-------
ro
i
ro
I
I
I
1
Figure 2-10. Average Daily Participate Emissions from Aircraft, Fourth Quarter, 1975.
-------
2.5 PARTICLE SIZE DISTRIBUTIONS
Particle size data presented in this section are in one of two forms.
If a source type is equipped with controls (as specified by the Maricopa
County Air Pollution Control District), size distributions for the con-
trolled emissions are given. Otherwise, uncontrolled size distributions
are reported. The efficiencies of the control were extrapolated from
Figures 2-11 and 2-12.
For many source categories, particle sizs data were scarce or unavail-
able. Thus, extrapolations and assumptions were necessary. The impact of
these assumptions is minimized by the relatively minor contribution of
conventional sources to the total emissions inventory.
Motor Vehicles
Five categories of motor vehicles are present in the study area:
light duty vehicles (LDV), light duty trucks (LOT), heavy duty gasoline
vehicles, heavy duty diesel vehicles and motorcycles. Data for only one
category, light duty vehicles, could be located and only for those light
duty vehicles using low-lead fuels.
It is assumed that the particle size distributions characteristic of
LDV's burning unleaded fuels and without catalytic mufflers are represen-
tative of the size distribution of all motor vehicles. This distribution
is as follows:
Particle Diameter (p) Weight Percent
<1 60
1-2 25
>2 15
Source: Reference [13]
2-27
-------
i BAG FILTERHOUSE
. / VENTURI SCRUeSIR '6-INCH THROAT, 30-INCH WATER GAUGE)
) SPRAY rc*Sfi '27-FOOT ClA.'.'.fTERi
'. DRY ELECTROSTATIC PRECiPI TATCR (3-SECONO CONTACT TIM
/ MULTIPLE CYCLONES (H-IM.tri DIAMETER TUBES)
3 < SI-.'PLE CYCLONE (4-FOOT DiAMETER)
( INERIIAL COLLECTOR
10
30 40 5'J
PARTICLE SIZE, n>\s,an.*
Figure 2-11. Composite Grade Efficiency Curves Based on Test Silica Dust
Source: Reference [11]
fARIICU DWMEIES - MICRONS
Figure 2-12. Extrapolated Efficiency of Control Devices
Source: Reference [12]
2-28
-------
Aircraft
No published studies could be located pertaining to particle size
distributions. It is assumed that the distributions for motor vehicles
will apply to aircraft.
Stationary Point Sources
The major point sources within the study area may generally be
classified into four categories (see Table 2-7 and 2-8): the mineral
industry, metals industry, agricultural processes, and power plants.
Metal s - the only metal industry plant belongs to Reynolds in Phoenix.
According to the NEDS point source listing, the particulate
emissions result from the chlorinating station, where the
magnesium content is reduced by lancing chlorine gas into
the molten metal. No control equipment is utilized. Par-
ticle size distribution is as follows:
Particle Diameter
<2
Weight Percent
90
100
Source: Reference [14]
Power Plants - all the power plants listed in Table 2-8 presently burn dis
tilled fuel oil.* Size distribution data for distillate is not
available; thus, data for residual fuel oil is assumed to apply:
Particle Diameter (y) Weight Percent
1-2
2-5
>5
Source: adapted from [14]
88
7
3
2
fln 1975, a very small percentage of the fuel used was natural gas. It is
not expected that any of these plants will receive natural gas in the future.
No power plants in Maricopa County burn coal.
2-29
-------
Minerals- the processes conducted by the mineral industries are comprised
of three categories: crushing and screening rock and sand, con-
crete batching and asphaltic mixing. An average size distribu-
tion for the overall emissions can be specified as follows:
Particle Diameter (p) Weigth Percent
<2 5
2-20 27
>20 68
Source: Reference [12]
(The Maricopa County APCD reports that spray bars are used at
the crusher and transfer points. However, no control effici-
encies were found in the literature for these devices. There-
fore, uncontrolled sized distributions were assumed,)
Agricultural Processes - industries in this category are mainly involved
with grain storage and shipment. As could be expected, no infor-
mation on size distributions could be found. Thus, it is assumed
that the distributions for numeral industries will apply to agri-
cultural processes.
Stationary Area Sources
Emissions from area sources are the result of burning distillate fuel
oil for space heating. Particle size distributions for power plants are
assumed to be applicable for area sources.
2-30
-------
REFERENCES FOR SECTION 2.0
1. PEDCo Environmental Specialist, "Investigation of Fugitive Dust
Volume I - Sources, Emissions, and Control," EPA-450/3-74-036-a.
2. Communication with Ellwood C. Neiman of the Transportation Planning
Division of the Arizona Department of Transportation, March 1976.
3. Arizona Department of Transportation, "Arizone Traffic FA-FAS State
Routes 1974," Planning Survey Group, 1975.
4. Telephone communication with Ed. Baldwin of the Maricopa County
Auto License Department, 3-15-76.
5. EPA, "Supplement No. 5 for Compilation of Air Pollutant Emission
Factors," Second Edition, December 1975.
6. Telephone communication with Greg Witherspoon of the Maricopa
County Health Department, March and April 1976.
7. Communication with James R. Weiss of Arizona Public Service Company,
Phoenix, April 1976.
8. Communication with Don Moon of the Salt River Project, Phoenix,
April 1976.
9. U.S. Department of Interior, "Sales of Fuel Oil and Kerosine in 1973,"
Mineral Industry Survey, 9-5-74.
10. U.S. Department of Interior, "Natural Gas Production and Consumption:
1974," Mineral Industry Surveys, 8-29-75.
11. U.S. Department of Health, Education and Welfare, "Control Techniques
for Particulate Air Pollutants," National Air Pollution Control
Administration, Washington, D.C., 1969.
12. Midwest Research Institute, "Particulate Pollutant System Study,
Volume II," prepared for the Environmental Protection Agency,
Contract No. CPA-22-69-104, 1971.
13. The Dow Chemical Company, "Characterization of Particulates and Other
Non-Regulated Emissions from Mobile Sources and the Effects of Exhaust
Emissions Control Devices on these Emissions," APTD-1567, March 1973.
14. U.S. Environmental Protection Agency, "Air Pollution Engineering Manual,"
Publication No. AP-40, 1973.
2-31
-------
3.0 BASEYEAR ANTHROPOGENIC SOURCES OF FUGITIVE DUST
For the context of this study, anthropogenic fugitive dust sources
are considered to be those resulting directly from, and during, human
activities. Specifically, these are motor vehicles on unpaved roads,
agricultural tilling, cattle feedlots, off-road motor vehicles, construc-
tion activities, and dust suspended by motor vehicles on paved roads.
Fugitive dust emissions from aggregate storage, caused by both anthro-
pogenic and natural causes (wind erosion), are also evaluated in this
section.
Table 3-1 summarizes the baseyear emissions of fugitive dust from
anthropogenic sources in the study area. The largest source by far is
motor vehicles travelling on unpaved roads. Not surprisingly, these
emissions are distributed mainly in the rural areas of Maricopa and north-
ern Pinal Counties. The factor having the greatest influence on the
emissions is the silt content of the road surface, which can be as high as
27% for some dirt roads. Construction activities are the next major source
of fugitive dust, contributing about 100 tons/day. Off-road motor vehicles,
which includes motorcycles, contribute the third largest percentage of the
total inventory. The remaining three sources are relatively minor, as com-
pared to the latter emitters. Agricultural tilling operations are seasonal
in nature and range from a high of over 30 tons/day during the spring
quarter to a low of just over 1.5 tons/day during the summer quarter. Emis-
sion levels from aggregate storage and cattle feedlots are yet more insigni-
ficant, especially considering that these sources are generally located in
rural areas.
3.1 MOTOR VEHICLES ON UNPAVED ROADS
This section documents the methodology employed to estimate the magni-
tude and distribution of dust emissions arising from motor vehicle travel
on unpaved roads. In Section 3.1.1, previous emission inventories conducted
for the study area are reviewed to select an appropriate emission model for
the present study. Section 3.1.2 describes field tests conducted to permit
area-specific characterizations of unpaved road surfaces, and tabulates
transportation network data to estimate total mileages and spatial
3-1
-------
TABLE 3-1. SUMMARY OF BASELINE ANTHROPOGENIC FUGITIVE
DUST EMISSIONS IN THE STUDY AREA
Source Category Emissions (tons/day)
Motor Vehicles on Unpaved Roads 1281
Agricultural Tilling Operations
Wi nter 22
Spring 31
Summer 1.3
Fall 17
Aggregate Storage .06
Cattle Feedlots 7.5
Off-Road Motor Vehicles* 71
Construction Activities 100
* Off-road vehicle emissions are generated almost entirely over the
two-day weekend period (see Section 3.5 for further explanation).
distribution of unpaved roadways. An emissions model is then used to gener-
ate emissions estimates.
3.1.1 Review of Previous Inventories and Emission Factors
A literature search was conducted to obtain results of previous re-
search in the development of fugitive dust emission factors from motor
vehicles traveling on unpaved roads (see Table 3-2). The factors
of greatest interest to this study were those derived by the Midwest Research
Institute (MRI) and PEDCo Environmental Specialists, Inc. (PEDCO) as they
were the results of extensive testing and analyses programs. The remainder
of this section will be devoted to a review of MRI's and PEDCO's work.
A basic assumption underlying the development of the PEDCo emission
factor is that heavy traffic (five vehicles per minute) across an unpaved
road approaches the condition of a continuously-emitting infinite line
source, as described by Sutton [14]. Sampling data of particulate concen-
trations were taken by a beta gauge airborne .dust sampling/readout instru-
ment positioned at various distances (from 55 to 300 feet) and heights
3-2
-------
(from 3 to 100 feet) downwind of the road. Ambient data were substituted
into Button's equation to solve for the source emission rate. An equation
was then derived which expressed the relationship between vehicle speed
and emission rate over the range of speeds investigated:
E = (0.16) (1.068)x (1)
where
E = emissions, Ibs/vehicle-mile
x = vehicle speed, miles/hour
TABLE 3-2. FUGITIVE DUST EMISSION FACTORS FOR UNPAVED ROADS
INSTITUTION WKFGRHIHE
STUDY
Midwest Research
Institute [1]
PEDCo Environ-
nental Specialists,
Inc. [2]
University of New
Mexico [3]
University of Iowa [4]
C. Anderson [5]
Budget Sound
(Washington) Air
'Dilution Control
Agency [6]
EMISSION FACTOR
e = 0.81 s(3f )
where
e » emission factor,
Ibs/ vehicle-mile
s = silt content of
road surface
material (percent)
S = average vehicle
speed, miles/hour
E = (0.27)(1.068)x
where
E = emission factor,
Ibs/vehicle-mile
x = vehicle speed,
miles/hour
0.93 Ibs/veh1cle-m1le for
particles <6u
0.04 Ibs/vehicle-mile for
particles *3u
5.5 Ibs/vehicle mile
0.5 - 0.7 Ibs/veh1cle-m1le
3.5 Ibs/veh1cle mile at 10
miles/hour
7.0 Ibs/vehicle mile at 20
miles/hour
22.2 Ibs/veh1cle mile at 30
miles/hour
COMMENTS
Factor assumes a linear dependence on vehicle speed
from 30 to 50 mph.
Factor is accurate for 4-wheeled vehicles and must
be adjusted for all other types of vehicles.
No emissions are assumed for days with rainfall
greater 'than 0.01 inches.
Silt is defined to be particles with a diameter less
than 75p.
Factor is applicable for particles with a drift
potential of greater than 25 feet, I.e., particles
less than 100y in diameter
t For vehicle speeds below 30 mph, emissions increase
in proportion to the square of the vehicle speed.
Accuracy of the factor is - 10%.
t Factor is valid for vehicle speeds from 15 to 40
miles/hour.
Vehicle speed during testing was 25 miles/hour.
9 Vehicle speed during testing was 30 miles/hour.
3-3
-------
This equation, however, was corrected to account for the fact that the beta
gauge samples a narrower range of particle sizes than the Hi-Vol samples, on
which the particulate ambient air quality standards are based. Hi-Vol data,
taken concurrently with the beta samples, were used to determine the ratio
and correlation between readings of the two types of samples. As a result,
equation (1) was adjusted upward by a factor of 1.68, yielding the
emission factor:
E = (0.27) (0.068)x (2)
where
E = emissions, Ibs/vehicle-mile
x = vehicle speed, miles/hour
The major weakness in the PEDCo factor is that the "dustiness" (or quantity
of fine dirt particles) on the road surface is not considered. Another
weakness lies in the assumption that heavy traffic (five vehicles per
minute) approximates an infinite continuously-emitting line source. An
emission factor developed from such an assumption may not hold true for
vehicular traffic of lower volumes, which is the case in rural Arizona. One
final weakness is that background concentrations of particulates were not
discounted in determining the emission factor. It should be noted that
the primary intent of the PEDCo contract was not, specifically to develop-
ment of emission factors, but to develop control regulations to achieve
air quality standards.
MRI also employed a field sampling program to develop their emission
factor. These tests included the use of isokinetic samplers located at set
heights and at distances greater than 20 feet from the road. Hi-Vol samples
were also taken to correct for background dust concentrations. The following
equations were used in developing the final factor:
e<2 = ER6 F<2 (3)
e2-30 = ER6 (1'F<2)
e>30 = E
where
3-4
-------
e. = mass of dust emissions with diameter i per vehicle-
mile
E = integrated exposure measurement
Rg = ratio of dust concentration measured by the standard
Hi-Vol to the concentration measured by the isokinetic
profiler, at 6-ft. height.
F<2 = fraction of the particles smaller than 2y in diameter,
measured by high-volume cascade unpaction.
The only previous inventory accounting for fugitive dust emissions
from dirt roads in Phoenix was performed by PEDCo [2]. PEDCo's methodology
was realitvely standard and straightforward. Exact mileages of unpaved
foads by county were obtained from state highway department annual reports
on the status of the highway system. Where available, exact traffic counts
were used; otherwise, estimates obtained from state and county highway
officials were employed. An average vehicle speed of 30 miles/hour repre-
senting the low of several estimates given by highway department officials,
was assumed. With these data, total emissions were obtained by simple
multiplication.
Of more.interest was the determination of emissions on a gridded basis.
this was performed for Easter Maricopa and Pima Counties. Mileages of unpaved
roads within a given grid were measured off a county map illustrating the
unpaved roads. Average daily traffic, values were obtained from a county
highway map. Presumably, the same average vehicle speed, 30 miles/hour,
was assumed. In conversations with the Maricopa County Highway Department
[8], however, it was discovered that this approach introduced accuracies in
both the mileages and average dally traffic counts. This is because the
ipaps utilized are incomplete for both categories of data.
3-5
-------
3.1.2 Methodology of the Present Inventory
This section will detail the approach utilized in estimating fugitive
dust emissions from motor vehicles traveling on unpaved roads. Topics dis-
cussed are: (1) selection of an emission factor, (2) mileages and distribu-
tion of unpaved roads, (3) vehicle speed, (4) average daily traffic, and
(5) silt content of road surfaces, and (6) effect of rainfall. Items
(2) through (6) serve as inputs to the estimation process.
Emission Factoi Selection
Table 3-2 presents the various emission factors available for use.
The primary selection criteria for this study was the number of "influence
categories" considered in the factor - i.e., vehicle speed, vehicle type, .
road surface type. Also important were the test procedures employed in
deriving the factor. These include number of tests, type of analyses
performed, sampling method and locale in which the testing was performed,
Based on these criteria, the MRI emission factor was chosen, primarily
because of the "influence categories" considered, but also because of the
comprehensive flux measurements conducted in the field testing.
Mileages and Distribution of Unpaved Roads*
i
Because the emission inventory is to be utilized as an input to the
modeling effort, a spatial resolution of the distribution and mileage of
unpaved roads was mandatory. After consultation with knowledgeable personnel
at various organizations [7,8,9], two candidate approaches were identified.
The Maricopa County Highway Department has prepared a map illustrating traf-
fic volumes for various roads. This map also differentiates road types.
By overlapping a grid on this map and measuring road mileages, the distri-
For the purposes of this study, an unpaved road is one whose surface has
not been subjected to any chemical treatment, such as bituminous coating.
Within the study area of this project, unpaved roads are thus either dirt,
stone or gravel topped.
3-6
-------
bution of unpaved roads can be determined. The disadvant ges of this approach
are twofold - (1) many existing unpaved roads are not included on the map,
and (2) the map was prepared for the year 1974 and thus does not account for
the construction of new dirt roads or the paving of existing ones in 1975.
The second alternative and the one ultimately selected, involved manipulating
road maintenance data from the Maricopa Highway Department.
The distribution of unpaved roads maintained by Maricopa County are
summarized in terms of road maintenance districts (see Figure 3-1 and Table
3-3). It should be noted that the county is responsible for the maintenance
of roads outside metropolitan areas such as Phoenix, Tempe, Mesa, Chandler,
Scottsdale and Glendale. As for these areas, the city road maintenance de-
partments were contacted to obtain the mileages and distribution of unpaved
roads:
Phoenix 121 miles Scottsdale 12 miles
Paradise Valley 10 miles Glendale 10 miles
Tempe 3 miles Chandler 4 miles
Mesa 17 miles
No exact locations of these unpaved roads were readily available, so
it is assumed that these roads are distributed evenly throughout these
cities.
Two additional facts concerning the data presented in Table 3-3 must
be mentioned. Only 70% of the county maintained dirt roads are accounted
for, as the computerized maintenance records are not yet complete. To ad-
just for this discrepancy, it was decided to adjust by 30% the dirt road
mileages in Table 3-3 to develop a more accurate road inventory. The second
fact is that approximately 919 miles of unpaved roads are not maintained by
the county in the various maintenance districts [8, 15]. Of these, 167 are
in national forest areas, 36 in Indian Reservations, and 716 in the remain-
der of the county [15]. These mileages will be distributed as follows:
3-7
-------
CJ
I
00
AGUILA
IV F
AGUA CALIENTE
III G
WICKENSBURG
f J>ARADIS
GLENDALE *VALLEY
PHOENIX SCOTTSDALJ
GILA BEND
III H
NOTE: LOCATION OF CITIES
ARE APPROXIMATE AND
SHOULD ONLY BE USED
AS REFERENCE POINTS
Figure 3-1. Maricopa County Highway Department Road Maintenance Blading Districts
-------
TABLE 3-3. SUMMARY OF MILEAGES OF UNPAVED ROADS MAINTAINED
BY MARICOPA COUNTY- BY MAINTENANCE AREAS*
MAINTENANCE AREA
1A
IB
1C
ID
IE
IF
2A
2B
2C
2D
2E
2F
3A
3B
3C
3D
3E
3F
3G
3H
31
4A
4B
4C
4D
4E
4F
MILEAGE
28.7
76.47
52.63
51.57
79.15
77.68
134.28
94.41
66.53
71.88
88.89
20.50
65.67
96.45
48.45
53.6
108.25
80.45
56.0
96.50
40.5
91.56
29.47
53.00
134.30
76.20
91.50
* Data as of March 2, 1976. The figures are estimated to account for
approximately 70% of all county maintained unpaved roads.
3-9
-------
National Forest Areas 167 miles equally between maintenance
areas 1A, IB, and 2A.
Indian Reservations 36 miles equally between maintenance
areas 2B and 3A.
County 716 miles equally to all maintenance
areas.
Based on the above considerations, total unpaved road mileages are
tabulated. Table 3-4 illustrates the adjusted total miles of unpaved roads
in Maricopa County, including both county maintained and non-county main-
tained roads for the area of each maintenance district.
For the portion of the study area in Northern Pinal County, a differ-
ent procedure was required (maintenance data was not available for Pinal
County). Maps from the Arizona State Department of Transportation illus-
trating the distribution of unpaved roads were obtained and mileages were
extracted by measurement off the map. These are presented in Table 3-5.
Vehicle Speeds
Conversations with officials at the Maricopa County Highway Department
indicated that PEDCo's estimate of 30 miles/hour was probably low, as
vehicle speeds on unpaved roads were estimated to range from 30 to 40 miles/
hour. For the purposes of this study, an average of 35 miles/hour is
assumed, both for Maricopa and Northern Pinal Counties.
Silt Content of the Road Surface*
The determination of the silt content of the road surface is a crucial
issue, as emissions are directly proportional to the percentage silt. All
unpaved roads in Maricopa County are either dirt or gravel [8], No exact
percentages of each type are available, so the opinions of cognizant
county highway personnel were solicited. As a result, a distribution of 60%
dirt and 40% gravel of county maintained roads in each maintenance district
for unpaved roads in Maricopa County is assumed. Roads not receiving county
For the purpose of the emissions model, silt is defined as particles with
a diameter of 75y (.075 mm) or less. The silt content is expressed as per-
cent by weight.
3-10
-------
TABLE 3-4. UNPAVED ROAD MILEAGES IN MARICOPA
. COUNTY
MAINTENANCE AREA
1A
IB
1C
ID
IE
IF
2A
2B
2C
2D
2E
2F
3A
3B
3C
3D
3E
3F
3G
3H
31
4A
4B
4C
4D
4E
4F
COUNTY MAINTAINED (ADJUSTED)
41
109.2
75.2
73.67
113.07
110.97
191.83
134.87 /
95.04
102.69
126.99
29.29
93.81
137.79
69.21
76.57
154.64
114.93
80.00
137.86
57.86
130.8
42.1
75.71
191.86
108.86
130.71
NO COUNTY MAINTENANCE
82.1
82.1
26.5
26.5
26.5
26.5
82.1
44.5
26.5
26.5
26.5
26.5
44.5
26.5
26.5
26.5
26.5
26.5
26.5
26.5
26.5
26.5
26.5
26.5
26.5
26.5
26.5
3-11
-------
TABLE 3-4. UNPAVED ROAD MILEAGES IN MARICOPA
COUNTY (Continued)
CITY
Phoenix
Scottsdale
Paradise Valley
Glendale
Tempe
Chandler
Mesa
MILEAGE
121
12
10
10
3
4
17
3-12
-------
TABLE 3-5. UNPAVED ROAD MILEAGES IN NORTHERN PINAL COUNTY
TOWNSHIP AND RANGE
TIN,
TIN,
TIN,
TIN,
TIN,
TIN,
T1S,
T1S,
T1S,
T1S,
T1S,
T1S,
T2S,
T2S,
T2S,
T2S,
T2S,
T2S,
T2S,
T3S,
T3S,
T3S,
T3S,
T3S,
T3S,
T3S,
T3S,
T3S,
T3S,
T3S,
T3S,
T4S,
T4S,
T4S,
T4S,
T4S,
T4S,
T4S,
T4S,
T4S,
T4S,
T4S,
T4S,
T5S,
TBS,
T5S,
T5S,
T5S,
T5S,
T5S,
T5S.
TBS,
TBS,
TBS,
TBS,
T6S,
T6S,
T6S,
T6S,
T6S,
T6S,
T6S,
T6S,
T6S,
R8E
R9E
R10E
RUE
R12E
R13E "
R8E
R9E
R10E
RUE
R12E
R13E
R2E
R8
R9E
R10E
RUE
R12E
R13E
R2E
R3E
R4E
RBE
R6E
R7E
R8E .
R9E
R10E
RUE
R12E
R13E
R2E
R3E
R4E
RBE
R6E
R7E
R8E
R9E
R10E
RUE
R12E
R13E
R2E
R3E
R4E
RSE
R6E
R7E
RSE
R9E
R10E
RUE
R12E
R13E
R2E
R3E
R4E
RBE
R6E
R7E
RSE
R9E
R10E
DIRT
14
0
10
0
0
2
7
10
16
IB
3
8
11
22
0
9
20
7
14
6
7
42
26
26
30
23
6
13
24
0
3
14
3
32
11
9
16
12
1
16
10
7
10
16
29
19
4
6
18
28
7
26
10
14
7
14
29
39
30
26
4S
7
2
2
(MILES)
.0
.2
.0
.B
.0
.0
.0
.0
.0
.0
.B
.B
.0
.0
.0
.0
.0
.0 '
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.n
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
.0
GRAVEL (MILES)
10.0
2.0
0
0
0
0
O.S
8.0
2.S
0
2.2
2.0
0
1.0
0
2.0
2.0
6.0
0
0
3.0
2.0
6.0
1.0
0
0
0
0
0
0
0
10.0
11.0
17.0
6,0
0
B.n
1.0
B.O
0
0
0
0
0
B.O
4.0
4.0
8.0
4.0
10
4
0
0
0
0
3.0
10.0
S.O
0.0
0
0
0
0
0
3-13
-------
maintenance (second column in Table 3-4) are assumed to all be dirt surface.
As for city maintained roads, the same 60/40 split is assumed. In Northern
Final County, the maps from which mileages were obtained differentiated be-
tween dirt and gravel roads. Thus the distribution shown in Table 3-5
reflects the.actual mileages.
Gravel roads possess a relatively low silt content. Numerous field
measurements by MRI [10] show that an average of 12% silt is a reasonable
figure. Officials in the Maricopa County.Highway Department estimate a 10%
silt in gravel roads [8], For the purpose of this report, a 12% content is
assumed in both Maricopa and Final Counties.
For dirt roads, it was unclear whether the particle size distribution
of the road soil would be equivalent to that of the native soil. Conse-
quently, field tests were conducted to determine the silt levels of unpaved
roads selected to be representative of the predominant soil associations in
the study area. Sampling and analysis procedures were consistent with the
MRI approach used in developing the emissions model. Composite samples of
road dust were collected by sweeping loose material from lateral strips of
the road surface. The silt content of the road soil was determined by dry
sieve screening. Table 3-6 shows the results of the analysis. It can be
seen that the silt content of soils on unpaved road surfaces reaches an
equilibrium value substantially less than that of the native soil. This
is apparently caused by the continual removal of fines by vehicle traffic,
leaving on the road surface a higher percentage of coarse particles than is
observed in the native soil.
TABLE 3-6. CHARACTERIZATION OF SOIL MATERIAL ON
UNPAVED ROADS IN PHOENIX AREA
Soil Type
G1 Iman-Estrel 1 a-Avondal e
Mohal-Contine
Ebon-Pi naimt-Tremant
Rock Outcrop
Silt Content*
of Road Surface
27.2%
14.2
23.3
12.4
Silt Content*
of Native Soil
55 - 80%
55 - 80
15-45
10 - 30
* Silt content is defined as the percentage (by weight) of soil particles
less than 75 micron in diameter.
3-14
-------
A general soil map of Maricopa County [11] and Final County [19] were
employed to establish the soil association in each of the designated main-
tenance areas and townships of the study area. Accordingly, a silt level
was assigned to these cell areas as shown in Table 3-7.
Average Daily Traffic
The vast majority of unpaved roads in both Maricopa and Northern
Final Counties are not monitored for traffic counts. Because no substantial
alternative means of estimating daily traffic volumes were apparent, a
modified version of average daily traffic (ADT) figures obtained by
PEDCo [2] (see Table 3-8) was utilized. The modified version accounts
for two categories of unpaved roads - dirt and gravel, whereas PEDCo
included four road types. The following consolidation was made: .
PEDGo Road Types
Primitive I
Unimproved(
Graded and Drained
Rock, Gravel, Oiled Earth
TRW Road Types
Dirt- no maintenance
Dirt- city or county maintained
Gravel- in county or city
Table 3-9 presents the ADT values employed in this study. Table 3-10
classifies the maintenance area and cities into urban and rural. All un-
paved roads in Pinal County are considered to be rural.
Effect of Rainfall
Estimates for the average daily emissions throughout the year should
reflect an adjustment for those days in which rainfall is assumed to
eliminate emissions from unpaved roads. Rainfall of .01 inch or more is
assumed to diminish these emissions to negligible levels. Table 3-11
shows the number of days during which .01 inch or more of rainfall occured
when suspended particulate levels were being measured.* Emissions calcu-
lated for each quarter of 1975 should reflect the effect of rainfall in
the quarter. Hence, average emissions from unpaved roads would be 20%
* The rainfall adjustments were related to the periods of air quality
monitoring because this permits direct air quality to emissions re-
lationships to be established later in the "study.
3-15
-------
TABLE 3-7. SOIL SILT CONTENT OF UNPAVED ROADS IN STUDY AREA.
ROAD MAINTENANCE AREAS, MARICOPA COUNTY
1A
IB
1C
ID
IE
IF
2A
2B
2C
2D
2E
2F
3A
3B
3C
3D
3E
3F
3G
3H
31
4A
4B
4C
4D
4E
4F
CITIES IN MARICOPA COUNTY
Phoenix
Scottsdale
Paradise Valley
Glendale
Tempe
Chandler
Mesa
AVERAGE SOIL SILT CONTENT ( % )
12
23 ,
20
23
12
12
. 12
23
19
23
23
23
25
23
21
27
26
23
23
23
27
19
21
23
23
23
12
19
19
19
23
23
23
23
3-16
-------
TABLE 3-7 (CONTINUED). SOIL SILT (
TOWNSHIP-RANGE, NORTH FINAL COUNTY
TIN, R8E
TIN, R9E
TIN, R10E
TIN, RUE
TIN, R12E
TIN, R13E
T1S, R8E
T1S, R9E
T1S, R10E
T1S, RUE
T1S, R12E
T1S, R13E
T2S, R2E
T2S, R8E
T2S, R9E
T2S, R10E
T2S, RUE
T2S, R12E
T2S, R13E
T3S, R2E
T3S, R3E
T3S, R4E
T3S, R5E
T3S, R6E
T3S, R7E
T3S, R8E
T3S, R9E
T3S, R10E
T3S, RUE
T3S, R12E
T3S, R13E
T4S, R2E
T4S, R3E
T4S, R4E
T4S, R5E
T4S, R6E
T4S, R7E
T4S, R8E
T4S, R9E
T4S, R10E
T4S, RUE
T4S, R12E
T4S, R13E
INTENT OF UNPAVED ROADS IN STUDY AREA.
AVERAGE SOIL SILT CONTENT ( % ) .:
19
12
12
12
12
12
21
13
12
12
12
12
27
27
27
21
12
12
12
27
27
27
27
23
12
14
14
21
12
12
12
14
27
14
20
27
23
23
23
27
27
27
12
3-17
-------
TABLE 3-7 (CONTINUED). SOIL SILT CONTENT OF UNPAVKD ROADS IN STUDY AREA.
TOWNSHIP-RANGE, NORTH PINAL COUNTY
T5S,
T5S,
T5S,
T5S,
T5S,
T5S,
T5S,
T5S,
T5S,
T5S,
T5S,
TBS,
T6S,
T6S,
T6S,
T6S,
T6S,
T6S,
T6S,
T6S,
T6S,
T6S,
T6S,
T6S,
R2E
R3E
R4E
R5E
R6E
R7E
R8E
R9E
R10E
RUE
R12E
R13E
R2E
R3E
R4E
R5E
R6E
R7E
R8E
R9E
R10E
RUE
R12E
R13E
AVERAGE SOIL SILT CONTENT ( % )
12
27
21
27
27
27
27
14
23
23
27
27
27
27
21
14
27
27
27
14
14
14
27
27
3-18
-------
TABLE 3-8. PEDCo AVERAGE DAILY TRAFFIC VOLUMES ON
UNPAVED ROADS IN PHOENIX AREA
TYPE OF ROAD
Primitive
Unimproved
Graded and drained
Rock, gravel, oiled earth
AVERAGE
URBAN
5
25
75
100
DAILY VEHICLE COUNT
RURAL
2
20
40
60
SOURCE: Reference [2]
TABLE 3-9. TRW AVERAGE DAILY TRAFFIC VOLUMES ON
UNPAVED ROADS IN PHOENIX AREA
TYPE OF ROAD
AVERAGE DAILY VEHICLE COUNT
URBAN RURAL
Dirt - county maintainance
- no county maintenance
Gravel - county maintenance
Cities - dirt
- gravel
75
15
100
75
100
40
11
60
40
60
3-19
-------
TABLE 3-10.
MAINTENANCE AREAS
1A
IB
1C
ID
IE
IF
2A
2B
2C
2D
2E
2F
3A
3B
3C
3D
3E
3F
3G
3H
31
4A
4B
4C
4D
4E
4F
Phoenix
Scottsdale
Paradise Valley
Glendale
Tempe
Chandler
Mesa
CLASSIFICATION OF MAINTENANCE
CITIES INTO RURAL OR URBAN
RURAL
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
AREAS AND
URBAN
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
3-20
-------
TABLE 3-11. PORTION OF AIR QUALITY SAMPLING
DAYS WITH RAINFALL IN 1975.
Quarter
of year
1
2
3
4
No. of days
sampling
participates
15
15
15
15
No. of
days with
rain
1
0
0
3
Fraction of
sampling days
with rain
.06
.00
.00
.20
year 60 4 .06
less in the fourth quarter of 1975 than those observed in the second or
third quarters.
3.1.3 Emission Estimates
The calculation of emissions is accomplished according to the procedures
outlined in this section.
Maricopa County
All emissions are calculated on the basis of each road maintenance
area or city.
Emissions from dirt and gravel roads are calculated separately.
For gravel roads, a 12% silt content and an average speed of
35 miles/hour are assumed. The mileage of gravel roads in each
maintenance area is 40% of the column labeled "County Maintenance
(Adjusted)" in Table 3-4. For cities, mileage is 40% of the total
miles of unpaved roads. Average daily traffic counts are either
100 vehicles/day (urban) or 60 vehicles/day (rural).
For dirt roads, the silt content of each maintenance area or city
is determined from Table 3-7. The average vehicle speed is 35
miles/hour. The mileages of dirt roads in each maintenance area
are 60% of the column labeled "County Maintenance (Adjusted)" and
the column labeled "No. Maintenance" in Table 3-4. Dirt road mi-
leage in cities is 60% of the total unpaved road mileages. Aver-
age daily traffic is determined from Table 3-9.
Northern Pinal County
All emissions are calculated on the basis of individual townships
and ranges .
3-21
-------
Emissions from dirt and gravel roads are calculated separately.
Mileages of dirt and gravel roads in each township and range) were
obtained from maps provided by the Arizona Department of Transportation.
For gravel roads, a 12% silt content and an average vehicle speed
of 35 miles/hour are assumed. All gravel roads are classified as
rural and possessing an ADT of 60 vehicles/day.
For dirt roads, the silt content of each township and range is
the average of those shown in Table 3-7. Average vehicle speed
is 35 miles/hour and the ADT is 40 vehicles/day (based on the
assumption that all dirt roads are rural).
The emissions model is used to estimate average daily dust emissions
from unpaved roads. For example, in Maintenance area 3A, the silt content
of county-maintained dirt roads is 25% (Table 3-7), the total mileage of
these roads is 93.8 (Table 3-4), the road is classified as rural (Table
3-10) with an average traffic rate of 40 light-duty vehicles per day (Ta-
ble 3-9) at average speed 35 miles/hour, and during a year (1975) in which
rainfall of .01 Inches or more occured on 6% of the days (Table 3-11).
The average daily emissions from Area 3A in 1975 are:
e = .81(25)(35/30)(40)(.94) = 89 Ibs/day.
Computer programs were developed to calculate total unpaved road
emissions for each of the maintenance or township areas. An additional
program was developed to translate the emissions from the maintenance and
township areas into the cells of the standard emissions grid network.
The calculated emissions are shown in the grid map format in Figure 3-2,
and portrayed graphically in Figure 3-3. As indicated, emissions from un-
paved roads are concentrated at the perimeter of metropolitan Phoenix,
and a significant portion of the emissions are generated within the city
areas.
The total dust emissions from unpaved roads throughout the study area
in 1975 were estimated as follows:
Quarter
1
2
3
4
Average
tons/day
1281
1365
1365
1086
1281
3-22
-------
GRID
CODE
0
1
2
3
4
5
6
7
8
9
.004
.02
.06
.16
.33
.60
1.04
1.67
EMISSIONS
TONS/DAY
0 TO 0
0 TO .004
TO .02
TO .06
TO .16
TO .33
TO .60
TO 1.04
TO 1.67
TO 2.53
Figure 3-2. Grid Map for Dust Emissions from Unpaved
Roads, 1975.
3-23
-------
co
ro
Figure 3-3. Average Daily Dust Emissions from Unpaved Roads, 1975.
-------
Uncertainties are introduced at all levels of the emissions estimates.
For example, errors are introduced in the estimates of average daily traffic
(ADT), as only estimates based on previous work performed by PEDCo were
available. It proved impossible to verify these ADT figures as very few
vehicle counts have been made on unpaved roadways. Inaccuracies also arise
with respect to mileages of unpaved roads in the study area, and the
assumed distribution of road types (60% dirt and 40% gravel) in Maricopa
County.
3.1.4 Particle Size Distributions
Based on field tests performed with conventional cascade impactors,
the average particle size distribution of roadway emissions have been
determined as shown below [1]. Due to the low capture efficiency of the
impactor for larger particles, the investigators (MRI) have cautioned that
these determinations,are biased toward overestimation of the smaller parti-
cles.
Particle Diameter (microns) Weight Percent
<2
2-30
30 - 100
25
35
40
3.2 AGRICULTURAL TILLING OPERATIONS
This section reviews current procedures utilized to estimate fugitive
dust emissions from agricultural tilling operations, and documents the
methodology developed for use 1n the present Inventory.
3.2.1 Review of Previous Inventories and Emission Factors
Emissions from agricultural activities can be expected to occur during
both the planting season (when the soil is prepared by tilling) and during
the harvesting season. A literature survey revealed no previous research
for emissions during the harvesting process and only two studies on
emissions from tilling operations (see Table 3-12).
The PEDCo emission factor was obtained from an article published in the
USSR. The manner In which this emission rate was derived is unclear. The
3-25
-------
TABLE 3-12. EMISSION FACTORS AND AGRICULTURAL TILLING OPERATIONS
SOURCE
PEDCo [2]
MRI [1]
co
i
f\3
EMISSION FACTORS
Q = (45)(1.28)v
where
Q = emission, grams/second
v = tractor speed, location/hour
1.4 s
(*}
V5T57
e =
/ PE \
(50 )
where
e = emissions, Ibs/acre
s = silt content of surface soil,
percent
S = implement speed, miles/hour
PE = Thornthwaite's prectpitation-
evaporation index
COMMENTS
Factor obtained from an article published
in the USSR.
Factor must be corrected for irrigation.
t Factor derived from tests conducted with
one-way disk plow and sweep-tvpe plow,
with a cut width of 12 ft.
Accuracy is +_ 15%.
t Applicable for particles with a drift
potential >25 ft., i.e., particles
<100y in diameter.
-------
MR! factor was the result of a test program similar to the one conducted
for .Improved roads (see Section 3.1.1).
No previous inventories were available for agricultural tilling emis-
sions in the Phoenix area. In developing estimates of fugitive emissions
for agriculture in the Phoenix area, PEDCo concluded that only 0.2 tons/acre/
year would be generated by tilling operations [2]. As this estimate resulted
in emission levels considerably less than those estimated by PEDCo for crop-
land wind erosion, the tilling operations were neglected 1n their inventory.
3.2.2 Methodology of Present Inventory
The MRI factor was selected for the same reasons the MRI factor for
unpaved roads was chosen in Section 3.1.2. This section will be devoted to
a discussion of the parameters affecting the calculation of agricultural
tilling emissions. The parameters include: (1) silt content of the soil, (2)
implement speed, (3) distribution of agricultural acreage and (4) temporal
distribution of tilling activities.
Two general assumptions should be mentioned. The
first involves the type of implement - the MRI tests are presumed valid
for one-way disk and sweep-type plows. Conversations with the Maricopa
County Agricultural Agent [16] indicated that a wide variety of implements
are actually employed, ranging from disk plows to moldboard plows to listers.
It is assumed emissions do not differ greatly from one implement type to
another. Secondly, it is presumed that no irrigation is conducted before
plowing. This was substantiated by the County Agricultural Agent [16]. It
should be noted that most fields are flooded with 9" to 12" of water after
plowing to leach out salts from the previous season.
Distribution of Agricultural Acreage
The spatial distribution of agricultural acreage .within the study area
was obtained from the "Cropland Atlas of Arizona" [17]. This publication
illustrates the location and shape of agricultural fields for the entire
state as they appear from high altitude. Flights were conducted by the
National Aeronautics and Space Administration from May 1972 to October 1973.
Although this period does not correspond to the baseyear of this study
3-27
-------
(1975), the distribution of all crop acreage has not changed substantially
during the intervening years [16].
The agricultural acreage within each township was estimated by scal-
ing the aerial maps of the cropland Atlas." A check procedure was employed
for Maricopa County to compare the published agricultural acreage (Refer-
ence [18]) versus the estimated acreages. The total of the estimated
acreage of all townships was found to be only 8% less than the published
figures.
Soil Silt Content
Silt content is defined to be the weight percent of the top four
inches of soil having particle diameter from 2 to 50 microns (.002 mm to
.05mm). The procedure employed to determine silt content for cropland
of a given townwhip is as follows:
In any given township, the predominant soil type in the area where
crops are grown is assumed to be the soil types for all agricultural
acreage in that township. Soil type distributions were found in
References [11] and [19].
For soil types which surface silt content was available (Reference
[13], these figures were employed. Otherwise, silt content of a
deep core sample (generally 0 to 5 feet in depth) as described
in Reference [12] were used. In all cases, a range of silt con-
tents is available.
Implement Speed
Limited data are available to characterize typical speeds of tillage
implements [1]. Investigation during the present study confirmed previous
findings that a speed of 5 miles/hour is generally representative of most
tilling operations [16].
Temporal Distribution of Emissions
Tilling operations are conducted once anually and in a given season
depending on the crop type. Emissions were calculated on a temporal basis
to demonstrate this variation. Figure 3-4 illustrates the usual planting
periods for the major crops in Maricopa and Final Counties (Citrus fruits
are not included, as they are not planted yearly).
3-28
-------
CO
I
ro
vo
Crop
Cotton
Alfalfa1
Wheat
Barley
Sorghum
Vegetables2 A
Saf flower
Sugarbeets
Jan
k
Feb
t
Mar
A_
i
Apr
1
>
May
k
>
June
July
,
,
Aug
v
^
Sep
t
t
k
Oct
,
>
t
Nov
A
,
,
Dec
t
L
Jan
,
,
,
,
Feb
I
,
Source: Reference (18)
1
Alfalfa is planted and then cut for three years. Planting ts usually during Fall and Spring.
"Vegetables include broccoli, cabbage, carrots, cauliflower, lettuce and onions. These vegetables
are planted at different times during the year (i.e. cabbage from Aug. 1-March 15, onions from
Oct. 12-Dec. 5) but span the entire year. For the purposes of this study, vegetables are assumed
to be planted all-year around.
Figure 3-4. Typical Planting Dates in Arizona
-------
3.2.3 Emission Estimates
All emissions are calculated on a township basis as follows:
(1) The fraction of each township used for agriculture is obtained
from Reference [17]. The percentage multiplied by 23,040
acres/township yields the acreage of farmland.
(2) The silt content of the agricultural acreage calculated in Step (1)
is available in References [12] and [13]. An average value of silt
is employed.
(3) The average speed of the implement is 5 miles/hour,
(4) The historical Thornthwaite Precipitatlon-Evappration Index for irri-
gated agricultural lands in the study area is approximately 50 (see
Section 4.3).
(5) The emission (Ibs/acre) can be calculated from the information
obtained in Steps (2), (3) and (4).
(6) The total agricultural tilling emissions in a township are calculated
from the result of steps (1) and (5).
The following sequence of steps describes how the emissions are distribu-
ted within any township on a temporal basis:
(7) Table 3-13 illustrates the percentage of the total acreages in
Maricopa and Final Counties devoted to each crop type. Only
crops requiring tilling (i.e., excluding citrus crops) are
considered. These percentages are assumed to be applicable for each
township, e.g., 35% of each township in Maricopa County is used
to grow cotton.
(8) Emissions from one crop type are distributed temporally only during
the planting season for that crop. For example, all cotton related
tilling emissions occur only from mid-March to the end of April
(see Figure 3-4).
(9) Table 3-14 presents the temporal distribution of tilling emissions
by crop type. For cotton cropland in Maricopa County, 1/3 x 35% =
11.6% and 2/3 x 35% = 23.4% of the annual study area tilling emis-
sions occur on cotton fields in March and April respectively.
Tilling emissions vary substantially by season. The greatest tilling
activity occurs in the second quarter of the year, when about 30 tons/day of
fugitive dust are generated. Tilling on cotton fields contributes the major
portion of dust emissions during this period. Tilling emissions average
only 1 ton/day during the third quarter, when planting activity for most
crops 1s minimal. The total emissions inventory for tilling operations in
3-30
-------
TABLE 3-13. CROP ACREAGE DISTRIBUTIONS IN MARICOPA AND FINAL COUNTIES [18]
County
Maricopa
Final
Does not
and field
2
Includes
onions.
Crop1
Cotton
Alfalfa
Wheat
Barley
Sorghum
2
Vegetables
Saf flower
Sugarbeets
Cotton
Wheat
Barley
Alfalfa
Sorghum
Saf flower
Sugarbeets
Vegetables
include citrus crops
crops.
1974 Acreage
166,100
106,900
74,000
50,000
32,000
25,410
7,700
4,670
472,580
141,950
56,000
38,000
18,900
14,000
6,800
4,670
4,380
284,700
and miscellaneous
broccoli, cabbage, carrots, cauliflower
Percent of
Total Acreage
35
23
16
11
7
5
2
1
100
50
20
13
7
5
2
2
1
100
fruits, vegetables
, lettuce and dry
3-31
-------
TABLE 3-16. TEMPORAL DISTRIBUTION OF TILLING EMISSIONS IN MARICOPA AND FINAL COUNTIES
County
Maricopa
Final
Crop
Cotton
Alfalfa
Wheat
Barley
Sorghum
Vegetables
Safflower
Sugarbeets
Cotton
Wheat
Barley
Alfalfa
Sorghum
Safflower
Sugarbeets
Vegetables
Percent of
Total County
Emissions
35
23
16
11
7
5 '
2
. 1
50
20
13
7
5
2
2
1
Percent Distribution of Crop Type Emissions by Month.
J
5.4
2.2
0.42
1
8
2.6
1
.083
F
2.2
0.42
2.6
.083
M
11.6
0.42
0.33
16.1
0.67
.083
A
23.4
1.27*
0.42
33.4
0.39*
.083
M
1.27*
3.5
0.42
0.39*
2.5
.083
J
1.27*
3.5
0.42
0.39*
2.5
.083
J
0.42
.083
A
0.42
.083
S
0.42
0.33
0.67
.083
0 '
1.27*
2.2
0.42
0.33
2.6
0.39*
0.67
.083
N
1.27*
3.2
2.2
0.42
4
2.6
0.39*
.083
D
1.27*
5.4
2.2
0.42
1
8
2.6
0.39*
1
.083
CO
no
*Alfa1fa is planted once each three years. These percentages are thus 1/3 of emissions from tilling operations.
-------
the second quarter is shown in grid map format in Figure 3-5, and graphi-
cally in Figure 3-6. As indicated, the greatest agricultural activity
occurs at the Northwest and Southeast boundaries of metropolitan Phoenix.
3.2.4 Particle Size Distributions
The MRI test results indicated that, on the average, dust emissions
from agricultural tilling have the following particle size characteristics:
Particle Diameter (microns) Weight Percent
< 2 35
2-30 45
> 30 20
3.3 AGGREGATE STORAGE PILES
3.3.1 Review of Previous Inventories and Emission Factors
Only two published emission factors are known to be reported, one in
the EPA Publication AP-42 [20] and one by the Midwest Research Institute [1]
(see Table 3-15). No details concerning the EPA derivation are known, so
the discussion will focus on MRI's work.
3-33
-------
GRIP
coor
cWISSIGNS
IONS/DAY
TO
.00000 TO
.00011 10
.^0057 TO
.001SO TO
.00*40 TO
,omi3 TO
.nif.9? 10
,0?fl»fc TCl
.n<.«.?? TQ
.00000
.001)11
.00057
.uoico
.00913
. 070
-------
CA>
cn
Figure 3-6. Average Dally Dust Emissions from Agricultural Tilling Operations, Second Quarter, 1975.
-------
TABLE 3-15. EMISSION FACTORS FOR AGGREGATE STORAGE PILES
Comments
Emission Factor
EPA Document AP-42 [20]:
e = 2 Ibs/ton of stored product
e = 10 Ibs/ton of stored product
Screening, conveying and handling losses
Storage pile losses
MRI Investigation [1]:
Aggregate Storage Operation (1)
Storage Pile
Activity
Active3
Inactive
(wind blown)
Normal mix *c
Lbs/acre of
Storage/day
13.2
3.5
10.4
Lbs/ton placed
in storage
0.42
0.11
0.33
a8-12 hour activity/24 hour day
*C5 active days/week
Normal Mix
Loading onto piles
Vehicular traffic
Wind erosion
Loadout from piles
Lbs/ton placed
in storage
0.04
0.13
0.11
0.05
0.33
Applicable for particles with a drift potential
>1QOO ft, i.e., particles smaller than 30v in
diameter
Correction factor for normal mix for different
climatic regions:
e _ 0.33
where
PE =
Thornthwaite's precipitation
evaporation index
Aggregate Loadout Operation C2)
e = 0.11 Ibs/ton loaded
-------
MRI conducted two field sampling programs. The first was designed to
quantify total dust emissions from the various constituent sources asso-
ciated with a representative aggregate storage operation, while the second
attempted to quantify emissions from a specific storage transfer operation -
aggregate loadout.
Conventional Hi-Vol samplers with wind direction activators were
employed in the first study because of the diffuse and variable nature of
the source. Four influence factors - rainfall, wind speed, type of aggre-
gate and amount of activity in the piles - were considered. Only two,
rainfall and amount of activity, were found to affect emissions. Emission
factors were calculated by assuming that all emissions from the stockpiles
passed through an imaginary vertical plane with the dimensions of the width
of the storage area by the average height of the piles; that the samplers
located downwind of the piles sampled particulate concentrations represen-
tative of average partfculate concentrations passing through this vertical
cross section; and that the total air volume containing this average con-
centration could be approximated as the average wind speed times the area
of the cross section. Calculations were performed for two conditions,
active piles and inactive piles, and included contributions from the move-
ment of traffic among the storage piles and from loading and unloading
operations, plus wind erosion. The factors do not include emissions from
the mining or processing of the aggregate or from traffic movement in
other parts of the plant. MRI cautions that the factors are not uni-
versally applicable and are intended to be representative for storage
piles in areas of the country with climatic conditions similar to Cincinnati,
Ohio. For normal mix operations (see Table 3-15), a correction factor for
different climatic conditions is given.
Field measurements were also made during the aggregate loadout pro-
gram. Conventional Hi-Vol and cascade impactors were the instrumentation.
A high-loader and dump truck were the "test vehicles." Total dust emis-
sions were the sum of the integrated exposure (above the background) and
the amount of deposition between the back of the truck and the exposure
profiler. Results of the program are shown in Table 3-15.
3-37
-------
A previous inventory of aggregate pile emissions was performed for
the Phoenix-Tucson AQCR by PEDCo. Emissions were estimated utilizing the
EPA emissions factor and by obtaining storage pile data through existing
emission source files at county and state air pollution control agencies.
3.3.2 Methodology of the Present Inventory,
The MRI "normal mix" emission factor, adjusted to the historical PE
Index for Phoenix (see Section 4.2), was selected. Accordingly, an emis-
sion factor of 36.6 Ibs/ton of aggregate storage was calculated. The
locations and storage rates of aggregate piles were obtained from the most
recently available NEDS point source listing. Based on an average of
approximately 1100 tons of aggregate pile material stored throughout the
study area, total dust emissions arising from these atorage piles is esti-
mated to be relatively insignificant just .01 tons/day. Figures 3-7
and 3-8 illustrate the grid map and distribution of aggregate pile emissions
for the study area.
3.3.3 Particle Size Distributions
MRI did not conduct a particle size distribution measurement program
for the "normal mix" emission factor. However, such a program was carried
out for the aggregate loadout emission factor. The loadout size distribu-
tions were assumed to be representative for the normal -mix emissions. This
distribution is as follows:
Particle Size (n ) Weight Percent
1 30
1-2 46
2-3 16
3-4 6
4 4
Three major sources of uncertainties are associated with this data: (1)
the sampling technique 1s biased towards the smaller diameters, (2) aggre-
gate loadout emissions comprise only 1/3 of the total "normal mix" emis-
sions (see Table 3-15) and (3) the characteristics of aggregate as tested
by MRI may not be similar to those in Arizona.
3-38
-------
GRID
CODE
0
1
2
3
4
5
6
7 v
8
9
EMISSIONS
TONS/DAY
0.00000 TO
.00000 TO
.00004 TO
.00023 TO
.00072 TO
.0017} TO
.00363 TO
.00672 TO
.01147 TO
.01837 TO
.00000
.00004
.00023
.00072
.00179
.00163
.00672
.01147
.01837
.02800
Figure 3-7. Grid Map for Dust Emissions from Aggregate
Piles, 1975.
3-39
-------
i.
Figure 3-8. Average Daily Dust Emissions from Aggregate Piles, 1975.
-------
3.4 CATTLE FEEDLOTS
3.4.1 Review of Previous Inventories and Emission Factors
PEDCo was found to have developed the only emission factor for cattle
feedlots (see Table 3-16). The development involved ambient air measure-
ments during two 24-hour periods at 24 California feedlots. The feedlot
emission factor was derived by relating ambient air data to emission rates
utilizing the Pasquill-Gifford diffusion equation [14]. Concurrent wind
data for the tests was not available, hence, mean local annual wind speeds
and a D stability class were assumed. Thus, PEDCo concluded that the calcu-
lated average values could be inaccurate by a factor of 2. The emission
factor is expressed in terms of tons per thousand head cattle or as tons
per acre of feedlot.
The only emission inventory performed for cattle feedlots in the Study
Area was also conducted by PEDCo [2]. Feedlots containing more than 5000
head only were considered. The names and sizes of individual lots were ob-
tained by a telephone survey of names shown in local agency files or in the
telephone directory. The totals from this survey were balanced against
published data in county agricultural statistical reports.
3.4.2 Methodology of the Present Inventory
The Maricopa County Agricultural Agent [16] was contacted to
determine the size and locations of major cattle feedlots (greater than
5000 head/feedlot) in Maricopa and northern Pinal Counties. These are
presented in Table 3-17. By applying the emission factors shown in
Table 3-16, total average feedlot emissions were calculated to be 6.5 tons/
day in the study area. Figures 3-9 and 3-10 illustrate the emission distri-
butions for the study area.
3.4.3 Particle Size Distributions
Particle sizes of cattle feedlot dust emissions are not reported in
the literature. Because of the continual pulverization of the feedlot soil
by cattle, the dust arising from this activity was assumed to approximate
the size distributions of dust emissions off dirt roads.
3-41
-------
TABLE 3-16. EMISSION FACTORS FOR CATTLE FEEDLOTS
Cattle,
1000 head
Range Average
<3 2
3-30 9
>30 45
Size of Feed lots
acres
Range Average
<20 5
10-100 20
>60 90
Annual
Emissions
tons/103 heads
8
8
5
Annual
Emissions
tons /acre
3
4
3
TABLE 3-17. CATTLE FEEDLOTS IN THE STUDY AREA
County
Maricopa
Pinal
Feedlot and Address
Rogers Feedlot - Baseline and 51st Avenue
Herseth Feed Co. - 35th Ave and Southern
Hughes-Garry Co. - Queen Creek Rd.
Scottsfield Feeding Co. - Scottsdale
Willis Feed Co. - McQueen Rd and Germaine
Arlington Cattle Co. - Arlington
Gila Feed Yard - Gila Bend
Producers Livestock - Washington St.
Spur Industries - Sacaton
Red River Feeding Co. - Stanfield
Benedict Feed Co., - Stanfield
Kelly Feeding Co. - Maricopa
T & C Feeding - Maricopa
West Coast Cattle Co. - Casa Grande
Size (103 Head)
8
30
55
11
4
30
40
15
30
125
20
5
25
30
3-42
-------
GRID
CODE
0
1
2
3
*
5
6
7
EMISSIONS
TONS/DAT
o.oonoo TO
.00000 TO
.0001* TO
.00070 TO
.00220 TO
.00537 TO
.01115 TO
.02065 TO
.03573 TO
.056*2 TO
.00000
.0001*
.00070
.00220
.00537
.01115
.02065
.03523
.056*2
.08600
Figure 3-9. Grid Map for Dust Emissions from Cattle Feedlots, 1975.
3-43
-------
co
i
Figure 3-10. Average Daily Dust Emissions from Cattle Feedlots, 1975.
-------
3.5 OFF-ROAD MOTOR VEHICLES
In the context of this study, off-road vehicles are defined to
include both motor vehicles and motorcycles. Generally, the motor
vehicles possess four-wheel drive and the motorcycles are of the two-
stroke variety.
Very little data is available to determine the frequencies and loca-
tions of off-road vehicle use. The activity is recreational in nature and
subject to unpredictable variations. The information presented here is
based on crude estimates obtained from cognizant individuals familiar with
off-road vehicle use.
3.5.1 Motorcycles
Over 95% of the dirt bike activity occurs within a 100 mile range
of the metropolitan Phoenix area. The most popular areas are in the
hills and mountains to the north and east of the metropolitan areas,
where 3000 - 4000 riders may be found during weekends [21, 26]. On
weekdays, the activity drops into the hundreds. Typical of the riding
activity in these locations is cross country biki.ng, with the Cavecreek
and Usery Mountain areas as locations of where this activity originates.
Other areas include Apache Junction in Pinal County, Buckeye, Lake
Pleasant and the Four Peaks area in Maricopa County [21,22,23,24,25,26].
The city of Phoenix has set aside 270 acres northeast of the town of
Catcus for dirt riding. In that area, weekends draw about 75 bikers/day
and weekdays about 10/day [23].
Bureau of Land Management property is widely and indiscriminately
used by bikers. Most commonly used are the ground surfaces readily
accessible from roadways, where there is a lack of development and where
there are no indications of BLM supervision [22], Maricopa County has a
no-riding policy which apparently cannot be enforced. Both the U.S. Forest
Service and BLM are contemplating the closure of certain areas, but defi-
nite action has yet to be taken [21,22],
3-45
-------
Dirt biking is a year-around activity in the Phoenix area. The
bikers generally stay on site for 3-5 hours and travel at speeds not
exceeding 30 miles/hour.
Emission Factor
The MRI emissions' model [1] for motor vehicles on unpaved roads was
adopted for use. Consultation with MRI [10] indicated that
the factor should be adjusted downwards by 25% to 50% due to both the
number of wheels and aerodynamic characteristics of motorcycles versus
motor vehicles. The decision was made to employ a 50% reduction.
Location and Level of Activity
Based on an average of 3500 total cycles operating per weekend in the
designated areas, the townships within the study area may be determined.
The assigned activity levels are shown, township by township, in Table
3-18. Weekday activity is assumed to be about one seventh that for a
weekend day.
Average daily travel per cycle is assumed to be about 45 miles based
on 3 hours of riding at approximately 15 miles/hour.
Vehicle Speed
An average speed of 15 miles/hour is assumed.
Soil Silt Content
The silt content of the townships presented in Table 3-19 are deter-
mined from References [11] and [19], utilizing the same procedure as was
applied for agricultural fields (Section 3.2.2).
Emission Estimates
Table 3-20 illustrates the results of the emissions calculations.
The emissions are calculated both for the weekend period, when the substan-
tial portion of off-road travel is conducted, and for the weekdays, when
off-road activity is relatively minimal. The average daily emission rate
for off-road cycle travel is calculated to be 54.2 tons/day.
3-46
-------
TABLE 3-18. LOCATIONS AND LEVELS OF OFF-ROAD MOTORCYCLE ACTIVITY
Township and Range
T1S, R3W
TIN, R8E
T2N, R6E
, R7E
, R8E
T3N, R1E
T4N, R5E
, R7E
, R8E
, R10E
T6N, R1W
, R1E
, R4E
, R5E
, R6E
, R7E
Cycles/Weekend
150
300
150
150
150
300
75
150
150
300
150
150
80
80
80
80
Cycles/Weekday9
11
21
11
11
11
21
6
11
11
21
11
11
6
6
6
6
a. Weekday activity Is assumed to be one seventh the level of
weekend day activity.
3-47
-------
TABLE 3-19. SOIL SILT CONTENTS FOR OFF-ROAD MOTORCYCLE ACTIVITY
Township and Range
T1S, R3W
TIN, R8E
T2N, R6E
, R7E
, R8E
T3N, R1E
T4N, R5E
, R7E
, R8E
, R10E
T6N, R1W
, R1E
, R4E
, R5E
, R6E
, R7E
Soil Silt Content (percent)
20-60
5-30
10-30
10-30
10-30
30-50
10-30
20-60
10-30
10-30
10-30
20-60
10-30
10-30
10-30 .
10-30
3-48
-------
TABLE 3-20. EMISSIONS FROM OFF-ROAD MOTORCYCLES
Township - Emission Rate
and Range Average Silt Content (%) (Lb/Veh-Mile)
T1S,
TIN,
T2N,
>
>
T3N,
T4N,
>
>
>
T6N,
>
»
»
»
>
R3W
R8E
R6E
R7E
R8E
R1E
R5E
R7E
R8E
R10E
R1W
R1E
R4E
R5E
R6E
R7E
40
17
20
20
20
40
20
40
20
20
20
40
20
20
20
20
8.1
3.4
4.1
4.1
4.1
8.1
4.1
8.1
4.1
4.1
4.1
8.1
4.1
4.1
4.1
4.1
Cycles
Per Weekend
150
300
150
150
150
300
75
150
150
300
150
150
80
80
80
80
Emissions
tons/weekend
27.3
22.9
13.8
13.8
13.8
54.6
6.9
27.3
13.8
27.7
13.8
13.8
7.4
7.4
7.4
7.4
279.1
tons/weekday
2.0
1.6
1.0
1.0
1,0
3.9
.5
2.0
1.0
1.9
1.0
1.0
.5
.-5
.5
.5
19.9
CO
UD
NOTE: Average motorcycle speed is 15 miles/hour
Average mileage/cycle is 45
-------
3.5.2 Motor Vehicles
Because of their relatively limited mobility (as compared to dirt
bikes), the activities of four-wheel drive vehicles were discovered to
be of lesser scope than motorcycles. However, data on the frequency and
total number of vehicles were sadly lacking. Only the organized functions
of the major off-road vehicle club in the area, the Phoenix 4-Wheel Club,
could be documented. Activities of private parties, such as hunters and
occasional weekend vacationers, could not be quantified. As a result,
the estimates made in this report are probably less than the actual levels.
According to the Phoenix 4-Wheel Club [27], three locations in
Maricopa and Northern Pinal Counties are preferred - the Sycamore Caryon
in the Tonto National Forest, the P-4 W Ranch* outside of Wickensbunj
and an area near Florence (in Pinal County). Normally, the Club conducts
one organized trip/month, consisting of approximately 13 vehicles ami
having an average trip length of 150 miles. Occur ing more frequently
are impromptu trips arranged by individuals in the Club.
Emission Factor
The MRI Emissions Model [1] for vehicles on unpaved roads was selected
for use. Discussions with MRI [10] resulted in the decision that no adjust-
ment was required.
Location and Level of Activity
The location of off-road motor vehicle activity is described on a
township basis as shown in Table 3-21. An average weekend traffic level
of 13 vehicles per location is assumed, as well as an average trip length
of 150 miles. The average speed is assumed to be 30 miles/hour. Weekday
traffic activity is assumed to be one seventh the level of a weekend day.
* The Bureau of Land Management has given the Phoenix 4-Wheel Club
(P-4W) a special permit to use this area.
3-50
-------
TABLE 3-21. LOCATION OF OFF-ROAD FOUR WHEEL VEHICLE ACTIVITY
Township and Range
T7N, R4W
T4N, R7E
T4S, R10E
Soil Silt Content
The silt content of the affected townships is presented in Table
3-22 and are determined from References [11] and [19], utilizing the same
procedure as detailed for agricultural fields (see Section 3.2.2).
Emission Estimates
Table 3-23 presents the emission estimates for off-road four wheel
vehicle travel. The emissions are calculated for the weekend period, when
the major portion of off-road travel is conducted, as well as for weekdays,
when travel activity is minimal. The average daily emission rate for off-
road four wheel vehicle travel is calculated to be 16.8 tons/day.
The total average dust emissions associated with both off-road cycle
and four wheel vehicle activity is 71 tons/day. Weekday emissions are
only one seventh that occuring on weekend days. Figure 3-11 shows the dis-
tribution of emissions in the grid format, and Figure 3-12 portrays the
distribution graphically. As indicated, dust emissions from off-road
vehicles are generally concentrated in remote areas outside of Metropolitan
Phoenix. The uncertainty associated with the estimates of both the magni-
tude and location of the emissions is substantial.
3.5.3 Particle Size Distributions
It is assumed that the size distribution of emissions from off-road
motor vehicles will be the same as for vehicles on unpaved roads:
Particle Size (n ) Weight Percent
< 2 25
2-30 35
30 - 100 40
3-51
-------
TABLE 3-22. SOIL SILT CONTENT IN AREAS OF OFF-ROAD FOUR WHEEL VEHICLE ACTIVITY
Township and Range
T7N, R4W
T4N, R7E
T4S, R10E
Soil Silt Content
10-30
20-60
30-70
TABLE 3-23. EMISSIONS FROM OFF-ROAD FOUR WHEEL VEHICLES
Township
and Range
T7N, R4W
T4N, R7E
T4S, R10E
Average Silt
Content (%)
20
40
50
Emission Rate
(Lb/Veh-Mile)
16.2
32.4
40.5
Emissions
(Tons/Weekend)
15.8
31.59
39.48
86.9
Note: Average vehicle speed is 30 miles/hour, activity is 13
vehicles /day per township, and average trip length is
150 miles.
3-52
-------
GRID
CODE
0
1
Z
3
<,
5
6
7
EC.ISS10NS
TLNS/DAY
0.00000 TO
.00000 10
.00117 TO
.00590 TO
.01(165 TO
.0<>553 TO
.OS<.<.1 TO
,17<,90 TO
.29636 1U
,*779
-------
en
Figure 3-12. Daily Average Dust Emissions from Off-Road Motor Vehicle Activity, 1975.
-------
3.6 FUGITIVE DUST FROM CONSTRUCTION ACTIVITIES
Construction activities inevitably result in the exposure and dis-
turbance of soil. Fugitive dust is emitted both during the activities
(i.e., excavation, vehicle traffic, human activity) and as a result of
wind erosion over the exposed earth surfaces. The major types of con-
struction occurring in Phoenix are flood control projects, roadway con-
struction, and residential/commercial/industrial building.
Review of Previous Inventories
Fugitive dust arising from construction activities in 1970 was
estimated previously by PEDCo. Emission rates were based on a field
investigation from specific construction sites in Paradise Valley, Phoenix,
and in Las Vegas, Nevada. The Paradise Valley site was an 80 acre residen-
tial development with a shopping center. The Las Vegas site was a 100
acre residential development. Particulate sampling stations were placed
at various locations surrounding the construction sites. Measurements
of particulate levels and wind were used to solve diffusion equations for
source dust emission rates from the construction site. The tests indicated
an average dust emission rate of 1.4 tons/acre/month from construction
sites. This rate was applied to the number of acres of activity con-
struction during 1970 to calculate an average daily dust emission level
of 170 tons/day for Maricopa County.
Midwest Research Institute [1] has recently reviewed the PEDCo field
experiments [2] including additional measurements from the test sites not
available for the PEDCo analysis. The review resulted in derivation of
dust emission rates consistent with the initial findings, but slightly
lower. An average dust emission rate of 1.2 tons/acre/month for active
construction was established.
Methodology for the Present Inventory
The previous studies sited above constitute the basic awareness
available for deployment in the present study. Construction activities
should be summarized in terms of acres of soil disturbed, and the single
emission rate (1.2 tons/acre/month) is applied to all types of active
construction to estimate total dust levels emitted.
3-55
-------
Roadway construction activities for the study area in 1975 are sum-
marized in Table 3-24. The county, the state, and each of the cities
execute separate construction programs in the county. Based on average
roadway clearing widths used in construction, the average area of exposed
surface is calculated as shown in Table 3-25. ' the duration of active
construction during which the road bed is exposed soil is generally about
6 months for a major road job of one mile length and 80 feet width, and
about 2 months for each half a mile of local streets 33 feet wide [28].
Based on an average emission rate of 1.2 tons/acre/month, the dust emis-
sions arising from road construction are shown in Table 3-25.
TABLE 3-24. SUMMARY OF ROAD CONSTRUCTION
ACTIVITY IN PHOENIX AREA, 1975 [29]..
RESPONSIBLE
AGENCY
County
Phoenix
Glendale
Paradise Valley
Peoria
Mesa
Tempe
State Highway Dept
IMPROVEMENTS SUBDIVISION
(MAJOR & LOCAL (PRIVATE CON-
ROADS) STRUCTION
20.0
26.4
0
1.5
0
0
0
0
47. 9C
a' Of those roads financed
highways 80' wide, and
' Average width
' Average width
of these
of local
MILES OF ROADWAY
56.0
58.7
14.7
2.8
0
32.7
10.3
0
175. 2b'
by federal aid, 18.9
37.3 miles are 2 lane
roads is 33 feet.
and major roadways is
FEDERAL
AID
SYSTEM
15.8
3.6
0
0
0
0
0
36.8
56. 2a
miles are
highways
55 feet.
CITY
OR
COUNTY
128.7
1.4
0
.6
2.1
0
0
0
132. 8b'
4 lane
48 ft. wide.
3-56
-------
TABLE 3-25. DUST EMISSIONS ARISING DURING ACTIVE
CONSTRUCTION OF ROADS IN PHOENIX AREA,
AGENCY
County
Phoenix
Glendale
Paradise Valley
Peoria
Mesa
Tempe
State Highway Dept
ACRES OF SOIL EXPOSED
IN ROAD CONSTRUCTION
990
446
59
26
8
130
41
262
1952
AVERAGE DURATION
OF SOIL DISTURBANCE
2.5 months
2.9
2.0
3.1
2.0
2.0
2.0
4.0
DUST EMISSIONS
TONS/DAY ANNUAL
AVERAGE)
8.2
4.3
.4
.3
.1
.9
.3
3.5 >
18.0
Because the magnitude of exposed soil area resulting from roadway
construction is relatively small by comparison with other fugitive dust
source areas, efforts to resolve this source spatially on the grid net-
work were limited. Construction dust emissions for each of the cities
was allocated evenly on the emissions grid network within the entire city
boundaries, and road construction dust for the county and State Highway
Department was apportioned evenly throughout the county portion of the study
area.
The most significant source of construction dust arises during the
building of residential/commercial/industrial structures. Residential
housing comprises the major portion of the activity in this construction
category. Figure 3-13 shows the distribution of housing units constructed
during 1975. Most of the new housing was constructed around the perimeter
of urbanized Phoenix, and overall construction activity was relatively
light in 1975.
3-57
-------
i'-: (Based on Building Permits Issued January through December, 1975)
fe ,,."iV*: ./.,
^A'3-#i^$h>^-' *:&r' Mop Key i
P;- 1.1^>^^V.-;^,-i;..^f;;; Total Housing Unity
iSJSJy^W^!'. "5°°-w
District \
1 j
2 '
3 .
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
Total
Metro
Phoeria
1975
Total
/Metro
Single
319
953
548
552
127
744
52
37
7
9
6
39
734
16
211
513
1,184
808
1,846
1974
Percent
Townhouse
f 43 '
5 5
j
\ 8
! 7
k
0
i 12
i -
4
1
*
il
» 104
'* 32
} 22
t 176
1 409
Multiple
13
9
17
440
10
152
20
15
95
2
21
14
5
30
2
845
i J
'' \
2,354 S 6,073
t 1
-82.6% j -86.1%
Total Units
375
967
565
1,000
134
754
204
69
22
104
8
39
734
37
211
631
1,221
860
2,024
9,959
19,707
-49.59£
Less than 500
8,705
11,280
-22.8%
Source: Maricopa Countv Housing Study Committee, M. R. Welt Marketing
Research, Inc.
Figure 3-13. New Housing Units in Maricopa County, 1975 [30].
Recent studies by the Maricopa County Planning Department [31]
provide a basis for estimating the amount of disturbed soil associated with
housing development. One study utilizes 1970 census data to develop the
following occupancy rates for housing units.
Single Family Dwellings
Multi-family Units
Mobile Homes
3.45 persons
2.22
2.22
Weighted Average 3.14 persons/home
Another study [32] has established the relationship between land use and
population in Maricopa County. Table 3-26 shows this relationship for
various separate land use categories. These land use ratios have been
employed by the Maricopa County Planning Department to forecast land use
allocation consistent with population growth projections. The ratios were
used in the present inventory as a basis for total amounts of land utiliza-
tion in each of the land use sectors for 1975. First, residential housing
3-58
-------
TABLE 3-26. URBAN LAND USE RATIOS [32].
LAND USE CATEGORY
ACRES PER
100 PERSONS
Single-Family
Multi-Family
Mobile Homes
TOTAL RESIDENTIAL
TOTAL COMMERCIAL
Light Industry
Heavy Industry
Railroads and Public Utilities
TOTAL INDUSTRIAL
Streets and Alleys
Parks and Playgrounds
Public and Semi-Public
TOTAL PUBLIC AND SEMI-PUBLIC
TOTAL DEVELOPED LAND
5.20
.85
.20
6.25
.70
.55
' .25
.40
1.20
3.45
2.00
1.40
6.84
15.00
land use was estimated by combining the land use ratios with average
occupancy rates, 1975 housing construction data (Figure 3-13), and a
housing unit inventory compiled by M. R. West Marketing Research, Inc.
[30]. Average acreage figures per housing unit were established by
housing unit type as shown in Table 3-27.. These average rate figures
were then employed to calculate disturbed soil areas associated with
housing construction in each of the districts as shown in Table 3-28.
TABLE 3-27. LAND USE BY HOUSING UNIT TYPE IN MARICOPA COUNTY
Single Dwellings
Multiple Dwellings
Mobile Homes
OCCUPIED,
UNITS a>
299,300
120,000
42,000
PERSONS
PER UNIT
3.46
2.22
2.22
TOTAL PERSONS
. OCCUPING
D> DWELLINGS
1,035,000
267,000
93,200
ACRES OF
LAND USE r ACRES PER
PER PERSONC> DWELLING
.052
.0085
.0020
.242
.099
.066
a.
Reference [30].
b.
Reference [31].
c.
Reference [32],
3-59
-------
TABLE 3-28. DUST EMISSIONS ARISING FROM CONSTRUCTION ACTIVITIES IN MARICOPA COUNTY, 1975.
DISTRICT ACRES OF DISTURBED SOIL DURING HOUSING CONSTRUCTION
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
a.
b.
SINGLE MULTIPLE UNITS TOTAL ALL
DWELLINGS AND MOBILE HOMES HOUSING
77 7 ' 84
232 2 234
133 2 135
134 55 189
31 1 32
180 1 181
13 19 32
9 4 13
224
2 11 13
1 01
909
178 0 178
4 -3 7
51 0 51
124 .15 139
287 5 292
196 5 ' 202
447 22 469
AVERAGE DUST EMISSIONS FROM HOUSING AND OTHER CONSTRUCTION*5'
TONS/DAY
3.1
8.6
4.9
6.9 .
1.2
6.6
1.2
.5
.1
.5
0
.3
6.5
.3
1-9
5.1
10.7
7.4
17.2-
83.0
The inventory of new mobile homes by district was not available. Therefore, mobile units
were assumed to increase to the same degree as multiple and townhouse dwellings in each of the districts.
"Other"construction land use average was estimated using historical land use ratios for the Phoenix area (Table 3-26).
The ratio of "other" land use (excepting street use) to housing land use was computed to be .85. Dust emissions were
calculated using the general emission rate 1.2 tons/month/acre of disturbed (developed) soil, applied for an average
of 6 months active construction duration.
co
i
-------
Development of other sectors of the community associated with housing
was estimated by applying historical land use to population ratios for the
Phoenix area (Table 3-26). These ratios indicate that for every 6.25 acres
of housing development, there is another 8.75 acres of development of various
other land use types. Because roadway construction has already been con-
sidered previously (including both new development and improvements), this
land use category was deducted from the data base. Consequently, it was
estimated that for each acre of housing development, there would be .85
acres of development for commercial, industrial, and public use. This
ratio was employed to calculate the amount of land disturbed by construction
activities other than housing for each district. Estimates of dust emissions
arising from all categories of construction activities were generated by
applying the general emission factor of 1.2 tons/month/acre of construction.
The results are shown in Table 3-28.
The building construction emissions levels and road construction ',
emissions levels were assigned to the computerized emission grid network
by district areas as shown in Figure 3-13. A grid network overlay was
used to accomplish the appropriate allocations. Construction activities
in the Final County portion of the study area were neglected in the
analysis because of their relative insignificance in 1975. Figure 3-14
presents the grid map of fugitive dust emissions from construction activi-
ties, and Figure 3-15 portrays graphically the distribution of construc-
tion dust emissions in the study area for 1975. The magnitude of dust
loading from construction activity is substantial, and is generally
distributed most heavily in the growth belt around the urban region of
Phoenix. It should be noted that land use development during 1975 was greatly
below the expectations reflected in the county planning forecasts, and represented
the lowest dip in a recent decline of construction activity over the past several
years. This pattern is expected to reverse sharply in 1976 and future years.
Hence 1975 is probably non-representative with respect to dust emissions load-
ings occurring from construction.
The particle size distribution of construction dust emissions are expected
to approximate that of the parent soil [33]. The predominant soil types in Maricopa
County yield the following particle size distribution based on shallow core
tests [11]:
3-61
-------
SB JO
CDUE
0
1
2
3
0.00000
.00000
tPISSIDNS
ILNS/D4Y
IL
TO
.oou-j^ rc
.002<
-------
GO
I
Ot
oo
Figure 3-15. Average Dally Dust Emissions from Construction Activities, 1975.
-------
Rillito-Gunsight - Pinal Gilman-Estrella-Avondale
<2y
2-20
20-50
>50
5%
10
17
68
<2p
2-20y
20-74
>74
7%
20
35
38
Since the construction emission factor was developed for particles of 30
micron diameter and less, only the particle size below 30 micron is rele-
vant in the discussion here. The expected aerosol distribution for parti-
cles smaller than 30 micron will be approximated based on an averaging of
the particle size distribution of the two predominant soil types. The
resulting size distribution for the emissions is as follows:
<2y 21%
2-20 54
20-30 25
3.7 ENTRAPMENT OF DUST OFF PAVED ROADS
Until recently, only limited consideration had been directed to
the analysis of fugitive dust sources on paved roads. Studies in Chicago
[34] demonstrated that suspension of street dust contributed to substantial
levels of suspended particulates. Increasing evidence that street dust
exerts a significant influence on air quality is leading to efforts to
quantify this fugitive emission source. Midwest Research Institute has
recently completed a study[35] to evaluate the dust,emission rate from streets
and to parametize the influence factors affecting this rate. This general
dust emissions model represents the most direct and complete attempt to
quantify street dust emissions to date, and will be employed in the
present study. The model gives the emission level as
3-64
-------
e = KLS
where k = 15 x 10" , an empirical proportionality factor
L = street surface dust load, g/curbed mile of
road.
S = silt content of surface dust
(usually about .10).
The dust loadings on a given roadway may vary significantly depending
on several factors. Rain or street sweeping may reduce dust loadings to
negligible levels for short periods. Accumulation of materials to an
equilibium level after the washouts occurs rapidly, usually within 2 or
3 days. Equilibium is attained more rapidly after street cleaning, since
-often the cleaning process is only moderately effective. After rainfall,
carry-over of mud collected under motor vehicles occurs at varying rates
for several days until an equilibrium of street dust levels is attained/
The equilibrium attainment rate has also been found to increase rapidly
with higher vehicle speeds.
Street dust loadings for the Phoenix area are shown in Table 3-29.
The limited number of measurements, and the lack of a definitive pattern
of dust loads relative to street types does not warrant development of a
separate emission rate for different street types in the present study.
A weighted average of 780 Ib/curb mile was selected as a representative
dust loading for the entire population of curbed road types in Phoenix.
Based on a study by American Public Works [36], the dust load level was
increased by a -factor of four for uncurbed streets.
Based on the appreciable proportion of unpaved road shoulders in
metropolitan Phoenix, it is not unlikely that dust suspension off city
streets would contribute greatly to the ambient particulate problem.
There are 470 miles of city streets with unpaved shoulders in the city.
Over half of these roads are major streets experiencing substantial
traffic volumes. The ratio of uncurbed to curbed roads in the various
unincorporated cities was assumed to be equivalent to that in the city
of Phoenix. The county roadway system is comprised of approximately
3-65
-------
TABLE 3-29. DUST LOADS ;ON STREET SURFACES OF PHOENIX [35],
Land Use
Residential
low/old/single
low/old/multi
med/new/single
med/old/multi
Industrial
light
Medi um
Commercial
central business area
Shopping center
Overall weighted mean
Loading
Site #1
770
1900
180
310
450
1300
210
640
650
Intensity (Ib/curb
Site #2
1600
1100
380
500
260
1100
200
180
910
mile)
Mean
1185
1500
280
405
355
1200
205
410
95% uncurbed streets. There is an active city street sweeping program,
including cleaning of major streets every 10 days, collectors every 2
weeks, and local roads once monthly. However, this program is only
marginally effective with respect to controlling entrained dust levels,
due to rapid deposition of surface dust which produces equilibrium levels
of road materials within 2 or 3 days.
3-66
-------
The silt content of the street surface dust load is controlled
/
within a relatively narrow range by the mechanism of deposition-
reentrainment equilibrium. Coarse dust aggregates are continuously
being pulverized into finer particles which become suspended by traffic
activity, and additional aggregates are continuously deposited on the
roadway by vehicle carry over, dustfall from adjacent sources, motor
vehicle exhaust, and tire and brake wear. Measurements have shown
that the silt content of street surface dust is from 5 to 15% for a
wide range of street and traffic conditions [37]. A value of 10% silt
was assumed to be representative for Phoenix street dust.
Emission Estimates
The emission factors for resuspended dust off paved streets in
Phoenix were calculated using the MRI model. They are:
Curbed roads 5.3 g/vehicle mile
Uncurbed roads 21.2 g/vehicle mile
These factors were applied to traffic volumes for each curbed and uncurbed
link of the transportation link network in the study area. However,
because the transportation tape does not identify the curbed or noncurbed
status of the various road types, it was necessary to develop an overall
weighted emission factor to be applied to the three major street categories
(local, collector, major). The factor is weighted according to the
proportion of miles of curbed to noncurbed streets as shown below. Local
roads were omitted from consideration due to the insignificance of traffic
volume on these streets relative to the total area VMT.
Street Type
Major and Collector
Total Miles
in City
900
Total Uncurbed
Miles in City
329
Weighted Emission
Factor for 1975
11.1 g/vehicle mil
Emissions calculated for each link were assigned to grid squares of
the study area grid network by means of the TRW emissions simulator soft-
ware. The simulator operates on a computer tape of 1975 transportation
link data (including designation for city and county roads) provided by
the Arizona Department of Transportation. The software operations are
3-67
-------
essentially the same as those employed to estimate conventional motor
vehicle source emissions (see Section 2.0).
Figure 3-16 illustrates the gridded emission inventory for
entrained street dust. The magnitude of these dust emissions is
significant, especially considering they are concentrated within
the urbanized areas where other major fugitive sources, i.e., unpaved
roads, agricultural) are absent. The distribution of the resuspended
dust emissions is shown graphically in Figure 3-17.
The particle size distribution of the suspended street dust is
given by MRI [35].
< 5^ 40%
5-30^ 60%'
3-68
-------
CD 10
CMf
EMISSIONS
TONS/DAY
0.00000
.00000
.00389
.01970
.06227
.19202
.31523
.58401
.99630
l.»9)»7
TO
TO
TO
TO
TO
TO
TO
TO
TO
TO
.00000
.03369
.01970
.06227
.15202
.31523
.58
-------
Figure 3-17. Average Daily Street Dust Emissions Entrained by Motor Vehicles on Paved Streets, 1975,
-------
REFERENCES FOR SECTION 3.0
1. Midwest Research Institute, "Development of Emission Factors for
Fugitive Dust Sources," prepared for the Environmental Protection
Agency, Office of Air Quality Planning and Standards, Research
Triangle Park, North Carolina, June 1974.
2. PEDCo Environmental Specialists, Inc., "Investigation of Fugitive
Dust, Volume I - Sources, Emissions and Control," prepared for the
Environmental Protection Agency, Office of Air Quality Planning and
Standards, Research Triangle Park, North Carolina, June 1974.
3. "Air Pollution from Unpaved Roads," a research paper by the School
of Engineering, University of New Mexico, January 12, 1971.
4. Hoover, J. M. "Surface Improvement and Dust Palliation of Unpaved
Secondary Roads and Streets," Final Report, by Engineering Research
Institute, Iowa State University, ERI Project 856-S, submitted to
the Iowa State Highway Commission, July 1973.
5. Anderson, C., "Air. Pollution from Dusty Roads," as presented at the
17th Annual Highway Engineering Conference, 1 April 1971.
6. Roberts, J. W., et. al, "Cost and Benefits of Road Dust Control in
Seattle's Industrial Valley," JAPCA, Vol. 25, No. 9, September 1975.
7. Arizona Department of Transportation, personal communication, March
1976.
8. Maricopa County Highway Department, personal communication, March
1976.
9. Maricopa Association of Governments, personal communication, March
1976.
10. Dr. Chatten Cowherd , Midwest Research Institute, personal communi-
cation, March 1976.
11. U. S. Department of Agriculture, Soil Conservation Service, "General
Soil Map, Maricopa County, Arizona," Portland, Oregon, 1973.
12. U. S. Department of Agriculture, Soil Conservation Service, "Soil
Survey - Eastern Maricopa and Northern Pinal Counties Area, Arizona,"
Washington, D. C., 1974.
13. U. S. Department of Agriculture, Soil Conservation Service, "Soil
Survey Laboratory Data and Description for Some Soils of Arizona,"
Soil Survey Investigations Report No. 28, August 1971.
3-71
-------
14. Turner, D. B., "Workbook of Atmospheric Dispersion Estimates,"
U. S. Department of Health Education and Welfare, Public Health
Service, National Air Pollution Control Administration, Cincinnati,
Ohio, 1969.
15. Arizona Department of Transportation, Planning Survey Group, "Status
of the Road Systems Mileage," June 1975.
16. Maricopa County Agricultural Agent, personal communication, April
1976.
17. Arizona Crop and Livestock Reporting Service,"Cropland Atlas of
Arizona," Phoenix, Arizona, October 1974.
18. Arizona Crop and Livestock Reporting Service, "1974 Arizona Agri-
cultural Statistics," Bulletin S-10, Phoenix, Arizona, March 1975.
19. U. S. Department of Agriculture, Soil Conservation Service, "General
Soil Map, Pinal County, Arizona," Portland, Oregon, 1972.
20. U. S. Environmental Protection Agency, "Compilation of Air Pollutant
Emission Factors," Publication AP-42, Office of Air and Water Pro-
grams, Research Triangle Park, North Carolina, April 1973.
21. U. S. Forest Service, Phoenix, Arizona, personal communication,
May, 1976.
22. Bureau of Land Management, U. S. Department of Interior, personal
communication, May, 1976.
23. Phoenix City Parks and Recreation Department, personal communication,
May, 1976.
24. Glendale City Parks and Recreation Department, personal communica-
tion, May, 1976.
25. American Motorcycle Association, Phoenix, Arizona, personal commun-
ication, May, 1976.
26. Tonto National Forest Service, Phoenix, Arizona, personal communica-
tion, May, 1976.
27. Phoenix 4-Wheel Club, personal communication, May, 1976.
28. City of Phoenix Department of Traffic Engineering, personal communica-
tion, May 1976.
29. State of Arizona Highway Department, personal communication, April
1976.
30. Phoenix Newspapers, Inc., "Inside Phoenix 1976," 1976.
3-72
-------
31. Maricopa County Planning and Zoning Department, "Data for School
Planning," April 1973.
32. Maricopa County Planning Department, "A Report Upon Future General
Land Use for Maricopa County, Arizona," February 1975.
33. Gillette, D, and BUfford, I, National Center for Atmospheric Research,
"The Influence of Wind 2elocity on the Size Distribution of Aerosols
Generated by the Wind Erosion of Soils," Journal of Geophysical Re-
search. September 20, 1974.
34. Harrison, P., Draftz, R. and W.H. Murphy, "Identification and Impact
of Chicago's Ambient Suspended Dust," Paper submitted to Atmospheric
Environment, 1974.
35. Midwest Research Institute, "Quantification of Dust Entrainment from
Paved Roadways," final report draft, prepared for Environmental Pro-
tection Agency, March 1976.
36. American Public Works Association, "Water Pollution Aspects of Urban
Runoff," Chicago, 1969.
37. Chatten Cowherd, Midwest Research Institute, personal communication,
May 1976.
3-73
-------
4.0 BASEYEAR WINDBLOWN FUGITIVE EMISSIONS
In dry regions where large amounts of exposed earth are prevalent,
entrainment of soil particles by force of wind may contribute signifi-
cantly to total suspended particulate levels. The magnitude of windblown
dust emissions varies dramatically with climate. Subsequently, the
importance of windblown dust changes seasonally. Table 4-1 summarizes
the dust emissions levels estimated to have occurred during the baseyear
(1975). Of the five windblown dust sources investigated, only two are
of major importance. Dust blowing from the undisturbed desert and from
disturbed soils in and near the metropolitan area account for about one
fourth of the total particulate emissions estimated for 1975. Emissions
from the desert are substantial because of the vast amounts of this
source that exist around the urban areas. Windblown dust from disturbed
soil areas (vacant lots, parking lots, dirt residence yards) are sub-
stantial because of both the suspendable nature of the disaggregated
surface soils, and the vast amounts of disturbed soil surfaces through-
out the study area. Windblown dust emissions from agricultural fields
are estimated to be relatively insignificant because of the consolidated
structure of the irrigated soils and their subsequent resistance to
suspension by wind.
The seasonal variation of windblown dust levels is shown clearly
in Table 4-1. The combined effect of temperature, precipitation and
wind speed produced progressively greater forces of soil wind erosion
during each successive quarter of 1975. However, this pattern is
atypical, as the second and third quarters usually produce the conditions
causing greatest wind erosion. Also (as will be shown in Section 4.2
and later in Section 5.0), climatic conditions during 1975 were con-
ducive to levels of wind erosion approximately three times as great as
that corresponding to "typical" conditions.
The windblown dust emissions are inventoried spatially according
to the grid network described previously in Section 2.0. Figure 4-1
presents the gridded emission inventory for total windblown fugitive
dust emissions for the baseyear. Figure 4-2 is a graphical portrayal
of the emissions grid. It can be seen that dust emissions caused by
4-1
-------
TABLE 4-1. WINDBLOWN FUGITIVE DUST
IN PHOENIX STUDY AREA, TONS/DAY.
SOURCE
CATEGORY
Agricultural fields
Unpaved Roads
Undisturbed Desert
Tailings Piles
Disturbed Soil
1st
QUARTER
4.1
1.4
160
1.4
161
2nd
QUARTER
4.0
2.1
244
1.4
248
3rd
QUARTER
3.8
2.7
321
1.4
323
4th
QUARTER
4.0
3.8
450
1.4
456
ANNUAL
4.0
2.5
294
1.4
297
TOTAL 328 500 652 915 599
wind erosion are most prevalent in the northern suburbs of the metro-
politan area, where there are vast areas of undisturbed desert as well
as disturbed vacant lands.
The physical mechanisms causing entrainment of soils by wind are
not fully understood, and empirical data describing the atmospheric-
surface exchange of soil particles is relatively limited. Accordingly,
methodology now available to estimate windblown dust levels is somewhat
crude. The methodology currently in practice involves simplified versions
of the wind erosion equation, adapted to include a suspension factor
for the portion of eroded soil which is entrained. Section 4.1 describes
the general methodology of the wind erosion model employed in the esti-
mates of this study. Section 4.2 through 4.6 document the specific
assumptions and procedures utilized to generate emissions estimates for
the various sources identified in the study.
4-2
-------
Z 2 I t (Np
Z Z 2 Z 0/>
2 I/O
GRID
CODE
0
1
2
3
4
5
6
7
8
9
EMISSIONS
TONS/DAY
0.0
0.0
TO
TO
0.003 TO
0.01 TO
0.04
0.11
0.23
0.42
0.72
1.10
TO
TO
TO
TO
TO
TO
0.0
0.003
0.01
0.04
0.11
0.23
0.42
0.72
1.10
1.70
Figure 4-1. Fugitive Dust Emissions Arising from Wind Erosion,
Average Dally Emissions, 1975.
4-3
-------
Figure 4-2. Emissions of Fugitive Dust Arising
from Wind Erosion, Average Daily
Emissions, 1975.
-------
4.1 GENERAL METHODOLOGY FOR PRESENT INVENTORY
Only limited attention has been directed to the understanding of dust
suspension resulting from wind erosion of soils. In a recent literature
survey of available methods of estimating soil entrainment [1], Midwest
Research Institute concluded a most appropriate method of estimating wind
blown soil emissions would involve use of wind erosion relationships
developed by the U.S. Department of Agriculture. It was evident that the
horizontal movement of soils is caused by the same factors which affect
suspension of the soils. However, the exact mechanisms causing entrain-
ment of the soils is only recently being fully understood. The quantifi-
cation of these mechanisms (direct aerodynamic entrainment and surface
sand blasting) for application in air pollution studies will not be avail-
able in the short term. It appears the best approach at present is to
assign a suspension rate to the horizontal soil movement as determined by
the established wind erosion equations. This approach has been used
recently in studies concerning control of fugitive dust emissions.
The most relevant treatment of the wind erosion equation for the pre-
sent study is provided by the recent MRI review of fugitive dust sources [1],
This is a simplified version of the basic wind erosion equation, given by
ES = AIKCL'V
where: E = suspended particulate fraction of soil wind erosion
losses, tons/acre/year
A = portion of total wind erosion losses that would be
measured as suspended particulate
I = soil credibility, tons/acre/year
K = surface roughness factor, dimensionless
C = climatic factor, dimensionless
L1 = unsheltered field width factor, dimensionless
V = vegetative cover factor,, dimensionless.
The variable of greatest uncertainty in the adopted wind erosion
relationship is the suspension factor A. Only limited data are available
to characterize the mechansim of soil particle suspension generated by the
wind erosion of soils. Qualitatively, it is known that the suspension
4-5
-------
rate depends on the soil structure and the wind speed. Two aspects of
soil structure are important: 1) the distribution of particle sizes, and
2) the aggregate structure of the soil. Gillette [4] showed that increased
agitation of the soil disconsolidated the silt-sized soil aggregates, and
caused increased concentrations of suspended soil dust for a given wind
velocity. The undisturbed desert soil surfaces are generally composed of
silt aggregate and a thin crust of gravel and sand. This crust is easily
disaggregated. Human activities in the open desert disturb the soil con-
solidation and produce soil surface susceptible to suspension by wind.
The high credibility of these disturbed soils results in a higher fraction
of suspended particles from the mass of eroding soil. Agitation of soil
can also occur from the mechanism of wind erosion itself. Gillette
observed that the dominant mechanism of fine soil wind erosion and sus-
pension is sandblasting of the soil surface once soil movement has begun.
Soil movement begins to occur at a threshold wind speed determined by the
degree of consolidation of the soil surface. At higher wind speeds, sand-
blasting of the surface releases soil fines and a greater proportion of
the moving soil mass becomes suspended.
The traditional concern in wind erosion studies involves quantifica-
tion of soil losses, mostly for agricultural purposes. The objectives of
these studies do not concern the issue of soil suspension. Consequently,
very little empirical data has been obtained to establish the relationship
of the suspension ratio of eroded soil with wind speed and soil type. In
some of the earlier experiments, Chepil[3] estimated that 3-to-40% of
soil movement is in suspension. In a recent study, Gillette [4] measured
the vertical flux of particles (<20y) associated with a sand flux in
horizontal movement by wind erosion and found the fraction of suspended
_5
particles to vary from 2x10 to .019 depending on soil type and wind
velocity. For higher wind velocities, the Gillette experiments give a
low value for vertical particulate fluxes as only the 2 to lOpdiameter range
were measured. Since parent soils generally contain the greatest
portion of particles greater than 50u in size, the suspension fraction
may be appreciably greater than that measured, particularly when
4-6
-------
wind speeds are sufficient to support suspension of larger particles.
Gillette has shown airborne particle distributions are relatively inde-
pendent of wind speed for particles far in excess of 20u diameter [7]. Fig-
ure 4-3 shows this relationship for soil particles at several wind speeds
for particle sizes up to 30^ radius. Figure 4-4 illustrates the suspension/
settling characteristics for particles of different sizes as a function of
wind speed.
Shinn has formulated a model to estimate vertical dust flux [8]. The
model depends on parameters which should be determined for a given region,
and Shinn suggests a general index for dry nonvegetated sites similar to
that studied in the investigation. The model relates soil emissions
to frictional wind velocity as follows:
F = F
The coefficients F and y are determined by the soil surface properties,
and Shinn suggests the values are related to the soil errodibility index
accordings to the characterization of Figure 4-5. y is shown to increase
to values of 7 or 8 for soils of high errodibility. The GMX data shown
010
RADIUS (MICRONS)
Figure 4-3. Size Distributions of Aerosols
Obtained During Soil-Blowing
Wind Tunnel Experiments,
Friction Velocities were 11,
113,12,97,13,74ym/sec [7],
4-7
-------
200 r-
6 8 10 12
REFERENCE WIND SPEED (mph)
Figure 4-4. Particle Settling/Suspension Regimes [1].
4-8
-------
200 400 600 000 1000
Soil erodibitity index
Figure.4-5. The effect of Soil Errodibility Index
on Reference Dust Flux F and the Power
frof the Shinn-Gillette Dust Model [8],
in Figure 4-5 involved tests on the Nevada desert. The surface was
undisturbed desert pavement exhibiting many pebbles and a crust surface
with around 10% desert shrub cover 60 in. high. The parametrized form
of the model at the Nevada site is:
F = .73 V.
3.1
mg/m sec ton/acre/day
where V* = frictional wind velocity
Midwest Research Institute [9] has recently developed an emission
factor for wind-suspended dust based on the wind erosion equation:
where
E = .0089
esV
(PE/50)'
E = emissions of suspended dust in tons/acre/year
e = Soil credibility in tons/acre/year
s = percent silt content of surface soil
4-9
-------
f = fraction of time wind exceeds the threshold value
for wind erosion (12 mph)
V = mitigative fractional reduction in wind erosion
due to vegetative cover
PE = Thornthwaite's Precipitation-Evaporation Index.
This version assumes a constant fraction of the eroded soil is suspended,
and bases the value of the constant on data from Gillette findings. A
significant modification to the wind erosion equation concerns MRI treat-
ment of the wind speed term. In the traditional use of the wind erosion
equation, wind speed was considered in calculating the climatic factor,
entering as U in this term. In the above version, dust emissions are not
related to wind speed, except as the fraction f represents the extent of
time to which the threshold wind speed is exceeded.
PEDCO [2] compared estimates derived from wind erosion equation
applications to field test results and found fair agreement when assuming
a constant 10% suspension ratio for wind-blown soils on unpaved dirt roads.
It should be noted that PEDCO assumed a rather high errodibility index
(77 ton/acre/year) for the soil surfaces of dirt roads. This index was
based on silt measurements of the native soils of the area and is not
representative of the true errodibility of unpaved road surfaces in the
study area (see Section 3.1). For agricultural cropland soil erosion
emissions, PEDCO assumed a 2.5% suspension rate. Dust emissions calcu-
lated from the wind erosion equation were apparently in agreement with those
actually measured in the field.
Table 4-2 provides a comparison of suspension rates derived from results
of the investigations discussed above. The suspension factors have been
derived by calculating the ratio of measured suspensed dust and calculated
horizontal soil movement (based on the wind erosion equation). For the
Gillette experiments, an additional "actual" factor can be calculated, since
measurements of both horizontal and vertical, flux were performed during the
study. Excepting the estimates from the Shinn Model, the range of cal-
culated suspension factors (ratio of measured emissions to calculated wind
erosion losses) varies from .6% to 6.7%. The anomolous htgh fluxes
and suspension factors calculated from the Shinn Model apparently
4-10
-------
TABLE 4-2. FRACTION OF SOIL LOSSES SUSPENDED, AS DERIVED FROM AVAILABLE TEST RESULTS
Erosion -
Horizontal Flux
as measured(tons/
acre/year)
Soil Erosion, as
calculated from
soil erosion
equation (tons/
acre/yr.)
Vertical Flux
of soil particles
(tons/acre/yr)
Suspension
Fraction
(vertical flux/
soil erosion)
Soil Character-
ization
GILLETTE
Wind Speed
= 14 mph
1300
(Measured)
3460b
20
(measured)
.015(actual)
.006
Previously
Cultivated
cropland,
follow for
several years
and partially
covered with
grass.
ulind Speed
= 14 mph
151,000
(Measured)
2540
22
(Measured)
.0001 (Actual)
.009
Previously
cultivated
cropland
follow for
several years
SHINN GILLETTE d
/ v*\Y
~°w
Wind Speed
= 14 mph
16. la
24.7
(Calculated)
1.54
Undisturbed
desert pave-
ment
Wind Speed
= 6 mph
1.27a
1.76
(Calculated)
1.39
Undisturbed
desert pave-
ment
MR I
2
E- 00£0esv(5° )f
C * UVJOj
PE2
Average wind speed
=7.8 mph (46% of
time exceeding
6 mph)c
2.77a'd
.051
(Calculated)
.018
Undisturbed
desert pave-
ment
PEDCO
Wind Speed « 6 mph
90
6.0
(Measured/
Calculated)
.067 .025
Dirt roads Agricultural
fields
a based on soil characteristics assumed to be representative of Arizona or Nevada desert pavement.
b based on soil data reported by Gillette [4].
c these conditions correspond to meteorology observed in Phoenix during 1975.
d soil erosion loss is calculated here for the single average wind speed of 7.8 mph.
-------
reflect the interference of local fugitive sources reported to occur
[24] during the field flux measurements, and do not appear to be repre-
sentative of potential dust levels blowing off undisturbed desert pavement.
There is evidence (Gillette, Shfnn) that the suspension factor varies
inversely wtth the soil errodtbtitty tndex, dtrectly with the soil
errodibility index, and directly with wind speed [4,8]. This would sug-
gest that suspended soil losses should be estimated utilizing probability
functions for wind speed, and unique parameters associated with the soil
types. However, only inexact and tentative parametrizations (such as the
Shinn-Gillette model) are available at this time. For general applications,
it does not appear that the present state-of-art can be used to support
emission parametrizations more precisely than previous attempts. That is,
emissions should still be calculated by assuming a certain constant fraction
of the soil erosion losses (as calculated by the wind erosion equation) are
suspended. This approach, should however, reflect representative and current
data. Accordingly, the following suspension factors were proposed for use
in the present study:
Soil Surface Category Dust Suspension Factor
Croplands .025
Unpaved dirt roads .009 to .067
Undisturbed desert pavement ^018
Disturbed native soil (parking .009 to .067
lots, residence yards, excava-
tion clearnings)
The selected range of the suspension factor for unpaved dirt roads
reflects the Texas test results (Gillette), as well as, measurements con-
ducted for dirt roads in the Southwest desert areas by PEDCO. Because
the Gillette experiments were not concerned with measuring flux for
particles > 20n diameter, the suspension rate .009 is probably an under-
statement of the expected suspended soil losses. Figure 4-4 shows that
for wind speeds of 10 mph (within standard variance of average wind in
Phoenix), particles up to 40u diameter remain suspended Indefinitely.
Therefore, it would not be unexpected that total soil emissions be
4-12
-------
substantially greater than those measured for the range d < 20p . On the
other hand, evidence from numerous studies [1,9] indicate the suspension
fraction of .067 derived from PEDCO may be high. Adjustment for each
extreme of the range for the unpaved road suspension factor suggests
that a median value between .009 and .067 be used for the present inventory.
This value will be applied to other soil surfaces which experience dis-
turbance, s.uch as unpaved parking lots, private residence yards, and
cleared vacant lots.
The suspension rate corresponding to estimates of dust emissions using
the MRI model appears to be most consistent with an expected value which
would apply for wind blown dust off undisturbed desert. However, for
greater wind velocities, the calculated suspension rate of the soil erosion
losses (MRI derived vertical flux/horizontal soil movement calculated by
wind erosion equation) decreases, since the MRI model does not depend on
a power term of wind velocity as does the wind erosion equation. Since
it is not clear that the confidence associated with estimates derived
from the model is greater than that obtained with the coupling of a
suspension factor and the wind erosion equation, the latter emissions
estimating procedure was employed, and a constant suspension factor of
.018 was adopted. Section 4.4 describes this selection in further detail.
The PEDCO suspension estimate appears to be the most representative
value which may be assigned for calculation of suspended agricultural soils.
There is presently limited data available to confirm the suspension
factors selected for this study. Moreover, it is unlikely that the con-
cept of suspension factor will be appropriate as further investigations
are performed. What is needed are a series of parameterized relation-
ships directly describing the vertical flux of soil particles. In the
absence of such information, the crude assumptions identified above were
utilized as the basis for estimating the.suspendable portion of wind
erosion losses.
In contrast to the difficulty in evaluating reasonable values for the
factor A, the procedure for employing the remaining portion of the MRI
version of the wind erosion equation is well-established. The remaining
4-13
-------
parameters comprise the major elements of the basic equation which is a
result of 30 years of research to determine the primary factors that
influence erosion of soil by wind. In the following sections of this
chapter, area-specific values for the various factors are developed and
utilized to calculate wind erosion losses and suspended dust emissions.
Seasonal emissions are estimated for each square of a spatial grid network
designed to enclose a 120 km by 120 km area around the urban center of
Phoenix. The gridded emissions inventory is computerized for convenience
of emission calculations, presentation, and for expedient evaluation of
emission control alternatives later in the project.
4.2 WINDBLOWN EMISSIONS OFF UNPAVED ROADS
Two mechanisms are responsible for dust generation from unpaved
roads. First, soil particles are injected into the atmosphere by forces
of wheels and air currents from motor vehicle traffic. Second, soil
particles are injected into the atmosphere when movement of the soil by
wind action occurs. The former pick-up mechanism has been the subject of
considerable interest in most fugitive dust studies, while wind-blown
dust from unpaved roads has seldom been addressed. Depending on soil
type, meteorology, and vehicle traffic, fugitive dust emissions fromwind
erosion of unpaved roads may be a significant cause of suspended particu-
late levels.
Review of Previous Inventories
Of those studies reviewed by MRI, only the PEDCO investigation has
included an estimate of dust emissions arising from wind erosion on
unpaved roads. In that study, wind-blown dust was assessed to contribute
about 42% of all dust suspended from unpaved roads. Emission values were
estimated by utilizing the theory of the wind erosion equation and region-
specific data for meteorology, soil, and the unpaved roads. The wind
erosion equation calculations were validated by relating 24-hour and
48-hour hi-vol field test values to a continuous line source air dif-
fusion equation with the unknown term as the emission rate. The sus-
pended wind erosion losses from unpaved roads in Phoenix was estimated to
be 3.0 tons/acre/year. Based on average traffic counts and vehicle miles
4-14
-------
traveled, PEDCO expressed the wind blown emission rate as 1.54 Ib/vehicle
mile.
Methodology for the Present Inventory
Wind-blown dust emissions from the unpaved road network were esti-
mated for each of the designated county maintenance or township areas
(described previously in Section 3.0) by assigning area specific values
to the variables of the MRI form of the wind erosion equation. Two basic
road types are considered: gravel and dirt. The configuration of each
type is assumed to be equivalent, but the soil characteristics of each type
were distinguisable by maintenance areas or townships. The following
discussion relates the procedures employed to assemble representative
values of the erosion equation parameters, as well as, total emission
estimates.
Soil errodibility of the unpaved road surfaces was determined by
relating silt content of the road surface to errodibility as shown in
Figure 4-6. The value presented represents the potential soil loss in
tons/acre/year from a wide, unsheltered, isolated field with a bare,
smooth, non-crusted surface. The silt content of the roads throughout
the study area was determined by actual measurements as described in
Section 3.1. Table 4-3 summarizes the silt content and errodibility of
roads located in the predominant soil associations in the study area.
As indicated, the silt content of soils on unpaved roads reaches an
equilibrium value substantially less than that of the native soil.
Consequently, roadway .surfaces are generally relatively resistant to
wind erosion. The data of Table 4-3 and a general soil map [6] were em-
ployed to assign a representative errodibility value to the unpaved
roads in each of the roadway maintenance or township areas. The unit
of spatial resolution (maintenance and township areas) was selected
based on the format in which roadway data was available (see Section 3.1).
The surface roughness factor K for dirt roads was assumed to be
1.0. It is not expected that the limited number of ridges worn in dirt
roads would affect the value of K significantly..
4-15
-------
S-
>*>
o
C/l
£Z
O
-o
o
s_
o
oo
teo
-160
: ico
Percentage of Dry Soil Aggregates Greater than 84y Diameter
Figure 4-6. Soil Erodibility as a Function of Particle Size [1]
4-16
-------
TABLE 4-3. ERRODIBILITY OF UNPAVED
ROAD SURFACES IN PHOENIX AREA.
Silt Content .
Soil Type Of Road Surface ,%D
Gilman-Estrella-
Avondale
Mohal-Contine
Ebon-Pi nai mt-Tremant
Rock Outcrop
Gravel Road
27.2
14.2
23.3
12.4
12.0
Silt Content9 of
Native Soil,%
55-80
55-80
15-45
10-30
-
trrodiaDi iity ot
Road Surface0
Tons/Acre/Yr.
8
0
5
0
0
a. Silt content is defined as the percentage (by weight) of soil particles
less than 75y in diameter.
b. Determined from field tests conducted by TRW in May 1976.
c. Determined by relating measured silt content to errodibility according
to Figure 4-6. The measured silt level (particles smaller than 75n )
was assumed to approximate closely the parameter used in Figure 4-6
to determine errodibility (% of particles smaller than 84y).
The climatic factor C was calculated to reflect seasonal variations
in temperature, precipitation, and average wind speeds for the Phoenix
area. While it is recognized that the wind erosion equation has been
derived for annual averages, it is also evident that seasonal variations
in meteorology will affect wind erosion in the short-term. This effect
was accounted for by calculating "seasonal climatic factors" and inserting
these values in the wind erosion equation to forecast seasonal wind
erosion levels. Table 4-4 summarizes the tabulation of seasonal factors
for 1975 and for long-term historical meteorology for the area. The
differences between factors in 1975 and those based on annual average
climate are due to the transient moisture content of the soil and the
changing magnitude of wind speed. Soil moisture content is determined
by the cumulative balance between precipitation and evaporation. The
Thornthwaite Precipitation Evaporation Index (PE Index) was formulated to
express this net moisture exchange between soil and atmosphere. The index
is a measure of cumulative moisture balance over the past 12 month period.
Table 4-4 shows that moisture content in the Phoenix area was highly
variable during 1975 as low rainfall and high temperature caused the
4-17
-------
PE Index to diminish from 8.8 in the first quarter to 5.3 in the last
quarter. Average wind speeds were also greater than the historical aver-
ages for each of the seasons in 1975. These factors contributed to an
unusual seasonal pattern for the climatic factor C, as well as, values of
C which were appreciably higher than usual historical levels.
Table 4-4. Seasonal Climatic Factor, C, in Phoenix
Area for 1975 and Historical Long-Term
Averages
Period
1975
1st qtr.
2nd qtr.
3rd qtr.
4th qtr.
Historical
Averages
1st qtr.
2nd qtr.
3rd qtr.
4th qtr.
Quarterly
PE Average*
8.8
8.8
7.7
5.3
9.4
9.4
9,4
9.4
/
Average Wind
Speed, w
(mph)
7.2
8.4
8.3
7.3
5.6
6.7
6.5
5.2
C = .345 %-
(PE)2
1.7
2.6
3.4
4.8
0.7
1.2
1.1
0.6
a. PE = Thornthwaite's Precipitation Evaporation Index (see
Table 4-5).
4-18
-------
Table 4-5. 1975 Prectpttation Evaporation Index for Phoenix Area
Month
1
2
3
4
5
6
7
8
9
10
11
12
P1974
.02
1.37
.01
.00
.00
.84
1.15
1.07
2.12
.44
.59
*1974
56.7
64.5
70.6
80.2
92.2
92.4
91.2
87.2
75.9
61.5
50.6
P.
6 1974
0.0
0.2
0.0
0.0
0.0
0.1
0.1
0.1
0.3
0.1
0.1
P1975
.02
.33
.63
.43
.00
.00
.38
.00
.82
.23
.55
1.12
^975
52.3
54.0
59.0
62.6
76.7
86.6
94.3
91.9
86.2
72.9
60.9
54.8
P_
6 1975
0.0
0.1
0.1
0.1
0.0
0.0
0.1
0.0
0.1
0.1
0.1
0.2
(PE)1975
8.8
9.3
8.3
8.8
8.8
8.8
8.4
7.4
7.2
4.9
5.1
5.9
1975
Quarterly PE
Average
)
/8.8
8.8
7.7
)
5.3
I
<£>
Notes:
10
12 p
2. PE = lOJE-iOn
3. PE historical = 9.4
where p - monthly rainfall in inches, t = temperature in °F.
p
is precipitation evaporation ratio.
where PE = Thornthwaite Precipitation Evaporation Index.
-------
The unsheltered distance factor for a given road surface in the
prevailing wind direction varies continually. To assess an average effec-
tive distance factor, it was assumed that in the long-term, wind direction
is equally distributed for all roads. Any error attributable to this
assumption would be minimized by the more probable assumption that unpaved
dirt roadways are equally distributed in terms of direction. For example,
when the prevailing wind traverses north-south roadways at a 10° angle,
it must in turn traverse all the east/west roads at an 80° angle. The net
effect is to balance the various cases of wind directions oblique to the
road. Figure 4-7 shows the effect of wind direction to unsheltered road
distance for an average unpaved road in the Phoenix area. Figure 4-8
relates the unsheltered distances to the unsheltered distance factor L'.
L1 is related to the distance in which maximum soil movement is reached,
and varies with soil credibility. For an equally distributed wind
direction, the average value of L for road surfaces of specified
credibility IK, are shown in Table 4-6. It is evident that L1 varies
only slightly for the range of soil surfaces to be considered in the
Phoenix area.
Table 4-6. Unsheltered Road Distance Factor L1
IK
10
40
60
L1 at Different Prevailing Wind Directions
e = 90°
.01
.05
.08
e = 60°
.01
.06
.09
e = 30°
.01
.07
.10
e = 0°
1.00
1.00
1.00
Average L'
.26
.29
.32
4-20
-------
§
oo
o
a:
o
< K»
£ "»LC
_ CSJh-
Q JW
O
LU
Qi
140
120
100-
80-
60
40
20
Road
Width
Dlrectior
15°
30° 45° 60° 75°
ANGLE OF WIND WITH ROAD (8)
90C
Figure 4-7. Effect of Wind Direction on Unsheltered Road Distance
4-21
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1000 2000 3000 400C 5000 6000
L = UNSHELTERED DISTANCE ALONG PREVAILING WIND DIRECTION. FEET
100 . 150 200 250 300 , 350 400
I UNSHELTERED DISTANCE ALONG PREVAILING WIND DIRECTION, FEET
Figure 4-8. Effect of Unsheltered Field Length on Relative Emission Rate [1]
4-22
-------
Emission Estimates
Estimates of suspended dust arising from wind over unpaved dirt roads
were calculated by assigning specific values discussed previously to the
parameters of the wind erosion equation. A suspension factor of .038 was
applied to approximate the suspended portion of the wind erosion soil
losses. Table 4-7 summarizes the overall computation procedure. The emis-
sions are computed on a seasonal basis to reflect the significance of
differences in the climate.
Figure 4-9 illustrates the gridded emission inventory for windblown
fugitive particulate emissions off unpaved roads. The magnitude of
emissions for each of the 2 km grid squares is given by a single digit
number representing an emissions regime as shown by the accompanying grid
legend. As indicated, the magnitude of windblown dust from unpaved roads
is relatively insignificant. An emissions grid was developed for each of
the seasons, and demonstrated the following variation for 1975:
Quarter tons/day
1 1.4
2 2.1
3 2.7
4 3.8
Average 2.5
It should be remembered that the seasonal variation of climate in 1975 was
appreciably different than the historical average, and that any given year
is likely to show a unique variation in windblown roadway emission levels.
Also, because windblown emissions are related to the cube of wind speed,
it is evident that short term wind blown dust levels may exceed the amount
shown above by several times during gusty winds.
The distribution of emissions resulting from windblown roadway dust
is illustrated graphically in Figure4-10. As expected, the areas generat-
ing the greatest levels of roadway dust are in the immediate neighborhood
surrounding urban Phoenix, as well as in the surburban and remote areas
to the northwest and south. The distribution remains unchanged by season,
since climate has been assumed homogeneous over the entire study area. It
should be clear however, that short term spatial variations in climatology
would affect the distribution of Figure 4-9 significantly.
4-23
-------
Table 4-7. Wind-Blown Fugitive Emissions Off Unpaved Roads in the Phoenix Area, 1975
Specific Area
(Maintenance
area or
township)
D, Miles of
Dirt Roads
a
Basic Erodibility,
I, of Soil, (ton/
acre/year)
b
Unsheltered
Distance
Factor, L1
c
Emissions = AIKCL'V'( D )(. 00828) tons/day
1st
Quarter
E=.00543IL'D
d
2nd
Quarter
E=.000912IL'D
d
3rd
Quarter
E=.0015IL'D
d
4th
Quarter
E=.0015IL'D
d
-p>
ro
a See discussion of Section 3.1.2.
b Derived from soil silt content and Figure 4-6.
c Determined from Table 4-6.
d Computed from the wind erosion equation and the suspension factor .038. K = 1, V
factor C is calculated for each season (Table 4-4).
= 1, and the climatic
-------
GRID
CODE
0
1
2
3
4
5
6
7
8
9
EMISSIONS
TONS/DAY
0
0
.00001
.00007
.00021
.00052
.0010
.0019
.0034
.0055
to 0
to .00001
to .00007
to .00021
to .00052
to .0010
to .0019
to .0034
to .0055
to .0083
Figure 4-9. Participate Emissions Grid for Wind Blown Dust off Unpaved
Roads, Fourth Quarter, 1975.
4-25
-------
I
ro
CTt
Figure 4-10. Wind Blown Fugitive Particulate Emissions
from Unpaved Roads, Fourth Quarter, Daily
Average, 1975.
-------
The particle size distribution of the suspended dust was approximated
based on two considerations. The first is Gillete's finding [7] that sus-
pended aerosol distributions approximate the particle size distribution
of the parent soil and are independent of wind speed for particle dia-
meters 2Qu or less. Second is the assumption that at average wind speed
7.8 mph (1975 Phoenix average), particles greater than 30y will not be
suspended or will settle quickly (see Figure 4-4). Table 4-8 shows the
average distribution of particle sizes estimated for windblown dust from
unpaved roads.
TABLE 4-8. Particle Size Distribution of Suspended Soil Losses from
Unpaved Roads (1975)
Particle
Size Range
(diameter)
< 2y
2y to 20y
20u to 30u
Percentage
in
native
soil9
6%
15%
7%
of Soil Particles by
in suspended
soil losses
21%
54%
25%
weight
While it was shown that the silt content of unpaved
road surfaces was unlike that of the native soils,
no specific data was available to define the distri-
bution among those particles assumed suspendable by
wind (0 to 3Q}. It was assumed that the weight dis-
tribution of the suspendable particles could be
approximated closely by the relative distribution
of these particles in the native soil. The native
soil was considered to consist of two predominant
soil types (see Section 3.6).
4-27
-------
4.3 WINDBLOWN EMISSIONS OFF AGRICULTURAL FIELDS
Except for the region to the horth and Northeast, the Metropolitan
Phoenix Area is surrounded by agricultural croplands. These lands comprise
an estimated 1450 square miles including a portion of Final Colony in the
project study area. Soils of these; lands are variable, and range in silt
content (<75y) from about 20 to 70%. Mechanical disturbance of these soils
through agricultural activities contributes to the disaggregation of the
soils, tending to make them more susceptible to drifting by wind. In
addition, dry climate and high temperatures contribute substantially to
soil errodibility. The suspension of soil particles during periods of
maximum soil erosion may cause significant impact on particulate levels
throughout the Metropolitan Phoenix Area. The following discussion
provides a review of previous wind blown agricultural emissions, a des-
cription of the methodology utilized for the present emission inventory,
and a summary of agricultural emissions estimates derived for this study.
Review of Previous Inventories
Only the PEDCo investigation has considered wind blown soil emissions
from agricultural fields. In that study dust emissions from agricultural
fields were estimated by employing the wind erosion equation. A 2.5%
suspension of the soil erosion losses was assumed. These calculated dust
emission rates were compared to rates calculated by solution of Pasquill-
Gifford diffusion equations (ground level sources with no effective plume
rise) using measured particulate concentrations in agricultural fields.
Based on the final report [2], it is unclear if results of these approaches
were consistent. However, because the wind erosion equation approach
accounts for a variety of different crop situations, the equation was
employed by PEDCo to estimate 1970 agricultural emission sources in the
Phoenix area. Crop data was obtained to assess the specific emission
totals associated with the various major crop type.
A specific limitation of the previous study was the climatic factor due
to seasonal and historical variations, and irrigation practices. Irrigation
results in maintenance of soil moisture, and the consolidation of the soil.
Depending on the crop, irrigation requirements vary from about 25 inches of
equivalent rainfall to 74 inches. This irrigation exerts a substantial
effect on the year-long aggregation of agricultural soils. The irrigation
4-28
-------
moisture for the various crop is reflected dramatically by the corresponding
value of the climatic factors. The factors are several times less than that
for non-irrigated lands experiencing only the native moisture levels
(as will be shown in following sections). Therefore, neglecting the
effect of irrigation on agricultural soil losses has probably resulted in
emission estimates which were substantially overstated in the previous
inventory.
The variation of wind speed is another important determinant to the
year-long or seasonal levels of soil wind erosion losses. Area-specific
wind speeds occuring in the baseyear for the study should be used to esti-
mate specific emission levels for that year. Long-term historical averages
which are only region-specific are not represent!ve of base year emissions,
and limit the credibility of source=receptor relationships which employ base-
year air quality data for calibration.
Methodology of the Present Inventory
Wind blown dust emissions from agricultural fields were estimated by
assigning area specific values to the variables of the MRI form of the
wind erosion equation (Section 4.2)., Except for the potential soil
errodibility I, the emission determinants depend on crop type. In the
process of the development of the wind erosion equation, the U.S. Depart-
ment of Agriculture has assembled sufficient data to parameterize soil
surface preparations and agricultural practices for various crops. These
data will be employed to estimate crop specific soil losses in each town-
ship of the study area.
An average value for the soil errodibility I, was determined for the
agricultural area of each township of the study area. Soil silt measure-
ments by the U.S. Department of Agriculture [5] were related to soil types
identified on general soil maps [6]. Agricultural regions were then located
on the soil maps with the use of aerial photographs [10]. An average silt
content was estimated for cropland within each township by weighting
township cropland acreage and corresponding soil silt levels. Average
errodibility of the croplands was then determined by the silt content/
errodibility relationship shown in Figure 4-6 (the fraction of soil particles
<.84y was assumed to approximate that fraction <.75y as available from
USDA silt measurements [5]). The soil errodibility was found to vary from
4-29
-------
2 to 55 tons/acre-year among the townships. This variation is substantial
and would cause significant local variations in windblown dust levels from
agricultural fields.
Values for the soil surface roughness factor K, the unsheltered field
length L, and the vegative cover, are relatively uniform for a specific
crop. The surface roughness factor accounts for resistance to wind erosion
due to ridges or clods in the field. An optimal ratio of ridge heights to
ridge spacing w;ill reduce soil erosion by a factor of .5. Table 4-9 shows
typical roughness factors associated with soil preparation for various
crops.
Average field sizes for relatively flat terrain devoid of tall natural
vegetation have been established for various crops as shown in Table 4-9.
Soil losses from wind erosion accross a field vary from the windward edge
of the field and increase proportionately with length until a terminal rate
of soil movement is attained. The distance required before attaining
maximum erosion rate is influenced by the potential errodibility (I) and
roughness (K) of the soil. The relationship between the unsheltered field
length (L), the surface erosion potential IK, and the field length factor
L1 is shown in Figure 4-8.
The amount of vegative cover residue left on a field after the growing
season varies appreciably by crop (Table 4-9). Cover residue reduces soil
wind erosion losses by the factor V as shown in Figure 4-11. The degree
of reduction attainable with crop residue is related to the value of
IKCL'.
Five major crops comprised about 94% of all agricultural land use in
1975. Table 4-10shows the extent of acreage used for each of the crops.
During the growing season, wind erosion losses from soil under these
crops is assumed to be negligible except for lands growing cotton. Cotton
provides only minimal cover for the land leaving the soil susceptible to
erosion throughout the year. Alphalfa on the other hand, provides sufficient
cover during and after the growing season to deter soil erosion to negli-
gible levels.
4-30
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TABLE 4-9. VALUES OF K, L AND V FOR COMMON FIELD CROPS [1]
Crop
Alfalfa
Barley
Beans
Corn
Cotton
Grain Hays
Oats
Peanuts
Potatoes
Rice
Rye
Saf flower
Sorghum
Soybeans
Sugar Beets
Vegetables
Wheat
K
1.0
0.6
0.5
0.6
0.5
0.8
0.8
0.6
0.8
0.8
0.6
1.0
0.5
0.6
0.6
0.6
0.6
L,ft.
1000
2000
1000
2000
2000
2000
2000
1000
1000
1000
2000
2000
2000
2000
1000
500
2000
V,lb/acre
3000
1100
250
500
250
1250
1250
250
400
1000
1250
1500
900
250
100
100
1350
4-31
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I
CO
ro
Figure 4-11, Effect of Vegetative Cover on Relative Emission Rate [1],
-------
TABLE 4-10. MAJOR CROPS IN PHOENIX STUDY ARF.A
CROP TYPE AREAS OF CROPLAND* PERCENTAGE OF
TOTAL CROPLAND
Cotton
Alphafa and Hays
Barley
Sorghum
Wheat
Other
TOTAL
296,000
125,100
85,500
45,650
128,600
45,350
726,350
40.7
17.2
11.8
6.3
17.7
6.2
:* Reference [10] and [11].
Typical crop parameters (Table 4-9) were assigned to the five major
crops grown in the study area. Since there were no apparent patterns
involving crop spatial distribution, the study area crop distribution by
township was assumed to be constant for both the Pinal and Maricopa County
portions of the study area.
The climatic factor C, was calculated to reflect seasonal variations in
temperature, soil moisture (including precipitation and irrigation effects)
and average wind speeds for the study area in the 1975 baseyear. Considera-
tion for these specific variations has obvious implications for the soil
erosion estimates. Values of C are unique for the study region, and vary
significantly by season and crop type. Values of C for the study area by
season were derived in Section 4.2. To calculate wind blown soil losses
from agriculture fields, these values were adjusted to reflect additional
soil moisture provided by crop irrigation.
Figure4-12 illustrates approximate water use requirements for cotton
crops in the study area. A total of 41 inches of water is provided during
the growing season on a schedule peaking in August. Additional water
(about 20 inches) is supplied for other reasons than consumptive use by the
4-33
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crop (for leaching salts, softening a crust, moving fertilizers into soil,
compensation for runoff losses, etc.)- The effect which these irrigation
waters exert on soil moisture, and the manner in which this may be related
to the precipitation evaporations is not clear. Surely irrigation water
on cropland soils will not produce as great an effect on the soil moisture
as an equivalent amount would on soil supporting less vegetation. Consumptive
use of the water by plants will account for much of the water use. Also,
the irrigation schedule applies to the growing season, not the period when
the soil is most susceptible to wind erosion. On the other hand, periodic
irrigation during the growing season does maintain the soil moisture and
aggregated state of the soil. The effects of the irrigation are significant
in the non-growing season, when disconsolidation of the soil and exposure to
winds would reduce resistance to soil erosion. In the absence of available
guidelines, it was assumed for the purposes of this study that irrigation
water use could be related to soil moisture in the same manner as rainfall
in the precipitation evaporation index. However, only the minimal crop water
use, as shown in Figure 4-12 was incorporated to calculate the adjusted PE
values.
Based on area-specific irrigation schedules for the five major crops,
and monthly precipitation and temperature data, a PE index was calculated
for each crop. The PE values were then combined with 1975 quarterly
average wind speeds to calculate quarterly climatic factors for each crop.
The results of these calculations are shown in Table 4-11.
TABLE 4-11. CROP-SPECIFIC CLIMATIC FACTORS
CROP
Cotton
Alphalfa
Barley
Sorghum
Wheat
PE INDEX
58.0
113
52.8
40.2
54.9
AVERAGE CLIMATIC FACTOR
1st
quarter
.04
.01
.05
.08
.04
2nd
quarter.
.06
.02
.07
.13
.07
3rd
quarter
.06
.02
.07
.12
.07
4th
quarter
.04
.01
.05
.08
.04
4-34
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SEASONAL
SOIL MOISTURE DEPLETION
o
Q
1
cj
c
04
0.3
0-1
£ 3-4
a
«
Q 4-5
5-6
16.0"
(39%)
8.2
(20%)
3 0.2
Q.
E
3
in
3 o.i
6.6" | (16%)
SIT1") (12%)
2.9" (7%)
.5" (6%)
First blossom
Last blossoms that
usually mature
SEASONAL USE 41.2 "
SEMIMONTHLY USE IN INCHES
Figure 4-12. Mean Consumptive Use of Water
by Cotton at Mesa, Arizona, 1954-1962 [12].
4-35
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Emission Estimates
Estimates of suspended dust arising from soil wind erosion losses were
calculated based on assignment of wind erosion equation parameters as specified
previously. A suspension factor of .025 was employed to approximate the
suspended portion of the soil losses. Table 4-12 - summarizes the overall
computation procedure. The calculations were computerized for convenience in
dealing with the numerous townships containing agricultural fields. Values
of the errodibility index I, the unsheltered field length factor L1, and
the vegative factor V were extracted from the curves of Figure 4-6, 4-8,
and 4-11 through a software interpolation program.
Figure 4-13 illustrates the gridded emission Inventory for fugitive
wind blown emissions over agricultural lands in the first quarter of 1975.
The magnitude of emissions for each of the 2 km grid squares is represented
by a emissions regime rank number as defined by the grid legend. Such an
emission grid was developed for each of the seasons. The variation in
seasonal emission levels is summarized below:
QUARTER TONS/DAY
1 4.1
2 4.0
3 3.8
4 4.0
Average 4.0
The variation is less significant than might be expected due to the fact
that the cotton crop, which is assumed susceptible to wind erosion through-
out the year, dominates the emissions total.
The distribution of emissions arising over agricultural lands is
illustrated graphically in Figure 4-14. The substantial portion of the wind
blown emissions originate southeast of Phoenix. The prevailing direction
of gusty winds (during the thunderstorm season) is also from the southeast.
Since windblown emissions increase with the third power of wind velocity,
it appears that agricultural wind blown soil dust could exert a significant
impact on dust levels in Phoenix during windy conditions. The distribution
represented in Figure 4-14 remains relatively constant by season, since it has
4-36
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TABLE 4-12. COMPUTATIONAL PROCEDURE FOR ESTIMATION OF FUGITIVE DUST
FROM WIND EROSION OF CROPLANDS IN FIRST QUARTER6.
E = .025 GIK^L'V'f
-F»
-J
TOWNSHIP CROP TYPE
Cotton
Barley
Sorghum
Alphafa
Wheat
a. Values
b. L1 is
c. V is
d. The pe
G I K
ACRES OF SOIL ERRODIBILITY SURFACE ROUGH-
CROPLAND (tons/acre-yr) NESS FACTOR
a. .5
-
-
-
-
.6
.5
1.0
.6
of I are determined from silt content and Figure
Cl
CLIMATIC FACTOR
FOR 1st QUARTER
.04
.05
.08
.01
.04
5-3.
L L1 V V f
UNSHELTERED LENGTH VEGETATIVE VEGETA- FRACTION OF YEAR
LENGTH (ft) FACTOR RESIDUE TIVE FOR WHICH SOIL IS A
(Ib/acre) FACTOR EXPOSED IN QUARTER
TOTAL EMISSIONS
Tons/Quarter
2000 b. 250 c. 3/12
2000
200
1000
2000
1100
900
3000
1350
0
3/12
0
0
-
-
-
-
determined from IK and Figure 4-8.
determined from ICCL' and Figure 4-11.
riod of soil exposure is equivalent to non-grow1nc
season for grain
crops ,
and assumed to exist throughout the year for cotton crops due to limited soil
cover provided by cotton vegetation. The exposure periods are:
- cotton, throughout the year
- barley, May to Decmeber
- sorghum, November to July
- alphalfa, no period
- wheat, May to December
To calculate emissions for remaining quarters of 1975, the procedure
above 1s repeated using appropriate values for c and f.
-------
GRID
CODE
0
1
2
3
4
5
6
7
EMISSIONS
TONS/DAY
.00000 TO
.00000 TO
.00002 TO
.00009 TO
.0003
.0007
.0015
.0028
.0048
.0078
.00000
.00002
.00009
.0003
.0007
.0015
.0028
.0048
.0078
.012
Figure 4-13.
Particulate Emissions Grid for Wind Blown Dust off
Agricultural Fields, Third Quarter, 1975.
4-38
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I
CO
UD
Figure 4-14. Windblown Dust From Agricultural
Fields, Third Quarter, Daily Average, 1975.
-------
been assumed that the relative proportion of crop types is constant by
township for the two contained areas of Maricopa County and Final County
(only the relative emission level between Pinal and Maricopa varies).
The particle size distribution of the suspended dust was approximated
based on two considerations. The first is Gillette's finding [7] that
suspended aerosol distributions approximate the particle size distribution
of the parent soil and are independent of wind speed for particle diameters
2Cu or less. Second is the assumption that at wind speed 7.8 mph (Phoenix
1975 average), particles greater than 30 micron diameter will not be sus-
pended or will settle quickly (see Figure 4-4). Table 4-13 shows the
average distribution of particle size estimated for windblown dust off
agricultural fields.
TABLE 4-13. PARTICLE SIZE DISTRIBUTION OF SUSPENDED
SOIL LOSSES FROM AGRICULTURAL FIELDS (1975)
PARTICLE SIZE ' PERCENTAGES SOIL PARTICLES BY WEIGHT
RANGE (DIAMETER)
IN PARENT SOIL3' IN SUSPENDED SOIL LOSSES
<2 6% 21%
2y to 20u 15% 54%
20u to 30U 7% 25%
a. The average soil particle size distribution was determined by averaging
the two predominant soil types in Maricopa County (see Section 3.6).
4-40
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4.4 WIND BLOWN EMISSIONS OFF UNDISTURBED DESERT
Approximately 30% (1650 square miles) of the study area is comprised
of undisturbed desert pavement. Most of this land is concentrated to the
north and south of Phoenix. The soil surface of undisturbed desert dis-
plays a crusty surface including many pebbles, and generally supports a
variety of desert scrub, creosote, and cactus. The crust of the desert
pavement is relatively resistant to wind erosion, although this resistance
may vary significantly during the year. Exposure of the crust to the
sandblasting effect caused by winds tends to disturb the consolidation
of the surface, while precipitation tends to restore the crust. Only
very limited attention has been directed to the understanding of this
behavior. Consequently, the methodology established in the following
sections for the estimation of wind blown soil from the desert floor
is subject to appreciable uncertainty.
Review of Previous Emission Inventories
None of the previous emission inventories developed for the Phoenix
area have included an estimate of fugitive dust loadings off the un-
disturbed desert. The basis of this omission in previous work is not
clear. It was probably considered that fugitive dust arising from the
stable desert pavement would not be a significant contributor to dust
levels. This assumption is undoubtedly correct for periods of low wind
speeds. However, as shown in the air quality review of this project
[13], increasing wind speeds result in high levels of suspended part-
iculates in environments adjacent to appreciable segments of undisturbed
desert. Because of the broad expanses of land comprising this fugitive
source, it is appropriate to address the significance of its emission
strength.
Methodology for Present Inventory
The most apparent relevant study characterizing fugitive dust emis-
sions from undisturbed desert is described by Shinn [8]. The Shinn model,
discussed in Section 4.1, describes vertical flux of soil particles
4-41
-------
from a desert pavement as a function of wind velocity. The model, based
on field measurements of dust loadings from desert (Nevada) very similar
to the Arizona desert, appears to express unreasonably high values of
suspended soil particles (see Table 4-2). As discussed previously, the
highest estimates may be due to the influence of local source influences
dominating the dust loadings. Another model similar to the Shinn version,
proposed by Gillette [23], expresses the vertical flux F as
F= k(*
\uthresh
= ° for u < uthresh
In this version, > > 3. The value of Y increases with silt per unit
mass content of the soil. The threshold friction velocity varies for
different soils and surface roughness ratios, but was found to be approx-
imately .6 mph (corresponding to a wind speed of about 6 mph) for the
conditions supporting derivation of the model. Unfortunately the char-
acteristics of the soils tested by Gillette were dissimilar to conditions
of the Arizona desert. The field sites were Texas agricultural fields,
exhibiting relatively high soil silt contents, while the Arizona desert
pavement demonstrates a relatively low silt content and a crusted.surface.
A third model, developed by MRI [9], combines elements of the wind erosion
equation and the Gillette findings to relate wind blown soil dust to
soil and site characteristics, and the duration of time which the
threshold wind speed is exceeded. This model is derived from a synthesis
of field data, none of which bear similarity to Arizona desert environ-
ments.
Clearly, the research is presently too narrow in scope to utilize
parametrized relationships such as the Gillette model. The MRI model
appears to yield reasonable estimates of suspended soil loadings, but
does not account for the impact of increasing velocities on vertical
flux. When compared to Gillette test data, the MRI model estimates
are consistent with the apparent pattern that the fraction of horizontal
soil flux which is suspended increases with decreasing horizontal flux.
However, at higher wind speeds, the MRI model will not conform to this
pattern. It may be plausible therefore to utilize estimates calculated
4-42
-------
by the MRI model to establish parameterization of the Gillette model at
wind speeds near the threshold value, and to employ the Gillette model
to describe soil emissions associated with the higher end of the wind
speed distribution. This approach is, however, similar to utilization
of the wind erosion equation, which also assumes a third power term of
wind velocity. Because it is at present unclear which of these approaches
would yield best results, it was concluded that estimations of wind blown
desert soil would be derived employing the wind erosion equation (in
combination with a suspension factor). This approach is consistent with
those estimations derived for other fugitive source categories (i.e.,
wind blown dust off unpaved roads) identified in the study.
Wind blown suspended dust off the desert pavement was estimated
by the adapted and simplified form of the wind erosion equation dis-
cussed in Section 4.1. This form, including the suspension factor of
.018, is
E = .018 IKCL'V.
The soil errodibility index (I) for typical soil of the Arizona
desert was approximated by assuming it equivalent to that of the
Nevada desert surface, which has been sampled and analyzed by Shinn
[8,15]. A sample of the surface soil indicated an average silt content
of about 30% (percentage of particles <84/i). This corresponds to an
errodibility index of 10 ton/acre/yr. A further adjustment of the
index to reflect-surface consolidation, or crust, indicates an errod-
ibility of 1.67 ton/acre/year is the appropriate effective index to
be applied in the calculations [14].
The climatic factor C was calculated to reflect seasonal variation
in temperature, precipitation, and average wind speeds for the Phoenix
area. These computations are discussed in Section 4-2 and summarized
in Table 4-4. Due to lower than normal rainfall and higher than usual
wind speeds, an unusual seasonal pattern for the climatic factor (C)
was experienced in 1975.
The unsheltered distance factor for the undisturbed desert was
assumed to approach unity since most of the desert area is subject
to uninterrupted erosion for thousands of feet. The vegetation
4-43
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cover factor was presumed to be .9. The desert surface exhibits
abundant scrub, but this growth is intermittent and actually covers
a small fraction of the desert surface. The true effect of the desert
growth on the vegetative factor is unclear, since empirical derivation
of the factor is based on agricultural crop residues, quite unlike the
desert type of growth. Selection of .9 as the vegetative cover will
insure that the fugitive emission levels are not underestimated.
The amount of desert in each township was estimated using aerial
photographs included in the Arizona Cropland Atlas [10], and a current
land use map of the study area [18]. A software program developed for the
study was employed to convert the township acreage to the grid cell net-
work utilized for spatial expression of emissions levels.
Estimates of suspended dust arising from wind over the undisturbed
desert were calculated by assigning the parameter values to the wind
erosion equation.^ The seasonal wind blown desert emissions for 1975
is presented below.
Quarter Tons/Day
1 160
2 244
3 321
4 450
average 294
Figure 4-15 illustrates the gridded emission inventory for wind
blown fugitive desert dust. It is important to note that windblown
emissions may exceed the amounts shown above by several times during
gusty winds. The distribution of the desert soil emissions is illus-
trated in Figure 4-16. The desert areas generate large area sources
of dust surrounding the Phoenix area, particularly to the north and
south.
The particle size distribution of the suspended desert dust was
approximated by assuming it to be equivalent to that of the parent
soil for particle sizes 30>u diameter or less. Disintegration of
the soil aggregates by increased sandblasting of the surface causes
the soil particles to exhibit the same aerosol distribution as if they
had originally risen from a disturbed desert surface. Based on the
4-44
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GRID
CODE
0
1
2
3
4
5
6
7
8
9
EMISSIONS
TONS/DAY
0
0
.001
.004
.01
.03
.06
.12
.20
.32
to 0
to .001
to .004
to .01
to .03
to .06
to .12
to .20
to .32
to .49
Figure 4-15.
Emissions Grid Map for Fugitive Dust Emissions Arising
from Wind Erosion of Undisturbed Desert in Phoenix
Area, First Quarter, 1975.
4-45
-------
I
Figure 4-16. Participate Fugitive Emissions Arising from Wind Erosion of Undisturbed
Desert in Phoenix Area, First Quarter, Daily Average, 1975.
-------
1975 average wind speed of 7.8 mph, the suspendable portion of the
injected particles will be less than 30 ju in diameter. The expected
aerosol distribution for d < 30 ju was approximated from parent soil
data (see Section 3-6) as follows:
< 2y 21%
2-20u 54%
20-30u 25%
4.5 TAILINGS PILES
Tailings piles consist of deposits of earth removed during mining
operations. For large mines, the tailing piles may expand over several
thousand acres. Generally the piles are composed of substantial pro-
portions of fines which are relatively susceptible to significant wind
erosion losses. Fugitive emissions from tailings piles represent a
minor source in the study area since few mining operations are conducted,
and these are located at the southern border of the study area.
Review of Previous Inventories and Emission Factors
Only limited information is available concerning soil emissions
from tailings piles. Recently, PEDCo [2] has developed an emission
factor for this fugitive source by employing the wind erosion equation.
No field testing was performed in the PEDCo analysis. Representative
characteristics were identified for tailings for use in the wind erosion
equation. The piles were described as being composed of sand and loamy
sand soils with possible fines for surface cementation. They are charac-
tized by a smooth, unridged surface and no vegetative cover. Wind
fetch-over the piles is approximately 2000 feet. Ten percent of the
soil loss estimated by the wind erosion equation is assumed to become
suspended. The emissions are seasonally related to the climatic factor,
which may vary substantially during the year (see Section 4.2). This
relationship is illustrated in Table 4-14. Total emissions are calculated
by applying the emission factor to the number of acres of tailings piles.
4-47
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TABLE 4-14. EMISSION FACTORS FOR TAILINGS PILES.
CViiudtic Factor
30
40
50
60
70
80
90
100
120
Emissions
tons/acre/year
4.0
5.3
6.6
8.0
9.5
10.5
12.2
13.3
16.0
Source: Reference [2]
Methodology of the Present Inventory
Based on the historical climatic factor for the study area (.80),
the PEDCo emission factor was determined to be 10.5 tons/acre/year. How-
ever, data was apparently unavailable to quantify the size and character-
istics of tailings piles. No useful data was available from the Arizona
State Department of Health, the Final County APCD, or the University of
Arizona Bureau of Mines. None of these agencies are at present concerned
with quantifying the sizes and locations of tailings piles. Attaining
information from the individual mines was difficult because of require-
ments to corporation confidentiality. Due to the relative insignificance
of the tailings pile sources, pursuit of the data was abandoned and emis-
sions data from a previous PEDCo inventory were utilized.
The PEDCo estimates were adjusted since PEDCo had inventoried tailings
piles in all of Pinal County (1200 acres of piles). This figure was
modified by apportioning the total acreage in proportions to the number
of employees at the major mines in Pinal County* (Table 4-15). Table
4-16 presents the tailings piles inventory for the Phoenix study area.
*It would have been more direct to base the adjustment on production
rates at the mines, but these data were available for only one mine
(from the NEDS point source listing).
4-48
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TABLE 4-15. SIZE OF MAJOR MINES IN FINAL COUNTY.
Company
ASARCO
Hecla
Magma
Location
Sacaton
Casa Grande
San Manuel
Superi or
Number of Employees
360
1150
4200
1150
Source: Reference [25]
TABLE 4-16. EMISSIONS FROM TAILINGS PILES IN PHOENIX STUDY AREA.
Company
ASARCO
Hecla
Location
Sacaton
Casa Grande
Size of Tailings
Piles (Acres)
60
204
Emission Factor
(tons/acre/yr.)
10.5
10.5
Emissions
(tons/day)
0.3
1.1
Figure 4-17 shows the gridded emissions inventory for windblown
dust from tailings piles, and Figure 4-18 illustrates graphically the
spatial distribution of the emissions. The insignificance of tailings
piles emissions for the study region air quality is heightened by the
remote location of this source.
No, data were provided by PEDCo as to particle size distributions of
the suspended tailings piles emissions. It was assumed that the
distribution could be approximated by that of emissions from aggregate
loadout operations.
Particle Size (M ) Weight Percent
<1 30
1-2 46
2-3 16
3-4 6
<4 4
4-49
-------
GRID
CODE
0
1
2
3
4
5
6
7
EMISSIONS
TONS/DAY
0 to 0
0 .002
.002 to .009
.009 to .03
.03
.07
.14
.26
.45
.72
to .07
to .14
to .26
to .45
to .72
to 1.1
Figure 4-17. Emissions Grid Map for Fugitive Dust Arising from
Wind Erosion of Tailings Piles, Daily Average, 1975.
4-50
-------
-p.
en
Figure 4-18.
Fugitive Dust Emissions Arising from Wind Erosion of
Tailings Piles, Daily Average, 1975.
-------
4.6 DISTURBED SOIL SURFACES.
There are substantial amounts of exposed earth throughout the
study area. Where the exposed earth is subject to repeated traffic or
other disturbance, the surface crust becomes disaggregated into fine
particles which are susceptible to suspension by wind. The vulnerable
soil surfaces consist of vacant lots and parking lots, and dirt residence
yards. Windblown dust from these surfaces constitutes a significant
source of suspended particulate matter, particularly during the more
windy and dry periods.
Review of Previous Emission Inventories
None of the previous emission inventories developed for the Phoenix
area have included an estimate of windblown fugitive dust emissions from
distrubed soil surfaces. Established emission factors applicable to this
source have not yet been quantitatively determined.
Methodology for Present Inventory
Estimates of suspended dust emissions from distrubed soil surfaces
were calculated based on an assignment of value to parameters of the wind
erosion model. A suspension factor equivalent to that selected as
representative of soil of unpaved roads (.038) was assumed applicable
for vacant lots, parking lots, and dirt residence yards. Since an inven-
tory of vacant land acreage was unavailable, the amount of vacant land
in each township of the study area was determined by scaling the vacant
areas indicated.on a 1973 land use map for Phoenix [18]. It was estimated
that about 71 square miles (45,200 acres) of vacant land were within the
urbanized artds of the study region. These vacant areas were considered
to be subject to regular disturbance; those vacant areas outside the
urbanized region were considered to be mainly undisturbed desert land.
The amount of exposed earth on private residences with dirt yards
was estimated for the Phoenix metropolitan area with the aid of infor-
mation provided by the City of Phoenix Planning Department. The infor-
mation consisted of a map of the 1975 Phoenix Census Tracts, including
designation of those tracts comprised primarily of residential dwellings
4-52
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having dirt yards. The designations were based on planning personnel
familiarity with the Phoenix area. A comparison of the marked census
tract map with a map of census tract median family income showed that
dirt residence yards were generally located in the economically depressed
areas. The marked census tract map was related to the map of the General
Land Use Plan for Maricopa County [17] to determine the approximate
housing density of the marked tracts. According to the map, the marked
tracts consisted of either 0-r5 or 5-15 housing units per gross acre.
The amount of exposed land was calculated assuming that 27% of the land
in the designated areas is used for streets and that 86% of the remaining
land is exposed in those tracts averaging 2 1/2 residences per acre and
and 34% is left exposed in those tracts averaging 10 residences per acre.
These assumptions were based on a special zoning district study con-
ducted by the Maricopa County Planning and Zoning Department [16]. It
was also assumed that one fourth of all residence yards in the 0 to 5
dwellings per acre tracts were landscaped with some kind of soil cover,
and that one half of the exposed area of the yards is covered or sheltered
by buildings or other obstructions. Based on the above assumptions, it
was estimated that approximately 3.2 square miles (2020 acres) of exposed
residence yards exist within the metropolitan Phoenix area.
The average unsheltered field lengths for vacant and cleared lands
was assumed to be 300 by 300 feet. Based on typical dwelling and lot
sizes of Rl zoning districts, a distance of 120 feet was selected as
the representative unsheltered length of exposed soil strips between
dwellings.
An average value for errodibility of the vacant soils was assumed
to be 60 tons/acre/year. This value reflects the average errodibility
of non-crusted native soils in Phoenix. An errodibility of 80 tons/acre/
year, which reflects the higher extreme of the normal range for native
Phoenix soils, was assigned to the highly pulverized soils characteristic
of private residence yards.
The climatic factor was calculated to reflect seasonal variations
in temperature, wind speed, and precipitation, as described in Section
4.2. Due to lower than normal rainfall and higher than usual wind speeds,
dust emissions from vacant lots and residence yards would be significantly
4-53
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greater than usual during 1975. The emissions estimates are shown below.
Figure 4-19 illustrates the gridded emissions inventory obtained.by
Quarter
1
2
3
4
Year Average
Emissions
Tons/Day
161
248
323
456
297
Emission Factor, tons/acre/year
Vacant lots
1.24
1.90
2.48
3.50
2.28
Residence yards
1.45
2.22
2.90
4.10
2.67
calculating emissions for the amount of vacant land or dirt residence
yards in each of the cells of the emission grid network. Figure 4-20
illustrates graphically the emissions distribution in the study area.
The particle size distribution of the dust emissions was approxi-
mated from parent soil data (see Section 3-6) as follows.
<2M 21%
2-20 p 54%
20-30 n 25%
4-54
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GRID
CODE
0
1
2
3
4
5
6
7
8
9
EMISSIONS
TONS/DAY
0 to 0
0 to .004
.004 to .02
.02 to .07
.07 to .17
.17 to .35
.35 to .64
.64 to 1.1
to 1.7
to 2.7
1.1
1.7
Figure 4-19.
Emissions Grid Map for Fugitive Dust Arising from Wind
Erosion of Disturbed Soil Surfaces, First Quarter, 1975.
4-55
-------
tn
en
Figure 4-20. Fugitive Dust Emissions Arising from Wind Erosion of
Disturbed Soil Surfaces, First Quarter, Daily Average, 1975.
-------
REFERENCES FOR SECTION 4.0
1. Cowherd, Chatten; Axetell, Kenneth; Midwest Research Institute,
"Development of Emission Factors for Fugitive Dust Sources,"
Prepared for U.S. Environmental Protection Agency, June 1974.
2. Jutze, George; Axetell, Kenneth, PEDCo Environmental Specialists,
Inc., "Investigation of Fugitive Dust, Volume I - Sources,
Emissions, and Control," Prepared for U.S. Environmental Pro-
tection Agency, June 1974.
3. Chepil, W.S., "Dynamics of Wind Erosion: Initiation of Soil
Movement," Soil Science, 60: 1945.
4. Gillette, Dale, National Center for Atmospheric Research,
"Production of Fine Dust by Wind Erosion of Soil: Effect on Wind
and Soil Texture," from Proceedings of a symposium at Rich!and,
Washington, September 1974, on Atmosphere-Surface Exchange of
Particulate and Gaseous Pollutants.
5. U.S. Department of Agriculture, Soil Conservation Service, "Soil
Survey - Eastern Maricopa and Northern Pinal Counties Area,
Arizona," Washington, D.C., 1974.
6. U.S. Department of Agriculture, Soil Conservation Service,
"General Soil Map, Maricopa County, Arizona," 1973.
7. Gillette, Dale; Blifford, Irving; National Center for Atmospheric
Research, "The Influence of Wind Velocity on the Size Distributions
of Aerosols Generated by the Wind Erosion of Soils," Journal of
Geophysical Research, September 20, 1974.
8. Shinn, J.H., Lawrence Livermore Laboratory, "Observations of Dust
Flux in the Surface Boundary Layer for Steady and Nonsteady Cases,"
from Proceedings of a Symposium on Atmosphere-Surface Exchange of
Particulate and Gaseous Pollutants, September 1974.
9. Midwest Research Institute, "Quantification of Dust Entrainment
from Paved Roads," Prepared for Environmental Protection Agency,
March 1976.
10. Arizona Crop and Livestock Reporting Service, "Cropland Atlas of
Arizona," Phoenix, Arizona, October 1974.
11. Arizona Crop and Livestock Reporting Service, "1974 Arizona
Agricultural Statistics," Bulletin S-10, Phoenix, Arizona, March
1975.
12. Cooperative Extension Service, University of Arizona, "Arizona
Agri-File, Cotton Water Use," July 1973.
4-57
-------
13. Richard, George; Tan, Ron; Avery, Jim, TRW Environmental Engineer-
ing Division "An Implementation Plan for Suspended Participate
Matter in the Phoenix Area, Volume I, Air Quality Analysis,"
Prepared for Environmental Protection Agency, May 1977.
14. Woodruff, N.P.; Siddoway, F.'H., Soil and Water Conservation
Research Division, U.S. Department of Agriculture, "A Wind Erosion
Equation," Kansas Department of Agronomy Contribution No. 897,
March 1965.
15. Communication with J.H. Shinn, Lawrence Livermore Laboratory,
University of California, May 1976.
16. Maricopa County Planning and Zoning Department, "Data for School
Planning," April 1973.
17. Maricopa County Planning Department, "A Report Upon Future General
Land Use for Maricopa County, Arizona," February, 1975.
18. Maricopa County Planning Department, "Generalized Existing Land
Use, Phoenix, Arizona, 1973."
4-58
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5.0 PROJECTION OF CONVENTIONAL AND FUGITIVE DUST
PARTICULATE/EMISSIONS
One of the major limitations of the previous particulate inventory was
that no projections were included. The impact of control strategies were
evaluated with respect to current (1970) emissions. If emissions increase
over time, then control strategies would not be sufficiently strict to
meet the desired levels of air quality; if emissions decreased, then the
control strategies would be too stringent. Therefore, to accurately
assess the impact of prospective control strategies, baseline emission
projections should be developed,
In addition to changes in the magnitude of emission sources, the rela-
tive significance of the various particulate sources 1s expected to change
substantially by 1980 and 1985. Fugitive dust emissions produced by human
activity (anthropogenic sources) are expected to exert a more pronounced
impact on total suspended particulate levels, while particulate emissions
from conventional sources and wind erosion of soil are estimated to dimin-
ish or remain Insignificant 1n relative Importance. The forecast of emis-
sion levels from these three emission categories are summarized below.
EMISSIONS, TONS/DAY
conventional
sources
34.8
42.2
50.6
anthropogenic
sources
1726
2121
2265
windblown
dust
599
203
148
1975
1980
1985
This chapter documents the emission projections f^r each of the
emission sources for the years 1980 and 1985. The methodology and emission
estimates for these projections are discussed 1n the following section.
5.1 PROJECTION OF EMISSIONS FOR CONVENTIONAL SOURCES
This section Includes a discussion of the methodology employed to
forecast particulate emissions levels from conventional sources. These
sources consist of motor vehicles, point sources, stationary area sources,
5-1
-------
and aircraft.
5.1.1 Motor Vehicles
Projections of vehicle miles traveled (VMT) were based upon population
projections by the Maricopa County Association of Governments [1]. These
population prelections are summarized in Table 5-1.
TABLE 5-1. POPULATION PROJECTIONS
YEAR
1975
1980
1985
POPULATION
(Millions of Residents)
1.374
1.751
2.057
GROWTH RATIO
FROM 1975
1.000
1.274
1.497
VMT
(Millions)
16.7
21.2
24.9
Because of the pending controls on automobiles it was necessary to
project emission factors also. The catalytic converter results in signifi-
cant reductions of automobile and light truck particulate emissions.
Supplement 5 of AP-42 [4] indicates that only 1975 through 1977 light duty
vehicles (LDV's) can be expected to have catalytic converters. After that,
it is probable that new control alternatives will cause a return to
previous emission levels. Therefore, post-1977 cars are assumed to have
the same emissions as pre-1975 cars. Calculations of projected emission
factors for 1980 and 1985 cars and light trucks were included in Section
2.0 (Table 2-3 and 2-4) with the baseyear calculations for convenience.
Gas and diesel heavy duty vehicle and motorcycle emissions are assumed
over the study period.
Projected emissions are based upon the projected VMT and emission
factors. The projected emission factors are calculated below:
E~ = -731 (ELDV) + -°" (ELDT} + -06 (EHDV gas) + '°6 (EHDV diesel
o
+ -049 (Emc).
5-2
-------
"1980
.731 (.45) + .099 (.48) + .06 (1.21) + .06(1.60) + .049 (.16)
,533 gm/m1le.
-1985
.731 (.51) + .099 (.52) + .06 (1.21) + .06 (1.60) + (.049 (.16)
,601 gm/mlle.
The projected emissions from motor vehicles are given 1n Table 5-2. The
emissions are portrayed 1n the gridded format 1n Figure 5-1.
TABLE 5-2. PROJECTED MOTOR VEHICLE PARTICULATE
EMISSIONS
YEAR
1975
1980
1985
EMISSIONS
(tons/day)
11.0
12.9
16.5
5.1.2 Point Sources
Projections of the. 1972 NEDS data were made by using employment data
from the.Arizona Department of Economic Security [2]. Four categories of
employment were used for projecting point sources: (1) mining, >quarrying,
and rock crushing, (2) manufacturing, (3) agriculture, and (4) utilities.
By assuming that emissions are proportional to employment activity,
projection factors were developed for each of the first three source
categories (utilities are considered separately later in the section).
Historical employment totals and projections are shown in Table
5-3 for the minerals industry and for general manufacturing. These pro-
jections were made by the Arizona Department of Economic Security, and
5-3
-------
GRID LfGENC
GRID
CODE
0
1
2
3
EMISSIONS
TONS/OAT
n.ooooo TC
,00000 TO
.0003? TO
.00160 TO
.00505 TO
.0123? TO
,0?555 TO
.0473". TO
.OP075 TG
.OOOOC
.00032
00160
00505
11232
-.555
.08075
.12935
.19715
Figure 5-1. Grid Map for Emissions from Motor Vehicles, Daily Average, 1985.
5-4
-------
will be the basis for projecting in the present inventory. These growth
factors were applied to the baseyear mineral and manufacturing emissions
levels to obtain the forecasted levels for 1975, 1980, and 1985 (the 1975
levels were used for incorporation into the baseyear inventory).
Agricultural employment and crop activity trends are shown in Tables 5-4 and
5-5. Since no employment projections are available for agriculture, pro-
jection factors were established by considering historical trends. The
data in Table 5-4 indicates a downward trend in employment with a slight
recent upswing. A similar trend can be observed in the agricultural crop
acreage shown in Table 5-5, except that recent activity levels off, and the
cropping activity pattern appears to be about two or three years ahead of
the employment data. In view of the diminishing downtrend pattern shown by
the data, it appears appropriate to assume a constant activity level for
agriculture throughout the study period. Hence, emission levels related to
agricultural processing activities were assumed to remain unchanged through
1985.
TABLE 5-3. EMPLOYMENT DATA AND PROJECTIONS
1972 1973 1974 1975 1980 1985
Mining, Quarying and
Rock Crushing
Employment 400 400 400 400 529 657
Growth From 1972 1.00 1.00 1.00 1.00 1.32 1.64
Manufacturing
Employment 74,400 82,900 . 84,200 71,100 95,900 120,700
Growth From 1972 1.00 1.11 1.13 .96 1.29 1.62
5-5
-------
TABLE 5-4. AGRICULTURAL EMPLOYMENT IN MARICOPA
COUNTY
YEAR
1970
1971
1972
1973
1974
1975
EMPLOYMENT
14,400
13,900
13,525
13,400
13,400
13,600
SOURCE: Arizona Department of Economic Security
TABLE 5-5. AGRICULTURAL CROP AREA IN MARICOPA
COUNTY
YEAR
1950
1955
1960
1965
1970
1971
1972
TOTAL CROPPED ACRES
535,000
485,000
524,000
481 ,000
463,000
443,000
443,000
SOURCE: "Arizona Agricultural" Annual Bulletin of Cooperative
Extension Service, Agricultural Experiment Station,
University of Arizona.
Beginning late in 1976 or 1977, a new foundary will be producing steel
a few miles south of Chandler [3]. Because production has not yet begun,
future emission levels for the foundry are not clear. However, with the
use of certain design parameters and a few assumptions, it was possible to
make an estimate for emissions in 1980 and 1985. The foundary will have two
electric arc furnaces each with a 15 ton capacity. By assuming that each
furnace is charged at 12 tons and 100 times per week, the operating rate be-
comes 2400 tons per week or 343 tons per day.
5-6
-------
The foundary is to install a 120,000 CFM baghouse for furnace emissions
and a baghouse for emissions collected over both the ball wheel and the
breaker barrels. It was assumed that the emission factor would be 13 Ib/ton
[typical value from AP-42] and that the baghouses would control 98% of these
emissions. The calculation of emissions is show below:
c /o/n Tons Steel \ /,o Lb Particulates\ / no\ /I Ton \
Eday = {343 DIP" ] (13 Ton Steer ('02) IflJfflTlb'
E. = .0446 Tons/Day
The foundary is located on Arizona Avenue, South of Chandler, between
the cross streets Chandler Heights Road and Riggs Road. By use of a 7-1/2
minute USGS map and a street map of the area it was determined that the
UTM coordinates are 421.8 km north and 3676.7 km south to within about
.5 km.
Projections of power plant fuel use were available from each of the
power companies. The projections are given on an annual basis for each of
the plants in the study area. The baseyear seasonal distributions have
been assumed to apply to the projections with the exception of the Santan
Plant which did not have a complete year of operating data at the time of
this study. The power company projection data was applied to the baseyear
power plant emission levels to generate seasonal forecasted power plant
emissions in 1980 and 1985. These forecasts are shown in Table 5-6. The
total projected point source emission levels for the study period are shown
below. The emissions are presented 1n the grid format in Figure 5-2.
There are significant changes 1n the emission levels 1n future years.
PROJECTED PARTICIPATES EMISSIONS FROM POINT SOURCES
1975 (Baseyear) 21.8 tons/day
1980 27.0
1985 30.8
5.1.3 Stationary Area Sources
Population growth data (see Section 3.1) were used to project space
heating emissions to 1980 and 1985. The population distribution was
assumed to be unchanged. Projected emission levels are shown in Table 5-7.
The emissions are shown 1n the grldded format 1n Figure 5-3.
5-7
-------
TABLE 5-6. PROJECTED SEASONAL POWER PLANT EMISSIONS
(Tons/Day)
Cross Cut
1980
1985
Agua Fria
1980
1985
Kyrene
1980
1985
Santan
1980
1985
Octillo
1980
1985
West Phoenix
1980
1985
TOTALS
1980
1985
JFM
0
0
0.854
0.528
0.333
0.147
0.840
0.500
0.679
0.530
0.494
0.371
3.200
2.076
AMJ
0
0
0.792
0.490
0.274
0.121
0.778
0.463
0.630
0.491
0.458
0.343
2.932
1.908
JAS
0
0
1.090
0.675
0.325
0.144
1.072
0.638
0.867
0.676
0.631
0.473
3.985
2.606
OND
0
0
0.740
0.458
0.178
0.079
0.728
0.433
0.589
0.459
0.429
0.321
2.664
1.750
ANNUAL AVERAGE
0
0
0.869
0.538
0.277
0.123
0.854
.0.508
0.691
0.539
0.503
0.377
3.194
2.085
-------
GRID
CODE
GRID LEGEND
EMISSIONS
TONS/Oir
0.00000 TO
.00000 TO
.00
-------
6RJD
CODE
GPIO LEGEND
EMISSIONS
TONS/DAY
0.00000 TO
.00000 TO
.00003 TO
.00013 TU
.00040 TO
_ -oooie TO
.00303 TO
.00376 TO
.00000
.00003
.00013
.00040
.00098
. 00*03
.0017*
.00*41
___
.01027 TO
.01565
Figure 5-3. Grid Map for Emissions from Stationary Area Sources, Dally
Average, 1985.
5-10
-------
TABLE 5-7. AREA EMISSIONS PROJECTIONS
Distillate Oil
Natural Gas
TOTAL
(Tons/Year)
(Tons/Day)
1975
(Tons/Year)
156.0
350.6
506.6
1.39
1980
(Tons/Year)
198.7
446.7
645.4
1.77
1985
(Tons/Year)
233.4
524.8
758.2
2.08
5.1.4 AIRCRAFT
Projections for 1980 and 1985 were developed by utilizing airport
growth rates from the Arizona Aviation Systems Plan [5]. These growth
rates are shown for each of the five major airports in Table 5-8. Pro-
jected activity levels for the two military airports were not available.
Activity levels there were assumed to remain constant through 1985.
Adjustment of baseyear inventory by the growth rates shown in Table 5-8
yields the forecasted aircraft emission levels (Table 5-9).
TABLE 5-8. ANNUAL OPERATIONS* AND PROJECTIONS FOR
FIVE MAJOR CIVILIAN AIRPORTS IN PHOENIX AREA
Operations (1000)
Sky Harbor
Falcon Field
Phoenix Litchfield
Scottsdale
Phoenix Dear Valley
* An operation is either
1975
328
272
214
202
164
a landing or a
1980
453
383
294
346
196
takeoff
1990
688
705
502
598
299
5-11
-------
TABLE 5-9. EMISSION ESTIMATES FOR AIRCRAFT
Emissions (Tons/Day)
en
r
ro
AIRPORT
Sky Harbor
Falcon Field
Scottsdale
Phoenix Litchfield
Phoenix Dear Valley
Williams AFB
Luke AFB
TOTAL
1975
.190
.008
.007
.004
.003
.093
.054
.359
1980
.262
.011
.012
.005
.004
.093
.054
.440
1985
.330
.016
.017
.007
.005
.093
.054
.520
i
-------
5.2 ANTHROPOGENIC SOURCES
This section discusses the methodology employed in projecting emissions
from vehicles on unpaved roads, agricultural tilling, aggregate storage piles,
cattle feedlots, off-road motor vehicles and the entrainment of fugitive
dust by motor vehicles on paved roads.
5.2.1 Motor Vehicles on Unpaved Roads
Several studies were examined in an attempt to predict future trends of
both miles of unpaved roads and traffic volumes on unpaved roads [6,7,8,9,10].
These documents, however, proved to be of no assistance, as their predictions
were based on road-functional classifications (i.e. collector and local streets,
interstate highways) and not on road surface type. An attempt was then made
to extrapolate past trends of unpaved road mileages. However, no discernable
trends were found to exist.
Ultimately, knowledgeable officials at both the county and city levels
were contacted and their expertise solicited. The following sections detailed
the information received:
(1) The Maricopa County Highway Department - the County has historically
paved approximately 50 miles of unpaved roadways per year. Three
criteria govern the selection of roads to be paved - (1) ADT, (2)
development of subdivisions and (3) accident reports from the
Sheriff's Department. Thus, no systematic pattern exists. There
is a County ordinance requiring the paving of all streets in new
County subdivisions. This ordinance, however, is not retroactive.
No new unpaved roads are expected to be created in the future due
to this ordinance.
(2) Phoenix - the city, in 1960, embarked upon a program to upgrade
all substandard streets,* with a goal of 30 miles per year in mind.
The actual trend has been closer to 18 miles per year. Most of the
unpaved roads are in existing subdivisions, with a very small por-
tion in commercial and industrial areas. No new unpaved roads are
expected to come into existence, as there is a city ordinance re-
quiring all streets in new subdivisions to be paved.
*A substandard street is one that is not paved and does not have gutters and
curbs. Thus both unpaved streets as well as paved ones without gutters and
curbs are classified as substandard. In Phoenix, only collector and local
streets are substandard.
5-13
-------
(3) Mesa - there are presently only 17 miles of unpaved streets in
Mesa. Of these, 10 miles are in subdivisions and the remaining
7 miles are arterials. The city is paving the arterials through
capital improvement programs and expects to be through by 1985.
The residential unpaved streets are improved only when the local
residents form Improvement Districts. All new subdivisions are
required to have paved streets.
(4) Scottsdale, Chandler, Glendale, Temne, Paradise Valley - the sit-
uation 1s similar in all these cities; thus they will
be discussed as a unit. Almost all unpaved roads are located in
existing subdivisions, with a very small percentage as arterials.
Residential unpaved roads are paved only through the formation
of Improvement Districts. There is no schedule to pave the art-
erial streets. All new subdivisions are required to have paved
streets.
To summarize the situation in Maricopa County, it appears that no new
(i.e. not presently existing) unpaved roads will be created in the future.
In all cities except for Phoenix, there will still be unpaved roads, of which
almost all are in existing subdivisions. These are not expected to be paved
very rapidly, as the number of miles paved through the formation of Improve-
ment Districts has been extremely low historically (on the order of 2-4 miles
in the last 10 year period). As for Phoenix, the majority of existing unpaved
streets will probably be paved by 1985.
One fact complicates the projection of mileages of unpaved roads on a
spatial basis. Phoenix and its neighboring cities have historically experienced
a rapid increase in population and can be expected to continue experiencing
this trend. County land is annexed and the cities assume responsibility for
the maintenance of all roads in the annexed land. What plans the cities may
have to pave unpaved roads in these annexed areas is unknown. As TRW's data
on the spatial distribution of unpaved roads is on a maintenance area basis,
the removal of mileages and the uncertainty as to the disposition of unpaved
roads in the annexed lands requires several assumptions to be made.
Projections for Maricopa County
In the city of Phoenix, all existing unpaved roads (121 miles) will
be paved at the rate of 11 miles/year. This figure is derived from the fact
that the rate of upgrading substandard streets in Phoenix is 18 miles/year
and 121 of the remaining 200 miles of substandard streets are unpaved [(121/200)
x (18) = 10.89 or 11]. For Mesa, 25% of the 10 miles of unpaved residential
5-14
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roads are assumed to be paved by 1980 and 50% by 1985. The remaining 7 miles
of unpaved arterial roads are expected to be paved by 1985. For 1980, it is
assumed that 3 of the 6 miles will be paved. In the remaining cities (Scotts
dale, Chandler, Tempe, Glendale and Paradise Valley), all existing unpaved
streets will be assumed to be paved (through the formation of Improvement
Districts) at the following rate - 25% of the total unpaved mileage to be
paved by 1980 and 50% of the total by 1985. (This strategy assumes that all
unpaved roads in the remaining cities are in residential areas. This 1s a
plausible assumption, as the majority of the unpaved roads are 1n resi-
dential areas).
To estimate the future distribution of unpaved road mileages, the
following procedure was employed:
(1) Figure 5-4 illustrates the urbanized areas in Maricopa County
in 1985. By overlaying a map showing the present boundaries
of urbanization, the locations of future growth were deter-
mined.
(2) A second overlay depicting the Highway Department maintenance
areas was then utilized to determine the expansion of urbani-
zation into each maintenance area.
(3) A third overlay with the network of all road types* was also
placed over Figure 5-4 and the first two overlays to obtain:
a. The mileages of a1J_ road types in a maintenance area.
b. The mileages of all road types in the urbanized portion
of a maintenance area.
(4) To determine the mileage of unpaved roads in the urbanized
portion of a maintenance area, the following procedures was
implemented:
a. Calculate the percentage:
C =
p ~
= Miles of all road types in the urbanized area of a maintenance area
~ Miles of all road types in the maintenance area
b. Multiply Cp times the miles of unpaved roads in the
maintenance area (given in Table 4-11) to obtain the
miles of unpaved roads in the urbanized portion of the
maintenance area.
*This overlay was adopted from road maps provided by the Arizona Department
of Transportation. Although they do not illustrate all road types in the
County, these maps were the best available for spatial distribution.
5-15
-------
en
L E G E N D
EXISTING OR POTENTIAL URBANIZED AREAS
AGRICULTURE
MAJOR PARKS AND OTHER OPEN SPACE AREAS
AIRPORTS AND MILITARY RESERVATIONS
DESERT OR MOUNTAIN AREAS
FREEWAY
MAJOR HIGHWAY
SCENIC HIGHWAY
HIKING AND RIDING TRAIL
MAJOR WATERWAY
FLOOD CONTROL STRUCTURE
Figure 5-4. Future General Land Use,
Maricopa County, Arizona [15].
-------
(5) As an example of Steps (1) through (4), consider maintenance area
I-F. From Steps (1), (2) and (3), 1t was determined that 38% of
all the roads 1n I-F would fall Into urbanized portions by 1985.
From Table 3-4, plus the assumption 40% of all county maintained
unpaved roads are gravel, the total miles of unpaved roads 1n I-F
is 137 (93 dirt miles and 44 gravel miles). Thus (.38) x (93 miles)
= 35 miles of dirt and (.38) x (44) = 17 miles of gravel roads are
allocated to the urbanized section of Area I-F 1n 1985.
(6) This methodology is performed for each maintenance area subject
to urbanization and the results can be seen in Table 5-10.
(7) All mileages of dirt and gravel roads determined in Steps (1) -
(6) are assumed to be paved by 1985. .
(8) Since it is assumed that the Highway Department paves 50 miles
of road/year, it is expected that 500 miles of paving will occur
from 1975 to 1985. Steps (1) - (6) account for only 372 of these
miles (see Table 5-10). The assumption is made that the remaining
128 miles of roadway to be paved in this period will be done
according to transportation needs indirectly associated with
urbanization. Therefore, the remaining 128 miles is distributed
proportionally among the maintenance areas subject to urbanization.
The proportionality constant is determined by dividing the total
miles of road to be paved in each maintenance area by the total
number of miles of road to be paved in all maintenance areas.
For instance, according to Table 5-10, 35 miles of dirt and 17
miles of gravel roads in area I-F are due to be paved by 1985.
The proportionality constants are:
Dirt = |yg- x 100 = 9%
Gravel = ij=r x 100 = 4%
Thus, (.09) x (128) = 12 additional miles of dirt roads and
(0.4) x (128) = 5 additional miles of gravel roads will be
paved by 1985. The total mileages of unpaved roads to be
paved in I-F are:
Dirt = 35 (due to urbanization) + 12 (due to indirect needs) = 47 miles
Gravel = 17 (due to urbanization) + 5 (due to indirect needs) = 22 miles
(9) Fifty percent of the paving in all maintenance areas by 1985
is assumed to occur by 1980.
(10) In addition to the change in miles of unpaved roads, the ADT
in all maintenance areas and cities is assumed to increase at
the same rate which the population is expected to Increase from
1975 to 1980 to 1985 [1].
1975"1980 : 27.4%
1975^ 1985 : 49.7%
5-17
-------
TABLE 5-10. PROJECTION OF UNPAVED ROAD MILEAGES IN MARICOPA COUNTY
Maintenance Areas
Subject to Urbanization
! 1n Study Area
I-B
I-C
1-0
I-E
l-F
II-A
II-B
II-E
III-A
III-B
III-C
Ill-li
HI-I
IV-B
IV-C
IV-D
IV-E
TOTAL
Percent of Total Road Mileage
of the Maintenance Ares In the
Urbanized Portion of the
Maintenance Area
2
3
15
3
38
33
12
3
12
3
2
6
99
30
2
2
5
Miles of Unpaved Roads in
1975 in Maintenance Area
Dirt
147
72
71
94
93
197
125
103
101
109
68
72
61
52
72
142
92
1671
Gravel
44
30
32
45
44
77
54
51
38
55
28
31
23
17
30
77
44
720
Miles of Unpaved Roads to be
Paved Due to Urbanization in
each Maintenance Area in 1985
Dirt
3
22
11
3
35,
65
15
3
12
3
1
4
60
16
1
3
5
262
Gravel
1
9
5
1
17
28
7
2
5
2
1
2
23
5
1
2
2
110
Paving Proportionality
Constant, C a
Dirt
1
6
3
1
9
17
4
1
3
1
0.5
1
16
4
0.5
1
1
70
Gravel
0.5
2
1
0.5
4
6
2
1
1
1
0.5
1
5
1
0.5
1
1
30
Total Miles of Paved Road in
Each Maintenance Area in 1985
Dirt
4
30
15
4
47
87
20
4
16
4
2
5
80
21
2
4
6
351
Gravel
2
12
6
2
22
33
10
3
6
3
2
3
31
6
2
3
3
149
Total Miles of
in Each Mainte
1910
Dirt
145
52
64
92
70
154
115
101
93
107
67
70
21
42
71
140
89
1498
Gravel
43
24
29
44
33
61
49
50
35
54
28
30
8
14
2S
76
43
'648
Unpaved Roads
nance A'-ea
19 !5
Oirt
143
42
56
90
46
110
105
99
85
105
66
67
0
31
70
138
86
1339
Gravel
42
18
26
43
22
44
44
48
32
52
26
28
0
11
28
74
41
579
in
00
-------
(11) Emission projections are also affected by rainfall predictions
(See Section 3.1). Typical meteorology is assumed to prevail
in 1980 and 1985 as shown below:
Quarter of
year
1
2
3
4
year
Number of days
.01 inch or
more of rain
11
4
12
9
36
Fraction of
.01 inch
of rain
.12
.04
.13
.09
.09
days
or more
Projections for Pinal County
As no data was available for Pinal County, it is assumed that no change
in the mileage of unpaved roads will occur. The ADT is expected to increase
at the following rate:
1975 1980 : 27.4%
1975* 1985 : 49.7%
Projections for the Total Study Area
Dust emissions from unpaved roads increase from 1281 tons/day in 1975
to 1553 tons/day in 1985. The distribution of the emissions change as
improvement programs will reduce the number of unpaved roads in the metro-
politan area. An increasing portion of the unpaved road emissions will
be generated at the perimeter of the urban areas and outside the boundaries
of the city of Phoenix. Figure 5-5 presents the grid map of emissions
arising from unpaved roads as forecast for 1985. Figure 5-6 "illustrates
graphically the distribution of unpaved road dust emissions.
5.2.2 Agricultural Tilling
Knowledgeable personnel at the College of Agriculture, University of
Arizona [13] were consulted as to projected growths or declines in cropland
average. These conversations revealed that total crop acreages in Maricopa
and Pinal Counties have not changed substantially in the last 26 years
5-19
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GRID
CODE
0
1
2
3
4
5
6
7
8
. 9
EMISSIONS
TONS/DAY
0 to 0
0 to 005
0 to .02
.02 to .07
.07 to .18
.18 to .37
.37 to .68
.68 to 1.2
1.2 to 1.9
1.9 to 2.8
Figure 5-5. Grid Map for Dust Emissions from Motor Vehicles on
Unpaved Roads, 1985.
5-20
-------
in
i
ro
Figure 5-6,
Dust Emissions Arising from
Motor Vehicles on Unpaved Roads,
Daily Average, 1985.
-------
and are not expected to vary greatly in the next ten year period. This
was partially verified by examining the acreages committed to major crops
in Maricopa County over the previous eight years. As agriculture is a
major industry in Arizona and especially Maricopa County, it is not sur-
prising to expect a fairly steady trend.
However, as the metropolitan Phoenix area has grown at an extremely
rapid pace in the previous ten years and is expected to continue expanding,
the location of croplands will change. To document this phenomena, land
use maps for 1985 [17] were examined and compared to present locations of
croplands. This procedure permitted an adjustment to be made to the
township-by-township agricultural acreage distributions described in
Section 3.2.2. A comparison of total agricultural acreages in 1985
and 1975 revealed a decline of only 31,000 acres, thus verifying the
observations made in the foregoing paragraph. For 1980, a linear inter-
polation scheme was adopted, where 50% of the increase or decrease in
crop acreage from 1975 to 1985 in a given township is assumed.
Although crop type acreages may vary substantially from year to year
(depending on national and international supply and demand), this variation
is unpredictable in the long term, hence, it was assumed that distribution
of cropland by crop type would remain unchanged from 1975.
The projected 1980 and 1985 emissions from agricultural tilling are
obtained by adjusting the 1975 baseyear inventory to reflect the changes
discussed above. The emissions forecasts are portrayed 1n the gridded
format of Figure 5-7, and the emissions distribution is presented graphic-
ally in Figure 5-8. The change in magnitude of tilling emissions is ex-
pected to be Insignificant from 1975 to 1985, however, the distribution
of these emissions is expected to be altered noticeably as urban expansion
claims existing croplands and new croplands are established in turn.
5.2.3 Aggregate Storage Piles
Projection of fugitive dust emissions are based on employment projec-
tions for the minerals^industry (see Section 3.0):
1975 1980 +32%
1975 1985 +64%
5-22
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GRID
CODE
EMISSIONS
TCNS/Dtr
.onnno TO
,00000 TL
.oroop TO
.OnO<,7. TO
.0013? TO
.003?? TO
.006*" TO
.01737 TO
.07110 10
.03380 TO
.00000
.00006
.000', 2
.00132
.00322
.03068
.01237
.0211Q
.03360
.C5151
Figure 5-7. Grid Map for Emissions Arising from Agricultural
Tilling, 1985.
5-23
-------
en ;
i
ro
Figure 5-8. Forecast of Agricultural Tilling Emissions, Daily Average, 1985.
-------
To obtain the projected emissions levels, the baseyear inventory of
aggregate pile emissions is adjusted to reflect the employment forecasts.
Table 5-11 summarizes the emissions forecasts. The location and number of
sources are assumed to remain unchanged.
TABLE 5-11. PROJECTED FUGITIVE DUST EMISSIONS
FROM AGGREGATE STORAGE PILES
Year
1980
1985
Emissions, tons/day
.073
.091
5.2.4 Cattle Feedlots
The Maricopa County Agricultural Agent [14] was consulted as to
future trends in cattle feedlot sizes. The following facts are -
pertinent:
As is the case with most agricultural products, cattle feed-
ing depends greatly upon the weather conditions and the
nationwide economy. Thus, trends are extremely difficult
to predict.
The number of cattle on feed in the study area (see Table
3-17) during 1975 represents a low year; only 40%-60% of
the capacity of the feedlots were utilized. The corres-
ponding figures for 1976 should be up to 80% capacity.
The best guess estimate for the 1975-1985 period given by
the Agricultural Agent is that the number of cattle on feed
should be at least 50% greater than the number on feed in
1975.
Thus, the methodology employed to predict future emissions consists of
adjusting the baseyear inventory to reflect an increase 1n the number
of cattle-on-feed by 50 % for both 1980 and 1985. Accordingly, emissions
are increased by 50% over the baseyear levels (see Table 5-12).
5.2.5 Off-Road Motor Vehicles
As off-road vehicle use is a recreational activity, the projections
will be proportional to the growth rate in population as forecasted by
5-25
-------
TABLE 5-12. PROJECTED FUGITIVE DUST EMISSIONS FROM
CATTLE FEEDLOTS IN THE STUDY AREA
County 1980 and 1985 Emissions
tons/day
Maricopa 3.2
Final 5.1
Total, study area -*8.3
the Maricopa Association of Governments [I].1
The location of off-road vehicle activity 1s assumed to remain unchanged
with the exception of the area of Sun City, where it is assumed off-road
activity will be eliminated due to planned urban expansion and local
ordinances. The projected emissions are summarized in Table 5-13.
TABLE 5-13. PROJECTED EMISSIONS FROM OFF-ROAD
MOTOR VEHICLES
Emissions (tons/day)
1980 1985
Motorcycles
Motor Vehicles
Total
68.0
23.0
91.0
80.0
27.0
.107-.0
5.2.6 Construction Activities
Based on the general future land use plan for Maricopa County [15],
urbanization development is expected to occur at the rate of 18.7 square
miles per year from 1973 to 1990. Figure 5-4 shows the forecasted area
which will be developed by 1990. The developed portion represents 640
square miles. By contrast, the existing urbanized area in 1973 comprised
5-26
-------
some 323 square miles.
Estimates of land areas involved in construction for 1980 and 1985
were assumed to be consistent with the forecasts of the County General
Plan. 18.7 square miles of new urbanization development occurs annually.
Roadway construction improvements also contribute a significant amount
of additional soil disturbance, and consequently, dust emissions. These
improvements are expected to occur at the rates shown in Table 5-14.
Expected dust emissions arising from these activities are also shown in
Table 5-14. These dust emissions may be located within the computerized
emissions grid as area sources spread throughout the region of agency
jurisdiction, except for those activities of the State Highway Department,
which were located according to the forecasted State Highway Future General
Plan [16].
TABLE 5-14. ANNUAL STREET IMPROVEMENTS SCHEDULED FOR MARICOPA
COUNTY OVER NEXT TEN YEAR PERIOD.
Agency Improvements Acres of Soil Emissions Average
miles/year Disturbed tons/day
County
Phoenix
Glendale
Paradise Valley
Scottsdale
Chandler
Mesa
Tempe
State Highway
Dept.
20a
40b
lc
lc
1.2C
.4C
1.7C
.3C
37
a. Representative value based on
b. This value
is based on target*
133
274
6.7
6.7
8.0
2.7
11.4
2.0
360
804.5
previous
id 20 mill
1.8
3.6
.1
.1
.1
_
.2
-
7.1
13.0
years [17].
2/year rate of the Improvement
District for upgrading local streets, and a 20 mile/year program of
the Traffic Department for improvment of major streets in 1980[18,19]
c. Based on conservative assumption that improvements by cities will at
least account for upgrading all unpaved roads by 1985.
5-27
-------
Development of 18.7 square miles of land in 1980 and 1985 (assuming
an active construction duration of 6 months) will result in an estimated
dust loading of 86,300 tons/year, or an average of 246 tons of dust
emissions per day. The location of the development will proceed outward
from the center of the cities in the Phoenix area. A geometric mapping
procedure was used to estimate the location of the construction activity
in 1980 and 1985. Isolines reflecting the constant rate of expanding
development were constructed for the years 1980 and 1985 by interpolating
between the boundaries of the existing developed area and that developed
area forecasted by the 1990 Future General Land Use Plan. The differen-
tial development in the years 1980 and 1985 was assumed to occur within
a growth belt representing the expanded urbanization over the past five
year period. The forecasted dust emissions loadings were apportioned
according to the relative area of the growth belt in each of the grid
squares of the computerized emissions grid networks. The distribution
is illustrated on the grid map of Figure 5-9, and on the three-dimensional
graphical emissions portrayal of Figure 5-10. It can be seen that dust
from construction emissions is being generated further away from the down-
town Phoenix area as development proceeds in future years. Comparison
of the forecasted total dust emissions levels with the 1975 baseyear con-
firms the relatively low degree of construction activity in 1975.
Year Dust Emissions from Construction
tons/day
1975 - 100
]980 254
1985 256
5.2.7 Suspension of Dust from Paved Roads
Roadway improvements expected to be implemented over the next ten
years will incur significant impact on street dust loadings. Due to a
local roads improvement program in the city, the 200 existing miles of
substandard city local streets will be upgraded by 1985. In addition,
rnajor streets will be renovated at the rate of about 20 miles per year.
5-28
-------
GRID
CODE
0
1
2
3
4
5
6
7
8
9
EMISSIONS
TONS/DAY
0 to 0
0 to .001
.001 to .005
.005 to .01
.01 to .04
.04 to .08
.08 to .15
.15 to .27
.27 to .43
.43 to .64
Figure 5-9. Grid Map for Total Dust Emissions from Construction
Activities 1n 1985.
5-29
-------
en
i
u>
o
Figure 5-10. Forecast of Dust Emissions from Construction Activities, Daily Average, 1985.
-------
Considering both local and major improvements, some 400 miles of city
streets will be upgraded by 1985. Since there are some 120 miles of
unpaved streets in the city at present, it may be reasonably assumed
these will be paved by 1985. Further, it was assumed that the remaining
280 miles of street improvements was directed toward upgrading uncurbed
streets. The impact of these improvements on total mileage of uncurbed
streets in the city is shown below:
Miles of Uncurbed City Streets
Road Type 1975 1980 1985
Local
Collectors
and Major
142
329
72
260
0
191
This data is important because dust loadings on streets with uncurbed road
shoulders is four times less than that observed on curbed streets(see Section
3.7).
Most of the improvements in the county will consist of paving dirt
or gravel roads. The county improvement program will probably exert
only minor impact on the mileage of paved county roads currently unpaved.
Projections of dust emissions in 1980 and 1985 were based on pop-
ulation projections as discussed in Section 5.1. These projections were
applied to the existing traffic network. The adjusted emission factor
reflecting newly curbed streets was calculated by weighting the emission
factors for uncurbed streets and curbed streets relative to the proportion
of each of these street configurations in 1980 and 1985. The resulting
emission factors for application to the baseyear transportation tape are:
Dust Suspension Rate, g/vehicle mile
Road Type in 1975 1975 1980 1985
Uncurbed Major and 11.1 9.9 8.7
Collector
These emission rates are applied to the applicable streets in the city
and unincorporated cities only, while emission rates remain unchanged
for uncurbed roads in the county. At the same time, VMT changes in 1980
5-31
-------
and 1985 cause associated increases in total dust suspension levels in
both the city and county. The net effect of these changes on particulate
emissions in the study area is summarized below:
Year Suspension of Street Dust
tons/day
1975 248
1980 295
1985 322
The gridded emissions inventory for suspended street dust in 1985
is shown in Figure 5-11. The distribution of these fugitive emissions
is shown graphically in Figure 5-12 for 1985. Street dust emissions and
seen to remain relatively unchanged in the city areas, but increase
significantly in the county.
5.3 WINDBLOWN FUGITIVE DUST
This section documents the procedures employed to forecast dust emis-
sions arising from wind blowing over various types of soil surfaces. The
emissions forecasts are conducted for 1980 and 1985.
5.3.1 Unpaved Roads
The procedure for estimation of projected wind erosion emissions from
unpaved roads is the same as that outlined in Section 4.2. The adjustments
which must be applied to the baseyear parameters used in the wind erosion
model concern: 1) the miles of unpaved roadways in the various grid sec-
tors, and 2) the Climatic Factor. The former item is obtained by the con-
siderations outlined in Section 5.2.1. The Climatic Factor, calculated to
reflect typical annual and seasonal meteorology for the study area, is
obtained from Table 4-4.
Forecasts of windblown dust off unpaved roads indicate substantial de-
creases from the baseyear levels. This is due mainly to the assertion that
typical historical meteorology will prevail in the projected periods.
5-32
-------
GRID
CODE
0
1
2
3
4
5
e
7
8
9
EMISSIONS
TONS/DAY
0 to 0
0 to .004
.004 to .02
.02 to .07
.07 to .18
.18 to .37
.37 to .69
.69 to 1.2
1.2 to 1.9
1.9 to 2.9
Figure 5-11. Grid Map for Dust Emissions off Paved Roads, 1985.
5-33
-------
CO
Figure 5-12. Forecast of Dust Emissions from Paved Roads, Dally Average, 1985,
-------
QUARTER TONS/DAY
1980 1985
1
2
3
4
Annual
Average
.3
.5
.7
.9
.6
.3
.5
.7
.9
.6
5.3.2 Agricultural Fields
The procedure for estimating wind erosion emissions from agricultural
fields 1n 1980 and 1985 1s the same as that outlined 1n Section 4.3. The
adjustments which must be applied to the baseyear estimates to obtain the
forecasted emissions concern: 1) the amount of cropland acreage 1n each
township, and 2) the anticipated Climatic Factor.
The location of cropland acreage was determined by evaluation of the
general future land use map for Maricopa County[15] as described in Section
5.2.2. The total cropland acreage is not expected to change, however,
location of croplands are expected to be displaced by urban expansion.
Consequently, the spatial distribution of wind blown agricultural emissions
will change, and the magnitude of emission levels will be affected slightly
due to changes 1n soil errodibillty. Distribution of crop acreage by crop
type was assumed to remain constant in future years.
The most dramatic.changes 1n windblown agricultural emissions levels
are attributable to variations 1n climate. Assuming that historical clima-
tic averages will prevail in future years, the crop-specific Climatic Fac-
tors for 1980 and 1985 are estimated to be approximately half of the value
in the baseyear (when it was drier and more windy than normal).
The computational procedure of Section 4.3 was employed using the ad-
justed values of Climatic Factors and soil errodibillty to obtain the emis-
sions forecast summarized below.
5-35
-------
QUARTER TONS/DAY
1980 1985
1
2
3
4
Average
1.7
1.7
1.6
1.7
1.7
1.7
1.7
1.6
1.7
1.7
5.3.3 Undisturbed Desert
One consideration associated with projection of emissions from the
desert surface involves changes in spatial distribution and total source
area. Desert area is expected to diminish somewhat due to projected urban
expansion. The total acreage of undisturbed desert in the study area was
estimated by geometric plotting of the 1990 Future General Land Use Map
[15]. The township by township acreage 1n 1980 and 1985 was derived by a
linear interpolation of the diminishing acreage indicated between 1975 and
1990.
The major parameter involved in estimating future dust emissions from
the desert is the Climatic Factor. Assuming that precipitation and wind
speed for 1980 and 1985 will reflect historical averages for the study area,
the Climatic Factors of Table 4-4 must be employed to derive the emission
forecasts.
Based on the forecasted acreages of undisturbed desert land and Cli-
matic Factors, emissions of dust off the desert pavement are estimated as
shdwn below. The future emissions levels are estimated to be substantially
less than were,estimated 1n the baseyear. The reduction is attributable
principally to the assumed change 1n climatology, as the change in total
desert acreage is insignificant.
QUARTER TONS/DAY
1975 1980 1985
1
2
3
4
160
244
321
450
66
112
104
56
66
112
104
56
Average 294 85 85
5-36
-------
5.3.4 Tailings Piles
The change in quantities of windblown dust off tailings piles in future
years was estimated by assuming that the size of the mineral waste heaps
would grow in proportion to employment in the minerals industry. This
expected growth in employment is 32% from 1975 to 1980, and 64% from 1975
to 1985 (see Section 5.1.2). The general location of the tailings piles is
not expected to change. The emissions forecast for 1980 and 1985 is 1.9
and 2.3 tons/day, respectively.
5.3.5 Disturbed Soil Surfaces
Forecasts of windblown dust off vacant lots, unpaved parking lots and
dirt residence yards were calculated by adjusting baseyear estimates to
reflect changes 1n two parameters: the Climatic Factor, and the amount of
disturbed soil surface. These parameters are directly related to windblown
emissions levels.
The change 1n Climatic Factor from 1975 to future years is determined
by assuming that the historical annual meteorology will prevail. The expec-
ted annual and seasonal meteorology has been calculated previously in Table
4-4.
Projection of the amount of vacant lands was based on the estimate
that 15% of all potential urban area would be vacant in 1990, and that 50%
of such potential urban area was vacant in 1973 [15]. This rate of decrease
in vacant land was applied to the amount of vacant land Inventoried for
1975 (see Section 4.6) to obtain the adjusted levels for 1980 and 1985.
The amount of exposed soil from 'dirt residence yards in the study area
was assumed to increase in proportion to population growth through 1985.
Accordingly, the Increase from 1975 to 1980 1s 27%, and from 1975 to 1980
the Increase 1s 50%.
The spatial distribution of the disturbed soil surfaces was assumed
unchanged. There was no legitimate basis for altering the distribution
based on available Information, and the assumption that vacant land inven-
toried in 1975 would diminish evenly throughout the study area, was con-
sidered plausible. Similarly, the assumption that the number of dirt
residence yards would expand in the vicinity where they are now concen-
trated (economically depressed areas) seems plausible.
5-37
-------
The future expected levels of windblown dust emissions from disturbed
soil surfaces is summarized below. Changes in the levels are affected
mostly by the assumption that "normal" meteorology will prevail in the
future, as contrasted to the "unusual" climatological conditions in 1975
which favored high levels of windblown dust emissions.
QUARTER TONS/DAY
1980 1985
1 85 43
2 151 77
3 138 70
4 77 39
Annual 114 58
5-38
-------
REFERENCES FOR SECTION 5.0
1. Maricopa Association of Governments, "Maricopa County Projected Popula-
tion Summary Page," Pamphlet with preliminary census projections,
September, 1975.
2. Personal Communication, W1lma Richard of the Arizona Department of
Economic Security, Labor Force Statistics Division, Phoenix, March,
1976.
3. Telephone Communication, Greg Witherspoon of the Maricopa County Depart-
ment of Health, April, 1976.
4. U.S. Environmental Protection Agency, "Compilation of Air Pollutant
Emission Factors," Supplement No. 5, December 1975.
5. Arizona Department of Aeronautics, "State of Arizona Aviation Systems
Plan, 1974-1993," December, 1973.
6. Wilbur Smith and Associates, L.H. Bell and Associates, "Highway Needs
and Fiscal Study- Arizona's Future Highways," December 1967.
7. Arizona Department of Transportation, "First Biennial Statewide Trans-
portation Needs Report to the Arizona Legislature," Phoenix, Arizona,
January 1976.
8. Arizona Highway Department, Planning Survey Division, "Preliminary
Report on Future Highway and Street Needs, Maricopa County, Arizona,"
Phoenix, Arizona, June 1970.
9. Arizona Highway Department, "Future Highway and Street Needs, Pinal
County, Arizona," Phoenix, Arizona, May ..-1969.
10. Technical Advisory Committee, "Arizona Highway Studies," January 1968.
11. Maricopa County Highway Department, personal communication, March 1976.
12. Arizona Department of Transportation, Planning Survey Group, "Status
of Road Systems Mileage," Phoenix, Arizona, 1972, 1973, 1974, 1975.
13. College of Agriculture, University of Arizona (Tucson), personal
communication, April 1976.
14. Maricopa County Agricultural Agent, personal communication, April 1976.
15. Maricopa County Planning Department, "A Report Upon Future General Land
Use for Maricopa County, Arizona," February 1975.
16. Arizona Department of Transportation, "Tentative Five Year Construction
Program," 1976.
17. Arizona Highway Department, personal communication, April 1976.
5-39
-------
18. City of Phoenix Traffic Department, personal communication, April 1976.
19. City of Phoenix, Arizona, "1975 Accelerated Major Street Program," July
1975.
5-40
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA-450/3-77-021b
2.
3. RECIPIENT'S ACCESSION NO.
4. TITLE AND SUBTITLE
5. REPORT DATE
An Implementation Plan for Suspended Particulate
Matter in the Phoenix Area, Volume II, Emission
Inventory
1Q77
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
George Richard, Ronald Tan, James Avery
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
TRW
Environmental Engineering Division
One Space Park
Redondo Beach, California
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
68-01-3152
12. SPONSORING AGENCY NAME AND ADDRESS
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Research Triangle Park, N.C. 27711
13. TYPE OF REPORT AND PERIOD COVERED
Final
14. SPONSORING AGENCY CODE
200/04
15. SUPPLEMENTARY NOTES
Volume I, Air Quality Analysis - EPA 450/3-77-021a; Volume II
Emission Inventory - EPA 450/3-77-021b; Volume III, Model Simulation of Total
ParHrulatP Mat-t-or lowolc - FPfl Zmn/T-77-091^ Wnlnmo TW rrm + v»r.l
16. ABSTRAC
Strategy Formulation - EPA 450/3-77-021d
This document is one volume of a four volume report presenting an implementation
plan for control of suspended particulate matter in the Phoenix area,
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS C. COSATI Field/Group
Particulate Matter
Total Suspended Particulate
Emission Sources
Fugitive Dust
Emission Factors
18. DISTRIBUTION STATEMENT
Release Unlimited
19. SECURITY CLASS (ThisReport)
Unclassified
21. NO. OF PAGES
216
20. SECURITY CLASS (Thispage)
Unclassified
22. PRICE
EPA Form 2220-1 (Rev. 4-77) PREVIOUS EDITION is OBSOLETE
5-41
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