wrap rmc phase ii wind blown dust project results status environ international corporation and...
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General Formulation for Emissions Estimation Dust = f(LULC,z 0,u *,u *th,SC) u * = f(u,z 0 ) u *th = f(z 0 ) z 0 = f(LULC)TRANSCRIPT
WRAP RMC Phase II Wind Blown Dust Project
Results & Status
ENVIRON International Corporationand
University of California, Riverside
Dust Emission Joint Forum MeetingLas Vegas, NV
November 16, 2004
Phase II Project Overview• Develop improved general methodology based on Phase I
recommendations and recent literature review • Update gridded PM inventory of WB Dust for 2002 using the Inter-
RPO regional modeling domain • Develop of surface friction velocities and threshold friction
velocities• Develop improved emission flux relationships• Improve vacant land characterization
– Disturbance– Land use type– Reservoirs
• Conduct model performance evaluation
General Formulation for Emissions Estimation
• Dust = f(LULC,z0,u*,u*th,SC)
• u* = f(u,z0)
• u*th = f(z0)
• z0 = f(LULC)
Threshold Friction Velocities• u*th determined from relations developed by Marticorena, et
al, (1997)
u*t = 0.31e7.44x(Zo)
R2 = 0.60
u*t = 0.30e7.22x(Zo)
0
0.5
1
1.5
2
2.5
3
0.00001 0.0001 0.001 0.01 0.1 1
zo (cm)
u *t (
m s-1
)
wind tunnel data Marticorena et al. 1997Expon. (wind tunnel data) Expon. (Marticorena et al. 1997)
Emission Rates• Depends on soil type; based on results of Alfaro and
Gomes (2001)
FFSF = 2.45x10-6 (u*)
3.97
FSF = 9.33x10-7 (u*)
2.44
MSF = 1.243x10-7(u*)
2.64
CSF = 1.24x10-7 (u*)
3.44
0.000000001
0.00000001
0.0000001
0.000001
0.00001
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Friction Velocity (m s-1)
Emis
sion
Flu
x (F
, g c
m-2
s-1)
FSSFSMSCSPower (FSS)Power (FS)Power (MS)Power (CS)
NLCD Summary
NLCD Land Use Summary (Continental US)
Land Use Type Total Area (acres) % % excluding waterWater 98,484,739 5.0%Urban 35,629,865 1.8% 1.9%Barren 37,204,176 1.9% 2.0%Forest 556,424,387 28.1% 29.6%Shrubland 355,796,082 18.0% 18.9%Grasslands 302,601,621 15.3% 16.1%Agricultural 515,624,831 26.0% 27.4%Wetlands 78,127,135 3.9% 4.2%Total 1,979,892,836 100.0%
Total excluding water 1,881,408,097 100.0%
Dust Code 3 4 6 7
Land use category Ag. Grass Shrubs Barren
Surface roughness (cm) 0.031 0.1 0.05 0.002
Threshold friction Velocity (mile/h) 8.33 13.81 9.62 6.81
Threshold wind velocity at 38m height (mile/h) 29.50 44.25 32.75 28.50
Characteristics of Dust Categories
Soil CharacteristicsU.S. soil texture Chatenet (1996) Chatenet (1996)
Soil Texture (from Chamley, 1987) Groupings
sand sand CS
loamy sand sand CS
sandy loam silty sand MS
sandy clay loam clayey sand MS
sandy clay clayey sand MS
(medium) loam clayey silty sand MS
clay loam clayey silty sand MS
silty loam clayey sandy silt FS
silty clay loam clayey silt FFS
silt silt FFS
silty clay silty clay FFS
clay sandy clay FS (10-50% sand, 75-50% clay)
clay sandy silty clay FS (10-45% sand, 12-45% silt, 35-75% clay)
Reservoir Characteristics
• All soils assumed loose, undisturbed• Dust events limited to 10hrs/day
– Sensitivity simulations conducted based on above assumptions
• Rain events: Dust re-initiated after set number of days dependent on soil texture, amount of rainfall and season
Number of days after rain event to re-initiate wind erosion
• Rainfall > 2 inches • Rainfall < 2 inchesSoil type Spring/Fall Summer Winter
Sand 3 2.1 4.2
Sandy Loam 3 2.1 4.2
Fine Sand Loam
3 2.1 4.2
Loam 4 2.9 3.8
Silt Loam 4 2.9 3.8
Sandy Clay Loam
4 2.9 3.8
Clay Loam 5 3.6 7.2
Silty Clay Loam
6 4.3 8.6
Clay 7 5 10
Soil type Spring/Fall Summer Winter
Sand 1 0.7 1.4
Sandy Loam 1 0.7 1.4
Fine Sand Loam 1 0.7 1.4
Loam 2 1.4 2.8
Silt Loam 2 1.4 2.8
Sandy Clay Loam 2 1.4 2.8
Clay Loam 3 2 4
Silty Clay Loam 4 2.8 5.6
Clay 5 3.6 7.2
Model Sensitivity Simulations
• Run a :– No limitation on dust event duration– All soils considered loose undisturbed
• Run b :– Dust events limited to 10 hrs/day– All soils considered loose undisturbed
Model Sensitivity Simulations
• Run c :– No limitation on dust event duration – Assume 10% of barren, grass & shrublands area is disturbed– Threshold velocity for grass & shrublands = 0.5 * undisturbed value– Threshold velocity for barren lands = .27 * undisturbed value
• Run d :– Dust events limited to 10 hrs/day for undisturbed soils– Assume 10% of barren, grass & shrublands area is disturbed– Threshold velocity for grass & shrublands = 0.5 * undisturbed value– Threshold velocity for barren lands = .27 * undisturbed value
Model ResultsScenario a: no limit on duration; all soils loose, undisturbed
Dust emissions, Scenario a
60.2%18.4%
20.4%
1.0%Dust Code 3 - AgDust Code 4 - GrasslandsDust Code 6 - ShrublandsDust Code 7 - Barren
Model ResultsScenario b: event duration <=10 hrs/day; all soils loose, undisturbed
Dust emissions, Scenario b
61.7%15.7%
21.5%
1.1% Dust Code 3 - AgDust Code 4 - GrasslandsDust Code 6 - ShrublandsDust Code 7 - Barren
Model ResultsScenario c: no limit on duration; assume 10% disturbed area for grass,
shrub, barren lands
Dust emissions, Scenario c
48.6%
26.0%
23.3%
2.1% Dust Code 3 - AgDust Code 4 - GrasslandsDust Code 6 - ShrublandsDust Code 7 - Barren
Model ResultsScenario d: event duration <= 10hrs/day for disturbed soils; assume 10%
disturbed area for grass, shrub, barren landsDust emissions, Scenario d
42.9%
28.6%
25.7%
2.8%Dust Code 3 - AgDust Code 4 - GrasslandsDust Code 6 - ShrublandsDust Code 7 - Barren
Dust Totals for WRAP Statestons/year
Scenario WRAP States Domain Total (US only)
a 2,222,219 9,451,368
b 1,310,120 5,228,818
c 3,077,196 11,098,731
d 2,165,096 6,876,180
1996 2,240,288 4,366,907
Annual PM10Dust Yearly Total by State
Western States
0
200000
400000
600000
800000
1000000
1200000
1400000
1600000
1800000
AZ
AR
CA
CO ID IA KS
LA
MN
MO
MT
NE
NV
NM
ND
OK
OR
SD
TX
UT
WA
WI
WY
State
Ton/
y
scen ascen bscen cscen d1996
Annual PM10Dust Yearly Total by State
WRAP States
0
100000
200000
300000
400000
500000
600000
700000
800000
900000
1000000
AZ
CA
CO ID MT
NV
NM
ND
OR
SD
UT
WA
WY
State
Ton/
y
scen a
scen b
scen c
scen d
1996
Comparison of Monthly Dust EmissionsMonthly Dust Emissions
0.0
500000.0
1000000.0
1500000.0
2000000.0
2500000.0
3000000.0
3500000.0
4000000.0
4500000.0
1 2 3 4 5 6 7 8 9 10 11 12
month
Ton/
Mon
th
scen a scen b
scen c scen d
Dust from Category 3 (Ag land)PM10 Yearly Total
0
50000
100000
150000
200000
250000
300000
350000
400000
AZ
CA
CO ID MT
NV
NM
ND
OR
SD
UT
WA
WY
State
Ton/
y
scen ascen bscen cscen d
Annual PM10 from Ag Land for WRAP States
Dust from Category 4 (Grass land)PM10 Yearly Total
0
40000
80000
120000
160000
200000
240000
280000
320000
AZ
CA
CO ID MT
NV
NM
ND
OR
SD
UT
WA
WY
State
Ton/
y
scen a
scen b
scen c
scen d
Annual PM10 from Grass Land for WRAP States
Dust from Category 6 (Shrub land)PM10 Yearly Total
0
20000
40000
60000
80000
100000
120000
140000
160000
180000
AZ
CA
CO ID MT
NV
NM
ND
OR
SD
UT
WA
WY
State
Ton/
y
scen ascen bscen cscen d
Annual PM10 from Shrub Land for WRAP States
Dust from Category 7 (Barren land)PM10 Yearly Total
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
AZ
CA
CO ID MT
NV
NM
ND
OR
SD
UT
WA
WY
State
Ton/
y
scen ascen bscen cscen d
Annual PM10 from Barren Land for WRAP States
Scenario b Annual PM10 from All Dust Categories for WRAP States
Dust from all Categories for Scenario bPM10 Yearly Total
0
30000
60000
90000
120000
150000
180000
210000
240000
AZ
CA
CO ID MT
NV
NM
ND
OR
SD
UT
WA
WY
State
Ton/
y
Dust Code 3 - Ag
Dust Code 4 - Grasslands
Dust Code 6 - Shrublands
Dust Code 7 - Barren
Scenario d Annual PM10 from All Dust Categories for WRAP States
Dust from all Categories for Scenario dPM10 Yearly Total
0
30000
60000
90000
120000
150000
180000
210000
240000
AZ
CA
CO ID MT
NV
NM
ND
OR
SD
UT
WA
WY
State
Ton/
y
Dust Code 3 - AgDust Code 4 - GrasslandsDust Code 6 - ShrublandsDust Code 7 - Barren
2002 Annual PMC Scenario a: no limit on duration; all soils loose, undisturbed
2002 Annual PMC Scenario b: event duration <=10 hrs/day; all soils loose, undisturbed
2002 Annual PMC Scenario c: no limit on duration; assume 10% disturbed area for grass,
shrub, barren lands
2002 Annual PMC Scenario d: event duration <=10 hrs/day; assume 10% disturbed area for
grass, shrub, barren lands
2002 Annual PMC Scenario b: event duration <=10 hrs/day; all soils loose, undisturbed
2002 Seasonal PMC
Model Limitations• Grid resolution
– Coarse resolution of met data can’t resolve high wind events; wind gusts
• LULC and Soils data– LULC not detailed enough on a regional-scale– Soils data lacks depth of layers, moisture data
• Agricultural land adjustments– No agricultural data for Eastern states (prepared for WRAP &
CENRAP regions only)– Data gaps in Ag Census
Model Performance Evaluation1. Evaluate model results for reasonableness and accuracy
– Compare predicted WB dust emissions near IMPROVE monitors with measured IMPROVE dust extinction (Bdust)
2. Enhancements to CMAQ to track WB and other dust– Evaluate model CMAQ model performance with and without
WB dust emissions
3. Refined model performance evaluation using results of Etyemezian, et al.
– For events characterized as wind blown dust events, determine whether dust model predicts impacts
2002 Coarse Mass
Seasonal Coarse Mass (2002)
Annual Fine & Coarse Mass (2003)
Model Performance Evaluation (1)• Evaluate model results for reasonableness and accuracy• Compare predicted WB dust emissions near IMPROVE monitors with
measured IMPROVE dust extinction (Bdust)
– Identify occurrences of:1) Zero WB dust and near-zero Bdust
2) Enhanced WB dust and near-zero Bdust
3) No WB dust and elevated Bdust
4) Enhanced WB dust and elevated Bdust
• Modeled dust averaged over 5 x 5 block of grid cells centered on IMPROVE sites
• Daily averaged model results paired (in time & space) with monitored data
• Compare modeled PM with Bextdust
– Bextdust = [FS] + 0.6[CM]
Model Performance Evaluation (1)YELL
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg5x
5)
YELL
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg3x
3)
Model Performance Evaluation (1)
ZION
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg5x
5)
ZION
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg3x
3)
Model Performance Evaluation (1)YOSE
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg5x
5)
YOSE
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg3x
3)
Model Performance Evaluation (1)
LOST
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg5x
5)
LOST
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg3x
3)
Model Performance Evaluation (1)
CAPI
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg5x
5)
CAPI
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg3x
3)
Model Performance Evaluation (1)
MELA
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg5x
5)
KALM
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg5x
5)
Model Performance Evaluation (1)
PORE
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg5x
5)
GUMO
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg5x
5)
Model Performance Evaluation (1)
MORA
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg5x
5)
DEVA
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg5x
5)
Model Performance Evaluation (1)
BADL
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg5x
5)
BADL
0
20
40
60
80
100
0 20 40 60 80 100
Normalized DUST_Bext
Nor
mal
ized
PM
10 (a
vg3x
3)
Model Performance Evaluation (2)
• Enhancements to CMAQ to track WB and other dust emissions separately
• Run CMAQ w/ and w/o WB Dust emissions• Evaluate CMAQ model results with and with out WB dust
emissions
Model Performance Evaluation (2)
January, 2002
Model Performance Evaluation (2)
July, 2002
Model Performance Evaluation (2)
Model Performance Evaluation (3)• Refined model performance evaluation using results of
Etyemezian, et al.• For events characterized as wind blown dust events, determine
whether dust model predicts impacts• Model and measurements agree …
– Analyze for trends– Systematic over- or under-prediction ?
• Model and measurements disagree …– Wind speed errors ? – Landuse type mischaracterization ?– Other ?
Analyses on-going based on DRI project results
Next Steps• Complete Model Performance Evaluation (end of year)• Address deficiencies in Ag data for the Eastern States
– Assume constant crop canopy %– Develop generic crop calendars, crop canopy % , etc.– Collect detailed Ag data from Eastern States
• Re-run model w/ latest MM5 data• Make use of 12-km resolution MM5 data• Apply to small region for verification of methods, assumptions• Apply transport fraction by county for air quality model
applications