wrap regional modeling center uc riverside/environ presented at rpo national workgroup meeting
DESCRIPTION
WRAP Wind Blown Fugitive Dust and Ammonia Emissions Updates. WRAP Regional Modeling Center UC Riverside/ENVIRON Presented at RPO National Workgroup Meeting November 4 – 6, 2003 St. Louis, Missouri. Project Team. Fugitive Dust Gerard Mansell; ENVIRON Martinus Wolf, Paula Fields; ERG - PowerPoint PPT PresentationTRANSCRIPT
WRAP Regional Modeling CenterUC Riverside/ENVIRON
Presented atRPO National Workgroup Meeting
November 4 – 6, 2003St. Louis, Missouri
WRAP Wind Blown Fugitive Dust and Ammonia Emissions Updates
Project Team
Fugitive Dust• Gerard Mansell; ENVIRON• Martinus Wolf, Paula Fields; ERG• Jack Gillies; DRI• Mohammad Omary; UCR• Bill Barnard; MACTEC Engr. & Consulting• Michael Uhl; DAQM, Clark County, NVAmmonia• Mark Chitjian; UCR• Gerard Mansell; ENVIRON
Outline
• Project Background & Overview• Literature Review• Estimation Methodology• Agricultural Considerations• Data Sources• Summary of Assumptions• Program Implementation• Results• Recommendations
Background and Overview of Project
• Develop General Methodology to Facilitate Future Revisions and Control Strategy Development
• Develop Integrated SMOKE Processing Modules for PM10 and PM2.5 Emissions Modeling
• Develop PM10 and PM2.5 Emission Inventory Applicable to the Western Region
Overview of Technical Approach
• Categorize Vacant Land Types• Identify Wind Tunnel Emission Factors• Develop Meteorological Data• Develop Threshold Wind Velocities, Wind Events,
Precipitation Events• Apply Emission Factors to Vacant Land Categories
Literature Review
• Portable field wind tunnels have been used to investigate particle entrainment thresholds, emission potentials, and transport of sediment by wind.
• Major contributions of information on: – thresholds from Gillette et al. (1980), Gillette et al.
(1982), Gillette (1988), Nickling and Gillies (1989);– emission fluxes from Nickling and Gillies (1989),
James et al. (2001), Columbia Plateau PM10 Program (CP3), Houser and Nickling (2001).
• Key information has also come from dust emission modeling (e.g., Alfaro et al., 2003) and desert soil characterization studies (e.g., Chatenet et al., 1996).
Wind Tunnel Study Results: Thresholds
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)
Comparison between modeled relationship of threshold friction velocity and aerodynamic roughness length and wind tunnel data.
*
*(Gillette et al., 1980; Gillette et al., 1982; Gillette, 1988; Nickling & Gillies, 1989)
Wind Tunnel Study Results: Emissions
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)
Em
issi
on F
lux
(F, g
cm
-2 s-1
)
FSSFSMSCSPower (FSS)Power (FS)Power (MS)Power (CS)
The emission flux as a function of friction velocity predicted by the Alfaro and Gomes (2001) model constrained by the four soil geometric mean diameter classes of Alfaro et al. (2003).
Wind Tunnel Study Results: Emissions as a function of texture
Sand(CS) Silty sand (MS) Sandy silt (FS) Silt (FSS)
Clayey silt
Silty clay
sand silt
clay
Clay
Sandy siltyclay
Clayey sandysilt
Clayey siltysand
Sand
y clay
Clay
ey sa
nd
50%
7525
7525
10
10
10
Sand(CS) Silty sand (MS) Sandy silt (FS) Silt (FSS)
Clayey silt
Silty clay
sand silt
clay
Clay
Sandy siltyclay
Clayey sandysilt
Clayey siltysand
Sand
y clay
Clay
ey sa
nd
50%
7525
7525
10
10
10
Sand(CS) Silty sand (MS) Sandy silt (FS) Silt (FSS)
Clayey silt
Silty clay
sand silt
clay
Clay
Sandy siltyclay
Clayey sandysilt
Clayey siltysand
Sand
y clay
Clay
ey sa
nd
50%
7525
7525
10
10
10
Relations between the soil types deduced from aggregate size distributions of various desert soils and soil textural categories (Chatenet et al. 1996). The “gray” highlighted textural classes indicate the 4 sediment types; the arrows indicate the pathways linking these types to the other textures. These can be linked to the North American soil texture triangle.
Wind Tunnel Study Results: Emissions
1E-10
1E-09
1E-08
1E-07
1E-06
10 100u* (cm/s)
Fv (g
/cm
2/s)
FS
Casa Grande
Mesa (Salt River )
Hayden
Ajo
Yuma (ag)
Glendale
Tucson (Sta Cruz)
Tucson (const.site)Mesa (ag)
CS
Yuma (scrubdesert)Yuma (distdesert)
Comparison between model relationship for FS and CS sizes and the wind tunnel data of Nickling and Gillies (1989). Ten (out of 13) sites have a dust production potential similar to the FS model and one site (Mesa agricultural) is closely aligned with the CS model (after Alfaro et al., 2003).
0
0.005
0.01
0.015
0.02
0.025
0.03
0.035
20 - 24.9 25 - 29.9 30 - 34.9 35 - 39.9 40 - 44.9 45 - 49.9 50 - 54.9
Emission Rates by Soil Group for Stable Soils Em
issi
on F
acto
r (to
n/ac
re/h
our)
Soil Group 1Soil Group 2
Soil Group 3Soil Group 4Soil Group 5
10-m Wind Speed (mph)
Emission Rates by Soil Group for Unstable Soils
0
0.005
0.01
0.015
0.02
0.025
0.03
20 - 24.9 25 - 29.9 30 - 34.9 35 - 39.9 40 - 44.9 45 - 49.9 50 - 54.9
10-m Wind Speed (mph)
Emis
sion
Fac
tor (
ton/
acre
/hou
r)
Soil Group 1Soil Group 2
Soil Group 3Soil Group 4Soil Group 5
Agricultural Considerations
• Non-climatic factors significantly decrease soil loss from agricultural lands
• Similar approach to CARB, 1997• Five “adjustment” factors simulate these effects:
– Bare soil within fields – Bare borders surrounding fields– Long-term irrigation– Crop canopy cover– Post-harvest vegetative cover (residue)
0.000
0.100
0.200
0.300
0.400
0.500
0.600
0.700
0.800
0.900
1.000
0 10 20 30 40 50 60 70 80 90 100
% Cover
Fact
or V
alue Canopy Cover Factor
Residue Cover Factor
Canopy Cover and Residue Cover Adjustment Factor
Agricultural Adjustment Factor Development
• New regional data collected for WRAP project:– Crop calendars with growth curves from Revised
Universal Soil Loss Equation (RUSLE2) model– Residues remaining after harvest due to
conservation tillage practices from Purdue’s Conservation Technology Information Center (CTIC)
– Irrigation events from crop budget databases • Factors applied by county/crop type, crop
management zones (CMZs)
Data Sources
• Land Use/Land Cover (LULC)– Biogenic Emission Landcover Database (BELD3)– North American Land Cover Characteristics – National Land Cover Database (NLCD)
• Soils Characteristics– State Soil Geographic Database (STATSGO)– Soil Landscape of Canada (SLC_V2)– International Soil Reference and Information Centre
• Meteorological Data– 1996 MM5 36-km (Wind Velocity, Precipitation,
Snow/Ice, Soil Temperature)
Land Use/Land Cover Data
• BELD3 LULC Data
Summary Total Area (Acres) % % excluding waterUrban 6,781,771 0.26% 0.34%Agriculture 531,231,552 20.54% 26.35%Shrub/grassland 720,022,464 27.84% 35.71%Forest 741,902,639 28.69% 36.80%Barren 5,801,931 0.22% 0.29%Wetlands 681,383 0.03% 0.03%Tundra 9,096,875 0.35% 0.45%Snow&Ice 603,210 0.02% 0.03%Water 569,829,853 22.04%Total 2,585,951,680 100.00%
Total excluding water 2,016,121,827 100.00%
Meteorological Data
• 1996 MM5– 1996 Annual, hourly, gridded meteorology– 36-km horizontal resolution– 10-m wind speeds– Precipitation rates– Snow/ice cover flag– Soil temperature
Data Compilation for Land Use and Soil Types
• Land use and soil texture aggregated to 12-km resolution
• Major land use categories– Urban– Agricultural– Shrub and grasslands– Forest– Barren and Desert
• Land use fractions from 1-km data retained as percentages
• Dominate soil texture at 12-km resolution
Soil Texture Categorization
• Standard soil types mapped to 5 major types for dust calculations– Silty Sand and Clay– Sandy Silt– Loam– Sand– Silt
STATSGO Soil Texture
Soil Texture Code
Soil Group Code
No Data 0 0Sand 1 4Loamy Sand 2 4Sandy Loam 3 2Silt Loam 4 1Silt 5 5Loam 6 3Sandy Clay Loam 7 2Silty Clay Loam 8 5Clay Loam 9 3Sandy Clay 10 2Silty Clay 11 5Clay 12 1
Vacant Land Stability
• Windblown dust emissions affected by soil stability• Stability determination based on land types• Urban lands may be stable or unstable
LULC Category Stability Urban Stable/Unstable (see below) Agricultural -- Shrubland Stable Grassland Stable Mixed Shrub/Grassland Stable Forest Stable Barren Unstable Desert Unstable
Urban Land Stability
• Urban lands divided into core and boundary areas• Core = 92.67%; Boundary = 8.33% • Core urban areas:
– 8 % unstable– 92% stable
• Boundary urban areas:– 30% unstable– 70% stable
Reservoir Characteristics
• Reservoirs characteristics based on stability– Stable = limited– Unstable = unlimited
• Stable reservoirs are depleted within 1 hour• Unstable reservoirs are depleted within 10 hours• Reservoirs require 24 hours to recharge
Precipitation and Freeze Events
• No dust emissions during rain events• Rainfall from MM5 at 36-km resolution• No dust emissions if snow/ice cover present• Dust emissions re-initiated:
– 72 hours after rain– 72 hours after snow/ice meltdown– 12 hours after thaw
Vegetative Cover Adjustments
• Vegetation cover reduces dust emissions• Methodology developed for bare soil• Emissions reduction factors developed from White
(2000)• Vegetation density based on land use types
Vegetative Cover Adjustments
LULC Category Vegetation Cover % Reduction Factor Urban 55(stable)/0(unstable) 0.07/1.0 Shrubland 11 0.70 Grassland 23 0.19 Mixed Shrub/Grassland 17 Forest 55 0.07 Barren 0 1.0 Desert 0 1.0
Summary of Assumptions
• Threshold velocity = 20 mph• Vacant land stability• Urban lands• Dust reservoirs• Reservoir depletion and recharge times• Precipitation, snow and freeze events• Vegetation density
Program Implementation
• Daily/Hourly Meteorological Data• State/County, Crop Management Zone, and Soil
Type, For Each 12km Cell.• Area fractions For Each 12km Cell, and Land Use
For Each Area Fraction.• Agricultural Adjustment Data• Emission Rates by Soil and Wind Speed Categories
Agricultural Input Data
• County and CMZs for 12-km grid cells• Crop area percentages for 12-km cells• Barren, border and crop fractions for BELD3 crops• Long term irrigation factors by soil type• Irrigation fraction by county and crop• Tillage fractions by crop and county• Planting and harvesting dates by crop (crop
calendars)• Crop canopy cover by crop (growth curves)• Residue cover
Summary of Annual PM10 Emissions
Annual PM10 by Landuse
urbanAg_nonadjustAgdesert,barren landforestshrubgrasslandshrub/grassland
PM10 Dust Emissions by Month
Total Dust Emission
00
200000
400000
600000
800000
1000000
1200000
1400000
1600000
1 2 3 4 5 6 7 8 9 10 11 12
Month
(tons
)
Monthly PM10 Emissions by Landuse Type
Total PM10 (tons)
0
200000
400000
600000
800000
1000000
1200000
1400000
1600000
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Month
tons
water/welandshrub/grasslandgrasslandshrubforestdesert,barren landAgAg_nonadjusturban
Monthly PM10 Emissions by Crop Type
Monthly PM10 by crops
0
50000
100000
150000
200000
250000
300000
350000
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Month
PM
10(to
ns)
WheatTobaccoSoybeansSorghumRyeRicePotatoesPeanutsPastureOatsMiscHayGrassCottonCornBarleyAlfal
Annual PM10 and PM2.5
Monthly PM10 Emissions
Monthly PM10 Emissions
Monthly PM10 Emissions
Monthly PM10 Emissions
Monthly PM10 Emissions
Monthly PM10 Emissions
Sensitivity Simulation
• Evaluate impact of threshold velocity and reservoir assumptions
• Extend emissions factor relations to lower wind speeds
• Relax reservoir recharge assumptions:– 6 hours between wind events– 24 hours after rain events– 24 hours after snow/ice meltdown– 6 hours after thaw
Recommendations
• Methodology review and refinement• Current, detailed data to characterize vacant lands• Methodology validation with small-scale, high
resolution domain• Comparison with other methodologies• Identification and evaluation of additional wind
tunnel studies• Application to other domains, years
WRAP Ammonia Emissions Updates
Activity Data
EmissionFactors
NLCDCensus Data
Meteorological Data
Soils Data
AllocationAssociation
Table DomainDefinition
Annual Inventory
-by source -by county
ReportsSummaries
QA/QC
Gridded Inventory
-total NH3 -by grid cell
EmissionEstimation
Spatial andTemporalAllocation
ArcGisAmmoniaEmission
Model
Model Flow
• Designed to :– treat relationship of ammonia emissions to environmental variables– incorporate high resolution spatial data (LU/LC databases; population
density; geo-coded point sources)– incorporate detailed source classification schemes
• Based on Arc/INFO GIS• Flexible input data sources/formats; easily modified input tabular data
(activity data, EF, spatial surrogate relationships, domain definition)• Efficient processing capabilities • Modular• Intuitive user interface
GIS-Based Emissions Model Development
• Livestock - dairy, beef, pigs, poultry, sheep, horses
• Fertilizer
• Soils – highly uncertain, may at time act as source or sink, potentially very large source
Focus on Largest Sources
Minor Sources
•Mobile - on-road and off-road•Domestic - respiration, perspiration, cigarettes, pets, etc.•Landfills•Composting•Industrial •Wildfire/Ag fire
Spatial Allocation
• Point Sources – As many sources as possibleLandfills Confined Feeding OperationIndustrial Large Poultry FacilitiesCompost Dairies
• National Land Cover Data (NLCD)• Census Coverages – Domestic Sources• Environmental Parameters – i.e., Soil pH
Temporal Allocation
• Empirically Based Seasonal and Diurnal Profiles
• Temporally Varying Environmental ParametersWind SpeedAir Temperature Soil Surface Temperature
NLCD
• 30 meter resolution• 21 Land Cover Classification Categories• Based on Landsat Thematic Mapper Data• Developed by Multi-Resolution Land Characterization
Consortium• USGS• EPA• Forest Service• NOAA
NLCD Classification Codes
11 Open Water 12 Perennial Ice/Snow21 Low Intensity Residential 22 High Intensity Residential 23 Commercial/Industrial/Transportation31 Bare Rock/Sand/Clay32 Quarries/Strip Mines/Gravel Pits33 Transitional41 Deciduous Forest42 Evergreen Forest43 Mixed Forest
51 Shrubland61 Orchards/Vineyards/Other71 Grasslands/Herbaceous81 Pasture/Hay82 Row Crops83 Small Grains84 Fallow85 Urban/Recreational Grasses91 Woody Wetlands92 Emergent Herbaceous Wetlands
WRAP NH3 Model Main Menu
Emission Calculation Menu
Annual Gridded Domestic NH3 Emissions
Literature Review
Eleven Relevant Recently Published Papers• Temporal Allocation – Sakurai and Fujita, 2002; vanHove
et al., 2002; Pinder at al., 2003; Roelle and Aneja, 2001;De Visscher et al., 2002; Anderson et al., 2003
• Livestock Emission Factors – Jarvis and Ledgard, 2002; Battye et al., 2003; Pinder at al., 2003Keener et al., 2001; Doorn et al., 2002; De Visscher et al., 2002
• Mobile Emission Factors – Durbin et al 2002• Soil Emission Factors – Battye et al., 2003; Roelle and
Aneja 2001
Schedule
• Draft 1996 NH3 modeling inventory by December 2003
• Next Step: 2002 NH3 inventory