United States
Environmental Protection
Agency
Environmental Sciences Research
Laboratory
Research Triangle Park NC 2771 1
>>00 3 7'
Research and Development
&EPA
Dust Transport in
Maricopa County,
Arizona
-------
RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development, U.S. Environmental
Protection Agency, have been grouped into nine series. These nine broad cate-
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The nine series are:
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2. Environmental Protection Technology
3. Ecological Research
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This report has been assigned to the ECOLOGICAL RESEARCH series. This series
describes research on the effects of pollution on humans, plant and animal spe-
cies, and materials. Problems are assessed for their long- and short-term influ-
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This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.
-------
EPA-600/3-79-082
September 1979
DUST TRANSPORT IN MARICOPA CO'JNTY, ARIZONA
by
S. Suck, E. Upchurch, and J. Brock
University of Texas
Austin, Texas 78712
Grant No. 803660
Project Officer
Jack L. Durham
Atmospheric Chemistry and Physics Division
Environmental Sciences Research Laboratory
Research Triangle Park, North Carolina 27711
ENVIRONMENTAL SCIENCES RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
RESEARCH TRIANGLE PARK, NORTH CAROLINA 27711
-------
DISCLAIMER
This report has been reviewed by the Environmental Sciences Research
Laboratory, U.S. Environmental Protection Agency, and approved for publica-
tion. Approval does not signify that the contents necessarily reflect the
views and policies of the U.S. Environmental Protection Agency, nor does
mention of trade names or commercial products constitute endorsement or
recommendation for use.
ii
-------
ABSTRACT
Numerical simulations have been carried out" for ambient supermicrometric
particulate concentrations in Maricopa County, Arizona during late fall and
winter periods of atmospheric stability. Results of model studies are in
approximate agreement with limited field observational data. On the basis
of the model studies it is concluded that observed high particulate concen-
trations in Maricopa County urban areas during late fall and winter periods
of atmospheric stability are associated with local fugitive dust sources.
Because of light drainage winds prevalent during these periods, advective
transport of dust from countryside to the urban areas is not an important
contribution to urban supermicrometric particulate concentrations. Surface
roughness, dry deposition, and source strengths, are among the most important
determinants of ground level concentrations. Reduction in ground level con-
centrations could be effected through control of dust emissions, as well as
by planting trees and other foliage to increase surface roughness and
particle deposition. An adequate and practical predictive model, along the
lines of the current model, could be developed for Maricopa County as well
as for the other urban areas in the high desert regions.
This report was submitted in fulfillment of Grant R803660 by the
University of Texas, Austin under the sponsorship of the U.S. Environmental
Protection Agency. This report covers a period from December 1, 1975 to
December 1, 1977, and work was completed as of March 1, 1978.
iii
-------
CONTENTS
Abstract iii
Figures vii
Tables viii
1. Introduction 1
2. Procedure 2
3. Data for Modelling Maricopa Co 5
4. Results 11
5. Conclusions 40
References 41
-------
FIGURES
Number Page
1 Study area in Maricopa Co., Arizona with day wind
field of Berman and Delaney (10) 6
2 Study area in Maricopa Co., Arizona with day wind
field of Berman and Delaney (10) 7
3 Estimated variation with time of traffic dust 9
4 Dust concentration at 10m for Maricopa County, Arizona,
DIM Easting 358ooo to 446ooo, UTM Northing 3670ooo to
3734ooo 12
5 Dust concentration at 10m for Maricopa County, Arizona,
UTM Easting 358ooo to 446ooo, UTM Northing 3670ooo to
3734ooo 13
6 Dust concentration at 10m for Maricopa County, Arizona,
UTM Easting 358ooo to 446ooo, UTM Northing 3670ooo to
3734000 14
7 Dust concentration at 10m for Maricopa County, Arizona,
UTM Easting 358ooo to 446ooo, UTM Northing 3670ooo to
3734ooo 15
8 Dust concentration at 10m for Maricopa County, Arizona,
UTM Easting 358ooo to 446ooo, UTM Northing 3670ooo to
3734ooo 16
9 Dust concentration at 10m for Maricopa County, Arizona,
UTM Easting 358ooo to 446ooo, UTM Northing 3670ooo to
3734ooo 17
10 Dust concentration at 10m for Maricopa County, Arizona,
UTM Easting 358ooo to 446ooo, UTM Northing 3670ooo to
3734ooo 18
11 Dust concentration at 10m for Maricopa County, Arizona,
UTM Easting 358ooo to 446ooo, UTM Northing 3670ooo to
3734000 19
-------
Number Page
3
12 Particle concentration isopleths in yg/m in plane
perpendicular to surface at UTM Northing 3702ooo
extending from UTM Easting 382ooo to 422ooo 32
3
13 Particle concentration isopleths in yg/m in plane
perpendicular to surface at UTM Northing 3702ooo
extending from UTM Easting 382ooo to 422ooo 33
3
14 Particle concentration isopleths in yg/m in plane
perpendicular to surface at UTM Northing 3702ooo
extending from UTM Easting 382ooo to 422ooo 34
3
15 Particle concentration isopleths in yg/m in plane
perpendicular to surface at UTM Northing 3702ooo
extending from UTM Easting 382ooo to 422ooo 35
3
16 Particle concentration isopleths in yg/m in plane
perpendicular to surface at UTM Northing 3702ooo
extending from UTM Easting 382ooo to 422ooo 36
17 Particle concentration isopleths in yg/m in plane
perpendicular to surface at UTM UTM Easting 398ooo
extending from UTM Northing 3694ooo to 3734ooo 37
vii
-------
Number Page
3
1 Calculated Hourly Particulate Concentrations (ug/m )
at 10 Meters above the Surface. (See Fig. 4) 20
3
2 Calculated Hourly Particulate Concentrations (iig/m )
at 10 Meters above the Surface. (See Fig. 6) ...... 24
viii
-------
SECTION 1
INTRODUCTION
Many urban areas in the high desert regions of the western United
States consistently exceed the national ambient air quality standards for
particulate matter. In considering control strategies for these areas,
complex predictive models of suspended particulate matter dynamics are
necessary. Empirical models, which correlate limited observational data,
are ineffective in examining and predicting alternative control strategies.
High ambient particulate concentrations (as measured by high-volume
samplers) are usually observed in Maricopa, Co. during late fall and winter
days. During this period, meteorological conditions are characterized by
light drainage winds associated with the area's valley topography. The
whole area forms an air drainage basin with a gentle slope down the area's
rivers from east to west. The analysis, presented here covers typical
drainage and other conditions prevalent during late November in Maricopa Co.
A comprehensive computer code, AROSOL, was used to analyze the aerosol
dynamics.
-------
SECTION 2
PROCEDURE
Of all the atmospheric trace constituents, the atmospheric aerosol
probably possesses the most complex dynamical features. These include such
processes as coagulation, condensation, nucleation, sedimentation, deposition,
resuspension, primary and secondary source inputs, and advection and
dispersion.
The advent of high speed computers has made it feasible to deal with
these complexities (1,2). Computer code AROSOL has been developed by us
to investigate atmospheric aerosol dynamics. AROSOL gives a numerical
solution of the following equation describing the evolution of the singlet
density function of an aerosol.
3n(u;r,t)/ t + V • TM(u;r,t) = (K^ + Ky)V2n(y;r,t)
+ V-K (r,t)7n(u;r,t) + 1/2 / dp'Mu-u1 ,y')n(y-y' ;r,t)n(y';r,t)
z o
- n(y;r,t) dyb(y,u')n(u' ;r,t) - - [iKy;r,t)n(y;r,t)]
o oV
+ G(y)-Vn(y;r,t) + Zcr.+ Zv. (1)
i i j J
Boundary and initial conditions may be set as a particular physical system
demands, but always includes phenomena such as dry deposition at boundary
surfaces. n(u;r,t) represents the number of aerosol particles having mass
y in the range y,dy at a point in space r at time t. In the atmosphere, U
is the time average wind speed. K , K , and R are the turbulent eddy
dlffusivities (a rectangular Eulerian coordinate system is employed) in the
x,y, and z directions, respectively. The fourth and fifth terms on the
right hand size of (1) account for particle coagulation. The sixth term
-------
represents condensation'^ and the seventh graviational sedimentation, G
being the sedimentation velocity. The last two terms allow for input of
primary source aerosol, a., and aerosol resulting from homogeneous nucleation
of trave gaseous species, v..
Eq. (1) is coupled to the corresponding onservation equations of
those trace gaseous species which act as sources of' secondary aerosol (3).
The appropriateness of eq. (1) for representing the evolution of an aerosol
under conditions of atmospheric turbulence has been verified (4,5).
The details of the numerical solution of eq. (1) and of computer time
and memory requirements will be covered in another publication (6). The
portion of AROSOL dealing with advection and dispersion is a modification
of an earlier computer code due to Shir and Shieh (7).
In modelling particulate concentrations for Maricopa County during
stable late fall periods, considerable simplification of eq. (1) is possible.
Source emission data (8) and dichotomous and hi-vol data (9) show that
supermicrometric dust is the largest contributor to the large (24 hour
3
averages of 100-300 yg/m ) ambient particulate concentrations. For this
situation, coagulation, condensation, and nucleation all play negligible
roles. Hence the following equation has been employed in our model:
3n(y;r,t)/3t + V-Un(y;r,t) = (K + K )V2n(y;r,t)
x y
+V*K Vn(y;r,t) + G'Vn(y;r,t)
z
(2)
with boundary conditions:
= 0; x = 0, x = x (3)
• - 0; y = 0, y - y (4)
nVd = -(Kz+D(y))|| - Gn; z = 0 (5)
^T = 0; z = z (6)
3z max
-------
n - no(y;r,t); t » 0 (7)
vhere z is the axis perpendicular to the surface at a point x,y of a grid
covering Maricopa Co. In eq. (5), V. is the deposition velocity; 6(y) the
sedimentation velocity at the surface point x,y; and D the Brownian diffusion
coefficient of particle of mass, y.
-------
SECTION 3
DATA FOR MODELLING MARICOPA CO.
.4
Even with the simplifications introduced in arriving at eq. (2), the
dynamical system is still very complex. Accurate modelling represents a
large project in data processing. Data inputs comprise the following items:
(1) Numerical grid for a portion of Maricopa Co.
(2) Elevations for a portion of Maricopa Co.
(3) Particulate area and point source emissions data.
(4) Particle size distributions and diurnal variation of particulate
emissions.
(5) Surface roughness.
(6) Wind data.
(7) Particulate dry deposition.
(8) Diurnal variation of mixing heights.
(9) Atmospheric dispersion coefficients.
These data inputs will be discussed in order.
(1) Numerical grid for a portion of Maricopa Co.: An area of 92 km.
by 68 km. (see Figs. 1&2) was chosen for this analysis. A grid 23 x 17 con-
sisting of 4 km. x 4 km. squares covers the area. These choices were deter-
mined by the available wind data of Herman and DeLaney (10).
(2) Elevations for a portion of Maricopa Co.: Elevations in meters
were required for each grid square. These were estimated from a variety
of sources (10,11,12).
(3) Particulate area and point source emissions data: These were
estimated for each grid point from 1975 winter quarter data of TRW, Inc. (8).
(4) Particle size distributions and diurnal variations of particulate
emissions: These were estimated as in a previous study of Denver pollution
episodes (13). Three major categories of dust emissions were considered:
-------
3638
3718
3678000
DAY WIND TRAJECTORIES
3698
Figure 1. Study area in Maricopa Co., Arizona with day wind field of
Herman and Delaney (10).
-------
3638 -
3718 -
3698
3678ooo -
390ooo
374
398
422
446
Figure 2. Study area in Maricopa Co., Arizona with day wind field of
Berman and Delaney (10)-
-------
(a) "traffic dust" consisting of unpaved automotive roadway emissions,
wind-blown unpaved roadway emissions, and off-roadway vehicle emissions.
(Variation with time of this component is given in Fig. 3.) (b) "diurnal
dust" consisting of agricultural tillage emissions, wind-blown undisturbed
desert emissions, and construction emissions. (These sources were "switched
on" at sunrise and thereafter remained constant.) (c) "constant dust"
consisting of tailing pile emissions, cattle feed lot emissions, and vacant
soil emissions.
Considerable uncertainty exists as to the particle size distributions
for the various sources. Also, computer time requirements for the CDC
6400/6600 system for accurately including atmospheric particle size distri-
butions are prohibitive. We assigned a single mean diameter to the suspended
particles. This mean diameter is varied in the course of our model studies.
(5) Surface roughness: Two types of surface roughness were considered.
"Micro-scale" surface roughness was required for estimation of dry deposition
velocities from data of Sehmel and Hodgson (14). For the desert area
(unpopulated) a *Nn1r.ro-Rra1 e" roughness of 3 cm was chosen, and for the urban
area a roughness of 10 cm was used. The urban area was defined to be the
populated areas defined by reference (12). "Macro-scale" surface roughness
was estimated by the method of Shir and Shieh (7).
(6) Wind data: These include x and y components of wind velocity
and determination of stability class from average wind speed by the method
of Shir and Shieh (7). The components of wind velocity were obtained from
the report of Herman and DeLaney (10) and adjusted for our grid system by
the continuity equation. Wind trajectories are given schematically in
Figs. 1 and 2.
(7) Particulate dry deposition: This input relates to.the boundary
condition of eq. (5). Deposition velocities, V^t were calculated from the
correlation of Sehmel and Hodgson (14) for a friction velocity of 10 cm/sec.
Sedimentation velocities, G , were calculated by standard methods (15).
z
(8) Diurnal variation of mixing height, H: These were obtained for
Ifovember 1974 from the daily mixing height studies of NQAA (16). The diurnal
8
-------
00
04 08 12 16 20
HOUR OF DAY, LST
24
4J
CO
O
•H
M-l
4-1
CD
o
cu
4->
TS
o
•rl
4J
(0
T)
01
4-1
CO
W
cu
-------
variations during this period were as follows in LST:
0 - 0500, vfl = H_in
0600 - 1300, H-p. +(H -H. )(LST hr. - 5.5)/8
' 'min v max min
1400 - 1800, H - H
max
1800 - 2400, H - H - (H - H. ) (LST hr. - 17.5)/6
max max min
Typical values of H. and H^ during this period were 130 m. and 1650 m.,
respectively.
(9) The vertical eddy diffusivity, K (x,-y, z), was calculated
Z
according to the methods of Shir and Shieh (7)- The horizontal eddy
2
-«&ffuaivity, K_, was chosen as 10 m /sec to reflect the assumed stable
u
f*rmfHl-
-------
SECTION 4
RESULTS
GENERAL FEATURES
As is evident from the discussion in the previous section, data input
requirements for eq. (2) are relatively large and, in the present study,
were obtained from a wide variety of sources. An accurate case study would
require at least hourly measurements of wind velocity as a function of
altitude over the study area. More accurate and detailed particulate emis-
sions data would also be necessary. Effects of "macroscale" roughness can
be assessed through a study of distribution of an inert species. Validation
of a case study would require accurate data (at least hourly) on particulate
concentrations and particle size distributions as a function of altitude
over the study area. Since none of these refined data souces were available
to us, our approach is to present a model study in which the sensitivity of
total ambient particulate concentrations to the various model parameters is
examined. This study indicates the important dynamical features governing
ambient particulate concentrations. Because of the complex interrelation-
ships of the various processes in the model, the effects of varying one of
the parameters are not intuitively obvious and are revealed only by such a
model study as performed here.
For purposes of limited comparison with the IITRI Field Sampling Study
(9) and with the high-vol data for the region (9), calculated hourly parti-
culate concentrations at 10 meters above the surface are presented in Tables
1 and 2 and Figs. 4.to 11 with variation of mean particle size, wind speed,
and dry deposition. Particle concentration isopleths are given in Figs. 12
to 17 in a cross section up to an altitude of 300m above surface and progress-
ing from UTM Easting 382OOO to 422OOO at UTM Northing 3702QOO. This cross
section, runs from Tolleson on the west through the center of Phoenix and
ends just north of Mesa.
11
-------
3730
3710 - -
3690
3670ooo.
RUN
298
358000
1100
1400
1700
•Figure 4. Dust Concentration at 10m for Maricopa County, Arizona, UTM Easting 358ooo to 446ooo, UTM
Northing 3670ooo to 3734ooo.
Particle Size: 5 urn, Wind Field: IX. Gravitational Sedimentation and Deposition Operating.
Height above surface proportional to particle concentration in pg/m^ (See Table 1).
-------
3670ooo_ -
358 oo
438
1100
1400
1700
Figure 5. Dust Concentration at 10m for Maricopa County, Arizona, UTM Easting 358ooo to 446ooo, UTM
Northing 3670ooo to 3734ooo.
Particle Size: 5 ym, Wind Field: IX. Gravitational Sedimentation and Deposition Operating.
Height above surface proportional to particle concentration in
-------
3670ooo
RUN
300
358ooo
0800
418 438
1100
1400
1700
Figure 6. Dust Concentration at 10m for Maricopa County, Arizona, UTM Easting 358ooo to 446ooo, UTM
Northing 3670ooo to 3734ooo.
Particle Size: 20 ym, Wind Field: IX. Gravitational Sedimentation and Deposition Operating.
Height above surface proportional to particle concentration in yg/m^ (Table 1).
-------
3730-x_
3710
3690.
3670ooo
RUN
302
358ooo
378
0800
1400
uoo
1700
Figure 7.
Dust Concentration at 10m for Maricopa County, Arizona, UTM Easting 358ooo to 446ooo, UTM
Northing 3670ooo to 3734ooo.
Particle Size: 5 ym, Wind Field: hX. Gravitational Sedimentation and Deposition not
Operating. Height above surface proportional to particle concentration in
-------
RUN
303
3670ooo-
358ooo
378
0800
418
438
1100
1400
1700
Figure 8. Dust Concentration at 10m for Maricopa County, Arizona, UTM Easting 358ooo to 446ooo, UTM
Northing 3670ooo to 3734ooo.
Particle Size: 20 \ant Wind Field: 4X. Gravitational Sedimentation and Deposition not
Operating. Height above surface proportional to particle concentration in yg/m .
-------
RUN
304
3670ooo--
358ooo
— '
V
\j
^_
7
\
— '
i —
\
-/
~~~r
—
-
. —
-^.
—
1400
noo
1700
Figure 9.
Dust Concentration at 10m for Maricopa County, Arizona, UTM Easting 358ooo to 446ooo, UTM
Northing 3670ooo to 3734ooo.
Particle Size: 20 ym, Wind Field: 2X. Gravitational Sedimentation and Deposition not
Operating. Height above surface proportional to particle concentration in yg/m-^.
-------
3670ooo
3586oo
378
0800
418
HUN
306
438
uoo
00
1400
1700
Figure 10. Dust Concentration at 10m for Maricopa County, Arizona, UTM Easting 358ooo to 446ooo, UTM
Northing 3670ooo to 3734ooo.
Particle Size: 5 ym, Wind Field: 2X. Gravitational Sedimentation and Deposition Operating.
Height above surface proportional to particle concentration in
-------
VO
RUN
307
3670ooo
358ooo
378
0800
418
438
1400
1100
1700
Figure 11. Dust Concentration at 10m for Maricopa County, Arizona, UTM Easting 358ooo to 446ooo, UTM
Northing 3670ooo to 3734ooo.
Particle Size: 20 ym, Wind Field: 2X. Gravitational Sedimentation and Deposition Operating.
Height above surface proportional to particle concentration in yg/m^.
-------
TABLE 1. CALCULATED HOURLY PARTICULATE CONCENTRATIONS (yg/m3) AT 10 METERS ABOVE THE SURFACE.
(See Fig. 4).
0800 LSI
IUTM
1
B
-
358
1
362
2
366
3
370
4
374
5
378
6
382
7
386
8
390
9
394
10
398
11
402
12
406
13
410
14
414
15
418
16
422
17
426
18
430
19
434
20
438
21
442
22
446
23
3734
3730
3726
3722
3718
3714
3710
3706
3702
3698
3694
3690
3686
3682
3678
3674
3670
17
16
15
14
13
12
H
JO
9
8
7
6
5
4
3
2
1
71
25
94
65
46
48
65
85
33
36
138
55
78
136
58
42
8
92
95
87
80
64
55
81
122
103
37
13
194
44
124
49
38
38
85
87
86
78
68
67
110
156
132
73
11
7
57
49
35
33
36
76
78
81
64
20
49
133
462
123
69
25
6
19
44
45
46
53
79
81
69
12
47.
11
23
100
57
23
25
21
0
0
40
49
63
76
86
97
148
28
24
273
215
41
29
33
28
56
0
0
56
77
69
80
98
169
60
76
169
147
45
72
26
35
59
43
0
0
82
87
126
142
180
63
80
148
52
107
77
34
39
46
65
58
0
0
116
87
29
242
317
87
99
93
69
144
78
52
54
80
92
61
63
64
106
35
35
210
103
117
115
85
71
45
70
0
40
73
60
52
134
125
130
47
59
291
129
126
136
117
71
41
0
169
179
81
58
1
136
159
222
64
0
163
157
125
118
66
0
0
207
218
95
66
0
0
0
139
351
0
0
126
99
99
54
0
92
203
214
104
89
0
0
0
37
281
150
0
0
110
101
219
161
169
223
220
118
324
0
0
0
0
35
166
119
132
145
87
244
118
139
149
146
102
124
1
0
0
0
41
230
143
175
232
50
236
185
142
114
105
78
108
0
0
0
0
0
58
115
85
37
179
84
53
214
41
73
28
116
1
0
0
0
0
0
128
115
178
24
99
43
47
377
19
54
28
0
0
0
0
0
0
119
23
40
249
93
278
42
85
80
79
51
0
0
0
0
0
0
0
0
22
24
92
151
14
127
18
132
49
2
0
0
0
0
0
0
0
0
0
69
42
10
14
13
15
40
0
0
0
0
0
0
0
0
0
0
63
16
10
3
41
5
35
0
0
0
0
0
0
0
0
0
2
2
5
4
13
0
5
5
UTH Northing
(Continued)
-------
TABLE 1. (Continued)
ISJ
1100 LSI
IUTM
I
-'
=
358
1
362
2
366
3
370
4
374
5
378
6
382
7
386
8
390
9
394
10
398
11
402
12
406
13
410
14
414
15
418
16
422
17
426
18
430
19
434
20
438
21
442
22
446
23
3734
3730
3726
3722
3718
3714
3710
3706
3702
3698
3694
3690
3686
3682
3678
3674
3670
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
32
11
83
47
39
32
33
35
14
16
62
24
35
51
21
14
4
97
94
85
74
61
51
53
59
44
18
16
425
17
194
81
60
22
102
102
99
90
80
73.
78
81
59
31
5
a
112
51
35
33
26
73
71
69
52
33
143
247
342
47
37
9
3
8
58
43
44
36
58
51
40
11
32
. 8
19
55
33
15
12
9
0
0
40
48
57
112
120
122
155
41
31
163
99
29
21
18
17
38
0
0
55
28
107
114
119
136
84
85
104
77
28
34
11
37
54
41
0
0
179
122
138
142
153
89
90
90
43
56
33
14
19
22
69
112
0
3
61
31
14
516
134
95
105
85
67
80
34
23
44
64
68
59
62
39
42
14
17
338
41
123
84
35
112
80
32
0
25
44
58
44
102
81
71
19
25
486
48
92
150
139
117
13
0
195
210
97
41
3
140
118
121
26
0
220
222
144
189
42
0
0
250
259
114
49
0
0
2
256
449
0
0
261
121
172
20
0
86
248
257
125
62
0
0
1
58
209
45
0
0
143
141
160
325
56
271
262
142
83
0
0
0
0
30
101
90
160
123
103
213
163
160
176
177
123
93
0
0
0
0
62
292
137
150
132
35
265
218
182
137
126
96
92
0
0
0
0
0
150
38
41
17
211
106
26
295
24
44
43
116
0
0
0
0
0
0
164
64
97
14
99
21
27
685
12
46
40
0
0
0
0
0
0
179
10
21
276
120
353
21
119
83
97
68
0
0
0
1
0
0
0
1
9
12
99
184
7
143
9
164
70
1
0
0
0
0
0
0
0
0
0
72
51
4
7
6
8
66
0
0
0
0
0
0
0
0
0
0
71
24
12
2
60
2
69
0
0
0
0
0
0
0
0
0
1
4
5
4
13
0
3
10
UTM Northing
(Continued)
-------
N5
N5
TABLE 1. (Continued)
1400 LST
1UTM
I
=
=
358
1
362
2
366
3
370
4
374
5
378
6
382
7
386
8
390
9
394
10
398
11
402
12
406
13
410
14
414
15
418
16
422
17
426
18
430
19
434
20
438
21
442
22
446
23
3734
3730
3726
3722
3718
3714
3710
3706
3702
3698
3691
3690
3686
3682
3678
3671
3670
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
32
11
75
42
35
30
32
35
14
16
57
24
34
47
20
14
3
94
87
77
68
57
48
53
61
47
19
21
482
18
260
113
82
19
106
99
91
81
71
65
72
77
58
31
5
9
197
78
50
46
27
97
94
88
64
37
156
257
346
46
35
10
3
8
80
59
58
27
63
56
43
12
33
7
18
54
31
14
12
9
0
0
56
65
64
117
115
112
143
38
28
155
99
28
21
18
17
38
0
0
73
23
120
115
111
124
73
75
98
74
27
34
11
47
68
53
0
0
265
151
160
151
152
74
80
83
39
53
33
14
18
31
27
217
0
11
60
31
15
850
103
146
85
87
61
79
34
24
38
55
64
56
62
36
41
14
18
556
39
139
61
33
176
116
25
0
26
45
59
45
J21
103
86
19
26
623
45
104
197
196
160
13
0
250
280
135
41
4
168
95
119
26
0
250
391
205
296
25
0
0
332
351
163
49
0
0
3
319
312
0
0
398
182
252
18
0
135
336
353
178
63
0
0
1
56
197
45
0
0
203
158
157
456
56
362
356
199
83
0
0
0
1
37
116
134
249
128
127
229
249
221
244
248
172
93
0
0
0
1
102
407
108
153
128
50
334
289
261
188
173
135
92
0
0
0
0
0
147
37
41
17
265
151
28
406
27
48
58
115
0
0
0
0
0
0
177
47
111
15
127
22
30
850
14
47
40
0
0
0
0
0
0
233
10
22
346
185
459
23
199
109
132
71
0
0
0
0
0
0
0
1
9
13
136
243
8
189
10
218
77
1
0
0
0
0
0
0
0
0
0
96
76
5
7
6
8
74
0
0
0
0
0
0
0
0
0
0
92
39
18
2
90
3
87
0
0
0
0
0
0
0
0
0
1
5
7
4
18
0
3
14
UTM Northing
(Continued)
-------
TABLE 1. (Continued)
ro
CO
1700 LST
IUTM *
I -
356
1
362
2
366
3
370
4
374
5
378
6
382
7
386
8
390
9
394
10
398
11
402
12
406
13
410
14
414
15
418
16
422
17
426
18
430
19
434
20
438
21
442
22
446
23
3734
3730
3726
3722
3718
3714
3710
3706
3702
3696
3694
3690
3686
3682
3678
3674
3670
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
62
23
110
67
52
47
58
74
33
36
130
55
78
105
44
30
11
129
126
114
104
87
74
90
118
98
39
17
602
32
393
168
121
36
134
130
124
110
95
87
118
147
123
72
13
9
290
126
82
74
44
135
131
120
79
27
107
270
686
103
73
23
6
17
116
94
93
51
92
88
71
14
49
11
25
99
61
24
25
20
0
0
89
103
92
144
150
156
218
40
28
282
201
49
34
36
33
65
0
0
116
50
139
141
147
194
99
106
172
138
47
69
26
75
111
83
0
0
352
183
207
205
219
100
113
146
62
103
72
35
34
60
47
311
0
20
106
64
27
850
204
191
123
138
88
147
74
46
63
92
106
83
88
59
82
31
33
831
77
195
108
70
268
165
55
0
40
72
83
68
190
154
125
41
53
850
91
171
304
298
234
27
0
374
426
205
68
2
221
143
213
55
0
276
628
317
436
45
0
0
497
531
249
79
0
0
1
366
472
0
0
540
277
366
35
0
222
503
534
272
104
0
0
0
51
313
99
0
0
280
189
237
661
111
548
538
301
138
0
0
0
1
47
199
223
364
160
187
335
372
339
367
375
261
145
1
-0
2
1 .
89
584
151
244
220
71
498
434
386
282
261
203
134
0
0
0
0
0
112
83
74
35
386
222
52
602
43
74
49
161
1
0
0
0
0
0
238
83
178
25
192
42
48
850
20
68
38
0
0
0
0
0
0
332
21
38
504
269
680
42
291
164
195
84
0
0
0
0
0
0
0
0
20
23
203
361
14
277
18
319
94
2
0
0
0
0
0
0
0
0
0
142
111
10
14
12
15
89
0
0
0
0
0
0
0
0
0
0
141
60
27
3
137
5
103
0
0
0
0
0
0
0
0
0
2
6
12
8
30
0
5
17
UTM Northing
-------
TABLE 2. CALCULATED HOURLY PARTICULATE CONCENTRATIONS ()Jg/m3) AT 10 METERS ABOVE THE SURFACE.
(See Fig. 6)
0800 LST
1UTM
1
•
=
358
1
362
2
366
3
370
4
374
5
378
6
382
7
386
8
390
9
394
10
398
11
402
12
406
13
410
14
414
15
418
16
422
17
426
18
430
19
434
20
438
21
442
22
446
23
3734
3730
3726
3722
3718
3714
3710
3706
3702
3698
3694
3690
3686
3682
3678
367A
3670
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
73
25
96
67
47
49
67
87
34
36
141
56
80
142
60
43
8
93
111
102
94
74
66
100
147
117
38
14
249
55
163
64
49
40
85
103
102
91
80
80
136
188
157
81
12
7
69
61
43
42
37
75
92
96
72
20
49
144
609
136
83
27
7
19
56
55
58
55
80
97
80
12
49
11
24
103
68
29
30
24
0
0
49
60
65
76
103
120
189
31
24
335
255
45
37
39
33
68
0
0
69
80
69
95
122
200
70
96
208
180
57
88
28
42
74
53
0
0
85
87
152
174
215
75
103
182
67
135
90
36
47
57
81
73
0
0
119
107
30
316
387
106
123
118
90
178
92
64
67
97
113
74
64
65
132
36
38
290
132
152
147
105
90
56
86
0
46
89
73
52
136
159
163
48
61
409
165
157
172
146
88
50
0
200
214
97
59
1
175
207
286
69
0
219
208
157
144
79
0
0
244
259
114
68
0
0
0
172
404
0
0
171
125
123
65
0
119
240
255
125
91
0
0
0
38
368
185
0
0
140
125
264
196
199
263
261
142
127
0
0
0
0
35
210
152
171
193
104
298
141
166
179
174
122
128
1
0
0
0
42
307
178
215
279
60
288
219
173
139
125
93
111
0
0
0
0
0
65
141
107
38
228
103
54
266
42
77
29
119
1
0
0
0
0
0
159
147
223
25
122
43
48
481
19
60
28
0
0
0
0
0
0
146
23
43
315
114
335
43
103
98
93
52
0
0
0
0
0
0
0
0
22
24
114
178
14
162
18
161
50
2
0
0
0
0
0
0
0
0
0
84
51
10
14
13
15
41
0
0
0
0
0
0
0
0
0
0
75
19
12
3
51
5
36
0
0
0
0
0
0
0
0
0
2
2
5
4
13
0
5
5
UTM Northing
(Continued)
-------
TABLE 2. (Continued)
U1
IUIM
I
1100 un
3M
•
1
i
342
2
366
3
370
4
374
5
378
6
382
7
386
8
390
9
394
10
398
11
402
12
406
13
410
14
414
15
418
16
422
17
426
18
430
19
434
20
438
21
442
22
446
23
3734
3730
3726
3722
3718
3714
3710
3706
3702
3698
3694
3690
3686
3682
3678
3674
M70
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
33
11
85
47
39
33
34
36
15
16
62
24
35
50
21
14
4
102
112
101
90
74
61
62
66
47
18
17
538
17
281
113
82
23
105
121
118
109
99
90
95
91
65
33
5
8
138
67
45
43
27
74
81
77
56
34
165
310
456
47
43
9
3
8
91
56
57
38
59
59
44
12
34
8
21
59
40
17
14
10
0
0
50
61
58
117
150
i53
196
49
35
195
108
35
26
19
19
50
0
0
69
28
111
140
147
163
109
111
124
88
34
38
11
45
74
53
0
0
186
125
170
172
185
120
118
106
54
64
36
15
21
27
92
143
0
4
62
35
14
642
165
119
139
114
90
94
36
.25
56
79
88
74
64
40
49
14
17
454
46
167
110
38
144
101
37
0
27
50
72
47
102
100
81
19
26
759
-59
110
191
175
148
13
0
236
255
118
42
3
187
164
155
27
0
479
361
183
238
50
0
0
302
315
139
49
0
0
3
346
535
0
0
486
158
222
22
0
121
299
313
153
63
0
0
1
69
285
44
0
0
192
183
189
410
56
327
318
173
83
0
0
0
1
32
125
119
215
166
128
260
198
196
215
215
150
94
0
0
0
0
70
409
185
188
156
41
329
264
226
170
153
117
93
0
0
0
0
0
170
42
48
17
266
132
27
366
25
46
46
118
0
0
0
0
0
0
220
83
112
14
121
21
27
850
13
52
40
0
0
0
0
0
0
222
10
22
342
147
431
21
145
102
118
69
0
0
0
2
0
0
0
1
9
12
122
222
8
180
10
201
72
1
0
0
0
0
0
0
0
0
0
89
63
4
7
6
8
67
0
0
0
0
0
0
0
0
0
0
87
29
15
2
74
3
71
0
0
0
0
0
0
0
0
0
1
4
5
4
13
0
3
11
MM torthiof
(Continued)
-------
NJ
ON
TABLE 2. (Continued)
1400 LS'f
IUTM
I
=
=
358
1
362
2
366
3
370
4
374
5
378
6
382
7
386
8
390
9
394
10
398
11
402
12
406
13
410
14
414
15
418
16
422
17
426
18
430
19
434
20
438
21
442
22
446
23
3734
3730
3726
3722
3718
3714
3710
3706
3702
3698
3694
3690
3686
3682
3678
3674
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
32
11
76
43
35
30
32
35
15
16
57
24
34
48
20
14
96
100
87
77
65
56
61
68
50
19
21
607
19
388
166
112
108
114
105
93
83
76
85
87
64
33
5
9
244
167
68
63
97
107
99
68
38
180
328
472
47
41
10
3
8
123
79
78
63
64
47
13
34
8
19
56
36
17
13
10
0
0
72
85
121
139
135
173
42
30
180
109
33
25
20
19
50
0
0
95
126
140
135
143
88
92
144
83
32
37
11
58
95
70
0
0
158
199
185
180
93
100
95
47
61
35
14
22
33
34
298
0
60
34
16
850
104
207
113
112
78
91
36
27
45
65
81
70
36
47
14
19
774
41
197
74
34
233
150
26
0
28
51
71
118
125
99
19
27
850
47
130
258
251
203
13
0
303
344
168
•3
243
131
145
27
0
547
679
270
381
25
0
0
402
429
202
0
0
5
457
362
0
0
726
248
331
18
0
206
404
431
221
0
0
2
67
270
44
0
0
284
202
177
574
57
436
434
245
0
0
0
1
39
145
192
360
177
156
277
304
273
301
303
212
0
0
0
0
125
635
130
189
147
60
417
350
325
235
211
166
0
0
0
0
0
158
39
47
17
335
193
29
505
29
51
60
0
0
0
0
0
0
242
50
131
15
157
22
31
850
15
52
0
0
0
0
0
0
294
11
23
428
229
558
23
243
133
160
0
0
0
1
0
0
0
0
9
13
168
294
8
238
11
266
1
0
0
0
0
0
0
0
0
0
118
93
5
7
6
8
0
0
0
0
0
0
0
0
0
0
113
48
22
2
112
3
0
0
0
0
0
0
0
0
0
1
5
8
5
19
0.
3
3670 1 4 19 28 28 66 24 277 11 64 46 42 49 64 84 95 94 117 41 72 78 75 89 14
UTM Northing
(Continued)
-------
TABLE 2. (Continued)
1700 LSI
IUTM - 358 362 366 370 374 378 382 386 390 394 398 402 406 410 414 418 422 426 430 434 438 442 446
I
•
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
3734
3730
3726
3722
3718
3714
3710
3706
3702
3698
3694
3690
3686
3682
3678
3674
3670
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
63
24
112
68
53
48
60
76
33
37
133
56
80
109
45
31
11
131
158
142
132
111
99
117
142
108
40
17
850
34
790
315
213
37
135
167
159
141
126
119.
157
179
144
79
13
9
417
221
142
130
46
133
167
149
83
27
123
366
850
105
92
24
7
18
221
158
156
53
93
110
83
14
52
12
26
103
80
33
30
23
0
0
141
166
95
146
208
219
311
47
30
365
237
64
48
42
41
97
0
0
183
51
141
195
205
245
138
154
222
170
63
83
27
110
200
136
0
0
373
187
289
283
288
148
166
184
88
131
83
36
39
85
52
562
0
21
109
75
28
850
211
326
175
212
133
188
84
.56
88
122
150
116
91
60
100
31
35
850
83
330
134
73
48
263
59
0
45
90
114
70
187
224
163
42
55
850
97
247
484
456
348
28
0
509
596
297
68
2
396
208
296
59
0
700
850
514
668
46
0
0
671
736
363
80
0
0
3
663
565
0
0
850
468
581
36
0
470
676
742
396
105
0
0
1
63
500
100
0
0
482
274
293
850
113
735
746
431
140
0
0
0
1
50
295
420
689
246
259
451
523
487
527
525
371
148
1
0
0
0
120
850
167
360
272
96
706
590
552
405
364
287
137
0
0
0
0
0
138
96
93
35
566
332
53
850
44
79
50
165
1
0
0
0
0
0
389
104
234
25
273
43
49
850
21
79
39
0
0
0
0
0
0
493
22
40
713
387
850
42
410
220
268
86
0
0
0
1
0
0
0
0
21
23
288
481
14
401
18
436
97
2
0
0
0
0
0
0
0
0
0
199
154
10
14
13
15
92
0
0
0
0
0
0
0
0
0
. 0
195 '
85
38
4
195
5
106
0
0
0
0
0
0
0
a
0
2
5
13
8'
30
0
5
18
IffN Northing
-------
A number of parameters were varied in the model study. Two mean
particle sizes were used for the suspended particles: 5 ym equivalent
diameter and 20 urn equivalent diameter. Wind speeds were varied as Ix, 2x,
and 4x the wind vector components of Herman and DeLaney (10). The model runs
presented cover the time 0600 - 1900 LST during which constant daytime wind
fields (10) were used. Obviously this procedure is not correct, but suitable
for the purposes of our model studies. Finally, identical runs were carried
out with gravitational sedimentation and dry deposition "switched off" and
"switched on" according to current estimates (14).
Figs. 4 to 11 give these model studies for the hourly average particle
concentrations at 10 m. from 0800 to 1700 LST. Tables 1 and 2 give a
quantitative assessment of particle concentration values indicated in the
Fig. 4 and Fig. 6. The height above the baseline surface in these figures
is proportional to the particle concentration. In the figures, the maximum
2
particle concentration shown is 850 yg/m .
In considering the information presented in the figures, the very
complex topography and wind fields in Maricopa County must be kept in mind
(see Figs. 1 to 2). Some of the results are not intuitively obvious and arise
from the complex dynamical relationships between source strength variation
in space and time, advection, vertical dispersion, sedimentation, and dry
deposition.
Several features are common to all model runs. Outstanding is the
somewhat localized nature of particle concentration maxima. Maxima tend to
remain centered over their initial positions during the course of the day.
This behavior is attributed* to the relatively low wind speeds studied and to
the relatively rapid vertical transport and deposition processes.
In some cases, near the base of North Mountain for example, there is
evidence of advective transport and accumulation of dust. However, on the
whole, large amounts of dust do not appear to be advected for distances
greater than a few grid squares (4 km. x 4 km.). Another feature is the
monotonic growth of most of the maxima during the course of the day. However,
some of the maxima tend to decrease after 1000 or 1100 LST and to increase
again after 1500 or 1600 LST owing to the particular nature of the sources
28
-------
at these locations. For a pollutant such as CO, which is almost entirely
derived from automotive emissions, the hourly variation of traffic density
combines with the increase in mixing height during the first part of the
day to give a variation of CO concentration with time. This variation con-
sists of two maxima and a minimum in the mid-afternoon (10). For dust, over
60% of the estimated emissions are not related to traffic, there is not a
pronounced mid-afternoon mim-iTTmin in dust emissions. Also, our emissions
data are averaged over a 4 km. x 4 km. grid and do not reflect specific
roadside concentration levels. The minimum mixing height assumed is 130 m.
so that there is not a dramatic change in dust concentration at 10 m. as the
mixing height increases during the first part of the day. As will be
apparent later, however, such dramatic changes do occur in the dust concen-
tration at greater heights above the surface.
The results of these computer runs are in qualitative agreement with
available data (9). For example, it was observed (9) that the average
surface (10 m.) particulate mass concentrations at Chandler during the late
November 1975 IITRI field study were approximately twice those found in
Phoenix. In addition, the average experimental values for mass concentration
3 3
reported (9) for Phoenix (203 yg/m ) and Chandler (431 yg/m ) are in approxi-
mate comparison with the calculated results of runs 298.and 300, given in
Tables 1 and 2. Owing to insufficient data, we have carried out model
studies and did not attempt to simulate exactly the complex meteorological
conditions that occurred during the IITRI study.
EFFECT ON 10 m. DUST CONCENTRATION OF VARIATION IN MEAN PARTICLE SIZE
Comparison may be made between runs 298 and 300. Run 298 assumes mean
suspended particle diameter of 5 urn, the wind field (Ix) of Berman and
DeLaney (10), and the presence of gravitational sedimentation and dry
deposition (14). Run 300 only differs from 298 in the assumption of me«p.
suspended particle diameter of 20 ym. Examination of Figs. 4 and 6 shows
that dust concentrations during the day at 10 m. are higher for the 20 ym
mean diameter than for 5 ym. This difference is greater over populated
areas (such as Phoenix) where the macro-scale surface roughness is high,
with a resultant increase in vertical transport rates. These increased
rates tend to magnify the effects of the different sedimentation rates on
29
-------
the 10 m. dust concentrations for 5 ym and 20 ym particles. Outside the
built-up areas, the 10 m. dust concentrations for 20 ym mean diameter
particles (run 300) are only slightly greater than those for 5 ym (run 298).
EFFECT ON 10 m. DUST CONCENTRATION OF VARIATION IN WIND SPEED
Wind speed is varied for fixed particle size (5 ym) with deposition and
gravitational sedimentation shown in Figures 4 and 10 (runs 298 and 306).
The latter run is for a wind field exactly twice that of the former. The
increased wind field means that the friction velocity is increased, which
has the effect of increasing the vertical dispersion rate. Intercomparison
of hourly values for runs 298 and 306 shows that the concentration levels
for run 298 are usually somewhat larger than for run 306. The increased
vertical dispersion and deposition rates for run 306 lowers the 10 m. dust
concentrations relative to those for run 298. An analogous comparison is
afforded by the results of Figures 6 and 11 (runs 300 and 307) for 20 ym
mean particle size. 10 m. particle concentrations are much greater for run
307 which has twice the wind speed of run 300. The explanation for the
larger concentrations is related to the complex interrelationships of source
strength, surface roughness, advective wind field, and gravitational
sedimentation.
This result is opposite to that found for runs 298 and 306 for 5 ym
particles. The difference arises in that for the 5 ym particles, gravita-
tional sedimentation is of minor importance. For 20 ym particles, gravita-
tional sedimentation is critical and its interaction with the other processes
produces the differences found between runs 300 and 307-
EFFECT ON 10 m. DUST CONCENTRATION OF DEPOSITION AND GRAVITATIONAL SEDIMENTATION
These effects are closely related to particle size. Consider runs 298
and 299 for 5 ym particles with and without deposition and gravitational
sedimentation. Relative to advective and vertical transfer rates, gravita-
tional sedimentation is negligible for 5 ym particles. Hence, only deposi-
tion at the surface is of importance. Therefore, the 10 m. dust concentrations
for run 298, where deposition and sedimentation occur, are slightly lower
than those for run 299 where these processes are absent. For 20 ym particles,
30
-------
gravitational sedimentation is a very important process and the analogous
comparison for 20 um particles is quite different.
Runs 307 and 304 for 20 pm particles compare 10 m. dust concentrations
with and without deposition and gravitational sedimentation. In this case
the inclusion of gravitational sedimentation results in much higher 10 m.
dust concentrations (run 307) than found neglecting this process (run 304).
A'study of the variation of the dust concentration with height provides
considerable insight into the dynamics of dust transport. Figs. 12 to 17
3
give dust concentration isopleths in ug/m in a plane perpendicular to the
surface extending in an easterly direction from Tolleson to just east of
Scottsdale (see map, Fig. 1). The heights indicated in these figures refer
to height above the surface. In this plane, the surface rises to the east
from 305 m. (1000 ft.) above sea level at Tolleson to 366 m. (1200 ft.) above
sea level at Scottsdale. This particular plane was chosen to correspond to
the IITRI study regions. The plane includes Phoenix and Scottsdale and
avoids the mountainous terrain which would be encountered by a plane running
north-south and ineluding Phoenix. One example of a north-south plane is
included (Fig. 17). Its interpretation is difficult because of the mountains
immediately north and south of Phoenix.
Discussion will be centered here on Figs. 11 to 16 where the effects of
various parameters on the vertical dust concentration profile are studied.
The complex surface wind patterns must be noted, Fig. 1. During the day,
the general trend in this region is flow from west to east.
Figs. 11 to 16 show a pronounced •nrtn-tmimi in dust concentration with
height at a DTM Easting of around 394 . Several factors produce this
ooo
behavior. First, the area source emission strength in this region is almost
one—half that of the areas immediately east and west. Second, based on
Herman and DeLaney's wind field data (10), the advective flow into this
region is so small that the neighboring stronger dust sources have no effect
on the dust concentration at 394 . Finally, the roughness, z , is small
for this region in comparison with, for example, z for Phoenix (> 396 );
o ooo
this leads to small rates of vertical transport.
31
-------
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-------
Figs. 11 to 16 show a rapid rise in dust concentration with height
once the area of Phoenix is entered (UTM Easting 396 - 402 ). This
0 ooo ooo
is due to greatly increased source strengths in the city proper and also to
larger values of roughness z over the city. The increased surface roughness
has the effect of increasing the rate of vertical transport and reducing the
advective wind. There is very little evidence in these results of advective
transport of dust from outside the city.
The rapid drop in vertical dust concentration for UTM Easting greater
than around 418 is notable. This drop is due to the rapid decrease in
ooo
roughness, z , and to a decrease in local source strength; also increased
deposition over the urban areas just to the west has decreased advective
dust transport from these urban areas to the east of 418
ooo
The effects on the vertical dust concentration profile of various
model parameters can now be examined.
THE EFFECT OF ROUGHNESS, z , ON VERTICAL DUST CONCENTRATIONS
This, together with source strength, constitutes one of the decisive
parameters in determining vertical concentration profiles. Its role has
been indicated in the preceding discussion.
THE EFFECT OF DEPOSITION AND GRAVITATIONAL SEDIMENTATION ON VERTICAL DUST
CONCENTRATIONS
This is shown clearly in Figs. 12 and 13. The expected effect of
deposition and gravitational sedimentation is to lower the vertical dust
concentrations above a certain height. This effect is more important over the
urban areas with higher surface roughness and is more important for 20 ym
particles.
THE EFFECT OF MEAN PARTICLE SIZE
Figs. 12 and 15 compare mean particle sizes of 5 ym and 20 ym,
respectively. As would be expected, larger dust concentrations are found
for 20 ym particles than for 5 ym particles below around 200 m. height,
and smaller concentrations above 200 m. This effect of gravitational sedi-
mentation is much more pronounced over the urban areas with higher surface
38
-------
roughness, z , and hence larger rates of vertical transport. This leads
also to an alteration in the isopleths as shown in Figs. 12 and 15.
THE EFFECT OF WIND SPEED ON VERTICAL DUST CONCENTRATIONS
In Figs. 15 and 16 the general forms of the isopleths are similar, the
latter representing the assumption of twice the wind field of the former.
For the higher wind field, the vertical dust concentrations are greater at
all heights. This is because greater vertical transport rates are associated
with higher wind speeds. With higher wind speeds, advective dust transport
is important; this is shown downwind of the urban regions for DTM Easting
greater than 418 ___.
THE EFFECT OF TIME OF DAY ON VERTICAL DUST CONCENTRATIONS
In comparing Figs. 14 and 15 for 800 and 1100 LSI, respectively, one
sees a decisive difference in the isopleths over the urban area for these
two cases. The 0800 case shows much less variation over the urban areas
(398 to 418 ) in the isopleths flmm for 1100. At 0800 the mixing height
is small; this reduces the role of vertical transport. The advective winds
for 0800 tend to "smooth" the isopleths over the urban area and produce
somewhat greater uniformity at a given height. Also, at 0800 the sources
have only recently been turned to their daytime values, and the dust concen-
trations aloft do not yet reflect the greatly increased day-time dust emission
rates over the night-time values. By 1100 LST the mixing height approaches
the maximum value and the increased day-time source emissions show up in the
higher vertical dust concentrations.
39
-------
SECTION 5
CONCLUSIONS
1. Observed high particulate concentrations in urban areas of
Maricopa County during late fall and winter periods of atmospheric stability
are associated with large local sources; because of the light drainage winds
prevalent in late fall and winter in Maricopa County, the advective trans-
port of dust from the countryside to the urban areas is not an important
contribution to the urban dust loading.
2. Surface roughness and dry deposition, along with source strengths,
are among the most important determinants of ground level particulate con-
centrations. Steps to reduce dust emissions in regions of high ambient
particulate concentration would be one obvious remedy. Addition of trees
and other foliage to increase surface roughness and deposition rates would
also lower ground-level dust concentrations.
3. During late fall and winter periods of atmospheric stability,
extremely large dust concentrations are found in a few areas where large
local sources occur in conjunction with very low advective wind speeds.
Paradise Valley is one example of such a situation.
Additional study is needed to perfect our particulate model of
Maricopa County. The inadequacy of the available data prevent any
quantitative, detailed test of our model. The available data were obtained
by different investigators at different times and frequently with inadequate
specification of meteorological conditions. Detailed knowledge of particle
size distribution for the ambient aerosol and for the sources was lacking.
However, results achieved with our current crude data base are encouraging.
This leads to our view that an adequate and practical predictive model, along
the lines suggested here, could be developed for Maricopa County as well as
for the other urban areas in the high desert regions.
40
-------
REFERENCES
1. Middleton, P. and Brock, J.R. Simulation of Aerosol Kinetics.
J. Colloid and Interface Sci.
2. Suck, S.H., Middleton, P., and Brock, J.R. On the Multimodality of
the Atmospheric Aerosol. Atmos. Environ. (In Press)
3. Middleton, P. and Brock, J.R. Modelling the Urban Aerosol. (To
Appear.)
4- Brock, J.R. Processes, Sources and Size Distributions. In: Fogs
and Smokes, Discussions of Faraday Society, London, 1974.
5. Lamb, R.G. 1973. Note on Application of It-Theory and Turbulent
Diffusion Problems Involving Chemical Reaction. Atmos. Environ.
7:234.
6. Suck, S.H. and Brock, J.R. (To Appear.)
7. Shir, C.C. and Shieh, L.J. Development of Urban Air Quality Simulation
Model with Compatible RAPS Data. Final Report, Contract 68-02-1833,
IBM Research Laboratory, San Jose, California, May 1975.
8. TRW, Inc. Maricopa Co. Source Inventory, Personal Communication.
9. IITRI Report No. C633C05-2, Field Air Sampling Study. Phoenix,
Arizona. April 1976.
10. Berman, N.S. and DeLaney, K.6. Atmospheric Modelling for Phoenix.
Arizona Engineering Research Center Technical Report ERC-R-75009,
May 1975.
11. U.S. Geological Survey, Map NI12-8, 1954.
12. U.S. Geological Survey, Map NI12-7, 1954 (Revised 1969).
13. Middleton, P. and Brock, J.R. Atmospheric Aerosol Dynamics: The
Denver Brown Cloud. Denver Air Pollution Study - 1973, EPA Report
EPA-600/9-76-007a, June 1976.
41
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
EPA-600/3-79-082
3. RECIPIENT'S ACCESSION-NO.
4. TITLE AND SUBTITLE
5. REPORT DATE
September 1979
DUST TRANSPORT IN MARICOPA COUNTY, ARIZONA
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
S. Suck, E. Upchurch and J. Brock
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
University of Texas
Department of Chemical Engineering
Austin, Texas 78712
10. PROGRAM ELEMENT NO.
1AA603 AE-09 (FY-77)
11. CONTRACT/GRANT NO.
803660
12. SPONSORING AGENCY NAME AND ADDRESS
Environmental Sciences Research Laboratory - RTF, NC
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
13. TYPE OF REPORT AND PERIOD COVERED
Final 12-75 - 12/77
14. SPONSORING AGENCY CODE
EPA/600/09
15. SUPPLEMENTARY NOTES
16. ABSTRACT
Numerical simulations have been carried out for ambient air, supermicrometric
particulate concentrations in Maricopa County, Arizona during late fall and winter
periods of atmospheric stability. Results of model studies are in approximate
agreement with limited field observational data. On the basis of the model studies,
observed high particulate concentrations in Maricopa County urban areas during late
fall and winter periods of atmospheric stability are associated with local fugitive
dust sources. Because of light drainage winds prevalent during these periods,
advective transport of dust from countryside to the urban areas is not an important
contribution to urban supermicrometeric particulate concentrations. Surface rough-
ness, dry deposition, and source strengths are among the most important determinants
of ground level concentrations. Reduction in ground level concentrations could be
effected through control of dust emissions, as well as by planting trees and other
foliage to increase surface roughness and particle deposition. An adequate and
practical predictive model, along the lines of the current model, could be developed
for Maricopa County as well as for other urban areas in high desert regions.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.lDENTIFIERS/OPEN ENDED TERMS
c. COSATI Field/Group
*Air pollution
*Dust
*Sources
*Atmospheric circulation
*Mathematical models
*Surface roughness
Maricopa County, Arizona
13B
11G
04B
12A
18. DISTRIBUTION STATEMENT
RELEASE TO PUBLIC
19. SECURITY CLASS (ThisReport)
UNCLASSIFIED
21. NO. OF PAGES
50
20. SECURITY CLASS (Thispage)
UNCLASSIFIED
22. PRICE
EPA Form 2220-1 (9-73)
42
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