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operations are 336-,000 tons/year (Table 4.8-1, Volume I). If the net
control is 20$, the emissions < 3 p, are estimated to be
(.v>36,000 tons/year)(1-0.20)(0.37) •= 99,000 tons/year
However, this number may be erroneous because the limited information on
control procedures for these sources obtained during the survey of the lime
industry indicated that many of these sources are controlled with fabric
filters. Therefore, net control of these sources may be closer to 80$ and
the fine-partiele emissions about 25,000 tons/year.
7.2.9 Secondary nonferrous metallurgy; Particle-size distribu-
tions from either uncontrolled or controlled sources are meager for all pro-
cesses in secondary nonferrous metallurgy. Information on degree of appli-
cation of control js also meager for all sources. Available particle-size
data for all the specific sources listed under the secondary nonferrous
metallurgy category in Table 4.1-1, Volume I, indicate that uncontrolled
sources emit nearly 100$ < 2 p,.i§/ Therefore, a gross estimate of fine-
particle emissions from secondary nonferrous metallurgical operations is
127,000 tons/year. The number of particles emitted that are < 2 y, in
diameter is estimated to be 7.85 x 1021 particles/year.
7.2.10 Carbon black: The particle size of carbon black particles
is 0.01-0.4 p, in diameter.16/ Therefore, the total mass emissions (93,000
tons/year) listed in Table 4.1-1, Volume I, are also the fine-particle
emissions. The number of particles emitted that are < 2 p, in diameter
is estimated to be 1 x 10^2 particles/year.
7.2.11 Coal preparation plants: Thermal dryers are the only
particulate emission source in coal preparation plants for which adequate
data were available to permit an estimate of fine-particle emissions. The
fine-particle emissions from thermal dryers were calculated using an emis-
sions factor of 12 Ib/ton following the primary cyclones, and available
extent of control information.i/ Information on control of thermal dryers
indicates that all plants are equipped with primary cyclones, and that 85$
of the production is also equipped with wet scrubbers following the primary
cyclones. The available particle-size data for thermal dryer effluents
shown in Figure 43 indicate that the particles exiting the primary cyclone
average about 40$ < 3 (j,.
Using the emission factor of 12 Ib/ton, the total particulate
emitted from the primary cyclones was calculated to be 438,000 tons/year.
Since 15$ of the production is not equipped with additional control devices,
the total emissions from these units were calculated to be 65,700 tons/year
with 40$ of the quantity, or 26,300 tons/year, being < 3 p,.
107
-------
to
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40
20
9
'<&£* OUTLET FROM
VT C?
MAIN CYCLONE
0.01 0.2 2 20 50 80 96 99.8 99.99
% LESS THAN STATED SIZE (WT. %)
Figure 43 - Particle-Size Analysis for Particulates Emitted from Coal
Thermal Dryersi§/
The remaining 85$ of the production, which accounts for 372,300
tons/year emissions from the primary cyclones, is controlled with wet
scrubbers. Assuming that the wet scrubbers are "medium" efficiency scrub-
bers, and that the penetration for < 3 p, particles was 25%, fine-particle
emissions were calculated to be 37,200 tons/year. Therefore, the total
fine-particle emissions from thermal dryers are:
Plants controlled with cyclones = 26,300 tons/year < 3 p,
Plants controlled with cyclones and scrubbers = 57,200 tons/year < 5 p,
Total fine-particle emissions = 63,500 tons/year < 3 y,
The 63,500 tons/year represent 67.5$ of the total mass emission for thermal.
dryers reported in Table 4.1-1, Volume I.
The number of particles emitted that are < 3 p, in diameter is
estimated to be 3.9 x 1021 particles/year.
108
-------
7.2.12 Petroleum refineries; Catalyst regenerators, boilers,
process heaters, decoking operations, and incinerators are sources of par-
ticulate pollution. Meager particle-size data exist for all uncontrolled
sources, and only an estimate of fine-particle emissions from catalyst
regenerators was made.
Figure 44 summarizes available particle-size distribution data
from eight uncontrolled FCC units. In order to use this particle-size
data to calculate fine-particle emissions, it is necessary to know the
quantity entering the cyclones. The total mass emissions of 45,000 tons/
year from FCC units (Table 4.1-1, Volume I) was calculated on the basis of
an emission factor for controlled FCC units. Assuming that all FCC units
are equipped with 80$ efficiency cyclones, the quantity of particulate
material entering the cyclones is 225,000 tons/year.
Using the inlet rate of 225,000 tons/year, the particle-size data
in Figure 44, and the fractional efficiency curve for a high efficiency
cyclone (Figure 17), fine-particle emissions were calculated to be 56,600
tons/year. This figure exceeds the total mass emission of 45,000 tons/year.
However, in view of the assumptions in the calculations, the difference in
the emissions is not considered significant, and fine-particle emissions
are assumed to equal the total mass emissions of 45,000 tons/year.
The number of particles emitted that are < 2 p, in diameter is
estimated to be 3.7 x 1021 particles/year.
7.2.13 Fertilizer and phosphate rock; Particulate emissions
from the processing of phosphate rock and from fertilizer manufacturing
originate from dryers, roasters, digesters, granulators, and coolers.
Particle-size distributions were obtained only for granulators and dryers
used in the manufacture of phosphate fertilizers. Figure 45 presents the
particle-size data for these sources. The data were obtained from eight
individual fertilizer plants.
Because of the lack of adequate particle-size distribution data
for the other sources, estimates of fine-particle emissions were made only
for the granulators and dryers. Fine-particle emissions from the granu-
lators and dryers are estimated to be 13,700 tons/year as shown in Table 15.
Details of the calculations are given in Tables E-22 to E-25, pages 251 to
254. This represents about 8$ of the total mass emissions reported for
these sources in Table 4.1-1, Volume I.
7.2.14 Iron foundries: The iron melting process in foundries is
the principal source of particulate emissions. Cupola, electric arc, elec-
tric induction, and reverberatory air furnaces are used to obtain the molten
metal. Secondary sources of particulates include materials handling, cast-
ing shakeout systems, buffing and grinding operations, and core ovens.
109
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Figure 44 - Particle-Size Distribution of Particulates Emitted from
Petroleum FCC Units (cyclone inlet, Banco data)
110
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100
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n nil I I I I I I 1 I
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WEIGHT % LESS THAN STATED SIZE
Figure 45 - Particle-Size Distribution of Particulates Emitted from
Uncontrolled Fertilizer Dryers (Banco data)
111
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Particle-size distributions, emission factors, and degree of application of
control information were available only for the cupola furnaces, and esti-
mates of. fine-particle emissions were confined to that source.
Table 16 summarises Cine-particle cmluuiona from cupola.';. Uota'drj
of the calculations are given in Tab lee E-44 to E-49, pages 273 to WV. The
13,100 tons/year of fine particulate matter comprises approximately 12.5$
of the total mass emission from these furnaces (Table 4.1-1, Volume I).
Available particle-size data for uncontrolled cupolas are presented in
Figure 46. The data in Figure 46 were obtained from 25 individual cupola
7.2.15 Acids;
7.2.15.1 .Sulfuric acid; Chamber plants are uncontrolled,
and the particles emitted from these plants are typically 90-96$ < 3 jj,.*y
Total mass emissions from chamber plants are only 2,000 tons/year.. Fine-
particle emissions are estimated to be 5% of this total, or 100 tons/year.
The available particle-size data for effluents from contact
plants show that 65 wt. $ are < 3 y,. Since the control devices normally
remove mostly larger particles, it is estimated that at least 65 wt. % of
the total emissions of 4,000 tons/year, or 2,600 tons/year, are < 3 p,.
Fine-particle emissions from spent acid concentrators were
not estimated because of inadequate particle-size data. The number of par-
ticles emitted from sulfuric acid plants that are < 3 p, in diameter is
estimated to be 3.4 * 1020 particles/year.
7.2.15.2 Phosphoric acid—thermal process; Particle-size
data for thermal-process phosphoric acid plants indicate that particulate
effluents are 50 wt. % < 1.6 p,. The only estimate of fine-particle emis-
sions that can be made is that at least 50$ of the total emissions of
2,000 tons/year, or 1,000 tons/year, are < 1.6 p,.
The number of particles emitted that are < 3 p, in diameter
is estimated to be 1.2 x 10^ particles/year.
7.2.16 Frimary nonferrous metallurgy; No estimate was made for
fine-particle emissions from primary nonferrous metallurgy sources. Very little
particle-size data are available for the many varied sources within each of
the primary nonferrous groups. These sources range from copper reverbera-
tory furnaces (51$ < 37 p,) to zinc sintering machines (100$ < 10 p,). The
variability of the operations and the inadequate particle-size data do not
permit even a generalization as to percent < 2 p,.
Furthermore, the extent of control information for the many pri-
mary nonferrous operations has only fair reliability, and this would fur-
ther decrease the accuracy of any estimation of fine-particle emissions.
113
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Figure 46 - Particle-Size Distribution of Particulates Emitted from
Uncontrolled Iron Foundry Cupolas (Banco data)
115
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7.2.17 Clay products; No calculations for fine-particle emissions
from clay product manufacturing could br> made because of inadequate particle-
size and .'ipplicntlon-of-control data J'or all iiourcoo.
7.2.18 Operations related to agriculture; No estimates of fine-
particle emissions were made for this category because of lack of particle-
size distribution data for nearly all individual sources.
7.2.19 Municipal incineration; Municipal incineration is not
strictly an industrial source of particulate air pollutants, but it produces
significant quantities of fine-particle emissions and has been included in
Tables 1 and 2.
Estimates of fine-particle emissions from municipal incineration
are presented in Table 17. Fine-particle emissions are estimated to be
36,400 tons/year, which is about 37$ of the total mass emissions reported
for this source in Table 4.1-2, Volume' I. Details of calculation of fine-
particle emissions are given in Tables E-68 to E-73, pages ?97 to 302.
Particle-size distribution data for uncontrolled incinerators are
shown in Figure 47. The data in Figure 47 were taken from Ref. 18.
Before calculating fine-particle emissions it was necessary first
to calculate total mass emissions, before any control devices. This was
computed to be 240,000 tons/year based on incineration of about 20 x 10
tons/year of waste^l/ and an emission factor of 24 Ib/ton reported in a
study conducted by A. D. Little for APCO.^2/ This same study also provided
the information on percent application of control.
7.3 Fine-Particle Emissions from Mobile and Miscellaneous Sources
To indicate the relative magnitude of the fine particulate prob-
lem from stationary sources, fine-particle emissions were also estimated
for mobile and miscellaneous sources.
7.3.1 Mobile sources; Particulate emissions from mobile sources
were assumed to be uncontrolled and to consist of all < 2 p, particulate.
Table 4, page 10, summarizes the estimate of fine-particle emissions from
these sources.
7.3.2 Miscellaneous sources; Table 5, page 10, presents an
estimate of fine-particle emissions from miscellaneous sources for which
adequate particle size data were available. Fine-particle emissions from
natural dusts, forest fires, and agricultural burning could not be esti-
mated because of lack of reliable particle size data.
116
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Figure 47 - Particle-Size Distribution of Particulates Emitted from
'Uncontrolled Municipal Incinerators (Banco data)
118
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8. Projections of Fine-Particulate Emissions to the Year 2000
8.1 Mass Basis
Projections of fine-particle emissions through the year 2000 were
performed for those sources for which adequate particle-size distribution
data and information on application of control devices were available. Two
projection methods were used which are similar to Method 1 and Method 5
previously described in Volume I. The first method reflects no change in
control,while the other method reflects establishment of controls on all
sources by 1980 and an increasing use of the most efficient control devices.
Method 1 - The projection of emissions by Method 1 assumes that
there will be no change in the net control for a source. This means that
the emissions increase in proportion to increases in production capacity.
Production figures were projected by the same methods outlined in Volume I,
and were used to proportionally increase the current mass of fine-
particle emissions. An example of the calculation method is given in Table
18.
TABLE 18
PROJECTIONS OP FINE-PARTICLE EMISSIONS FOR ASPHALT DRYERS
Year
1968
1970
1975
1980
1985
1990
1995
2000
Production
106 Tons/Year
251
274
333
406
498
610
747
915
(Method 1)
Production
Ratio
1.00
1.09
1.33
1.62
1.98
2.43
2.98
3.65
Fine Particle Emissions
(tons /year)
154,200
168,100
205,100
249,800
305,300
374,700
459,500
562,800
Method 2 - The projection of emissions by Method 2 also takes
into account the increases in production, but two assumptions are also made:
1. All sources will be controlled by 1980; i.e., application of
control will reach 100$ by 1980.
119
-------
2. Increased utilization of the most efficient control devices
will continuously increase the efficiency of control on fine particles so
that by the year 2000 it will be equivalent to controlling all sources with
baghouses.
The fabric filter was selected as a reference standard of per-
formance because it is one of the most efficient devices available today
for collecting fine particulates. It seems realistic to assume that
improvements in the other control devices and possible development of new
devices would allow the efficiency of control, in the year 2000, to match
the performance capability of the best devices that are presently available.
The calculation of projected fine-particle emissions by Method 2
uses the present average efficiency of control on fine particles as a start-
ing point. Therefore, the first step in this method is the back calcula-
tion of the average efficiency of control on fine particles as shown in the
example for asphalt dryers, Table 19.
TABLE 19
CALCULATION OF AVERAGE EFFICIENCY OF CONTROL
FOR FINE PARTICLES FROM ASPHALT MYERS
(Method 2)
1968 Total Production = 251 x 10^ tons/year
Emission Factor = 32 Ib/ton
Process Emissions = 15.5$ < 3 p,
Fine Particle Emissions = 154,200 tons/year
Application of Control = 99$
Calculation of Average Efficiency of Control for Fine Particles (x):
(251 x 106)f gooo J(15.5$)(1 - 0.99x) = 154,200
1 - 0.99x = 0.248
0.99x = 0.752
x = 0.76
Average Efficiency of Control for Fine
Particles from Asphalt Dryers = 76$
120
-------
The second step in the calculations is to determine the efficiency
of control on fine particles using a baghouse. This is based on the particle-
size distribution of the process emissions and the fractional efficiency
curve for a fabric filter as shown in Table 20. The value computed is
assumed to represent the efficiency of control for the source in the year
2000. The efficiency of control for the intervening years is increased
linearly from the present value to the efficiency calculated for the year
2000.
TABLE 20
CALCULATION OF AVERAGE EFFICIENCY OF CONTROL ON FINE
PARTICLES FOR FABRIC FILTER ON ASPHALT DRYER
Basis: 100 Ib. of process emission
15.5$ < 3 (j,
Fine Particle Process Emission - 15.5 Ib.
Size Fabric Filter Fine Particle
Range (p.) # Penetration (%) . Emission
1-3 12.6 0.5 0.06
0.5-1.0 2.18 1.8 0.04
0.1-0.5 0.71 3.3 0.02
0.12
Average Efficiency of Fabric Filter on Fine Particles = " — = 99.2$
-LO • O
Method 2 also assumes that the application of control increases
linearly to 100$ by 1980, as shown in Table 21. Table 21 also summarizes
the variables used to calculate the projected emissions of fine particles
for asphalt dryers. The calculation of the projected fine-particle emis-
sions for asphalt dryers is illustrated in Table 22.
121
-------
TABLE 21
VALUES USED IN CALCULATION OF PROJECTED FIKE-PARTICLE
EMISSIONS FOR ASPHALT DRYERS
(Method 2)
At Present, Application of Control = 99$
Efficiency of Control on Fine Particles = 76%
Production Application of Fine-Particle Efficiency
Year (tons/year) Control (%) of Control
1968 251 X 106 99 76
1970 274 x 106 99.1 77.5
1975 333 X 106 99.6 81.2
1980 406 x 106 100 84.9
1985 498 x 106 100 88.6
1990 610 X 106 100 92.3
1995 747 X 106 100 96.0
2000 915 X 106 100 99.2
TABLE 22
PROJECTIONS OF FINE-PARTICLE EMISSIONS FOR ASPHALT DRYERS
(Method 2)
Year Calculation
1968 (251 x 106)(-~-)(0.155)[l - (0.99)(0.76)] = 154,200 tons/year
\ 2000/
1970 (274 x 106)(-^-)(0.155)[l - (0.991)(0.775)] = 157,600 tons/year
\ 2000/
1975 (333 x 106)(-^-Vo.l55)[l - (0.996)(0.812)] = 157,700 tons/year
»2000/
1980 (406 x ,106)( -2=-) (0.155) (1 - 0.849) = 152,000 tons /year
\2000'
1985 (498 x 106)(-^-)(0.155)(l - 0.886) = 140,800 tons/year
\cOOO/
1990 (610 x 106)(-^-)(0.155)(l - 0.923) = 116,500 tons/year
1995 (747 x j!06)(-^-Vo.l55)(l - 0.960) = 74,100 tons/year
V 2000/
2000 (915 x 3.06)(-^-)(0.155)(l - 0.992) = 18,200 tons/year
»2000'
122
-------
Table 6, p. 13, and Figures 48 to 65 summarize the projections
of fine-particle emissions on a mass basis. Fine-particle emissions for
the sources listed in Table 6 can be reduced from 3.5 x 106 tons/year (1968
emission level) to 3.5 x 105 tons/year by the year 2000 if the efficiency
of control on all these sources in the year 2000 is equivalent to perfor-
mance of the best device currently available (i.e., baghouse). The projec-
tions also show that, even if stringent control is achieved in the year
2000, coal-fired power plants, basic oxygen furnaces, and kraft pulp mill
recovery furnaces will each emit over 50,000 tons/year of < 2 p, particulate.
The calculation methods described above involve many assumptions
and the two projection methods represent two extremes; that is, no improve-
ment in control versus increasingly stringent controls. However, even with
the assumptions involved, the calculation methods must be based on knowledge
of the particle-size distribution for the specific uncontrolled source and
on information regarding the percent application of each type of control
device on the specific source. Without this information, it is very diffi-
cult to estimate, with any reliability, the present level of fine-particle
emissions, and any attempt to make projections of these emissions wouM be
of little value. For this reason, projections of fine-particle emissions
were made only for those sources for which adequate particle size dis-
tribution data and percent of application of each major type of control
device were available.
8.2 Number Basis
The number of fine particles emitted to the year 2000 by sta-
tionary sources was projected by two methods that are extensions of the
techniques used to project mass emissions. The first method assumes no
change in the net control from 1968 to 2000 which means that the number
emissions, as were the mass emissions, are directly proportional to the
projected production capacities. Method 2 utilizes the mass emissions pro-
jected by the second technique discussed in Section 8.1 and an assumption
regarding the average diameter of fine particles emitted from sources in
future years. The two methods are discussed in more detail in the follow-
ing paragraphs.
Method 1 - This method is the same as Method 1 for the projection
of mass emissions. Therefore, the number of particles emitted increases in
direct proportion to increases in production capacity. Projected produc-
tion figures, reported in Ref. 1, were used to proportionally increase the
current number of fine particle emissions (Table 2). An example of the
calculation method is given in Table 23.
123
-------
2.0
1.5
I
O
i i.o
a
u
0.5
I I
COAL-FIRED ELECTRIC UTILITY
2.38 IN YEAR 2000
A METHOD 1
O METHOD 2
_L
1968 1970
1975
1980
1985
YEAR
1990
1995
2000
Figure 48 - Projections of Fine-Particle Emissions from Electric Utility
Coal-Fired Power Plants
124
-------
0.20
0.15
i o.i
Of
<
Q.
UJ
0.05
oU
COAL-FIRED INDUSTRIAL POWER
A METHOD 1
O METHOD 2
1968 1970 1975
1980
1985
YEAR
1990 1995
2000
Figure 49 - Projections of Fine-Particle Emissions from Industrial
Coal-Fired Power Plants
125
-------
in
o
g.
\7t
a
u
I I
Crushed Stone
A Method 1
O Method 2
_L
I
I
(968 1970
1975
1980
1990
1995*
196S
YEAR
Figure 50 - Projections of Pine-Particle Emission from Crushed Stone
Operations
2000
126
-------
0.010
0.009 \-
Iron and Steel
Sinter Plants
A Method 1
O Method 2
0.001 I-
1968 1970
Figure 51 - Projections of Fine-Particle Emissions from Sinter
Machines (iron and steel plants)
2000
127
-------
0.4
0.3
O
z
2 0.2
10
to
a
y
a:
0.1
I I
Iron and Steel
Open Hearth
A Method 1
O Method 2
I I
1968 1970
Figure 52
1975
1980
1985
YEAR
1990
1995
2000
Projections of Fine-Particle Emissions from Open
Hearth Furnaces (iron and steel plants)
128
-------
<
*
I/)
o
a
o
I
Iron and Steel
Basic Oxygen Furnaces
A Method 1
O Method 2
2000
Projections of Fine-Particle Emissions from Basic
Oxygen Furnaces (iron and steel plants)
129
-------
0.04
— Iron and Steel
Electric Arc Furnaces
A Method 1
O Method 2
2000
Projections of Fine-Particle Emissions from Electric
Arc Furnaces (iron and steel plants)
130
-------
0.20
A Method 1
O Method 2
2000
Projections of Fine-Particle Emissions from Kraft
Pulp Mill Bark Boilers
131
-------
0.8
O
O
y
0.6
0.4
0.2
I I
Pulp Mills
Recovery Furnaces
0 I I
A Method 1
O Method 2
1968 1970
Figure 56
1975
1980
1985
YEAR
1990
1995
2000
Projections of Fine-Particle Emissions from Kraft
Pulp Mill Recovery Furnaces
132
-------
0.004
0.003
LA.
<
I
0
*/»
z
O 0.002
y
>—
<
Q_
LU
Z
0.001
Pulp Mills
Lime Kilns
A Method 1
O Method 2
I I
1968 1970
1975
1980
1985
YEAR
1990
0.0043
1995
2000
Figure 57 - Projections of Fine-Particle Emissions from Kraft
Pulp Mill Lime Kilns
133
-------
0.40
0.30
UJ
in
O
z
§ 0.20
y
I
a.
0.10
. I T
CEMENT KILNS
0.476 IN YEAR 2000
/
A METHOD 1
O METHOD 2
1968 T970
1975
1980
1985
YEAR
1990
1995
2000
Figure 58 - Projections of Fine-Particle Emissions from Cement Plant
Rotary Kilns
134
-------
0.40
0.30
1 o.»
£
UJ
SJ
U
0.10
I I
ASPHALT DRYERS
0.562 IN YEAR 2000
A METHOD 1
O METHOD 2
I
1968 1970
1975
1980
1985
YEAR
1990
1995
2000
Figure 59 - Projections of Fine-Particle Emissions from Hot-Mix
Asphalt Plant Dryers
135
-------
0,40
0.30
IU
£ 0.20
(/>
2
o
0.10
FERROALLOY
A METHOD 1
O METHOD 2
1968 1970
1975
1980
1985
YEAR
1990
1995
2000
Figure 60 - Projections of Fine-Particle Emissions from Ferroalloy
Electric Furnaces
136
-------
0.40
0.30
ee.
in
O
i 0.20
in
5
UJ
y
ee
<
Q.
LU
z
0.10
LIME KILNS
0.466 IN YEAR 2000
A METHOD 1
O METHOD 2
1968 1970
1975
1980
1985
YEAR
1990
1995
2000
Figure 61 - Projections of Fine-Particle Emissions from Lime Plant
Rotary Kilns
-137
-------
0.20
0.15
Of
UJ
I/I
o
z
o
sa o.io
to
5
UJ
y
P
CK
0.05
A METHOD 1
O METHOD 2
I
COAL DRYERS
1968 1970
1975
1980
1985
YEAR
1990
1995
2000
Figure 62 - Projections qf Fine-Particle Emissions from Coal Preparation
Plant Thermal Dryers
138
-------
0.10
Municipal Incineration
A Method 1
O Method 2
2000
Projections of Fine-Particle Emissions from Municipal
Incineration
139
-------
0.04
0.03
I
o
z
O 0.02
a
0.01
Fertilizer
Gronulators and Dryers
A Method 1
O Method 2
I I
I
I
I
1968 1970
Figure 64
1975
1980
1990
1995
1985
YEAR
Projections of Fine-Particle Emissions from Fertilizer
Granulators and Dryers
2000
140
-------
0.020
0.015
vf
o
1
o.io
y
I
o.
UJ
Z
0.005
T I T
IRON FOUNDRIES
A METHOD 1
O METHOD 2
1968 1970
1975
1980
1985
YEAR
1990
1995
2000
Figure 65 - Projections of Fine-Particle Emissions from Iron Foundry
Cupolas
141
-------
TABLE 23
PROJECTION OF FINE PARTICLE EMISSION, ON A NUMbER BASIS,
FOR ASPHALT DRYERS
(Method 1)
Production Ratio Number of Fine Particles
Year (from Table 20 ) Emitted per Year
1968 1.00 6.0 x 1023
(from Table 2)
1970 1.09 6.5 x 1023
1975 1.33 8.0 x 1023
1980 1.62 9.7 x 1023
1985 1.98 11.9 x 1023
1990 2.43 14.6 x 1023
1995 2.98 17.9 x 1023
2000 3.65 21.9 x 1023
Method 2 - Method 2 employs:
1. The mass emissions projected by the second technique presented
in Section 8.1, and
2. The average diameter of fine particles emitted from sources
in future years.
The average diameter of the particles emitted in 1968 could be
computed from the mass emissions vs. particle size data given in Table 1.
However, some method had to be devised to determine an average diameter
for the years between 1968 and 2000. This was accomplished by computing an
average diameter for the fine particles emitted in the year 2000 when all
sources were assumed to be controlled by baghouses or their equivalent.
The average fine-particle diameter for the intervening years between 1968
and 2000 was taken from a straight-line interpolation between the average
size of the fine particles emitted in 1968 and in 2000.
The sequence of steps involved in projecting the number of fine
particles emitted from asphalt dryers in future years by Method 2 is
described below and is illustrated in Tables 24-27.
Step 1 - Calculate the average diameter of the fine particles
emitted in 1968 (see Table 24).
142
-------
TABLE 24
CALCULATION OF THE AVERAGE DIAMETER OF FENE PARTICLES
FROM ASPHALT DRYERS IN 1968
(Method 2)
Fine Particle Emissions = 154,200 tons/year (from Table l)
Number of Fine Particles Emitted = 6.0 x 1023 particles/year (from Table 2)
5/(l7.5 x 105)(mass emission tons/year)
p ~ t\l(density g/cm3)(number emissions)
5/(l7.5 x 105)(154.2 x 105)
N (2.6*)(6.0 x 1023)
dmp = /y/171 x 10"15
dmp = 5.55 x 10"5 cm.
* Density values were taken from Ref. 18.
Step 2 - Calculate the average diameter of the fine par-
ticles emitted in the year 2000. Calculation is based on the projected
mass emission for the year 2000 (Method 2, Section 8.1) and on the assump-
tion that all sources will be controlled with baghouses or the equivalent
in the year 2000.
The size distribution of the particulates escaping the bag-
house was computed using the size distribution of the particles emitted
from the uncontrolled source and the fractional efficiency curve for a
fabric filter (Figure 17). For most sources, this had already been done
in conjunction with computing the mass emissions of fine particles. The
size distribution of the particles emitted from the baghouse and the pro-
jected total mass emissions of fine particles for the year 2000 are then
used to calculate the mass emission of fine particles within each size
range. The mass emission within each size range is in turn used to calcu-
late the number of particles emitted within each size range. Knowing the
total mass and total number of fine particles emitted, the average diameter
can be calculated. Table 25 presents an example calculation.
143
-------
TABLE 25
CALCULATION OF THE AVERAGE DIAMETER OF FIME PARTICLES
FROM ASPHALT DRYERS IN THE YEAR 2000
(Method 2}
A. Calculate Mass Emissions Within Each Size Range
(~\ f\C.
I-3 H /* 'TTT? = 50$ x 18,200 tons/year = 9,100 tons /year
\ it
(from Table 20) \ (from Table 22)
0.5-1 (j, ' , = 33$ x 18,200 tons/year = 6,000 tons/year
0.1-0.5 „ %g • 17* » 18,200 tons/year -
B. Calculate Number of Particles Eknitted Within. Each Size Range
1-3 „ N = (17.5 x 105 g/ton)(9.1 x 105 tons/year) = y<6 x 1Q20 particles/ye
(2.6 g/cm3)(2 x 10'4cm.)3
,
(2.6)(0.75 x 10"4)-
0.5-1,
0.1-0.5 , N = ..1xlCa ?64>Q x 1Q20
(2.6)(0.30 x 10'4)3
EN = 866 x 1020 particles/year
C. Calculate Average Diameter of Fine Particles
3/ (17.3 x 105 g/ton)(!8.2 x 105 tons/year)
dmp = ^ /
(2.6 g/cm3)(0.866 x 1023 particles/year)
dmp = 5.19 x 10 cm.
144
-------
Step 3 - The data to be used in projecting the number of fine
particles emitted by asphalt dryers are compiled as i;hown in Table P6. Th<
averaKQ particle diejnotera for the yuarn butwcen IWi and POOO were ubtalno't
by straight-line intcrp<».!atl<>n boLwcori the avur/igc dltunoter \'nr the yuur
1968 and the year 2000 as discussed in Stops 1 and c'. The macs emission
of fine particles was taken from previous projection of these emissions
(Method 2, Section 8.1).
Step 4 - The data compiled in Step 3 are used to calculate
the number of fine particles emitted, up to year 2000, as shown in Table 27.
Table 7, page 14, summarizes the results of the projections
of fine-particle emissions on a number basis. The projections show that
ferroalloy electric furnaces, rotary lime kilns in lime plants, municipal
incinerators, coal-fired power plants, and steel making furnaces (EOF and
electric arc) will be significant sources of fine-particle pollutants, on
a number basis, even with stringent control in the year 2000.
145
-------
TABLE 26
COMPILATION OF DATA TO BE USED IN PROJECTION OF NUMBER OF
FINE PARTICLES EMITTED FRCM ASPHALT DRYERS
(Method 2)
Average Diameter of Fine-Particle Fine-Particle Mass Emissions
Year Emissions (dmp) (tons/year)(from Table 25)
1968
1970
1975
1980
1985
1990
1995
2000
5.55 x 10~5 cm,
5.53 x 10~5
5.47 x 10~5
5.42 x lO-5
5.36 x 10-5
5.30 x 10-5
5.25 x 10-5
5.19 x 10-5 cm.
(from Table 24)
(from Table 25)
TABLE 27
PROJECTION OF FINE-PARTICLE EMISSIONS ON A
154,200
157,600
157,700
152,000
140,800
116,500
74,100
18,200
NUMBER BASIS FOR ASPHALT DRYERS
(Method 2)
No. of Fine Particles
Year (Refer to Table 26) Emitted Per Year
1968 = 6.0 x 1023 (from Table 2)
1Q,n TT (17t3 x 1C)5 g Aon) (157. 6 x 103 tons/year) _ 23
J»y ' U JN ~ ty tr 'Z. ~* O • t X J.U
(2.6 g/W)(5.53 x 10"° cm.)
(17.3 x 105)(l57.-7 x 103) a*
1975 N = * - ^ - r-= — L = 6.4 x 1023
(2.6)(5.47 x Kfbr
(17.5 x 105)(152.0 x 103)
1980 N = - - " - =-= — *• = 6.3 x
(2.6)(5.42 x 10~b)5
1985 N = (17.5 X 105)(140.8 x 103) = ^ x
(2.6)(5.36 x 10'5)5
1990 N = (I?-3 x 105)(116.5 x 103) „ ^ x
(2.6)(5.30 x 10-5)3
1995 N -
(2.6)(5.25 x 10-5)3
2000 y.(l7.5xlo5)(lB.2xlQ3) = 0.87 x 1023
(2. 6) (5. 19 x 10-5 )3
146
-------
9. Conclusions and Recommendations
9.1 Conclusions
1. An accurate assessment of the mass of fine particles
emitted from specific sources was precluded because neither particle size
distribution data nor fractional efficiency curves for control devices were
available in the 0.01-2 p, size range. The lack of particle size data for
effluents from controlled sources indicates that neither control equipment
manufacturers nor air pollution control agencies have placed any emphasis
on the particle size of material emitted from control equipment.
2. Fine-particle emissions from industrial sources of particu-
late pollution are estimated to be at least 4 x 10° tons/year. This rep-
resents approximately 20-25$ of the total mass emissions for these sources.
3. Major industrial sources of fine particles, based on mass
and number emitted, include: (a) ferroalloy furnaces, (b) steelmaking
furnaces, (c) electric utility power plants, (d) lime kilns, (e) kraft pulp
mill recovery furnaces, (f) municipal incinerators, and (g) iron foundries.
*
4. Discrepancies exist in the fine-particle and total mass emis-
sions from some sources that emit mainly micron or submicron particulates
(e.g., basic oxygen furnaces and kraft pulp mill recovery furnaces). Analy-
sis of the possible causes of these discrepancies led to observation that
erroneous conclusions may have been reached regarding the high overall mass
efficiency of control equipment on these sources.
5. Currently, control equipment is rated by one parameter, namely,
overall mass efficiency. Specification of control equipment efficiency by
overall performance is inadequate with respect to small particles. Penetra-
tion (i.e.', 1-mass efficiency) in specific size ranges is a more revealing
term for rating control equipment performance.
6. There is considerable doubt that present air pollution control
procedures, which are based on overall percentage reduction in emissions
(tons/year), actually achieve the desired reduction in suspended particulate
matter in the community air.
7. Fractional efficiency characteristics of control devices
have not been accurately determined, and, as a result, the ability of con-
trol devices to collect < 2 y, particles is ill-defined.
8. A major portion (over 95$) of the data currently available on
the particle size of particulates emitted from industrial sources has been
obtained by sampling and particle sizing techniques that are not suitable
147
-------
for the particle size range < 2 ^. As a result, only a meager, quantity of
accurate data is available on particle size in the < 2 y, size range for
effluents from uncontrolled or controlled sources.
9. Fine particulates emitted from man's activity contribute
significantly to all the major adverse aspects of air pollution. Fine par-
ticles can initiate or contribute to problems related to human health,
atmospheric physical properties, and/or material degradation. The chemical
and physical properties of the atmosphere affected include: its electrical
properties; its ability to transmit radiant energy; its ability to convert
water vapor to fog, cloud, rain, and snow; its ability to damage and to
soil surfaces.
10. The effects of particulate matter on human health are, for
the most part, related to injury to the surfaces of the respiratory system.
11. A combination of particulates and gases may produce an effect
on human health that is greater than the sum of the effects caused by either
individually (i.e., synergistic effects).
9.2 Research Recommendations
1. Source sampling with more advanced instrumentation (e.g.,
cascade impactors, thermal precipitators, and electrostatic precipitators)
must be done to define the effectiveness of control equipment for the col-
lection of particulate pollutants. Standard sampling techniques are inade-
quate for collecting and sizing particles, particularly for particles 1 (j,
or smaller. The program should involve actual field testing, and attention
should be directed to the determination of the particle-size distribution
before and after control equipment and the.fractional efficiency of specific
control devices on specific sources.
2. Current.control devices do not adequately collect fine par-
ticles. Therefore, research programs should be initiated to study methods
for the collection of fine particulates. Research should be directed to
these main areas: (a) improvement of existing control equipment via better
design, (b) development of new and/or novel devices for controlling fine
particles, and (c)\agglomeration mechanisms of fine particles. Research
on the agglomeration mechanisms should improve existing collector perfor-
mance and may lead to new collector devices.
3. Current' capability to monitor, sample, and size effluents
from particulate pollution sources is inadequate. Research should be
initiated to improve this capability. Optical techniques for monitoring fine
particle emissions should be pursued. Simple, yet reliable stack sampling
methods need to be developed. A collection mechanism which collects
148
-------
submicron particles and causes neither a formation nor a break-up of aggre-
gates is necessary if accurate particle size information is to be obtained.
4. Research should be directed to defining the relationships
between total suspended particulate in the air and specific sources of
particulate pollution. Information is needed to help identify the origins
of suspended particles in the air and to assess the contribution of various
sources to the total particulate burden in the atmosphere. Investigations
should focus on material that leaves the source as a particulate (i.e.,
primary particulate), and source effluents that form particulates after
leaving the source (i.e., secondary particulates). Reduction of total sus-
pended particulate matter may require control at the source of effluents
that form secondary particulates.
5. Epidemiological and laboratory studies of the effects of
particulate pollutants on humans, including experiments on animals, should
be carefully coordinated and selectively accelerated. Attention should be
focused on synergistic effects produced by gases in combination with par-
ticulates.
6. Information on chemical composition of particulate pollutants
as a function of particle size should be obtained to assist in defining
potential health hazards of particulate pollutants. Attention should be
focused on potentially harmful metals.
7. Material damage caused by fine particulate pollutants should
be assessed more closely.
8. The influence of suspended-particulate matter on the behavior
of the atmosphere should be defined in more detail. Attention should be
focused on their effect on solar radiation and weather modification.
9. Since the major adverse effects of particulate pollutants on
human health and welfare are associated with micron and submicron.particles,
the technical and economic feasibility of establishing national emission
standards based on particle size should be investigated. Performance or
emission standards based on particle size should be studied because there
is great doubt that present procedures which are based on overall percent-
age reduction in emissions (tons/year) actually achieve the desired reduc-
tion in suspended particulate matter in the community air. If a performance
standard based on particle size were adopted, accurate data expressing
control equipment efficiency over the various particle size ranges will be
necessary. Simple, accurate, and reliable methods for testing the perfor-
mance of various control devices in the fine-particle range will also be
needed. These test procedures will be needed to confirm compliance of
installed equipment with regulations as well as to provide a means of
149
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comparing performance capabilities of various devices on a single source.
Research recommendations 1 and 3 would provide input to this area. More
stringent regulations will produce substantial costs in design, engineering,
and testing. Data on those costs will need to be accumulated. Also more
analytical data on the.dependence of control equipment performance on source
operating variables and effluent characteristics will need to be developed,
industry by industry.
150
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152
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Performance and Limitations of Sonic Type Flocculators and Collectors,"
Ultrasonic Corporation, Cambridge, Massachusetts.
52. Burke, E., "Dust Arrestment in the Cement Industry," Chem. and Ind.,
1312-1319, October 1955.
53. Peterson, A. A., "Fly Ash Collection for Small Plants," Meeting of the
American Society of Mechanical Engineers, Washington, D. C., April
1950.
54. Larcombe, H. L. M., "Centrifugal Dust Collectors," The Mining Magazine,
137-148, September 1947.
55. Penick, Walter L., and Howard W. Lange, "Fifty Years of Dust and Fume
Collection in the Mining Industry," Proceedings of the Ninth Pacific
Northwest Industrial Dust Waste Conference, April 1959.
154
-------
56. Henschen, H. C., "Wet vs. Dry Gas Cleaning in the Steel Industry,"
Journal APCA, 18, 538-342, 1968.
57. Wellet, H. P., and D. E. Pike, "The Venturi Scrubber for Cleaning
Oxygen Steel Process Gases," Iron and Steel Engineer, pp. 126-131,
July 1961.
58. Private communication, Mr. Al Brandt, Bethlehem Steel Corporation,
January 1971.
59. Private communication, Mr. Jack Smith, Kaiser Steel Company, January
1971.
60. Person, R. A., "Control of Emissions from Ferroalloy Furnace Process-
ing," Union Carbide Corporation, Niagara Falls, New York, 1969.
155
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APPENDIX A
PARTICULATE SAMPLING AND SIZING
157
Preceding page blank
-------
Summary
Standard stationary source sampling techniques are inadequate
for collecting particles for accurate particle size determinations, par-
ticularly for particles 1 ^ or smaller. Cyclone separators tend to breafc
up aggregates and friable particles, stainless steel or alundum thimbles
do not quantitatively capture the submicron particles, and small particles
may penetrate deeply into the body of a fiber filtering medium before they
are captured and then cannot be removed for subsequent analyses.
A sampling device which collects submicron particles and causes
neither formation nor breakup of aggregates is necessary if accurate parti-
cle size information is to be obtained. Cascade impactors, thermal pre-
cipitators, and small electrostatic precipitators are devices that come
close to meeting these requirements, and are clearly superior to the standard
sampling trains. A cascade impactor which can be inserted inside a duct is
the most versatile of these devices. Stainless steel cascade impactors are
now available which permit "in-stack" collection of submicron particles.
The Bahco Micro-Particle Classifier has been used extensively for
routine particle size measurements, and 95$ of the data currently available
on the particle size of particulates emitted from industrial sources have
been obtained by using this device'. The range of applicable particle di-
ameter for the Bahco instrument is 5 to 60 p. As a result of the extensive
use of the Bahco method, only a meager quantity of accurate data is avail-
able on particle size in the < 2 g, size range.
158
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1. Introduction
Measurements of the chemical and physics] properties of particu-
late pollutants omitted from flpeciflc oources generally require a sample to
be collected, i.e., the purtlcuiatuE must be suparatod uut, from the ^ua
stream in which they exist. The process of sampling may change the physi-
cal properties of the individual particles and the size distribution of
the particles. Following collection of the particulate, the desired physi-
cal and chemical measurements can be performed. Particulate pollutants,
however, are not all alike and can be of different shapes and compositions.
The variability in particulate properties has led to the development of
numerous methods for the measurement of specific properties, such as par-
ticle size.
The selection of the method for determining the particle size
or particle-size distribution of a given material is generally based on
(l) the particle-size range, (2) the form in which results are desired
(i.e., number-or-weight size curves), (3) application of the results, and
(4) accuracy required. Different methods of determining the particle size
may give quite different results, and the method used to prepare the sam-
ples for analysis can alco be a rloddlnp; factor in what the analysis actu-
ally measures.
The limiting aspects of sampling methods and particle size analy-
sis techniques assume added importance for the determination of the quan-
tity of fine particulate emitted from specific sources. -The applicability
of standard sampling techniques and routine particle-sizing methods to the
micron-or-less size regime is questionable. A discussion of conventional
source sampling and particle-sizing methods and their ability to collect
and measure fine particles is presented in'the following sections.
2. Source Sampling Methods
The accurate collection of a representative sample from a flow-
ing gas stream containing particulate matter is by no means a simple matter.
In general, a representative sample can only be withdrawn from a flow if
the probe through which it passes does not disturb the streamline pattern.
Therefore, an ideal probe samples isokinetically and has infinitely thin
walls. Both of these conditions are difficult to achieve in practice, and
the problem is one of determining how far from the ideals one can depart
and still obtain representative samples.
At the extremes of particle size, representative samples can be
obtained despite disturbances caused by the presence of the probe and an
anisokinetic sampling. Very small particles have low inertia and follow
159
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deflections of the streamlines with insignificant Departure, and particle
and gas are drawn into the probe in the correct proportions.
At tho other extreme, vcr.y Juj-tfn partjcloa, with rolat.lv<:.Ty hlph
inertia, enter the probe in straight trajectories independent of the stream-
line deflection, and the correct flow rate of particles is measured. When
particles are about 10 |j,, and the sampling velocity is lower than the velocity
in the duct, some of the gases will be deflected around the probe. However,
some of the particles, because of their inertia, will enter the probe and
the sample will be biased toward the large particles. Conversely, if the
sampling velocity is greater than the dust velocity, the sample will be
biased toward the smaller particles.
An approximate guide to indicate when careful sampling is neces-
sary can be obtained by using the dimensionless inertia parameter, ^ .
This parameter, which is frequently used in deposition studies, is the ratio
between the stopping distance of the particle and the diameter of the probe.
The stopping distance, defined by Equation 1, is the distance the particle
will travel when projected horizontally into a still atmosphere with velocity
U .
Stopping Distance = £E- (l)
18 n
where ^ = viscosity of gas
Pp = density of particle
d = diameter of particle
U = stream velocity
C = Cunningham correction factor
Theoretical and experimental studies have shown that if | exceeds 50,
the particles are not affected by the streamline deflection, and if if is
less than 0.05 the particles follow the streamline closely.!/ Thus, iso-
kinetic sampling is required if
Pdd2UC
0.05 < — < 50
18 ^P
where Dp = probe diameter.
160
-------
A number of devices have been designed which nearly achieve iso-
kinetic sampling. These devices either use a null-type sampling probe, or
measure the velocity of the gas stream with a pitot tube as near to the
probe as possible without interfering with the gas flow, and then adjusting
the sampling velocity.?.;.5/ Since the velocity in a stack generally varies
with distance from the wall, accurate sampling also requires the accumula-
tion of samples from several different positions (i.e.,'traverse of the
stack).
2.1 Sample Collectors
The usual method for collecting the particles from the gas-streem
sampled by the probe is to draw the entire stream through a filter which
is often in the form of a thimble. A small cyclone separator is also use'-
in series with filters in some cases. Wet scrubbers have also been used
in conjunction with cyclones.—/
The standard collecting techniques are probably inadequate for
collecting particles for accurate size determinations, particularly for
particles in the micron or less size range. The cyclone separators will
tend to break up aggregates and friable particles; stainless steel or
alundum thimbles probably do not capture all or any of the submicron par-
ticles; and small particles may penetrate deep into the body of a fiber
filtering medium before they are stopped. Particles which penetrate into
the filters cannot be removed or observed microscopically. Another source
of error in sampling aerosols for subsequent particle size analysis is lead-
ing the aerosol through a long and/or tortuous path before the particles
are removed. The danger from this procedure is that particles are caught
on the walls of the tubing, particularly near bends. Preferential trapping
of certain particle sizes can produce serious errors in the particle size
determinations.
A collection mechanism which collects submicron particles and
causes neither a formation nor a break-up of aggregates is necessary if
accurate size information is to be obtained. Small electrostatic precipi-
tators, thermal precipitators, and cascade impactors are devices that come
close to meeting these requirements.
2.2 Collector-Measuring Devices
2.2.1 Impaction devices; Impactor sampling devices are based on
the fact than an aerosol particle suspended in a fluid stream tends to move
in a straight line because of its inertia when the fluid flows around an
obstacle. The larger particles, because of their greater mass, will have
sufficient momentum to continue to move toward the object and impact on the
surface. At the same time, particle motion relative to the gas stream is
161
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slowed by fluid resistance, and some particles may fail to reach the col-
lector surface before they are carried past the sampler due to deflection
in the fluid flow field. Impactors will provide meaningful results only
under isokinetic sampling conditions.
Cascade impactors, constructed of stainless steel, are beginning
to be used for "in-stack" source testing. Cascade impactors consist of a
series of stages containing jets and collector plates. The jets in each
stage through which the aerosol is drawn become progressively smaller. The
particles are classified by inertial impaction according to their mass;
the larger (heavier) ones are collected on the plate opposite the first
stage, and the smallest (lightest) on the plate opposite the last stage.
Figure A-l illustrates a schematic of a source test cascade impactor ..ii/
The classification of particle size produced by impactors has
certain advantages for microscopic determinations of size distributions
when there is a large variation in particle size. Furthermore, this clas-
sification provides a technique for obtaining mass distribution curves,
normally in the size range 0.3 to 60 jj,. The impactor is calibrated to de-
termine the smallest particles collected at each stage or, preferably, the
sir.e of particles which are sufficiently small that they are collected with
only 50$ efficiency at each stage. Size calibration is dependent upon the
specific gas velocity through the instrument. Following calibration, the
dust whose particle-size distribution is to be determined is then collected
with the impactor. The weight of material collected at each stage is de-
termined and the results are plotted as cumulative weight-distribution
curves.,!/
Impactors are capable of very high collection efficiency under
rigid, experimental conditions. An efficiency of 100$ for particles as
small as 0.6 p, has been obtained.^/ A commercial stainless steel eight-
stage, multi-jet impactor for "in situ" stack sampling has recently become
available, and is reported to be capable of sizing particles down to 0.1 ^.S/
Particle-size distributions determined by cascade impactors may
be distorted by particle bounce, surface overloading (i.e., particle build-
up and blow-off) and wall losses. Wall losses can be minimized by good
impactor design and proper operation. Particle bounce may be reduced by
using a viscous surface coating on the collector plates.
2.2.2 Thermal precipitators; Thermal precipitators have been
used for many years in England and South Africa for ambient sampling. Ther-
mal precipitators have also been used to a limited extent for stack sam-
pling in this ftnnnt.ry.6-8/ The thermal precipitator makes use of a radiom-
eter force produced by a thermal gradient between two different surfaces.
Direct measurements of collection efficiency indicate that thermal precipitators
162
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IMPACTOR STAGE
77A 77A
\V\\\\\\\\
\\\\\\\\V\
IMPACTOR PLATE
O-RINGS
SPACING STUDS
LOCATED AT EQUAL
INTERVALS ABOUT
CIRCUMFERENCE
Figure A-l - Schematic of Source Test Cascade Impactor^/
163
-------
Deposit virtually all particles of most materials from 5 down to 0.01 ^
and possibly smaller. Ficure A-2 illustrates the narnpling head of ,-A z^w.w:
thermal precipitator .£/
hy 'iQjxjsitjrip; hhu pM.r-1/ic los on an electron microscope grid, t,hc-
thermal precipitator can be u;:«:d .in conjunction with an electron micro-
scope for sizing particles. provided the deposit is not so dense that
overlapping occurs and attention is paid to statistical errors, the thermal
precipitator provides one of the most accurate methods for sampling of non-
volatile solid particles. The upper limit of number concentration which
can be determined with the thermal precipitator depends upon the accuracy
of measurement of the volume sample drawn through the instrument.
2.2.3 Small-scale electrostatic precipitators; Small-scale
electrostatic precipitators in various configurations'have been used with
some degree of success for source sampling, and subsequent particle sizing
by optical methods. The essential feature of many of these devices is a
collecting electrode in the form of a tube down which the particles pass
and a central ionizing electrode maintained at a high potential. The elec-
tric field is such that the particles acquire a high charge and travel to
the outer electrode, where they are deposited. A drawback is that the de-
posit varies in density and size distribution along a length of the electrode
so that a full assessment entails considerable counting and sizing. Electron
microscope screens have also been used as deposit sites.£/ Figure A-3 pre-
sents a schematic of an electrostatic precipitator for sampling.57
Dust Laden Air
Microscope
Cover Glass
Heated
Wire
Strip of
Deposited
Dust
Figure A-2 -
To Water Aspirator
Sampling Head of Standard Thermal Precipitator^/
164
-------
-p
O
-p
cd
-P
•H
PH
•H
O
o;
o
•H
-P
w
o
SH
-P
O
-------
Impactors, thermal precipitators, and electrical precipitators
are all capable of collecting particles in the submicron range. The cas-
cade impactor is probably the most versatile of these devices for "in-
stack" collection of submicron particles. Unfortunately, impactors have
been used only to a limited extent,5/ Research groups at the University of
Washington have utilized ouccude impactors to ,'jump.lo pulp mill recovery
furnaces, plywood veneur dryerc, bark boilnrs, and aluminum reduction
I'.nllr..H>12/ The thermal prccipitutor has boon iiiiod by liush and co-workers,
in conjunction with an electron microscope, to study power plant ctack dis-
charges .£l§/ In the device used by Bush, the particles were thermally pre-
cipitated onto the electron-microscope specimen grids.
2.2.4 Other devices; Investigations by Whitby and co-workers
at the University of Minnesota have led to development of a particle-size
distribution analyzer based on electric mobility analysis. This instru-
ment, designed for atmospheric sampling of submicron airborne particles,
is commercially available from Thermo-Systems, Inc., in St. Paul, Minnesota
This electric mobility device consists of an aerosol charging de-
vice and an electrical mobility analyzer. Entering aerosol is given a uni-
polar negative charge by a special diffusion charger (sonic-jet-diffusion-
charger) . The charge per particle is a reproducible function of the par-
ticle size and is a monotonically increasing function over the size range
of interest. The charged aerosol passes to the mobility analyzer, where
it is introduced as a bhin annular cylinder around a core of clean air.
A metal rod, to which a variable, positive voltage can be applied, passes
axially through the center of the analyzer tube. Particles smaller than
a certain size (with high electric mobility) are drawn to the collecting
rod while the larger particles escape collection because of their lower
mobility and are therefore collected by a current collecting filter. The
electrical charges on these particles drain off through an electrometer,
giving a measure of current. A step increase in rod voltage will cause
particles of a discrete larger size to be collected by the rod with a re-
sulting decrease in electrometer current. The change in electrometer cur-
rent is related directly to the number of particles in the aerosol between
the two discrete particle sizes.
With a constant applied voltage, the removable collector rod may
also be used to collect particles classified by size along the length of
the rod for subsequent analysis with an electron microscope. Discussions
with Dr. Whitby and with Dr. Olin and Mr. Sem of Thermo-Systems indicate
that the electric mobility device might be adapted for use in stack sam-
pling. This would require the use of dilution air to decrease the mass
concentration entering the instrument to < 500
166
-------
The recently developed method of laser holography offers a po-
tential for remote particle size analysis. Hologram systems have recently
been designed and used for recording and reconstructing relatively large
volumes of particles in the size range from 3 to 1,000 ^ mean diameter.iZzl2/
3. Particle Size Measurement
Following collection of a particulate sample, a method of par-
ticle size determination must be selected. With the standard sampling
techniques utilizing filters as collectors, redispersion of the collected
particles is a potential problem. The methods used to prepare the samples
for analysis can be the deciding factor in what the selected analysis mefchou
actually measures. Utilization of cascade impactors, thermal precipitaturs,
or electrical precipitators minimizes this troublesome factor as optical
techniques are generally used in conjunction with these devices.
Determination of particle size cannot be unique except for the
special case of spherical particles. For irregular dust particles, the
average dimension along three mutually perpendicular axes may be used, or
the diameter of a sphere having the same volume or the same surface area
as the particle may be chosen. Obviously, the more irregular the shape
of the particles, the greater will be the variations in equivalent diameters.
For extremely irregular particles like plates, rods, or stars, some other
measure, such as specific surface or settling rate, will usually be more
significant, in many gas-cleaning processes the settling velocity has
direct physical meaning, independent of particle structure, and is preferred
to equivalent diameter.
Because of the wide variations in particle shapes and sizes, no
universal method or apparatus for particle size determination is possible
even in principle. Table A-l summarizes the type and character of size-
discriminating properties that have served as the basis for particle size
analysis, as well as classes of measurement techniques.157 Each size analy-
sis method depends on some property or combination of properties to distin-
guish one size from another. Table A-2 presents examples of devices common
to each class, and the range of particle size for which each technique is
likely to be applicable. References 3, 4, and 14 present extensive discus-
sions of particle size analysis and analyzers, and the reader interested in
more details is directed to these sources.
3.1 Current Practice in Industry
A major portion of the data currently available on the particle
size of particulates emitted from industrial sources has been obtained by
using the Bahco Micro-Particle Classifier. The Coulter Counter, Whitby
Centrifuge/MSA Sedimentation, and microscopic techniques have also been
167
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TABLE A-l
SHORT SUMMARY OF ANALYSIS TECHNIQUES^
Size-Discriminating Property
Type Character
Geometric
Mechanical or Dynamic
(in fluids)
Optical
Electrical
Magnetic
Thermal
Physico-chemical
Physical barrier
Inertia
Terminal settling
velocity
Diffusion
Imaging
Transmission
Scattering
Diffraction
Resistance
Capacitance
Charge
Magnetic particles
Particle deposition
Condensation
Types of Measurement
Technique
Sieving
Ultrafiltration
Impaction on surface
Pressure pulse (sonic)
Elutriation
Sedimentation
Decantation
Photo-sedimentation
Particle displacement
Particle deposition
Light microscopy
Ultramicroscopy
Electron microscopy
Spectrum
Single particle count
Macroscopic
Light
X-ray
Laser
Current alteration
Potential pulse
Tribe-charging
Induction charging
Corona cnarging
Particle migration; pulse
Particle migration
Growth of nuclei
168
-------
TABLE A-2
SUMMARY OF TYPES OF SEE-ANALYSIS TECHNIQUES
Slie-dlicr
~ Tjfp.
Geometric
Mcrhonicol
nf Dynamic
(in flutdi)
Optical
Electrical
Magnetic
Thermal
Physico-
chemical
mlnallni Proptrty
Chancier or
Mtcrt»n.tfti
Physical barrier
Inorlio
Tcrmmol settling
vcloc ity (in
gravity or ccntri"
fugal fields)
(possibilities of
using electrical
fields exist)
Diffusion
Imaging!
Transmission
• (spectral)
Scattering
Diffraction
Resistance
Capacitance
Charge
Applicable to
magnetic
materials only
Particle deposition
Condensation
Technique and Volitions
Sieving
Uttrnlihtolion
Impar. lion on lufl
Wet
Dry
nee
Pressure pulse (some)
Elutnotion
Sedimentation
Deeanlation (in I
Single Liquid
froctionation
Gas
Sertes Liquid
Cos
Layer Liquid
methods
(differential)
Gas
Suspension Differential*
methods liquid
Integral-
liquid
Integral-gat
quid only)
[Photo-sedimentation (photography of particle streaks)
Porlicle displacement (random walk}
Particle deposition
Light microscopy
Ultromicroscopy (gives mean size only)
Electron microscopy
Extinction measured at function of wavelength
Single porttcfe
count
Right angle (90°)
Angular
Forward
Polarization
Macroscopic (gives mean size only)
Light
X-ray
Laser (hologrophy*reconstruction of diffraction
pattern)
Alteration of current flow by particles
Potentiaf pulse due to particle deposition
Tribo*chorging
Induction charging
Corona charging
Particle mi grot ton in magnetic fields; magnetic
pulses
Particle migration in thermal gradient
Growth of nuclei with controlled super saturation
Eiantple of Common
Applfltui*
Ro-Top (Tyler),' Pulver.t
Sholtor, Sonic Sifter
(All.n-Brodley); eloelro-
formed novel (Buckboe
M*o>»)
M*r*hr0netf Millipore,
Gtlmon
Greenburg-Smlth, Moy,
Andyrfton, Cotiello;
Bottelli
IITRI
Schone
Roller (G); Federal
Pneumatic (C), Bohca (C)
Andrews
Kaultain "Infrasiler";
Gonell; Aminco
Palo Travis (G), Werner
(G), MSA-Whnby (G, C);
Koy. (C)
Micrcmerigraph (Sharpies)
(G); Con i fug* (C)
Pipette (Andreasen) (G);
hydrometer (G); diver
(G), Komack (C); turbi-
diffleter (G,C), differen-
tial manometer; gamma-
ro^ absorption
Sedimtntation balance
(Oden, Cahn, Sartorius)
(G); rnanometer (Weigner)
(G); pendulum (C)
Aerosol spectrometer
(Oa'ii'l (C), ndimenlo-
lion chonnol (C)
Cummlngs
Corey & Stoirmond
Mlllihan cell
Oiffuiion battery
American Optical; Bausch
& Lamb; Leitz; Nikon
Reichert, Tivodo;
Unitron; Vickers; Wild,
Zeiss, etc. Flying-Spot
counters
Hitachi; Norelco; RCA; '
Siemens
Boiley
Royco counter (gas.
liaurd); O'Konski
Owl (monodisperse
oorosols)
Sincfair-Phoenix (aerosol
concentration)
Slat Volt Co.
Coulter counter
Guylon counter
Drozin and LaMer; Mercer
Cas.ello;
GE condensotion nucloi
counter
Rjnje of
Appliciult Pj'tlq'*
Oljmelir," !
Micron I I
!/ 1000 ;
0.01 S
0,1 K'O
10- 1000' 'I
5 100
l-IOO(G)
0.02- IOIC)
0.002- I(UC)
1 \W.)
1 lOWOi
0.01-1
0.2-100
0.005-1
0.002-15
0.1-2C)
0.2-50
(higher with
microwave)
1-100
1-30
0.1- lOf?) !
0.01-0. 1C)
* Items in parentheses hove following significance: C - in centrifugal field; G = in gravity field; UC * uitNKMtrlfug*.
1 Replicas may b« used in place of particles that might evaporate or be destroyed during measurement, e.g,, in electron microscopy to ovoid the effect of voct/*mi
or electron beam, and in magnesium oxide film method for measuring size of drops
lea
-------
used. Cascade impactors, such as the Andersen and those developed by
Pilat,iiii£/ are just beginning to be introduced in routine stack sampling.
Since in this program nearly all the data used to estimate fine particle
emdssionn were obtained b.y one of the above; methods, the capabilities of
each method will be discu.'ined In come detail.
3.1.1 Banco c la s s i f ie r ; The Bahco Micro-Particle Classifier is
used extensively for routine measurements by control device manufacturing
companies . The Bahco instrument is a combination air eentrifuge-elutriator
consisting of a brush feed system and a rotor assembly. The Bahco instru-
ment separates a dry dust into nine fractions, according to terminal set-
tling velocity. It does this by subjecting the particles to a centrifugal
force, which is opposed by a current of air. The dust is thus divided into
an elutriated or fine fraction and a settled or coarse fraction. By varying
the air flow through the instrument, it is possible to change the particle
size limit of division and thus the material can be divided into any number
of fractions with limited particle size ranges. Eight throttles or air-
orifice settings are used successively to permit the collection of nine
fractions. If the weight and some measure of particle size of each dust
fraction are known, a particle-size distribution curve can be plotted .2±i/
A simplified schematic diagram of a Bahco unit is shown in Figure A-4.15/
1. Electric Motor 9.
2. Threaded Spindle 10.
3. Symmetrical Disc 11.
4. Sifting Chm 12.
4. Sifting Chamber 13.
5. Container 14.
6. Housing I 5.
7. Top Edge 16.
8. Radial Vanes
Feed Point
Feed Hole
Rotor
Rotary Duct
Feed Slot
Fan Wheel Outlet
Grading Member
Throttle
Figure A-4 - Simplified Schematic Diagram of a Bahco-Type Micro-
Particle Classifier Showing Its Major Components'^/
170
-------
Failure to disperse the particles adequately as discrete particles
is a major source of error with the Bahco instrument. Also, friable par-
ticulate matter may be broken by the analyzer and nonrepresentative size
distributions will be obtained. Another common and inherent error in all
elutriation techniques is that the fluid velocity is not constant across
the ducts, so that the assumption of particle velocity equal to fluid
velocity is usually invalid. In addition, the fractions obtained from
elutriation do not have a sharp size distribution, so that average, esti-
mated sizes have to be assigned. No quantitative measure is made of the
amount of dust lost during transfer into and out of the instrument, but the
loss can be miniwr'.cd by careful handling. The range of applicable partici<>
diameter for the Bahco instrument is b to 60 jj,.
3.1.2 Coulter Counter; The Coulter Counter utilizes a change
in electrolytic resistivity to determine particle size. The instrument de-
termines a number-volume particle-size distribution of particles suspended
in an electrically conductive liquid. The suspension flows through a small
aperture having an immersed electrode on either side. The particle con-
centration is made low enough that the particles traverse the aperture one
at a time in most cases.i^/ A simplified layout of the Coulter. Counter is
presented in Figure A-5.i§/
Each particle passage displaces electrolyte within the aperture,
momentarily changing the resistance between the electrodes and producing a
voltage pulse, presumably proportional to particle volume. The resulting
series of pulses is amplified, scaled, and counted using pulse-height
analysis.
In order to have the Coulter Counter response proportional to
size, a highly conducting medium is required, about 0,1 M electrolyte. In
some instances this type of medium may interact with and/or solvate the
particles and alter their size-to-voltage response ratio. Other potential
sources of error are poor particle dispersion and the response of the in-
strument to physical-chemical properties of the particulate matter other
than particle volume. The size range of applicability of this instrument
is approximately 0.3 to 100 jj,.
3.1.3 Differential sedimentation; The MBA-Whitby device is based
on the differential layer sedimentation technique. Basic to the method
"are specially designed centrifuges that have speeds constant to withir. l£
and whose speed versus time curves during starting and stopping are known
and constant enough so that corrections do not vary by more than ±0.5 sec.
Centrifuges of 300, 600, 1,200, 1,800 and 3,600 rpm whose starting and
stopping characteristics are controlled by a combination of an inertia disk
and a variable resistor in series with one winding of the motor have been
developed. Special centrifuge tubes and a feeding chamber are employe^.
171
-------
172
-------
At the beginning of a size analysis, the clean tube is filled to
the line near the top of the tube with a suitable sedimentation liquid
(Figure A-6). Next a suspension of particles is made up in a liquid that
is irascible with the sedimentation liquid but has a slightly lower density
and a slightly higher viscosity, in order to minimize density streaming.
An aliquot of this suspension is placed in a feeding chamber and then trans-
ferred to the sedimentation tube, leaving a sharp layer of suspension on
top of the sedimentation liquid. Then, at the time calculated from Stokes'
equation for desired sizes, the sediment height is read. When the particle-
size distribution lies below 20 to 30 jj,, the sedimentation tube is trans-
ferred to the lowest speed centrifuge and run for precalculated times,
after which the sediment height is observed. The ratio of the sediment
height at any time to the final height of sediment is assumed to give the
fraction larger than the size calculated.
FEEDING CHAMBER
40-MESH WIRE SCREENlJX
1.4 CM.
1.1 CM.
FILLING
r
i
12.5
i
C
0.75 OR 1.0 MM.
CAPILLARY
Figure A-6 - Centrifuge Tube and Feeding Chamberi§/
Design According to Whitby
173
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Sediment height is assumed to be proportional to sediment weight.
When complete dispersion of particulate matter is achieved, this is a good
assumption, because one-size particles are essentially settling at one time,
and the void space is independent of size for monodisperse systems. In many
cases, however, strong aggregates of small particles exist; for example,
2-p, silica particles are aggregates of 0.01 to 0.03 ultimate particles. In
these cases, compression of the sediment column with increasing centrifuge
speed takes place, and bulk density correction factors must be used.16/
Another complication with this device is that no temperature con-
trol is provided, so that data obtained in non-air-conditioned laboratories
are suspect. When a material having a narrow size distribution is studied,
many particles may enter the capillary at the same time, causing plugging.
Although a tapper is provided to minimize plugging and surface diffusion
after settling, it disturbs sedimentation. In some cases involving trans-
parent particles, serious difficulty may arise in deciding where to read
the sediment height, because a sharp line is not apparent. With proper
choice of sedimentation fluids, distribution of particle sizes in the range
of 0.1 to 80 p, can be measured with this device .M/
3.1.4 Optical techniques; Optical techniques are the most direct
method for particle-size distribution measurements. Theoretically, the
applicability range of optical methods is unlimited; but practical limita-
tions and availability of more expedient techniques make microscopy a less
desirable tool in certain size ranges.
Microscopic examination is generally considered most reliable
for particle size analysis provided samples are properly prepared, the
particles are all or nearly all of one geometric shape, and enough of them
are measured to give statistically reliable data. Inevitably, these methods
are difficult and time-consuming. The particles must be magnified to such
an extent that individual particles can be examined and their dimensions
measured. Of course, the images may be photographed and the analysis made
from the photographs. The particle-size distribution is then determined
from the individual particle data. Optical techniques are generally used
in conjunction with impactors, thermal precipitators, and electrostatic
precipitators.
Table A-3 shows the particle size regions of applicability of
several microscopic techniques. The lower limits are imposed by the at-
tainable resolving power. A particle cannot be resolved if its size is
close to the wavelength of the light source.
174
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TABLE A-3
RANGE OF APPLICABILITY OF MICROSCOPIC TECHNIQUES
Method Normal Size Range
White light 0.4 - 100
Ultraviolet light 0.1 - 100
Ultramicroscopy 0.01 - 0.2
Electron microscope 0.001 - 5
The errors involved in the microscope method can be broadly
grouped in four categories: technique of slide preparation including sam-
pling, dispersion and mounting; the optical arrangements; technique of par-
ticle measurement including questions of aggregation, shape factor and
choice of diameter; and counting procedures.
Significant results from light microscopic measurements depend, first,
on depositing a representative sample on a substrate by one of the sampling
methods or on redispersing the sample effectively when a mass of material has
been collected, perhaps with a filter. If the particle collection method,
perhaps impingement or thermal precipitation, produces a deposit on a glass
slide, the particles can be measured directly, provided the deposit is not
dense (i.e., minimal superposition). When the collection is on a membrane
filter, measurements can be made directly if the filter is made transparent.
Extreme care must be taken to ensure that a representative portion
of any bulk sample is selected for analysis and that no classification occurs
during microscope-slide preparation procedures. One method commonly used to
distribute fine particles over a slide is to disperse the particles by means
of agitation in a nondissolving liquid containing, usually, a dispersion
agent. Stirring is continued to avoid any settling of the larger particles.
A drop of this suspension is placed on the microscope slide for measurement.
Classification may occur on the slide as the liquid evaporates. In so doing,
small particles tend to migrate to the liquid boundaries, while the larger
ones stay in place. If this is the case, individual particle measurements
may be made by passing through the center of the deposit and examining par-
ticles from one periphery to the other. Sometimes classification caused by
liquid evaporation can be avoided by spreading the suspension as quickly as
possible into a thin film. A proper concentration of the particle sus-
pension can be obtained only by experience or the trial-and-error approach.
Because separating previously collected particles into discrete
entities without actually producing particle disruption is often difficult,
the dispersing or wetting agent must be carefully chosen and only sufficient
175
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agitation provided to achieve the required dispersion. Lists of agents for
use with a number of materials have been prepared. J-4,16/ jn some cases,
when analyzing a mass of collected aerosol material, complete dispersion
may not be desirable. What may really be desired is the degree of agglomera-
tion that prevailed in the aerosol state. Direct sampling by precipitation
on a slide is best for this purpose.
Under a microscope a particle is seen as a projected area whose
ilimensions depend on the orientation of the particle on the slide. In
order to get consistent measurements of the profiles of irregularly sized
particles it is essential to adopt certain conventions; in practice, the
most suitable
1. Martin's diameter, which is the length of a line intercepted
by the profile boundary which approximately bisects the area of the profile.
The line may be drawn in any direction, but must be maintained constant for
all the profile measurements.
2. Feret's diameter — length between two tangents on opposite
sides of the particle and perpendicular to the bottom of the microscope
field.
3. The diameter of the circle whose area is equivalent to the
projected area of the particle.
Most observers find it easier to use the equivalent circle method.
To facilitate use of this method, a graticule, which has a series of cir-
cles of different diameter scribed on it, is placed in the microscope eye-
piece ,14/
A real difficulty in size estimation arises with some precipitated
materials and sintered powders in which the partieulate may be aggregates
which are unaffected by dispersing agents. Such aggregates may have a very
open structure and extremely variable shape, together with a rather in-
definite density depending on particle size. The density may vary from the
true material density for the smallest particle to a quite low figure for
the largest aggregates. In such cases an approximation must be made in
order to obtain figures for the weight distribution. A suitable one might
be to measure the equivalent circle diameter of the aggregates, but to use
for each size group an estimated density based on the apparent closeness of
packing in the aggregates or found from settling tests on individual aggre-
gates .li/
Many particulates emitted from industrial sources contain a high
proportion of particles smaller than 0.5 ^ in diameter, and for these very
fine particles electron microscopy provides a direct means of measuring
176
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size and shape. The electron microscope is the ultimate tool used to ref-
erence submicron particles to the size parameter. It is the only means of
obtaining a full-size analysis of extremely small samples containing par-
ticles in the size range 0.001 to 5 jj,. As the instrument uses electron
lens or objectives of very small numerical aperture, it has a large depth
of focus, while its resolving power is many times greater than that of the
visible light microscope.
Electron microscopy requires specialized techniques for specimen
preparation and these require some consideration if the utility of the
method is to be fully appreciated.4>.16/ Selection of the proper technique
for preparing for electron microscope measurements depends on the kind of
information sought, the condition of the sample, and the physical proper-
ties of the particles, just as in light microscopy. Likewise, other prob-
lems encountered are those of securing a representative sample and getting
it sufficiently dispersed for individual particles to be distinguished one
from another.
Direct examination of the particles from an aerosol is possible
if the particles are deposited directly on prepared specimen grids by means
of thermal or electrical precipitation. Caution should be exercised here,
for particle classification can inadvertently occur depending on the loca-
tion of the grids. Several grids placed at various locations in these
samplers should be exposed unless the aerosol is known to contain a narrow
particle size range.
Because of the very small field of view available and the con-
sequently large number of plate exposures which must be made in order to
count sufficient particles for an accurate analysis, electron microscopy
is not suitable for routine analysis. However, the method is invaluable
as a reference method when the time involved in specimen preparation may be
justified.
177
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REFERENCES
1. Parkes, G. J., "Some Factorn Governing the Deaifjn of Probou for nim-
pling in Particle- and Jjrop-Jnden ;;t;reumr.," Atmospheric Knvlro runout,
Vol. 2, 477-490 (l'JC.0).
2. Strauss, W., Industrial Gas Cleaning, Pergaiaon Press, New York (1966).
3. Cadle, R. D., Particle Size - Theory and Industrial Applications,
Reinhold Publishing Corporation, New York (1965).
4. Cadle, R. D., Particle Size Determination, Interscience Publishers,
New York (1955).
5. Sales Brochure, "Andersen Air Samplers," 2000, Inc., South State Street,
Salt Lake City, Utah.
6. Bush, A. F., and E. S. C. Bowler, "Electron Microscopy Studies of a
Coal-Fired Steam Electric Generating Stack Discharge," Report No.
S.I. 395, Department of Engineering, University of California,
Los Angeles, California, December 1965.
7. Bush, A. F., and E. S. C. Bowler, "Electron Microscope Studies of a
Bag Filterhouse Pilot Installation on a Coal-Fired Boiler," Report
No. S.I. 405, Department of Engineering, University of California,
Los Angeles, California, September 1966.
8. Bush, A. F., and E. S. C. Bowler, "Electron Microscopy Studies of a
Steam Electric Generating Stack Discharges," Report No. C 60-79,
S. I. 8007, Department of Engineering, University of California,
Los Angeles, California (1960).
9. Green, H. L., and W. R. Lane, Particlulate Clouds; Dusts, Smokes, and
Mists, 2nd Edition, D. Van Nostrand Company, Inc., Princeton,
New Jersey (1964).
10. Flesch, J. P., "Calibration Studies of a New Submicron Aerosol Size
Classifier," Journal of Colloid and Interface Science, 29 (3),
502-509 (1969).
11. Private communication, Prof. M. J. Pilat, University of Washington,
Seattle, Washington, November 1970.
12. Bosch, J. C., "Size Distribution of Aerosols Emitted from a Kraft
Mill Recovery Furnace," M. S. Thesis, University of Washington,
Seattle, Washington (1969).
178
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13. Lapple, C. E., "Particle-Size Analysis and Analyses," Chemical
Engineering, .149-156, May 20, 1968.
14. Harden, G., Small Particle Statistics, 2nd Edition, Butterworth's
Scientific Publications, London (i960).
15. Sales Brochure, If. W. Dietert Company, Detroit, Michigan.
16. Irani, R. R., and C. F. Callis, Particle Size; Measurement, Inter-
pretation y. and Application, John Wiley, New York (1963).
17. Thomson, B. J., et al., "Application of Hologram Techniques for
Particle Size Analysis," Applied Optics, Vol. 6, No. 3, 519-526
(1967).
18. "Holographic Determination of Injected Limestone Distribution in
Unit 10 of the Shawnee Power Plant," TRW Report 14103-6001-RO-OO,
June 1970 (Contract CPA 22-70-4).
19. "Investigation of Scattered Light Holography of Aerosols and Data
Reduction Techniques," TRW Report 14103-6002-RO-000, November 1970
(Contract CPA 22-70-4).
179
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APPENDIX B
ADVERSE EFFECTS OF PARTICULATES ON HUMAN HEALTH
181 ., -,
Preceding page blank
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Summary
The adverse offsets caused by particulate matter on hurn.Mn h
are, for the most part, related to injury to the surfaces o1' the re::pi r.-ii,ory
system. Particulate material in the respiratory tract may produce injury
itself, or it may act in conjunction with gases, altering their sites or their
modes of action. A combination of particulates and gases may produce &n
effect that is greater than the sum of the effects caused by either individ-
ually (i.e., synergistic effect).
Laboratory studies of man and other animals show that the depo-
sition, clearance, and retention of inhaled particles is a very complex
process, which is only beginning to be understood. Particles 'cleared from
the respiratory tract may exert effects elsewhere. Available data from
laboratory experiments do not provide suitable quantitative relationships
for establishing air quality criteria for particulates. These studies do,
however, provide valuable information on some of the bio-environmental
relationships that may be involved in the effects of particulate air pollution
on human health.
Toxicological studies on animals have shown that:
1. Particulate matter may exert a toxic effect via one or more
of three mechanisms:
(a) The particle may be intrinsically toxic because of its
inherent chemical and/or physical characteristics.
(b) The particle may interfere with one or more of the
clearance mechanisms in the respiratory tract.
(c) The particle may act as a carrier of an adsorbed toxic
substance.
2. Evaluation of irritant particulates on the basis of mass or
concentration alone is not sufficient; data on particle size and number
averages per unit volume of carrier gas are needed for adequate interpretation.
3. The toxicological importance to mankind of submicron particles
cannot be overemphasized.
4. Particles below 1 ^ may have a greater irritant potency th&n
larger particles.
5. A small increase in concentration could produce a greater-then-
linear increase in irritant response when the particles are < 1 .|i.
182
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6. All particulate matter does not potentiate the response to
irritant gases.
7. Both solubility of sulfur dioxido in a droplet and catalytic
oxidation to sulfuric acid play a role in the potentiation of sulfur dioxide
by certain particulate matter.
The analyses of numerous epidemiological studies clearly indicate
an association between air pollution, as measured by particulate matter
accompanied by sulfur dioxide, and health effects of varying severity. This
association is most firm for the short-term air pollution episodes. The
studies concerned with increased mortality also show increased morbidity.
The association between long-term residence in a polluted area
and chronic disease morbidity and mortality is somewhat more conjectural.
However, in the absence of other explanations, the findings of increased
morbidity and of increased death rates for selected causes, independent of
economic status, must still be considered consequential.
Information is lacking regarding the mechanisms involved in the
enhancement of viral virulence by specific air pollutants. Specific methods
by which air pollutants can synergistically affect viral infections are
unknown. It is possible thot fine particulate matter may act as carriers
for certain virus agents.
183
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1. Introduction
The effects on man and his environment of particulate matter are
produced by a combination of particulate and gaseous pollutants. The effects
on human health are, for the most pert, related to injury to the surfaces
of the respiratory system. Such injury may be permanent or temporary. It
may be confined to the surface, or it may extend beyond, sometimes producing
functional or other alterations. Particulate material in the respiratory
tract may produce injury itself, or it may act in conjunction with gases,
altering their sites or their modes of action. A combination of particulates
and gases may produce an effect that is greater than the sum of the effects
caused by either individually (i.e., synergistic effect).
Laboratory studies of man and other animals show clearly that the
deposition, clearance, and retention of inhaled particles is a very complex
process, which is only beginning to be understood. Particles cleared from
the respiratory tract may exert effects elsewhere. Available data from
laboratory experiments do not provide suitable quantitative relationships"
for establishing air quality criteria for particulates. These studies do,
however, provide valuable information on some of the bio-environmental
relationships that may be involved in the effects of particulate air pollution
on human health.
The following sections present an overview of (l) the physics ^
and physiology of deposition, retention, and clearance in the respiratory
system; (2) toxicological studies of atmospheric particulate matter; and
(3) epidemiological studies of atmospheric particulate matter.
2. Deposition, Retention, and Clearance Processes in the Respiratory ,
System
An understanding of the effect on human health of particulate
pollutants requires knowledge of the following processes: ;
1. Mechanisms and efficiencies of particle deposition in the
respiratory system;
2. Retention mechanisms;
3. Clearance mechanisms; and
4. Secondary relocation to other sites in'the body.
Theoretical and experimental studies have been conducted to define the fac-
tors involved in deposition, retention and clearance processes. The princi-
pal results of these studies are summarized in the following sections.
184
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2.1 Deposition
2.1.1 Theoretical aspects: Hie physical forces which operate
to bring about aerosol deposition within the respiratory system vary in
mofTiitude not only with particle size but also with the oir velocities and
times of transit of the air from place to place within the system and from
moment to moment throughout the breathing cycle. Three mechanisms are of
importance in the deposition of particulate matter in the respiratory tract:
1. Inertial impaction - greatest importance in deposition of
large particles of high density, and at points in the respiratory system
where the direction of flow changes at branching points in the airways;
2. Gravitational settling (sedimentation) - most important in the
deposition of large particles or of high-density particles such as dusts of
heavy metals; and
3. Diffusion (Brownian motion) - major mechanism for the depo-
sition of small particles (below 0.1 (a,) in the lower pulmonary tract.
Hie effectiveness with which the decomposition forces remove
particles from the air at various sites depends upon the obstruction en-
countered, changes in direction of air flow, and the magnitude of particle
displacement necessary to remove them from the air stream. The anatomical
arrangement and physical dimensions of the respiratory system, transport
mechanisms, flow rates and gas mixing, and aerosol particle size are important
factors that must be considered in any physical analysis of the deposition
of inhaled aerosols.
The Task Group on Lung Dynamics has recently developed a model
for the deposition of particles in the respiratory tract.^/ Findeisen's
anatomical model?/ was chosen as the basis for the Task Group Model. The
Task Group used the conventional division of the respiratory tract into
three compartments (nasopharyngeal, tracheo-bronchial, and pulmonary),
and made three fundamental assumptions in the development of their model.
These were:£/
1. Log-normal frequency distribution is generally applicable to
particle sizes in the atmosphere.
2. The physical activity of the individual affects deposition
primarily by its action on ventilation.
3. The aerodynamic properties of the particle, the physiology
of respiration, and the anatomy of the respiratory tract provide a basis for
a meaningful and reliable deposition model.
185
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Calculations, basically similar to those of Findeisen, were used
to estimate the deposition in the three respiratory compartments. When
the mass median aerodynamic diameters of 0.01 to 100 (a, of various distri-
butions were plotted against the estimated mass deposition of particles
occurring in each respiratory compartment, surprisingly little variability
was seen. The geometric standard deviation for these distributions varied
from 1.2 to 4.5. The results of these calculations are shown in Figure
B-1.2/ The curves indicate a relationship between the mass median aero-
dynamic diameter and the gravimetric fraction of the inhaled particles
which would be deposited in each anatomical compartment. Within these limits
(0.01 to 100 ji), the-mass median aerodynamic diameter served to characterize
the deposition probabilities of the entire particle size distribution. Other
pnr rime trie functions of the particJo distribution failed to produce such
uimple cohesive relationships.!^/ Figures B-2 and B-?> present plots of the
mass median diameter versus mean respiratory performance. The deposition in
the tracheo-bronchial compartment is considered as constant at approximately
8% of the respired particulate matter.
2.1.2 Experimental studies; Experimental studies of the deposi-
tion of inhaled particulate material may be divided into two broad cate-
gories. The first group deals with the measurement of total deposition in
the respiratory tract, and the second group is concerned with regional
deposition within the various areas of the respiratory tract. Details of
these experiments are given in Refs. 1 and 4. The following points can be
made with respect to the overall retention characteristics of the respiratory
system:!/
1. Percentage deposition increases with aerodynamic particle
size from a minimum value of about 25% at approximately 0.5 y. and approaches
100$ for particles > 5 \i. Particles -of different densities and shapes
follow the same deposition curve wh'?n size is expressed in terms of equivalent
diameter of unit-density spheres.
2. Percentage deposition also increases as particle size decreases
below 0.5 M, owing to the increasing magnitude of the force of deposition
by diffusion. For particles < 0.1 p,, the percentage deposited out of the
total respired air approaches, in value, the fraction of tidal volume which
reaches the pulmonary air spaces. This fact suggests that the absolute
efficiency of alveolar deposition of these submicron particles approaches
100%.
3. Particles of hygroscopic materials are removed in higher per-
centages than are nonhygroscopic particles of the same (dry) size because
of the growth of such particles by water adsorption from the moist air in
the respiratory system.
186
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NASOPHARYNGEAL
MASS MEDIAN DIAMETER, MICRON
Figure B-l - Fraction of Particles Deposited in the Three
Respiratory Tract Compartments as a
Function of Particle Diameter^/
187
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188
-------
4. Percentage deposition varies with br^wthing frequency, in-
creasing, for n heterogeneous aerosol, in both directions from a minimum
level et frequencies of ]5 to I'O cycl''C/min. At slower rates, the prob'ibNi'.y
of deposition by gravity settlement and diffusion goey up in proportion to
the increase in transit time of the dust-laden eir into and out of the lungs.
With more rapid breathing, percentage deposition of the coarser particles
increases because of the rise in force of inertial deposition with increasing
air velocity.
5. There is reasonably good agreement between the directly mee-
sured values of overall deposition and the levels predicted from mathematical-
physical equations, with respect to both particle size and dynamics of air
flow into and out of the respiratory system. Thus, in its behavior as a
dust-trapping device, the respiratory system appears to act very much like
any other similar physical apparatus.
The differing characteristics of particle retention at various
depths within the respiratory system may be summarized as follows:—'
1. Particles larger than 10 n are essentially all removed in the
nasal chamber and therefore have little probability of penetrating to the
lungs. Upper respiratory efficiency drops off as size decreases and becomes
essentially zero at about 1 |j,.
2. The efficiency of particle removal is high in the pulmonary
air spaces, being essentially 100$ down to around 2 p-« Below this size it
falls off to a minimum at about 0.5 jj,. It then increases again as the force
of precipitation by diffusion increases with further reduction in size.
3. The percentage penetration of particles into the pulmonary
air spaces rises from essentially zero at 10 jj, to a maximum at and below
1 n, where it equals the fraction of tidal air which reaches the lung.
4. Below 0.5 m the probability of deposition in the pulmonary
air spaces rises in proportion to the increase in the force of precipitation
by diffusion with decreasing size.
5. Relative amount deposited and the distribution of the collected
particles in the respiratory system change with breathing frequency and
tidal volume. Upper respiratory trapping increases as the rate of inspired
air flow goes up with faster breathing frequency. Magnitude of deep-lung
deposition increases with slow, deep breathing because of the larger frac-
tion of tidal air which reaches the pulmonary spaces and the longer transit
time of air into and out of the lungs.
189
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2.2 Clearance of Particulate Matter from the Respiratory System
The overall effectiveness of clearance mechanisms in the lung is
well documented by the finding that the actual amount of mineral dust found
in the lungs of miners or city dwellers at autopsy is only a minor fraction
of the total dust that must have been deposited there during their lives.
The clearance of certain particles may be very slow, and the rate is dependent
upon size, site of deposition, and chemical composition.
Relative to other factors, the importance of removal from the
respiratory system of trapped particulate materials depends on the rate at
which the material elicits a pathological or physiological response. The
effect of an irritant substance which produces a rapid response may depend
more on the amount of initial trapping than on the rate of clearance. On
the other hand, materials such as carcinogens, which may produce a harmful
effect only after long periods of exposure, may exhibit activity only if the
relative rates of clearance and deposition are such that a sufficient con-
centration of material remains in the body long enough to cause pathological
change. In such a case, the amount of initial deposition will be of rela-
tively minor importance,=J
Different clearance mechanisms operate in the different portions
of the respiratory tract, so that the rate of clearance of a particle will
depend not only on its physical and chemical properties such as shape and
size, but also on the site of initial deposition. The fast phases of the
lung clearance mechanisms are different in ciliated and nonciliated regions.
In ciliated regions, a flow of mucus transports the particles to the entrance
of the gastrointestinal tract, while in the nonciliated pulmonary region,
phagocytosis by macrophages can transfer particles to the ciliated region.
The rate of clearance is an important factor in determining toxic responses,
especially for slow-acting toxicants such as carcinogens. The presence of
a nonparticulate irritant or the coexistence of a disease state in the lungs
may interfere with the efficiency of clearance mechanisms and thus prolong
the residence .time of particulate material in a given area of the respiratory
tract. In addition, since the clearance of particles from the respiratory
system primarily leads to their entrance into the gastrointestinal system,
organs remote from the deposition site may be affected.i/
The Task Group on Lung Dynamics developed a model for respiratory
clearance and also summarized experimental work on clearance. Details of
the model and the analysis of experimental data are presented in Refs. 1
and 2, and the reader interested in a more complete discussion of respiratory
clearance is directed to these sources.
190
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3. Toxicological Studies of Atmospheric Particulate Matter
Experimental toxicology develops information on the mode of action
of specific pollutants, on the relative potency of pollutants having a
similar mode of action, and on the effect of one pollutant on the magnitude
of response to another. If man could "be used as the experimental subject,
experimental toxicology would be the best means of deriving air quality
criteria. However, the impossibility of performing experiments using human
exposures to varying concentrations of a wide range of compounds precludes
this direct approach. A limited amount of intentional human experimentation
has been conducted, but most of the data for human toxicology are derived
from accidental or occupational exposures.
The use of laboratory animals in toxicological experiments is more
straightforward, but the obvious anatomical and metabolic differences be-
tween the animals and man require the exercise of caution in applying the
results of animal exposures to human health criteria. Furthermore, many of
the animal experiments have been conducted at exposure concentrations far in
excess of those likely to be found in the atmosphere.
In spite of these limitations, toxicological studies have shown that
atmospheric particles may elict a pathological or physiological response.
Three types of responses have been determined:
1. The particle may be intrinsically toxic;
2. The presence of an inert particle in the respiratory tract may
interfere with the clearance of other airborne toxic materials; and
3. The particle may act as a carrier of toxic material.
Few common atmospheric particulate pollutants appear to be in-
trinsically toxic; of these, the most important toxic aerosol is sulfur
trioxide (SOs) (either as the free oxide, or hydrated as sulfuric acid—
112804), which has a high degree of toxicity, at least for the guinea pig.
Although silica (from fly ash) is frequently present as a pollutant,
atmospheric concentrations are normally too low to lead to silicosis. In
recent years, however, concern has been expressed over a number of less
common toxic particulate pollutants, including lead, beryllium, and asbestos.
Toxic substances may be adsorbed on the surface of particulate
matter, which may then carry the toxic principle into the respiratory system.
The presence of carbon or soot as a common particulate pollutant is note-
worthy, as carbon is well known as an efficient adsorber of a wide range of
organic and inorganic compounds.
191
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The role played by the affinity for the adsorbate by the particle
is complex. A high affinity will mean that relatively large loads of ad-
sorbate may be carried by each particle. If the adsorbate in its free state
is slowly removed from the air in the respiratory system, then the deposi-
tion of particles carrying high concentrations may constitute a greater toxic
hazard, especially at the localized deposition points. Whether or not the
effect is significant .depends on whether the efficiency of the desorption
and elution processes is greater or less than that of the clearance process.
The chemical nature of both adsorber and adsorbate, and the size of the ad-
sorbing particle, all play a part in determining these various efficiencies,
and each system will show its own individual characteristics.
3.1 Toxicological Studies of Specific Particulate Materials
Certain particulate materials are pulmonary irritants, and have
been shown to produce alterations in the mechanical behavior of the lungsj
the alteration is predominantly an increase in flow resistance. This was
demonstrated by Amdur for sulfuric acid,Z/ and by Amdur and Cornjy for am-
monium sulfate, zinc sulfate, and zinc ammonium sulfate, using the guinea
pig as an assay animal. Nader and co-workers report a correlation between
the alterations in pulmonary mechanics and actual anatomical change in cats
exposed to aerosols of histamine and zinc ammonium sulfate.§/
The effect of various aerosols on the response to SOg has also been
also examined, using the guinea pig bioassay system. These data are pre-
sented in detail in Ref. 9. Conditions which lead to the solution of SOg
in a droplet and catalyze its oxidation can alter the irritant potency of
levels of SOg which occur in areas of high pollution. The concentration of
the catalytic aerosols (soluble salts of iron, manganese, and vanadium) was
of the order of 1 mg/m3 which is higher than concentrations reported for
these metals in urban air. Particles which do not form liquid droplets, i.e.,
non-soluble salts such as iron oxide fume, carbon fly ash, open hearth dust,
and manganese dioxide, did not show a potentiating effect.
Dautrebande and DuBois have reported constriction and increased
airway resistance in isolated guinea pig lungs and in human subjects with
a wide variety of supposedly inert particulates ,12/ The relationship of
their'results to Amdur*s work is not clear since Dautrebande*s particle
concentrations appear to be abnormally high.
When a substance is dispersed in the air in the form of particulate
matter, a simple statement of its concentration is insufficient to define in
meaningful terms its toxic potential. The size of the particles is also a
prime factor in the overall biological impact of inhaled particulate material.
192
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This point can be illustrated with data obtained by Amdur and Corn for an
aeroso^ of zinc ammonium sulfate,^J The investigation of this compound wee
undertaken because it had been identified as one of the substances'present
during the 1040 Donora i'of/.ly FJj/ure B-4 tihows the response of //u.inea plfis
to zJnc nmmoniium ou'lfnlc i\\, n i"on;;Utnl concentration (fibout I ro#/rn3), !>nt of
different pnrtide size;:. W.illiin the nizc r tinge studied, the irritant
potency increased with d<;<: reusing partJcle size. Figure B-5 shows the more
extensive data obtained on the dose-response curves of zinc ammonium sulfato
at different particle sizes. These data show that not only is the irritant
effect greater for the smaller particles at a given concentration, but also
the dose-response curve steepens as the particle size is decreased. Thus,
if an irritant aerosol is composed of very small particles, a relatively
slight increase in its concentration can produce a relatively great increase
in irritant response.
From the analytical datajy it can be estimated that the concentra-
tion of zinc ammonium sulfate present during the Donora fog might have been
on the order of magnitude of 0.05 to 0.25 mg/m^. The toxicological data
can in no way be extrapolated to predict what, if any, contribution this
substance made to the overall irritant character of the atmosphere. On the
other hand, the data do indicate that without information on particle size,
such predictions are not possible.
The possible influence of inert particulate matter on the toxicity
of irritant gases has been the subject of considerable speculation and a
limited amount of experimental work. Work on the synergistic.effects of
aerosols and irritant gases is reported in Refs. 11 to 19. The potentiation
of irritant gases by particulate material noted in these studies was attrib-
uted to the adsorption of gas on the particles. Adsorption of the gas on
small particles would tend to carry more gas to the lungs and thus increase
the toxicity. Unfortunately in many of these studies, the end point was the
dosage required to produce death. With concentrations of this magnitude,
the results have little applicability to air pollution.
Amdur has studied the effect of particulate material on the
response to sulfur dioxide using the pulmonary flow resistance technique.
None of the aerosols used in the studies produced any effect alone.£/ From
these studies it appears that the major mechanism underlying the potentia-
tion is solubility of sulfur dioxide in a droplet and subsequent catalytic
oxidation to sulfuric acid.
193
-------
u
z
i/i
UJ
Of
200-
100-
50^
20-
10
5-
10
± 2
^* 1
0.01 0.05 0/50
AEROSOL MEAN SIZE BY WEIGHT, MICRON
111 ii
5.0
Figure B-4 - Effect of Particle Size on the Response to Approximately
1 mg/m3 Zinc Ammonium Sulfate. Numbers beside
each point indicate the number of animals.§/
3.6
mg/n
Figure B-5 - Relationship of Response to Concentration for Zinc Atnmonium
Sulfate of Different Particle Sizes. Numbers beside
each point indicate the number of animals.57
194
-------
Figure B-6 shows the effect of aerosols of sodium chloride,
potassium chloride, and ammonium thiocyanate, at concentrations of about
10 mg/m^, on the response to about 2 ppm sulfur dioxide. All these sub-
stances are soluble salts which would absorb water to become liquid droplets
at the humidity of the respiratory tract. Sulfur dioxide is increasingly
soluble in aqueous solutions of these salts as one goes from sodium chloride,
to potassium chloride, to ammonium thiocyanate. The degree of potentiation
observed can be related in a reasonable manner to the degree of solubility
of sulfur dioxide in the salt solutions.
Figure B-7 shows the results of exposure to about 2 ppm of sulfur
dioxide alone and in the presence of another group of aerosols. These
aerosols do not take on water to become droplets during transit of the
respiratory tract, and have no detectable effect upon the response to sulfur
dioxide. The combination of data in Figures B-6 and B-7 suggests that
solubility in a droplet plays a role.2/
Figure B-8 shows the dose-response curves to sulfur dioxide alone
and in the presence of aerosols of soluble salts of manganese, iron, and
vanadium. These substances were present at a concentration of about 1 mg/m^.
They have another property in common. When such salts become nuclei of fog
droplets, they are capable of catalyzing the oxidation of sulfur dioxide to
sulfuric acid.§2/ The addition of these inert particles produced about a
threefold potentiation in the response to sulfur dioxide. The similar
magnitude of potentiation produced by the three salts suggests a similar
mechanism for the potentiation. The data from Figure B-7 showing the lack
of potentiation by dry manganese dioxide or iron oxide would appear to in-
dicate the importance of solubility.
Experimental data on the effect of particulate matter on the
responses to sulfur dioxide in human subjects are very limited.£ii£5/
Furthermore, there is no general agreement regarding potentiation by
particulates. To date human exposures have been disappointing in disclosing
mechanisms of interaction between various air pollutants. On the other hand,
there is no evidence as yet for a species difference between animals and
man; therefore, we may extrapolate judiciously to man from the animal studies.
Conclusions
1. Particulate matter may exert a toxic effect via one or more of
three mechanisms:
(a) The particle may be intrinsically toxic because of its
inherent chemical and/or physical characteristics.
195
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SO2
u
z
<
—
CO
LU
oe.
LU
CO
<
LU
a:
U
Z
100
80
60
40
0
"™
-
—
-
-
so2
•X'X'X'X*
so2 +
NaCI
XvXvXv
SO2 +
KCI
X:X:x:::x:
:j:|:^i;:j:j:|:|
;:-x'$x"?:::
|V
1114 :*.
xvx-:vx
:x:x:x:x:
5:?:?:W:
:?:-:S?S
IN
PPM
ANIMALS
2.6
16
2.0
10
2.3
16
1.9
16
Figure B-6 - Effect of Aerosols Capable of Dissolving
Differing Amounts of Sulfur Dioxide on
the Irritant Potency of the Gas§/
Z.
CO
CO
LU on
of 20
Z
LU
CO
I 10
-------
UJ
U
Z
<
—
«/»
UJ
C£
100
50
S ,0
U
S i
A SO,
A SO2 + V
D SO2 + Mn
O SO2 •
,+5
i 11 u in
0.1 0.5 1 5 10
SO2 - PPM
50 100
Figure B-8 - Effect of Aerosols Which Would Form Droplets
and Also Catalyze the Oxidation of Sulfur
Dioxide to Sulfuric Acid on the Irritant
Potency of the Gas. The numbers beside
each point indicate the number of animals.^/
197
-------
('()) 'llu; I'.'irUr li; limy iiitx^r/V-r'; wJth on<: or trio/1'.- of Ui';
olunruneu mc.'chaniumt; in l,lx: i".:;;pjrulory trfju-t.
(c) Ihe particle may act as a carrier of an adsorbed toxic
substance.
2. Evaluation of irritant particulates on the basis of mass or
concentration alone is not sufficient; data on particle size and number
averages per unit volume of carrier gas are needed for adequate interpretation.
3. The toxicological importance to mankind of submicron particles
cannot be overemphasized.
4. Particles below 1 M, may have a greater irritant potency than
larger particles.
5. A small increase in concentration could produce a greater-than-
'linear increase? in irritant response whnn the particles ar*: < ~\ M-.
6. All particulate matter does not potentiate the response to
irritant gases.
7. Both solubility of sulfur dioxide in a droplet and catalytic
oxidation to sulfuric acid play a role in the potentiation of sulfur dioxide
by certain particulate matter.
4. Epidemiological Studies of Atmospheric Particulate Matter
Ihe ultimate assessment of the impact of air pollution on human
health can come only from epidemiology. Because particulate matter and
sulfur oxides tend to occur together in a polluted atmosphere, few epidemic-
logic studies have been able adequately to differentiate the effects of the
two pollutants. Because we do not now have a good epidemiological basis for
stating the influence of particulates, only a brief synopsis of epidemiological
studies of atmosphere particulate matter will be presented. References 1
and 26 present an extensive review of epidemiological studies, and those
seeking more detail are directed to these sources.
Epidemiologic studies of the relationship between pollutant con-
centrations and their effects on health have used indices varying from
disturbance of lung function to death. British studies of acute episodes
of increased pollution show excess deaths occurring at smoke levels from
750 |j,g/m3 to 2,000 ng/m3. High SOg levels are, of course, concurrently
present. The excesses of mortality are always accompanied by a very large
198
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increase in illness, mainly exacerbations of chronic conditions. Similar,
but less spectacular, episodes have been reported in Now York City.i/
Winkelstein found in Buffalo that increases in the mortality rate
were significantly linked to higher levels of suspended particulate pollu-
tion.27/ His studies showed that mortality from all causes, from chrord'; .
respiratory diseases, and from gastric carcinoma increased from the lowest
of his five levels of pollution (less than 80 ^.g/m3) through the three higher
ranges, after the effects of socioeconomic status had been considered.
Zeidberg found in Nashville significant increases in all respiratory deaths
at soiling levels over 1.1 cons annual average.28^29/ Neither of these
studies took smoking habits into account, and the Nashville study only
partially allowed for socioeconomic factors.
Studies of illness in relation to residence in more- and less-
polluted areas contribute additional information. Fletcher e_t al. noted
a proportional decline in the production of morning sputum in chronic
bronchitics in West London from 1961 to 1966 as smoke pollution in their
residence areas declined from 140 (jg/m3 annual mean.30./ Douglas and Waller
found an increase in frequency and severity of lower respiratory illness at
smoke and S02 levels over 130 ^g/m3 annual average.3i/ A study of Lunn
ot al. shows similar differences occurring with more morbidity measured be-
twoen about 100 ^g/m3 and 200 u-g/m3 of smoke, and for others between 200
|j,g/m3 and 300 jig/m3 annual average .3§/
Physiologic studies of lung function have also been made in both
adults and children. On the basis of present limited knowledge it appears
that the alterations found may be both temporary and permanent. The obser-
vations now available relate to long-term residence in a given area. The
study reported in Ref. 32 shows reduced pulmonary function in the children
in the most polluted area, i.e., where smoke concentration is above 300 ^tg/m3.
Studies in Japan show a decrease in pulmonary function in school children
living in areas of high dustfall as compared with those living in low dust-
fall areas. In Osaka the dustfall levels were 6.5 gm/n^-month and 13.3 gm/m^-
month.33/
The analyses of numerous epidemiological studies clearly indicate
an association between air pollution, as measured by particulate matter
accompanied by sulfur dioxide, and health effects of varying severity. This
association is most firm for the short-term air pollution episodes. The
studies concerned with increased mortality also show increased morbidity.
The association between longer term community exposures to
particulate matter and respiratory disease incidence and prevalence rates
is believed to be intermediate in its reliability.!/
199
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The association between long-term residence in a polluted area
and chronic disease morbidity and mortality is somewhat more conjecture].
However, in the absence of other explanations, the findings of. increased
morbidity and of increased death rates for selected causes, independent
of economic status, must still be considered consequential.
Information is also lacking regarding the mechanisms involved in
the enhancement of viral virulence by specific air pollutants. Specific
methods by which air pollutants can synergistically affect viral infections
are unknown. It is possible that fine particulate matter may act as carriers
for certain virus agents. Experimental evidence bearing on this point is
lacking. The complex interrelationship between the dynamic inflammatory
processes is difficult to define. So are the equally important irritative
effects of air pollutants and viral infections.
200
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REFERENCES
1. Air Qiality Criteria for Particulate Matter, USDHEW, NAPCA Publication
AP-49, Washington, D. C., January 1969.
2. "Deposition and Retention Models for Internal Dosimetry of the Human
Respiratory Tract," Task Group on Lung Dynamics, Health Physics,
12, 173-207 (1966).
3. Findeisen, W., "Uber das Absetzen kleiner in der Luft suspendierten
Teilchen in der menschlichen Lunge bei der Atraung," Arch. Ges. Physiol.,
Vol. 236, 367-379 (1935).
4. Hatch, T. F., and Paul Gross, Pulmonary Deposition and Retention of
Inhaled Aerosols, Academic Press, New York (1964).
5. Andur, Mary 0.; and Morton Corn, "The Irritant Potency of Zinc Ammonium
Sulfate of Different Particle Sizes," Amer. Indust. Hyg. Assoc. Journal,
24_, 326-333 (1963).
6. Hemeon, W. G. L., "The Estimation of Health Hazards from Air Pollution,"
Arch. Indust. Health, 11, 397-402 (1955).
7. Amdur, M. 0., "The Respiratory Responses of Guinea Pigs to Sulfuric Acid
Mist," Arch. Ihd. Health, 18, 407-414 (1958).
8. Nader, J. A., .et al., "Location and Mechanism of Airway Constriction
after Inhalation of Histamine Aerosol and Inorganic Sulfate Aerosol,"
Ir: Inhaled Particles and Vapors,,Vol. 11, C. N. Davies (ed.), Pergamon
Press, London (1967).
9. Amdur, M. 0., and D. Underhill, "ihe Effect of Various Aerosols on the
Response of Guinea Pigs to Sulfur Dioxide," Arch. Environ. Health, !£,
460-468 (1968).
10. Dautrebande, L., Microaerosols, Academic Press, New York (1962).
11. Dautrebande, L., "Bases experimentales de la protection centre les gas
de combat," J. Duculot (Belgium) (1939).
12. Dautrebande, L., and R. Capps, "Studies on Aerosols. DC. Enhancement
of Irritating Effects of Various Substances in the Eye, Nose, and Throat
by Particulate Matter and Liquid Aerosols in Connection with Pollution
of the Atmosphere," Arch. Intern. Pharmacodyn, 82^ 505-527 (1950).
201
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13. Dautrebande, L., J, Shaver and R. Capps, "Studies on Aerosols. XI.
Influence of Particulate Matter on Eye Irritation Produced by
Volatile Irritants and Importance of Particle Size in Connection
with Atmospheric Pollution," Arch. Intern. Pharmacodyn, 85^ 17-48
(1951).
14. LaBelle, C. W., J. E. Long and E. E. Christofano, "Synergistic Effects
of Aerosols. Particulates as Carriers of Toxic Vapors," Arch. Ind.
Health, 11, 297-304 (1955).
15. Dalharan,T., and L. Reid, "Ciliary Activity and Histologic Observations
in the Trachea after Exposure to Ammonia and Carbon Particles," In:
Inhaled Particles and Vapours, Vol. II, C. N. Davies (ed.), Pergamon
Press, London (1967).
16. Boren, H. C., "Carbon as a Carrier Mechanism for Irritant Gases,"
Arch. Environ. Health, 8, 119-124 (1964).
17. Gross, P., W. E. Rinehard and R. T. DeTreville, "The Pulmonary Reactions
to Toxic Gases," Am. Ind. Hyg. Assoc. J., 2JT, 315-321 (1967).
18. Pattle, R. E., and F. Burgess, "Toxic Effects of Mixtures of Sulphur
Dioxide and Smoke with Air," J. Pathol. Bacteriol., 73, 411-419
(1957 ). "*""
19. Salem, H., and H. Cullunbine, "Kerosene Smoke and Atmospheric Pollutants,"
Arch. Environ. Health, 2, 641-647 (1961).
20. Johnstone, H. F., and D. R. Coughanowr, "Absorption of Sulfur Dioxide in
/_•?-,- o>:i Lition in Dropn Containing Dis.iolvad Catalysts," Induct. Erg.
Chc.a., _5Q, 1169-1172 (1958).
21. Frank, N. R., M. 0. Amdur and J. L. Whittenberger, "A Comparison of the
Acute Effects of SO^ Administered Alone or in Combination with NaCl
Particles on the Respiratory Mechanics of Healthy Adults," Intern. J.
Air & Water Poll., 8_, 125 (1964).
22. Burton, G. G., M. Corn, J. B. L. Gee, C. Vassallo and A. Thomas, "Absence
of Synergistic Response to Inhaled Low Concentration Gas-Aerosol Mix-
tures in Healthy Adult Males," Presented at Ninth Annual Air Pollution
Medical Research Conference, Denver, Colorado (1968).
23. Toyama, T., "Studies on Aerosols. I. Synergistic Response of the
Pulmonary Airway Resistance of Inhaling Sodium Chloride Aerosols and
S02 in Man," Japan J. Ind. Health, 4, 86 (1962).
202
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24. Nakamura, K., "Response of Pulmonary Airway Resistance by Interaction
of Aironola and Gfiaea in Different PhyaJoal '».nd Chemical States,
"
25. Toyama, T. , and K. Naknmura, "yynergistit: Response of Hydrogen K- ro /.:.'>.•
Aerosols and Sulfur Dioxide to Pulmonary Airway Resistance," Ind.
Health, 2, 34 (1964).
26. Speizer, F. E., "An Epidemiological Appraisal of the Effects of Ambient
Air on Health: Particulates and Oxides of Sulfur," JAPCA,
647-656 (1969).
27. Winkelstein, W., "The Relationship of Air Pollution to Cancer of the
Stomach," Arch. Environ. Health, 18. 544-547 (1969).
28. Zeidburg, L. D., R. M. Hagstrom, H. A. Sprague and E. Landau, "Nashville
Air Pollution Study. VII. Mortality from Cancer in Relation to Air
Pollution," Arch. Environ. Health, !£, 237-248 (1967).
29. Zeidberg, L. D., R. J. M. Ilorton and E. Landau, "'Hie Nashville AJr
Pollution Study. V. Mortality from Diseases of the Respiratory
System in Relation to Air Pollution," Arch. Environ. Health,
214-224 (1967).
30. Fletcher, C. M., B. M. Tinker, I. D. Hill and F. E. Speizer, "A Five-
Year Prospective Field Study of Chronic Bronchitis," Preprint.
(Presented at the llth Aspen Conference on Research in Emphysema
June 1968. )
31. Douglas, J. W. B., and R. E. Waller, "Air Pollution and Respiratory
Infection in Children," Brit. J. Prevent. Soc. Msd., j2
-------
APPENDIX C
MODIFICATION OF THE ATMOSPHERE
BY PARTICULAR! POLLUTION
205
Preceding page blank
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Summary
Suspended fine particles may have considerable influence on the
behavior of the atmosphere and thus on human activities. They can act as
condensation or freezing nuclei and thereby modify weather patterns.
They absorb and scatter light and decrease visibility. Fine particlcc in
the atmosphere may nine influence xnlnr radiation and interfere with
astronomical observation.'; .
Visibility reduction related to air pollution is caused primar-
ily by the 0.1 to 1.0 )J, radius particles in the atmosphere. The visi-
bility problem associated with particulate air pollution can be divided
into specific smoke plumes and well-aged aerosols. The visual appearance
of smoke plumes and visual obscuration by smoke plumes are closely related
to the amount of light the plumes scatter in the direction of the viewer
from their surroundings and the sun. Consequently, evaluation of plumes
by a visual effect is more difficult for nonblack plumes than for black
plumes, and depends on plume illuminating and viewing conditions. Because
of this, nonblack plumes could be evaluated differently when viewed on
different days or viewed from different directions, though their aerosol
content has not changed. Furthermore, the size of particles and mass per
unit time emitted from the stack, and not the appearance or optical prop-
erties of the plume, are more important to the eventual air composition,
even though appearance may be aesthetically objectionable.
Recent advances in our knowledge of the Hize distributions and
optical properties of well-aged atmospheric aerosols have resulted in a
clearer description of visibility reduction by such aerosols. Theoretical
and experimental studies of well-aged aerosols have shown that:
1. Aerosols in the lowest region of the atmosphere (troposphere),
whether over urban areas or not, tend to have similar size distributions.
2. A narrow range of particle sizes, usually from 0.1 to 1.0 p,
radius, controls the extinction coefficient and thereby visibility.
3. The mass concentration of a well-aged aerosol -is approximately
proportional to the light scattering coefficient for atmospheric aerosols
originating naturally or as the result of man's activity.
The increased emission of fine particles into the atmosphere may
cause changes in the delicate heat balance of the earth-atmosphere system,
thus altering worldwide climatic conditions. Comparisons at different
sites over the world covering periods of up to 50 years suggest that a
general worldwide rise in turbidity may be taking place . This may well be
indicative of a gradual buildup of worldwide background levels of suspended
206
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particulates. The net influence of atmospheric turbidity on surface tem-
perature is uncertain, but *ne emission of long-lived particles may well be
leading to a decrease in world air temperature. As more is learned nbout
the general circulation of the atmo.-iphore and the delicate bnlnncc b •tw-'-n
incoming and outgoing radiation, It r^eems increasingly probable that r;m/ij,i
changes such as those occasioned by increasing particle loads in the atmo-
sphere may produce very long-term meteorological effects.
Suspended particulate matter may alter weather patterns. There
is evidence that some of the particles introduced into the atmosphere by
man's activities can act as nuclei in processes which affect the formation
of clouds and precipitation. Investigations of snow and rainstorm patterns
indicate that submicroscopic particulates from man-made pollution may be
initiating and controlling precipitation in a primary manner, rather than
being involved in the secondary process wherein precipitation elements com-
ing from natural mechanisms serve to remove the particles by diffusion,
collision, and similar scavenging processes.
207
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1. Introduction
The suspended atmospheric particles are of four general types.
The first are the "light ions" produced in the air by cosmic rays and
radioactivity. They consist of small aggregates of molecules having dimen-
sions up to a few molecular diameters. The second important type of par-
ticle consists of the so-called "aitken nuclei." These particles range in
radius from 2 x 10 cm. up to 10 cm. They are particularly prevalent
near cities and the earth's surface. As a rule of thumb, one anticipates
finding about 100,000 of these particles per cm3 in a large city, about
10,000/cm in the country, and about 1,000/cm3 at sea. The numbers decrease
with increasing altitude and only about 10$ of the surface populations are
found at an Altitude of 7 km. Thu fine jiurticl^ polDutJori of the air is
largely composed of these nuclei.
The third type of atmospheric particle is the cloud droplet hav-
ing a radius from 10"^ cm. to 5 x 10"^ cm. Finally, the cloud droplets
associate to form raindrops or snowflakes that fall at velocities depen-
dent upon their size. Rain or snow represents the final stage for the re-
moval of atmospheric pollution by natural methods.
Suspended fine particles may have considerable influence on the
behavior of the atmosphere and thus on human activities. They can act as
condensation or freezing nuclei and thereby modify weather patterns. They
absorb and scatter light and decrease visibility. Fine particles in the
atmosphere may also influence solar radiation and interfere with astronom-
ical observations. These facets of fine particulate pollution are reviewed
in the following sections.
2. Visibility
Decreased visibility obviously interferes with certain human ac-
tivities, such as safe operation of aircraft and automobiles and the enjoy-
ment of scenic vistas. Air pollution that reduces visibility, in addition
to endangering the safety of both air and land travel, results in incon-
venience and economic loss to the public, and to transportation companies
due to disruption of traffic schedules.
Visibility reduction related to air pollution is caused primarily
by the 0.1 to 1.0 p. radius particles in the atmosphere. Deterioration of
visibility caused by suspended particulate matter is the result of absorp-
tion and scattering of light. Both the brightness of the viewed object
and its visual contrast with the background are reduced by attenuation of
light due to scattering and absorption. In addition, a further contrast
208
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reduction results from scattering of sunlight into the observer's line of
sight. Loss of brightness and contrast are responsible for the subjective
impression of impaired visibility.
The visibility problem associated with particulate air pollution
can be divided into specific smoke plumes and well-aged aerosols. The vi-
sual appearance of smoke plumes and visual obscuration by smoke plumes are
closely related to the amount of light the plumes scatter in the direction
of the viewer from their surroundings and the sun. Consequently, evaluation
of plumes by a visual effect is more difficult for nonblack plumes than for
black plumes, and depends on plume illuminating and viewing conditions. Be-
cause of this, nonblack plumes could be evaluated differently when viewed
on different days or viewed from different directions, though their aerosol
content has not changed.
At least two real difficulties exist in making any generalizations
about visual aspects of smoke plumes. First, it is not possible to deter-
mine the mas? emitted per unit time from a smokestack solely on the basis
of visually perceived light scatter or absorption. The size and mass per
unit time emitted from the stack, and not the appearance or optical proper-
ties of the plume, are pertinent to the eventual air composition, even though
appearance may be aesthetically objectionable.
Second, although many meteorological mixing equations have been
proposed, they cannot describe individual eddies of smoke as the plume dis-
integrates. The equations were meant for describing averages and not an
instantaneous property such as the extinction of light on some particular
eddy cf smoke as determined by eye.
The problem of measuring the contribution of individual plumes
to overall visibility reduction in a specific locality is extremely complex
and more detailed study is necessary to develop improved techiques. Ref-
erence 1 presents a detailed study of plume optics, and the reader is re-
ferred to it for further information.
Recent advances in our knowledge of the size distributions and
optical properties of well-aged atmospheric aerosols have resulted in a
clearer description of visibility reduction by such aerosols. Theoretical
and experimental studies of well-aged aerosols have shown that:
1. Aerosols in the lowest region of the atmosphere (troposphere),
whether over urban areas or not, tend to have similar size distributions.2"5/
2. A narrow range of particle sizes, usually from 0.1 to 1.0 p.
radius, controls the extinction coefficient and thereby visibility.6"8/
209
-------
3. The mass concentration of well-aged aerosols is approximately
proportional to the light scattering coefficient for atmospheric aerosols
originating naturally or as the result of man's activity.—/
Studies by Charlson, et al. ,—' and Noll, _et al_.,—-' suggest that
a useful relationship between visual range and mass concentration of atmo-
spheric part iculate matter can be obtained from the observation that mass
concentration is approximately proportional to the scattering coefficient.
The visual range is defined as the distance, under daylight conditions, at
which the apparent contrast between object and background is just equal to
the threshold contract of 1,b
-------
from sources to allow aerosol aging) suggests that these results will be
useful in the estimation of the effects of control of emissions of partic-
ulatc matter on visibility, provided the control techniques applied do not
ultfjr 1,ho tii'/.i: di:ilribut.i
-------
termed freezing nuclei. Without these, the water droplets would not freeze
except at temperatures below -40°C. There is evidence that some of the
particles introduced into the atmosphere by man's activities can act as
nuclei in processes which affect the formation of clouds and precipitation.
The potential influence of fine particles on solar radiation and
weather patterns is discussed separately in the next two sections.
3.2 Solar Radiation
The int"unity -md cpnobral distribution of direct sunlight and
scattered daylight, and the variation of intensity with time of day, season,
latitude, altitude, and atmospheric conditions are important because they
affect photosynthesis in plants and the distribution of plants and animals
on earth, the weathering of natural and man-made materials, climate, and
illumination for human activity.—/
The attenuation of solar radiation through the atmosphere is
caused by a number of physical factors ;-""-*-°/
1. Rayleigh scattering by air molecules such as ^ and Og, and
particles in size ranges less than the wavelength of solar radiation;
2. Selective absorption by gaseous constituents of the atmosphere;
and
3. Scattering and absorption by atmospheric dusts and particulate
matter of a size greater than the wave Length of solfir radiation.
The scattering of light by aerosol particles in ambient air is a
complicated process. Part of the light is transmitted, part is reflected
in all directions either at the front surface of the particle or at an in-
ternal discontinuity and part is absorbed. The transmission factor for
scattering is a function of the wavelength of the incident light and the
physical qualities of the scattering medium. In simple cases where the
form, size, and composition of scattering particles are known, the factor
can-be derived on a theoretical basis and is known as "Mie" scattering.
Except in cases of heavy particulate pollution of the atmosphere,
such as may occur in large urban centers or heavy industrial areas, it ap-
pears that the effect of turbidity is to scatter radiation out of the direct
solar beam and add an almost equal amount to the diffuse beam arriving from
the rest of the sky by forward-scattering. In cases of heavy particle con-
centrations, however, the loss from the direct solar beam greatly exceeds
the gain in the downward scattered beam, the difference being lost to
212
-------
backscattering off the top of the pollution layer, and to absorption within
the polluted layer or column.
Landsberg . / and SteinhauserM/ report that cities in general re-
ceive less solar radiation than do their rural environments. Seasonal,
weekly, and dnily variations in total solar radintjon in urban comunities
have also been noted. ..°/ Those variations appear to be related, in part,
to cycles of industrial and commercial activity.
Comparisons at different sites over the world covering periods
of up to 50 years suggest that a general worldwide rise in turbidity may
be taking place. This may well be indicative of a gradual buildup of world-
wide background levels of suspended particulates.SZ/ The net influence of
atmospheric turbidity on surface temperature is uncertain, but the emission
of long-lived particles may well be leading to a decrease in world air tem-
perature .^=/ As more is learned about the general circulation of the atmo-
sphere and the delicate balance between incoming and outgoing radiation, it
seems increasingly probable that small changes such as those occasioned by
increasing particle loads in the atmosphere may produce very long-term
meteorological effects.
3.3 Weather Modification
As noted previously, there is evidence that some of the particles
introduced into the atmosphere by man's activity can act as nuclei in pro-
cesses which affect the formation of clouds and precipitations. An example
of increased precipitation from air pollution appears to exist at La Porte,
Indiana, some 30 miles downwind from the heavy industrial complex in Chicago.
Precipitation and thunderstorm activity have increased significantly since
1925, and precipitation peaks have coincided with peaks in steel production
in the Chicago area.£=/ Hobbs, et al.=£/ have reported measurements of the
concentrations of cloud condensation nuclei in Washington State resulting
from pulp and paper mills and other industrial sources. Their study of the
precipitation and stream flow records in Washington State for the past 40
years revealed that in recent years there have been significant increases
in precipitation in several areas in the vicinity of large industrial sources
of cloud-condensation nuclei.
Excessive dustiness in the atmosphere can also reduce rainfall
under certain conditions when overseeding occurs. This happens when many
small droplets, formed by condensation, do not fall to earth if there is
insufficient moisture available to continue the droplet growth by condensa-
tion. Consequently, what would have fallen as rainfall stays in the form
of clouds. A case in point of this reduction in rainfall has occurred in
the sugar producing area in Queensland, Australia. During the cane harvest-
ing season, the common practice is to burn off the cane leaf before cutting
213 ~
-------
and harvesting. This results in fires over extensive areas and large palls
of smoke. The fine smoke particles have modified the cloud formation and
hindered the rainfall process. A reduction of up to 25$ in the rainfall
has occurred downwind of these areas, but there is no such effect in neigh-
boring areas unaffected by the smoke plume.^i/ Similar effects have been
reported in Puerto Rico, Africa, and yfowaii.25,26/ Schaefer has also re-
ported on observations of changes in micro-physics of clouds in the vicin-
ity of large cities during airplane flights through convective clouds.—/
His observations suggest that such clouds contain an increasing number of
cloud droplets. Schaefer's investigations of snow and rainstorm patterns
in New York State indicate that submicroscopic particulates from man-made
pollution may be initiating and controlling precipitation in a primary man-
ner, rather than bcJng involved in tho nr.-condnry proccsr, whoroln precipib.'i-
bion elements coming from natural mechanism:; uorvo to remov: thr; particloc
by diffusion, collision, and similar scavenging processes.
214
-------
REFERENCES
1. Connor, W. D., and J. R. Hodkinson, Optical Properties and Visual
Effects of Smoke-Stack Plumes, PHS Publ. No. 999-AP-30, Cincinnati,
Ohio (1967).
2. Junge, C. E., Air Chemistry and Radioactivity, Academic Press, New York
(1963).
3. Friedlander, S. K., and C. S. Wang, "The Self-Preserving Particle Size
Distribution for Coagulation by Brownian Motion," J. Colloid Inter-
face Sci., 2£, 126-132 (1966).
4. Whitby, K. T., and W. E. Clark, "Electric Aerosol Particle Counting and
Size Distribution Measuring System for the 0.15 p, to 1 p, Size Range,"
Tellus, IB, 573-586 (1966).
5. Peterson, C. M., and H. J. Paulus, "Micrometeorological Variables Ap-
plied to the Analysis of Variation in Aerosol Concentration and
Size," Preprint. (Presented at the 60th Annual Meeting, Air Pollu-
tion Control Association, Cleveland, Ohio, June 11-16, 1967).
6. Mie, G., "Beitrage zur Optik truber Medien, Speziell Kblloidaler Metallo-
sungen," Ann. Physik, 2£, 377-455 (1968).
7. Pueschel, R. F., and K. E. Noll, "Visibility and Aerosol Size Frequency
Distribution," J. Appl. Meteorol., (5, 1045-1052 (1967).
8. Air Quality Criteria for Parbiculate Matter, NAPCA Publ. AP-49,
Washington, D. C. (1969).
9. Charlson, R. J., H. Horvath, and R. F. Pueschel, "The Direct Measure-
ment of Atmospheric Light Scattering Coefficient for Studies of
Visibility and Air Pollution," Atmos. Environ., !L, 469-478 (1967).
10. Noll, K. E., P. K. Mueller, and M. Unada, Atmos. Environ., 1, 501 (1967).
11. Charlson, R. J., N. Ahlquist, and H. Horvath, Atmos. Environ., 2, 300
(1968). ~
12. Charlson, R. J., N. Ahlquist, and H. Selvidge, "The Use of the Inte-
grating Nephelometer for Monitoring Parbiculate Pollution," Pre-
sented at 10th Conference on Methods, San Francisco (1969).
13. Fett, W., Beitr. Phys. Atmos., 40, 262 (1967).
215
-------
14. McCormick, R. A., and D. M. Baulch, "The Variation with Height of tho
Dust Loading Over a City as Determined from the Atmospheric Tur-
bidity," JAPCA, 12, 492-496 (1962).
15. Gates, D. M., "Spectral Distribution of Solar Radiation at the Earth'3
Surface," Science, 151, 523-529 (1966).
16. Robinson, N., Solar Radiation, Elsevier, Amsterdam, London, ani
New York (1966).
17. Landsberg, H., Physical Climatology, 2nd Edition, Gray, Dubois,
Pennsylvania, 317-326 (1958).
IB. Steinhauser, F., 0. Eckel, and F. Sauberer, "Klima und Bioklima von Wien,"
Wetter und Leben, 7 (1955).
19. Meetham, A. R., Atmospheric Pollution; Its Origins and Prevention,
Pergamon Press, New York (1961).
20. Mateer, C. L., "Note on the Effect of the Weekly Cycle of Air Pollution
on Solar Radiation at Toronto," Intern. J. Air Water Pollution, _4,
52-54 (1961).
21. "Restoring the Quality of Our Environment," Report of the Environrner.tal
Pollution Panel, President's Science Advisory Committee. The White
House, Washington, D. C., 111-151, November 1965.
22. Changnon, S. A., "The LaPorte Weather Anomaly—Fact or Fiction,"
Bulletin of American Meteorological Society, 49 (l), 4-11 (1968).
23. Hobbs, P. V., et al., "Cloud Condensation Nuclei from Industrial Sources
and Their Apparent Influence on Precipitation in Washington State,"
Journal of Atmospheric Sciences, 27, 81-89 (1970).
24. Aynsley, E., "How Air Pollution Alters Weather," New Scientist, 66-67,
October 9, 1969.
25. Schaefer, V. J., "The Inadvertent Modification of the Atmosphere by
Air Pollution," Bulletin of American Meteorological Society, 50 (4),
199-206 (1969).
26. Warner, J., "A Reduction in Rainfall Associated with Smoke from Sugar
Cane Fires - An Inadvertent Weather Modification," J. Applied
Meteorology, 7, 247-251 (1968).
27. Gunn, R., "The Secular Increase of the World-Wide Fine Particle Pollu-
tion," J. Atmos. Sci., 21, 168-181 (1964).
216
-------
APPENDIX D
DATA SOURCES
217
-------
I. Companies that provided data
Organization
Courcoc
1. TVA
2. Coulter Electronics
3. Koppers Company
4. H. W. Dieteret Company
(Banco sales representative)
5. PEDCo - Environment.-i,l
6. Resources Research
10 distributions - power plants
(before and after control devices)
4 distributions - power plants and
cement plants (before control)
6 distributions - power plants
(before control)
6 miscellaneous distributions by
Banco methods
P dlr:tributionr; - power plant"
(bc:f.'ore control)
Compilation of 25-30 particle size
distributions for several sources—
power plants, kilns, dryers, electric
furnaces
7. Roy F. Weston Company
8. Abe Matthews Engineering
Company
9. George Clayton Associates
10. Universal Oil Products
(Air Correction Division)
11. Western Precipitator
12. National Dust Collector
6 distributions - power plants
(before control)
15 distributions - cupolas, power
plant, lime kiln, cement kiln, mineral
processing (before control)
10 distributions - power plant, cupolas,
lime kiln, cement kiln, electric
furnace (before control)
25 distributions - power plant (before
and after control)
Compilation of 250-300 particle size
distributions—12-15 different sources
(before control)
9 distributions - cupola, coal cleaning,
asphalt dryers, and mineral processing
(electron microscope data, before and
after control)
218
-------
Organization
13. Environmental Research
Corporation
14. Meteorology Research, Inc.
Sources
1 distribution - secondary aluminum
Power plant plume data
II. Other companies contacted that have data which were not acquired
1. Cottrell Environmental Data available, cost prohibitive
2. American Air Kilter
3. American Standard
4. Wheelabrator
5. Pulverizing Machinery
6. Buffalo Forge
Data available, will work only through
IGCI
Data not available for public disclosure
Data not available for public disclosure
Data not available for public disclosure
Data not available for public disclosure
III. Research groups
1. Dr. M. Pilat
University of Washington
£. Prof. A. F. ituch
UCLA
3. Dr. S. K. Fried-lander
Cal Tech
4. Dr. P. K. Mueller
California Department of
Public Health
5. Dr. A. Cohen
Ecological Research Branch
APCO, Durham
Power plant, recovery furnace (pulp
mill), plywood veneer dryer (cascade
impactor)
Power plant (thermal precipitator,
electron microscope data)
No source data
No source data
No source data
213
-------
6. Dr. Jack Wagman No source data
Division of Chemical and
Physical Research and
Development
APCO, Durham
7. Dr. Myron Robinson No source data
Atomic Energy Commission
8. Prof. M. Kerker No source data
Clarkson College
9. Dr. Mary Amdur No source data
Harvard School 'of Public
Health
IV. Companies contacted that did not have data
1. Mr. J. Katz 10. Mr. J. Pizzo
Jacob Katz Associates U. S. Testing Company, Inc.
2. Mr. Jorgen Hedenhag 11. Mr. R. E. Sommerclad
Polycom Corporation Foster Wheeler Corporation
3. Mr. Charles Billings 12. Mr. A. Licberman
GCA Royco Instruments
4. Mr. Ray Droger 13. Dr. William A. Perkins
Seversky Electronatom Metronics Associates
5. Mr. Sid Orem 14. Mr. H. D. Wheeler
Flyash Arrester Kaiser Engineers
6. Mr. I. Shah 15. Dr. M. Feldstein
Chemico Bay Area Air Pollution Control
District
7. Mr. Ballard
Menardi and Company 16. Mr. Walter Hamming
Los Angeles APCD
8. Mr. Charles Cook
Mine Safety Appliances Company 17. Dr. E. R. Hendrickson
Environmental Engineering, Inc.
9. Mr. Dick Glover
Monsanto Environmental Control
System
220
-------
APPENDIX E
CALCULATIONS OF FINE-PARTICLE EMISSIONS
-------
APPENDIX E
TABLE OF CONTENTS
List of Tables
Table Title
1. Asphalt, Hot Mix Batch Plant
E-l Summary of Fino-Par tide Emission::; From Asphalt Dryers . . 230
E-2 Distribution of Process Emissions From Asphalt Dryers . . 231
E-3 Fine-Particle Emissions From Uncontrolled Asphalt Dryers . 252
E-4 Fine-Particle Emissions From Asphalt Dryers Controlled
by Cyclones 233
E-5 Fine-Particle Emissions From Asphalt Dryers Controlled
by Cyclones Plus Scrubber . 234
E-6 Summary of Fine-Particle Emissions From Vent Lines .... 235
E-7 Distribution of Process Emissions From Vent Lines .... 236
E-8 Fine-Particle Emissions From Uncontrolled Vent Lines . . . 237
E-9 Fine-Particle Emissions From Vent Lines Controlled by
Cyclones 238
E-10 Fine-Particle Emissions From Vent Lines Controlled by
Cyclones Plus Scrubber 239
2. Cement Plants, Kilns
*
E-ll Summary of Fine-Particle Emissions From Cement Kilns . . . 240
E-12 Distribution of Process Emissions From Cement Kilns . . . 241
E-13 Fine-Particle Emissions From Uncontrolled Cement Kilns . . 242
E-14 Fine-Particle Emissions From Cement Kilns Controlled by
Electrostatic Precipitators ... 243
*v
E-15 Fine-Particle Emissions From Cement Kilns Controlled
by Cyclones 244
221
-------
List of Tables (Continued)
Table Title Page
E-16 Fine-Particle Emissions From Cement Kilns Controlled
"by Cyclones Plus Electrostatic Precipitators 245
E-17 Fine-Particle Emissions From Cement Kilns Controlled by
Fabric Filters 246
3. Ferroalloy Plants, Electric Furnaces .'
(
E-18 Summary of Fine-Particle Emissions for Ferroalloy
Electric Furnaces , '247 •
E-19 Distribution of Process Emissions From Ferroalloy
Electric Furnaces 248
E-20 Fine-Particle Emissions From Uncontrolled Ferroalloy ;'
Electric Furnaces 249
E-21 Fine-Particle Emissions From Ferroalloy Electric Furnaces
Controlled by Fabric Filters and Disintegrators .... 250
4. Fertilizer Plants, Granulators and Dryers
E-22 Summary of Fine-Particle Emissions From Fertilizer
Granulators and Dryers 251
E-23 Distribution of Process Emissions From Granulators and
Dryers 252
E-24 Fine-Particle Emissions From Uncontrolled Granulators
and Dryers 253
E-25 Fine-Particle Emissions From Granulators and Dryers
Controlled by Wet Scrubbers 254
5. Iron and Steel Plants •
a. Basic Oxygen Furnace
E-26 Summary of Fine-Particle Emissions From Basic Oxygen
Furnaces^ Iron and Steel 255
E-27 Distribution of Process Emissions From Basic Oxygen
Furnaces 256
222
-------
List of Tables (Continued)
Table Title Page
E-28 Fine-Particle Emissions From Basic Oxygen Furnaces
Controlled by Electrostatic Precipitator 257
E-29 Fine-Particle Emissions From Basic Oxygen Furnaces
Controlled by Venturi Scrubber 258
b. Electric Arc Furnace
E-30 Summary of Fine-Particle Emissions From Electric Arc
Furnaces, Iron and Steel 259
E-31 Distribution of Process Emissions From Electric Arc
Furnaces 260
E-32 Fine-Particle Emissions From Uncontrolled Electric Arc
Furnaces 261
E-33 Fine-Particle Emissions From Electric Arc Furnaces
Controlled by Wet Scrubber 262
£-34 Fine-Particle Emissions From Electric Arc Furnaces
Controlled by Electrostatic Precipitator 263
E-35 Fine-Particle Emissions From Electric Arc Furnaces
Controlled by Fabric Filter 264
c. Open Hearth Furnace
E-36 Summary of Fine-Particle Emissions From Open Hearth
Furnaces 265
E-37 Distribution of Process Emissions From Open Hearth
Furnaces 266
E-38 Fine-Particle Emissions From Uncontrolled Open Hearth
Furnaces 267
E-39 Fine-Particle Emissions From Open Hearth Furnaces
Controlled by Electrostatic Precipitator 268
223
-------
List of Tables (Continued.)
d. Sinter M;J
E-40 Summary of Fine-Particle Emissions From Sinter Machines,
Iron and Steel Plants
E-41 Distribution of Process Emissions From Sinter Machine . . 270
E-42 Fine-Particle Emissions From Sinter Machines Controlled
by Cyclones ...................... 271
E-43 Fine-Particle Emissions From Sinter Machines Controlled
by Cyclone Plus Electrostatic Precipitator ....... 272
6. Iron. Foundries, Cupola
E-44 Summary of F:ino-Partic:lo Kmi;;.';ion;; Kroiri J ron Foundry
Cupolas ........................ 275
E-45 Distribution of Process Emissions From Iron Foundry
Cupolas ........................ 274
E-46 Fine-Particle Emissions From Uncontrolled Iron Foundry
Cupolas ........................ 275
E-47 Fine-Particle Emissions From Iron Foundry Cupolas
Controlled by Cyclones ................. 276
E-48 Fine-Particle Emissions From Iron Foundry Cupolas
Controlled by Wet Scrubbers and Wet Caps ........ 277
E-49 Fine-Particle Emissions From Iron Foundry Cupolas
Controlled "by Fabric Filters . . . . .......... 278
7. Kraft Pulp Mills
a. Bark Boilers
E-50 Summary of Fine-Particle Emissions From Bark Boilers . . . 279
E-51 Distribution of Process Emissions From Bark Boiler .... 280
E-52 Fine-Particle Emissions From Uncontrolled Bark Boilers . . 281
224
-------
List of Tables (Continued)
Table Title Page
E-53 Fine-Particle Emissions From Bark Boilers Controlled
by Cyclones 282
d. Re c overy Furnac e
E-54 Summary of Fine-Particle Emissions From Recovery
Furnaces 283
E-55 Distribution of Process Emissions From Recovery Furnace . 284
b'-fjG Fine-Particle Krni.'jcjons I'Yorn Uncontrolled Rf:r:
-------
List of Tables (Continued)
Table TJtle T'n ge
E-66 F.ine -Particle- Emissions From Hol.Mry Liin<: Kilns Controller!
by Wet Scrubbers .................... 291;
E-67 Fine-Particle Emissions From Rotary Lime Kilns Controlled
by Fabric Filter .................... 296
9. Municipal Incinerators
E-68 Summary of Fine -Particle Emissions From Municipal
Incinerators ...................... 297
E-69 Distribution of Process Emissions From Municipal
Incinerator .................. . . . . . 298
E-70 Fine-Particle Emissions From Uncontrolled Municipal
Incinerators ...................... P99
E-71 Fine -Particle ISmisaiony From Municipal Incinerators
Contolled by Low Efficiency Scrubber .......... 300
E-72 Fine-Particle Emissions From Municipal Incinerator
Controlled by Medium Efficiency Scrubber ........ 301
E-73 Fine-Particle Emissions From Municipal Incinerators
Controlled by Cyclones . . ............... 302
10. Stationary Combustion
a. Electric Utility 3 Pulverized Coal-Fired Boiler
E-74 Summary of Fine-Particle Emissions From Electric Utility
Pulverized Coal-Fired Boilers ............. 303
E-75 Distribution of Process Emissions From Electric Utility
Pulverized Ccal-Fired Boiler .............. 304
E-76 Fine-Particle Emissions From Uncontrolled Electric Utility
Pulverized Coal-Fired Boilers ............. 305
E-77 Fine-Particle Emissions From Electric Utility Pulverized
Coal-Fired Boilers Controlled by Electrostatic
Precipitator ...................... 306
226
-------
List of Tables (Continued)
TJflQ
E-78 Fine-Particle Emiufiionr; From Electric Utility Pulverized
Coal-Fired Boilers Controlled by Cyclones SO/
E-79 Fine-Particle Emissions From Electric Utility Pulverized
Coal-Fired Boilers Controlled by Cyclone Plus
Electrostatic Precipitator 308
b. Electric Utility, Stoker Coal-Fired Boiler
E-80 Summary of Fine-Particle Emissions From Electric Utility
Stoker Coal-Fired Boilers 309
E-81 Distribution of Process Emissions From Electric Utility
Stoker Coal-Fired Boiler 310
E-82 Fine-Particle Emi:;nions From Uncontrolled EJeotric Utility
Stoker Coal-Fired Boilers . . . 3j 1
E-83 Fine-Particle Emissions From Electric Utility Stoker
Coal-Fired Boilers Controlled by Electrostatic
Precipitator 312
E-84 Fine-Particle Emissions From Electric Utility Stoker
Coal-Fired Boilers Controlled by Cyclones 313
c. Electric Utility, Cyclone Coal-Fired Boiler
E-85 Summary of Fine-Particle Emissions From Electric Utility
Cyclone Coal-Fired Boilers 314
E-86 Distribution of Process Emissions From Electric Utility
Cyclone Coal-Fired Boiler 315
E-87 Fine-Particle Emissions From Uncontrolled Electric
Utility Cyclone Coal-Fired Boilers 316
E-88 Fine-Particle Emissions From Electric Utility Cyclone
Coal-Fired Boilers Controlled by Electrostatic
Precipitator '" 3j_y
E-89 Fine-Particle Emissions From Electric Utility Cyclone
Coal-Fired Boilers Controlled by Cyclone 318
227
-------
List of Tables (Continued)
Table Title
d. Industrial Boilers, Pulverized Coal-fired
E-90 Summary of Fine-Particle Emissions From Industrial
Pulverized Coal-Fired Boilers ............. 319
E-91 Distribution of Process Emissions From Industrial
Pulverized Coal-Fired Boiler .............. 320
E-92 Fine -Particle Emissions From Uncontrolled Industrial
Pulverized Coal-Fired Boilers ............. 321
E-93 Fine-Particle Emissions From Industrial Pulverized Coal-
Fired Boilers Controlled by Electrostatic Precipitator . 322
E-94 Fine-Particle Emissions From Industrial Pulverized Coal-
Fired Boilers Controlled by Cyclones .......... 323
e. Industrial Boilers, Stoker Coal -Fired
E-95 Summary of Fine -Particle Emissions From Industrial Stoker
Coal-Fired Boilers ................... 324
E-96 Distribution of Process Emissions From Industrial Stoker
Coal-Fired Boilers ................... 32C
E-97 Fine-Particle Emissions From Uncontrolled Industrial
Stoker Coal-Fired Boilers ............... 326
E-98 Fine -Particle Emissions From Industrial Stoker Coal-Fired
Boilers Controlled by Electrostatic Precipitator .... 327
E-99 Fine-Particle Emissions From Industrial Stoker Coal-Fired
Boilers Controlled by Cyclones ............. 328
f . Industrial Boilers, Cyclone Coal-Fired
E-100 Summary of Fine-Particle Emissions From Industrial
Cyclone Coal-Fired Boilers ............... 329
E-101 Distribution of Process Emissions From Industrial Cyclone
Coal-Fired Boiler ................... 330
228
-------
List of Tables (Concluded)
Table Title Page
E-102 Fine-Particle Emissions Fron Uncontrolled Industrial
Cyclone Coal-Fired Boilers 331
E-103 FJne-Partide Emissions Prom industrial Cyclone Coal-
Fired Boilers Controlled by Electrostatic Precipitator . 332
E-104 Fine-Particle Emissions From Industrial Cyclone Coal-
Fired Boilers Controlled by Cyclones 333
g. Electric Utility and Industrial Boiler, Qil-Fired
E-105 Summary of Fine-Particle Emissions From Electric Utility
and Industrial Oil-Fired Boilers 334
h. Electric Utility and Industrial Boiler, Gas-Fired
E-106 Summary of Fine-Particle Emissions From Electric Utility
and Industrial Gas-Fired Boilers . 335
229
-------
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TABLE E-2
DISTRIBUTION OF PROCESS EMISSIONS FROM ASPHALT DRYERS
Source - Asphalt
Process - Dryers
Production Emission Factor
(tons/year) (ib/ton)
Process Emissions = ( 251 x 1Q6 ) ( 52 )
Application of Control = 99 ^
Process Emissions into Uncontrolled Plants =
. -v
f j\ = 4
40,200
Process Emissions into Controlled Plants = 3,975,800
= 4,016,000 tons/year
tons/year
tons/year
Type of
Control Device
Cyclone
% Application on
Controlled Plants
Process Emissions into
Control Device (tons/year)
198,600
Cyclone + Scrubber
FF
95
3,777,000
231
-------
TABLE ]-;-3
FINE-PARTICLE EMEIioIONo FROM IJNCONTHOLLM) ASPHALT
Process - Asphalt Dryers
Control Device - Uncontrolled
Process Bnissions into Control Device 40,200 tons/year
Control Device Control Device
[Uncontrolled | | |
Process Snissions Penetration (%) Penetration (%) fiaissions
Size (n) Percent (l - efficiency) (l - efficiency) (tons/year)
1-3 12.6 100 5,100
0.5-1.0 2.18 100 300
0.1-0.5 0.71 100 300
0.05-0.1
0.01-0.05
6,300
232
-------
TABLE E-4
FINE-PARTICLE EMISSIONS FROM ASPHALT DRYERS CONTROLLED BY CYCLONEC
Process - AsPhalt
Control Device - Cyclones
Process Emissions into Control Device 198,800
tons/year
Process Emissions
Size (jj.) Percent
1-3
0.5-1.0
12.6
2.18
Control Device
Control Device
Cyclones
Penetration (#) Penetration (#) . Emissions
(l - efficiency)^/ (l - efficiency) (tons/year)
73 ; 16.300
89
5.900
0.1-0.5
0.71
100
1.400
0.05-0.1
0.01-0.05
23,600
a/ Efficiency values were taken from medium fractional efficiency curve,
Figure 17.
233
-------
TABLE E-5
FINE-PARTICLE EMISSIONS FROM ASPHALT DRYERS CONTROLLED
BY CYCLONES PLUS SCRUBBER
Process - Asphalt Dryers
Control Device - Cyclones plus Scrubber
Process Bnissions into Control Device 3,777,000 tons/year
Control Device Control Device
I Cyclone I [ Scrubber ]
Process Bnissions Penetration ($) Penetration ($) Emissions
Size (u) Percent (l - efficiency)^/ (l - efficiency)^/ (tons/year)
1-3 12.6 73 21 75,000
0,5-1.0 2.18 89 45 51,500
Q.l-0.5 0.71 100 • 74 19,800
0.05-0.1 95
0.01-0.05 100
124,300
a/ Efficiency values were taken from medium fractional efficiency curve,
Figure 17.
234
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TABLE E-7
DISTRIBUTION OF PROCESS EMISSIONS FROM VENT IJNE.r;
Source - Asphalt
Process - Vent Line
Production Emission Factor
(tons/year) (ib/ton) /
Process Emissions = ( 251 x 10° ) ( 8 )
Application of Control = 99
Process Emissions into Uncontrolled Plants
10,000
Process Emissions into Controlled Plants = 994,000
= 1,004,000 tons/year
tons/yeai
tons/y
•ear
Type of
Control Device
Cyclone
$ Application on
Controlled Plants
Process Emissions into
Control Device (tons/year)
49.700
Cyclone plus Scrubber
95
944.300
236
-------
TABLE E-8
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED VENT LINES
Process - Asphalt - Vent Lines
Control Device - Uncontrolled
Process Bnissions into Control Device 10,000 tons/year
Control Device Control Device
[Uncontrolled |
Process Bnissions Penetration (%) Penetration (%) Emissions
Size (p.) Percent (l - efficiency) (l - efficiency) (tons/year)
1_3 7.55 100 800
0.5-1.0 0.41 100
0.1-0.5 0.05 100
0.05-0.1
0.01-0.05
800
237
-------
TABLE E-9
FINK-PARTICLE EMIJJUIOIW FKOM VKNT LBJKii CON'i'hOLLI'IL) Iff CYCLONIC
Process - Asphalt - Vont Lino3
Control Device - Cyclone
Process Emissions into Control Device 49,700
tons/year
Control Device
Control Device
Process
Size (n)
1-3
Emissions
Percent
7.55
1
Cyclone
1
Penetration ($)
(l - efficiency)^/
73
1 _.
1
Penetration ($)
(l - efficiency)
Emissions
(tons /year)
2,700
0.5-1.0
0.41
•89
200
0.1-0.5
0.03
100
0.05-0.1
0.01-0.05
2,900
a/ Efficiency values were taken from inedium fractional efficiency curve,
Figure 17. '.
238
-------
TABLE E-10
FINE-PARTICLE EMISSIONS FROM VENT LIMES CONTROLLED
BY CYCLONES PLUS SCRUBBER
Process - AsPhal"t - Vent Lines
Control Device - Cyclone plus Scrubber
Process Emissions into Control Device 944,500 _ tons/year
Control Device Control Device
I Cyclone | ( Scrubber ]
Process Emissions Penetration {%) Penetration ($) Emissions
Size (tx) Percent (l - efficiency )£/ (l - efficiency)^/ (tons /year)
1_3 _ 7.55 _ 73 _ 21 _ 10,900
0.5-l.Q _ 0.41 _ 89 _ 43 _ 1,500
Q.l-0.5 _ 0.05 _ 100 _ 74 _ 200
0.05-0.1 _ _ 95
0.01-0.05 _ 100
12,600
a/ Efficiency values were taken from medium fractional efficiency curve,
Figure 17.
239
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TABLE E-12
DISTRIBUTION OF PROCESS EMISSIONS FROM CEMENT KILNS
Cement Pl£mts
Process - Kilns
Production Emission Factor
(tons/year) (ib/ton)
Process Emissions = (74.6 x 106 ) ( 167 )
6.299
= x 106 tons/year
Application of Control = 94 ^
Process Emissions into Uncontrolled Plants = 0.574 x 10° tons /year
Process Emissions into Controlled Plants = 5.855 x 106 tons /year
Type of
Control Device
ESP
Cyclones
Cy + ESP
FF
% Application on
Controlled Plants
47
16
18
17
Process Emissions into
Control Device ( tons/year)
2.752 x 106 _
1.054 x 106 _
1.0J54 x 106 _ :
0.995 x 106
241
-------
TABLE E-13
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED CEMENT KILNS
Process - Cement Kilns
Control Device - Uncontrolled
Process Emissions into Control Device 0.374 x
tons/year
Control Device
Control Device
Process Emissions
Size (u) Percent
1-3
9.7
Uncontrolled!
Penetration ($)
(l - efficiency)
100
Penetration (^b) Emissions
{l - efficiency) (tons/year)
36,500
0.5-1.0
1.75
100
6,500
0.1-0.5
0.54
100
2.000
0.05-0.1
0.01-0.05
44,800
242
-------
TABLE E-14
FINE-PARTICLE EMISSIONS FROM CEMENT KILNS CONTROLLED
BY ELECTROSTATIC PRECIPITATORS
Process - Cement Kiljis
Control Device - Electrostatic Precipitators
Process Emissions into Control Device 2.752 x 10
tons/year
Control Device
Control Device
Process
Size (n)
1-3
Emissions
Percent
9.
7
1
ESP 1
Penetration (%
(l - efficiency
11
}*/
X 1
Penetration ($)
£L - efficiency)
Emissions
(tons/year)
29,
400
0.5-1.0
0.1-0.5
0.05-0.1
0.01-0.05
•1.75
0.54
17
29
8,200
4,300
41,900
a/ Efficiency values used were uaken from average fractional efficiency curve,
Figure 17.
Note: Outlet particle size distribution for cement kiln controlled by ESP
showed 43$ < 3 p,. (Figure 34).
If the overall efficiency of ESP's is assumed to average about 95%,
then the quantity emitted by ESP controlled plants is as follows:
(2.752 x 106 tons/year)(1-0.95)(43$) = 59,200 tons/year < 3 p,.
The 59,200 tons/year gives a cross-comparison with 41,900 tons/year.
243
-------
TA.BLE E-15
FINE-PARTICLE EMISSIONS FROM CEMENT KILNS CONTROLLED BY CYCLONES
Process - Cement Kilns
Control Device - Cyclones
Process Emissions into Control Device 1.054 x 106
tons/year
Control Device
Control Device
Process Emissions
Size (n) Percent
1-3 9-7
1 Cyclones 1
Penetration ($)
(l - efficiency)^/
57
1
X 1
Penetration ($)
(l - efficiency)
Emissions
(tons /year)
58,300
0.5-1.0
1.75
82
15.100
0.1-0.5
0.54
94
5.400
0.05-0.1
0.01-0.05
78,800
a/ Efficiency values used were taken from fractional efficiency curve for
high efficiency cyclones, Figure 17, because some plants use multi-
clones and since the dust is reusable to a certain extent, it is assumed
that higher efficiency devices would be used.
244
-------
TABLE E-16
FINE-PARTICLE EMISSIONS FROM CEMENT KILNS CONTROLLED BY CYCLONES
PLUS ELECTROSTATIC PRECIPITATOR
Process - Cement Kilns
Control Device - Cyclone + ESP
Process Emissions into Control Device 1.054 x 106
tons/year
Control Device
I CycloneI
Control Device
ESP
Process Emissions
Size (p.) Percent
1-3
9.7
Penetration
(l - efficiency)
57
Penetration
(l - efficiency)
11
Emissions
(tons/year)
6.400
0.5-1.0
1.75
82
17
2.600
0.1-0.5
0.54
94
29
1.600
0.05-0.1
0.01-0.05
10,600
245
-------
TABLE E-17
FINE-PARTICLE EMISSIONS FROM. CEMENT KILNS CONTROLLED
BY FABRIC FILTERS
Process - Cement Kilns
Control Device - Fabric Filters
Process Emissions into Control Device 0.995 x 10
tons/yi
•ear
Process Emissions
Size (n) Percent
1-3
9.7
Control Device
i' F£ —i
Penetration (%)
(l - efficiency)
0.5
Control Device
Penetration
(l - efficiency!)
Emisoionc
(tons/year)
400
0.5-1.0
1.75
1.8
300
0.1-0.5
0.54
3.3
200
0.05-0.1
0.01-0.05
900
246
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TA.BLE E-19
DISTRIBUTION OF PROCESS EMISSIONS FROM FERROALLOY ELECTRIC FURM.CES
(Tons/Year)
Source -
Ferroalloys
Process - Electric Furnaces
Production Emission Factor
(tons/year) (ib/ton)
Process Emissions = ( 2.119 x 10s ) ( 240 )
Application of Control = ^° jo ^
Process Emissions into Uncontrolled Plants = 152,600
Process Emissions into Controlled Plants = 101,700
= 254,300 tons/year
_tons/year
tons/year
of
Control Device
% Application on
Controlled Plants
Process Emissions into
Control Device (tons/year)
lbl.700
a/ Page 233, Reference 1, showed 50$ application of control. However,
the 80$ efficiency was mainly a result of capture efficiency. Control
devices are high efficiency type, such as baghouses, Venturi scrubbers
or disintegrators. Most are disintegrators and baghouses.
b/ Assume disintegrators are equivalent to fabric filters.
248
-------
TABLE E-20
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED FERROALLOY ELECTRIC FURNACES
Process - Ferroalloys - Electric Furnace
Control Device - Uncontrolled
Process Emissions into Control Device 152,600
tons /year
Process Emissions
Size (M-) Percent
1-3
12
Control Device
I Uncontrolled I
Penetration ($)
(l - efficiency)
100
Control Device
Penetration (%) Emissions
(l - efficiency) (tons/year)
18,300
0.5-1.0
18
100
27,500
0.1-0.5
52
100
79,400
0.05-0.1
11
100
16,800
0.01-0.05
4.9
100
7,500
149,500
249
-------
TABLE E-21
FINE-PARTICLE EMISSIONS FROM FERROALLOY ELECTRIC FURNACES CONTROLLED
BY FABRIC FILTERS AND DISINTEGRATORS
Process - Ferroalloys - Electric Furnace
Control Device - Fabric Filters and Disintegrators^8/
Process Emissions into Control Device 101,700 tons/year
Control Device Control Device
|FF + Disinteof | |
Process Emissions Penetration (%) , Penetration (%) Emissions
Size (n) Percent (l - efficiency)—' (l - efficiency) (tons/year)
1-5 12 0.5 100
0.5-1.0 18 1.8 500
0.1-0.5 52 5.5 1,700
0.05-0.1 11 4.2 .. 500
0.01-0.05 4.9 •- 4.5 200
2,800
a/ Assume disintegrators are equivalent to fabric filters.
250
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TABLE E-23
DISTRIBUTION OF PROCESS EMISSIONS FROM (XANUIATOR AND DRYER
Source -
Fertilizer
Process - Granulation and Drying
Production Emission Factor
(tons/year) (ib/ton)
Process Emissions = ( 18.1 x 106 ) ( 195 )
Application of Control = _95 $
Process Emissions into Uncontrolled Plants =
2,OUU) ~ •
^ /
=1,764,800 tonc/yoar-
88,200
Process Emissions into Controlled Plants = 1,676,600
_tons/year
tons/year
Type of
Control Device
Wet Scrubbers
% Application on
Controlled Plants
100
Process Emissions into
Control Device (tons/year)
1,676,600
252
-------
TABLE E-24
FES-PARTICLE SMISSI017S FROM UKCOMRQT.T.TTn GRAirUIATORS AMD DRYERS
Process - Fertilizer, Granulation and Drying, etc.
Control Device - Uncontrolled ;
Process Bnissions into Control Device 88,200 tons/year
Control Device Control Device
I Uncontrolled)
Process Bnissions Penetration ($) Penetration (%) Snissicr.s
Size (M,) Percent (l - efficiency) (l - efficiency) (tons/year)
1-3 1.62 100 1,400
0.5-1.0 0.45 100 400
C.l-0.5 0.25 100 | 200
0.05-0.1
C.01-0.05
2,000
255
-------
TABLE E-25
FIME-PARTICLE EMISSIONS FROM (SANUIATORS AND DRYERS
CONTROLLED BY WET SCRUBBERS
Process - Fertilizer> Granulation and Drying, etc.
Control Device - Wet Scrubbers
Process Emissions into Control Device 1,676,600
tons/year
Control Device
Control Device
Process Emissions
Size (y.) Percent
1-3 1-62
Scrubber |
Penetration ($)
(l - efficiency)^/
21
1
Penetration ($)
(l - efficiency)
Emissions
(tons/year)
5,700
0.5-1.0
0.43
3,100
0.1-0.5
0.23
74
2,900
0.05-0.1
95
0.01-0.05
100
11,700
a/ Efficiency values were taken from medium fractional efficiency curve,
Figure 17.
254
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TABLE E-27
DISTRIBUTION OF PROCESS EMISSIONS FROM BASIC OXYGEN FURNACE
Source - Iron ajlci Steel
Process - BOF
Production Emicsion Factor
(tons/year) (ib/ton)
Process Emissions = ( 45 x 106 ) ( 40 )
Application of Control = 100 %
Process Emissions into Uncontrolled Plants =
(y,oou)
= 960,000 tons/yeai
tons/year
Process Emissions into Controlled Plants = 960,000 tons/year
of
Control Device
ESP
% Application on
Controlled Plants
42
Process Emissions into
Control Device :(tons/year)
403,200 -
Venturi
58
556.600
256
-------
TABLE E-28
FINE-PAETICLE EMISSIONS FROM BASIC OXYGEN FURNACES CONTROLLED
'- BY ELECTROSTATIC PRECI1TCATOK
Process - Basic Oxygen Furnace
Control Device - Electrostatic Precipitator
Process Emissions into Control Device 405,200
tons/year
Control Device
Control Device
Process
Size (n/
1-3
Emissions
) Percent
6
. I ESP |
Penetration (#)
(l - efficiency)-^
1.6
L
1
Penetration ($)
(1 - efficiency)
••
Emissions
(tons /year)
400
0.5-1.0
36
2/6
3,300
0.1-0.5
57.8
3.8
8.900
0.05-0.1
0.2
5.5
0.01-0.05
8.2
12,600
a/ Efficiency values were taken from high fractional efficiency curve,
Figure 17.
257
-------
TABLE E-29
FINE-PARTICLE EMISSIONS FROM BASIC OXYGEN FURNACES
CONTROLLED BY VENTURI SCRUBBER
Process - Ba.sic Oxygen Furnace
Control Device - Venturi Scrubber
Process Emissions Into Control Device 556,800
tons/year
Process Emissions
Size (iQ Percent
1-3 6
Control Device
I Venturi I
Control Device
Penetration
(l - efficiency)
1.4
Penetration
(l - efficiency)
Emissions
(tons/year)
500
0.5-1.0
36
7.8
15,600
0.1-0.5
57.8
45
144,800
0.05-0.1
0.2
86
1,000
0.01-0.05
161,900
258
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TABLE E-31
DISTRIBUTION OF PROCESS EMISSIONS FROM ELECTRIC ARC FURNACE
Source - Iron and Steel
Process - Electric Arc Furnace
Production Emission Factor
(tons/year) (Ib/ton)
Process Emissions = ( 16.8 x 1Q6 ) ( 10 )
Application of Control
79
Process Emissions into Uncontrolled Plants =
Process Emissions into Controlled Plants =
(27000")
18,000
66,000
= 84'000 tons/year
_tons/year
tons/year
Type of
Control Device
Wet Scrubber
ESP
FF
% Application on
Controlled Plants
11
82
Process Emissions into
Control Device (tons/year)
7,300
. 4.600
54.100
260
-------
TABLE E-32
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED ELECTRIC AIR FURNACES
Process - Electric Arc Furnace
Control Device - Uncontrolled
Process Emissions into Control Device 16,000
tons/year
Process Emissions
Size (n) Percent
1-3
20
Control Device
[Uncontrolled |
Penetration (#)
(l - efficiency)
100
Control Device
I I
Penetration
(1 - efficiency)
Emissions
{•tons/year)
3,600
0.5-1.0
12
100
2,200
0.1-0.5
21
100
3,800
0.05-0.1
100
900
0.01-0.05
5.6
100
1,000
11,500
261
-------
TABLE E-33
FINE-PARTICLE EMISSIONS FROM ELECmiC ARC FURNACES
CONTROLLED BY WET SCRUBBER
Process - Electric Arc Furnace
Control Device - Wet Scrubber
Process Emissions into Control Device 7,300
tons/year
Control Device
Control Device
Process
Size (|i)
1-3
Emissions
Percent
20
| Wet Scrubber |
Penetration (#) ,
(l - efficiency)^
9
1
1
Penetration (#)
(l - efficiency)
Bid ss ions
^tons/year)
100
0.5-1.0
12
26
200
0.1-0.5
21
62
1,000
0.05-0.1
92
300
0.01-0.05
5.6
98
400
2,000
a/ Efficiency values were taken from high fractional efficiency curve,
Figure 17.
262
-------
TABLE E-34
FINE-PARTICLE EMISSIONS FROM ELECTRIC ARC FURNACES
CONTROLLED Hf ELECTROSTATIC PRECIPITATOR
Process - Electric Arc Furnace
Control Device - Electrostatic Precipitator
Process Bnissions into Control Device _ 4? 600
tons/y
ear
Control Device
Control Device
Process Emissions
Size (p.) Percent
1-3 20
1
ESP I
Penetration ($)
(1 - efficiency)2^
1.6
L
1
f Penetration (#)
(1 - efficiency)
Emissions
(tons /year)
0.5-1.0
12
0.1-0.5
0.05-0.1
0.01-0.05
5-6
8-2
100
a/ Efficiency values were taken from high fractional efficiency curve,
Figure 17.
263
-------
TABLE E-35
FINE-PARTICLE EMISSIONS FROM ELECTRIC ARC FURNACES
CONTROLLED BY FABRIC FILTER
Process - Electric Arc Furnace
Control Device - Fabric Filter
Process Emissions into Control Device
54,100
tons/year
Process Emissions
Size (p.) Percent
1-3
20
Control Device
Penetration
(l - efficiency)
0.5
Control Device
I I
Penetration (%)
(l - efficiency)
Emissions
(tons/year)
100
0.5-1.0
12
1.8
100
0.1-0.5
21
3.3
400
0.05-0.1
4.2
100
0.01-0.05
5.6
4.5
100
800
264
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TABLE E-37
DISTRIBUTION OF PROCESS EMISSIONS FROM OPEN HEARTH FURNACES
Source . Iron and Steel
Process - °Pen Heaxth
Production Emission Factor
(tons/year) (ib/ton)
Process Emissions = ( 65.8 x 106 ) ( 17 )
Application of Control = 41
-------
TABLE E-38
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED OPEN HEARTH FURNACES
Process - Open Hearth
Control Device - Uncontrolled
Process Hnissions into Control Device
1. Based on Particle
Process Emissions
Size (n) Percent
1-3 17
0.5-1.0 15
0.1-0.5 59
0.05-0.1 5-2
0.01-0.05 °-8
Size Distribution
Control Device
I Uncontrolled 1
Penetration (#)
(1 - efficiency)
100
100
100
100
100
2. Based on "Composite" Particle Size
Control Device
[Uncontrolled 1
Process Hnissions Penetration (#)
Size (M-) Percent (l - efficiency)
1-3 22.5
0.5-1.0 5.3
0.1-0.5 2.16
0.05-0.1 0.04
100
100
100
100
330,400 tons/year
in Lower Right of Figure 26.
Control Device
1 I
Penetration (#) Emissions
(l - efficiency) (tons/year)
56,200
49,600
194,900
17,200
2,600
320,500
Distribution in Figure 26.
Control Device
1 1
Penetration (%) Emissions
(l - efficiency) (tons /year)
74,300
17,500
7,100
100
0.01-0.05
99,000
267
-------
TABLE E-39
FINE-PARTICLE EMISSIONS FROM OPEN HEARTH FURNACES
CONTROLLED BY ELECTROSTATIC FRECIPITATOR
Process - Open Hearth
Control Device - Electrostatic Precipitator
Process Emissions into Control Device 229,600
tons/year
1. Based on Particle Size Distribution in Lower Right of Figure 26.
Control Device Control Device
ESP
Process Emissions Penetration (#) Penetration (#) Emissions
Size (n) Percent (l - efficiency)**/ (1 - efficiency) (tons/year)
1-3
17
11
4,300
0.5-1.0
15
17
5,900
0.1-0.5
59
29
39,500
0.05-0.1
5.2
41
4.900
0.01-0.05
0.8
55
1,000
55,400
2. Based on "Composite" Particle Size Distribution in Figure 26.
Control Device
Control Device
ESP
J
Process Emissions Penetration (%) . Penetration (#) Emissions
Size (ii) Percent (l - efficiency^ (l - efficiency) (tons/year)
1-3
22.5
11
5,700
0.5-1.0
5.3
17
2,100
0.1-0.5
2.16
29
1,400
0.05-0.1
0.04
41
0.01-0.05
55
9,200
a/ Efficiency values were taken from medium efficiency curve, Figure 17.
268
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269
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TABLE E-41
DISTRIBUTION OF PROCESS EMISSIONS FROM SINTER MACHINE
Source - Iron
Steel
Process - Sinter Machine—Windbox
Production Emission Factor
(tons/year) (ib/ton)
Process Emissions = ( 51.0 x 106 ) ( 20 )
Application of Control = 100
Process Emissions into Uncontrolled Plants
Process Emissions into Controlled Plants
(2,000)
= 510,000 tons/year
tons/year
510,000
tons/y i
ear
Type of
Control Device
Cyclone
% Application on
Controlled Plants
45
Process Emissions into
Control Device (tons/year)
229,500
Cyclone + ESP
FF
36
19
185,600
96,900
270
-------
TABLE E-42
FINE-PARTICLE EMISSIONS FROM SINTER MACHINES
CONTROLLED BY CYCLONES
Process - Sinter Machines—Windbox
Control Device - Cyclones
Process Emissions into Control Device 229,500
tons/year
Control Device
Control Device
Process Emissions
Size (n) Percent
1-3 2.7
[ Cyclones
Penetration (#)
(l - efficiency)^/
57
I
Penetration (#)
(1 - efficiency)
Emissions
(tons/year)
3,500
0.5-1.0
0.56
82
1,100
0.1-0.5
0.23
94
500
0.05-0.1
0.01-0.05
5,100
lyEfficiency values were taken from high fractional efficiency curve,
Figure 17.
Note: Outlet particle size distribution for sinter machines controlled by
cyclones showed 20 wt. #< 3 (j,. If overall efficiency of cyclones
is assumed to be 80$, then quantity emitted by sinter machines
controlled by cyclones is
(229,500 tons/year) (1-0.80)(0.20) = 9,200 tons/year .
271
-------
TABLE E-43
FINE-PARTICLE EMISSIONS FROM SINTER t&CHINES CONTROLLED BY CYCLONE
PLUS ELECTROSTATIC PRECIPITATOR
Process - Sinter Plant—Windbox
Control Device - Cyclone + Electrostatic Precipitator
Process Emissions into Control Device 163,600 tons/year
Control Device Control Device
I Cyclones I I ESP I
Process Emissions Penetration ($) Penetration (#) Emissions
Size (iQ Percent (l - efficiency )£/ (l - efficiency)**/ (tons/year)
1-3 _ 2/7 _ 57 _ 11 _ 300
0.5-1.0 _ 0.56 _ 82 _ 17 _ 100
0.1-Q.5 _ 0.25 _ 94 _ 29 _ 100
0.05-0.1
0.01-0.05
500
a/ Efficiency values were taken from high fractional efficiency curve,
Figure 17.
b/ Efficiency values were taken from medium fractional efficiency curve
Figure 17.
272
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273
-------
TABLE E-45
DISTRIBUTION OF PROCESS EMISSIONS FROM IRON FOUNDRY CUPOLAS
Source - Iron Foundries
Process - Cupolas
Production Emission Factor
(tons/year) (Ib/ton)
Process Emissions = ( 18.0 x 106 ) ( 16 )
Application of Control
53
Process Emissions into Uncontrolled Plants =
Process Emissions into Controlled Plants =
(2,oCo)
144,000 tons/year
96,000
tons/;
year
46,000 tons/year
of
Control Device
ESP
% Application on
Controlled Plants
Neglect < l
Process Bnissions into
Control Device (tons/year)
Cyclone
16
7,700
Wet Scrubber
FF
74
10
35.500
4.800
274
-------
TABLE E-46
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED IRON FOUNDRY CUPOIAS
Process - Cupolas
Control Device - Uncontrolled
Process Emissions into Control Device
96,000
tons/year
Process Emissions
Size (n>) Percent
1-3 6
Control Device
IUncontrolled1
Penetration (#)
(l - efficiency)
100
Control Device
Penetration
(l - efficiency)
Emissions
(tons/year)
5,800
0.5-1.0
100
1,900
0.1-0.5
2.3
100
2,200
0.05-0.1
0.34
100
300
0.01-0.05
0.31
100
300
10,500
275
-------
TABLE E-47
FINE-PARTICLE EMISSIONS FROM IRON FOUNDRY CUPOIAS
CONTROLLED BY CYCLONES
Process - Cupolas
Control Device - Cyclones
Process Emissions into Control Device 7,700
tons/year
Control Device
Control Device
Cyclones | | j
Process
Size (u)
1-3
Emissions
Percent
6
Penetration (#)
(l - efficiency)^/
73
Penetration (#)
(l - efficiency)
Emissions
(tons /year)
300
0.5-1.0
89
100
0.1-0.5
2.3
100
200
0.05-0.1
0.34
100
0.01-0.05
0.31
100
'600
a/ Efficiency values were taken from medium fractional efficiency curve,
Figure 17.
276
-------
TA.BLE E-48
FINE-PARTICLE EMISSIONS FROM IRON FOUNDRY CUPOLAS CONTROLLED
BY WET SCRUBBERS AND WET GAPS
Process - Cupolas
Control Device - Wet Scrubbers and Wet Caps
Process Bnissions into Control Device 35,500 tons/year
Control Device Control Device
I Wet Scrubber! I I
Process Bnissions Penetration ($) , Penetration ($) Bnissions
Size (M.) Percent (l - efficiency)-^ (l - efficiency) (tons/year)
1-5 6 31 700
0.5-1.0 2 fi 40°
0.1-0.5 2'3 86 70°
0.05-0.1
0.34 99 100
0.01-0.05
0.31 100 100
2,000
a/ Efficiency values were taken from low fractional efficiency curve,
Figure 17.
277
-------
TABLE E-49
FINE-PARTICLE EMISSIONS FROM IRON FOUNDRY CUPOLAS
CONTROLLED BY FABRIC FILTERS
Process - Cupolas
Control Device - Fabric Filter
Process Emissions into Control Device 4,800
tons/year
Control Device
I FF I
Control Device
Process Emissions
Size (iQ Percent
1-3
6
Penetration
(l - efficiency)
0.5
Penetration (%) Emissions
(l - efficiency) (tons/year)
0.5-1.0
1.8
0.1-0.5
2.3
3.3
0.05-0.1
0.34
4.2
0.01-0.05
0.31
4.5
« 100
278
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279
-------
TABLE E-51
DISTRIBUTION OF PROCESS EMISSIONS FROM BARK BOILER
Source -
Mills
Process - Bark Boilers
Production
(tons/year)
Process Bnissions = (
Application of Control
72
Emission Factor
(ib/ton)
(SjOUu)
= 7 54,400£/tons/yoar
Process Emissions into Uncontrolled Plants = 205,600
_tons/year
Process Bnissions into Controlled Plants = 528,800
tons/year
type of
Control Device
Cyclones
% Application on
Controlled Plants
100
Process Emissions into
Control Device (tons/year)
528,800
a/ See Reference 1 for method of process emissions calculations.
280
-------
TABLE E-52
PINE-PARTICLE EMISSIONS FROM UNCONTROLLED BARK BOILERS
Process - Bark Boilers
Control Device - Uncontrolled
Process Emissions into Control Device 205,600
tons/year
Control Device
Control Device
Process Emissions
Size (ti) Percent
1-3
8.3
Uncontrolled(
Penetration (#)
(l - efficiency)
100
Penetration () Emissions
(l - efficiency) (tons/year)
17,100
0.5-1.0
1.77
100
3,600
0.1-0.5
0.89
100
1,800
0.05-0.1
0.03
100
100
0.01-0.05
22,600
281
-------
TABLE E-53
FINE-PARTICLE EMISSIONS FROM BARK BOILERS CONTROLLED BY CYCLONES
Process -
Boilers
Control Device - Cyclones
Process Emissions into Control Device 528,800
tons/year
Control Device
Control Device
1 Cyclones
Process
Size (n)
1-3
Emissions
Percent
8.3
1
Penetration (<$>)
(l - efficiency)^/
73
1
1
Penetration ($)
(l - efficiency)
Emissions
(tons /year)
32,000
0.5-1.0
1.77
89
8,300
0.1-0.5
0.89
100
4,700
0.05-0.1
0.03
100
200
0.01-0.05
45,200
a/ Efficiency values were taken medium fractional efficiency curve,
Figure 17.
282
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283
-------
TABLE E-55
DISTRIBUTION OF PROCESS EMISSIONS FROM RECOVERY FURNACE
Source - Pulp Mill
Process - Recovery Furnaces
Production Emission Factor
(tons/year) (ib/ton)
Process Emissions = ( 24.5 x 106 ) (150 )
Application of Control =
99
Process Emissions into Uncontrolled Plants =
18.200
= 1,822.500 tons/year
tons/year
Process Emissions into Controlled Plants = 1.804.300 tons/year
Type of
Control Device
% Application on
Controlled Plants
Process Emissions into
Control Device (tons/year)
ESP
ESP + Wet
Venturi Evaporator
Venturi + Wet
82
4
11
3
1,804,300
(See Notej
Note: Fractional efficiency characteristics of these specialized Venturi
evaporator systems are not known. Since electrostatic precipitator
represents most applications, we will assume all are equivalent to
"medium" efficiency electrostatic precipitators.
284
-------
TABLE E-56
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED RECOVERY FURNACES
Process - Recovery Furnace
Control Device - Uncontrolled
Process Emissions into Control Device 18.200
tons/year
Process Emissions
Size (n) Percent
1-3
44
Control Device
[Uncontrolled|
Penetration ()
(l - efficiency)
100
Control Device
I I
Penetration
l - efficiency)
Emissions
(tons/year)
8,000
0.5-1.0
24
100
4,400
0.1-0.5
13.8
100
2,500
0.05-0.1
0.19
100
0.01-0.05
14,900
285
-------
TABLE E-57
FINE-PARTICLE EMISSIONS FROM RECOVERY FURNACES CONTROLLED
BY ELECTROSTATIC PRECIPITATOR
Process - Recovery Furnace
Control Device - Electrostatic Precipitators^
Process Emissions into Control Device
Control Devic<
ESP
Process Emissions Penetration ('
Size (p,) Percent (l - efficiency
1-3 44 11
0.5-1.0 24 17
0.1-0.5 13«8 29
0.05-0.1 0-19 41
0.01-0.05 55
Control Device
1
Process Emissions Penetration ($
Size (u) Percent (l - efficiency
1-3 44 1.6
0.5-1.0 24 2.3
0.1-0.5 13.8 3.8
0.05-0.1 0.19 5.5
0.01-0.05
1,804,300 tons/year
2 Control Device
1 1
») Penetration ($) Emissions
f^ (l - efficiency) (tons/year)
87,300
73,600
72,200
1,400
234,500
Control Device
1
) Penetration (#) Emissions
)£/ (l - efficiency) (tons /year)
12,700
10 ,000
9,500
200
32,400
a/ Efficiency values used were taken from medium fractional efficiency curve,
Figure 17.
b/ Efficiency values used were taken from high efficiency curve, Figure 17.
286
-------
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287
-------
TABLE E-59
DISTRIBUTION OF PROCESS EMISSIONS FROM PULP-MILL LIME KILNS
Source -
Mills
Process - Lime Kilns
Production Emission Factor
(tons/year) (ib/ton)
Process Emissions = ( 24.5 x 106 ) ( 45 )
Application of Control =
99
(2,600)
546,800 tons/year
Process Emissions into Uncontrolled Plants = _ 5,500 _ tons/year
Process Emissions into Controlled Plants = 541,500 _ tons/year
of
Control Device
Wet Scrubljers
% Application on
Controlled Plants
100
Process EMssions into
Control Device (tons/year)
541»300
288
-------
TABLE E-60
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED PULP-MILL LIME KILNS
Process - Lime Kiln — Pulp Mill _
Control Device - Uncontrolled
Process Emissions into Control Device
5,500
tons/year
Control Device
I Uncontrolled I
Process Emissions
Size (iQ _ Percent
1-3 1
Penetration
(l - efficiency)
100
Control Device
Penetration ($) Emissions
(l - efficiency) (tons /year)
100
0.5-1.0
0-09
0.1-0.5
0.05-0.1
0.01-0.05
100
289
-------
TA.BLK E-C1
FINE-PARTI OLE EMISSIONS FHOM PULP-MtJ.L JJMK KILNS
CONTROLLED BY WET SCRUBBERS
Process - Lime Kiln—Pulp Mill
Control Device - Wet Scrubbers
Process Emissions into Control Device 541,300
tons/year
Control Device
Control Device
Process Emissions
Size (M.) Percent
1-3 1.3
| Scrubbers j
Penetration ($)
(l - efficiency);*/
21
I
1
Penetration (#)
{l - efficiency)
Emissions
(tons /year)
1,500
0.5-1.0
0.09
43
200
0.1-0.5
74
0.05-0.1
95
0.01-0.05
100
1,700
a/ Efficiency values were taken from medium efficiency curve, Figure 17.
290
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291
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TABLE E-63
DISTRIBUTION OF PROCESS EMISSIONS FROM ROTARY LIME KILN
Source - Lime
Process - Rotary Kilns
Production Emission Factor
(tons/year) (ib/ton)
fie r\ ,, irt6
)
( 160 )
=1,458,000 tons/year
Process Emissions = (16.2 x •
Application of Control = 87 %
Process Emissions into Uncontrolled Plants = 190,000 tons/year
Process Emissions into Controlled Plants = 1,268,000 tons/year
Type of
Control Device
Cyclones
% Application on
Controlled Plants
20.6
Process Emissions into
Control Device (tons/year)
261,000
Wet
35.4
449,000
FF
44.0
558.000
292
-------
TABLE E-64
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED ROTARY LIME KILNS
Process - Lime Kilns—Rotary
Control Device - Uncontrolled Plants
Process Bnissions into Control Device 190,000 tons/year
Control Device Control Device
I Uncontrolled I I I
Process Bnissions Penetration ($) Penetration ($) Bnissions
Size (M-) Percent (l - efficiency) (l - efficiency) (tons/year)
1-3 8.5 100 16.200
0.5-1.0 3_.0 100 5.700
0.1-0.5 2.95 100 5,600
0.05-0.1 0.55 100 600
0.01-0.05 0.20 100 400
28,500
293
-------
TABLE E-65
FINE-PARTICLE EMISSIONS FROM ROTARY LIME KILNS CONTROLLED BY CYCLONES
Process -
Lime Kilns
Control Device - Cyclone
Process Emissions into Control Device
261.000
tons/year
Control Device
Process Emissions
Size (|i) Percent
1-3 8-5
Control Device
I Cyclone 1
Penetration ($) Penetration (%)
(l - efficiency)^/ (l - efficiency)
73
Emissions
(tons/year)
16,200
0.5-1.0
3.0
89
7,000
0.1-0.5
2.95
100
7,700
0.05-0.1
0.33
100
900
0.01-0.05
0.20
100
500
32,300
a/ Efficiency values used were taken from medium fractional efficiency curve,
Figure 17.
Note: Particle size distribution for kilns controlled by cyclones shows
58$ < 3 (j,. Therefore, assuming overall cyclone efficiency of
70$, emissions are calculated to be
(261,000 tons/year)(1-0.70)(58$) = 45,400 tons/ year < 3 u.
294
-------
TABLE E-66
FIDE-PARTICLE EMISSIONS FROM ROTARY LIME KILNS CONTROLLED BY WET SCRUBBERS
Process - Rotary Lime Kilns
Control Device - Wet Scrubbers
Process Emissions into Control Device 449,000
tons/jn
•ear
Control Device
Control Device
Process Emissions
Size (n) Percent
1-3 8.5
Wet Scrubber
Penetration (#)
(l - efficiency)^/
21
1
Penetration ($)
(l - efficiency)
Emissions
(tons /year)
8,000
0.5-1.0
3.0
43
5,800
0.1-0.5
2.95
74
9,800
0.05-0.1
0.33
95
1,400
0.01-0.05
0.20
100
900
25,900
a/ Efficiency values used were taken from medium efficiency curve, Figure 17,
Note: Particle size distribution for kilns controlled by wet scrubber in-
dicates 67% < 3 p,. Assuming overall scrubber efficiency of
emissions are calculated to be
(449,000 tons/year)(1-0.90)(0.67) = 30,100 tons year < 3 p,.
295
-------
TABLE E-67
FINE-PARTICLE EMISSIONS FROM ROTARY LIME KILNS CONTROLLED
BY FABRIC FILTER
Process - Rotary Lime Kilns
Control Device - Fabric Filter
Process Emissions into Control Device 558,000
tons/year
Control Device
L
J
Process Emissions
Size (n) Percent
1-3
8.5
Penetration
(l - efficiency)
0.5
Control Device
Penetration (%) Emissions
(l - efficiency) (tons/year)
200
0.5-1.0
3.0
1.8
300
0.1-0.5
2.95
3.3
500
0.05-0.1
0.33
4.2
100
0.01-0.05
0.20
4.4
1,100
296
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297
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TABLE E-69
DISTRIBUTION OF PROCESS EMISSIONS FROM MUNICIPAL INCINERATOR
Source - Municipal Incineration
Process - Incinerators
Production Emission Factor
(tons/year) (ib/ton)
Process Emissions = ( 20 x 1Q6 ) ( 24 )
Application of Control = 60 %
Process Emissions into Uncontrolled Plants =
Process Emissions into Controlled Plants =
(2,ouo)
= 240,000 tons/year
96,000 tons/year
144,000 tons/year
Type of
Control Device
Low efficiency scrubber
$ Application on
Controlled Plants
77
Process Emissions into
Control Device (tons/year)
1U .000
Medium efficiency scrubber 8_
Cyclones 15
11,500
21,500
298
-------
TABLE E-70
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED MUNICIPAL INCINERATORS
Process - Municipal Incinerator
Control Device - Uncontrolled
Process Bnissions into Control Device
96,000
tons/year
Control Device
Process Emissions
Size (M.) Percent
1-3
7.0
Uncontrolled]
Penetration (#)
(l - efficiency)
100
Control Device
Penetration
(1 - efficiency)
Emissions
(tons/year)
6,700
0.5-1.0
3.5
100
5,400
0.1-0.5
5.2
100
5,000
0.05-0.1
1.5
100
1,400
0.01-0.05
1.8
100
1,700
18,200
299
-------
TABLE E-71
FINE-PARTICLE EMISSIONS FROM MUNICIPAL INCINERATORS CONTROLLED
By LOW EFFICIENCY SCRUBBER
Process - Municipal Incinerator
Control Device - Low Efficiency Scrubber
Process Emissions into Control Device 111,000
tons/year
Control Device
Control Device
Process
Size (u)
1-3
Emissions
Percent
7.0
Scrubber |
Penetration ($)
(l - efficiency)^/
31
1
1
Penetration (%)
(l - efficiency)
Emissions
(tons /year)
2,400
0.5-1.0
3.5
61
2,400
0.1-0.5
5.2
86
5,000
0.05-0.1
1.5
99
1,600
0.01-0.05
1.8
100
2,000
13,400
a/ Efficiency values were taken from low efficiency curve, Figure 17.
300
-------
TABLE E-72
FIHE-PARTICLE EMISSIONS FROM MUNICIPAL INCINERATOR CONTROLLED
BY MEDIUM EFFICIENCY SCRUBBER
Process - Municipal Incinerator
Control Device - Medium Efficiency Scrubber
Process Emissions into Control Device 11,500 tons/year
Control Device Control Device
I ScrubberI II
Process Bnissions Penetration (#) Penetration (%) Emissions
Size (p.) Percent (l - efficiency)^/ (l - efficiency) (tons/year)
1-3
7.0 21 200
0.5-1.0 5-5 « 200
0.1-0.5 5-2 74 400
0.05-0.1 1-5 95 200
0,01-0.05 3-6 1£0 200
1,200
a/ Efficiency values were taken from medium efficiency curve, Figure 17.
301
-------
TABLE E-73
FINE-PARTICLE EMISSIONS FROM MUNICIPAL INCINERATORS
CONTROLLED BY CYCLONES
Process - Municipal Incinerator
Control Device - Cyclones
Process Emissions into Control Device
21,500
tons/year
Control Device
| Cyclone |
Control Device
Process Emissions
Size (u) Percent
1-3
0.5-1.0
7.0
3.5
Penetration ($) Penetration ($) Emissions
(l - efficiency)^/ (l - efficiency) (tons/year)
73 1,100
89
700
0.1-0.5
5.2
100
1,100
0.05-0.1
1.5
100
300
0.01-0.05 1.8
100
400
3,600
a/ Efficiency values were taken from medium efficiency curve, Figure 17.
302
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TAULE K-'/b
DISTRIBUTION OF PROCESS EMISSIONS FROM ELECTRIC UTILITY PULVERIZED
COAL-FIRED BOILER
Source - Stationary Combustion
Process - Electric Utility Pulverized Coal-Fired Boiler
Production Emission Factor
(tons/year) (ib/ton) . -^
Process Emissions = ( 258.4 x 106 ) ( 190 ) L j^] = 24.6 x 106 tons/year
Application of Control = 96.9 %
Process Emissions into Uncontrolled Plants = 0.6 x 10 tons/year
Process Emissions into Controlled Plants = 25.8 x 1Q6 tons/year
of
Control Device
Cyclones
Cy + ESP
ESP
% Application on
Controlled Plants
24.3
15.1
60.6
Fiimiorjlorin Into
Control Device (torm/y^ar)
5.8 x 106
5.6 x 106
14.4 x 106
304
-------
TABLE E-Y(J
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED ELECTRIC UTILITY
PULVERIZED COAL-FIRED BOILERS
Process - Electric Utility Pulverized Coal-Fired Boiler
Control Device - Uncontrolled
Process Bnissions into Control Device °»8 x 10
tons/year
Process Bnissions
Size (p.) Percent
1-3
10
Control Device
I Uncontrolled!
Penetration (#)
(l - efficiency)
100
Control Device
Penetration (%) Enissions
(l - efficiency) (tons/year)
60,000
0.5-1.0
2.1
100
16,600
0.1-0.5
0.87
100
7,000
0.05-0.1
0.02
100
200
0.01-0.05
104,000
305
-------
TABLE E-77
FINE-PARTICLE EMISSIONS FROM ELECTRIC UTILITY PULVERIZED COAL-FIRED BOILERS
CONTROLLED BY ELECTROSTATIC PRECIPIIATOR
Process - Electric Utility Pulverized Coal-Fired Boiler
Control Device - Electrostatic Precipitator
Process Emissions into Control Device 14.4 x 106
_tons/year
Control Device
Control Device
1 ESP 1 1
Process
Size (n)
1-3
Emissions
Percent
10
Penetration (%)
(1 - efficiency)^/
11
Penetration ($)
(l - efficiency)
Emissions
{tons /year)
158,400
0.5-1.0
2.1
17
51,400
0.1-0.5
0.87
29
36,300
0.05-0.1
0.02
41
1.200
0.01-0.05
247,300
a/ Efficiency values used were taken from average fractional efficiency
curve, Figure 17.
306
-------
TAHI.I'! K-'/H
FINE-PARTICLE EMISSIONS M
-------
TABLE E-79
FINE-PAHTICLE EMISSIONS FROM ELECTRIC UTILITY PULVERIZED COAL-FIRED BOILERS
CONTROLLED BY CYCLONE PLUS ELECTROSTATIC PRECIPITA.TOR
Process - Electric Utility Pulverized Coal-Fired Boiler
Control Device - Cyclone + Electrostatic Precipitator
c
Process Emissions into Control Device 3.6 x 10°
tons/year
Control Device
| Cyclone [
Control Device
ESP
Process Emissions
Size (M.) Percent
1-3
10
Penetration
(l - efficiency)
57
Penetration
(1 - efficiency)
11
Emissions
(tons/year)
22.600
0.5-1.0
2.1
82
17
10.500
0.1-0.5
0.87
94
29
6,500
0.05-0.1
0.02
100
41
300
0.01-0.05
41,900
308
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TABLE E-81
DISTRIBUTION OF MtOCI'gjn BMliJmoN.'I 1'KQM ELk'CTKlC UTILITY ."'J'OKEK
COAL-FIRED BOiLEK
Source - Stationary Combustion
Process - Electric Utility Stoker Coal-Fired Boiler
Production Emission Factor
(tons/year) (ib/ton) * >.
Process Emissions = ( 9.9 x 106 ) ( 146 ) L^ *^\ = 0.72xl06 tons/year
Application of Control = 87 %
Process Emissions into Uncontrolled Plants = 0.095 x 106 tons/year
Process Bnissions into Controlled Plants = 0.627 x 106 tons/year
of
Control Device
ESP
Cyclones
$ Application on
Controlled Plants
5.2
94.8
Prcxjess
Control Device (tons/your)
0.035 x 1Q6
0.594 x 106
310
-------
TABLE E-82
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED ELECTRIC UTILITY STOKER
COAL-FIRED BOILERS
Process - Electric Utility Stoker Coal-Fired Boiler
Control Device - Uncontrolled
ft
Process Emissions into Control Device 0.093 x 10 tons/year
Control Device Control Device
Uncontrolled
Process Emissions Penetration (%) Penetration (%) Emissions
Size (ti) Percent (l - efficiency) (l - efficiency) (tons/year)
1-5 4.8 100 4.500
0.5-1.0 0_.9 100 800
0.1-0.5 0.29 100 300
0.05-0.1
0.01-0.05 i
5,600
311
-------
TA.BLE E-83
FINE-PARTICLE EMISSIONS FROM ELECTRIC UTILITY STOKER COAL-FIRED BOILERS
CONTROLLED BY ELECIROSIA.TIC PRECIPITATOR
Process - Electric Utility Stoker Coal-Fired Boiler_
Control Device - Electrostatic Precipitator
Process Emissions into Control Device 0.053 x 106
tons/year
Control Device
Control Device
Process
Size (n)
1-3
Emissions
Percent
4.8
1
ESP 1
Penetration (#)
(1 - efficiency)^/
11
1
Penetration (#)
(l - efficiency)
Emissions
(tons /year)
900
0.5-1.0
0.9
17
500
0.1-0.5
0.29
29
300
0.05-0.1
0.01-0.05
1,700
a/ Efficiency values used were taken from average fractional efficiency
curve, Figure 17.
312
-------
TABLE E-84
FIME-PARTICLE EMISSIONS FROM ELECTRIC UTILITY STOKER COAL-FIRED BOILERS
CONTROLLED BY CYCLONES
Process - Electric Utility Stoker Coal-Fired Boiler
Control Device - Cyclones
Process Bnissions into Control Device 0.594 x 10
,6
tons/year
Control Device
Control Device
Process Bnissions
Size (n) Percent
1-3 4.8
1 Cyclone
Penetration (#)
(l - efficiency)^
57
1
Penetration (#)
(l - efficiency)
Emissions
(tons /year)
16,300
0.5-1.0
0.9
82
4,400
0.1-0.5
0.29
94
1,600
0.05-0.1
0.01-0.05
22,300
a/ Efficiency values used were taken from high efficiency cyclone curve,
Figure 17, because power plants use higher efficiency units.
313
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314
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TABLE E-86
DISTRIBUTION OF PROCESS EMISSIONS FROM ELECTRIC UTILITY CYCLONE
COAL-FIRED BOILER
Source - Stationary Combustion
Process - Electric Utility Cyclone Coal-Fired Boiler
Production Emission Factor
(tons/year) (It/ton) .
-------
TABLE E-87
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED ELECTRIC UTILITY
CYCLOME COAL-FIRED BOILERS
Process - Electric Utility Cyclone Coal-Fired Boiler
Control Device - Uncontrolled
C
Process Emissions into Control Device 0.148 x 10°
tons/year
Control Device
Process Emissions
Size (M.) Percent
1-3
22
Uncontrolled I
Penetration (%)
(l - efficiency)
100
Control Device
I I
Penetration
(l - efficiency)
Emissions
(tons/year)
52.600
0.5-1.0
5.5
100
8,100
0.1-0.5
2.44
100
3,600
0.05-0.1
0.05
100
100
0.01-0.05
44,400
316
-------
TABLE E-88
FINE-PARTICLE EMISSIONS FROM ELECTRIC UTILITY CYCLONE COAL-FIRED BOILERS
CONTROLLED BY ELECTROSTATIC PRECIPITA.TOR
Process - Electric Utility Cyclone Coal-Fired Boiler
Control Device - Electrostatic Precipitator
Process Emissions into Control Device 0.294 x 106
tons/year
Control Device
Control Device
Process Emissions
Size (n) Percent
1-3 22
1 ESP 1
Penetration ($)
(l - efficiency)^/
11
L
1
Penetration ($)
(1 - efficiency)
Emissions
(tons/year)
7,100
0.5-1.0
5.5
17
2,700
0.1-0.5
2.44
29
2,100
0.05-0.1
0.05
41
100
0.01-0.05
12,000
a/ Efficiency values used were taken from average fractional efficiency curve,
Figure 17.
317
-------
TABLE E-89
FINE-PARTICLE EMISSIONS FROM ELECTRIC UTILITY CYCLONE
CCAL-FIRED BOILERS CONTROLLED BY CYCLONE
Process - Electric Utility Cyclone Coal-Fired Boiler
Control Device - Cyclone
Process Emissions into Control Device 0.068 x 10 tons/year
Control Device Control Device
I Cyclone I I I
Process Emissions Penetration ($) Penetration (%) Emissions
Size (ii) Percent (l - efficiency)^/ (l - efficiency) (tons/year)
1-3 22 57 8,500
0.5-1.0 5.5 82 5,100
0.1-0.5 2.44 94 - 1,600
0.05-0.1 0.05 100
0.01-0.05
13,200
a/ Efficiency values used were taken from high efficiency cyclone curve,
Figure 17, because power plants use higher efficiency units.
318
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TABLE E-91
DISTRIBUTION OF PROCESS EMISSIONS FROM INDUSTRIAL
PULVERIZED COAL-FIRED BOILER
Source - Stationary Combustion
Process - Industrial Pulverized Coal-Fired Boiler
Production Emission Factor
(tons/year) (ib/ton) - >.
Process Emissions = ( 20 x 106 ) ( 170 ) f j^A = 1.7xl06 tons/year
V /
Application of Control = 95.5 %
Process Emissions into Uncontrolled Plants = 0.076 x 106 tons/year
Process Emissions into Controlled Plants = 1.624 x 106 tons/year
Type of
Control Device
ESP
Cyclones
% Application on
Controlled Plants
31
69
Process Emissions into
Control Device (tons/year)
0.505 x 106
1.12 x 106
320
-------
TABLE E-92
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED INDUSTRIAL
PULVERIZED COAL-FIRED BOILERS
Process - Industrial Pulverized Coal-Fired Boiler
Control Device - Uncontrolled _
Process Emissions into Control Device 0.076 x 10 _ tons/year
Control Device Control Device
lUncontr oiled | I |
Process Emissions Penetration (#) Penetration (#) Emissions
Size (tO _ Percent (l - efficiency) (l - efficiency) ( tons /year >
1-5 _ 1.95 _ 100 _ 1.500
0.5-1.0 _ 0.05 _ 100
0.1-0.5 _
0.05-0.1
0.01-0.05 __ .
1,500
321
-------
TABLE E-93
FINE-PARTICLE EMISSIONS FROM INDUSTRIAL PULVERIZED COAL-FIRED BOILERS
CONTROLLED BY ELECTROSTATIC PRECIPIIATOR
Process - Industrial Pulverized Coal-Fired Boiler
Control Device - Electrostatic Precipitator
r*
Process Emissions into Control Device 0.505 x 10P
tons/year
Control Device
Process Emissions
gize (iQ Percent
1-3
Control Device
I ESP "~1 I
Penetration ($) Penetration
(l - efficiency)^/ (l - efficiency)
1.95
11
Emissions
(tons/year)
1.100
0.5-1.0
0.05
17
0.1-0.5
0.05-0.1
0.01-0.05
1,100
a/ Efficiency values used were taken from average fractional efficiency
curve, Figure 17.
322
-------
TABLE E-94
FINE-PARTICLE EMISSIONS FROM INDUSTRIAL PULVERIZED COAL-FIRED BOILERS
CONTROLLED BY CYCLONES
Process - Industrial Pulverized Coal-Fired Boiler
Control Device - Cyclones
Process Emissions into Control Device
x 10
tons/year
Control Device
Control Device
Process
Size (n)
1-3
Emissions
Percent
1.95
1
Cyclone
1
Penetration ($)
(l - efficiency^/
57
Penetration ($)
(1 - efficiency)
Emissions
(tons /year)
12,500
0.5-1.0
0.05
82
500
0.1-0.5
0.05-0.1
0.01-0.05
13,000
a/ Efficiency values used were taken from high efficiency cyclone curve,
Figure 17.
323
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TABLE E-96
DISTRIBUTION OF PROCESS EMISSIONS FROM INDUSTRIAL
STOKER COAL-FIRED BOILERS
Source - Stationary Combustion
Process - Industrial Stoker Coal-Fired Boilers
Emission Factor
(ib/ton)
( 155 )
Production
(tons/year)
Process Emissions = ( 70 x 106 )
Application of Control = 62
fy,ouu)
4.655 x
= lp6 tons/year
Process Emissions into Uncontrolled Plants = 1.77 x 10° tons /year
Process Emissions into Controlled Plants = 2.886 x 106 tons/year '
Type of
Control Device
ESP
Cyclones
$ Application on
Controlled Plants
14.8
85.2
Process Emissions into
Control Device (tons/year)
0.427 x 106
2.46 x 106
325
-------
TABLE E-97
FIUE-PARTICLE EMISSIONS FROM UNCONTROLLED INDUSTRIAL
STOKER COAL-FIRED BOILERS
Process - Industrial Stoker Coal-Fired Boiler
Control Device - Uncontrolled
Process Emissions into Control Device 1.77 x 10
tons/year
Control Device
Control Device
Uncontrolled]
Process Emissions
Size (|i) Percent
1-3
1.76
Penetration
(l - efficiency)
100
Penetration
(l - efficiency)
Emissions
(tons/year)
31,100
0.5-1.0
0.19
100
3,400
0.1-0.5
0.05
100
900
0.05-0.1
0.01-0.05
35,400
326
-------
TABLE E-98
FINE-PARTICLE EMISSIONS FROM INDUSTRIAL STOKER COAL-FIRED BOILERS
CONTROLLED BY ELECTROSTATIC PRECIPITATOR
Process - Industrial Stoker Coal-Fired Boiler
Control Device - Electrostatic Precipitator
Process Emissions into Control Device 0.427 x
tons/year
Control Device
Control Device
Process
Size (n)
1-3
Emissions
Percent
1.76
1
ESP 1
Penetration ($
(l - efficiency
11
)»/
1
1
Penetration (%)
(l - efficiency)
Emissions
( tons/year')
800 .
0.5-1.0
0.19
17
100
0.1-0.5
0.05
29
0.05-0.1
0.01-0.05
900
a/ Efficiency values used were taken from average fractional efficiency
curve, Figure 17.
327
-------
TABLE l-J-99
FINE-PARTICLE EMISSIONS FROM INDUSTRIAL STOKER COAL-FIRED BOILERS
CONTROLLED BY CYCLONES
Process - Industrial Stoker Coal-Fired Boiler
Control Device - Cyclone
Process Emissions into Control Device 2.459 x 106 tons/year
Control Device Control Device
Cyclone
Process Emissions Penetration ($) Penetration ($) Emissions
Size (it) Percent (l - efficiency)^/ (l - efficiency) (tons/year)
1_3 1.76 57 24,700
0". 5-1.0 0.19 82 5,800
0.1-0.5 0.05 94 1,200
0.05-0.1
0.01-0.05
29,700
a/ Efficiency values were taken from high efficiency cyclone curve,
Figure 17.
328
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TABLE E-101
DISTRIBUTION OF PROCESS EMISSIONS FROM INDUSTRIAL CYCLONE
COAL-FIRED BOILER
Source - Stationary Combustion
Process - Industrial Cyclone Coal-Fired Boiler
Emission Factor
(Ib/ton) ,
( 31 )
Production
(tons/year)
Process Emissions = ( 10 x 106 )
0.155
= x Ip6 tons/year
Application of Control = 91 #
Process Emissions into Uncontrolled Plants = 0.014 x 10° tons/year
Process Emissions into Controlled Plants = 0.141 x 106 tons/year
of
Control Device
ESP
% Application on
Controlled Plants
55
Process Emissions into
Control Device (tons/year)
0.078 x 106
Cyclones
45
0.063 x 106
330
-------
TABLE E-102
FINE-PARTICLE EMISSIONS FROM UNCONTROLLED INDUSTRIAL CYCLONE
COAL-FIRED BOILERS
Process - Industrial Cyclone Coal-Fired Boiler
Control Device - Uncontrolled
Process Emissions into Control Device 0.014 x
tons/year
Process Emissions
Size (n) Percent
1-3
23
Control Device
|Uncontrolled!
Penetration ($)
(l - efficiency)
100
Control Device
Penetration
(l - efficiency)
Emissions
(tons/year)
3,200 _
0.5-1.0
8.5
100
1,200
0.1-0.5
4.3
100
600
0.05-0.1
0.16
100
0.01-0.05
0.04
100
5,000
331
-------
TABLE E-103
FINE-PARTICLE EMISSIONS FROM INDUSTRIAL CYCLONE COAL-FIRED BOILERS
CONTROLLED BY ELECTROSTATIC PRECIPITATOR
Process - Industrial Cyclone Coal-Fired Boiler
Control Device - Electrostatic Precipitators
Process Emissions into Control Device 0.078 x 10
tons'/year
Control Device
Control Device
Process Emissions
Size (jj,) Percent
1-3 23
1
ESP 1
Penetration ($)
(l - efficiency)^/
11
L_
1
Penetration ($)
(l - efficiency)
Emissions
(tons /year)
2,000
0.5-1.0
8.5
17
1,100
0.1-0.5
4.3
29
1,000
0.05-0.1
0.16
41
0.01-0.05
0.04
55
4,100
a/ Efficiency values used were taken from average fractional efficiency
curve, Figure 17.
332
-------
TABLE E-104
FINE-PARTICLE EMISSIONS FROM INDUSTRIAL CYCLONE COAL-FIRED BOILERS
CONTROLLED BY CYCLONES
Process - Industrial Cyclone Coal-Fired Boiler
Control Device - Cyclones
C
Process Bnissions into Control Device 0.065 x 10
tons/year
Control Device
Control Device
Process Snissions
Size (p.) Percent
1-3 23
1
Cyclone 1
Penetration (#)
(l - efficiency)*/
57
1
1
Penetration ($)
(l - efficiency)
Bnissions
(tons /year)
8,300
0.5-1.0
8.5
82
4,400
0.1-0.5
4.3
94
g,500
0.05-0.1
0.16
100
100
0.01-0.05
0.04
100
15,300
a/ Efficiency values were taken from high efficiency cyclone curve,
Figure 17.
333
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