EPA450/3-74-036-a
June 1974
INVESTIGATION
OF FUGITIVE DUST
VOLUME I SOURCES, EMISSIONS
AND CONTROL
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Waste Management
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
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EPA-450/3-74-036-a
INVESTIGATION
OF FUGITIVE DUST
VOLUME I - SOURCES, EMISSIONS,
AND CONTROL
bv
George Jutze and Kenneth Axetell
PEDCo Environmental Specialists, Inc. JUN 111986
Suite 13 Atkinson Sauare
Cincinnati, Ohio 45246
O.S.EPUE6iONV,AMD
Contract No. 68-02-0044
Task Order 9
Proaram Element No. 412953BDD1
EPA Project Officer: David R. Dunbar
Prepared for
ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Waste Manaqement
Office of Air Quality Planning and Standards
Research Triangle Park, N. C. 27711
June 1974
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This reoort is issued by the Environmental Protection Aqencv to
report technical data of interest to a limited number of readers.
Copies are available free of charge to Federal employees, current
contractors and grantees, and nonprofit organizations - as suonlies
permit - from the Air Pollution Technical Information Center,
Environmental Protection Agency, Research Triangle Park, North Carolina
27711, or from the National Technical Information Service, 5285 Port
Royal Road, Springfield, Virginia 22151.
This report was furnished to the Environmental Protection Agency by
PEDCo Environmental Specialists, Inc., Cincinnati, Ohio 45246, in
fulfillment of Contract No. 68-02-0044. The contents of this report
are reproduced herein as received from PEDCo Environmental Soecialists,
Inc. The opinions, findings, and conclusions expressed are those of
the a,uthor a"nd'#ot necessarily those of the Environmental Protection
Agency. "Mention of company or product names is not to be considered
as an endorsement by the Environmental Protection Agency.
Publication No. EPA-450/3-74-036-a
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ACKNOWLEDGMENT
Many individuals and organizations have been helpful
in developing this report; for these contributions the project
management extends its sincere gratitude.
The contributions of Messrs. Bruce Scott of the Arizona
Division of Air Pollution Control; Donald Arkell and Jeanette
Smith of the Clark County Health Department; Norm Covell and
Dan Dobrinen of the Fresno County Air Pollution Control
District; Robert Taylor and Grant Johnson of the Maricopa
County Health Department; Richard Serdoz of the Nevada Bureau
of Environmental Health; David Duran of the New Mexico
Environmental Improvement Agency; John Ensdorff and Willian
Griffith of the Pima County Air Pollution Control District;
Harry Davidson of the Albuquerque Department of Environmental
Health; David Howekamp of EPA's Region IX; Gary Bernath of
EPA's Region VI; Edward Li His of EPA's Control Programs
Development Division and a dedicated group of technical
specialists in EPA, SSPCP, were of particular significance.
Mr. David Dunbar, Environmental Protection Agency, served
as project officer, and Mr. George A. Jutze, PEDCo-Environmental
Specialists, Inc., the project manager, assisted by Messrs.
Kenneth Axetell, who directed the investigative program and
William Parker, who implemented the field effort.
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TABLE OF CONTENTS
Page
1. 0 INTRODUCTION 1-1
2.0 SAMPLING PROGRAM 2-1
2.1 Description of Sampling Conduct 2-1
2.2 Beta Gauge Measurements of Dust from
Unpaved Roads 2-2
2.3 Results 2-6
3.0 FUGITIVE DUST EMISSIONS IN THE SIX AIR
QUALITY CONTROL REGIONS 3-1
3.1 Derivation of Emission Factors 3-1
3.2 Survey Procedures and Techniques 3-15
3.3 Results 3-20
3.4 Distribution of Emissions within
Counties 3-23
3.5 Background Particulate Levels 3-25
4.0 CONTROL TECHNIQUES 4-1
4.1 Research Procedures 4-1
4 .2 Findings 4-2
4.3 Control Techniques by Source Category. 4-7
4.4 Estimates of Control Efficiencies .... 4-20
4.5 Control Cost Data 4-28
5.0 SUMMARY 5-1
Appendix A. References and Bibliography
Appendix B. Field Operations Manual
Appendix C. Data Forms
Appendix D. Diffusion Calculations
Appendix E. Wind Erosion Equation
Appendix F. Fugitive Dust Emission Summaries
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1.0 INTRODUCTION
Implementation plans for five Air Quality Control Regions
in the States of New Mexico, Nevada, Arizona, and California
failed to demonstrate achievement of primary and secondary
suspended particulate air quality standards. In addition, the
Albuquerque - Mid Rio Grande AQCR was included in the investiga-
tion since emissions from unpaved roads were identified in the
SIP. A preliminary investigation by EPA indicated that all six
of these AQCR's were arid areas with widespread fugitive dust
problems, and that this fugitive dust either had not been con-
sidered in the implementation plans or was poorly quantified in
particulate control strategy evaluations.
PEDCo-Environmental was asked to determine the fugitive dust
sources having a major impact on particulate levels and to in-
vestigate control techniques and regulatory approaches which
would result in attainment of the air quality standards. The
resulting project was divided into three phases, which could be
characterized as design, data collection, and strategy develop-
ment and testing.
In Phase I, significant fugitive dust sources in the
four-state study area were identified and sampling studies
were designed to better quantify their relative contributions.
This information was submitted for EPA review in the Phase I
report on July 14, 1972. In brief summary, three fugitive dust
sources were found to have regional impacts — unpaved roads,
agriculture, and construction activities — and several others
were found to create significant localized sources of particulate
Only the three major sources were investigated in the sampling
studies. A total of seven field sites in the four states were
established, with three specifically for unpaved roads, two for
agriculture, and two for construction. Figures 1-1 through 1-7
present the site characteristics and sampling locations.
1-1
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Phase II was composed of three distinct areas of data
collection performed concurrently:
1. conduct of field sampling at the seven sites to
generate source impact data;
2. survey of the six AQCR's to determine the number and
extent of their fugitive dust sources, from which to
estimate emissions; and
3. investigation of feasible control techniques for
fugitive dust, including the approximate efficiencies
of the controls.
The description and presentation of results for each of these
data collection efforts comprises a separate section of this
report.
1-2
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o
z
N
CORTARO FARMS RD
X XX
XX
X XX
LAMBERT LAN';
tgn i n in 4 base
SUMTER DR
1' c h i p i e a 1
OVERTON RD (paved )
Figure 1-2
THORNYDALE ROAD SITE
_JL, . J
2 3 *
SCALE, 1000 FT
X = iomplinq station
1-4
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MAIN ST
Univ of An zona
Exper i menta I Fc
BROADWAY AVE
n
posture
SOUTHERN RD
J
N
Mesa Community
College
T.
O
wl
10
O
O
agr rcu I turol test lite
BASELINE RD
farmland
Figure 1-4
MESA AGRICULTURAL STUDY
1 2 3
SCALE 1000 FT
X - sampling it o 11 on
1-6
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2.0 SAMPLING PROGRAM
The designs of the seven sampling studies were presented
in detail in the Phase I report. Sampling configurations and
other pertinent data are presented in the Appendix. Readers
are referred to that document for additional specifics, which
are not repeated here. This section does discuss occurrences
and changes during the sampling period and the results of the
sampling study.
2.1 Description of Sampling Conduct
All of the studies had the same sampling schedule of
32 periods between August 21 and October 22. Half of the
sampling periods were 48 hours and half 24 hours. The longer
periods were used to get sufficient loadings on the Andersen
filters for accurate weighing.
Sites were maintained by local agency personnel. For
the two sites in Tucson and the one in the San Joaquin Valley,
temporary technicians were hired by PEDCo-Environmental
to provide additional manpower. These temporary personnel
worked under the supervision of the respective local agencies.
A field operations guidebook was prepared by the project staff
to assist the personnel maintaining the sites in solving
any problems and to insure uniformity of operation. A copy
of the guidebook, which includes the sampling schedule and
many of the details of sampling conduct, is shown in Appendix B,
The operators also kept daily activity logs of pertinent
happenings on the sites for later comparison with sampling
and meteorological data. In addition to their primary purposes
of assisting in development of emission factors and estimation
of control efficiencies, these logs helped to explain anomalies
in the data by providing a record of external effects on the
readings (e.g., burning on nearby land). The logs were useful
in emission impact evaluation in differentiating between days
with activity on site and those in which only wind erosion
2-1
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contributed to emissions. The records also pointed out
specific activities or equipment which caused high dust
emissions. Copies of activity log forms are shown in
Appendix C.
All samples were returned to PEDCo's Cincinnati
laboratories for analysis to insure uniformity and quality
control. Lab work included the weighing of hi-vol and
Andersen filters, particle counts and microscopic analysis
of impaction plates, and reduction of meteorological data.
Standard analytical procedures were used in all cases.
2.2 Beta Gauge Measurements of Dust from Unpaved Roads
The beta gauge airborne dust sampling/readout instrument
developed by GCA was used in this study because of its ability
to measure low and intermediate concentrations of dust (in
the range of 100 to 50000 yg/m3) with short measurement
periods. Theee features plus its portability permitted samples
to be taken at several points downwind in the plume generated
by regulated traffic on an unpaved road. Specifications
for the beta gauge instrument are shown in Appendix B.
Samples were taken at varying distances from the road and
heights above grade. Data from the two-day study are
summarized in Table 2-1.
In analysis of the data, the assumption was made that
heavy traffic (five vehicles per minute) across an unpaved
road approaches the condition of a continuously-emitting line
source. The original intent was to estimate the plume height
at each sampling location and, together with measured wind
speeds and vertical particulate concentrations, calculate
the total particulate emissions per unit length of road at rhis
distance fron the road. Comparison of apparent emission
2-2
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values obtained at increasing distances from the road would
give a particulate fallout rate which would hopefully
approach zero, leaving only suspended particulate emissions
in the desired emission factor. The value could easily be
converted from emissions per unit time per unit of roadway
length to emissions per vehicle-mile, since traffic counts
were taken during the measurements. The sampling plan is
explained in detail in Appendix B.
After unsuccessful attempts to delineate the vertical
boundary of the plume by photography, transit measurements,
and visual comparison with fixed markers (on telephone poles),
the plan was modified to the use of a diffusion equation for
an infinite line source to relate the beta gauge measurements
with estimated emissions. This analytical procedure proved
quite successful. Its application is explained in section 3.2
of this report as part of emission factor derivation.
Use of any non-standard technique for sampling or analysis
should be accompanied by a calibration or control study in
which the non-standard technique is compared with the standard.
One-hour hi-vol measurements were taken at some of the same
locations which were sampled by the beta gauge. For ten
comparative readings throughout the study, the hi-vol measure-
ments averaged 1.68 times the beta gauge readings and the
correlation coefficient between the data sets was 0.87. These
values are considered excellent agreement because: (a) the hi-vol
samples a wider range of particulate sizes, especially of larger-
sized, heavier particles, so would be expected to sample a heavier
weight in the same plume; and (b) the beta gauge measurement
was taken during only a small part of the period required to
collect the hi-vol sample; therefore, a large part of the
2-5
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variation noted in the correlation coefficient of 0.87
could be attributed to differences in average source strength
between the short and long sampling periods.
Several field observations also indicated a good
reproducibility of readings by the beta gauge. This could
not be put to a statistical test, however, since no area of
uniform particulate concentration was available.
In addition to development of an emission or impact
factor, the purpose of this study was also to investigate
the relationships between emissions and vehicle speed and
between emissions and traffic volume. When average emission
values calculated for four different speeds were plotted
against those speeds, curve-fitting indicated a non-linear
relation of the nature anticipated. The equation for the
curve is presented in section 3.2. However, the expected
linear relationship between emissions and traffic volume was
not well demonstrated by the data, apparently because of the
narrow range of traffic densities during the study.
2.3 Results
A very large number of measurements, encompassing
instrumental, observed, physical, and analytical were made
during this investigation. Raw data tabulations or listings
of the following items are in the Project File:
0 Suspended Particulates (Regular and Directional) by
High-Volume Filtration
0 Suspended Particulate Fractionation by the Andersen
Modification to High-Volume Filtration
° Wind-Blown Particulates by Adhesive Impaction
0 Wind Velocity and Direction by Continuous Windvane/
Anemometer Sensors
0 Site Activity Logs.
2-6
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Since the information noted above was collected: (1)
to develop source-impact or emission rate factors, and,
(2) to define the efficiency of specific control techniques,
it is not advisable nor warranted to attempt any detailed data
summarization. However, in order to provide a general indi-
cation of suspended particulate levels encountered, several
brief summaries have been prepared. These presentations
must be qualified by noting that the data base is insufficient
to establish either regional or community representative levels
Table 2-2 lists the average maximum and minimum values
for suspended particulates from those stations where at least
twenty-five samples were collected. Table 2-3 presents the
average percentage of "non-respirable" suspended particulates
(>3.3 microns) and "respirable" suspended particulates
(<3.3 and >O.I microns) found in each sampling site area.
2-7
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TABLE 2-3
FRACTIONATED SUSPENDED PARTICULATE MEASUREMENTS BY
SAMPLING AREA FOR THE PERIOD
AUGUST 21 - OCTOBER 22, 1972
SAMPLING
AREA
Irvington Rd .
Thornydale Rd.
Treatment Plant Rd.
Paradise Valley
Las Vegas
San Joaquin
Mesa
S.P. > 3.3 MICRONS
(NON-RESPIRABLE)
63%
64%
52%
64%
56%
63%
62%
S.P. < 3.3 MICRONS
(RESPIRABLE) *
37%
36%
48%
36%
44%
37%
38%
* As Measured by Andersen Fractionator
2-9
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3.0 FUGITIVE DUST EMISSIONS IN THE SIX AIR QUALITY CONTROL
REGIONS
A reliable estimate of the quantity of particulate
emissions from fugitive dust sources is a prerequisite to
any analysis of the controls needed to achieve air quality
standards. An effective and equitable control strategy
requires knowledge of (1) the relative contribution of fugitive
dust compared to particulate emissions shown in a conventional
emission inventory and (2) the relative impact of individual
fugitive dust source categories amenable to control. However,
estimation of fugitive dust emissions is not easily accomplished
for several reasons:
0 The sources are not well defined in area or duration of
emission; some are temporary and others are seasonal in nature.
0 Meteorological conditions, themselves quite variable,
cause large variations in emission rates due to factors such
as periods between rainfall and frequency of high wind speeds
and atmospheric turbulence.
0 Emission rate is a function of the soil or material
texture of the surface becoming airborne.
0 Emission factors for most sources are not available.
0 Fugitive dust emissions are indistinguishable from
naturally-occurring dust (background) and are often emitted
as a result of the same force—wind erosion.
The survey described in this section has attempted to
produce the most accurate emission estimates possible within
the constraints of the technical limits just discussed
and the accuracy of other input data. Survey procedures
developed especially for this project are explained in detail.
3.1 Derivation of Emission Factors
As previously mentioned, field sampling studies and
derivation of widely applicable emission factors were not
3-1
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'* ;*r' -Pv^S^g^^ff*;'
central to the primary purpose of this project—the development
of fugitive dust control regulations capable of achieving
particulate air quality standards in six Southwest AQCR's.
Therefore, both of these efforts were pursued only to the
minimum extent necessary to produce emission estimates
comparable in accuracy with other evaluation tools. Approaches
used in developing appropriate emission factors for six fugitive
dust source categories are described below
and the resulting factors are summarized in Table 3-1.
Unpaved Roads. The final emission factor for unpaved
roads evolved from the beta gauge sampling of dust plumes in
Santa Fe and was verified by the results of hi-vol sampling at
the two unpaved road sites in Tucson.
First, the individual beta gauge sampling points shown
in Table 2-1 were substituted into Sutton's equation
for continuously emitting infinite line sources, as shown in
the Workbook for Atmospheric Dispersion Estimates,
the emission rate (q) of fugitive dust:
(57)
to calculate
X (x,y,0;H)
3
X (g/m )
q (g/m/sec)
o (meters)
L.i
u (m/sec]
TT a u
z
sin
exp
, where
= measured concentration of particulates at
x (meters) from the road and a height H
(meters) above the road
= source emission strength per unit of road
length
(degrees) = angle between wind direction and line source
= vertical dispersion coefficient of plume
concentration (a function of stability class
and downwind distance from source)
- mean wind speed affecting the plume.
3-2
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Table 3-1
EMISSION FACTORS USED IN FUGITIVE DUST
EMISSION SURVEY
SOURCE CATEGORY
EMISSION FACTOR
Unpaved Roads
Agriculture
Construction
Tailings Piles
Aggregate Storage
Cattle Feedlots
3.7 Ib/vehicle mile
None - used wind erosion equation to
estimate emissions
1.4 tons/acre/month of active
construction
4 to 16 tons/acre/year, depending
on climatic factor
10 Ib/year/ton for fine sand
1.5 Ib/year/ton for crushed rock or
gravel
8 tons/year/1000 head
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The diffusion calculations for 32 valid data points at
four different average vehicle speeds are shown in Appendix
Table D-l and the results are summarized in Table 3-2 below.
In these calculations, an initial (x = 0 meters) vertical
dispersion coefficient of •=—^ = 1-4 meters was assumed to
be created by the vortex of the passing vehicle, and e C
stability class was estimated from observed weather conditions
during both days of the sampling.
An equation was derived which expressed the relationship
between vehicle speed and emission rate over the range of
speeds investigated. Based on the results of some previous
work with dust emissions from tractors as a function of tractor
(23)
speed and the approximate linearity of the four data points
when plotted on semi-log graph paper, an equation of the form
E = a b was tested. The curve of best fit was:
E = (0.16) (1.068)X, where
E = dust emissions, Ib/vehicle mile
x = vehicle speeds, mph.
Solving this equation for x = 30 mph, an emission rate
of 1.15 Ib/vehicle mile was established. However, these mass
measurements were all taken with the beta gauge, which samples
a narrower range of particle sizes than the hi-vol sampler on
which the particulate air quality standards are based. As
the next step in developing the emission factor, concurrent
hi-vol samples taken at the same location as some of the beta
gauge samples (see Table 2-1) were used to determine
the ratio and correlation between readings of the two types of
particulate samplers. The hi-vol readings averaged 1.68 times
the beta gauge readings, with a correlation coefficient of
r = 0.87. Therefore, the equation of emissions versus speed
in hi-vol equivalents became
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TABLE 3-2
SUMMARY OF EMISSIONS FROM UNPAVED
ROADS AT DIFFERENT VEHICLE SPEEDS
Average vehicle
Speed, MPH
No. of ' Emissions,
Samples . g/m/sec
15 i 6
25
35
6
15
40 5
; 0.0064
' 0.0159
i
.! 0.0335
0.0570
I Emissions, •
Ib/veh-mi .
1 0.48 ;
0.70
: 1.47 ;
2.50 i
3-5
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E - (0.27) (1.068)X,
and the emission rate at x = 30 mph increased to 1.94 lb/
vehicle mile.
The above approach considered fugitive dust in the plumes
caused by vehicular traffic, but not that from wind blowing across
the exposed unpaved road surface. In order to determine whether
wind erosion losses were significant in comparison with dust
created by traffic, calculations employing the wind erosion
equation (see Appendix E) were used. The following average con-
ditions were assumed in solving the equation:
road width = 25 feet (equal to 132,000
square feet per mile of
road, or 3.0 acres)
V, vegetative cover = 0
K, roughness factor = 1.0 (no ridges)
C, climatic factor = 80
L, unsheltered wind distance = 300 feet
I, soil erodibility = primarily (70%) loams and
sandy clay, with some (30%)
sandy loams and clays
ADT, average daily traffic
on unpaved roads
for all 6 AQCR's) = 32 vehicles
The suspended wind erosion losses were calculated to be
3.0 tons/acre/year, or 9.0 tons/mile/year. Since this number
was not additive with that from vehicle plumes, it was divided
by a value representing average traffic volume (32 x 365) to
yield a corresponding factor of 1.54 Ib/vehicle mile.
The two partial emission factors, when added, gave a
combined emission rate of 3.7 Ib/vehicle mile. On an unpaved
road with average traffic volume, dust plumes from vehicles
accounted for 58 percent of this total and wind erosion caused
the remaining 42 percent. The value of 3.7 lb'vehicle mile
was used to estimate emissions from unpaved roads in all six
AQCR's.
3-6
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This factor was confirmed by comparison with estimates
made using a similar approach with data from the 24- and 48-
hour hi-vol samples at the two unpaved road sites in Tucson.
While these sampling studies in Tucson were designed primarily
to evaluate the effectiveness of surface treatment and chemical
soil stabilization in reducing fugitive dust, the untreated
control sections did provide some data that could be input
into the continuous line source diffusion equation described
above. Under selected conditions of steady winds approximately
perpendicular to the road and no unusual weather or traffic
conditions indicated during the sampling period, values for "q"
in g/m/sec (or Ib/mi/day) were calculated. since average daily
traffic counts on the test sections were available, the emission
rate factor could then be converted into units of Ib/vehicle
mile. The values resulting from these diffusion calculations
included the impact of both vehicle plumes and wind erosion on
the unpaved surface, because the samples were taken over a 24-
or 48-hour period rather than for only a few minutes.
Eleven valid samples taken at the Irvington Road site
indicated an average emission rate of 4.0 Ib/vehicle mile, with
a standard deviation of + 1.7 Ib/vehicle mile. Diffusion
calculations with samples from Thornydale Road showed higher
average emissions and the same variation: 6.0 + 1.7 Ib/vehicle
mile. Both of these results are considered to be in excellent
agreement with those from the beta gauge study and appear to
show substantial uniformity in emission rates from unpaved
roads in different geographical locations and with differing
traffic patterns. Data and calculations used in arriving at
the values reported here are presented in Appendix Tables D-2
and D-3.
Agriculture. The wind erosion equation was selected as
the method for estimating particulate emissions frorr croplands
3-7
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because of the large number of variables it considered (and
for which data could be collected) and because of the great
amount of research and sampling data that had gone into its
development. "Equation" is actually a misnomer for chis
estimation technique, which involves interpolation of data
from curves shown on a system of approximately 90 graphs rather
than solution of a single equation or series of equations.
While mathematical expressions have been developed to describe
the relationships between individual variables, these become
too complex when all the variables are combined. Variables
considered by the wind erosion equation are soil type and
erodibility, surface roughness, average wind speed, surface
soil moisture, unsheltered distance across fields along the
prevailing wind erosion direction, and vegetative cover. A
description of the equation and its use, including a condensed
set of the curves, is presented in Appendix E.
Of prime importance to the resulting emission estimates
was the assumption that an average of 2.5 percent of the
indicated wind erosion soil losses (product of the wind erosion
equation) became suspended particulate. Data in several
publications(7'12'16) and interviews with persons
instrumental in developing the wind erosion equation revealed
that the portion of soil loss that became suspended was relatively
independent of the soil type and almost always within the range
of 1 to less than 10 percent. The decision to use 2.5 percent
was made after review of this available data and evaluation of
emission estimates from several preliminary calculations.
The wind erosion equation outputs multiplied by 0.025
produced the factors for agricultural fugitive dust emissions
in tons/acre/year, which could then be multiplied by crop
acreage to get total emissions. Since different crops vary in
soil preparation practices (surface roughness), average field
size, and vegetative cover, a procedure of determining separate
3-i
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factors for each crop was adopted in this project. Similarly,
separate soil types and climatic conditions were determined
for each county. Therefore, no single emission factor for
agriculture emerged from the study, but individual calculations
for each major crop in each county.
Data from the agricultural study sites were used to confirm
the emission estimates of the wind erosion equation. Particulate
concentrations from 24- and 48-hour hi-vol samples were
substituted into a diffusion equation for ground-level sources
with no effective plume rise to estimate the emission source
strength corresponding to the measured concentrations. The
Pasquill-Gifford equation, from Workbook for Atmospheric
Dispersion Estimates, was of the form
Q = 2.78TT0ya2 u XXf0,0f0, where
Q (g/sec) = continuous emission rate from the ground-
level area source
a (meters) = horizontal dispersion coefficient of plume
^ concentration (a function of stability class
and downwind distance from source)
a (meters) = vertical dispersion coefficient of plume
z concentration (a function of stability class
and downwind distance from source)
u (m/sec) = mean wind speed affecting the plume
X (g/m ) = measured concentration of particulates at x
(meters) from the edge of the area source
The constant 2.78 was included in the equation to account
for decreases in measured concentrations associated with
sampling periods longer than the 3-minute period on which the
diffusion equation was based (reference: Workbook, pages 37-38).
Particulate concentrations used were the difference between
upwind and downwind directional hi-vol samplers and are there-
fore thought to represent only the contribution from the crop-
3-9
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land between the samplers or a half-mile radius semicircle,
whichever is smaller in area. This procedure was adopted
because of the difficulty in assigning a specific impact
source area surrounding a hi-vol in a predominantly agricultural
sampling area. The semicircular area source configuration
resulted from the 180° wind direction arc in which the hi-vol
samplers were activated. A half-mile radius semicircle contains
approximately 500 acres.
On four selected sampling days with a high percentage of
the winds in line with the upwind-downwind directional samplers
and no unusual local farming activities or weather conditions,
the site in Fresno County (San Joaquin AQCR) had a calculated
emission rate of 8.55 grams/second, or 298 tons/year. If
these emissions were assumed to emanate from 500 acres of active
cropland then the corresponding emission factor would be 0.6
tons/acre/year. The standard deviation associated with this
factor would be +0.2 tons/acre/year. Using this same procedure
for four selected sampling periods at the agricultural site in
Maricopa County (Phoenix-Tucson AQCR), the estimated emission
rates were 2.1 + 1.7 tons/acre/year. The data and calculations
for these emission factors are shown in Appendix Table D-4.
For purposes of comparison, application of the above factors
in their respective counties yields annual emission estimates
of 532,000 tons in Fresno County and 859,000 tons in Maricopa
County. Estimates using the wind erosion equation were
117,300 and 175,000 tons, or 22 and 21 percent, respectively.
A possible explanation for the apparent overprediction of the
emission factors is their failure to consider the greatly
reduced emissions from the high percentage of active farmlands
rhat are planted in alfalfa and other grass or hay crops which
maintain continuous ground cover. Both of the agricultural
sampling sites were primarily mature row crops or freshly
cultivated land. The differences in emission factors between
1-10
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the two sites also emphasizes the non-uniformity of emissions
from agricultural sites and the need to use a more comprehensive
technique than multiplication by a single, constant emission
factor.
The wind erosion equation does not account for fugitive
dust from the working of farm implements in the fields. No
direct sampling was done for this source, either. An article
( 2 "3 )
published in the USSR indicated that soil loss from a
deep loosener following a caterpiller-type tractor in the final
loosening of the soil was related to tractor speed as follows:
Q (gm/sec) = (45)(1.28)v, where
v (km/hr) = tractor speed.
At 5 km/hr (3 mph), and assuming a tracking width of 20 feet
and 2.5} percent of the soil losses remaining suspended, the
estimated emissions are 4 .2Ib/acre/pass. If 10 passes per
year are required to properly prepare and maintain the cropland,
then total emissions would still be less than 0.02 tons/acre,
or relatively insignificant compared to wind erosion losses.
Construction. The Pasquill-Gifford diffusion equation
for ground-level sources was also employed to determine the
emission rate from construction sites. The approach of sub-
tracting the upwind hi-vol reading from the downwind measurement
was again used to isolate the fugitive dust contribution of
the construction site. For the relatively well defined
boundaries of the construction site, there was no need to use
directional samplers or to otherwise assume an area of source
impact as there was with agricultural emissions; the entire
acreage of active construction was taken as the source emission
area.
At the Las Vegas sampling site, four sets of data taken
under acceptable wind conditions gave an average source
strength of 97 tons/month of active construction. This site
3-11
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was approximately 100 acres in area, so the resulting emissions
per unit area where 1.0 tons/acre/month. The factor was based
on a monthly rather than an annual time span so that potential
users would be aware that the emissions were related just to
the active construction period. For 12 selected sampling periods
at the construction site in Maricopa County, tne average
emissions and standard deviation were 164 + 160 tons/month.
The large standard deviation was expected because of the great
variations in emission intensity from different phases and
operations at the construction site. The active area under con-
struction at this location was 90 acres, with a corresponding
emission factor of 1.8 tons/acre/month. The two derived values
appeared consistent with each other for such a variable operation
as construction. An average of the two values — 1.4 tons/acre/
month — was taken as the final emission factor. The diffusion
calculations for tne construction activities are shown in
Appendix Table D-5.
The possible application of the wind erosion equation to
verify the value obtained from diffusion estimates was rejected
since most of the emissions from the construction site are
produced by earthmoving equipment and heavy traffic on exposed
earth, not from wind erosion.
Tailings Piles. Although many studies have been conducted
to determine the effectiveness of various control methods in
reducing fugitive dust losses from tailings piles, apparently
none of them have included an evaluation of effectiveness by
sampling for suspended particulates. Tailings piles were not
one of the sources selected for sampling, so no usable data
is-as generated in this project. Since tailings pile emissions
are caused by wind erosion across the flat, exposed surface,
it was judged that the wind erosion equation could predict
these emissions with some accuracy.
3-12
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The average characteristics assigned to tailings in
order to quantify the equation were: sand and loamy sand
soils with possible fines for surface cementation; a smooth,
unridged surface; no vegetative cover; an unsheltered length
of 2000 feet; and a climatic factor dependent on the
geographic location of the tailings pile. Due to the extreme
erodibility of fines in sandy soils, it was assumed that 10
percent of the soil loss estimated by the wind erosion
equation became suspended. Based on published data on
/ "] Q \
surface crusting, an 80 percent reduction in emissions
was used when the tailings were observed to naturally form a
well crusted surface.
The emission factors in tons/acre/year for a wide range
of climatic factors is presented in Table 3-3. If C values
are not available for the particular geographic area where
a tailings pile is located, it can be estimated as follows:
v3
C = 34.5 (pE)2 f where
V = mean annual wind velocity in mph corrected
for standard height of 30 feet
PE = yearly sum of monthly precipitation minus
potential evaporation totals , inches
TABLE 3-3
EMISSION FACTORS FOR TAILINGS PILES
Climatic Factor
30
40
50
60
70
80
90
100
120
Emissions ,
tons /acre /year
4
5
6
8
9
10
12
13
16
.0
.3
.6
.0
. 5
.5
. 2
.3
.0
3-13
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Aggregate Storage. Applicable emission factors were
__ - ^
already available for aggregate storage piles. There-
fore, no derivation was necessary. The factors utilized are
summarized below:
Uncontrolled Fugitive Dust Emissions,
Aggregate Ib/year/ton in storage pile*
Fine sand 10
Fill material
Crushed rock
Gravel 1-5
Coarse sand
* Based on the average weight of pile
Feedlots. Two 24-hour hi-vol samples were taken by the
California Cattle Feeders Association at the periphery of each
of 24 different feedlots. ^52^ While data on the number of
cattle and size of specific feedlots were not released,
information dividing the lots into three size ranges was
provided in a communication with the Association. This
permitted rough approximations to be developed of the
relationships between number of cattle or size of lot and
fugitive dust emissions. Feedlots were a relatively minor
source of emissions in the present fugitive dust survey, so
an order-of-magnitude estimate was sufficient.
The Pasquill-Gifford diffusion equation was again employed
to relate ambient hi-vol measurements to area source emission
rates. However, for these hi-vol samples, concurrent wind
data were not available (and could not be obtained, since
the feedlot locations were unknown). In order to get estimates,
the mean annual wind speed of 6.9 mph at Fresno, California and
a D stability class were used. Without concurrent wind data,
the calculated average values could possibly be inaccurate by
a factor of 2. The results of this exercise are summarized
in Table 3-4 below:
3-14
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Table 3-4
AVERAGE PARTICULATE EMISSIONS FROM FEEDLOTS
Cattle, Size of Feed-
1000 head lot, acres
range average range average
<3 2 <20 5
3-3C 9 10-100 20
>30 45 >60 90
No . of
Samples
10
28
10
Average Q,
tons/year
15.5
72
235
Annual
Emissions ,
tons/103 head
8
8
5
Annual
Emissions ,
tons/acre
3
4
3 -
For calculations in the emission survey, emission factors
of 8 tons/year/1000 head for uncontrolled lots with less than
25,000 cattle and 5 tons/year/1000 head for lots with more
cattle were used. During the course of the survey, it was
found that inventorying the number of cattle in feedlots was
simpler and more reliable than determining lot sizes. If
only the feedlot area is ascertained, a factor of 3 tons/year/
acre would provide an emission estimate. All three of the
emission factors for feedlots are presented with strong
qualifications on their accuracy and areas of applicability.
3.2 Survey Procedures and Techniques
The raw data was collected and logged in tabular form
by source category. This provided uniformity and rapid
comparison of relative AQCR emissions. The data notebook is
available in the project files. Except in the two AQCR's
which were modeled, the smallest jurisdiction for which data
was reported was by county. Wherever possible, a base year
of 1970 was used in collecting data. This was done to keep
the fugitive dust particulate emission inventory consistent
with the other particulate emission data and the air quality
data reported in the states' implementation plans.
3-1!
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The original intent in this project was for state and
local agency personnel to collect the survey data and transmit
it to the project staff for emission estimate calculations.
An instruction booklet and survey form were prepared and
distributed to explain and standardize the procedures for
the survey. A copy of the booklet is presented as Appendix B.
However, with few exceptions, all the information was gathered
and validated by project staff.
Unpaved Roads. Exact mileages by county for different
types of unpaved roads (e.g., primitive, graded and drained
dirt, gravel, and oiled earth) were obtained from state highway
department annual reports on the status of the highway system.
Such reports are a requirement for Federal aid. In some
states, these summaries had the further distinction of urban
or rural roads, which was of assistance in estimatinq traffic volume
Where it was available, exact data on traffic volume was
also used. In the two AQCR's in Nevada, annual vehicle miles
on different types of roads within each county, based on
gasoline consumption and some traffic counts, were published.
In Arizona, Maricopa and Pima Counties had made counts on
well-traveled roads in the county, including many unpaved
roads, and had shown average daily traffic counts on published
road maps of the two counties. Generally, however, specific
traffic volume information on unpaved roads was not available
because counts are not made on low-volume roads. In these
cases, average traffic volumes for each type of road that
had been obtained from state and county highway officials
or from the data described above were used. The values which
were applied are summarized in Table 3-5.
3-16
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Table 3-5
AVERAGE DAILY TRAFFIC VOLUMES ON UNPAVED ROADS
Type of Road Average Daily Vehicle Count
Urban Rural
Primitive 5 2
Unimproved 25 20
Graded and Drained 75 40
Rock, Gravel,
Oiled Earth 100 60
The number of vehicle-miles per county was next calculated
by multiplying miles of road by average traffic, then summing
vehicle-miles on different types of roads. In the present'
study, no distinction was made between emission rates from
dirt and gravel roads, although a research project presently
underway may show a significant difference between their
emissions per vehicle-mile of traffic.
Average vehicle speed on individual road links was not
considered in estimating emissions, either, although higher
speeds are known to increase emissions. There are no methods
of surveying average speeds on specific road links, on specific
types of roads, or in particular counties or AQCR's. There-
fore, an emission value corresponding to 30 mph vehicle speed
was used in estimating all unpaved road emissions. This number
was near the low of several estimates given by highway depart-
ment officials and should represent a conservative determination
of emissions (unpaved roads are not normally posted for speed
limits). Experience in controlled speed driving during the
3-17
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field studies indicated that it is difficult to maintain
speeds above 40 mph on most unpaved roads because of road
roughness.
Agriculture. It was decided that the wind erosion
equation would be used to estimate the agricultural contribution
of fugitive dust in the emission survey. Data required to
calculate county-wide emissions with this equation were:
County variables :
predominant soil textural types (e.g., sandy loam,
clay, clay loam, silty clay, etc.)
average annual wind speed, mph
potential evapotranspiration index (sum of 12
monthly precipitation minus potential evapotranspiration
totals), inches/year
number of acres in each major field crop
Crop variables (generally the same for a particular crop
regardless of county):
vegetative cover left as residue or stubble, Ib/acre
roughness coefficient, a dimensionless value measuring
the relative height of plowed ridges to the distance
between furrows
unsheltered length of field, feet.
These data were obtained from several governmental
agencies. Soil types in agricultural areas were available
in Soil Conservation Service (USDA) soil survey reports.
Climatological data were obtained from NOAA State Climatolo-
gists in the four states. Crop acreage statistics by county
were found in annual bulletins published jointly by USDA's
Statistical Reporting Service and the state university system
(except in California, where the data came from individual
3-18
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county agricultural reports). Representative regional values
for crop variables were from discussions with various SCS
and Agricultural Extension Service personnel and field
personnel at the two agricultural sampling sites.
Construction. The two pieces of information collected
were number of acres of active construction (ground disturbed),
preferably during 1970, and duration of the construction
activities. Data was obtained, in some cases by assimilating
partial information from different sources, from Public Works
or Building Department construction permit files, county and
state planning departments, county APCD permit files, and bank-
published economic reviews of metropolitan areas. Duration
of construction was determined from permit records and
discussions with agency personnel familiar with local construction
activities. Sometimes, the values were estimated from the
relative number of acres in residential, highway, and heavy
building construction. No attempt was made to derive different
emission factors per acre of construction for the three major
categories of construction mentioned.
Tailings Piles. The procedure for estimating emissions
from tailings piles was to determine (1) the total acreage of
each known pile and (2) the surface conditions and size of
different sections of the pile, i.e., active and moist, heavily
crusted, clay or slag cover, vegetative stabilization, or dry
and subject to wind erosion. Tailings piles were located in
only three of the AQCR' s under study-Northwest Nevada, Nevada
Intrastate, and Phoenix-Tucson—and the two state agencies
already had adequate information on file to provide the needed
data.
Aggregate Storage. Large aggregate storage piles were
located through existing emission source files at county and
3-19
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state air pollution control agencies. Individual forms
from sand and gravel operations and other mineral products
industries were examined and some follow-up telephone calls
made to determine the average tonnage and type of aggregate
in bulk, unenclosed storage,• plus any dust control procedures
presently in use. Although ^missions are also a function of
"movement" or turnover rate of the storage pile, not enough
emission factor data was available to permit this variable
to be included.
Feedlots. Feedlot emissions were estimated primarily
from the number of cattle in individual feedlots with more
than 5000 head. The total number of cattle on feed in each
county was published along with the crop statistics in county
and state agricultural statistics reports. The names and
size of individual lots in counties with a large number of
feedlots were obtained by telephone survey of names shown in
local agency files or in the telephone directory. The totals
from this survey were balanced against the published county
totals.
Real Estate Development. Acreage of all real estate
developments over 500 acres was obtained from regional planning
agencies. Due to inadequate data on the specific sources of
emissions within these developments or a reliable emission
factor based solely on the size of developments, no direct
emission calculations were made for this source category.
However, they were considered as construction or unpaved road
sources in cases where the collected data had indicated the
amount of either of these activities.
-•3 Results
The estimated emissions from fugitive dust sources in the
six AQCR's are summarized in Table 3-6 along with the particu_ate
er.issions from those six AQCR's as submitted in the implementation
3-20
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plans. The detailed emission totals by county for each AQCR
are presented in Appendix Tables F-l through F-6. For a more
valid comparison of particulate emissions between regions,
the area of each AQCR is shown beside the emission total in
Table 3-6.
The most obvious observation from the survey sumnary is
the magnitude of the fugitive dust emissions in comparison
with particulate emissions from conventional point and area
sources. This emphasizes the need for considering control of
these sources in developing a control strategy to achieve
particulate air quality standards. The validity of the emission
estimates may be questioned because of their extremely high
values. However, a recently published EPA report indicated
that approximately 63,000,000 tons of native soil enter the
atmosphere as particulate matter each year in the U.S. as a
result of surface wind action.(59) Based on a land mass of
3,615,000 square miles, this is an average of 17.4 tons/square
mile. In comparison, the fugitive dust emissions for individual
AQCR's range from 2.3 to 44 tons/square mile. This certainly
does not appear high for areas of the country with recognized
dust problems.
Agricultural emissions overshadow all other fugitive dust
sources in two of the regions and are a large contributor in
a third AQCR. These two regions do contain some of the most
intensely farmed land in the country. Their high emissions
from farming operations indicate that, although largely
ignored, agriculture may be an important source of particulates
in many parts of the country.
In the other four AQCR's, unpaved roads are the largest
source of particulates. This is the only source category of
major importance in all six of the regions. Fugitive dust
3-22
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from construction is prominent in the three AQCR's with large
metropolitan areas. Phoenix-Tucson is the only AQCR in which
any other source category makes a substantial contribution to
overall regional emissions. Here, tailings piles are the
source of almost 22,000 tons/year. It should be noted that
each of the regions has a completely different relative
contribution from the important source categories.
3 .4 Distribution of Emissions within Counties_
In the portions of two AQCR's in which IPP modeling was
done, a finer resolution of emission configuration was
required. The areas of concern were Bernalillo County in the
Albuquerque-Mid Rio Grande AQCR and eastern Maricopa and Pima
Counties in the Phoenix-Tucson AQCR. County emission totals
were distributed primarily into 5 and 10 km square grids of
the UTM coordinate system, with a few 2.5 and 20 km square
grids.
For unpaved roads, the adopted grid systems were over-
laid on county highway maps and the miles of each type of
unpaved road in each grid were measured and totaled. In
Tucson, this process was aided by a previous count of unpaved
roads done on a different grid system.(6) Vehicle counts on
these roads were determined as follows:
Phoenix - average daily traffic values shown on the
highway map
Tucson - separate map and computer printout listing
traffic counts on some roads; average values
from Table 3-5 applied on remainder
Albuquerque - values from Table 3-5 for all roads.
After mileages were multiplied by the appropriate traffic
volume values, the products were added to get total vehicle
miles per grid. This was converted to annual emissions with
the emission factor 3.7 Ib/vehicle mile.
3-23
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Agricultural activities were distributed by a similar
procedure of overlaying the grid system on an aerial photograph
or regional map showing the land under active cultivation.
The estimated acres of cropland in each grid were then multiplied
by a single emission factor derived from the total county agri-
cultural emissions divided by the acres of farmland. This
procedure did not account for differences in emission rates
from different crops, but the great amount of extra survey
work required to determine crops grown in each grid was not
warranted by the small additional accuracy in emission
distribution that would be gained.
Construction emissions were assigned to grids by use of
rating factors from 0 to 10 estimating the relative amount of
active construction in the area represented by each grid.
This was done in consultation with personnel from the local
control agency or planning department. The rating factors
were multiplied by a constant to become percentages of total
county construction. These percentage values were then used
directly to distribute the calculated county construction
emissions.
Sources in the other three fugitive dust categories-
tailings piles, aggregate storage, and feedlots—were treated
as individual point sources. The emissions were calculated
and location determined separately for each known source,
then the estimated emissions for the source were assigned to
the grid in which it was located. The UT>" coordinates for all
conventional point sources in the three areas modeled had
been recorded as part of other EPA contract work. Many of
the conventional area source emissions, which were minor in
all three areas, had also been distributed into grids as part
of the emission inventory submitted in the implementation
plan. When such information was not available, a rating system
analogous to that employed with construction emissions was used.
3-24
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Summaries by emission source category and grid were
prepared as part of the IPP control strategy testing program,
and are available in the project files. Other worksheets on
distribution of emissions can also be found in the project
files.
3.5 Background Particulate Levels
Control strategy testing by an accepted method requires
that background particulate concentrations be subtracted.from
measured values before estimating the impact of proposed
controls. The accuracy of the testing is therefore dependent
on the accuracy of the value used as background.
Several hi-vol sampling stations apparently unaffected
by nearby particulate sources, including fugitive dust sources,
were found in the AQCR's. The only AQCR in which a valid
background site could not be located was San Joaquin. All
past samples taken at these remote sites were used in
calculating the average particulate concentrations, since the
low measurements are subject to higher percentage variations.
No attempt was made to generate background samples during the
two-month sampling period of the present project because of
this need for many samples for at least a year in order to
produce a valid estimate of background. The locations of
the background stations and their long-term average readings
are shown in Table 3-7.
Although the particulate measured at the remote sites
nay be transported from other AQCR's, emitted by vegetation
(e.c., spores or pollen), or even formed in the atmosphere,
true background in the Southwest probably results almost
er.tirelv from wind action across arid land. It would logically
follov; from this premise that the same variables which affect
dust concentrations in the wind erosion equation—vegetative
ccver, surface roughness, average wind speed, surface soil
3-25
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TABLE 3-7
BACKGROUND MEASUREMENTS IN STUDY AREA
State
Sampling Site Location
Particuiate Level,
ug/m3
(Geometric Mean)
ev; Mexico
Arizona
Nevada
Albuqerque - NASN
Bernalillo County-Radar Stn
Dona Ana County
White Rock
Organ Pipe Cactus
.Nat' 1 Monument
Grand Canyon
Davis Dam
Page
White Pine - NASN
Las Vegas - Marina
Boulder City
Las Vegas - Civil Defense
Building
Reno
22
32
13
32
26
21
29
17
14
35
30
34
31
3-26
-------
moisture, and soil type—are of prime importance in determining
background levels.* Further, background concentrations should
be more closely related to the above geographic features than
to political jurisdictions such as states or AQCR's. There-
fore, it is proposed that average background concentrations
be developed for broad geographic or climatic zones in the
six AQCR's rather than values being assigned for regions or
states.
A generalized map of geographic areas has been prepared
for the parts of the Southwest involved in this study, using
the vegetal cover descriptions of the Soil Conservation Service
in their Selected Land Resource Data publication. Rainfall,
topography, and soil survey maps were also utilized in
establishing boundaries between the zones. The zones were
"calibrated" for background level with the data in Table 3-7.
The resulting map is presented in Figures 3-1 and 3-2.
T^ statement does not infer that the wind erosion equation
can~predict windblown dust emissions from native lands. The
natural surface in arid areas, often described as "Desert
pavement", has been scoured of fines by continued wind and
water erosion over long periods of time. As a result, it has
a Taver of gravel-sized particles shielding the surface from
further substantial wind action and is far less susceptible
tc dust losses than the croplands described in the wind
erosion equation.
3-27
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4.0 CONTROL TECHNIQUES
Unlike the control methods for stationary and mobile
sources, those for fugitive dust sources are not documented.
Within the scope of this project, several possible control
techniques for each fugitive dust source have been identified,
their efficiencies in reducing dust have been evaluated, and
their costs estimated. From this information, a file of
feasible techniques for each source has been prepared. This
file is compatible with control techniques' needs in strategy
testing and provides technical background for development of
control regulations.
4.1 Research Procedures
Several information sources were utilized in preparing
the control techniques file. Potential controls were first
identified by personal interviews, reports from research
projects, test claims of proprietary chemicals, and existing
fugitive dust control regulations. A bibliography of pertinent
material collected on control methods is included in
Appendix A. In some cases, telephone calls were made to
request additional unpublished data on the control methods.
Material was collected and assembled by type of source.
When the applicability of a method and/or its control
efficiency could be confirmed by published information, the
reported values were used. However, most control applications
were claimed successful, but no data establishing the
efficiency of dust removal was presented. The procedures used
to estimate control efficiencies in these cases are explained
in the text below.
4-1
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For methods which appeared feasible from the standpoints
of dust suppression and enforceability, preliminary cost data
was generated from the same information sources. The summary
of costs includes references to the sources of data.
4.2 Findings
With a few exceptions, all of the fugitive dust controls
uncovered were applications of one of three basic techniques--
watering, chemical stabilization, or reduction of surface wind
speed across exposed sources. Watering generally requires
a low first cost, but provides the most temporary dust control.
Depending on the nature of the dust-producing activity, water
may be an effective dust suppressant for only a few hours or
for several days. In addition to the direct cohesive force
of a film of moisture in holding surface particles together,
watering is also effective in forming a thin surface crust
that is more compact and mechanically stable than the material
below and which is less subject to dusting even after drying.
However, this crust and its dust-reducing capability is
easily destroyed by movement over the surface or by abrasion
from loose particles blown across the surface. Therefore,
the watering must be repeated frequently to reform the moisture
film or surface crust. An in-depth discussion of the effect
of surface soil moisture on soil erodibility can be found in
USDA Technical Bulletin No. 1185, Soil Conditions That
( 19)
Influence Wind Erosion.
It should be pointed out that the fugitive dust problem
is accentuated in the six AQCR's under investigation more
than in other parts of the country primarily because of arid
climate and lack of natural surface moisture. As a corollary
to this, water is a scarce resource in these regions, and not
readily available as an air pollution control material on a
reaion wide basis.
4-2
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Several types of chemicals have been found effective in
reducing dusting when applied on fugitive dust sources. These
chemicals act by several different means and are generally
categorized by their composition—bituminous, polymer, resin,
emzymatic, emulsion, surface-active agent, ligninsulfonate,
latex, etc. It is estimated that over 100 chemical products
are presently marketed or are under development specifically
as dust control agents. ^ 24 Information was collected
during the present study for those shown in Table 4-1.
With the wide range of characteristics available in
commercial products, a chemical stabilizer can be selected
with maximum efficiency for each dust control application.
Some of the materials can "heal" if the treated surface is
disturbed, but many will not reform. The life of the treated
surface under natural weathering also varies widely with
different chemicals. Selection of the appropriate material
may require that several other criteria be checked for
compatibility: effect on vegetative germination and growth;
application method; possible contamination of material being
protected from dusting; and correct chemical for texture of
specific soil or material. Although no single comprehensive
summary of dust suppressant chemicals and their properties
was found, several evaluations have been prepared for
different chemicals on a single type of fugitive dust source.
These are identified in further discussions in the following
section.
Wind erosion contributes significantly to all of the
fugitive dust categories surveyed. Therefore, reduction of
surface wind speed across the source would be a logical means
of reducing emissions. This takes such diverse forms as
windbreaks, enclosures or coverings for the sources, and
planting of tall grasses or grains on or adjacent to exposed
4-3
------- An error occurred while trying to OCR this image.
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I
(Ti
Soil Stabilization
Product*
30. ?
31. Geon 652
32. Soil Seal
33. Aerospray 52
Binder
34. Gantrez An-119
35. WICALOID Latex
7035
36. Gypsum Hemihydrate
37. E802 Mazofern
38. NC 1556L
39. Agri-mulch
Manufacturer*
Ashland Chemical Co.
B.F. Goodrich Chemi-
cal Co.
Soil Seal Corp.
American Cyanamid Co.
General Analine and
Film Corp.
Wica Chemicals
National Gypsum Co.
Corn Products Sales Co.
Dow Chemical Co.
Douglas Oil Co,
Chemical Composition
Liquid styrene-butadiene
emulsion in mineral oil
Latexes
formulation of copolymers
Synthetic resin-in-water
emulsion
Synthetic resins
Carboxylated styrene-but-
adiene latex
Powder gypsum hemihydrate
Fermented corn extract
Polyacrylamide
Petroleum asphalt
*Material names and manufacturers are included for the benefit of the reader and infer no
endorsement or preferential treatment by EPA or PEDCo-Environmenta.
? = Information could not be determined.
-------
surfaces. The vegetative techniques all need a soil which
supports growth—containing nutrients, moisture, proper
texture, and no phytotoxicants. These requirements, especially
adequate moisture, are often not present in the six AQCR's
and may be the reason that natural protection against wind
erosion is insufficient. The large size of most of the
fugitive dust sources eliminates physical enclosures or wind
barriers from practical consideration.
4.3 Control Techniques by Source Category
Unpaved Roads. Four distinct methods of roadway surface
treatment for dust control are used:
1. paving
2. surface treatment with penetration chemicals
3. soil stabilization chemicals worked into the roadbed
4. watering
The obvious problem with paving is the high cost for
the large number of miles of low traffic density roads in
sparcely populated areas of these six AQCR's. The Maricopa
and Pima County Highway Departments have both undertaken test
programs in low-cost paving methods. They have placed test
strips of single bituminous chip seal over various types of
compacted native soil bases which have been stabilized. With
the mild climate in this region and light traffic loads on
these roads, it is anticipated that this construction may
provide a semi-permanent surface. The test sections have
not been down long enough to assess maintenance requirements.
Based on an initial cost of slightly more than half that of
the standard double bituminous surface, a five to seven year
life would be required to break even with conventional paving.
A significant benefit for either type of paving over unpaved
roads is elimination of the routine maintenance cost for
blading and regrading the unpaved roads.
4-7
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Paving of minor roads creates a safety problem which is
often overlooked—drivers tend to "overdrive" these roads,
causing the number of accidents to increase. To prevent this,
grades, curves and the right-of-way must be improved. In
many cases, the cost of this improvement in the right-of-
way is more th?.n the strip paving. Therefore, a least-
cost solution to the particulate air pollution problem may
be counter to highway safety.
Application of a surface chemical treatment for dust
suppression is a relatively inexpensive control method.
However, in tests on public roads conducted by several different
highway departments, no commercial material has been found
which retains its effectiveness over a reasonable period of
time (e.g., two months) under traffic conditions. Most of
the treated surfaces abrade badly to the depth of penetration
of the chemical; others which maintain a stabilized surface
with traffic are water-soluble and lose their effectiveness
after rains. Several surface treatment chemicals are
presently under development or testing. Available technology
for this method may increase greatly within the next few years.
A few successful special applications of surface treatment
have been found. In non-traffic areas such as roadway shoulders,
chemical soil stabilization has proven highly effective in
reducing the dust produced by air disturbance from passing
vehicles. Since the low-cost paving procedures described
above do not generally include curbs and gutters, they would
require shoulder stabilization for complete elimination of
fugitive dust. Surface treatment has also been reported useful
in conjunction with frequent watering on high-maintenance
roads, such as mine or quarry roads, which cannot be paved
-------
because of the heavy weights they must carry and their
temporary nature. The Air Force sprays unpaved roads along
with other exposed soil areas for dust control on several Air
Force bases in the Southwest.1
An alternative intermediate in cost and effectiveness
between paving and surface treatment is working the stabilization
chemicals into the roadbed to a depth of two to six inches.
This construction technique has been used extensively in the
San Joaquin Valley, where locally available petroleum by-
products provide a cheap material for oiled earth roads.
Pima County, Maricopa County, and other Highway Departments
have also tested this type of road to reduce dust problems.
Several test sections are still functional, but the results
so far are not encouraging. The construction cost approaches
that of the single bituminous chip seal surface, and the
resulting road has a shorter life span with comparable
maintenance. Typical costs for the three methods of roadway
surface treatment for dust control are presented in Table 4-3
in Section 4.5. Stabilization of the roadbed does have
considerable potential as an interim control procedure, since
this roadbed can later be used as a base for paving.
Watering is not a feasible method of effective dust
control on public roads because of the high frequency of
treatment required. However, it may be used advantageously
on unpaved roads under special circumstances where the watering
equipment is already available and the roads are confined to
a single site, such as construction access roads or mining
haul roads.
The above information indicates that there is no obvious
best treatment for road dust control. Traffic controls may
4-9
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also be used to reduce emissions from unpaved roads. These
include speed limits and restricting unpaved roads to only
local traffic where alternate paved routes are available.
All studies to date show that emissions increase at a rate
more rapid than the increase in vehicle speed, and in direct
proportion to the number of vehicles traveling the road. The
cost of traffic control is negligible compared to road treat-
ment, but enforcement is a definite problem, especially on
low traffic density roads in rural areas. Nevertheless,
speed limits or restricted traffic may be effective as interim
control measures during a lengthy road improvement program
or as an additional measure in particular "hot spot" areas.
While control of existing unpaved roads is a complex
problem, control on new roads can be quite direct. Pima and
Maricopa Counties both have regulations requiring developers
to pave all new roads, and neither jurisdiction is accepting
further unpaved roads into the county highway system. This
policy places the financial responsibility on the developer,
who must include the cost of paved roads in his project.
Agriculture. Methods for control of fugitive dust off
agricultural lands were obtained from several publications of
the U.S. Department of Agriculture and discussions with
personnel of that agency. The staff at the USDA Agricultural
Research Station at Manhattan, Kansas provided much valuable
input. All of these control techniques were developed for
conservation of topsoil from wind erosion. Since the fugitive
dust from agriculture is thought to derive primarily from wind
erosion of exposed cropland,the techniques should be equally
effective in reducing this form of air pollution.
Many of these control methods were designed for use
on the arid, non-irrigated farmlands of the Great Plains.
4-10
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In adapting them to conditions of irrigation in the South-
west, some important considerations are: (1) a reduced need
for fields to lay fallow for long periods to store moisture;
(2) possible use of irrigation water as an emergency protection
during periods of high wind erosion; (3) the lower suscepti-
bility of irrigated cropland to wind erosion during periods
with growing crops because of regular watering cycles; (4) the
flat terrain associated with irrigated lands; and (5) the
generally lower average wind speeds in the Southwest than in
the Great Plains. These comparisons are not meant to infer
that fugitive dust problems are much greater on non-irrigated
land. The beneficial effects of continuous water availability
is usually more than counteracted by higher fugitive dust
emissions due to the density and intensity of farming in
irrigated areas.
Six broad types of control methods with possible applica-
tion in the Southwest were identified. Each of the six has
several modifications which are dependent on crop/ climate,
water availability, etc. The six general control methods are:
1. continuous cropping
2. stubble, crop residue, or mulch left on fields
after harvest for wind protection
3. limited irrigation of fallow fields
4. inter-row plantings of grain (on widely-spaced
row crops) or strip cropping
5. vegetative or physical windbreaks
6. spray-on chemical soil stabilizers.
Continuous cropping of a field eliminates the period
between crops when the exposed soil is most susceptible
to wind erosion. It is particularly attractive (a) on
irrigated lands where the farmer does not have to rely on a
period of fallow to store moisture or a rainy season to start
crops, and (b) in warm climates where the off-season planting
need not be just a winter cover crop, but can be a second
salable crop. Continuous cropping has the greatest impact
4-11
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on fields where cotton, sugar beets, beans, vegetables,
or other crops which do not leave a protective stubble or
residue are grown. Although no air pollution control agencies
currently regulate agricultural crop patterns, it appears
that an enforceable regulation could be developed requiring
all cultivated land to be kept in crops, adequately protected
against wind erosion by specified alternate methods, or
converted to rangeland.
Stubble mulching — the practice of maintaining crop
residues at the ground surface — offers good protection
from soil blowing during non-growing periods. Crop residue
also improves soil structure, which allows water to soak
into the soil more readily. The degree of wind protection
depends on the quantity and type of residue and cropping
practices used with the stubble mulching. Two examples of
practices which increase the effectiveness of mulching are
spring plowing (instead of fall plowing) and planting the
new crop in the old stubble. Obviously, this technique has
several limitations when applied on the large farms in the
Southwest with their highly mechanized farming procedures. In
many cases, the farmers are already taking maximum advantage
of stubble mulching consistent with operation of their
farm machinery. For some crops, the residue is burned or
plowed under to prevent infestation. From an enforcement
standpoint, development of a workable regulation for maintaining
crop residue would be difficult.
During periods when a field is barren, either after
harvest, between crops, or after a field has been planted,
dusting can be reduced by irrigating at frequent intervals.
As previously discussed, watering forms a thin surface crust
which protects the undisturbed soil for some time after the
4-12
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surface has dried. Possible disadvantages of this technique
would be the cost of the extra water, availability of
sufficient water to adopt this procedure on a region-wide
basis, and soil conditioning problems caused by keeping the
surface moist or crusted. These would need to be analyzed
separately for each locale. On the positive side, this
technique could produce significant reductions in the large
quantities of fugitive dust from agricultural operations,
and could be relatively easily implemented and enforced.
Inter-row planting of grains and strip cropping both
utilize the principle of protecting an erosion-susceptible
crop or fallow area with an erosion-resistant crop. Resistant
crops are small grains or wheat grasses which grow rapidly.
The most susceptible crops are cotton, sugar beets, beans,
potatoes, peanuts, asparagus, and most truck crops. For
maximum effectiveness, the strips or rows should be planted as
nearly perpendicular to the prevailing wind direction as
possible. These control methods do not remove any land from
cultivation, and may not require any change in cropping
practices if well planned. Like stubble mulching, they may
present some difficulties on large farms using large farm
machinery. Because of problems that can occur with strip or
inter-row cropping on particular fields, restriction of certain
crops to these planting methods would not be feasible. However,
it may well be specified as an acceptable alternate to other
required agricultural controls which have approximately
equivalent dust-reducing capabilities.
Windbreaks along the edges of cultivated fields can
reduce surface wind velocity and soil blowing. A great variety
of vegetation and physical barriers have been proposed as
windbreaks. These are discussed in a comprehensive USDA
publication, Windbreaks for Conservation. ' Several analyses
have shown that physical barriers are too costly for this
4-13
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application, even for the protection of expensive crops.
Vegetative windbreaks often take years to establish and
have several other limitations for widespread use on irrigated
farmland in the Southwest. Regulations requiring windbreaks
or specifying windbreaks as an alternate means of fugitive
dust control do not appear feasible.
The most recently developed soil conservation method,
the use of spray-on chemical soil stabilizers, was first
reported in 1969 and has been further tested since that
time. The more recent study investigated 34 materials
and found six which met all four of the researchers' criteria:
(1) cost less than $50 per acre, (2) prevented wind erosion
initially and continued to be effective for at least 2 months,
(3) did not reduce plant germination or growth, and (4) were
relatively easy to apply. While the chemicals provide only
temporary control (until the field is worked again), they do
protect against wind erosion during the susceptible period
when the new crop is in the seedling stage. They are generally
applied with an agricultural sprayer immediately after planting.
A herbicide must be added to the spray, since the field cannot
be cultivated without destroying the stabilized surface. Cost
for the soil stabilization chemical alone, not including
application, averaged $36 per acre for the six successful
chemicals applied at the manufacturers' recommended rates.
This method definitely requires additional development to
reduce its cost, but it promises to provide more effective
dust suppression than presently available techniques.
The emphasis for agricultural dust sources has been on
control of wind erosion rather than tilling activities. The
validity of this approach is borne out by the emission factor
calculations, which indicate that more than 90 percent of the
fugitive dust originates from wind erosion. Some work has been
done on control of emissions from tilling — notably speed
4-14
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control and deflector attachments for farm implements.
Reducing the speed of equipment in the fields has been shown
to reduce emissions, but enforcement of such a provision
would not be feasible. Attachments have not been demonstrated
to be effective in dust control. Another possibility for
control of tilling operations, watering the field prior to
plowing, would in many cases make the soil unworkable and
adversely affect the plowed soil's characteristics. Therefore,
the difficulty of control of emissions from tilling also
indicates that agricultural dust emissions can best be reduced
by control of wind erosion.
Construction. Information on control of fugitive dust
from construction activities was obtained from local control
agencies, the USDA's Soil Conservation Service, and the Army
Corps of Engineers. Construction includes a wide diversity
of operations; maximum effort in control should be directed
at those in which more than about one acre of land is cleared.
Many of the worst dust problems on heavy construction
sites are controlled because of labor union or worker demands
or to reduce high equipment maintenance costs. When con-
tractors have attempted to reduce dust generation on-site,
they have usually selected watering trucks. Watering on
construction sites, as with other sources, has a short duration
of effectiveness. However, it can be an adequate control if
it is repeated frequently at a sufficient application rate.
Watering can also be a low-cost control, since most con-
struction jobs already have necessary equipment and facilities
and need only more manpower for this task, or possibly extra
equipment. A good regulation should specify minimum frequency
and application rates, rather than leaving this decision to
the contractor.
4-15
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Dust sources created indirectly by the construction
activity may best be controlled as part of this operation.
Examples are trucks carrying fill material or aggregate and
temporary access roads to the site. Trucks hauling construction
materials are controlled by covering the truck bed before moving.
Access roads can be watered with other exposed parts of the
area or otherwise treated as described under Unpaved Roads.
Chemical stabilization has also been evaluated for use
in dust control on construction sites. Because of the constant
traffic and equipment movement over much of the exposed area,
this treatment is generally not successful in active con-
struction conditions. Most emissions result from the traffic
movement rather than from wind erosion. Also, continued
regrading brings new, untreated soil to the surface. However,
after the site or a portion has been completed, stabilization
is very effective in reducing wind erosion across the, cleared
site or exposed land. The State of Nevada has specifications
written into state construction contracts requiring stabiliza-
tion of all completed cuts and fills.
Several agencies have passed regulations requiring
permits to construct on a property. In order to obtain and
keep a permit, the contractor must have an approved plan to
control dust. This is an enforcement aid, since the permit
can be revoked if a dust problem is observed on the site.
Use of the permit system could be extended to provide another
control technique — minimal exposure of barren areas. Part
of an approved plan for large sites would be grading or other
work on portions of the site followed by treatment of the
finished portion prior to opening a new section to clearing
and regrading. Long-duration development of large tracts
cculd also be effectively regulated to prevent windblown dust
4-16
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problems. Any permit program requiring minimal exposure
periods would necessitate submittal of detailed plans and
schedules, and in-depth reviews.
Tailings Piles. Much research has been done on stabilization
of waste tailings for the prevention of air and water pollution,
primarily by mining companies and the Bureau of Mines' Salt
Lake City Metallurgy Research Center. Radically different
methods — chemical, physical, and vegetative — have been
tested, often successfully, on inactive tailings piles. Active
tailings generally have a moist surface from new deposits and
therefore are not susceptible to wind erosion.
Chemical stabilizers react with the tailings in the same
manner as with soils to form a wind-resistant crust or surface
layer. Limitations on the weight and types of equipment that
can travel across the tailings eliminate some common methods
of application such as watering trucks for the water-soluble
chemicals or tank trucks with hoses for petroleum-base materials.
Instead, the chemicals may be applied by automated sprinkling
system, large-wheeled light vehicles or carts with hand-held
nozzle guns, or even by aircraft. Of 65 chemicals whose test
results have been recorded, the resinous, elastomeric polymer,
ligninsulfonate, bituminous base, wax, tar and pitch products
have proved effective stabilizers for one or more types of
(41)
fine-sized mineral wastes. Most of the chemicals have
demonstrated a long time span of effectiveness in this
application.
Many materials have been tried for physical stabilization
of fine tailings. The material most often used is rock and soil
obtained from areas adjacent to the wastes to be covered. Soil
provides an effective cover and a habitat for encroachment of
local vegetation. However, it is not always available in areas
contiguous to the tailings piles and, even where available,
it may be too costly to apply. Crushed or granulated smelter
slag, another waste product, has been used to stabilize tailings.
Other physical methods of control which have been employed are
4-17
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covering with bark and harrowing straw into the top few
inches of tailings.
Successful vegetative stabilization produces a self-
perpetuating ground cover or fosters entrapment and germination
of native plant seeds that will grow without the need for
irrigation or special care. Only initial fertilization should
be required because the essential nutrients should be recycled
in place. Several mining companies have planted old tailings
accumulations in efforts to achieve both wind erosion control
and an attractive site. Resistance to vegetative growth was
encountered due to excessive salts and heavy metals in the
tailings, windblown sands destroying the young plants, high
temperatures, and lack of water on the tailings piles. Recently,
several piles have been successfully planted by use of a
combination chemical-vegetation technique. The chemical
stabilizers alleviate the problems of sandblasting and highly
reflective surfaces and hold more water near the surface of
the otherwise porous tailings, thus creating a more favorable
environment for vegetative growth. Chemicals are selected
which do not have an inhibitory effect on the plants.
Aggregate Storage. Controls for fugitive dust from
aggregate storage were determined by discussions with technical
representatives of control system manufacturers and with
control agency personnel. One difficulty cited in maintaining
a dust suppression system for storage piles is the turnover
of material in the pile continually exposing new surfaces to
wind erosion.
Watering of the storage piles and surrounding areas is
the most common technique, but its effects are quite temporary
and watering sometimes reduces ability to handle the material
easily. Also, it is difficult to enforce watering regulations
for this type of source.
4-18
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A more effective, longer lasting method of dust
control is the addition of chemicals to the water sprayed
onto the aggregate. Rather than acting as chemical soil
stabilizers to increase cohesion between particles, most of
these chemicals work as wetting agents to provide better
wetting of fines and longer retention of the moisture film.
Some of these materials remain effective without rewatering
on piles stored for weeks or months. The system of application
can be a continuous spray onto the aggregate during processing
or a water truck with hose and spray nozzle.
Cattle Feedlots. Methods for control of fugitive dusts
from cattle feedlots were investigated by the California
Cattle Feeders Association. Several feasible methods were
found — frequent watering, chemical stabilization, increasing
cattle density in pens, and removal of manure.
Watering either by truck or a fixed sprinkling system is
effective if all parts of the lot are covered. Rate and
frequency of water application are critical. In conjunction
with watering, chemical stabilizers help to retain the moisture.
However, if water is not applied, the stabilizers soon lose
their dust suppressing capability with disturbance of surface
material in the pens. By increasing the cattle density in pens,
the average moisture content is also increased. While this
provides an indirect control of dust generation, it would
be difficult to regulate and possibly has adverse effects on
the cattle's health and performance.
Good housekeeping in a feedlot apparently contributes
to fugitive dust control. Studies have shown that pens in
which the manure was removed produced less dust than those
in which it was not.
4-19
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4.4 Estimates of Control Efficiencies
Estimated percent reductions in fugitive dust emissions
achieved by the control techniques found to be effective
were needed in order to (a) choose between alternate controls
and (b) develop control strategies which could quantitatively
demonstrate the emission reductions necessary to meet
particulate air quality standards. The estimated control
efficiencies were obtained either from published data on
emission reductions for each particular technique or by
calculation using more indirect data. The reference or
rationale for selecting each of the control efficiencies
is presented in this section; the assigned values used for
control strategy testing are summarized in Table 4-2. These
values are rounded off in recognition of the accuracy of
data and procedures employed in their derivation.
Unpaved Roads. The efficiencies of paving, surface
treatment, and roadbed stabilization were obtained from the
sampling data from the Tucson road sites and from a recently
published paper reporting emissions from paved and unpaved
roads in the Seattle area.(2) The average of all sampling
values from stations adjacent to the paved, surface treated,
and stabilized sections of roads were compared with the
averages at their respective unpaved control sections to
determine the reduction in particulate attributable to the
treatments. A value of 50 ug/m3 was subtracted from all the
averages to account for particulate reaching the hi-vols from
sources other than the nearby road. The calculations were
as follows :
1" chip seal paving - Unpaved control - 304 - 50 - 254
paved section = 88 - 50 = 38
percent control = 254 - 38 __ g5.0%
4-20
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surface treatment - unpaved control = 284 - 50 - 234
treated section = 167 - 50 = 117
1 "* 7
percent control = ?t . = 50.0%
roadbed stabilization - unpaved control = 304 - 50 - 254
treated section = 179 - 50 = 129
254 - 1 ? 9
percent control = — — 2~54~J±~ ~ 49-2%
Emission factors from the Seattle study were 8.5 lb/
vehicle mile for unpaved roads and 0.83 Ib/vehicle mile on
a strip paved road, with all vehicles traveling at 20 mph .
This represented a 90 percent control by paving, which was
considered good agreement with the 85 percent value.
No estimate was made of the percent reduction in dust
emissions that could be achieved by watering of public roads,
since this method was judged to be unfeasible.
Based on the average vehicle speed of 30 mph on unpaved
roads used in development of the emission factor, enforced
speed limits of 25, 20, and 15 mph would produce the following
percent reduction in emissions :
2.8 Ib/veh.-mi. _ 0
R
25 mph 3.7 Ib/veh . -mi .
2.5 Ib/veh.-mi.
R20 mph ~ 3.7 Ib/veh.-mi.
= 1 _ 2.2 Ib/veh.-mi.
_
15 mph 3.7 Ib/veh.-mi.
As previously noted, only that portion of the emissions
generated by traffic are susceptible to reduction by speed
control. Emissions from wind erosion of the unpaved road
are not affected.
The reduction in emissions caused by restriction of
traffic on unpaved roads is directly proportional to the
decrease in traffic volume. However, no generalized percent
control can be assigned.
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Agriculture - The efficiencies of the several agricultural
control techniques were estimated by application of the wind
erosion equation.
Continuous cropping or the growing of an off-season crop
such as wheat, barley, rye, oats, or grain hay keeps good
ground cover on the land during much of the 4 to 5 months
that it normally lays idle. Therefore, the emissions over
35 percent of the annual period are reduced by the amount
indicated by the additional vegetation. While this 35 percent
of the farming cycle may have more than an average emission
rate because the ground is barren, the lower climatic factor
common to the winter months would probably compensate for this.
No seasonal variation in fugitive dust emissions was assumed
in the calculations. Using average values of 1000 Ib/acre
vegetative cover for the off-season crop and 250 Ib/acre for
the fallow field with all climatic conditions and soil types,
an average control of 70 percent was found to result from the
planted crop. On an annual basis, this represents a 25 percent
control efficiency:
annual control efficiency = (0.35) (0.70)
- 0.25
The normal amount of crop residue commensurate with good
farming practice was assumed to be left on the fields in the
calculations of existing agricultural emissions. Therefore,
bv optimizing crop residue maintenance and plowing procedures,
only an estimated 50 percent more in equivalent field cover
could be provided. This corresponds to about a 10 percent
reduction in annual emissions.
The control achieved by limited irrigation of fallow
fields is not primarily from wetting of the surface soil, but
from the crust formed by the watering. Therefore, the
efficiency is determined by the crusting ability of the soil,
4-23
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and watering frequency is determined by the life span of
the undisturbed crust before it is damaged by wind erosion.
( 19 )
Crusting reduces wind erosion by a maximum of 1 tc 6.
However, the original soil would not be completely free of
clods and cementation. Therefore, a value of 1 to 3 is
proposed. Again using 35 percent of the year as the time
the field is fallow and could be controlled by this method,
its average efficiency is:
(1 - j ) (0.35) = 23%
In order to reduce emissions by this amount, the field must
be reirrigated as the crust from the previous watering begins
to deteriorate.
For stripcropping, it was assumed that the average
unsheltered distance across the field decreases from 1000
feet to 200 feet. This results in approximately 45 percent
reduction in emission rate according to the wind erosion
equation, but is applicable only when winds are perpendicular
or nearly so to the strips. There is no reduction in un-
sheltered distance when winds are from either of the quadrants
parallel to the strips. If winds are in the quadrants
perpendicular to the strips 60 percent of the time, the total
efficiency of stripcropping as a dust control technique is
(0.60) (45%) = 27%.
One reference ^ 26 ^ reports that inter-row plantings are
as effective as tall trees in reducing surface wind speeds
when rows are perpendicular to winds and more effective than
trees with parallel winds. Based on the calculations presented
in the following paragraph, this is equivalent to approximately
15 percent reduction in fugitive dust emissions.
Windbreaks on the windward side of a field protect the
field from wind erosion to a distance equal to ten times the
height of the windbreak.( x ^ With a 1000 feet average length
for fields (value used in the emission survey), the wind
4-24
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erosion equation indicates that the following heights of
windbreaks around the field would reduce emissions by the
corresponding percentages shown:
reduction in
height, ft. emissions, %
10 4
20 6
30 10
Spray-on chemical stabilizers are assumed to remain
effective during the entire planting and growing seasons, or
about seven months. Their efficiency in eliminating dust is
estimated to be about the same as that of the crusting formed
by frequent irrigation, 67 percent. On an annual basis, the
resulting reduction by application of this technique is
(7/12) (0.67) = 40 percent.
Construction - Watering on construction sites produced
a wide variation in apparent control efficiencies, due in
part to the highly variable nature of the emission sources.
Activity logs kept at the construction sites showed that some
sampling periods with extensive watering were accompanied by
hi-vol readings 60 to 70 percent lower than anticipated with
no watering, while on other days the apparent effect of the
watering was negligible. The same variations were noted in
analyzing data from sampling periods with rainfall. With
daily watering and complete coverage, average control efficiency
is about 30 percent. This value is partially verified by
another study indicating a 30 percent reduction in dust emissions
over continuously-traveled gravel and dirt roads on days when
( 2 )
their surface was moist. However, with watering twice a
day at the same application rate, a reduction of 50 percent
appears feasible. One limiting factor with excessive watering
is carryout of mud onto adjoining streets and roads, thus
indirectly causing additional dust problems.
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Several publications have reported that the average
ratio of surface credibility for a crusted soil versus a
( 19 *>
non-crusted soil is about 1 to 6 . ' Chemical stabilization
of completed cuts and fills on construction sites vould produce
almost this amount of reduction, since (a) the finished
regraded areas are generally protected from wind erosion only
by compaction and (b) several commercial chemicals have
demonstrated strong binding or crusting properties in treat-
ments where the stabilized surface has no traffic.
Minimizing the period during which the cleared and
regraded lands are exposed would reduce fugitive dust emissions
by an amount directly proportional to the decrease in exposure
time. A generalized percent efficiency cannot be assigned for
this control.
Tailings Piles - Chemical stabilization of tailings piles,
like stabilization of construction cuts and fills, converts
a completely non-crusted surface into a hard-crusted one,
providing a similar control efficiency of about 80 percent.
Covering the tailings with a material such as smelter
slag should essentially eliminate fugitive dust losses from
the pile. The use of a native soil to cover the tailings would
initially replace tailings wind erosion with soil wind erosion.
However, the soil would rapidly become covered with vegetation,
resulting in a permanent control with approximately half the
emissions as direct vegetative control of the tailings. The
additional control would derive from the lower credibility of
the native soil at the surface rather than the tailings.
The efficiency of vegetative cover in reducing windblown
dust is dependent primarily on the density and type of
vegetation that can be grown on the resistant tailings. In
a recent study, Bureau of Mines researchers were able to grow
wheat and other small grain at a density of 2.4 plants per
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square foot on tailings. ^This is equivalent to 1000 to 1500
Ib per acre of strubble. Substituted into the wind erosion
equation v/ith soil class 2 (sand and loamy sands) , unridged
surface, and an unsheltered length of 2000 feet, the above
vegetative densities reduce calculated emissions by 50 to 80
percent. An average control of 65 percent is proposed, with
possible modifications of this value based on the density of
growth on the tailings.
The combined use of chemical stabilizers and vegetative
cover has a cumulative effect in reducing fugitive dust. The
plants minimize the initiation of wind erosion on the surface
by saltation and the chemicals increase germination and
growth. Therefore, the average rated efficiency would be
calculated as follows:
R = 1 - (1 - 0.65) (1 - 0.80)
= 1 - 0.07
= 93%
Aggregate Storage - No direct information was uncovered
which quantified the effect of water spray on windblown dust
control in aggregate storage piles. However, for other
fugitive dust sources, the efficiency of a moist surface in
dust control was found to vary between 30 percent for a
highly disturbed surface to 67 percent for a dust generating
surface with no disturbances. Most aggregate storage piles
have some activity, but with intermediate frequency. There-
fore, an efficiency of 50 percent has been assigned for
watering of storage piles.
Manufacturers of a continuous chemical spray system for
use in aggregate handling and storage operations have claimed
a 90 percent efficiency for dust removal for their product.
This value appears attainable when compared with a 50 percent
control for watering alone, since the chemical wetting agenr
4-27
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and application system provide more uniform wetting throughout
the pile, better wetting of fines, and longer retention of
moisture on the aggregate surfaces.
Cattle Feedlots - Hi-vol measurements taken at feedlots
during periods with and without watering were used to determine
the effectiveness of this technique for dust control. The
average of three readings on controlled lots was slightly
more than 80 percent less than the average of nine readings
on uncontrolled lots.
In semi-quantitative analyses of several chemical stabilizers,
none of them demonstrated dust supressing capabilities greater
than water alone The surface in the pens is apparently
abraded to such an extent that the binding properties of the
chemicals must be renewed by daily watering. When the treated
pens were not watered, dusting was intermediate between no
control and daily watering, representing about 40 percent
control efficiency.
According to the semi-quantitative analyses performed by
the California Cattle Feeders Association, scraping the lots
to remove manure does not appreciably reduce emissions when
done in conjunction with daily watering. With no watering,
periodic scraping appears to reduce dusting by about 20 percent.
4.5 Control Cost Data
Current cost data for most of the control techniques
discussed above are presented in Table 4-3. These values
represent total costs, including application. The source of
the cost data is also identified. Numbers shown in the
"Reference" column refer to publications from the reference
list in the Appendix.
4-28
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5.0 SUMMARY
As indicated by the title, this investigation was aimed
at identifying major sources of fugitive dust, quantifying
their respective contributions to emission inventories of
specific Air Quality Control Regions, and estimating means
for their control. Of necessity, the emission factors
utilized were based on a variety of information, ranging
from factors reported in the literature to values developed
from empirical data generated by this study. Some are well
supported while several are "best estimates". However, even
though further refinements and qualifications of all of these
factors are currently underway in EPA, USDA, and other involved
organizations, the values employed throughout this report are
felt to be appropriate relative to their use.
Fugitive dust emissions are much greater than particulate
emissions from conventional point and area sources in each of
the six Air Quality Control Regions. However, the relative
importance of individual fugitive dust source categories varies
considerably from one region to another. Agricultural emissions
overshadow all other sources in two of the regions and are a
large contributor in a third. However, these two regions do
contain some of the most intensely farmed land in the country.
In the other four Air Quality Control Regions, unpaved roads
are the largest source of particulates. Fugitive dust from
construction is prominent in the three regions with large
metropolitan areas. Phoenix-Tucson is the only area in which
any other source category makes a substantial contribution to
overall regional emissions. Here, tailings piles are the
source of almost 22,000 tons per year, or 3.4 percent of the
total particulate emissions.
5-1
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Most of the fugitive dust controls found are applications
of one of three basic techniques—watering, chemical stabiliza-
tion, or reduction of surface wind speed across exposed sources.
Other control mechanisms are paving and traffic control for
unpaved roads. All of these technologies or techniques share
the same basic implementation difficulties; they are generally
costly due to the magnitude of the problem and, often disrupt
the operation they are controlling. However, these problems are
not unique and should not be used as obstacles to a realistic
environmental protection program.
Much work is currently underway to better define the
conditions causing fugitive dust emissions and methods for
their control. However, of all the fugitive dust sources,
possibly the least attention from an air pollution control
standpoint is being given to agriculture. The present study
indicates that agriculture is the most difficult source to
control with existing technology. Specific work areas which
would advance understanding of agricultural fugitive dust
problems and lead to better control are: (1) determination
of the portion of wind erosion losses of topsoil that are
suspended particulate; (2) analysis of transport of agri-
cultural dust and its relation to particle size; (3) study
of effect that a particulate air quality standard for the
respirable particle sizes would have on problems of achieving
air quality standards in agricultural areas; (4) extensive
field testing of chemical stabilization of newly planted fields;
and (5) investigation of educational methods and economic
incentives for extending soil conservation programs to include
particulate air pollution control as a major objective.
5-2
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APPENDIX A
REFERENCES & BIBLIOGRAPHY
UNPAVED ROADS AND AIRSTRIPS
1. Anderson, C. Air Pollution from dusty roads. Presented at
17th Annual Highway Engineering Conference, April 1, 1971.
2. Roberts, J. W., A. T. Rossano, P. T. Bosserman, G. C. Hofer
and H. A. Watters. The measurement, cost and control of
traffic dust and gravel roads in Seattle's Duwamish Valley.
Paper No. AP-72-5 presented at the Annual Meeting of the
Pacific Northwest International Section of the Air Pollution
Control Association, Eugene, Oregon, November 1972.
3. Negri, S. Anti-dust chemicals fail county test. Tucson
Daily Citizen, p. 31 (October 9, 1972).
4. Scott, R. B. Meeting with counties regarding dust from
unpaved roads. Inter-office memorandum, Arizona State
Department of Health (April 7, 1972.
5. Ryckman, Edgerley, Tomlinson and Associates, Inc. Develop-
ment of Emission Factors for selected dust producing
sources. Report to the State of Arizona Division of Air
Pollution Control, September 20, 1971.
6. Langley-Cook, B.A. Air pollution particulate mapping.
Dissertation, University of Arizona, Department of Civil
Engineering (1971).
AGRICULTURE
7. Chepil, W. S. Dynamics of wind erosion: I. Nature of
movement of soil by wind. Soil Sci. 60(4): 395-320 (1945).
8. Woodruff, N. P. and F. H. Siddoway, A wind erosion
equation. Soil Sci. Soc. Amerc. Proc. 29(5): 602-608 (1965).
9. Chepil, W. S. Influence of moisture on erodibility of
soil by wind. Soil Sci. Soc. Amer. Proc. 20(2) : 288-292
(1956) .
10. Skidmore, E. L. and N. P. Woodruff. Wind erosion forces
in the United States and their use in oredicting soil
loss. Agr. Handbook 346. U. S. Dept. Agr., Washington,
D. C. (1968) .
11. 7_:relle, J. W. Adaoting basic wind erosion research data
A-l
-------
for field use on non-irrigated cropland. U. S. Dept.
Agr. SCS (1965).
12. Chepil, W. S. Erosion of soil by wind. 1957 Yearbook cf
Agriculture, pp. 308-314.
13. Craig, D. G. and J. W. Turelle. Guide for wind erosion
control on cropland in the Great Plains States. U. S.
Dept. Agri SCS, Washington, D. C. (1964) .
14. Woodruff, N. P. and D. V. Armbrust. A monthly climate
factor for the wind erosion equation. J. Soil Water
Conserv., pp. 103-104 (May-June 1968).
15. Hagen, L. J. and N. P. Woodruff. Air pollution from
duststorms in the Great Plains. (Accepted for publication
in Atmospheric Environment) U. S. Dept. Agr., Manhattan,
Kansas.
16. Stallings, J. H. Mechanics of wind erosion. U. S. Dept.
Agr. SCS, TP-108 (1951).
17. Weir, Walter W. Subsidence of peat lands of the Sacra-
mento-San Joaquin Delta. Agricultural Extnsion Service,
San Joaquin County, California.
18. Chepil, W. S. and N. P. Woodruff. How to control soil
blowing. U. S. Dept. Agr. Farmers' Bulletin No. 2169
(1961).
19. Chepil, W. S. Soil conditions that influence wind erosion.
U. S. Dept. Agr. Technical Bulletin No. 1185 (1958).
20. Lyles, L., D. V. Armbrust, J. D. Dickerson and N. P.
Woodruff. Spray-on adhesives for temporary wind erosion
control. J. Soil Water Conserv. 24(5): 190-193 (1969).
21. Zingg, A. W. and W. S. Chepil. Aerodynamics of wind
erosion. Agr. Engr. 31(6): 279-284 (1950).
22. Fryrear, D. W. and G. L. Randel. Predicting blowing dust
in the Southern Plains. Mp-1025, Texas Agr. Exp. Sta.,
Texas A & M University (March 1972).
23. Bocharov, A.P. and E. Yu. Terpilovsk. Study of the action
of machine-tractor units on the upper soil layer. Elec-
trification and Mechanization of Soviet Socialist Agriculture
8: 11-14 (1970). Translation by National Tillage Machinery
Laboratory, Auburn, Alabama.
24. Armbrust, D. V. and J. D. Dickerson. Temporary wind
erosion control: cost and effectiveness of 34 commercial
-aterials. J. Soil Water Conserv. 26 (4) : 154-157 (1971) .
A-2
-------
25. Black, A. L. and F. H. Siddoway. Tall wheatgrass barriers
soil erosion control and water conservation. J. Soil
Water Conserv. 26(3): 107-111(1971).
26. Schultz, H. B. and A. B. Carlton. Field windbreaks for
row crops. Calif. Agriculture, pp. 5-6 (November 1959).
27. Carlton, A. B. Sprinkling for bed stability and dust
control. Research report, Univ. of California, Davis
(November 1966).
28. Hayes, W. A. Mulch tillage in modern farming. U. S.
Dept. Agr. Leaflet No. 554 (1971).
29. Duncan, E.R. and W. C. Moldenhauer. Controlling wind
erosion in Iowa. Cooperative Extension Service, Iowa
State University (1968).
30. Facts about wind erosion and dust storms on the Great
Plains. U. S. Dept. Agr. Leaflet No. 394 (1961).
31. Ferber, A. E. Windbreaks for conservation. U. S. Dept.
Agr. Information Bulletin No.339 (1969).
CONSTRUCTION
32. Tucson Soil Chemicals. Quick, positive, low-cost way to
control dust in logging, mining and construction
operations. Product Information Bulletin - Norlig.
33. Moorheed, S. T. Where's the dust? Soil Conservation, pp.
232-233 (May 1972) .
34. Witco Chemical. Coherex manual for dust control. Product
Information Manual (1970) .
35. Paulson, M. C. Beware, buyer of dusty lots. National
Observer, P. 1 (June 10, 1972).
TAILINGS PILES
x
36. Dean, K. C., R. Havens and E. G. Valdez. Stabilization
of mineral wastes. Ind. Water
Engr., pp. 30-33 (October 1969).
37. Havens, R. and K. C. Dean. Chemical stabilization of the
uranium tailings at Tuba City, Arizona. U. S. Dept. Inter-
ior, Bureau of Mines, RI 7388 (August 1969).
38. Pettibone, H. C. and C. D. Kealy. Engineering properties
and utilization examples of mine tailings. Proceedings
of the Third Mineral Waste Utilization Symposium, Chicago,
Illinois, March 1972.
39. Dean, K. C., R. Havens and E. G. Valdez. Progress in
using and stabilizing mineral wastes. Presented at
A-3
-------
AIME Fall Meeting, St. Louis, Missouri, October 1970.
40. Dean, K. C., R. Havens and K. T. Harper. Chemical and
vegetative stabilization of a Nevada copper porphyry
mill tailing. U. S. Dept. Interior, Bureau of Mines,
RI 7261 (May 1969).
41. Dean, K. C. and R. Havens. Stabilizing mineral wastes.
Engr. Mining Journal, pp. 99 - 103 (April 1971).
42. Chemical treatment of waste tailings puts an end to dust
storms. Engr. Mining Journal, pp. 104-105 (April 1971).
43. Dean, K. C. and R. Havens. Reclamation of Mineral Milling
Wastes. Presented at the Annual AIME Meeting, San
Francisco, Calif., February 1972.
AGGREGATE STORAGE
44. Compilation of air pollutant emission factors. U. S.
Environmental Protection Agency, Office of Air Programs
Publication No. AP-42, pp. 8-17 - 8-19 (February 1972).
45. Chemical Binder solves material loss, provides dust con-
trol. DWL 1806-5M-171, Dowell Division of the Dow
Chemical Company, Tulsa, Oklahoma.
46. Denton, G. H., R. E. Hassel and B. E. Scott. Minimizing
in-transit windage losses of Olga low volatile coal.
Paper presented at the 1972 Coal Show, American Mining
Congress, Cleveland, Ohio, May 10, 1972. (Preprint by
Dowell Division of the Dow Chemical Company)
47. Dust suppressant clears the air at General Crushed Stone
plant. Rock Products, p. 63 (August 1971).
48. Chiaro, D.A. Significant operating benefits reported
from cement quarry dust control program. Pet and Quarry
(Jauary 1971).
49. Geesaman, J. Stone producer wins neighbors' acceptance.
Roads and Streets (July 1970).
50. Johnson - March Corporation. Chem-Jet dust suppression.
Product Information Brochure CJ2 (1963) .
FEEDLOTS
51. Elam, C.J., et al. Measurement and control of feedlot
particulate matter. Calif. Cattle Feeders Assn.,
Bulletin C (January 1971).
52. Algeo, J. W., et al. Feedlot air, water and soil analysis
Calif. Cattle Feeders Assn., Bulletin D (June 1972).
A-4
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GENERAL
53. Cowan, G. A., et al. Characterization and tracking of
aerosol sources with the use of aircraft sampling.
Research report, Univ. of Calif. Los Alamos Scientific
Laboratory (1971).
54. Marchesani, V. J. T. Towers and H. C. Wohlers.
Minor sources of air pollutant Emissions. J. Air
Pollution Control Assn. 20 (1): 19-22 (1970).
55. Barren areas treated for dust control. Public Works
October 1966).
56. Dust control for safety. Grounds Maintenance (May 1968).
57. Turner, D. B. Workbook of atmospheric dispersion esti-
mates. U. S. Dept. HEW, Nat. Air Pollution Control
Admin. Publication No. 999-AP-26 (1970).
58. Colder, K. L. Air pollution concentrations from a
highway in an oblique wind. (Accepted for publication
in Atmospheric Environment) EPA, Research Triangle
Park, N.C.
59. Vandegrift, A. E, and L. J. Shannon. Particulate
pollutant system study, vol. I—mass emissions. Midwest
Research Institute Project No. 3326-CB (1971).
60. Midwest Research Institute. Development of emission
factors for estimating atmospheric emissions from
agricultural tilling, unpaved roads and airstrips,
heavy construction site and aggregate storage piles.
MRI project No. 3669-C, EPA contract No. 68-02-0619 (current)
61. Arizona: selected land resource data. U.S. Dept. Agr ,
Soil Conservation Service (1969).
A-5
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APPENDIX B
FIELD OPERATIONS
GUIDEBOOK
LOCATION:
srrE CODE NO,
Fugitive Dust Project
August 1972
B-l
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CONTENTS
Project Communications
Telephone Directory
Sampling Site Code
Operations and Procedures
Supply, Handling, and Shipment
of Sample Media
Sampling Schedule
Operator's Log Sheets
B-2
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PROJEC
OMMUNI CAT I ON S
The fugitive dust study is a joint project among air
pollution control agencies at many levels. The study also has
several outside participants. Due to the large number of
groups actively involved and their dispersed geographical
locations, project coordination and communications are expected
to present continuing problems. This brief description of
project responsibilities and the attached telephone directory
have been prepared in an attempt to reduce these problems
Responsibilities are generally broken down as follows:
overall project coordination
EPA Regional representation
sampling study design
sampling equipment setup
control techniques evaluation
control strategy development
designated site maintenance
records of source activity
at microstudy sites
mapping of fugitive dust
source locations
EPA Durham, David Dunbar
(Stds Development &
Implementation Division)
Region VI, George Bernath
Region IX, David Howekamp
PEDCo- George Jutze/
Environmental Ken Axetell
designated state and local
agencies for each sampling
microstudy or AQCR
Specific assignments for the seven microstudies during the
sampling program are delineated in the detailed protocols that
were developed for each microstudy. The seven study locations
and agencies responsible for their maintenance are:
Site
Code No.
Location
Maintaining
Agency
Rl Thornydale Road, Tucson, Arizona
R2 i Irvington Road, Tucson, Arizona
R3 'Treatment Plant Road, Santa Fe,
. New Mexico
; Paradise Valley construction area,
i Phoenix, Arizona
Paradise Village construction area,
Las Vegas, Nevada
Westside Agricultural Station,
Five Points, Calif.
Mesa Agricultural Site, Mesa, Arizona
Pima County
Health Dept.
Pima County
Health Dept.
New Mexico Envir
mental Improveme
Agency
Arizona APCD
ClarK Co. Health
Dept.
Fresno Co. APCD
Ilaricopa Co.
Health Dept.
6-3
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If a problem or question arises during the project, the list
below is provided as a guide to get a rapid response:
problem or Question
Group to
Contact
Name to
Contact
Equipment breakdown or
operating procedure
Emission mapping
Sample handling problems
Preliminary data requests
Part-time personnel administration
Private property access
Questions on schedules or
responsibilities
Activity logs
Others
PEDCo
PEDCo
PEDCo
PEDCo
PEDCo
EPA R.O./PEDCo
EPA Durham
EPA R.O./PEDCo
EPA Regional
Office
Bill Parker
George Jutze
Larry Elfers
George Jutze
George Jutze
Gary Bernath
David Howekamp
David Dunbar
Ken Axetell
Gary Bernath
David Howekamp
After the sampling equipment has been set up and dry run,
operation will be transferred to the designated agency personnel
EPA Regional Office staff will spend a few days at each of the
sites during the initial week of sampling, in most cases the
v:eek of August 21. They will also make one-day return visits
at approximately biweekly intervals for the remainder of the
sampling period. A PEDCo instrument specialist will have one
scheduled visit to all of the sites in mid-September. This
trip will be in conjunction with a short-term study at the
Santa Fe site. EPA and PEDCo project staff will make additional
trips to the study areas while working on other phases of the
project. Their travel schedules are not yet fixed.
A directory of telephone numbers is presented on the following
page.
B-4
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TELEPHONE DIRECTORY
Name
Albuquerque-Bernalillo Health Dept.
Arizona Division of Air Pollution
Control
California Air Resources Board
Clark County Health Dept.
Davis-Monthan Air Force Base
Dobson Ranch
EPA Durham
EPA Region VT (Dallas)
EPA Region IX (San Francisco)
Fresno County Air Pollution Control
District
Maricopa County Health Dept.
Mesa Study Site
Dobson Ranch Office
Mesa Community College
Mesa Fire Station 4
1157 Farmdale
Nevada Dept. of Health
New Mexico Environmental Improvement
Agency
Paradise Valley Site
Hancock Construction Co.
Nelson Ranch
5110 East Paradise
5336 East Cactus
5335 East Windrose
PEDCO-Environmental
PEDCO Consultant
Pima County Health Dept.
Pima County Highway Dept.
Santa Fe Site
Santa Fe Airport
Sewage Treatment Plant
Thornydale Road Site
Anderson Engineering
Westside Agricultural Station
Contact
Harry Davidson
James Lareau
Norman Schell
Bruce Scott
Harmon Wong-Woo
John Kinosian
Don Arkell
Jeanette Smith
Col. Paul Copher,
Base Commander
Dwight Patterson
David Dunbar
Marty Martinez
Norman Thomas
Gary Bernath
David Howekamp
Terry Stumph
Norm Covell
Dan Dobrinen
Robert Taylor
Grant Johnston
Dwight Patterson
Bill Hollenbeck
Wayne McGinnis
Richard Serdoz
David Duran
Robert Harley
E. W. Nelson, Jr.
Roy Green
Peter Lucas
Marshall Field
George Jutze
Bill Parker
Larry Elfers
Charles Zimmer
Frank Meadows
Ken Axetell
John Ensdorff
Wm. Griffith
Jack Ross
D. A. DiCicco
C. Williams
Gene Anderson
Richard Hoover
Phone No.
505-842-7432
602-271-5306
916-445-1511
702-385-1291
602-793-3900
602-838-3076
919-688-8146,
x486
919-549-4571
214-749-2921
415-556-2330
209-488-3239
602-258-6381
602-838-3076
602-833-1261
602-969-1374
602-947-6311
702-882-7458
505-827-2813
602-264-3434
602-948-2477
602-948-4617
602-948-3775
602-272-5661
513-771-4330
703-560-0218
602-792-8686
602-624-0411
505-982-0080
505-983-3848
602-792-3636
209-884-2411
B-5
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FUGITIVE DUST STUDY
SAMPLING SITE
CODE
NO.
Rll
R12
R13
R14
R15
R 16
R17
R18
R19
-
R21
R22
R23
R24
R25
R26
R31
R32
R33
R34
R35
R36
_
Cll
C12
C13
C14
C15
C16
C21
C22
C23
C24
C25
All
A12
A13
A21
A22
A23
•TV*——*
A24
SAMPLING STUDY
Thornydale Road
(Tucson), Lignin
4" base section
Thornydale Road,
single chip seal
Thornydale Road,
unpaved section
Thornydale Road
Irvington Road
(Tucson), Lignin 1"
penetration section
Irvington Road,
unpaved section
Treatment Plant Rd.
(Sante Fe),
eastern section
Treatment Plant Rd.
(Sante Pe),
western section
Sante Fe
Paradise Valley
construction site
Las Vegas
construction
site
Five Points
agricultural study
Mesa agricultural
study
SAMPLER LOCATION
]
75' from road
200' from road
600' from road
75' from road
200' from road
600' from road
75' from road
200' from road
600' from road
Thornydale at Lambert
75 ' from road
200' from road
600' from road
75 ' from road
200 ' from road
600' from road
75 ' from road
200' from road
600' from road
75 ' from road
200' from road
600' from road
sewage treatment plant
Capst. Catfeu ,Sftaa RH
4601 E. Cholla
5110 E. Paradise Dr.
5336 E. Cactus Road
5335 E. Windrose
Century Country Club
Cascade Mobile Homes
Cashman Jr. High
Capri Mobile Homes
Fire Station
Clark High School
water tower, Oakland Av.
Reservoir No. 2
near Lassen Ave.
Dobson Ranch
Mesa Community College
Mesa Fire Station 4
1157 Farmdale
EQUIPMENT
-1IVOL I
I
X
X
X
X
X
DIREC.IIMPACTION
ilVOL .
x
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
x
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
SAMPLER
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
^^
X
X
X
X
X
X
X
MET
SYSTEM
X
X
X
X
X
•••M^
B-6
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OPERATIONS AND PROCEDURES
0 High-Volume Sampler
1.0 GENERAL DISCUSSION
A 24-hour sample of air is passed thru an 8" x 10" glass fiber
filter, using a high volume air sampler, to determine the
concentration of suspended particulates in the air.
The high volume air sampler is an apparatus for collecting a
relatively large volume of air (1.5 to 2.0 cubic meters per
minute) and capturing its suspended particulate matter on a
filter. Concentration of particulates suspended in the
atmosphere is expressed as micrograms per cubic meter of air
(yg/nr3) .
The sampler consists essentially of a motor-driven blower and
a supporting screen for the filter ahead of the blower unit.
During the sampling operation, the sampler is supported in a
protective housing so that the 8" x 10" surface of the filter
is in a horizontal position. The sampler incorporates a
continuous flow device for recording the actual air flow over
the entire sampling period and a 7-day clock switch to start
and stop the sampler. An elapsed time indicator is used on
directional samplers to determine the number of minutes of
operation in the pre-selected sampling mode.
2.0 SAMPLING PROCEDURE
2.1 Carefully center a new filter, rougher side up, on the
supporting screen. Secure the filter with sufficient snugness
to avoid air leakage at the edges. Undertightening will allow
air leakage; overtightening will damage the sponge rubber
face-plate gasket.
2.2 Place the recorder chart in position. Check the recorder
pen for ink and check to insure that the tubing from the recorder
is properly attached to the sampler. Check the time and zero on
the recorder and adjust if necessary. Start the sampler by
rotating the 7-day switch timer to insure that the sampler is
operating properly and the recorder pen is inking.
2.3 Close the roof of the shelter and check the 7-day timer
for proper setting. On directional samplers equipped with
elapsed time indicators, the initial time in minutes shall also
be recorded.
B-7
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2.4 Following the end of the sampling period, check the
timer to insure that the sampler operated during the desired
period.
2.5 The exposed filter shall be carefully removed from the
supporting screen, grasping it gently at the long edges -
not at the corners. Fold the filter lengthwise at the middle/
with the exposed side in. Place it in the folded manila folder
and then in the envelope. Enclose the sample record card,
having entered the appropriate data. On directional samplers
equipped with elapsed time indicators, the total elapsed time,
in minutes, shall also be recorded.
2.6 Remove the recorder chart. Blot any excess ink and place
the chart in the envelope along with the folded manila folder.
Do not place the chart in the manila folder as any excess ink
wTll~ be absorbed by the filter.
0 Andersen Head Modification
1.0 GENERAL DISCUSSION
The Andersen modification consists of a four-stage, multiorifice
high-volume fractionating impactor with backup filter, which can
be operated as a component of the standard high-volume sampler.
It separates particulate matter into five aerodynamic size
ranges: 7 microns or larger, 3.3 to 7 microns, 2.0 to 3.3
microns, 1.1 to 2.0 microns, and 0.01 to 1.1 microns. It's
relation to the sample is shown in Figure 1.
2.0 FILTER HANDLING
When installing or removing the Andersen filters (5) the head
assembly should be removed by pulling the speed ball handle
straight up. After the assembly is removed the whole unit
should be taken to shelter (car, etc.) and each filter removed
from the assembly at that time. Care must be taken not to tear
the individual filters when installing or removing them from
the head - they are extremely fragile. The filters are
installed as shown in Figure 2 according to the sample numbering
sequence described in "Supply, Handling, and Shipment of Sample
Media."
3.0 FIELD MEASUREMENT
Tne Andersen unit has been calibrated in the laboratory prior
to field use. However, due to its application in this study,
8-8
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------- An error occurred while trying to OCR this image.
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it is necessary to measure the pressure drop across the filter
both before and after a sample is taken. A "U-tube" oil
manometer is used (see Figure 1) and the pressure is set to a
predetermined value (factor provided with each individual head)
at the initiation of sampling by varying the line voltage.
Both measurements are recorded under "Remarks" on the Data
Sheet. Care must be taken to insure that the manometer is open
at each end during use.
0 Impaction Samples
At selected sites in each study area, a vertical stand is
provided with flat plates welded on at three locations (3, 6,
and 10 feet above base level). These plates will support sticky-
paper impaction samples which will be microscopically analyzed
for particle size and physical characteristics. Samples will
be exposed and handled as described in the Sampling Media
section. The sampling locations are designated as follows:
#1 - 10 foot plate
#2 - 6 foot plate
#3 - 3 foot plate
B-11
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SUPPLY, HANDLING AND SHIPMENT OF SAMPLE MEDIA
1.0 ROUTINE HI-VOL AND DIRECTIONAL HI-VOL SAMPLING
Each study area is assigned a specific quantity of numbered,
pre-weighed 8" x 10" glass fiber filters. These filters are
numbered with a six digit figure beginning with 900001. Prior
to and after sampling (see Operations and Procedures) the
"Particulate Record Data Sheet" is to be filled out. An
example of a typical record sheet for a routine sample is as
follows:
Particulate Record Data Sheet
Fugitive Dust Study PN-3050-H
Study Area Operator
Site Location Filter No.
Sampler type: Hi-Vol Date
Hi-Vol with Andersen Time off:
Directional Hi-Vol Time on:
Remarks:
The following information must be recorded on this sheet.
0 Study area - state location and any assigned code number.
0 Site location - each study area will have several sampling
sites and specific locations which have been assigned a
numerical designation.
0 Operator - record first initial and last name.
0 Filter number - record the filter number, this number will
begin with 900,000 and is printed on the edge of the filter.
0 Sampler type - check the blank marked Hi-Vol or Directional
Hi-Vol.
0 Date - record date that sampler is activated.
0 Time on - record the time of day or the minutes from the
running time meter.
0 Time off - record the time of day or the minutes from the
running time meter.
B-12
-------
0 Remarks - use this space to make any remarks as to weather
conditions, instrument performance, etc. One can never have
too much data when it comes time to validate and interpret the
results.
Following a sampling period and completion of the particulate
record data sheet, the sample is removed from the sampler, as
described in Operations and Procedures, folded upon itself with
the dirty side inside. The filter is then placed in the card-
board protective folder. This folder and the flow recorder
chart from the Dixon recorder are placed in the envelope provided.
This envelope is marked as follows:
Date sampled
Filter No.
Site Remarks
The date sampled, filter number and site are the same as recorded
on the "Particulate Record Data Sheet." Under the remarks
position include the study area and its numerical designation.
Place the sample in the sample case provided. After completion
of field work, remove filter envelopes and place them in the
cardboard box provided. Every two weeks return all samples to
the PEDCo laboratory by Parcel Post using the cardboard box and
address labels provided. Prior to shipping firmly pack the
filters in the cardboard box and fill any empty areas therein
with soft packing to assure safe shipment of the filters.
2.0 HI-VOL WITH ANDERSON HEAD
The media for use with this sample consist of five filters, four
of which are round and one which is a standard 8" x 10" back-up
filter. These filters are packaged five to a folder and a
Particulate Record Data Sheet is included within each folder.
The Anderson Sampler is charged with the five filters, as
described in Operations and Procedures. Each pack of five
filters are numbered in succession according to the filter
position and its filter number; the first digit directs the
position in the Andersen arrangement and the last digit includes
the sample number. For example, the first packet of Andersen
filters are numbered as follows:
100001 1st filter
200001 2nd filter
300001 3rd filter
400001 4th filter
500001 Backup filter
B-13
-------
The Particulate Record Data Sheet is to be filled out as in
Section 1.1 with the following exceptions:
Filter No. - Record the first number and the last
number; for example, 100001 to 500001 would be
used for the first sample.
Sampler type - check the position which states
"Hi-Vol with Andersen."
Remarks - Use the area as before but include the
manometer readings from the instrument, record
them before and after test period, and include
the instrument's identification number since
these instruments will be moved from one location
to another and flow is dependent upon each
specific sampler.
After sampling, remove the filters as described in Operations
and Procedures and fold them against themselves with dirty
side inside. Place the plain white or yellow sheet of paper
used to separate the filters between each folded filter and
place them and the completed data sheet into their original
folder. This folder is marked in the same manner as the
envelope used for the standard and directional Hi-Vol sampler
and the information must be provided as previously.described.
Secure the folder with the three paper clips and place it into
the field carrying case provided. After completion of the
field work, place the filters in the same cardboard box as
mentioned previously and return it to the PEDCo laboratory on
the noted bi-weekly basis.
3.0 IMPACTION PLATES
Sticky paper plates, cut 3" x 4", are provided in envelopes
marked with the sampling date, site and remarks. Include in the
remarks the study area and its numerical designation. Each
piece of sticky paper is numbered 1 through 3 and is to be
positioned on the exposure pole in the manner described
previously. Before installation, remove the brown protective
cover from the sticky paper and place the paper in the
appropriate position on the pole using two rubber bands to
secure the paper to each metal plate on the pole. After exposure,
record the exposure date and duration on the envelope. Spray
the sample with clear lacquer paint and permit to dry before
placing them into the envelope. If there is any concern that the
plates will stick together, separate them with a thin plastic
film such as saran wrap before placing them into the envelope.
Return these samples to the PEDCo laboratory every two weeks in
the same cardboard box containing the other filters, as previously
described.
B-14
-------
LOG SHEET
DATE
TIME
SITE
CODE
NO.
EQUIPMENT
SERIAL
NO.
REMARKS
(Relocation, special activities,
equipment malfunction, power
failure, etc.)
B-15
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-------
SAMPLING SCHEDULE
MESA AGRICULTURAL - A2
SAMPLING
PERIOD
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
BEGIN
DATE
8/21
8/23
8/25
8/27
8/29
8/31
9/2
9/4
9/6
9/8
9/10
9/12
9/14
9/16
9/18
9/20
9/22
9/24
9/26
9/28
9/30
10/2
10/4
10/6
10/8
10/10
10/12
10/14
10/16
10/18
10/20
10/22
DURATION
(HOURS)
24
48
24
48
48
24
48
24
24
48
48
24
24
48
24
48
24
48
48
24
48
24
48
24
24
48
48
24
24
48
48
24
LOCATION OF ANDERSEN
A21 A22 A23 A24
A A
A * *
A A
A
A* A*
A A
A A
A* A *
A
A* *
A A
A
A * *
A
A A
A A
A A
A* *
A A
A* A*
A A
A
* A *
A A
* A A*
A
A A
A A
A* *
A A
A A
A A
NOTE: All Particulate Samplers must be operated according to
schedule.
A = Hi-Vol operated with Andersen
* = Collect impaction sample
B-17
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-------
SAMPLING SCHEDULE
LAS VEGAS CONSTRUCTION SITE - C2
SAMPLING
PERIOD
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
NOTE:
BEGIN
DATE
8/21
8/23
8/25
8/27
8/29
8/31
9/2
9/4
9/6
9/8
9/10
9/12
9/14
9/16
9/18
9/20
9/22
9/24
9/26
9/28
9/30
10/2
10/4
10/6
10/8
10/10
10/12
10/14
10/16
10/18
10/20
10/22
All Particulate
DURATION
(HOURS)
24
48
48
24
48
24
24
48
24
48
24
48
48
24
48
24
24
48
24
48
24
48
24
48
48
24
24
48
48
24
24
48
Samplers
LOCATION
C21 C22
A
A
* A*
A
A
* A*
A
* A*
A
* A*
A
A
A
* A*
A
* A*
* *
* *
* *
* *
must be operated
OF ANDERSEN
C23
*
*
*
*
*
*
A
A
A*
A
A
A*
A
A
A
A*
A
A*
A
A
A
A
accordin
C24
*
*
*
»
*
*
*
*
*
*
q to
schedule.
A = Hi-Vol operated with Andersen
* = Collect impaction sample
B-19
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-------
SAMPLING SCHEDULE
IRVINGTON ROAD SITE - R2
SAMPLING
PERIOD
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
BEGIN
DATE
8/21
8/23
8/25
8/27
8/29
8/31
9/2
9/4
9/6
9/8
9/10
9/12
9/14
9/16
9/18
9/20
9/22
9/24
9/26
9/28
9/30
10/2
10/4
10/6
10/8
10/10
10/12
10/14
10/16
10/18
10/20
10/22
DURATION
(HOURS)
24
48
24
48
48
24
48
24
48
24
24
48
48
24
24
48
48
24
48
24
48
24
24
48
24
48
24
48
24
48
24
48
R2 1 R2 2
* A*
A
A
A
* A*
A
* A*
A
A
A
* A*
A
A
A
A
A
* A*
A
* A*
A
A
* A*
A
A
A
* A*
A
A
v A*
A
A
A
LOCATION OF
R2 3 R2 4 R2 5
* <• A*
A
A
A
* * A*
A
* * A*
A
A
A
* * A*
A
A
A
A
A
* * A*
A
* * A*
A
A
* * A*
A
A
A
* * j^*
A
A
* * A*
A
A
A
ANDERSEN
R26
*
*
*
*
*
*
*
*
*
NOTE: All Particulate Samplers must be operated according to schedule
A = Hi-Vol operated with Andersen
* = Collect impaction sample
B-21
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-------
August 30, .1.372
0 DRAFT PROPOSAL °
AIR SAMPLING STUDY FOR DUST FROM UNPAVED ROADS
Introduction
This is the outline for the first special air sampling study to quantify the
emissions of dust from unpaved roads. Its objective is to better define
some variables which affect the emission rate of dust from unpaved roads,
but which cannot be evaluated from 24- and 48-hour hi-vol readings.
A second and possible third intensive short-term study similar in scope to
this one may be required to fully delineate the effect ofvariables such as
traffic volume, average vehicle speed, and wind speed. They will not be
planned until the data from this study have been obtained and analyzed.
Study Requirements
Location: Sante Fe, road to the municipal sewage treatment plant
Personnel: total of 5 or 6
drivers of test vehicles - from 3 to 5
instrument monitors - 1 or 2
Time: 2 days when the wind has a consistent southerly conponent
SuppliesI 6 hi-vols (already in place)
. filters for hi-vols
data sheets (examples attached)
beta gauge mass particulate sampler
particle- counter (optional)
transit
traffic counters (already in place)
wind speed and direction recorder (already in place)
tape measure
step ladder ,
stop watches
signs to direct public traffic
Short-term Study #1 with Hi-vols
Primary
Variable: vehicle speed
Duration: full day (first day)
B-23
-------
Design:
a constant traffic volume : during each ,
ofMO v*tel»
when traffic is uncontrolled.
10:00a - 12:00n
12:30p - l:30p
2:00p - 3:00p-
15'mph
55 mph
30 mph
mph
5 vehicles full time
3 vehicles full time
5 vehicles full time
4 vehicles full time
as shown in the diagram below:
conditions)
B-24
-------
Product:
start-up and stop of samplers by electrical plugs at the 2
power poles
important correction to the raw sampling data
total traffic volume over the two counters should be recorded
on the data sheet
ss
with posted speeds.
the filters must be changed "and data sheets completed between
the sampling periods
this study should result in a plot of emission impact versus
.v^Mcle ^ed such as shown below (the shapes of the curves
are hypothetical ) :
75' from road
00' from road
1 from road
average vehicle speed —^
3-25
-------
Short-term Study #2 with Hi-vols
Primary
Variable:
Duration:
Design:
Product:
traffic volume
full day (second day)
all vehicles traveling at 45 mph, with the following traffic
volumes for each test segment:
250, 500 vehicles
50, 150 vehicles
350 vehicles*
4 vehicles: full time
3 vehicles
4 vehicles full time
10:68a - 12:00n
l:00p - 2:00p
2:30p - 4:00p
•samples on portion of test area west of gravel pit entrance
the driving pattern will vary with each portion of the test
other parts of the study design are the same as in Study #1
this study should either confirm of reject the proposed direct
relationship between emission impact and the number of vehicles
traveling, a given roadway. This relationship is plotted
graphically below:
vehicle travel
Plume Traversing Study #1
Duration: first day, 12:30 - 1:30 pm
Design- this study will be run In conjunction with the last segment of
the vehicle speed investigation
instrumentation will be the beta gauge mass
^e to 8 minute samples will be taken at several points
Plu«£ of dust from the road in an attempt to detente
antity of material emitted per vehicle-mile of travel
B-26
-------
because of the required sampling period of 1 to 8 minutes, the
plume density from a single car cannot be measured. Therefore,
a semi-continuous plume emanating from a line of cars must be
sampled
if appropriate, simultaneous readings can be taken with
a particle counter supplied by the New Mexico agency
Since this initial traversing study will be used to
perfect the beta-gauge sampling technique, no estimators
of the height of the plume will be made
only total particulate samples will be taken during this
run, for a total of 12 samples requiring 30 minutes
sampling time during the 60 minutes of controlled test
traffic
samples are to be taken at or near the locations of
the particulate samplers in the high traffic density
portion of the test area according to the specifications
below:
distance from road, ft. 50 75 125 200
length of sampling, min. 1 1 4 4
height above ground, ft. 3,6,10 3,6,10 3,6,10 3,6,10
the vertical and horizontal measurements of plume
density together with the estimate of plume height can
be used to develop an equation of particulate mass in
the plume per unit of roadway length. A cross-section
of the sampling set-up is shown below:
r
•
Boa a OAKY
•* Ptu-
\
V,
• Ml- VOL.
BETA GAU-C* SAKIPLCS
B-27
-------
Plume Traversing Study #2
Duration: second day, 10:00 am - 12:00 noon
Design: this study will be run in conjunction with the first segment of
the traffic volume investigation
the beta gauge will also be used in this study. Two fractions
will be sampled: total particulate matter (approximately 1 to
100 microns diameter) and the respirable fraction (all smaller
than 2 microns and a gradation of larger particles up to 10
microns}
the vertical boundary of the plume will be estimated by
transit measurements and triangulation. The exact site
for locating the transit will be determined after field
inspection
as before, samples are to be taken at or near locations of the
Hi-Vol samplers. Travel past this point is 250 vehicles per
hour, or one car every 15 seconds
because wind speed and direction is so critical to this study,
accurate correlation between the wind data generated at the
sewage treatment plant and the sampling data is necessary.
This can be accomplished by accurately noting the time of the
beta gauge samples on the data sheets. Data to determine
atmospheric stability conditions at the time of 'sampling should
also be recorded
due to the duplication of sampling for total and respirable
particulates, 26 readings requiring 94 minutes of sampling will
be needed during the 120 minutes of controlled test traffic
B-28
-------
sampling locations are specified in detail as follows:
distance from road, ft, 50 75 125 200 300
respirable particulate
sampling, min. 448
total particulate .
sampling, min. 1448
height above ground, ft. 3,6,10 3,6,10 3,6,10 3,6,10 6
Plume Traversing Study #3
JXiration: second dajt, 2:30 pm - 4:00 pm
Design: this study will be run in conjunction with the final segment of
the traffic volume investigation
the beta gauge sampler will be used in this study to measure both
total and respirable particulates. Instead of sampling a vertical
profile at different distances from the road, all samples will be
taken at 6 feet above grade at 5 different distances from the road
with the sampling times specified below, the beta gauge will be
in operation for 64 of the 90 minutes of controlled traffic:
distance from road, ft. 50 75 125 200 600
respirable particulate
4 A. 0 a a
sampling, min. ° ° °
total particulate ,
sampling, min. 44888
height above ground, ft. 6 6 6 6 6
longer samples are to be taken in this series than in Studies
1 and 2 for increased accuracy
transit readings will also be taken for the 90 minutes of thJs
sampling period, from the same location and at the same intervals
as in the previous study
this traversing study will be conducted at or near the
western most series of hi-vols
NOTE: If earlier samples indicate that particulate
concentrations 600 ft. from "the roadway will be lower
than instrument sensitivity, the furthest 's'ampling
point from the road may be changed to' 300 ft.
B-29
-------
DATA SHEET FOR SPECIAL HI-VOL STUDIES
TEST SEGMENT
DATE
STARTING TIME
ENDING TIME
DURATION OF SEGMENT
INITIAL TRAFFIC COUNT
BY ANDERSEN SAMPLERS
FINAL TRAFFIC COUNT
BY ANDERSEN SAMPLERS
TRAFFIC VOLUME
INITIAL TRAFFIC COUNT
BY HI-VOLS
FINAL TRAFFIC COUNT
BY HI-VOLS
TRAFFIC VOLUME
AV. VEHICLE SPEED
AVERAGE WIND SPEED
RESULTANT WIND DIR.
FILTER NUMBERS
ANDERSEN'S:
75 « FROM ROAD
200' " "
600' " "
HI-VOL'S
75' FROM ROAD
200' " "
600" " "
REMARKS
1
2
3
4
5
B-30
-------
DATA SHEET FOR PLUME TRAVERSING STUDIES
DATE
STARTING TIME
ENDING TIME
DURATION OF TEST
INSTRUMENT
OPERATED BY
DATA SHEET BY
LOCATION OF SAMPLING
INITIAL TRAFFIC COUNT
FINAL TRAFFIC COUNT
TRAFFIC VOLUME
AV. VEHICLE SPEED
CONCURRENT PHOTOGRAPHY
LOCATION OF CAMERA
RESPIRABLE DUST SAMPLING
TRAVERSE DATA: Record sampling time above slanted line and particulate concentration below
DISTANCE FROM ROAD, FT.
TOTAL OR
RESPIRABLE
HEIGHT ABOVE
GROUND, FT.
B-31
-------
GUIDELINES FOR DEVELOPING
A FUGITIVE DUST
EMISSION SURVEY
This guideline has been prepared to aid in the developing of
a fugitive dust emission survey for selected AQCR's. The
emissions will be calculated from the impact factors derived
from the fugitive dust micro-studies for unpaved roads,
agricultural and construction activities. The impact from
other minor fugitive dust sources will be derived from
personnel contacts and literature searches. Strength factors
multiplied by the relative distance from the maximum par-
ticulate matter receptor site will provide the impact or
relative emissions from each source of fugitive dust.
B-32
-------
I. Significant Fugitive Dust Sources
It will be necessary to survey the fugitive dust emissions
before a control strategy can be developed to attain and maintain
the national standards.
The following table should be completed for each county in
the air quality control region for which a control strategy is
to be developed. Please indicate by a check the significant
sources of fugitive dust for each county.
The following list of the AQCR's and counties are those for
which fugitive dust strategies may be required to achieve the
national standards.
California
San -Joaquin AQCR
Amador
Calaveras
Fresno
Kings
Madera
Mariposa
Merced
San Joaquin
Stanslaus
Tulare
Tuolumne
Kern - (portion)
Arizona
Phoenix-Tuscon AQCR
Gila
Maricopa
Pima
Pinal
Santa Cruz
New Mexico
El Paso - Las Cruces
Alamogordo AQCR
Dona Ana
Otero
Nevada
Clark-Mohave AQCR
Clark
Nevada Intrastate
Churchill
Elko
Esmeralda
Eureka
Humboldt
Lander
Lincoln
Mineral
NYE
Pershing
White Pine
Northwest Nevada AQCR
Carson City
Douglas
Lyon
Storey
Washoe
Alguquerque - Mid Rio Grande AQC1
Bernalillo
Sandoval -
Valencia -
(portion)
(portion)
Lincoln
Sierra
B-33
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-------
II. Survey Data Necessary for the Entire Air Quality Control
Region (not necessarily geographically distributed)
The following table provides the necessary data to develop
a fugitive dust emission survey and the sources from which the
information may be obtained.
Determining emissions from unpaved roads requires more
detailed information and therefore a footnote has been provided
to clarify the necessary data required.
B-35
-------
SURVEY DATA
Fugitive
Dust Source
Desired Data
Source From Which
Information May Be Obtained
Construction
Activity
1. Acres of active con-
struction
2. General type of con-
struction
3. Duration of project
1. Building permits
2. Planning commission
3. Building or trade associa-
tions
Agricultural
Activity
1. Acres of active
agricultural activity
2. Acreage by crop
3. Crop rotation by year
1. State Soil Conservation
Office
2. County Agricultural Exten-
sions
3. State Agricultural Depart-
ment
4. Farmers or Growers Trade
Associations
Land Clearance
for Real
Estate
Development
1. Acres cleared
2. Type of development
anticipated
3. Amount of regrading
1. State and local realtors
and home builders associa-
tion
2. Local planning commission
3. Local building department
Tailing Piles
1. Acres of inactive, 1,
unstabilized tailings
2. Tons of ore mined 2,
3. Mining operations at 3,
each mine 4,
State Department of Mining
and Minerals
Minerals Yearbook
State Mining Association
Individual mining companies
Aggregate
Storage Piles
1. Type of material
2. Tons of material in
storage
3. Turnover or through-
put rate
1. Individual companies, e.g.
sand and gravel, quarrying
and others with known
aggregate piles
Off-road
Recreational
Vehicles
Motorcycle registra-
tion by county
Population of other
off-road vehicles
Size and usage of
noncommercial unpaved
racing areas
1. State motor vehicle regis-
tration
2. Local police, county
sheriff's offices
Cattle feed
Lots
1. Number of cattle and
acres of feedlots
1. Cattle Feeders Association
2. County Agricultural Exten-
sions
3. County Planning Commission
Unpaved air-
strips , park-
ing lots, etc,
1. LTO at each airstrip
2. Number and capacity
of unpaved parking
lots
1. Airport offices
2. County Planning Commission
Unpaved roads 1. Vehicle miles
1. County or State Highway
Department
B-36
-------
*The desired data is total daily or annual vehicle miles on
unpaved roads per county or grid. This can be outlined from
either of two approaches.
1. If traffic volume estimates are available:
(a) On a county map, make and measure the mileage of the
unpaved roads
(b) Check the total mileage of unpaved public roads
against records of State or County Highway Department.
Some states even publish countywide totals annually.
(c) Estimate traffic volume on each length of unpaved
road, either from daily traffic county data or county
highway estimate.
(d) Multiply road mileage by daily traffic count to obtain
vehicle mile per length
(e) Sum vehicle miles for all roads in the county to obtain
the total for the entire county
2. If no traffic column estimates are available (in
predominately rural counties)
(a) Obtain annual county gasoline sales (gallons) from
State Revenue Department
(b) Estimate total annual vehicle miles in county =
(14.7 mi/gal) X (gasoline sales - gal)
(c) Determine vehicle miles on paved highways by procedure
outline in
(1) above.
(d) Convert daily vehicle miles to annual
(e) Subtract vehicle miles on paved road from estimate of
total vehicle miles to get vehicle miles on unpaved
roads.
B-37
-------
III. Detailed Information on Sources With Impact on Hi-Vols
Used in Control Strategy Calculations
In areas immediately surrounding the few hi-vol samplers
in each air quality control region that were used for par-
ticulate matter control strategy testing in the implementation
plan, fugitive dust sources are of extreme importance because
of their impact on measurements at these sites. More detailed
information than that specified above is necessary in these
areas, so that the contribution from the fugitive dust sources
can be estimated accurately.
Primarily, the additional data desired are the locations
of the sources in relation to the hi-vol sampling sites. Other
data which would be helpful in estimating emissions include
weekly or seasonal variation in source activities, dust control
procedures in use and specific operations for certain
meteorological conditions that result in higher emission levels.
The general procedures recommended to obtain and record
this additional information is to work from a large scale map
or aerial photograph of the area surrounding each specific
hi-vol site. The exact location and extent of the fugitive dust
sources should first be determined by ground level inspection
of. the area and then marked clearly on the map. Additional
information on each source should be recorded in the attached
tables .
Previous work has indicated that area sources within 20,000
meters of a hi-vol may affect the readings. Therefore, all
significant fugitive dust sources within this radius should be
inventoried individually and located on the map.
A step-by-step outline of this emission mapping procedure is
presented below:
B-38
-------
Obtain an appropriate map or aerial photograph of the
area surrounding the hi-vol site. (If available, 1 inch =
500 - 1000m.)
Locate hi-vol site on the map and draw a 20,000 meter
radius circle on the map, using the site as the center.
Verify the exact location and extent of the fugitive
dust sources within the circle by ground level inspection.
Mark the location and consecutively number each source
on the map
Record additional information on each source in a format
such as that shown in the attached table. The sources
should be identified by the numbers used on the map.
Indicate location on the same map of any particulate matter
point sources, and provide any updated emission data on
these sources (in the format used for control strategy
testing in the implementation plan).
B-39
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APPENDIX C
DATA FORMS
Agricultural Activity Log
General information
Site code
Location (street/or city) ~
Day of week
Date ZH^HIZI Time of daY
Meteorological conditions
Daily prevailing wind direction
Daily measurable precipitation
Temperature
Cloud condition '
Other observations
Equipment utilized
Tractor
Plow
Tiller
Cultivator
Combine
Other
Work area
Estimated number of acres
Approximate boundary
Type of activity
Plowing
Tilling
Cultivating
Planting
Other
Control measures
Watering
Chemical stabilizing
Other
C-l
-------
Construction Activity Log
General information
Site code
Location (street/or city)
Day of week
Date ZZZZZHHZZI Time of
Meteorological conditions
Daily prevailing wind direction
Daily measurable precipitation
Temperature ~
Cloud condition
Other observations "~~
Equipment utilized
Bulldozer
Grader "~~
Front loader "
Back hoe
Dump truck ~~
Crane
Scraper/or pan
Compressor "
Asphalt truck ~~
Cement truck ~
Water truck "~
Other ~
Work area
Estimated number of acres
Approximate boundary
Amount of earth moved
Type of activity
Earth moving
Grading & leveling
Digging
Masonry
Iron & steel erection
Carpentry
Finishing
Seeding
Other
Control measures
Watering
Chemical stabilizing
Other
C-2
-------
Unpaved Road Log
General information
Site code
Location (street/or city)
Day of week
Date Time of daY
Meteorological conditions
Daily prevailing wind direction
Daily measurable precipitation
Temperature . .
Cloud condition
Other observations
Type vehicles on road
Auto
Trucks
Farm equipment
Construction equipment
Other
Road description
Length
Access off road
Estimated vehicle count/day
Surface type
Other
Control measures
Watering
Chemical stabilizing
Other
C-3
-------
COUNTY FACT SHEET
FOR ESTIMATING FUGITIVE DUST LOSSES
1. UNPAVED ROADS
Name of
Unpaved Road
Length of
Road , mi .
Av . Daily
Traffic*
Name of
Unpaved Road
Length of
Road , mi .
Av. Daily
Traffic*
*estimate, if no traffic counts are available
D 2« AGRICULTURAL ACTIVITY
Major Crops
Acres in Crop
Amount of Residue
& Stubble per acre
Dry sieve analysis: representative farmland soil
has % greater than
0.84 mm (No. 2C standard sieve)
Total of 12 monthly potential evaporation indices
(P-E index) =
Types of Farmland Soils:
clay (subject to
granulation)
silty clay
silty clay loam
clay loam
loam
silt loam
silt
sandy clay
sandy clay loam
sandy loam
fine sandy loam
very fine sandy
loam
loamy very fine
sand
loamy sand
tint: sand
sand
very fine sand
wet or stony
soils not sub-
~'ect to wind
Average wind velocity at 30 ft. height =
C-4
-------
Q 3. CONSTRUCTION ACTIVITY
Name of Construction
Site*
•till out tor cu.
Type of
Construction
crent or recen
Acres of Active
Construction
t 12 -month period
Duration,
months
Watering
on Site
4. LAND CLEARANCE FOR REAL ESTATE DEVELOPMENT
Name of Real Es-
tate Development
Type of Develop-
ment Anticipated
Acres Cleared
Amount of
Regrading
5, MHNING ft.ND TAILINGS PILES
Wame of Mine
Ore Mined,
tons/year
Mining Operations,
Size of Pit
Acres of Inactive,
Unstabilized Tailings
Remarks
6. AGGREGATE STORAGE PILES
Name of
Process ing Co.
—
Type of
Material
Tons of Material
in Storage
— - ---- - -
Turnover or
Throughput Pate
. _ - .._
Watering
__. - .
D 7. CATTLE FEED LOTS
Name of Feedlot
No. of Cattle
Acres
Watering
Remarks
•*•
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TABLE D-2
Diffusion Calculations - Irvington Road Site
q = x y^T °7. u
(sin ) exp F-.
Get stability class from av. wind speed and table on p. 6 of Workbook,
assuming moderate solar radiation during day.
x,
meters
23
3
o
1 f °Z'
x = x + 15 i meters
38 ' 2.9
H,
meters
2
fcT
.476
-a
e
.787
degrees
45
' 2.9 ! 1.476 '.787 i 45
4.4
.207 :.905I 45
4.4 .207 ,.905', 45
2.9 i '.476 .787 90
4.4 i.207 '.9051 45
sin (j)
.707
.707
X/ 3
mg/m
.196
u,
m/sec
3.1
.216 3.1
.707 .272 ; 2.7
.707 .333 2.2
1.000 ' .370 4.5
.707 • .330 : 2.2
q' 1
mg/m/sec i
i
f
3.97
4.85
1 6.313
1 6.30
! 7.59
1 6.24
q,
tons/mi/yr
230
281
365
365
439
361
183
198 13
13
20 ;
20
13
•
2 .024
.024
.010
.010
.024
.98
.98
.99
.99
.98
45
45
45
45
90
i .707
! .707
1 .707
i .707
U.OOO
1
.025 -
.169
.062
.110
.069
3
3
2
2
4
.1
.1
.7
.2
.5
1
12
5
8
5
.82
.29
.94
.58
.15
av. =
105
711
344
497
29b
360
-------
TABLE D-3
Diffusion Calculation - Thornydale Road
q =
N/27
u
(sin (f>). 2 exp V- 1/2
Get stability class from av. wind speed and table on p. 6 of Workbook,
assuming moderate solar radiation during day.
x' az, ! H, ]/H_V , __ j
meters x1 = x + 15 meters i meters !la7 I : e '
» z/ ;
i ; f
23 38 4.4 2 .207 .90
2.9 2 .476 .787
o 4.4 2 .207 .90 \
.707
.707
.707
.-924
.924
.707
.924
.924
.707
.707
.707
.924
.924
.707
.924
.924
X, U,
mg/m^ m/sec
.256 2.2
.219 3.6
.282 3.1
.459 3.6
.449 4.5
.391 2.2
.329 3.1
.390 1.8
.075 2.2
.076 3.6
.092 3.1
.146 3.6
.106 4.5
.107 2.2
.141 3.1
.115 1.8
s
q/
mg/m/sec
4.87
5.14
7.55
8.24
10.07
7.43
6.76
4.65
5.83
6.84
10.08
10.05
9.12
8.32
11.82
5.6
„
q>
tons/mi/yr
282
298
437
477
583
430
391
269
338
396
584
582
528
482
684
324
iv. = 443
-------
TABLE D-4
Diffusion Calculations - Agricultural Sites
Q = 2.78 x (1TavazU)
—
x, y
Site meters
A-12 250
Five 150
-otnts 150
250
A-21 30 1
Mesa
_— — - — — • — •
o x ,
S meters
4.3
92 560
560
560
860
.85 1850
A~24 315 185 1210
Mesa
x1 = x + xy
810
710
710
1110
1880
1525
1
Data
9-28
9-26
9-22
8-21
9-26
9-18
9-30
9-28
Stability
Class
B
B
' B
C
C
C
B
B
a , ( oz, U,
meters meters m/sec i
i [—
1
128 87 i 3.1
116 75 2.2
116 75 3.1
115 67 4.0
186 108 3.1
186 108 3.6
228 172 2.7
228 172 2.7
x / Q' Q '
mg/rn3! g/sec tons/yr
1
.
.039 11.8 41 1
.026 5.0 174
.029 7.9 r/b
.035 9-5 ^1
av . - >'CSH
.019 10. J Ji>9
.037 ; 23.3 811
.023 21.3 7*2
.072 66.6 'nw
av . - 10 1. B
-------
TABLE D-5
Diffusion Calculations - Construction Sites
Q = 2.78x (irayazU)
cry
x,
Site meters ;
C-21 650
Las
Vegas
C-23 525 :
Las
Vegas
yn C-14 315 1
Mari-
copa
C-15 758 3
M^ T* i —
Aid .L. -L.
copa
C-16 1575
Mari —
copa
!
o x , j
S meters x = x + xy 1 Data
4.3 1
56 ' 510 ' 1160 8-25
330 . 980 8-27
i
56 510 , 1035 8-29
510 1035 9-10
16 720 : 1035 9-4
9-12
9-16
9-20
.16 720 1478 9-4
9-12
9-16
85 520 2095 9-6
9-16
9-20
9-30
i '
i < .
Stability
Class
C
B
i
C
1
\
! B
B
B
B
B
B
f B
] B
i B
1 B
*
S T3
i B
i
{
\
meters
118
152
107
107
159
159
159
159
159
223
' 223
| 223
i
300
J 300
300
300
;
meters
69
107
63
63
112
112
112
112
112
170
i 170
170
240
| 240
i 240
240
s
u,
m/sec
3.6
2.7
3.6
5.4
!
2.7
2.7
1.2
0.9
0.9
2.7
2.7
0.9
1.2
0.9
0.9
2.2
f
i
Xr,,
mg/m°
.092
.122
'
!
.162
.091
i .180
.220
.130
' .090
.155
.140
.215
.100
.040
: .020
, .065
.020
E
Q,
g/sec
23.6
46.8
34.3
28.9
75.6
92.3
j 24.2
! 12.6
i 21.7
125.0
192.0
29.8
t
30.2
11.3
36.7
27.6
j
Q,
tons/yr
821
1623
1193
1006
av. = 1162
2630
3212
: 842
i 438
! 755
! 4350
1 6681
1037
1
1051
393
1277
! 960
av. = 1970
i
-------
APPENDIX E
A Wind Erosion Equation
N P. WOODRUFF AND F. H. SIDDOWAY
Rcpniitea fiom SOIL SCIENC.I. SOCIKIV OT AM1KICA PUOC'l-
Vul. ?9, No •>, Scptuntxr-OuoUcr I9i'^. p.ij;ii ''(/-'- 60S
67^ Simtii Scuci- Ko.ul M.iJixm \\'isn-ivm 'i>"'ll I'SA
E-l
-------
A Wind Erosion Equation1
N. P. WOODRUFF AND i7. H. SIDI>O\VAY-
ABSTRACI'
Tlic amount of erosion, E, expressed in tons per acre per
annum, that will occur from a given agricultural field can be
expressed in terms of equivalent variables as: F. — f(F, K',
C, L', V) where 1' is a soil erodibility index, K' is a soil ridjje
rougness factor, C is a climatic factor, L' is field length along
the prevailing wind erosion direction, and V is equivalent
quantity of vegetative cover. The 5 equivalent variables arc
obtained by grouping some and converting others of the 11
primary variables now known to go\ern wind erodibilit). Rela-
tions among variables are extremely complex. Charts and tables
have been developed to permit graphical solutions of the equa-
tion. The equation is designed to serve the twofold purpose
of providing a tool to (i) determine the potential erosion from
a particular field, and (ii) determine what field conditions of
soil cioddiness, roughness, vegetative cover, sheltering by bar-
riers, or width and orientation of field are necessary to reduce
potential erosion to a tolerable amount Examples of these
applications of the equation are presented. Weaknesses in the
equation and areas needing further research are discussed.
THE WIND EROSION EQUATION was c^ eloped by the
late Dr. W. S. Chepil. It is the result of nearly 30
years of research to determine the primary variables or
factors that influence erosion of soil by wind.
The first wind erosion equation was a simple exponen-
tial expressing the amount of soil 'oss in a wind tunnel
as a function of per cent soil cioddiness, amount of surface
residue, and degree of surface roughness. The equation has
been modified continually as new research data became
available and now is a complex equation indicating the
relation between potential soil loss from a field and some
11 individual primary field and climatic variables.
The equation is designed to serve the twofold purpose
of determining (i) if a particular field is adequately pro-
tected from wind erosion, and (ii) the different held
conditions of cioddiness, roughness, vegetative cover, shel-
tering from wind barriers, or width and orientation of
field required to reduce potential soil loss to a tolerable
amount undc-r different climates.
This paper discusses the present btatus of the equation,
points out some applications and uses of the equation, and
indicates some weaknesses and areas needing further
research.
PRIMARY WIND EROSION VARIABLES
The wind erodibility of land surfaces is go\erned by
11 primary •\ariahles. A brief description of each follows
Soil Erodibility Index, I, and Knoll Erodibility, ls
Soil erodihility, I, is the potential soil loss in tons per
acre per annum from a wide, umhcllcrcd. isolated field
'Contribution from the Soil .in-1 NX'ntrr Coiiser\.i!n.:i Rtsi.irJi
Division, AR.s. 1'SDA and the Kansas Apr I \p M.i, Depart-
ment of'/i.nrcimum Contribution no S97 Recmcd J.>n (>, )'X>5.
Approved M.u 30. I'M 5
'ApnculUit.il hn.nntc.r VSDA. M.mliMt.m, K,m , .irn.1 Soil Su-
onhst I'SDA >idiK->. Afont , ri-.pc<.ti\c.'ly
with a bare, smooth, noncuisied surface It has been devel-
oped from wind tunnel and field measures of erodibility
and is based on climatic conditions for the vicinity of Gar-
den City, Kans, during 1954-56 (4, 7, 8, 9, 10). It is
related to soil cioddiness and its \alue increases as the pei-
centage of soil fractions greater than 0.84 mm in diameter
decreases It can be determined by standard dry sieving
procedure and use of Table 1.
Knoll erodibility, Is, is a factor needed to compute erodi-
bility for windward slopes less than about 500 feet long.
It varies with slope and is expressed in terms of per cent
slope, Eig. 1. The erosion rate for windward slopes longer
than 500 feet is about the same as fiom level land; there-
fore, Js is taken as 100% for this situation (13, 14).
Surface Crust Stability, Es
The mechanical stability of the surface crust, Fs, if a
crust is present, is of little consequence because it disinte-
grates readily due to abrasion after wind erosion has started.
Table 1—Soil erodibility I for soils with different percentages
of nonerodible fractions as determined
by standard dry sieving'-'
Percentage
of dry soil
flections
> 0. 34 mn-.
ID
20
30
40
50
60
70
80
0 1
.110
134 111
9S 95
7i 72
56 54
13 36
21 20
12 11
2
250
12S
92
71
52
S3
IS
10
3
220
90
69
51
31
1^
B
Unito
4
,
195 130
121 117
8S 86
67 r,j
50 tii
29 27
17 10
7 6
6
170
in
33
C'!
47
25
1C
4
~
lEM
109
gi
C2
i",
24
1.)
3
8
'.SO
106
79
60
4.1
23
14
3
9
140
102
76
58
41
22
i3
2
For a full\ crusted soil surfrtx, regardless of soil tt-xture, rl e eiociibility I 1% on
the average, about 1/6 of that sfco'vn.
100
WINDWASO KNOLL SLOPE,s, (PERCENT)
Fig. 1—Potential soil Joss from knoils, expressed as ncr cent
of th.it on level pro»»nd: (rt) from top of knoll, (b) from
that portion of \\iiKlward slope \\hc-rc drai; velocity jnd wind
draj; jre the same a* on top of knoil (from about the upper
third of the slojx-).
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VOODRUFT AND SIDDOXX'AY: \\'1NI) EROSION EQUATION
605
_.L. i! ilut-_;_
e, e 10
(THOUSANDS OF EQUIVALENT POUNDS PER ACRE)
Fig. 6—Chart to determine V from R' or R' from V of live or
dead small grain crops in seedling and stoohng stage, above
the surface of the ground, for crop in 3-inch-deep furrow (as
created by a deep furrow drill) and on smooth ground.
angles to the wind and with a height-spacing ratio of 1:4
(18). The rate of soil flow varies with ridge height, degree
of clocldiness of ridges, and wind velocity (1). The rela-
tionship between soil riow and ridge height, within pre-
scribed limits, follows an approximate catenary curve.
Ridges 2 to 4 inches high are most effective in controlling
erosion Rate of flow increases with ridges greater than 4
inches or less than 2 inches high. Figure 4 presents a curve
i"ot obtaining the equivalent soil ridge roughness factor,
K', from a measure of Kr The cune is based on a design
velocity of 50 miles/hour at 50-foot height with wind
direction at 45 degress to the ridges.
The local wind erosion climatic factor, C', has been
developed from the relationship stating that rate of soil
How varies directly as the cube of the wind velocity and
inversely as the square of the effective moisture or for
reasons stated previously, the P-E index. The climatic fac-
tor was computed from the equation
v3
C = 34.483 ,—r FH
^1-317\U LJ
vvhcie v — mean annual wind velocity for a particular
L'u^-raphic location corrected to a standard height of 30
ieet and P-E — Thornthwaite's P-E ratio =: 10(P/E) =
!t^(P/T -- 10)1-111. Factor C' has been computed for
in.ui} locations throughout the USA. A map gmng general
r.i:'ge-> of values of C' for the \\cstern half of the USA
•V-H be tuiind in a pievious publication (10). Detailed
"lips h.ue also been prepared and are available from the
I :«'M..H Research Laboratory at Manhattan. Kans. Figure ?
'• >vuh a map for the center o! the "dust bowl" area of
j V 1'^0's.
^ Ih-.- equivalent _fie!J length, L', is the unsheltered dis-
:• c across the held aloni; the prevailing wind erosion
' : '"'''I, thus I.' - l\ — D,,.
'>>.• eqimjlcrit \e-gi-Mtivc- teller variable, V, is obtained
•• i'lultiphmg the variables R', S, and K,, =: i'(K')
""•'•''Kr Dallies of V }).-•%c been computed for \arioiis
' '".^ and amounts of residue and are presented in Fig.
^ ' 111,J C
4 6 8 10 12 14 16 16 ZQ
V (THOUSANDS OF EQO'VALENT POUNDS PER ACRE)
Fig. 1—Chart to determine V from R' or R' from V of stand-
ing and flat anchored small £rain stubble with any row
width up to 10 inches, including stover.
^H^^Hdi^^^^a^
^^;^^:r^r^^r^^E|^grtrrr
6 (0 (2 14 16 16 20 22
(THOUSANDS OF EOUVW.ENT POUNDS PER ACRE)
26 28 30 32
Fig. 8 — Chart to determine V from R' or R' from V of stand-
ing and flat grain sorghum stubble of average stalk thickness,
leafiness, and quantity of tops on the ground.
RELATIONSHIPS BETWEEN VARIABLES
The general functional relationship between the depend-
ent variable, E. the potential average annual soil Joss in
tons per acre per annum, and the equi\aleni variables may
be expressed as
E - /(]', C', K', I/, V). [2]
Mathematical relationships ha\e been established between
individual \.iri.ibles However, because of the complexity
ot these relations, c.g , the relation between Ji and V is
an exponential equation ot the form F — f(ev) while that
between I; and I/ is a power equation of the form F —
i (L' — h)", a Miii'le equation expressing E as a function
ot the °i dependent \an.ibles has not }U been derived
The equation can be solved in the following 5 step-,, the
latter 2 involving graphical solutions, with each step t \.ilu-
ating the effect ol an addiiion.il variable
E-5
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60S
7.
SOIL i>c:u,Nu: SOCILTV PROCI.I DINGS
I960. Conversion of relative field erodibihty
to annual soil loss by wind. Soil X'l f f.inn fields
I Sou Water Consen. 1". 162-161
jj : t and N". P. Voodiuff 1963. 'J'hc plv.sics of
wind erosion and its control Ad\ar.;c A^ron 15 211-302
,7 , F H. SidJo-,v;n a.id D V Armb.ust 1964_
In the Great Plains prc\ailing wind ciosion dnxction I. Soil
Water Consen 19 6"'-70.
I3 .and 196 i. Wind
" ciodibilm of iiK.IK and level (drains j Soil Water Con^rv.
19.P9-181 ' . . „ .
11 Douphiy T. I. , nnd MatT 19 J3. Report of Investigation-,, Soil
Kesc-aixh Ubotatorj, C.an Dcp of AKI'- S\vift Current, Sask.,
3 7- V;
15. Thorntlnvaite. C \\" 19.31 Cluvaus of North Amuii.3 accord-
ing to a IK-V.- clas-.;hcation Gtot;r,,ph Rtv. 21 633 -6?5
16. Woodiuff, X. P. and A \Y /.,nt;t; 1952. \Vmd-tunnci studies
ol fL.nii,ii',cnt.il prohk-r.ii rr-latcd to v.mdb^eaks. L'SDA, SCS-
TP-H"1
I" 7.tncA A \\" 1953 Wind-tunnel studies of the movement
o't scdiiicr.tari mati-naU Proc 5th H\diaul Conf., lova State
Uni% . bull. 3-i P 1 11-135.
Kc . and N. P Woodruff. 1951 Calibration of a
portabL v.'ind tunnel for the sin-pie dt-Wimination of lough-
nti". and drag on field surfaces Agton J. 43.191-193.
E-8
-------
APPENDIX F - FUGITIVE DUST EMISSION SUMMARIES
Table F-l
SAN JOAQUIN AQCR .SUMMARY SHEET
ESTIMATED ANNUAL EMISSIONS FROM FUGITIVE DUST SOURCES
COUNTY
Amador
Calaveras
Fresno
Kings
Made r a
Mariposa
Merced
San
Joaquin
Stanislaus
Tulare
Tuolumne
Kern
(portion)
AQCR
Activity
Totals
AQCR
Emission
Totals
UN PAVED ROADS
VEH.
MI/DAY
750
4,350
158,000
62 ,050
90,400
7,300
11,200
1,300
800
20,350
2,650
27,800
386,950
EMIS.
T/YR
520
2,940
70,040
.36,900
68,510
4,920
* 7,550
I
8,840
540
3,530
1,800
1,300
199,390
AGRICULTURE
ACRES
3,400
~ 1,000
887,500
399,100
208,800
1,000
303,300
362,200
177,500
506,800
1,200
557,000
,408,800
EMIS.
T/YR
60
Neg.
117,300
133,000
40,000
Neg.
28,100
29,000
23,600
189,000
Neg
?,RR,210
848,350
CONSTRUCTION
ACRES
PER/YR
_
_
964
-
180
-
-
500
125
-
_
290
2,059
EMIS.
T/yr
—
-
16,200
-'
3,020
-
_
8,390
2,10(
-
—
i,R7n
TAILINGS PILES
ACRES
_
_
-
-
-
—
-
-
-
-
_
-
EMIS.
T/YR
~
—
-
-
-
-
_
-
-
-
—
"
AGGREGATE
STORAGE
103
TONS
_
-
562
-
55
~
-
300
80
—
-
315
1,312
EMIS
T/YR
*~
"™
1,620
-
160
-
-
860
230
-
"•
qnn
3,770
CATTLE FEEDLOTS
IS3
HEAD
-
-
130
45
—
"
67
70
30
-
165
507
EMIS.
T/YR
"
"
410
360
-
-
540
560
240
~
1,3?0
3,430
COUNTY EMISSION
TOTAL, TON S/YR
580
2 ,940
205,570
170,260
101,690
4,920
36,190
47,090
27,030
192,770
1,800
?Q«,*«n
1,089,520
-------
Table F-2
PHOENIX-TUCSON AQCR SUMMARY SHEET
ESTIMATED ANNUAL EMISSIONS FROM FUGITIVE DUST SOURCES
COUNTY
Gila
Xaricopa
Pima
Pinal
Santa
Cruz
AQCR
Activity
Total
AQCR
Emissions
Total
UNPAVED ROADS
VEH.
MI /DAY
13,622
121,758
45,530
58 ,936
9,258
249,104
EMIS.
T/YR
9,200
82,200
34,910
39,750
6,250
172,310
AGRICULTURE
ACRES
1,300
408,500
50,700
238,000
1,400
699,900
EMIS.
T/YR
50
175,000
8,900
126,500
50
310,500
CONSTRUCTION J
ACRES
PER/YR
3,775
1,440
5,215
EMIS .
T/yr
62,440
24,160
86,590
TAILINGS PILES
ACRES
1,785
2,680
1,100
5,565
EMIS.
T/YR
5,430
9,430
7,100
21,960
AGGREGATE
STORAGE
103
.TONS
30
552
212
120
75
989
EMIS.
T/YR
90
1,590
540
340
220
2,780
CATTLE FEEDLOTS
i?3
HEAD
235
13
2sa
451
EMIS.
T/YR
250
20
1,010
1,280
COUNTY EMISSION
TOTAL, TONS/YR
14,770
321,470
77,960
174,700
6,520
595,420
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Table F-3
ALBUQUERQUE-MID RIO GRANDE AQCR SUMMARY SHEET
ESTIMATED ANNUAL EMISSIONS FROM FUGITIVE DUST SOURCES
COUNTY
Bernalillo
Sandoval
(Portion)
Valencia
(Portion)
AQCR
Activity
Total
AQCR
Emissions
Total
UNPAVED ROADS
VEH.
MI/DAY
24,504
25,333
3,302
53,139
EMIS.
T/YR
16,540
17,100
2,230
35,870
AGRICULTURE
ACRES
8,500
8,100
22,900
39,500
EMIS.
T/YR
960
1,070
2,060
4,090
CONSTRUCTION
ACRES
PER/YR
1,600
27
50
1,677
EMIS.
T/yr
26,850
450
840
28,140
TAILINGS PILES
ACRES
-
-
-
-
EMIS.
T/YR
_
-
-
-
AGGREGATE
STORAGE
103
TONS
620
20
Neg.
640
1,780
EMIS.
T/YR
1,680
100
-
CATTLE FEEDLOTS
HEAD
-
"~
—
-
EMIS.
T/YR
-
-
-
COUNTY EMISSION
TOTAL, TONS/YR
46,030
18,720
5,130
69,880
-------
Table F-4
EL PASO-LAS CRUCES-ALAMOGORDO AQCR SUMMARY SHEET
ESTIMATED ANNUAL EMISSIONS FROM FUGITIVE DUST SOURCES
COUNTY
Dona Ana
Lincoln
Otero
Sierra
AQCR
Activity
Total
AQCR
Emissions
Total
VEH.
MI/DAY
35,160
46,973
36,350
17,613
136,042
EMIS.
T/YR
23,700
31,700
24,540
11,890
91,830
AGRICULTURE
ACRES
80,400
2,300
7,900
5,400
96,000
EMIS.
T/YR
48,000
620
2,970
2,000
53,590
CONSTRUCTION
ACRES
PER/YR
140
140
EMIS.
T/yr
2,350
2,350
TAILINGS PILES
ACRES
-
_
EMIS.
T/YR
-
_
AGGREGATE
STORAGE
103
TONS
95
55
150
EMIS.
T/YR
270
160
430
CATTLE FEEDLOTS
HEAD
-
-
EMIS.
T/YR
-
-
COUNTY EMISSION
TOTAL, TONS/YR
74,320
32,320
27,670
13,890
148,200
-------
Table F-5
NEVADA INTRASTATE AQCR SUMMARY SHEET
ESTIMATED ANNUAL EMISSIONS FROM FUGITIVE DU^T SOURCES
COUNTY
Churchill
Elko
Esmeralda
Eureka
Humboldt
Lander
Lincoln
Mineral
Nye
Pershing
White Pine
UNPAVED ROADS
103 VEH
MI/YR
15,920
14,680
2,085
4,420
9,920
3,776
5,749
5,635
11,480
5,460
9,376
EMIS.
T/YR
29,450
27,160
3,860
8,180
18,350
6,980
iO,720
10,420
21,250
10,100
17,350
AQCR
Activity
Total 88,546
AQCR
EMISSIONS
TOTAL 163,820
AGRICULTURE
ACRES
37,100
uo,ooo
20,600
10,300
50,100
35,400
0
3,100
2,200
71,200
13,200
413,200
EMIS.
T/YR
2,960
12,600
1,560
Neg.
100
2,400
Neg.
230
910
140
Keg.
20,900
CONSTRUCTION
ACRES
PER/YR
Neg.
Neg.
Neg.
Neg.
Neg
Neg.
Neg.
Neg.
Neg.
Neg.
Neg.
Neg.
EMIS.
T/yr
-
-
-
-
-
-
-
-
-
-
—
-
TAILINGS PILES
ACRES
—
255
6
-
-
460
-
-
22
-
3,690
4,433
EMIS.
T/YR
-
1,450
40
-
-
400
-
-
140
-
4',410
6,440
AGGREGATE
STORAGE
103
TONS
41
114
Neg.
Neg.
Neg.
Neg.
Neg.
32
96
Neg.
84
367
EMIS.
T/YR
120
330
-
-
-
-
-
90
280
-
240
1,060
CATTLE FEEDLOTS
HEAD
Neg.
Neg.
Neg.
Neg.
Neg.
Neg.
Neg.
Neg.
Neg.
Neg.
Neg.
Neg.
EMIS.
T/YR
-
-
-
-
-
-
-
-
-
-
-
-
COUNTY EMISSION
TOTAL, TONS/YR
32,530 '
41,540
5,460
8,180
18,450
9,780
10,720
10,740
22,580
10,240
22,000
192,220
1
,1
-------
Table F-6
NORTHWEST NEVADA AQC~* SUMMARY SHEET
ESTIMATED ANNUAL EMISSIONS FROM FUGITIVE DUST SOURCES
COUNTY
Carson City
Douglas
Lyon
Storey
Washoe
AQCR
Activity
Total
AQCR
Emissions
""otal
UNPAVED ROADS
103 VEH
MI/YR
3,560
1,660
5,670
755
42,000
53,645
EMIS.
T/YR
6,590
3,070
10,500
' 1,400
77,700
99,260
AGRICULTURE
ACRES
600
16,500
34,600
15,400
16,000
83,100
EMIS.
T/YR
Neg.
Neg.
50
Neg.
Neg.
50
CONSTRUCTION
ACRES
PER/YR
Neg.
Neg.
Neg.
Neg.
Neg.
Neg.
EMIS.
T/yr
-
-
-
-
_
TAILINGS PILES
ACRES
-
-
1,563
-
—
1,563
EMIS.
T/YR
_
-
1,920
-
-
1,920
AGGREGATE
STORAGE
103
TONS
5
12
31
3
50
101
EMIS.
T/YR
10
30
90
10
140
280
CATTLE FEEDLOTS
103
HEAD
Neg.
Neg.
Neg .
Neg.
Neg.
Neg.
EMIS.
T/YR
-
-
-
-
-
-
COUNTY EMISSION
TOTAL, TCNS/YR
6,600
3,100
12,560
1,410
77,840
101,510
-------
TECHNICAL REPORT DATA .
(Please read Instructions on the reverse before completing}
REPORT NO.
EPA-450/3-74-036a
2.
3. RECIPIENT'S
riTLE ANDSUBTITLE
Investigation of Fugitive Dust: Volume I - Sources,
Emissions and Control
5. REPORT DATE
June 1974
6. PERFORMING ORGANIZATION CODE
AUTHOR(S)
George Jutze, Kenneth Axetell
PERFORMING ORGANIZATION NAME AND ADDRESS
PEDCO Environmental Specialists, Inc.
Suite 13, Atkinson Square
Cincinnati, Ohio 45246
10. PROGRAM ELEMEN1
NU.
68-02-0044, Task No. 9
2. SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
13. TYPE OF REPORT AND PERIOD COVERED
Final
14. SPONSORING AGENCY CODE
5. SUPPLEMENTARY NOTES
6. ABSTRACT
A survey of available techniques for controlling fugitive dust emissions in
six (6) air quality control regions. Included topics are: (1) sampling program,
(2) fugitive dust emissions in the six agcr's, (3) control techniques. Also in-
cluded is a list of references and a bibliography. The procedures for sampling,
emission estimation and a description of each of the control tatiniques studied
are included in this report.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.IDENTIFIERS/OPEN ENDEDTERMS
COSAT! Field/Group
Fugitive dust
13b
13. DISTRIBUTION STATEMENT
Release unlimited
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