analysis of haul road emission test data
TRANSCRIPT
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Analysis of Haul Road Emission Test Data forDetermining Dispersion Modeling
Updated June 2004
Prepared by:
Arron Heinerikson Principal Consultant
Trinity Consultants
9777 Ridge DriveSuite 380
Lenexa, KS 66219www.trinityconsultants.com
(913) 894-4500
June 2004
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ANALYSIS OF HAUL ROAD EMISSION TEST DATA FORDETERMINING
DISPERSION MODELING PARAMETERS (UPDATED JUNE, 2004)
Arron Heinerikson and Abby Goodman
Trinity Consultants25055 West Valley Parkway, Suite 101
Olathe, Kansas 66061
INTRODUCTION
Many regulatory agencies require aggregate facilities to complete air quality dispersion
modeling analyses before issuing permits. One of the most subjective and time-consuming
aspects of air dispersion modeling is the modeling of sources that are fugitive in nature like
those found at a typical aggregate facility. Fugitive sources can include fugitive dust from
conveyor transfer points, haul roads and open storage piles, as well as emissions from
crushers/screens and truck loading and unloading. The current and proposed EPA air dispersion
models, Industrial Source Complex Model (ISCST3)1and Aermic Model (AERMOD)2, are able
to estimate ambient concentrations from these types of fugitive sources. The models allow for
categorization of sources into point, area, volume, or open pit sources (open pit sources are only
available in ISCST3).
The National Stone, Sand, and Gravel Association (NSSGA) is in the process of developing a
document that provides step-by-step instructions on how to appropriately model fugitive sources
from aggregate facilities. Methodologies for correctly characterizing fugitive sources are
necessary due to the models sensitivity to certain input parameters and the lack of guidance for
modeling fugitive sources. Incorrect characterization of fugitive sources can lead to unrealistic
model-predicted concentrations. Often, the impacts of fugitive sources are exaggerated to the
point of causing facilities to limit utilization of plant equipment to be able to demonstratemodeled compliance with air quality standards, while nearby monitors show only minimal
concentrations.
Many types of sources will be reviewed in the NSSGA document, including haul roads. It is
critical that haul roads are characterized correctly in a modeling analysis. Texas Commission of
Environmental Quality (TCEQ) guidance notes that if haul road sources are incorrectly
characterized, the model will over predict and may incorrectly identify road emissions as the
major cause of air pollution at the facility.3
This document provides methods for appropriately characterizing haul road sources such that the
modeled parameters, and thus calculated concentrations, accurately reflect the sources in
question. Discussions on regulatory guidance are included as well as summaries of the data andtechnical theory used to develop the suggested methodologies. The methodologies presented
should be adapted to fit site specific characteristics as shown in the following sections.
1Users Guide for the Industrial Source Complex (ISC3) Dispersion Models, Volume II Description of
Model Algorithms. EPA-454/B-95-003b, September 1995.
2Users Guide for the AMS/EPA Regulatory Model AERMOD. August 10, 2002.3Texas Commission of Environmental Quality (TCEQ) Air Quality Modeling Guidelines RG-25 (Revised).
February 1999.
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HAUL ROADS
Emissions from haul roads are caused by the force of the haul truck wheels pulverizing surface
materials. The surface particles are then lifted and thrust into the air by the rolling wheels. The
truck accelerating through the wind causes a turbulent wake. The dust is then mixed in the wake
before dispersing further by the motion of the wind, as shown in Figure 1.
FIGURE 1. EXAMPLE HAUL ROAD
CURRENT HAUL ROAD MODELING GUIDANCE
There is limited written guidance on how to model fugitive sources and more specifically haul
roads, further stressing the importance of consistent source characterization methodologies that
are based on source specific data and sound model theory. The limited written guidance
available is presented below.
A small number of state agencies have provided written guidance on how to model haul roads.
New Mexico, North Carolina, Oklahoma, and Texas suggest modeling haul roads as volume
sources. Whereas, the following states suggest modeling haul roads as an area source:
Missouri, Nebraska, Nevada, South Carolina, and Vermont. In contrast, Louisiana providesguidance on modeling haul roads as several point sources.
Several state agencies, such as Texas, Oklahoma, and Louisiana, also recommend that haul
roads should only be included in modeling analyses of annual averaging periods. These states,
as well as AP-42 Section 13.2.2, place low confidence on short-term haul road emission rates
unless site-specific data is used.
As a part of Texass model refinement processes, the TCEQ has developed a new procedure for
modeling low-level fugitive sources with release heights less than 10 meters. They allow
facilities to apply an adjustment factor of 0.6 to the emission rate of each fugitive source to
minimize the apparent tendency of the model to exaggerate modeled concentrations from low-
level fugitive sources.4
It is important to note the small number of states that provide written guidance on how to model
haul roads. In addition, even fewer states provide written guidance on determining the haul road
modeled parameters, such as release height and initial vertical dimension.
4Texas Commission of Environmental Quality (TCEQ), Interoffice Memorandum, March 6, 2002.
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Texas is the only state that provides specific written guidance for determining the appropriate
modeling parameters for a haul road source. The TCEQ guidance for determining haul road
volume source parameters is summarized below.5
1. Determine the adjusted width of the haul road. The adjusted width is the actual width of the
road plus 6 meters. The additional width represents turbulence caused by the vehicle as it
moves along the road.
2. Determine the height of the volume source. The height is 2 times the actual height of the
vehicle generating emission (i.e. the haul truck).
3. Determine the initial horizontal dimension (yo).
a. If the haul road is represented by a single volume source, yo = adjusted width / 4.3
b. If the haul road is represented by adjacent volume sources,yo = adjusted width / 2.15
c. If the haul road is represented by alternating volume sources, yo = twice the adjusted
width, measured from the center point of the first volume source to the center of the next
represented volume source / 2.15
4. The initial vertical dimension = height of the volume source / 2.15
5. The release height = height of the volume source / 2. This represents the center point of the
volume source.
40 CFR Part 51, Appendix W6indicates that ISCST3 (EPAs current model) and AERMOD
(EPAs proposed model) are the guideline models for short-term dispersion model analyses and
the ISC Users Guide, Volume 2 indicates that line sources, such as haul roads, can be modeled
with either volume or area sources.7
Mr. Richard Daye, EPA Region 7, references a study performed in December 1995 that found
model performance treating roadways as area sources is indistinguishable from modelperformance using volume sources.8 In addition, Mr. Daye notes the mathematical approach of
the area source is more defensible than volume sources in this situation. The volume source
algorithm uses the virtual distance approach for both the initial vertical and initial horizontal
dimensions, which is known to provide biased results in some circumstances.9
The federal and state guidance provided here was used in conjunction with current haul road
studies to develop the set of methodologies presented in this paper.
5Texas Commission of Environmental Quality (TCEQ) Air Quality Modeling Guidelines, RG-25 (Revised).
February 1999.6Chapter 40 Code of Federal Regulations Part 51 Appendix W.
7Users Guide for the Industrial Source Complex (ISC3) Dispersion Models, Volume II Description ofModel Algorithms. EPA-454/B-95-003b, Addendum, February 2002, Page 1-47 and 1-50.
8Modeling Fugitive Dust Impacts From Surface Coal Mining Operations Phase III. EPA-454/R-96-002,
December 1995.9Telephone Correspondence between Mr. Richard Daye, EPA Region 7, and D. Wilson and D. Doll.
July 2, 1997.
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CURRENT HAUL ROAD STUDIES
NSSGA sponsored PM10 emission factor tests at two aggregate facilities in Georgia. The tests
were performed by Air Control Techniques, P.C. in an effort to develop an equation that can
accurately quantify PM10
emission factors for aggregate facility haul roads. The data gathered
in this study were combined with previously gathered data to derive an industry specific haul
road emission factor equation. This study will be referred to as the January 2002, Haul Road
Emission Factor Test Program.10
Haul Road Emission Factor Test Program Background
The tests were performed at the Lafarge/Blue Circle plant in Cumming, Georgia and the Martin
Marietta Aggregates, Inc. plant in Forsyth, Georgia. The haul roads selected for the tests were
chosen based on maximum haul road traffic.
Air Control Techniques, P.C. used an upwind/downwind profiling system to measure PM10
emissions from the haul roads. Four PM10
ambient monitors were located on a 24-foot tower
16 feet from the downwind edge of the haul road. The PM10 ambient monitors were located at
the following heights: 5 ft, 10 ft, 15 ft, and 24 ft. One PM10 ambient monitor was located 16 ft
from the upwind side of the haul road. The upwind monitor was at a height of 10 ft. In
addition, meteorological monitoring stations were located at elevations of 6 and 30 ft on the
downwind side of the haul road. See Figure 2 for a depiction of the haul road PM10 ambient
monitor and meteorological monitor network.
A total of 20 one-hour tests were performed at each of the plants. The following parameters
were gathered for each test:
Road surface moisture content
Road silt content Road particulate size distribution
Number of truck passes along the haul road
Wind Speed
Wind Direction
Truck Speed
Production Data
Ambient PM10 Concentration (g/m3) for each monitor height (upwind and downwind)
10Haul Road Emission Factor Test Program for the National Stone, Sand, and Gravel Association. Air
Control Techniques, P.C., January 2002, ACTPC Job Number 707.
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FIGURE 2. UPWIND/DOWNWIND PROFILE SAMPLING SYSTEM11
The types and sizes of trucks that were present during each test were also recorded. The trucks
from both quarries were either 50 or 65 ton haul trucks with heights ranging from 14 feet
2 inches to 15 feet 2 inches.
Wet suppression was used for fugitive dust control of the haul roads at both facilities.
11Haul Road Emission Factor Test Program for the National Stone, Sand, and Gravel Association. Air
Control Techniques, P.C., January 2002, ACTPC Job Number 707, Page 5.
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Haul Road Emission Factor Test Program Implications on Modeling
Trinity reviewed the concentration and meteorological data collected for the haul road emission
factor test program to determine the concentration profiles of the plume generated by the quarry
haul trucks. If the behavior of the plume is understood, more accurate dispersion modeling input
parameters can be developed, such that more accurate modeled concentrations can be predicted.
Defining the Plume. A review of the downwind monitored concentration data (monitors
at 5, 10, 15, and 24 feet) revealed the following:
A plot of monitored concentration versus the height of the monitor revealed that the
concentrations were uniform with height. Further, the mean and standard deviation of the
monitored concentrations (four monitor heights) for each test run were calculated. It was
found that, on average, the standard deviation was less than 20 percent of the mean value for
each test at the Cumming quarry and less than 15 percent of the mean value for each test at
the Forsyth quarry. The data suggests that at the locations and heights of the monitors,
concentrations resulting from the plume were independent of height above ground, and do
not have a gaussian distribution in the vertical (z) dimension. Figures 3 and 4 provide plots
of concentration versus height for each run at the Cumming and Forsyth locations,
respectively.
During six of the twenty test runs at the Cumming Quarry, the wind was not blowing
towards the monitors during the time periods that the trucks were driving by the monitors.
Consequently, one would assume that there would have been a noticeable decrease in
monitored concentrations for those time periods. However, the monitored concentrations
for these situations were indistinguishable from the data obtained when the wind was
blowing towards the monitors. This data indicates that wind direction does not have a
measurable impact on the plumes dispersion at the locations and heights of the monitors,
and thus the concentrations in the plume are equivalent in the vertical dimension at the
locations of the monitors.
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FIGURE 3. CUMMING QUARRY DOWNWIND CONCENTRATION VERSUS HEIGHT
Cumming Quarry
Downwind Concentration vs. Height
0
20
40
60
80
100
120
140
5 10 15 20 25
Height (ft)
Concentration(ug/m3)
Series1Series2Series3
Series4Series5Series6Series7Series8Series9Series10Series11Series12Series13Series14Series15Series16Series17Series18
Series19Series20
FIGURE 4. FORSYTH QUARRY DOWNWIND CONCENTRATION VERSUS HEIGHT
Forsyth Quarry
Downwind Concentrations vs. Height
0
20
40
60
80
100
120
140
160
5 10 15 20 25
Height (ft)
Concentration(ug/m3)
Series1Series2Series3Series4Series5Series6Series7Series8
Series9Series10Series11Series12Series13Series14Series15Series16Series17Series18Series19Series20
The data from the upwind (10 foot) monitor was also reviewed and provided the following:
These data were very similar in magnitude to the downwind monitor concentrations. More
specifically, there was no statistically significant difference between the mean concentration
(average of four monitored concentrations, one from each height) calculated for a given run
using the downwind monitor values versus the upwind monitor concentration.
Over 25 percent of the time, the upwind monitor measured a higher concentration than any
of the four downwind monitors. This further substantiated that the wind direction was not
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impacting the monitored concentrations at the locations of the monitors. The data provides
that the plume generated is not measurably different in the horizontal or vertical dimensions
at least to a distance equivalent to the height off the tallest monitor (24 feet) and the distance
between the upwind and downwind monitors (82 feet).12 This type of plume behavior has
been defined as a cavity region.13 A cavity region is a region characterized by very chaotic
flow with considerable turbulence that is rapidly changing every few seconds. Cavity
regions are generated by mechanical turbulence and zones of turbulent eddies. The
development of such a region behind a haul truck could be explained by the turbulent eddies
created by the truck moving down the road.
Simulating the Plume. Now that the concentration profile behind the moving truck has beenestablished, one can determine the most representative method of simulating this type of plume
in the regulatory models, ISCST3 and AERMOD. According to the data reviewed above, the
plume resembles a cavity region with uniform concentrations in both the vertical and horizontal.
Cavity region calculations are usually discussed in terms of building downwash produced by
wind flow over and around buildings. Downwash of a plume due to wind flow over and around
buildings brings the plume down on the lee side of the building and recirculates the plume in theturbulent flow downwind of the building. A side view of this situation is provided as Figure 5.
Wind tunnel studies show that there is a cavity region directly downwind of the building
followed by a turbulent wake region before the flow returns to normal.
FIGURE 5. CHARACTERISTIC WIND FLOW PATTERNS AROUND AN OBSTACLE (SIDE VIEW)
Further, Figure 6 provides the view from above of flow patterns around a cube (similar to a
truck) exposed to a wind. The wind patterns are similar to those generated by a truck driving on
a haul road.
12Monitored concentrations at the 24ft level were the highest of the four downwind readings, 20 percent of
the time in both data sets, suggesting the cavity most likely extends further than 24 feet.13Dispersion of the recirculated cavity mass is based on building geometry and is assumed to be uniformly
mixed in the vertical.AERMOD: Description of Model Formulation. EPA-454/R-02-002d, October 2002.
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FIGURE 6. WIND PATTERNS RESULTING FROM WIND FLOW AROUND A CUBE (TOP VIEW)14
Algorithms to simulate building downwash have been incorporated into the ISCST3 and
AERMOD dispersion models. However, the algorithms do not take effect until the wake region.That is, the models do not perform cavity region calculations. Enhanced versions of ISCST3
and AERMOD that include the Plume Rise Model Enhancement (PRIME) can make cavity
calculations. These versions of the models are referred to as ISC-PRIME and
AERMOD-PRIME. The PRIME versions of the models have been proposed to be regulatory
guideline models but have not yet been approved.15
The plumes generated from haul roads appear to behave similar to plumes that are downwashed
on the lee side of a building. Downwash calculations in the models may only be made for point
sources, not area or volume source types. As such, the data suggests that the most representative
method of modeling emissions from haul roads is a continual series of point sources and
associated buildings. ISC-PRIME (Version 01228) was used to model a line of point sources
and structures to simulate emissions from the haul road. As there are an infinite number of
combinations of structure and point source combinations that could be used, dimensions of
14Atmospheric Science and Power Production, Technical Information Center Office of Scientific and
Technical Information United States Department of Energy. Page 250, 1984.15CALPUFF is a regulatory approved model that is commonly used for modeling of Class I impacts,
beyond 50 km. CALPUFF does incorporate the PRIME algorithms.
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measurable parameters were used as a starting point for the analysis. The parameters that were
fixed in the analysis included:
Buildings
Width = Road width (m) = 50 feet
Length: Assumed that a haul road length of 300 feet would be sufficient to minimize end
effects. Buildings were square and set end-to-end. Length of each = 300 feet divided by 6
buildings = 50 feet.
Point Sources
Diameter = Diameter of building = 50 feet Velocity = 0.001 m/s (simulating no vertical momentum) Temperature = Ambient (simulated by entering 459.6 F) Location = Centered in each building Emission Rate = Divided a unit emission rate (1 lb/hr) equally over 6 point sources = 0.167
lbs/hr each
To determine concentrations in the modeled plumes cross section, receptors were placed at a
distance of 16 feet from the source with flagpole heights varying in 0.1 meter increments from 0
meters to 10 meters (32.8 feet). Figure 7 describes the sources, buildings, and receptors
modeled.
The variables that remain include stack height and structure height. As there is no data to justify
using different heights for these variables, the assumption was made that the point source and
structure height should be equal. The point source and structure height (source height) were
then varied to determine the height that would result in a modeled concentration profile most
closely representing the monitored concentration profile. As described previously, the
monitored data provides the following:
Concentrations resemble a cavity region At a receptor located 16 feet from the edge of the structure, the standard deviation of the
modeled concentrations between ground level and 24 feet should vary by no more than 15 to20 percent of the mean value (referred to in this analysis as the Target Height).
A typical meteorological condition was established from the onsite data which included a wind
speed of 1.54 meters/second, an ambient temperature of 39 F (277 Kelvin), a stability class of
4, and a mixing height of 441 meters (which did not impact the analysis). To simulate the
source, the source height was first set to the actual average height of the truck (14.7 feet). The
modeled concentrations, provided as Case 1 in Table 1, resulted in a target height of 19.7 feet.
As this is less than 24 feet, the source height was increased to 15.7 feet, 16.7 feet, and 17.7 feet,
Cases 2, 3, and 4 respectively, until a modeled Target Height greater than 24 feet was found.
Finally, the source height was lowered to 17.5 feet, Case 5, such that the Target Height of
approximately 24 feet was achieved. These results are also provided in Table 1.
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FIGURE 7. HAUL ROAD MODELED AS A SERIES OF DOWNWASHED POINT SOURCES
Point Sources
(Circles)
Receptors
Buildings
(Squares)
TABLE 1. RESULTS OF SOURCE HEIGHT VARIABILITY IN ISC-PRIME
Case 1 Case 2 Case 3 Case 4 Case 5
Source & Building Height (ft) 14.7 15.7 16.7 17.7 17.5
Target Height (ratio of standarddeviation to the mean is 20%) ft
19.7 21.0 22.3 24.3 23.9
Ratio of modeled source height to
truck height (14.7 ft)
1.00 1.07 1.14 1.20 1.19
Table 1 provides that to recreate the monitored concentration profile resulting in both a cavity
height of 24 feet, and a ratio of standard deviation to the mean of 20%, a source release height to
truck height ratio of approximately 1.19 is necessary.
The results of modeling a haul road using the point source and building dimensions and relative
locations shown in Figure 7, as well as the source parameters for Case 5 in Table 1, are provided
in Figure 8 .
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FIGURE 8. MODELED CONCENTRATIONS RESULTING FROM A HAUL ROAD MODELED
AS A SERIES OF DOWNWASHED POINT SOURCES USING ISC-PRIME
0.00 5.00 10.00 15.00 20.00 25.00 30.00
X - Distance from source in meters
0.00
5.00
10.00
15.00
20.00
Z-Heightabovegroundinmeters
60
90
120
150
180
210
240
Ground level
Ratio of Standard Deviation to the Mean is20% at 24 feet (7.3 meters) above Ground
Point
Source
with
Structure
Figure 8 provides modeled concentrations versus height above ground and distance from the
source. Discrete receptors were placed at distances ranging from 0 meters to 30 meters from the
source, with flagpole receptor heights varying from 0 to 20 meters above ground.
Although the proposed method will represent the monitored concentrations, additional studiesare suggested with monitors located at heights greater than 24 feet as well as distances greater
than 16 feet from the source. Visual observations by the authors would suggest that the cavity
region may extend to twice the height of the truck.
As the PRIME versions of ISCST3 and AERMOD are not yet approved by all regulatory
authorities, methods for modeling haul roads using the current versions of ISCST3 or AERMOD
are also being provided. Although volume and area sources have gaussian concentration
profiles, they are more representative of a haul road plume than a point source without
downwash cavity calculations. As such, volume and area source types have long been the
suggested method for modeling haul roads as was stated above in the summary of regulatory
guidance available. Traditionally, a volume source was used to model haul road concentrations
because until version 3 of the ISCST model was released in 1995 there were significant flaws
with the area source algorithm. Some states have retained this methodology. With the
flexibility available in defining area source size parameters, area sources have become a popular
method of modeling haul roads. In addition, EPA has demonstrated that modeling haul roads as
an area source results in the same model performance as modeling them as a volume source.16
16Modeling Fugitive Dust Impacts From Surface Coal Mining Operations Phase III. EPA-454/R-96-002,
December 1995.
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Using either an area source or a volume source, the source should initially be defined to
encompass the cavity region created by the haul truck. The data reviewed in this study indicates
that the cavity is at least 24 feet in the vertical and 82 feet in the horizontal.
When using either the area or volume source types, the release height must also be specified. In
this case, the data alone does not reveal what this height should be. Absent quantifiable data,
video and photographs of quarry haul roads using similar trucks were reviewed to determine if
any indication of a point of maximum concentration could be determined. The photos suggest
that at a given point, the plume is in the shape of a sphere centered in location at a height of
approximately the height of the truck. The visual data also appears to support the conclusion
that the particulate emissions are equally mixed in the plume (cavity region) as the opacity of the
plumes appear constant throughout the sphere. Consequently, a release height of the center of
the sphere, or cavity, is suggested, which in this case is the average truck height (average of 14.2
and 15.2 feet = 14.7 feet). Figure 9 shows the cavity as defined by the monitored data.
FIGURE 9. CAVITY REGION CREATED BY MONITORED HAUL TRUCKS
4.3 z = 29.4 ft
Average Release Height =
14.7 ft
4.3 y = 82 ft
TCEQ guidance suggests that the plume thickness (height) be calculated as twice the height of
the vehicle generating the emissions (2 14.7 feet = 29.4 feet = 9.0 meters) rounded to the
nearest meter (9 meters).
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Since the monitoring data clearly shows that the cavity extended much farther than twice the
truck width in the horizontal direction, it is reasonable to assume that had monitoring data been
available at 29 feet or higher, it would have been proven that the cavity would have extended to
at least 29 feet. Consequently, it is suggested that the plume thickness be estimated as at least
twice the truck height until additional data becomes available.
The initial vertical dimension (zo) would then be determined by the following equation:
Plume Thickness (feet) = 2 height of haul truck in feet
zo (feet) = Plume Thickness (feet) /4.3
= (2 height of haul truck in feet)/4.3
= (height of haul truck in feet)/2.15
Note that for a volume source, this is consistent with current ISC guidance17. That is, zo is
equal to the structure (truck) height / 2.15 for a source on or adjacent to a structure (truck).
Proposed source parameters for characterizing haul roads as either area sources or volumesources are as follows:
Area Source (ISCST3/AERMOD)
Adjusted haul road width (feet) = Width of haul road (feet) + 32 feet
zo (feet) = (2 height of haul truck in feet)/ 4.3
Release height (feet) = height of haul truck in feet
Location = Area source centered on coordinates of the actual haul road.
Volume Source (ISCST3/AERMOD)
yo (feet) = (Width of haul road in feet + 32 feet)/4.3 zo (feet) = (2 height of haul truck in feet)/ 4.3
Release height (feet) = height of haul truck in feet
Locations = Series of volume sources centered on the haul road centerline, spaced width of
haul road in feet + 32 feet apart.
Figure 10 provides modeled concentrations versus height above ground and distance from thesource using the same meteorological data and receptors as used for Figure 8 as well as the
following model inputs:
Area source width = 82 feet (25 meters) Area source length = 300 feet (91 meters)
Total area = 24,600 ft2 Emission Rate (per unit area) = 1 lb/hr / 24,600 ft2 = 4.065 E-05 lbs/hr/ft2 Release Height = Average truck height = 14.7 feet (4.5 meters) zo = 2 Avg. truck height / 4.3 = 6.8 feet (2.1 meters)
17Users Guide for the Industrial Source Complex (ISC3) Dispersion Models, Volume I Users
Instructions. EPA-454/B-95-003a, Table 3-1, September 1995, Page 3-30
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FIGURE 10. MODELED CONCENTRATIONS RESULTING FROM A HAUL ROAD MODELED
AS AN AREA SOURCE
0.00 5.00 10.00 15.00 20.00 25.00 30.00
X - Distance from source in meters
0.00
5.00
10.00
15.00
20.00
Z-Heightabovegroundinmeters
60
70
80
90
100
110
120
130
Ground level
Ratio of Standard Deviation to the Mean is20% at 26.2 feet (8 meters) above GroundRatio of Standard Deviation to the Mean is
15% at 23 feet (7 meters) above Ground
AreaSource
As mentioned previously, based on the data available, the modeled source characteristics are
conservative estimates since the cavity region is likely to extend beyond the limits currently
measured in this data set, which would lead to larger adjusted widths and zo.
Comparing Figure 8 and Figure 10 visually reveals the difference between modeling a haul road
as a source initially existing as a cavity region using ISC-Prime versus a source with Gaussian
dispersion from the point of generation respectively. In Figure 8, there is a large region of
constant concentration whereas in Figure 10 the concentration is highest at the center and
decreases in all directions from this center line concentration.
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CONCLUSIONS
The following methods for modeling haul roads have been developed:
Point Source(s) with Building(s) (ISC-PRIME and AERMOD-PRIME)
Point Source Height (feet) = 1.19 Height of haul truck (feet)
Point Source Diameter (feet) = Series of point sources with overall length equal to the length
of the road. Each point sources diameter equal to the road width (feet). Point Source Velocity = 0.01 m/s (simulating no vertical momentum) Point Source Temperature = Ambient (simulated by entering 459.6 F) Point Source Location = Centered in building, with a separation distance such that the point
sources do not overlap Point Source Emission Rate = Divide emission rate equally over all point sources
Building Height (feet) = 1.19 Height of haul truck (feet)
Building Width (feet) = Road width (feet)
Building Length (feet) = Series of buildings with overall length equal to the length of the
road. Each buildings length equal to the road width (feet).
Area Source (ISCST3/AERMOD)
Adjusted haul road width (feet) = Width of haul road (feet) + 32 feet
zo (feet) = (2 x height of haul truck in feet)/ 4.3
Release height (feet) = height of haul truck in feet
Location = Area source centered on coordinates of the actual haul road.
Volume Source (ISCST3/AERMOD)
yo (feet) = (Width of haul road in feet + 32 feet)/4.3 zo (feet) = (2 x height of haul truck in feet)/ 4.3
Release height (feet) = height of haul truck (feet)
Locations = Series of volume sources centered on the haul road centerline, spaced width of
haul road in feet + 32 feet apart.
These source characterizations provide a methodology for re-creating the monitoring data from
the January 2002, Haul Road Emission Factor Test Program. NSSGA is planning to perform
additional monitoring studies. When this data becomes available, it should be incorporated into
the overall data set, and the conclusions should be re-evaluated to determine if refinements to
the proposed source characterizations can be made.