100 % 100 % 100 % 100 % 100 % 100 % All sources
51% 49% 63% 82% 80% 80% 75% All industry
50% 48% 62% 80% 78% 79% 73% Industry large
14% 14% 21% 14% 14% 18% 18% Industry low
48% 37% 42% 42% 49% 44% 51%Without Industry
46% 35% 41% 39% 46% 42% 49% Vehicles
59% 55% 68% 86% 88% 86% 81%Without vehicles
11% 12% 20% 12% 11% 15% 15%Without
emissions
Comparison of Ozone Peak for all Scenarios in % (discounting initial 45 ppb)
השוואה בין המקורות השונים
0%
20%
40%
60%
80%
100%
120%
תחבורהללא תחבורהללא תעשייהתעשייה גבוההכל התעשייהתעשייה נמוכהללא מקורותכל המקורות
סוגי המקורות
ס )סי
ב )
ע רק
קו מ
ון אוז
הא
שי ל
המ
רות
הז
חוא
29.8.97-15
28.8.97-16
10.8.97-16
8.8.97-14
7.8.97-14
3.8.97-15
1.8.97-15
השוואה בין המקורות השונים
Factor Separation contribution of different sources to formation of ozone
022ˆ fff
011̂ fff
0211212 )(ˆ fffff
00ˆ ff
SumInitial and Boundary
Conditions
SynergeticContribution WT T Date- Hour
100% 11% 6% 48% 35% 29.8.97-15:00
100% 12% 22% 43% 23% 28.8.97-16:00
100% 20% 11% 48% 21% 10.8.97-16:00
100% 12% -14% 74% 28% 8.8.97-14:00
100% 11% -22% 77% 35% 7.8.97-14:00
100% 15% -14% 72% 27% 3.8.97-15:00
100% 15% -15% 66% 34% 1.8.97-15:00
100% 14% -4% 61% 29% Average
The Relative Contribution to the Daily Ozone Peak of “Transportation” and “Without Transportation”
in % (discounting initial 45 ppb)
SumInitial and Boundary
Conditions
SynergeticContribution WI AI Date- Hour
100% 11% 12% 37% 40% 29.8.97-15:00
100% 12% 26% 25% 37% 28.8.97-16:00
100% 20% 14% 23% 43% 10.8.97-16:00
100% 12% -11% 30% 70% 8.8.97-14:00
100% 11% -17% 38% 69% 7.8.97-14:00
100% 15% -10% 30% 66% 3.8.97-15:00
100% 15% -11% 36% 60% 1.8.97-15:00
100% 14% 0% 31% 55% Average
The Relative Contribution to the Daily Ozone Peak of “All Industry” and “Without Industry”
in % (discounting initial 45 ppb)
0
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40-60
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LegendO3 ppb
1.8.97 15:00
Vehicle sources
SumInitial and Boundary
Conditions
SynergeticContribution WT T Date- Hour
100% 15% -10% 38% 57% 29.8.97-15:00
100% 22% 1% 24% 53% 28.8.97-16:00
100% 21% 0% 26% 53% 10.8.97-16:00
100% 12% -29% 57% 60% 8.8.97-14:00
100% 15% -17% 46% 56% 7.8.97-14:00
100% 15% -32% 46% 71% 3.8.97-15:00
100% 19% -69% 60% 90% 1.8.97-15:00
100% 17% -23% 43% 63% Average
The Relative Contribution to the Secondary Ozone Peak of “Transportation” and “Without Transportation”
in % (discounting initial 45 ppb)
SumInitial and Boundary
Conditions
SynergeticContribution WI AI Date- Hour
100% 15% -3% 60% 28% 29.8.97-15:00
100% 22% 11% 59% 8% 28.8.97-16:00
100% 21% 6% 55% 17% 10.8.97-16:00
100% 12% -23% 63% 48% 8.8.97-14:00
100% 15% -11% 59% 37% 7.8.97-14:00
100% 15% -25% 77% 33% 3.8.97-15:00
100% 19% -58% 99% 40% 1.8.97-15:00
100% 17% -15% 68% 30% Average
The Relative Contribution to the Secondary Ozone Peak of “Transportation” and “Without Transportation”
in % (discounting initial 45 ppb)
Conclusions
• The model agrees with the spatial distribution of ozone concentration and has reasonable agreement with the daily ozone peak.
• Major NOx emission sources - power plants and large industries - are the major contributors to the main daily ozone peak.
• The contribution of transportation is also significant to the formation of ozone in the events studied, but less than large industries.
• The added value of VOC sources (vegetation and solvents) to ozone formation is small.
• Small industries have only a minor influence on the formation of ozone.
Acknowledgments • Ministry of Infrastructure • Dr. Miriam Haran, Shuly Nezer -Ministry of Environment • HUJI: Hagar Leshner, Prof. Avinoam Danin , Dr. Ronen Kadmon,
Eran Tas, Ilan levy, David Rosen, Elad Shilo • Prof. Bob Bornstein - SJSU• Tim Michaels - SJSU • Jim Wilkinson - Alpine Geophysics • Dr. Ruth Shishinski, Shahar Kats, Orit Stone - ISRAELI CBS• Yonat Magal, Yisrael Taober- INNPPA • Igodie Arim: Ashdod, Ashkelon, Haifa, Hadera, Yavne, Jerusalem.• Ori Weinroth
Temperature inversion graph 1.8.97 13:00 ( T Celsius and height in Km)
First inversion 500 m above surface
Temperature inversion graph 28.8.97 13:00 ( T Celsius and height in Km)
First inversion 100 m above surface layer
AVIATION SOURCES
• Information was obtained from the Israeli Aviation Administration
NOx to VOC
57%
43%VOC
NOx
References:
• ARB (California Air Resources Board).(1993). EMFAC7 Computer Model, Technical Support Division.• Benjamin Mt.,Sudol M., Vorsatz D. and Winer MW. (1997). A spatially and temporally resolved biogenic
hydrocarbon emissions inventory for the California South coast air basin. Atmos. Environ.,31, 18, 3078-3100• Benjamin Mt.,Sudol M., Bloch L. and Winer MW. (1996).Low emitting urban forests: A taxonomic methodology
for assigning Isoprene and Monoterpene emission rates. Atmos. Environ.,30, 9, 1437-1452• Benjamin Mt. and Winer MW.(1998) Estimating the Ozone-forming potential of urban trees and shrubs. Atmos.
Environ.,32, 1, 53-68• Kaplan J., (1997). Model Structure and Data Requirements. Working Paper for the Trilateral Research Project on
GIS Tools for Sustainable Transport in Palestine and Israel.(Personal communication).• Kleindienst TE., Smith DF., Hudgens EE., Snow RF., Perry E., Claxton LD., Bufalini JJ., Black F. and Cupitt LT.
(1992). The Photooxidation of automobile emissions - measurements of the transformation products and their mutagenic activity., Atmos. Environ.,26, 16, 3039-3053
• Pierson w., et al.,(1996).Real world automobile emissions – Summery of studies in Fort Mc-Henry tunnel. , Atmos. Environ., 30, 2233-2256.
• Tratakovsky L., Gotman M., Zvirin Y., Golgotio I. and Alinikov Y.,(1997). Estimation of vehicles emission factors in Israel, Research report –Technion Israel Institute of Technology, Transportation research Institute, 87 pp.
• US-EPA (ed.) (1995), Compilation of the Pollutant Emission Factors; Volume 1: Stationary Point and Area Sources fifth edition. Office of Air Quality Planning and Standards Research Triangle Park NC.
• User’s guide to MOBILE5(mobile source emission factor model)(1994)• U.S.EPA Office of air and radiation office of mobile sources emission planning and strategies division air quality
analysis branch 2565 Plymouth road Ann Arbor, Michigan 48105• Winer MW., Arey J., Atkinson R., Aschmann SM., Long WD., Morrison L. and Olszyk DM.(1992) Emission rates of
organics from vegetation in California’s central valley., Atmos. Environ., 26A, 14, 2647-2659
Emission FactorsNOx (g/km)
0
5
10
15
20
25
30
35
8 16 24 32 40 48 56 64 72 80 88
Speed (km/hr)
Em
issi
on F
acto
r (g
/km
)
L D Leaded
L D Unleaded
L D Diesel
H D Diesel
Emission FactorsTOG (g/km)
0
5
10
15
20
25
8 16 24 32 40 48 56 64 72 80 88
Speed (km/hr)
Em
issi
on F
acto
r (g/
km)
L D Leaded
L D Unleaded
L D Diesel
H D Diesel
Vegetation
Biomass Amount per hectare
Vegetation Coverage percentage
VOC emissions per Biomass Amount
VOC emissions per hectare
=**
