-------
TABLE 6.4-5. TOTAL PARTICULATE EMISSION FACTORS FOR
GRAIN ELEVATORS, BASED ON AMOUNT OF GRAIN RECEIVED OR SHIPPED3
EMISSION FACTOR RATING: C
Typo of Operation
Country elevators
Unloading (receiving)
Loading (shipping)
Removal from bins (tunnel belt) .
Dryingd
Cleaning*
Hcadhouse (legs)
Inland terminal elevators
Unloading (receiving)
Loading (shipping)
Removal from bins (tunnel belt)
Drying*
Cleaning0
Hcadhouse (legs)
Tripper (gallery belt)
Export elevators
Unloading (receiving)
Loading (shipping)
Removal from bins (tunnel belt)
Dryingd
Cleaning6
Headhouse (legs)
Tripper (gallery belt)
Emission factor,
kg/Mg handled1*
0.3
0.2
0.5
0.4
1.5
0.8
0.5
0.2
0.7
0.6
1.5
0.8
0.5
0.5
0.5
0.7
0.5
1.5
0.8
0.5
X
Typical ratio of grain
processed to grain
received or shipped0
1.0
1.0
2.1
0.3
0.1
3.1
1.0
1.0
2.0
0.1
0.2
3.0
1.7
1.0
1.0
1.2
0.01
0.2
2.2
1.1
=
Emission factor,
kg/Hg received
or shipped
0.3
0.2
1.0
0.1
0.2
2.5
0.5
0.2
1.4
0.1
0.3
2.3
0.8
0.5
0.5
0.8
0.01
0.3
1.7
0.6
*>to obtain units of Ib/ton, multiply factors by 2.0.
cRcfcrence 6. Average values from a survey of elevators across the U. S.
for any individual elevator or group of elevators in the same locale.
dSeo Note b in Table 6.4-1.
eSoc Note c in Table 6.4-1.
Can be considerably different
6.4-8
EMISSION FACTORS
9/88
-------
about 25 percent of the total loading), allowing essentially uncontrolled
emissions to escape. j
i i
Most elevators utilize particulate control devices on at least some of
their operations. The traditional form of control at elevators has been
mechanical collectors, or cyclones. Cyclones collect particles larger than
about 10 microns with only 85 to 95 percent control efficiency, often
producing visible emissions. Hence, fabric filters are usually selected in
areas having more stringent control requirements. Typical efficiencies for
well operated fabric filters exceed 99 percent, with no visible emissions.
The air aspirated from enclosed equipment and hoods is ducted to a fabric
filter or, in some cases, one or more cyclones. Rarely are other particulate
control devices, such as wet scrubbers and electrostatic precipitators,
applied at elevators. Grain dryers present a different sort of control
problem because of the large volumes of warm, moist air exhausted. Most
dryers are enclosed with a continuously vacuumed polyester or stainless steel
screening to collect particulate, with the vacuum usually discharged to a
cyclone. Two principal dryer configurations, rack and column, are in use.
The majority of dryers manufactured today are of the column type, which has
considerably lower emissions than the rack type.16
i
6.4.2.2 Grain Processing Plants - Several grain milling operations, such as
receiving, conveying, cleaning and drying, are similar to those at grain
elevators. In addition to these, breaking down (milling) the grain or grain
by-products for processing through various types of grinding operations is a
further source of emissions. The hammermill is the most: widely used grinding
device at feed mills. Product is recovered from the hammermill with a
cyclone collector, which can be a major source of dust esmissions. Again,
like elevators, mills use a combination of cyclones and fabric filters to
conserve product and to control emissions. Drying at a grain mill is accom-
plished using several types of dryers, including fluidizied bed dryers (soy-
bean processing) and flash fired or direct fired dryers (corn milling).
These newer dryer types might have lower emissions than the traditional rack
or column dryers, but data are. insufficient at this time to quantify the
difference. The grain pre-cleaning often performed before drying also likely
serves to reduce emissions. Emission factors for various grain milling and
other processing operations are presented in Table 6.4-6, and the particle
size distribution and size specific emission factor for a roaster operation
are shown in Table 6.4-7 and Figure 6.4-5. The origins of these emission
factors are discussed below. ,
1 Emission factor data for feed mill operations are sparse. The factors
for receiving, shipping and handling are based on estimates made by experts
within the feed industry.17 The remaining feed mill factors are based on test
data in References 2, 18 and 19.
i "
The roasting of carob kibble (or pods), which are ground and used as a
Chocolate substitute, is similar to coffee roasting. The emission factor and
particle size distribution for this operation were derived from References 20
and 21.
i
I Three emission areas for wheat mill processing operations are grain
receiving and handling, cleaning house and milling operations. Data from
Reference 5 were used to estimate emission factors for grain receiving and
9/88 Food And Agricultural Industry 6.4-9
-------
TABLE 6.4-6. TOTAL PARTICIPATE EMISSION FACTORS FOR
UNCONTROLLED GRAIN PROCESSING OPERATIONS*
EMISSION FACTOR RATING: D
Type of Operation
Feed mills
Receiving
Shipping
Handling
Grinding
Hamme rail lingb
Flakingb
Crackingb
Pellet cooler^
Carob kibble roasting
Wheat milling
Receiving
Precleaning and handling
Cleaning house
Mill house
Durum milling
Receiving
Precleaning and handling
Cleaning house
Mill house
Rye milling
Receiving
Precleaning and handling
Cleaning house
Mill house
e
Oat milling
Rice milling
Receiving
Precleaning and handling
Drying^
Cleaning and mill house
Emission factor
kg/Mg
1.3
0.5
2.7
O.lc»d
O.lc
_ [
0.01c»d
0.2C
3.0
0.5
2.5
35.0
0.5
2.5
^
.
0.5
2.5
35.0
1.25
0.32
2.5
0.15
Ib/ton
2p
.5
1.0
5.5
0 2^* »^*
«. A*i
0.2d
o!4e
6.0
1.0
5.0
~
70.0
1.0
5.0
"
1.0
5.0
"
70.0
2.5
0.64
5.0
0.30
H>
6.4-10
EMISSION FACTORS
9/88
-------
TABLE 6.4-6 (concluded).
Type of Operation
Soybean milling
Receiving
Handling
Cleaning
DryingS
Cracking and dehulling
Hull grinding
Bean conditioning
Flaking
Meal dryer
Meal cooler
Bulk loading
)ry corn milling
Receiving
DryingS
Precleaning and handling
Cleaning house
Degerming and milling
Jet corn milling
Receiving
Handling
Cleaning
Dryingh
Bulk loading
Emission factor
kg/Mg
0.8
2.5
_
3.6
1.7
1.0
0.05
0.29
0.75
0.9
0.14
0.5
0.25
2.5
3.0
-
0.5
2.5
3.0
0.24
Ib/ton
1.6
5.0
7.2
3.3
2.0
0.1
0.57
1.5
1.8
0.27
1.0
0.5
5.0
6.0
1.0
5.0
6.0
0.48
* ** ^*" *-"*-o ***- '-*>*-*«» i- cuu_ u ucu/ unx u wtsj_y llL. \
grain entering the plant, not necessarily the same as amount of material
^processed by each operation. Dash = no data. j
^Expressed as weight of dust emitted/unit weight of grain processed.
cWith cyclones.
Measured on corn processing operations at feed mills.
^Represents several sources at one plant, some controlled with cyclones and
others with fabric filters.
fAverage for uncontrolled column dryers; see Table 6.4-2.
SDryer types unknown.
kFor rotary steam tube dryers.
9/88
Food And Agricultural Industry
6.4-11
-------
TABLE 6.4-7. PARTICLE SIZE DISTRIBUTION AND EMISSION
FACTORS FOR UNCONTROLLED CAROB KIBBLE ROASTERS3
EMISSION FACTOR RATING: E
Aerodynamic particle
diameter (urn)
Cumulative weight
< stated size
Emission factor^
(kg/Mg)
2.5
6.0
10.0
15.0
0.6
0.7
2.0
11.5
0.018
0.021
0.060
0.35
Total particulate
3.QC
aReference 18.
^Expressed as cumulative weight of particulate _< corresponding
particle size/unit weight of carob kibble roasted.
Reference 21.
99.9
99
S
H
V
8-5
SO
UNCONTROLLED
^ Weight percent
Emission factor
I li 11
0.10
2 5 10 20 50 100
Particle diameter, urn
Figure 6.4-5. Cumulative size distribution and
emission factors for uncontrolled carob kibble roasters.
6.4-12
EMISSION FACTORS
9/88
-------
Dandling. Data for the cleaning house are insufficient to estimate an emis-
sion faptor, and information contained in Referenced wias used to estimate the
emission factor for milling operations. The large emission factor for the
milling operation applies to uncontrolled operations. Almost all of the
sources involved, however, are equipped with control devices to prevent
product losses. Fabric filters are widely used for this purpose.
, Durum and rye milling operations are similar to those for wheat milling.
Therefore, most of these emission factors are assumed equal to those for
wheat mill operations. , j
; The grain unloading, handling and cleaning operations for dry corn mill-
ing are similar to those in other grain mills, but the subsequent operations
are somewhat different. Also, some drying of corn received at the mill may
be necessary before storage. An estimate of the emission factor for drying
was obtained from Reference 2. Insufficient information is available to
estimate emission factors for degerming and milling. j
, Information necessary to estimate emissions from oat milling is unavail-
able, and no emission factors for other grains are considered applicable
because oats are reported to be dustier than many other grains. The only
emission factor data available are for controlled emissions.
I Emission factors for rice milling are based on those for similar opera-
tions in other grain handling facilities. Insufficient information is avail-
able to estimate emission factors for drying, cleaning and mill house
operations. -
'; Information contained in Reference 2 is used to estimate emission factors
for soybean mills'. |
j Emissions information on wet corn milling is generally unavailable, in
part because of the wide variety of products and the diversity of operations.
Receiving, handling and cleaning operations emission factors are assumed to
be similar to those for dry corn milling. The drying emission factor is from
tests at a wet corn milling plant producing animal feed.72
! . , . - . - - ' ' ' \
:. Due to operational similarities between grain milling and processing
plants and grain elevators, the control methods used are similar. Both often
use cyclones or fabric filters to control emissions from the grain handling
operations (e.g. , unloading, legs, cleaners, etc.). These same devices are
also often used to control emissions from other processing operations. A
good example of this is the extensive use of fabric filters in flour mills.
However, there are also certain operations within some milling operations
that are not amenable to the use of these devices. Therefore, wet scrubbers
have found some application, particularly where the effluent gas stream has
tiigh moisture content. Certain other operations have been found to be
especially difficult to control, such as. rotary dryers in wet corn mills. .
The various emission control systems that have been applied to operations
within the grain milling and processing industry are described in Reference
2. ' .' ' - L
9/88 Food And Agricultural Industry 6.4-13
a
-------
References for Section 6.4
1. G. A. LaFlam, Documentation for AP-4.2 Emission Factors; Section 6.4,
Grain Elevators and Processing Plants, Pacific Environmental Services,
Inc., Durham, NC, September 1987.
2. L. J. Shannon, et al., Emissions Control in the Grain and Feed Industry,
Volume I - Engineering and Cost Study. EPA-450/3-73-003a, U. S. Environ-
mental Protection Agency, Research Triangle Park, NC, December 1973.
3. The Storage and Handling of Grain, PEI, Inc., Cincinnati, OH, for
U. S. EPA Region V, Contract No. 68-02-1355, March 1974.
4. Technical Guidance for Control of Industrial Process Fugitive Particu-
late Emissions, PEI, Inc., for U. S. Environmental Protection Agency,
Research Triangle Park, NC, Contract No. 68-02-1375, March 1977.
5. P. G. Gorman, Potential Dust Emission from a Grain Elevator in Kansas
City, Missouri, MRI for U. S. Environmental Protection Agency, Research
Triangle Park, NC, Contract No. 68-02-0228, May 1974.
6. L. J. Shannon, et al., Emission Control in the Grain and Feed Industry,
Volume II - Emission Inventory, EPA-450/3-73-003b, MRI for U. S.
Environmental Protection Agency, Research Triangle Park, NC, September
1974.
7. W. H. Maxwell, Stationary Source Testing of a Country Grain Elevator at
Overbrook, Kansas, MRI for U. S. Environmental Protection Agency,
Research Triangle Park, NC, Contract No. 68-02-1403, February 1976.
8. W. H. Maxwell, Stationary Source Testing of a Country Grain Elevator at
Great Bend, Kansas, MRI for U. S. Environmental Protection Agency."
Research Triangle Park, NC, Contract No. 68-02-1403, April 1976.
9. F. J. Belgea, Cyclone Emissions and Efficiency Evaluation, (Tests at
elevators in Edinburg and Thompson, North Dakota), Pollution Curbs,
Inc., St. Paul, MN, March 10, 1972.
10. F. J. Belgea, Grain Handling Dust Collection Systems Evaluation for
Farmer's Elevator Company, Minot, North Dakota, Pollution Curbs, Inc.,
St. Paul, MN, August 28, 1972.
11. M. P. Schrag, et al., Source Test Evaluation for Feed and Grain Indus-
try, EPA-450/3-76-043, U. S. Environmental Protection Agency, Research
Triangle Park, NC, December 1976.
12. Emission test data from Environmental Assessment Data Systems, Fine
Particle Emission Information System (FPEIS), Series No. 228, U. S.
Environmental Protection Agency, Research Triangle Park, NC, June 1983.
13. Air Pollution Emission Test, Burtge Corporation, Destrehan, LA. EMB-
74-GRN-7, U. S. Environmental Protection Agency, Research Triangle Park, Jlllti
NC, January 1974. ll|||
6.4-14 EMISSION FACTORS 9/88
-------
14. W. Battye and R. Hall, Particulate Emission Factors and Feasibility of
Emission Controls for Shiploading Operations at Portland, Oregon Grain
Terminals, Volume I, GCA Corporation, Bedford, MA, June 1979.
15. Emission Factor Development for Ship and Barge Loading of Grain, GCA
i Corporation for U. S. Environmental Protection Agency, Research Triangle
: Park, NC, Contract No. 68-02-3510, October 1984.
i
16. J. M. Appold, "Dust Control for Grain Dryers," in Dust Control for Grain
I Elevators, presented before the National Grain and Feed Association, St.
Louis, MO, May 7-8, 1981.
1 - i
17. Written communication from D. Bossman, American Feed Industry Associa-
tion, Arlington, VA, to F. Noonan, U. S. Environmental Protection
Agency, Research Triangle Park, NC, July 24, 1987.
18. Written communication from P. Luther, Purina Mills, Inc., St. Louis, MO,
to G. LaFlam, PES, Inc., Durham, NC, March 11, 1987,.
! ' '
19. Written communication from P. Luther, Purina Mills, Inc., St. Louis, MO,
to F. Noonan, U. S. Environmental Protection Agency,, Research Triangle
Park, NC, July 8, 1987.
2*0. Emission test data from FPEIS Series No. 229, U. S. Environmental
; Protection Agency, Research Triangle Park, NC, June 1983.
2.1. H. J. Taback, Fine Particle Emissions from Stationary and Miscellaneous
Sources in the South Coast Air Basin, KVB, Inc., Tusstin, CA, for the
California Air Resources Board, February 1979.
. . - - ':
22. Source Category Survey; Animal Feed Dryers, EPA-450/3-81-017, U. S.
Environmental Protection Agency, Research Triangle Park, NC, December
1981.
9/88
Food And Agricultural Industry
6.4-15
-------
-------
About 10 percent of all lime produced is converted to hydrated (slaked)
lime. There are two kinds of hydrators, atmospheric and pressure. Atmo-
spheric hydrators, the more prevalent type, are used in continuous mode to
produce high calcium and normal dolomitic hydrates. Pressure hydrators on
the other hand, produce only a completely hydrated dolomitic lime and oper-
ate only in batch mode. Generally, water sprays or wet scrubbers perform
the hydrating process, to prevent product loss. Following hydration, the
product may be milled and then conveyed to air separators for further drving
and removal of coarse fractions.
In the United States, lime plays a major role in chemical and metal-
lurgical operations. Two of the largest uses are as steel flux and in
alkali production. Lesser uses include construction, refractory and agri-
cultural applications. 5
I "
8.15.2 Emissions And Controls3'5
i Potential air pollutant emission points in lime'manufacturing plants
are shown in Figure 8.15-1. Except for gaseous pollutants emitted from
lq.lns, particulate is the only pollutant of concern from most of the opera-
tions, i r
I The largest ducted source of particulate is the kiln. Of the various
kiln types, fluidized beds have the most uncontrolled particulate emissions
because of the very small feed size combined with high air flow through
these kilns. Fluidized bed kilns are well controlled for maximum product
recovery. The rotary kiln is second worst in uncontrolled particulate emis-
sions, also because of the small feed size and relatively high air veloci-
ties and dust entrainment caused by the rotating chamber. The calcimatic
(rotary hearth) kiln ranks third in dust production, primarily because of
the larger feed size and the fact that, during calcination, the limestone
remains stationary relative to the hearth. The vertical kiln has the lowest
uncontrolled dust emissions, due to the large lump feed, and the relatively
low air velocities and slow movement of material through the kiln.
i Some sort of particulate control is generally applied to most kilns.
Riidimentary fallout chambers and cyclone separators are commonly used for
control of the larger particles: Fabric and gravel bed .filters, wet (com-
monly venturi) scrubbers, and electrostatic precipitators are used for sec-
ondary control.
; i
Nitrogen oxides, carbon monoxide and sulfur oxides are all produced in
kilns, although the last are the only gaseous pollutant emitted in signifi-
cant quantities. Not all of the sulfur in the kiln fuel is emitted as sul-
fur oxides, since some fraction reacts with the materials in the kiln. Some
sulfur oxide reduction is also effected by the various equipment used for
secondary particulate control. j
: . Product coolers are emission sources only when some of their exhaust
gases are not recycled through the kiln for use as combustion air. The
10/86 Mineral Products Industry 8.15-3
-------
trend is away from the venting of product-cooler exhaust, however, to maxi-
mize fuel use efficiencies. Cyclones, baghouses and wet scrubbers have been
employed on coolers for particulate control.
Hydrator emissions are low, because water sprays or wet scrubbers are
usually installed to prevent product loss in the exhaust gases. Emissions
from pressure hydrators may be higher than from the more common atmospheric
hydrators, because the exhaust gases are released intermittently, making
control more difficult.
Other particulate sources in lime plants include primary and secondary
crushers, mills, screens, mechanical and pneumatic transfer operations,
storage piles, and roads. If quarrying is a part of the lime plant opera-
tion, particulate may also result from drilling and blasting. Emission
factors for some of these operations are presented in Sections 8.19 and 11.2
of this document.
Controlled and uncontrolled emission factors and particle size data for
lime manufacturing are given in Tables 8.15-1 through 8.15-3. The size dis-
tributions of particulate emissions from controlled and uncontrolled rotary
kilns and uncontrolled product loading operations are shown in Figures
8.15-2 and 8.15-3.
8.15-4
EMISSION FACTORS
10/86
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Mineral Products Industry
8115-5
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18.19.2 CRUSHED STONE PROCESSING ', .
8.19.2.1 Process Description! '
i
Major rock types processed by the rock and crushed stone industry include
limestone, dolomite, granite, traprock, sandstone, quartz and quartzite. Minor
types include .calcareous marl, marble, shell and slate.! Industry classifica-
^ions vary considerably and, in many cases, do not reflect actual geological
Definitions.
i
[ Rock and crushed stone products generally are loosened by drilling and
blasting, then are loaded by power shovel or front end loader and transported
by heavy earth moving equipment. Techniques used for extraction vary with the
nature and location of the deposit. Further processing may include crushing,
'screening, size classification, material handling, and storage operations. All
pf these processes can be significant sources of dust emissions if uncontrolled.
Some processing operations also include washing, depending on rock type and
desired product.
! Quarried stone normally is delivered to the processing plant by truck and
is dumped into a hoppered feeder, usually a vibrating grizzly type, or onto
screens, as illustrated in Figure 8.19.2-1. These screens separate or scalp
large boulders from finer rocks that do not require primary crushing, thus
reducing the load to the primary crusher. Jaw, or gyratory, crushers are
usually used for initial reduction. The crusher product, normally 7.5 to 30
centimeters (3 to 12 inches) in diameter, and the grizzly throughs (undersize
material) are discharged onto a belt conveyor and usually are transported either
to secondary screens and crushers or to a surge pile for temporary storage.
! Further screening generally separates the process flow into either two
pr three fractions (oversize, undersize and throughs) ahead of the secondary
crusher. The oversize is discharged to the secondary crusher for further
reduction, and the undersize usually .bypasses the secondary crusher. The
fchroughs sometimes are separated, because they contain unwanted fines, and are
stockpiled as crusher run material. Gyratory crushers or cone crushers are
commonly used for secondary crushing, althpugh impact crushers are sometimes
found.
! , ''''':'
( The product of the secondary crushing stage, usually 2.5 centimeters (1
inch) diameter or less, is transported to secondary screens for further sizing.
Oversize material is sent back for recrushing. Depending on rock type and
desired product, tertiary crushing or grinding may be-necessary, usually using
cone crushers or hammermills, (Rod mills, ball mills and hammer mills normally
are used in milling operations, which are not considered a part of the construc-
tion aggregate industry.) The product from tertiary crushing may be conveyed
j:o a classifier, such as a dry vibrating screen system, or to an air separator.
Any oversize is returned to the tertiary crusher for further reduction. At this
point, end products of the desired grade are conveyed or trucked directly to
finished product bins or to open area stockpiles.
J9/88 Mineral Products Industry 8.19.2-1
-------
FIGURE 8.19.2-1. Typical stone processing plant.
8.19.2-2
EMISSION FACTORS
9/88
-------
, In certain cases, stone washing is required to meet particular end product
specifications or demands, as with concrete aggregate processing. Crushed and
broken stone normally are not milled but are screened and shipped to the con-
sumer after secondary or tertiary crushing.
8.19.2.2 Emissions And Controls1"3
Dust emissions occur from many operations in stone quarrying and pro-
cessing. A substantial portion of these emissions consists of heavy particles
that may settle out within the plant. As in other operations, crushed stone
emission sources may be categorized as either process sources or fugitive dust
sources. Process sources include those for which emissions are amenable to
capture and subsequent control. Fugitive dust sources generally involve the
reentrainment of settled dust by wind or machine movement,I Factors affecting
emissions from either source category include the type, quantity and surface
moisture content of the stone processed; the type of equipment and operating
practices employed; and topographical and climatic factors.
1 ' ' !
I Of geographic and seasonal factors, the primary variables affecting uncon-
trolled particulate emissions are wind and material moisture content. Wind
parameters vary with geographical location, season and weather. It can be
expected that the level of emissions from unenclosed sources (principally fugi-
tive dust sources) will be greater during periods of high winds. The material
moisture content also varies with geographic location, season and weather.
Therefore, the levels of uncontrolled emissions from both process emission
sources and fugitive dust sources generally will be greater in arid regions
of the country than in temperate ones, and greater during',the summer months
because of a higher evaporation rate. ,
, The moistur.e content of the material processed can have a substantial
effect on uncontrolled emissions. This is especially evident during mining,
initial material handling, and initial plant process operations such as primary
crushing. Surface wetness causes fine particles to agglomerate on, or to adhere
toi the faces of larger stones, with a resulting dust suppression effect. How-
ever, as new fine particles are created by crushing and attrition, and as the
moisture content is reduced by evaporation, this suppressive effect diminishes
and may disappear. Depending on, the geographic and climatic conditions, the
moisture content of mined rock may range from nearly zero (to several percent.
Since moisture content is usually expressed on a basis of overall weight per-
cent, the actual moisture amount per unit area will vary with the size of. the
rock being handled. On a constant mass fraction basis, the per unit area mois-
ture content varies inversely with the diameter of the rock. Therefore, the
suppressive effect of the moisture depends on both the absolute mass water con-
tent and the.size of the rock product. Typically, a wet material will contain
1.5 to 4 percent water or more.
There are a large number of material, equipment and operating factors
which can influence emissions from crushing. These include: (1) rock type,
(2) feed size and distribution, (3) moisture content, (4) throughput rate, (5)
crusher type, (6) size reduction ratio, and (7) fines content. Insufficient
data are available to present a matrix of rock crushing emission factors
detailing the above classifications and variables. Data available from which
to .prepare emission factors also vary considerably, for both extractive testing
and plume profiling. Emission factors from extractive testing are generally
9/88 Mineral Products Industry 8.19.2-3
-------
higher than those based upon plume profiling tests, but they have a greater
degree of reliability. Some test data for primary crushing indicate higher
emissions than from secondary crushing, although factors affecting emission
rates and visual observations suggest that the secondary crushing emission
factor, on a throughput basis, should be higher. Table 8.19.2-1 shows single
factors for either primary or secondary crushing reflecting a combined data
base. An emission factor for tertiary crushing is given, but it is based on
extremely limited data. All factors are rated low because of the limited and
highly variable data base.
TABLE 8.19.2-1.
UNCONTROLLED PARTICULATE EMISSION FACTORS
FOR CRUSHING OPERATIONS3
Type of crushing"
Primary or secondary
Dry material
Wet materialc
Tertiary dry material*1
Particulate
< 30 urn
kg/Mg (Ib/ton)
0.14 (0.28)
0.009 (0.018)
0.93 (1.85)
< 10 urn
kg/Mg (Ib/ton)
0.0085 (0.017)
-
-
Emission
Factor
Rating
D
D
E
aBased on actual feed rate of raw material entering the particular operation.
Emissions will vary by rock type, but data available are insufficient to
characterize these phenomena. Dash = no data.
^References 4-5. Typical control efficiencies for cyclone, 70 - 80%;
fabric filter, 99%; wet spray systems, 70 - 90%.
References 5-6. Refers to crushing of rock either naturally wet or
moistened to 1.5 - 4 weight % with wet suppression techniques.
^Range of values used to calculate emission factor is 0.0008 - 1.38 kg/Mg.
Emission factor estimates for stone quarry blasting operations are not
presented here because of the sparsity and unreliability of available test
data. While a procedure for estimating blasting emissions is presented in
Section 8.24, Western Surface Coal Mines, that procedure should not be applied
to stone quarries because of dissimilarities in blasting techniques, material
blasted and size of blast areas.
There are no screening emission factors presented in this. Section. How-
ever, the screening emission factors given in Section 8.19.1, Sand and Gravel
Processing, should be similar to those expected from screening crushed rock.
Milling of fines is also not included, in this Section as this operation is
normally associated with non construction aggregate end uses and will be covered
elsewhere in the future when information is adequate.
Open dust source (fugitive dust) emission factors for stone quarrying and
processing are presented in Table 8.19.2-2. These factors have been determined
8.19.2-4
EMISSION FACTORS
9/88
-------
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^Expressed as g/Mg
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cReference 2.
Reference 3.
Industry
CO
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8.19.2-5
-------
through tests at various quarries and processing plants.6~? The single valued
open dust emission factors given in Table 8.19.2-2 may be used when no other
information exists. Empirically derived emission factor equations presented
in Section 11.2 of this document are preferred and should be used when possible.
Because these predictive equations allow the adjustment of emission factors for
specific source conditions, these equations should be used instead of those in
Table 8.19.2-2, whenever emission estimates applicable to specific stone quarry-
ing and processing facility sources are needed. Chapter 11.2 provides measured
properties of crushed limestone, as required for use in the predictive emission
factor equations.
References for Section 8.19.2
1. Air Pollution Control Techniques for Nonmetallic Minerals Industry,
EPA-450/3-82-014, U. S. Environmental Protection Agency, Research
Triangle Park, NC, August 1982.
2. P. K. Chalekode, et al., Emissions from the Crushed Granite Industry;
State of the Art, EPA-600/2-78-021, U. S. Environmental Protection
Agency, Washington, DC, February 1978. .
3. T. R. Blackwood, et al., Source Assessment; Crushed Stone, EPA-600/2-78-
004L, U. S. -Environmental Protection Agency, Washington, DC, May 1978.
4. F. Record and W. T. Harnett, Particulate Emission Factors for the
Construction Aggregate Industry, Draft Report, GCA-TR-CH-83-02, EPA
Contract No. 68-02-3510, GCA Corporation, Chapel Hill, NC, February 1983.
5. Review Emission Data Base and Develop Emission Factors for the Con-
struction Aggregate Industry, Engineering-Science, Inc., Arcadia, CA,
v September 1984.
6. C. Cowherd, Jr., et al., Development of Emission Factors for Fugitive Dust
Sources, EPA-450/3-74-037, U. S. Environmental Protection Agency, Research
Triangle Park, NC, June 1974.
7. R. Bohn, et al., Fugitive Emissions from Integrated Iron and Steel Plants,
EPA-600/2-78-050, U. S. Environmental Protection Agency, Washington, DC,
March 1978.
8.19.2-6
EMISSION FACTORS
9/88
-------
8.24 WESTERN SURFACE COAL MINING
8.24.1 General1
» . are 12 raaJ°r coal fields in the western states (excluding the
Pacific Coast and Alaskan fields), as shown in Figure 8,24-1. Together
they account for more than 64 percent of the surface minable coal reserves
COAL TYPE
LIGNITE
SUBBITUHINOUSEZ3
BITUMINOUS
1
2
3
4
5
6
7
3
9
10
11
12
Coal field
Fort Union
Powder River
North Central
Bighorn Basin
Wind River
Hams Fork
Uinta
Southwestern Utah
San Juan River
Raton Mesa
Denver
Green River
Strippable reserves
(JO6 tons)
23,529
56,727
All underground.
All underground
3
1,000
308
224
2,318
All underground
All underground
2,120
9/88
Figure 8.24-1. Coal fields of the western 13.S.3
Mineral Products Industry
8.24-1
-------
in the United States.2 The 12 coal fields have varying characteristics
which may influence fugitive dust emission rates from mining operations,
including overburden and coal seam thicknesses and structure, mining equip-
ment, operating procedures, terrain, vegetation, precipitation and surface
moisture, wind speeds and temperatures. The operations at a typical west-
ern surface mine are shown in Figure 8.24-2. All operations that involve
movement of soil, coal, or equipment, or exposure of credible surfaces,
generate some amount of fugitive dust.
The initial operation is removal of topsoil and subsoil with large
scrapers. The topsoil is carried by the scrapers to cover a previously
mined and regraded area as part of the reclamation process or is placed in
temporary stockpiles. The exposed overburden, the earth which is between
the topsoil and the coal seam, is leveled, drilled and blasted. Then the
overburden material is removed down to the coal seam, usually by a dragline
or a shovel and truck operation. It is placed in the adjacent mined cut,
forming a spoils pile. The uncovered coal seajn is then drilled and
blasted. A shovel or front end loader loads the broken coal into haul
trucks, and it is taken out of the pit along graded haul roads to the tip-
ple, or truck dump. Raw coal sometimes may be dumped onto a temporary
storage pile and later rehandled by a front end loader or bulldozer.
At the tipple, the coal is dumped into a hopper that feeds the primary
crusher, then is conveyed through additional coal preparation equipment
such as secondary crushers and screens to the storage area. If the mine
has open storage piles, the crushed coal passes through a coal stacker onto
the pile. The piles, usually worked by bulldozers, are subject to wind
erosion. From the storage area, the coal is conveyed to a train loading
facility and is put into rail cars. At a captive mine, coal will go from
the storage pile to the power plant.
During mine reclamation, which proceeds continuously throughout the
life of the mine, overburden spoils piles are smoothed and contoured by
bulldozers. Topsoil is placed on the graded spoils, and the land is pre-
pared for revegetation by furrowing, mulching, etc. From the time an area
is disturbed until the new vegetation emerges, all disturbed areas are sub-
ject to wind erosion.
8.24.2 Emissions ,
Predictive emission factor equations for open dust sources at western
surface coal mines are presented in Tables 8.24-1 and 8.24-2. Each equa-
tion is for a single dust generating activity, such as vehicle traffic on
unpaved roads. The predictive equation explains much of the observed vari-
ance in emission factors by relating emissions to three sets of source pa-
rameters: 1) measures of source activity or energy expended (e.g., speed
and weight of a vehicle traveling on an unpaved road); 2) properties of the
material being disturbed (e.g., suspendable fines in the surface material
of an unpaved road); and 3) climate (in this case, mean wind speed).
The equations may be used to estimate participate emissions generated
per unit of source extent (e.g., vehicle distance traveled or mass of mate-
rial transferred).
8.24-2 EMISSION FACTORS 9/88
-------
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EMISSION FACTORS
9/88
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9/8J8
Mineral Products Industry
8.24-5
-------
The equations were developed through field sampling of various western surface
mine types and are thus applicable to any of the surface coal mines located in
the western United States.
In Tables 8.24-1 and 8.24-2, the assigned quality ratings apply within
the ranges of source conditions that were tested in developing the equations,
given in Table 8.24-3. However, the equations are derated one letter value
(e. g., A to B) if applied to eastern surface coal mines.
TABLE 8.24-3.
TYPICAL VALUES FOR CORRECTION FACTORS APPLICABLE TO THE
PREDICTIVE EMISSION FACTOR EQUATIONS3
Number
Source Correction of test
factor samples
Coal loading
Bulldozers
Coal
Overburden
Dragline
Scraper
Grader
Light /medium
duty vehicle
Haul truck
Moisture
Moisture
Silt
Moisture
Silt
Drop distance
11 11
Moisture
Silt
Weight
it
Speed
i
Moisture
Wheels
Silt loading
it tt
7
3
3
8
8
19
7
10
15
7
7
29
26
Range Geometric
mean
6.6 -
4.0 -
6.0 -
2.2 -
3.8 -
1.5 -
. 5 -
0.2 -
7.2 -
33 -
36 -
8.0 -
5.0 -
0.9 -
6.1 -
3.8 -
34 -
38
22.0
11.3
16.8
15.1
30
100
16.3
25.2
64
70
19.0
11.8
1.7
10.0
254
2270
17.8
10.4
8.6
7.$
6.9
8.6
28.1
3.2
16.4
48.8
53.8
11.4
7.1
1.2
8.1
40.8
364
Units
%
%
%
%
m
ft
%
%
Mg
ton
kph
mph
%
number
g/m2
Ib/ac
aReference !
In using the equations to estimate emissions from sources found in a
specific western surface mine, it is necessary that reliable values for
correction parameters be determined for the specific sources of interest,
if the assigned quality ranges of the equations are to be applicable.
For example, actual silt content of coal or overburden measured at a facility
8.24-6
EMISSION FACTORS
9/88
-------
should be used instead of estimated values. In thevevent that site spe-
cific values for correction parameters cannot be obtained, the appropriate
geometric mean values from Table 8.24-3 may be used, but the assigned qual-
ity rating of each emission factor equation is reduced by one level (e.g.,
A to B).
Emission factors for open dust sources not covered in Table 8.24-3 are.
in1Table 8.24-4. These factors were determined through source testing at
various western coal mines.
The factors in Table 8.24-4 for mine locations I through V were devel-
oped for specific geographical areas. Tables 8.24-5 and 8.24-6 present
characteristics of each of these mines (areas). A "mine specific" emission
factor should be used only if the characteristics of the mine for which an
emissions estimate is needed are very similar to those of the mine for
which the emission factor was developed. The other (noaspecific) emission
factors were developed at a variety of mine types and thus are applicable
to any western surface coal mine.
As an alternative to the single valued emission factors given in Table
8.24-4 for train or truck loading and for truck or scraper unloading, two
empirically derived emission factor equations are preseiated in Section
11J2.3 of this document. Each equation was developed for a source opera-
tion (i.e., batch drop and continuous drop, respectively), comprising a
single dust generating mechanism which crosses industry lines.
Because the predictive equations allow emission factor adjustment to
specific source conditions, the equations should be used in place of the
factors in Table 8.24-4 for the sources identified above,,, if emission esti-
mates for a specific western surface coal mine are needed. However, the
generally higher quality ratings assigned to the equations are applicable
only if 1) reliable values of correction parameters hav« been determined
for the specific sources of interest and 2) the correction parameter values
lie within the ranges tested in developing the equations. Table 8.24-3
lists measured properties of aggregate materials which can be used to esti-
mate correction parameter values for the predictive emission factor equa-
tions in Chapter 11, in the event that site specific valiies are not avail-
able. Use of mean correction parameter values from Table 8.24-3 reduces
the quality ratings of the emission factor equations in Chapter 11 by one
level.
9/88 Mineral Products Industry 8.24-7
-------
TABLE 8.24-4.
UNCONTROLLED PARTICIPATE EMISSION FACTORS FOR
OPEN DUST SOURCES AT WESTERN SURFACE COAL MINES
Source
Drilling
Topsoil removal by
scraper
Overburden
replacement
Truck loading by
power shovel
(batch drop)
Train loading (batch c
or continuous drop)
Bottom dump truck
unloading
(batch drop)
End dump truck
unloading
* (batch drop)
Scraper unloading
(batch drop)
Wind erosion of
exposed areas
Material Mine
location
Overburden
Coal
Topsoil
Overburden
Overburden
, Coal
Overburden
,
Coal
Coal
Topsoil
Seeded land,
, stripped over-
burden, graded
overburden
Any
V
Any
IV
Any
V
Any
III
-V
IV
III
11
I
Any
V
IV
Any
TSP
emission
factorb
1.3
0.59
0.22
0.10
0.058
0.029
0.44
0.22
0.012
0.0060
0.037
0.018
0.028
0.014
0.0002
0.0001
0.002
0.001
0.027
0.014
0.005
0.002
0.020
0.010
0.014
0.0070
0.066
0.033
0.007
0.004
0.04
0.02
0.38
0.85
Emission
Units Factor
Rating
Ib/hole
kg/hole
Ib/hole
kg/hole
Ib/T
kg/Mg
Ib/T
kg/Mg
Ib/T
kg/Mg -
Ib/T
kg/Mg
Ib/T
kg/Mg
Ib/T
kg/Mg
Ib/T
kg/T
Ib/T
k«/Mg
Ib/T
kg/Mg
Ib/T
kg/Mg
Ib/T
kg/Mg
Ib/T
kg/Mg
Ib/T
kg/Mg
Ib/T
kg/Mg
I
MR
(hectareJCyr)
B
B
E
E
E
I
D
D
C
C
C
C
D
D
D
0
E
E
E
E
E
E
E
E
D
D
D
D
.E
E
C
C
C
c
1 Ronan numerals I through V refer to specific mine locations for which the
corresponding emission factors were developed (Reference 4). Tables 8.24-4
and 8.24-5 present characteristics of each of these nines. See text, for
correct use of these "nine specific" emission factors. The other factors
(froa Reference 5 except for overburden drilling from Reference 1) can be
. applied to any western surface coal mine.
° Total suspended particulate (TSP) denotes what is measured by a standard high
voluae sanpler (see Section 11.2).
Predictive emission factor equations, which generally provide nore Accurate
estimates of emissions, are presented in Chapter 11.
8.24-8
EMISSION FACTORS
9/88
-------
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eu
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0 - <=>
o r*» in in *ff o
co en *« »^ CM ri
§in
m
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CM -a- o\ in CM in
n
Overburden thickness
Overburden density
Coal seam thicknesses
Parting thicknesses
Spoils bulking factor
Active pit depth
o
JS
D,
R
U
oc
- < re
4^ ikJ
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n
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Moisture
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Heat content
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- CM CO CM CO 1-1
oo o
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i-i co in - i n
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U Lf hi U b U
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Total disturbed land
Active pit
Spoils
Reclaimed
Barren land
Associated disturbance!
g
o
H
rt
U C.
R tt
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en '
0 .
g
CO .
a
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,
2
<
|
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e
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en co i i
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Frequency, overburden
Area blasted, coal
Area blasted, overburd
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-------
References for Section 8.24 '
I - .
'1.1 K. Axetell and C. Cowherd, Improved Emission Factors for Fugitive Dust
| from Western Surface Coal Mining Sources, 2 Volumes, EPA Contract No.
I 68-03-2924, U. S. Environmental Protection Agency, Cincinnati, OH,
July 1981.
2.i Reserve Base of U. S. Coals by Sulfur Content: Part 2, The Western
States, IC8693, Bureau of Mines, U. S. Department of the Interior,
Washington, DC, 1975. j, .
3. Bituminous Coal and Lignite Production and Mine Operations - 1978,
DOE/EIA-0118(78), U. S. Department of Energy, Washington, DC, June
1980. i
i '
4.! K. Axetell, Survey of Fugitive Dust from Coal Mines', EPA-908/1-78-003,
U. S. Environmental Protection Agency, Denver, CO, February 1978.
5. D. L. Shearer, et al., Coal Mining Emission Factor Development and
Modeling Study, Amax Coal Company,, Carter Mining Company, Sunoco
Energy Development Company, Mobil Oil Corporation, and Atlantic
Richfield Company, Denver, CO, July 1981.
9/88
Mineral Products Industry
8.24-11
-------
-------
CHAPTER 11. MISCELLANEOUS SOURCES
; This chapter contains emission factor information on those source cate-
gories that differ substantially from, and hence cannot be grouped with, the
other "stationary" sources discussed in this publication; These miscellaneous
emitters, both natural and raanmade, are almost exclusively area sources, with
their pollutant generating process(es) dispersed over large land areas. Another
characteristic of these sources is the inapplicability, In most cases, of con-
ventional control methods, such as wet/dry equipment, fuel switching, process
changes, etc. Instead, control of these emissions, where possible at all, may
include such techniques as modification of agricultural burning practices,
paving with asphalt or concrete, or stabiliation of dirt roads. Finally,
miscellaneous sources generally emit pollutants intermittently, when compared
tb most stationary point sources. For example, a wildfire may emit large
quantities of particulate and carbon monoxide for several hours or even days.
But, when measured against a continuous emitter, such as a sulfuric acid plant,
over a long period of time, its emissions may seem relatively minor. Effects
on air quality may also be of relatively short duration.
;9/88
Miscellaneous Sources
11-1
-------
-------
1-11.1 Wildfires And Prescribed Burning
j
11.1.1 General1
i , . .-
A wildfire is a large scale natural combustion process that consumes
various ages, size and types of flora growing outdoors in a geographical area.
I Consequently, wildfires are potential sources of large amounts of air pollut-
!ants that should be considered when trying to relate emissions to air quality.
i '
The size and intensity, even the occurrence, of a wildfire depend
I directly on such variables as meteorological conditions, the species of vege-
:tation involved and their moisture content, and the weight of consumable fuel
iper acre (available fuel loading). Once a fire begins,, the dry combustible
imaterial is consumed first. If the energy release is large and of sufficient
iduration, the drying of green, live material occurs, with subsequent burning
; of this material as well. Under proper environmental and fuel conditions,
(this process may initiate a chain reaction that results! in a widespread
(conflagration.
The complete combustion of wildland fuels (forests, grasslands, wetlands)
irequire a heat flux (temperature gradient), adequate oxygen supply, and
[sufficient burning time. The size and quantity of wildland fuels, meteo-
irological conditions, and topograhic features interact to modify the burning
'Behavior as the fire spreads, and the wildfire will attain different degrees
.of combustion efficiency during its lifetime.
'
The importance of both fuel type and fuel loading on the fire process
jean not be overemphasized. To meet the pressing need for this kind of infor-
imation, the U. S. Forest Service is developing a model of a nationwide fuel
(identification system that will provide estimates of fuel loading by size
I class. Further, the environmental parameters of wind, slope and expected
moisture changes have been superimposed on this fuel model and incorporated
(into a National Fire Danger Rating System (NFDRS). This system considers
'five classes of fuel, the components of which are selected on the basis of
'combustibility, response of dead fuels to moisture, -and whether the living
fuels are herbaceous (grasses, brush) or woody (trees, shrubs).
1 Most fuel loading figures are based on values for "available fuel," that
is, combustible material that will be consumed in a wildfire under specific
weather conditions. Available fuel values must not be confused with corres-
ponding values for either "total fuel" (all the combustible material that
iwould burn under the most severe weather and burning conditions) o.r "potential
jfuel" (the larger woody material that remains even after an extremely high
(intensity wildfire). It must be emphasized, however, that the various methods
;of. fuel identification are of value only when they are related to the existing
[fuel quantity, the quantity consumed by the fire, and the geographic area and
conditions under which the fire occurs. j
i " . '
i For the sake of conformity and convenience, fuel loadings are estimated
;for the vegetation in the U. S. Forest Service Regions are presented in
Table 11.1-1. Figure 11.1-1 illustrates these areas and regions.
9/88 Miscellaneous Sources 11.1-1
-------
TABLE 11.1-1. SUMMARY OF ESTIMATED FUEL CONSUMED BY WILDFIRES*
National region*5
Rocky Mountain
Region 1:
Region 2:
Region 3:
Region 4:
Northern
Rocky Mountain
Southwestern
Intermountain
Pacific
Region 5:
Region 6:
Region 10:
California
Pacific Northwest
Alaska
Coastal
Interior
Southern
Region 8:
Southern
Eastern
North central
Region 9:
Conifers
Hardwoods
Estimated average fuel loading
Mg/hectare
83
135
67
22
40
43
40
135
36
135
25
20
20
25
25
22
27
ton/acre
37
60
30
10
8
19
18
60
16
60 r
11
9
9
11
11
10
12
aReference 1.
*>See Figure 11.1-1 for region boundaries
11.1-2
EMISSION FACTORS
9/88
-------
9/88
rH
g
H
Miscellaneous Sources
11.1-3
-------
11.1.2 Emissions And Controls1
It has been hypothesized, but not proven, that the nature and amounts of
air pollutant emissions are directly related to the intensity and direction
(relative to the wind) of the wildfire, and are indirectly related to the rate
at which the fire spreads. The factors that affect the rate of spread are
(1) weather (wind velocity, ambient temperature, relative humidity); (2) fuels
(fuel type, fuel bed array, moisture content, fuel size); and (3) topography
(slope and profile). However, logistical problems (such as size of the burning
area) and difficulties in safely situating personnel and equipment close to the
fire have prevented the collection of any reliable emissions data on actual
wildfires, so that it is not possible to verify or disprove the hypothesis.
Therefore, until such measurements are made, the only available information is
that obtained from burning experiments in the laboratory. These data, for both
emissions and emission factors, are contained in Table 11.1-2. It must be
emphasized that the factors presented here are adequate for laboratory scale
emissions estimates, but that substantial errors may result if they are used to
calculate actual wildfire emissions.
The emissions and emission factors displayed in Table 11.1-2 are calculated
using the following formulas:
(1)
(2)
Ei « F^A = PALA
where: Fj - Emission factor (mass of pollutant/unit area of
forest consumed) ...' . . '
Pi - Yield for pollutant "i" (mass of pollutant/unit
mass of forest fuel consumed)
s 8.5 kg/Mg (17 Ib/ton) for total particulate
- 70 kg/Mg (140 Ib/ton) for carbon monoxide
- 12 kg/Mg (24 Ib/ton) for total hydrocarbon (as CH4)
s 2 kg/Mg (4 Ib/ton) for nitrogen oxides (NOV)
- . A ,
s Negligible for sulfur oxides (SOV)
**
L = Fuel loading consumed (mass of forest fuel/unit land
area burned)
A " Land area burned
Ei =- Total emissions of pollutant "i" (mass pollutant)
For example, suppose that is is necessary to estimate the total particu-
late emissions from a 10,000 hectare wildfire in the Southern area (Region 8).
From Table 11.1-1, it is seen that the average fuel loading is 20 megagrams per
hectare (9 tons per acre). Further, the pollutant yield for particulates is
8.5 kilograms per megagram (17 Ib/ton). Therefore, the emissions are:
11.1-4
EMISSION FACTORS
9/88
-------
;9/88
s~*
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oo m o m o
r^ »o vo PO r-.
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co CM oo r~ *
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* sf
Pacific
California
(Region 5)
Alaska
(Region 10)
Pacific Northwest
(Region 6)
aneous Sources
00 00
CM CM
in in
in u-i
PI m
CO CO
so \o
m in
o\ er\
-H I
* '*
00 00
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CM CM
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00 CO
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0 0
00 00
Southern
Southern
M
-a- NO
r in
NO op
oo r~
r~ -^
CM -*
in vO
in -a-
m r~
CM PI
NO -a1
-< CM .
ON OO
PI ON
r~ in
ON ON
i CM
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«**
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O O
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00
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K
. 1*4
iH
t
3
1
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u
& ..
aConsunption 'data are
bExpr eased as methane
1.1-
-------
E - (8.5 kg/Mg of fuel) (20 Mg of fuel hectare) (10,000 hectares)
E - 1.700,000 kg - 1,700 Mg
The most effective method of controlling wildfire emissions is, of course,
to prevent the occurrence of wildfires, by various means at the land manager's
disposal. A frequently used technique for reducing wildfire occurrence is
"prescribed" or "hazard reduction" burning. This type of managed burn involves
combustion of litter and underbrush to prevent fuel buildup under controlled
conditions, thus reducing the danger"of a wildfire. Although some air pollution
is generated by this preventive burning, the net amount is believed to be a
relatively smaller quantity than that produced by wildfires.
11.1.3 Prescribed Burning1
Prescribed burning is a land treatment, used under controlled conditions,
to accomplish natural resource management objectives. It is one of several
land treatments, used individually or in combination, including chemical and
mechanical methods. Prescribed fires are conducted within the limits of a fire
plan and prescription which describes both the acceptable range of weather,
moisture, fuel and fire behavior parameters and the ignition method to achieve
the desired effects. Prescribed fire is a cost effective arid ecologically
sound tool for forest, range and wetland management. Its use reduces the
potential for destructive wildfires and thus maintains long term air quality.
Also, the practice removes logging residues, controls insects and disease,
improves wildlife habitat and forage production, increases water yield, main-
tains natural succession of plant communities, and reduces the need for pes-
ticides and herbicides. The major air pollutant concern is the smoke produced.
Smoke from prescribed fires is a complex mixture of carbon, tars, liquids
and different gases. This open combustion source produces particles of widely
ranging size, depending to some extent on the rate of energy release of the
fire. For example, total particulate and particulate less than 2.5 micrometers
mean mass cutpoint diameter are produced in different proportions, depending on
rates of heat release by the fire.2 This difference is greatest for the highest
intensity fires, and particle volume distribution is bimodal, with peaks near
0.3 micrometers and exceeding 10 micrometers.^ Particles over about 10 microns,
probably of ash and partially burned plant matter, are extrained by the turbu-
lent nature of high intensity fir.es.
Burning methods differ with fire objectives and with fuel and weather
conditions.^ For example, the various ignition techniques used to burn under
standing trees include 1) heading fire, a line of fire that runs with the wind;
2) backing fire, a line of fire that moves into the wind; 3) spot fires, which
burn from a number of fires ignited along a line or in a pattern; and 4) flank
fire, a line of fire that is lit into the wind, to spread laterally to the
direction of the wind. Methods of igniting the fires depend on forest manage-
ment objectives and the size of the area. Often, on areas of 50 or more acres,
helicopters with aerial ignition devices are used to light broadcast burns.
Broadcast fires may involve many lines of fire in a pattern that allows the
strips of fire to burn together over a sizeable area.
11.1-6 EMISSION FACTORS " 9/88
-------
i In discussing prescribed burning, the combustion process is divided into
preheating, flaming, glowing and smoldering phases. The different phases of
combustion greatly affect the amount of emissions produced.5~7 The preheating
nhase seldom releases significant quantities of material to the atmosphere.
Glowing combustion is usually associated with burning of large concentrations
of woody fuels such as logging residue piles. The smoldering combustion phase
is a very inefficient and incomplete combustion process that emits pollutants
at a much higher ratio to the quantity of fuel consumed than does the flaming
combustion of similar materials.
The amount of fuel consumed depends on the moisture! content of the fuel.8~9
For most fuel types, consumption during the smoldering phase is much greatest
when the fuel is driest. When lower layers of the fuel are moist, the fire
usually is extinguished rapidly.10
! The major pollutants from wildland burning are particulate, carbon monoxide
and volatile organics. Nitrogen oxides are emitted at rates of from 1 to 4
grams per kilogram burned, depending on combustion temperatures. Emissions of
sulfur oxides are negligible. ^~*
| Particulate emissions depend on the mix of combustion phase, the rate of
energy release, and the type of fuel consumed^ All of these elements must be
considered in selecting the appropriate emission factor for a given fire and
fuel situation. In some cases, models developed by the U. S. Forest Service
have been used to predict particulate emission factors s;nd source strength.^
These models address fire behavior, fuel chemistry, and ignition technique, and
they predict the mix of combustion products. There is insufficient knowledge
at this time to describe the effect, of fuel chemistry on emissions.
' | ' " ''- i '' '' :
; Table 11.1-3 presents emission factors from various pollutants, by fire
and fuel configuration, table 11.1-4 gives emission factors for prescribed
burning, by geographical area within the United States. Estimates of the
percent of total fuel consumed by region were compiled by polling experts
from the Forest Service. The emission factors are averaiges and can vary by
as much as 50 percent with fuel and fire conditions. To use these factors,
multiply the mass of fuel consumed per hectare by the emission factor for the
appropriate fuel type. The mass of fuel consumed by a fire is defined as the
available fuel. Local forestry officials often compile ^information on fuel
consumption for prescribed fires and have techniques for estimating fuel
consumption under local conditions. The Southern Forestry Smoke Management
Guidebook^ and the Prescribed Fire Smoke Management Guide^ should be consulted
when using these emission factors. ,, "
i . ' j- -;". ! ....... j '
' The regional emission factors in Table 11.1-4 should be used only for
general planning purposes. Regional averages are based on estimates of the
acreage and vegetation type burned and may not reflect prescribed burning
activities in a given state. Also, the regions identified are broadly defined,
and the mix of vegetation and acres burned within a givesn state may vary
considerably from the regional averages provided. Table 11.1-4 should not be
used to develop emission inventories and control strategies.
! To develop state emission inventories, the user is
tact that state's federal land management agencies and
tihat conduct prescribed burning to obtain the best information
Miscellaneous Sources
strongly urged to con-
state forestry agencies
on such activities,
11.1-7
-------
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-------
TABLE 11.1-4.
EMISSION FACTORS FOR PRESCRIBED BURNING
BY U. S. REGION
Regional
configuration and
fuel type3
Pacific Northwest
Logging slash
Piled slash
Douglas fir/
Western hemlock
Mixed conifer
Ponderosa pine
Hardwood
Underburning pine
Average for region
Pacific Southwest
Sagebrush
Chaparral
Pinyon/ Juniper
Underburlng pine
Grassland
Average for region
Southeast
Palme tto/gallberry
Underburning pine
Logging slash
Grassland
Other
Average for region
Rocky Mountain
Logging slash
Underburning pine
Grassland
Other
Average for region
North Central and Eastern
Logging slash
Grassland
Underburning pine
Other
Average for region
Percent
of fuelb
42
24
19
6
4
5
100
35
20
20
15
10
100
35
30
20
'10
5
100
50
20
20
10
100
50
30
10
10
100
Pollutant0
Particulate
(K/ks)
PM2.5
4
12
12
13
11
30
9.4
8
PM10
5
13
13
13
12
30
10.3
9
9
13
30
10
13.0
15
30
13
10
17
' 18.8
4
30
10
17
11.9
13
10
30
17
14
PM
6
17
17
20
18
35
13.3
15
15
17
35
10
17.8
16
35
20
10
17
21.9
6
35
10
17
13.7
17
10
35
17
16.5
CO
37
175
175
126
112
163
111.1
62
62
175
163
75
101.0
125
163
126
75
175
134
37
163
75
175
83.4
175
75
163
175
143.8
aRegional areas are generalized, e. g., the Pacific Northwest includes
Oregon, Washington and parts of Idaho and California. Fuesl types
generally reflect the ecosystems of a region, but users should seek
advice on fuel type mix for a given season of the year. An average
factor for Northern California could be more accurately described as
chaparral, 25%; underburning pine, 15%; sagebrush, 15%; grassland,
5%; mixed conifer, 25%; and Douglas fir/Western hemlock, 15%.
Dash = no data.
bBased on the judgment of forestry experts.
cAdapted from Table 11.1-3 for the dominant fuel types burned.
9/88
Miscellaneous Sources
11.1-9
-------
References for Section 11.1
1. Development Of Emission Factors For Estimating Atmospheric Emissions From
Forest Fires, EPA-450/3-73-009, U. S. Environmental Protection Agency,
Research Triangle Park, NC, October 1973.
2. D. E. Ward and C. C. Hardy, Advances In The Characterization And Control
Of Emissions From Prescribed Broadcast Fires Of Coniferous Species Logging
Slash On Clearcut Units, EPA DW12930110-01-3/DOE DE-A179-83BP12869, U. S.
Forest Service, Seattle, WA, January 1986.
3. L. F. Radke, e't al., Airborne Monitoring And Smoke Characterization Of
Prescribed Fires On Forest Lands In Western Washington and Oregon,
EPA-600/X-83-047, U. S. Environmental Protection Agency, Cincinnati, OH,
July 1983.
4. H. E. Mobley, et al., A Guide For Prescribed Fire In Southern Forests,
U. S. Forest Service, Atlanta, GA, 1973.
5. Southern Forestry Smoke Management Guidebook, SE-10, U. S. Forest Service,
Asheville, NC, 1976.
6. D. E. Ward and C. C. Hardy, "Advances In The Characterization And Control
Of Emissions From Prescribed Fires", Presented at the 77th Annual Meeting
of the Air Pollution Control Association, San Francisco, CA, June 1984.
7. C. C. Hardy and D. E. Ward, "Emission Factors For Particulate Matter By
Phase Of Combustion From Prescribed Burning", Presented at the Annual
Meeting of the Air Pollution Control Association Pacific Northwest
International Section, Eugene, OR, November 19-21, 1986.
8. D. V. Sandberg and R. D. Ottmar, "Slash Burning And Fuel Consumption In
The Douglas Fir Subregion", Presented at the 7th Conference On Fire And
Forest Meteorology, Fort Collins, CO, April 1983.
9. D. V. Sandberg, "Progress In Reducing Emissions From Prescribed Forest
Burning In Western Washington And Western Oregon", Presented at the Annual
Meeting of the Air Pollution Control Association Pacific Northwest
International Section, Eugene, OR, November 19-21, 1986.
10. R. D. Ottmar and D. V. Sandberg, "Estimating 1000-hour Fuel Moistures In
The Douglas Fir Subregion", Presented at the 7th Conference On Fire And
Forest Meteorology, Fort Collins, CO, April 25-28, 1983.
11. D. V. Sandberg, et al. , Effects Of Fire On Air - A State Of Knowledge
Review, WO-9, U. S. Forest Service, Washington, DC, 1978.
12. C. K. McMahon, "Characteristics Of Forest Fuels, Fires, And Emissions",
Presented at the 76th Annual Meeting of the Air Pollution Control
Association, Atlanta, GA, June 1983.
13. D. E. Ward, "Source Strength Modeling Of Particulate Matter Emissions From
Forest Fires", Presented at the 76th Annual Meeting of the Air Pollution
Control Association, Atlanta, GA, June 1983.
11.1-10 EMISSION FACTORS 9/88
-------
14.
15.
i
D. E. Ward, et al. , "Particulate Source Strength Determination For Low-
intensity Prescribed Fires", Presented at the Agricultural Air Pollutants
Specialty Conference, Air Pollution Control Association. Memphis, TN.
March 18-19, 1974. : j
Prescribed Fire Smoke Management Guide. 420-1, BIFC-BLM Warehouse, 3905
Vista Avenue, Boise, ID, February 1985.
9/88
Miscellaneous Sources
11.1-11
-------
-------
11.2.1 UNPAVED ROADS
11.2.1.1 General
: Dust plumes trailing behind vehicles traveling on unpaved roads are a
familiar sight in rural areas of the United States. When a vehicle travels an
unpaved road, the force of the wheels on the road surface causes pulverization
of surface material. Particles are lifted and dropped from the rolling wheels,
and the road surface is exposed to strong air currents in turbulent shear with
the .surface. The turbulent wake behind the vehicle continues to act on the
road surface after the vehicle has passed.
i " f
l'l.2.1..2 Emissions Calculation And Correction Parameters
| The quantity of dust emissions from a given segment of unpaved road varies
linearly with the volume of traffic. Also, field investigations have shown
that emissions depend on correction parameters (average vehicle speed, average
vehicle weight, average number of wheels per vehicle, road surface texture and
road surface moisture) that characterize the condition of a particular road and
the associated vehicle traffic.1~^
; Dust emissions from unpaved roads have been found to vary in direct
proportion to the fraction of silt (particles smaller than 75 micrometers in
diameter) in the road surface materials.1 The silt fraction is determined by
measuring the proportion of loose dry surface dust that passes a 200 mesh
sjcreen, using the ASTM-C-136 method. Table 11.2.1-1 summarizes measured silt
values for industrial and rural unpaved roads.
| . , :
The silt content of a rural dirt road will vary with location, and it
should be measured. As a conservative approximation, the silt content of the
parent soil in the area can be used. However, tests show that road silt con-
tjent is normally lower than in the surrounding parent soil, because the fines
ajre continually removed by the vehicle traffic, leaving a higher percentage
of coarse particles.
| ' ' . . . - i
; Unpaved roads have a hard, generally nonporous surface that usually dries
quickly after a rainfall. The temporary reduction in emissions caused by
precipitation may be accounted for by not considering emissions on "wet" days
(more than 0.254 millimeters [0.01 inches] of precipitation).
: The following empirical expression may be used to estimate the quantity of
size specific particulate emissions from an unpaved road, per vehicle kilometer
traveled (VKT) or vehicle mile traveled (VMT), with a rating of A:
(kg/VKT)
: E=k(5.9) [ _ ~\ (ib/VMT)
! \12J \30/ V3/ W \36V
9/88 Miscellaneous Sources i 11.2.1-1
-------
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11.2.1-2
EMISSION FACTORS
9/88
-------
where: E = emission factor
k = particle size multiplier (dimensionless)
I s = silt content of road surface material (%)
S = mean vehicle speed, km/hr (mph)
| W = mean vehicle weight, Mg (ton)
[ w = mean number of wheels
, p = number of days with at least 0.254 mm
(0.01 in.) of precipitation per year j
The particle size multiplier, k, in the equation varies with aerodynamic particle
size range as follows: : -
Aerodynamic Particle Size Multiplier For Equation
<30 uma
1.0
<30 urn
0.80
j<15 urn
0.50
<10 um <5um
0.36 0.20
^2.5 um
0.095
The number of wet days per year, p, for the geographical area of interest
shpuld be determined from local climatic data. Figure 11.2.1-1 gives the
geographical distribution of the mean annual number of wet days per year in the
United States. h
! The equation retains the assigned quality rating, if applied within the
ranges of source conditions that were tested in developing the equation, as
follows:
i
Ranges Of Source Conditions For Equation
Road silt
content
(wgt. %)
4.3 - 20
Mean vehicle weight
Mg
2.7 - 142
ton
3 - 157
.. .
Mean vehicle speed
km/hr
21 - 64
mph r
13 - 40
!
mean no.
of wheels
4-13
Aljso, to retain the quality rating of the equation when addressing a specific
unpaved road, it is necessary that reliable correction parameter values be
determined for the road in question. The field and laboratory procedures for
determining road surface silt content are given in Referenced. In the event
thjat site specific values for correction parameters cannot: be. obtained, the
appropriate mean values from Table 11.2.1-1 may be used, but the quality rating
ofithe equation is reduced to B. j
i
The equation was developed for calculating annual average emissions, and
thus, is to be multiplied by annual vehicle distance traveled (VDT). Annual
average values for each of the correction parameters are to be substituted for
the equation. Worst case emissions, corresponding to dry road conditions, may
be; calculated by setting p = 0 in the equation (equivalent: to dropping the last
9/88
Miscellaneous Sources
11.2.1-3
-------
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11.2.1-4
EMISSION FACTORS
9/88
-------
term from the equation). A separate set of nonclimatic correction parameters
andi a higher than normal VDT value may also be justified for the worst case
average period (usually 24 hours). Similarly, in using the equation to calcu-
late emissions for a 91 day season of the year, replace the term (365-p)/365
with the term (91-p)/91, and set p equal to the number of wet days in the 91 day
period. Also, use appropriate seasonal values for the nonclimatic correction
par&meters and for VDT. I
11.2.1.3 Controls
_ Common control techniques for unpaved roads are paving;, surface treating
with penetration chemicals, working into the roadbed of stabilization chemicals
watering, and traffic control regulations. Chemical stabilizers work either by'
binding the surface material or by enhancing moisture retention. Paving as a
control technique, is often not economically practical. Surface chemical treat-
ment; and watering can be accomplished with moderate to low costs, but frequent
^treatments are required. Traffic controls, such as speed limits and traffic
volume restrictions, provide moderate emission reductions but may be difficult
to enforce. The control efficiency obtained by speed reduction can be calcu-
lated using the predictive emission factor equation given above.
i
_ ! The control efficiencies achievable by paving can be estimated by comparing
emission factors for unpaved and paved road conditions, relative to airborne
particle size range of interest. The predictive emission factor equation for
paved roads, given in Section 11.2.6, requires estimation of the silt loading
on the traveled portion of the paved surface, which in turn depends on whether
the pavement is periodically cleaned. Unless curbing is to be installed, the
effects of vehicle excursion onto shoulders (berms) also must be taken into
account in estimating control efficiency. i
The control efficiencies afforded by the periodic use of road stabilization
chemicals are much more difficult to estimate. The application parameters
which determine control efficiency include dilution ratio, application intensity
(.mass of diluted chemical per road area) and application frequency. Other
factors that affect the performance of chemical stabilizers include vehicle
characteristics (e. g., traffic volume, average weight) and road characteristics
(e. g., bearing strength).
Besides water, petroleum resin products have historically been the dust
suppressants most widely used on industrial unpaved roads. Figure 11.2 1-2
presents a method to estimate average control efficiencies associated with
petroleum resins applied to unpaved roads. Several items should be noted:
' 1. The term "ground inventory" represents the total volume (per
, unit area) of petroleum resin concentrate (not solution)
applied since the start of the dust control~sea'soiu^
2. Because petroleum resin products must be periodically reapplied
to unpaved roads, the use of a time-averaged control efficiency
value is appropriate. Figure 11.2,, 1-2 presents control effi-
ciency values averaged over two common application intervals,
! two weeks and one month. Other application intervals will
require interpolation.
.
9/88 Miscellaneous Sources i 11.2.1-5
-------
is
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iq
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3. Note that zero efficiency is assigned until the ground inventory
reaches 0.2 liters per square meter (0.05 gallons per square yard).
As an example of the use of Figure 11.2.1-2, suppose that the equation has
rrv, JfT*: estimaje an emlssion factor of 2-0 kilograms; per vehicle kilometer
traveled for particles equal to or less than 10 microns from a particular road.
Also, suppose that, starting on May 1, the road is treated with 1 liter per
square meter of a (1 part petroleum resin to 5 parts water) solution on the
first of each month until October. Then, the following average controlled
emission factors are found:
Period
May
June
July
August
September
aFrom Figur
inventory
Ground
Inventory
(L/m2)
0.17
0.33
0.50
0.67
0.83
e 11.2.1-2, < 10
is less than 0.2
Average Control
Efficiency3
f °/ \ '
\ fo j
0
62
68
74-
80
Average Controlled
Emission Factor
(kg/VKT)
2.0
0.76
0.64
0.52
0.40
urn. Zero efficiency assigned if ground
L/m2 (0.05 gal/yd2).
Newer dust suppressants have been successful in controlling emissions from
unpaved roads. Specific test results for those chemicals,, as well as 'for petro-
leum resins, are provided in References 14 through 16. P
References for Section 11.2.1
1, C. Cowherd, Jr. , et al., Development Of Emission Factors For Fugitive Dust
2i R. J. Dyck and J. J. Stukel, "Fugitive Dust Emissions From Trucks On
i Unpaved Roads , Environmental Science and Technology: ,10(10) : 1046-1048,
UCtODG3T 1976» i
I
3. R. 0. McCaldin and K. J. Heidel, "Particulate Emissions From Vehicle
Travel Over Unpaved Roads", Presented at the 71st Annual Meeting of the
Air Pollution Control Association, Houston, TX, June 1978.
4. 1 C. Cowherd, Jr., et al. . Iron And Steel Plant Open Dust Source
5.
" ' - - __~_ ~" "f ***«. **\*.i* i, IS\J\Ai. ^.c A **& -L L. J. \
Evaluation, EPA-600/2-79-013, U. S. Environmental Protection
Agency, Cincinnati, OH, May 1979.
'
Fugit.ive Emissions From Integrated Iron And Steel Plants.
, U. S. Environmental Protection Agency, Cincinnati, OH,
March 1978
9/88
Miscellaneous Sources
11.2.1-7
-------
6. R. Bohn, Evaluation Of Open Dust Sources In The Vicinity Of Buffalo, New
York, EPA Contract No. 68-02-2545, Midwest Research Institute, Kansas
City, MO, March 1979.
7. C. Cowherd, Jr., and T. Cuscino, Jr., Fugitive Emissions Evaluation,
MRI-4343-L, Midwest Research Institute, Kansas City, MO, February 1977.
8. T. Cuscino, Jr., et al., Taconite Mining Fugitive Emissions Study,
Minnesota Pollution Control Agency, Roseville, MN, June 1979.
9. K. Axetell and C. Cowherd, Jr., Improved Emission Factors For Fugitive
Dust From Western Surface Coal Mining Sources, 2 Volumes, EPA Contract
No. 68-03-2924, PEI, Inc., Kansas City, MO, July 1981.
10. T. Cuscino, Jr., et al., Iron And Steel Plant Open Source Fugitive Emis-
sion Control Evaluation, EPA-600/2-83-110, U. S. Environmental Protection
Agency, Cincinnati, OH, October 1983.
11. J. Patrick Reider, Size Specific Emission Factors For Uncontrolled Indus-
trial and Rural Roads, EPA Contract No. 68-02-3158, Midwest Research
Institute, Kansas City, MO, September 1983.
12. C. Cowherd, Jr., and P. Englehart, Size Specific Particulate Emission
Factors For Industrial And Rural Roads, EPA-600/7-85-038, U. S. Environ-
mental Protection Agency, Cincinnati, OH, September 1985.
13. .Climatic Atlas Of The United States, U. S. Department Of Commerce,
Washington, DC, June 1968."
14. G. E. Muleski, et al.. Extended Evaluation Of Unpaved Road Dust Suppres-
sants In The Iron And Steel Industry, EPA-600/2-84-027, U. S. Environmental
Protection Agency, Cincinnati, OH, February 1984.
15. C. Cowherd, Jr., and J. S. Kinsey, Identification. Assessment And Control
Of Fugitive Particulate Emissions, EPA-600/8-86-023, U. S. Environmental
Protection Agency, Cincinnati, OH, August 1986.
16. G. E. Muleski and C. Cowherd, Jr., Evaluation Of The Effectiveness Of
Chemical Dust Suppressants On Unpaved Roads, EPA-600/X-XX-XXX, U. S.
Environmental Protection Agency, Cincinnati, OH, November 1986.
11.2.1-8
EMISSION FACTORS
9/88
-------
11.2.3 AGGREGATE HANDLING AND STORAGE PILES |
11.2.3,1 General -[...'
! Inherent in operations that use minerals in aggregate form is the
maintenance of outdoor storage piles. Storage piles are usually left uncovered,
partially because of the need for frequent material transfer into or out of
storage. i
:
* i
| Dust emissions occur at several points in the storage cycle, such as
during material loading onto the pile, disturbances by strong wind currents,
and loadout from the pile. The movement of trucks and loading equipment in the
storage pile area is also a substantial source of dust.
11.2.3.2 Emissions And Correction Parameters
I The quantity of dust emissions from aggregate storage operations varies
with the volume of aggregate passing through the storage cycle. Also, emis-
sions depend on three parameters of the condition of a particular storage pile:
age of the pile, moisture content and proportion of aggregate fines.
1 ' ' ' '!"'
When freshly processed aggregate is loaded onto a storage pile, its
potential for dust emissions is at a maximum. Fines are easily disaggregated
and| released to the atmosphere upon exposure to air currents, either from aggre-
gate transfer itself or from high winds. As the aggregate weathers, however,
potential for dust emissions is greatly reduced. Moisture causes aggregation
and; cementation of fines to the surfaces of larger particles. Any significant
rainfall soaks the interior of the pile, and the drying process is very slow.
i
! Silt (particles equal to or less than 75 microns in diameter) content is
determined by measuring the portion of dry aggregate material that passes
through a 200 mesh screen, using ASTM-C-136 method. Table 11.2.3-1 summarizes
measured silt and moisture values for industrial aggregate materials.
11.2.3.3 Predictive Emission Factor Equations
! . i
I Total dust emissions from aggregate storage piles are contributions of
several distinct source activities within the storage cycle:
I 1. Loading of aggregate onto storage piles (batch oricontinuous drop
! operations).
Equipment traffic in storage area. . [ .
Wind erosion of pile surfaces and ground areas around piles.
Loadout of aggregate for shipment or for return to the process stream
(batch or continuous drop operations). j
2.
3.
4.
Adding aggregate material to a storage pile or removing it both usually
involve dropping the material onto a receiving surface. Truck dumping on the
pile or loading out from the pile to a truck with a front end loader are exam-
ples of batch drop operations. Adding material to the pile by a conveyor
stacker is an example of a continuous drop operation.
9/88
Miscellaneous Sources
11.2.3-1
-------
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td
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75
Material
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11.2.3-2
EMISSION FACTORS
9/8.8
-------
The quantity of particulate emissions generated by either type of drop
operation, per ton of material transferred, may be estimated, with a rating of
A,i using the following empirical expression2;
E = k(0.0016)
E = k(0.0032)
(kg/Mg)
(Ib/ton)
where: E = emission factor
: k = particle size multiplier (dimensionless)
U = mean wind speed, m/s (mph)
M = material moisture content (%)
i
The particle size multiplier, k, varies with aerodynamic particle diameter, as
shown in Table 11.2.3-2.
TABLE 11.2.3-2. AERODYNAMIC PARTICLE SIZE MULTIPLIER (k)
<30 um
0.74
(15 um
0.48
<10 um
0.35
<5
0.
um
20
<2.5 um
0.11
I The equation retains the assigned quality rating if applied within the
ranges of source conditions that were tested in developing the equation, as
given in Table 11.2.3-3. Note that silt content is included in Table 11.2.3-3,
even though silt content does not appear as a correction parameter in the equa-
tion. While it is reasonable to expect that silt content and emission factors
are; interrelated, no significant correlation between the two was found during
the! derivation of the equation, probably because most tests?: with high silt
contents were conducted under lower winds, and vice versa.i It is recommended
that estimates from the equation be reduced one quality rating level, if the
silt content used in a particular application falls outside the range given in '
Table 11.2.3-3.
9/8,8
Miscellaneous Sources
11.2.3-3
-------
TABLE 11.2.3-3. RANGES OF SOURCE CONDITIONS FOR EQUATION 1
Silt
Content
0.44 - 19
Moisture
Content
0.25 - 4.8
Wind Speed
(m/s) (mph)
0.6-6.7 1.3 - 15
Also, to retain the equation's quality rating when applied to a specific
facility, it is necessary that reliable correction parameters be determined for
the specific sources of interest. The field and laboratory procedures for
aggregate sampling are given in Reference 3. In the event that site specific
values for correction parameters cannot be obtained, the appropriate mean
values from Table 11.2.3-1 may be used, but, in that case, the quality rating
of the equation is reduced by one level.
For emissions from equipment traffic (trucks, front end loaders, dozers,
etc.) traveling between or on piles, it is recommended that the equations for
vehicle traffic on unpaved surfaces be used (see Section 11.2.1). For vehicle
travel between storage piles, the silt value(s) for the areas among the piles
(which may differ from the silt values for the stored materials) should be used.
Worst case emissions from storage pile areas occur under dry windy condi-
tions* Worst case emissions from materials handling operations may be calcu-
lated by substituting into the equation appropriate values for aggregate material
moisture content and for anticipated wind speeds during the worst case averaging
period, usually 24 hours. The treatment of dry conditions for vehicle traffic
(Section 11.2.1), centering on parameter p, follows the methodology described
in Section 11.2.1. Also, a separate set of nonclimatic correction parameters and
source extent values corresponding to higher than normal storage pile activity
may be justified for the worst case averaging period.
11.2.3.4 Controls
Watering and chemical wetting agents are the principal means for control
of aggregate storage pile emissions. Enclosure or covering of inactive piles
to reduce wind erosion can also reduce emissions. Watering is useful mainly to
reduce emissions from vehicle traffic in the storage pile area. Watering of
the storage piles themselves typically has only a very temporary slight effect
on total emissions. A much more effective technique is to apply chemical wet-
ting agents for better wetting of fines and longer retention of the moisture
film. Continuous chemical treatment of material loaded onto piles, coupled
with watering or treatment of roadways, can reduce total particulate emissions
from aggregate storage operations by up to 90 percent-9
References for Section 11.2.3
1. C. Cowherd, Jr., et al., Development Of Emission Factors For Fugitive Dust
Sources, EPA-450/3-74-037, U. S. Environmental Protection Agency, Research
Triangle Park, NC, June 1974.
11.2.3-4 EMISSION FACTORS 9/88
-------
2.
3.
4.
5.
6.
7.
8.
9.
R. Bohn, et al., Fugitive Emissions From Integrated Iron And Steel Plants.
EPA-600/2-78-050, U. S. Environmental Protection Agency, Cincinnati, OH
March 1978.
C. Cowherd, Jr., et al., Iron And Steel Plant Open Dust Source Fugitive
Emission Evaluation, EPA-600/2-79-103, U. S. Environmental Protection
Agency, Cincinnati, OH, May 1979.
R. Bohn, Evaluation Of Open Dust Sources In The Vicinity Of Buffalo.
New York, EPA Contract No. 68-02-2545, Midwest Research Institute, Kansas
City, MO, March 19799
C. Cowherd, Jr., and T. Cuscino, Jr., Fugitive Emissions Evaluation.
MRI-4343-L, Midwest Research Institute, Kansas City, MO, February 1977.
"* I '
T. Cuscino, et al.. Taconite Mining Fugitive Emissions Study. Minnesota
Pollution Control Agency, Roseville, MN, June 1979. |
K. Axetell and C. Cowherd, Jr., Improved Emission Factors For Fugitive
Dust From Western Surface Coal Mining Sources. 2 Volumes, EPA Contract
No. 68-03-2924, PEI, Inc., Kansas City, MO, July 1981.
_
E. T. Brookman, et al.. Determination of Fugitive Coal Dust Emissions From
Rotary Railcar Dumping. 1956-L81-00, TRC, Hartford, CT, May 1984.
G. A. Jutze, et -al,. Investigation Of Fugitive Dust ISources Emissions And
Control, EPA-450/3-74-036a, U. S. Environmental Protection Agency, Research
Triangle Park, NC, June 1974.
9/88
Miscellaneous Sources
11.2.3-5
-------
-------
11.2.6 INDUSTRIAL PAVED ROADS
11.2.6.1 General
I
I Various field studies have indicated that dust emissions from industrial
paved roads are a major component of atmospheric particulate matter in the
vicinity of industrial operations. Industrial traffic dust has been found to
consist primarily of mineral matter, mostly tracked or deposited onto the road-
way by vehicle traffic itself, when vehicles enter from an unpaved area or
travel on the shoulder of the road, or when material is spilled onto the paved
surface from open truck bodies.
!
11.2.6.2 Emissions And Correction Parameters^-~2
!
i The quantity of dust emissions from a given segment jof paved road varies
linearly with the volume of traffic. In addition, field investigations have
shown that emissions depend on correction parameters (road surface silt content,
surface dust loading and average vehicle weight) of a particular road and asso-
ciated vehicle traffic.
I Dust emissions from industrial paved roads have been found to vary in
direct proportion to the fraction of silt (particles equal to or less than 75
microns in diameter) in the road surface material. The silt fraction is deter-
mined by measuring the proportion of loose dry surface dust that passes a 200
mesh screen, using the ASTM-C-136 method. In addition, it has also been found
that emissions vary in direct proportion to the surface dust loading. The road
surface dust loading is that loose material which can be collected by broom
sweeping and vacuuming of the traveled portion of the paved road. Table 11.2.6-1
summarizes measured silt and loading values for industrial paved roads.
11.2.6.3 Predictive Emission Factor Equations
: The quantity of total suspended particulate emissions generated by vehicle
traffic on dry industrial paved roads, per vehicle kilometer traveled (VKT) or
vehicle mile traveled (VMT), may be estimated with a rating of B or D (see
below), using the following empirical expression^:
0.022 I
E - 0.022 I /
(kg/VKX)
(Ib/VMT)
(1)
where: E = emission factor
I = industrial augmentation factor (dimensionless) (see below)
I n = number of traffic lanes
I s = surface material silt content (%)
L = surface dust loading, kg/km (Ib/mile) (see below)
W = average vehicle weight, Mg (ton)
9/88
Miscellaneous Sources
11.2.6-1
-------
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11.2.6-2
EMISSION FACTORS
9/88
-------
; The industrial road augmentation factor (I) in Equation 1 takes into account
higher emissions from industrial roads than from urban roads. I = 7.0 for a
paved industrial roadway which traffic /enters f^oto unpaved areas. I = 3.5 for
'an industrial roadway; w^^^ of the vehicles
are forced to travel "temporarily ;wiJ:h^ shoulder. I = 1.0
for cases inv. which : tr-affic^r.^^ 1.0 and
7;0 which best represents conditiohs^fbf" pa^dVtoadl? at a
certain industrial
facility should be used for 1 in the equatiott; -.-.'.
I - / .. ..; . - ' .. ' .;.% -:<-.. ..** :?-,-<. V-' ;;;''.
The equation retains the quality rating of B if applied to vehicles
traveling entirely on paved surfaces (I = 1^.0) and if applied within the range
of source conditions that were tested in developing the equation as follows:
Silt
content
(%)
5.1-92
Surface loading ;
kg/km . . Ib/mile
42.0 - 2000 > U9 - YtiDO"'
/ ^ -\
- ' -
No. of
lanes
i2 **4 -
Vehicle weight
Mg tons
^2.7 - 12 3-13
If I is less than 1.0, the rating of the equation drops to D, because of the
subjectivity in the guidelines foT estimating 1. i
f
The quantity of particle emissions in the/finer size ranges generated by
traffic consisting predominately of medium and heavy duty vehicles on dry
industrial paved roads, per vehicle unit of travel, may be estimated, with a
rating of A, using the equation: .
0.3
E = k(3.5)
(kg/VKT)
(lb/VMT)
(2)
where: E = emission factor :
sL = road surface silt loading, g/m2 (bz/yd%
j The particle size multiplier (k) above varies with aerodynamic size range
as follows:
Aerodynamic Particle Size
Multiplier (k) For Equation 2
(Dimensionless)
<15 urn
OO.tM;
<2,5 urn
0.28 0.22
9/88
Miscellaneous Sources
11.2.6-3
-------
To determine particulate emissions for a specific particle size range, use the
appropriate value of k above.
The equation retains the quality rating of A, if applied within the range
of source conditions that were tested in developing the equation as follows:
silt loading, 2 - 240 g/m2 (0.06 - 7.1 oz/yd2)
mean vehicle weight, 6 - 42 Mg (7 - 46 tons)
The following single valued emission factors^ may be used in lieu of
Equation 2 to estimate particle emissions in the finer size ranges generated by
light duty vehicles on dry, heavily loaded industrial roads, with a rating of C:
Emission Factors For Light Duty
Vehicles On Heavily Loaded Roads
<15 urn
<10 urn
0.12 kg/VKT
(0.41 Ib/VMT)
0.093 kg/VKT
(0.33 Ib/VMT)
These emission factors retain the assigned quality rating, if applied within
the range of source conditions that were tested in developing the factors, as
follows:
silt loading, 15 - 400 g/m2 (0.44 - 12 oz/yd2)
mean vehicle weight,
-------
' Although there are relatively few quantitative data on emissions from
controlled paved roads, those that are available indicate that adequate esti-
mates generally may be obtained by substituting controlled loading values into
Equations 1 and 2. The major exception to this is water flushing combined
with broom sweeping. In that case, the equations tend to overestimate emis-
sions substantially (by an average factor of 4 or more).
! I ' '
On a paved road with moderate traffic (500 vehicles per day), to achieve
control efficiencies on the order of 50 percent, requires cleaning of the
surface at least twice per week.4 This is because of the characteristically
rapid buildup of road surface material from spillage and the tracking and depo-
sition of material from adjacent unpaved surfaces, including the shoulders
(berms) of the paved road. Because industrial paved roads usually do not have
curbs, it is important that the width of the paved road surface be sufficient
for vehicles to pass without excursion onto unpaved shoulders. Equation 1
indicates that eliminating vehicle travel on unpaved or untreated shoulders
would effect a major reduction in particulate emissions. An even greater
effect, by a factor of 7, would result from preventing travel from unpaved
roads or parking lots onto the paved road of interest. |
References for Section 11.2.6
1. R. Bohn, et al., Fugitive Emissions From Integrated Oron And Steel Plants,
! EPA-600/2-78-050, U. S. Environmental Protection Agency, Cincinnati, OH,
! March 1978.
2. C. Cowherd, Jr., et al., Iron And Steel Plant Open Dust Source Fugitive
I Emission Evaluation, EPA-600/2-79-103, U. S. Environmental Protection
i Agency, Cincinnati, OH, May 1979.
3. R. Bohn, Evaluation Of Open Dust Sources In The Vicinity Of Buffalo,
New York, EPA Contract No. 68-02-2545, Midwest Research Institute, Kansas
i City, MO, March, 1979.
4; T. Cuscino, Jr. , et al., Iron And Steel Plant Open Source Fugitive Emission
Control Evaluation, EPA-600/2-83-110, U. S. Environmental Protection Agency,
Cincinnati, OH, October 1983.
5;. J. Patrick Reider, Size Specific Particulate Emission Factors For Uncon-
! trolled Industrial And Rural Roads, EPA Contract No. 68-02-3158, Midwest
j Research Institute, Kansas City, MO, September 1983.
61 C. Cowherd, Jr., and P. Englehart, Size Specific Particulate Emission
! Factors For Industrial And Rural Roads, EPA-600/7-85-038, U. S. Environ-
i mental Protection Agency, Cincinnati, OH, September 1985.
9/88
Miscellaneous Sources
11.2.6-5
-------
-------
11.2.7 INDUSTRIAL WIND EROSION
' ' i
li.2.7.1 General1-3 !
i
j Dust emissions may be generated by wind erosion of open aggregate storage
piles and exposed areas within an industrial facility. These sources typically
are characterized by nonhomogeneous surfaces impregnated with nonerodible ele-
ments (particles larger than approximately 1 cm in diameter). Field testing of
coal piles and other exposed materials using a portable wind tunnel has shown
that (a) threshold wind speeds exceed 5 m/s (11 mph) at iL5 cm above the surface
or 10 m/s (22 mph) at 7 m above the surface, and (b) parl:iculate emission rates
tend to decay rapidly (half life of a few minutes) during an erosion event. In
other words, these aggregate material surfaces are characterized by finite
availability of erodible material (mass/area) referred to as the erosion
potential. Any natural crusting of the surface binds the erodible material,
thereby reducing the erosion potential.
!
11.2.7.2 Emissions And Correction Parameters
t
i_
i If typical values for threshold wind speed at 15 cm are corrected to
typical wind sensor height (7-10 m), the resulting values exceed the upper
extremes of hourly mean wind speeds observed in most areas of the country. In
other words, mean atmospheric wind speeds are not sufficient to sustain wind
erosion from flat surfaces of the type tested. However, wind gusts may quickly
deplete a substantial portion of the erosion potential. Because erosion poten-
tial has been found to increase rapidly with increasing wind speed, estimated
emissions should be related to the gusts of highest magnitude.
1 i '
The routinely measured meteorological variable which best reflects the
magnitude of wind gusts is the fastest mile. This quantity represents the wind
speed corresponding to the whole mile of wind movement which has passed by the
1!mile contact anemometer in the least amount of time. Daily measurements of
the fastest mile are presented in the monthly Local Climatological Data (LCD)
summaries. The duration of the fastest mile, typically about 2 min (for a
fastest mile of 30 mph), matches well with the half life of the erosion
process, which ranges between 1 and 4 min. It should be noted, hbWever, that
peak winds can significantly exceed the daily fastest mile.
' . ' . ' . i
I The wind speed profile in the surface boundary layer is found to follow a
logarithmic distribution:
where u
1 u*
i z
: zo
, 0.4
u(z) = u* In z (z > z0)
0.4 z0
wind speed, cm/sec
friction velocity, cm/sec
height above test surface, cm
roughness height, cm
von Karman's constant, dimensionless
(1)
The friction velocity (u*) is a measure of wind shear stress on the erodible
surface, as determined from the slope of the logarithmic velocity profile. The
roughness height (zo) is a'measure of the roughness of the exposed surface as
determined from the y intercept of the velocity profile, i.e., the height at
9/88
Miscellaneous Sources
.2.7-1
-------
which the wind speed is zero. These parameters are illustrated in Figure
11.2.7-1 for a roughness height of 0.1 cm.
Emissions generated by wind erosion are also dependent on the frequency of
disturbance of the erodible surface because each time that a surface is dis-
turbed, its erosion potential is restored. A disturbance is defined as an
action which results in the exposure of fresh surface material. On a storage
pile, this would occur whenever aggregate material is either added to or
removed from the old surface. A disturbance of an exposed area may also-result
from the turning of surface material to a depth exceeding the size of the
largest pieces of material present.
11.2.7.3 Predictive Emission Factor Equation*
The emission factor for wind generated particulate emissions from mixtures
of erodible and nonerodible surface material subject to disturbance may be
expressed in units of g/m^-yr as follows:
N
Emission factor = k P (2)
i = 1
where k 3 particle size multiplier
N = number of disturbances per year
Pi » erosion potential corresponding to the observed (or probable)
fastest mile of wind for the ith period between disturbances,
g/m2
The particle size multiplier (k) for Equation 2 varies with aerodynamic
particle size, as follows:
AERODYNAMIC PARTICLE SIZE MULTIPLIERS FOR EQUATION 2
<30 urn <15 urn <10 urn <2.5 urn
1.0 0.6 0.5 0.2
This distribution of particle size within the <30um fraction is comparable
to the distributions reported for other fugitive dust sources where wind speed
is a factor. This is illustrated, for example, in the distributions for batch
and continuous drop operations encompassing a number of test aggregate materials
(see Section 11.2.3).
In calculating emission factors, each area of an erodible surface that is sub-
ject to a different frequency of disturbance should be treated separately. For
a surface disturbed daily, N = 365/yr, and for a surface disturbance once
every 6 months, N = 2/yr.
Equations 2 and 3 apply only to dry, exposed materials with limited erosion
potential. The resulting calculation is valid only for a time period as long
or longer than the period between disturbances. Calculated emissions repre-
sent intermittent events and should not be input directly into dispersion
models that assume steady state emission rates.
11.2.7-2 EMISSION FACTORS 9/88
-------
B
Figure 11.2.7-1. Illustration of logarithmic velocity profile.
9/88 Miscellaneous Sources
11.2.7-3
-------
The erosion potential
-p-58
nASlonyfor ^^ ^^ r
(u* - 1^)2*25 <.:; ;: , ,J
Threshold friction velocities for several surface types have been determined
by field measurements wifh a portable wind tunnel. These values are presented
in Table 11.2.7-1. ,-., »' i , - ^ _ . ;
. * $ ;; -"
TABLE 11.2.7-1. FIELD PROCEDURE FOR DETERMINTION OF THRESHOLD
FRICTION VELOCITY
Tyler
sieve no.
5 . --;:
9
16
32
60
Opening Midpoint
(mm) (mm)
,-<,'' -.', ''.' '
. . . . :'-'- ... ' ' . -
'-'' ^r.^/^-X-'' -v'";.
. ; ^ ;, ...:;. 3 . ..;
'. . 2':;-'- - ''/ - .-; '.. ;'
'.' ''' ''"'*' ' '':'''-. v"i.5' '''
i ' '
0.75
0.5
.: -,:'.. :-'. .<.:.. -':-. 0,375.-
''\.:r^^.^."Si:'^; '''..- '.
u* (cm/sec)
t
100
,72
58
43 .
-'-'"',.,! . '.
- ,- , ,-,; ' \". - , -» > . . '- '
FIELD PROCEDURE FOR DETERMINATION OF THRESHOLD FRICTION VELOCITY
(from a 1952 laboratory procedure published by W. S. Chepil)
1. Prepare a nest of sieves with the following openings: 4 mm, 2 mm, 1 mm,
0.5 mm, 0.25 mm. Place a collector pan below tlm crhhrj r f taga *5M36
2. Collect a sample representing the s,ur,fa;pe layer of loose particles
(approximately 1 cm in depfch, for ;an >fnc.rusted surface), removing any rocks
"* - '» *i'v~ t*f^in''^L * "'JS*!!*1 '''''. . '.,,,-
1+ n -, t -,-,. , ^iift-t'** - *. ^wfr- '*, - ,-.^ , - :
1-2.7-4 >^*EMISSIP^ FACTORS '; :"".: 9/88
-------
larger than about 1 cm in average physical diameter.
sampled should be not less than 30 cm.
The area to be
3. Pour the sample into the top sieve (4 mm opening), a:hd place a lid on the
t top.
4J. Move the covered sieve/pan unit by hand, using a broad circular arm motion
in the horizontal plane. Complete 20 circular movements at a speed just
necessary to achieve some relative 'horizontal motion between the sieve and
the particles.
5j. Inspect the relative quantities of catch within each sieve, and determine
; where the mode in the aggregate size distribution lies, i. e. , between the
opening size of the sieve with the largest catch and the opening size of
the next largest sieve.- .
6. Determine the threshold friction velocity from Figure 1.
1 : ' I '
The fastest mile of wind for the periods between disturbances may be obtained
firom the monthly LCD summaries for the nearest reporting weather station that
is representative of the site in question.^ These summaries report actual
fastest mile values for each day of a given month. Because the erosion
potential is a highly nonlinear function.of the. fastest mile, mean values of
the fastest mile are inappropriate. The anemometer heights of reporting
weather stations are found in Reference 8, and should be corrected to a 10 m
reference height using Equation 1.
TABLE 11.2.7-2. THRESHOLD FRICTION VELOCITIES
;
1 Material
i
Overburden3
Sporia (roadbed
material)3
Ground coala
. (surrounding coal
i pile)
Uncrusted coal pilea
Scraper tracks on
coal pilea>b
Fj.ne coal dust on
< concrete padc
i
a| Western surface coal
b Lightly crusted.
ci Eastern power plant.
Threshold
friction
velocity
(m/s)
1.02
1.33
0.55
1.12
0.62
0.54
mine.
Roughness
height
(cm)
0.3
0.3
0.01
0.3
0.06
0.2
Threshold wind . ,
velocity at 10 m (m/s)
z0 = Actual z0 = 0.5 cm
21 19
27 25
16 10
23
15
11
21
12
10
Ref.
2
2
2
2
2
3
9!/88
Miscellaneous Sources
11.2.7-5
-------
To convert the fastest mile of wind (u+) from a reference anemometer height of
10 m to the equivalent friction velocity (u*), the logarithmic wind speed
profile may be used to yield the following equations
u* = 0.053 u+10 (4)
where u* = friction velocity (m/s)
u IQ ** fastest mile of reference anemometer for period between
disturbances (m/s)
x
This assumes a typical roughness height of 0.5 cm for open terrain.
Equation 4 is restricted to large relatively flat piles or exposed areas with
little penetration into the surface wind layer.
If the pile significantly penetrates the surface wind layer (i.e., with a
height-to-base ratio exceeding 0.2), it is necessary to divide the pile area .
into subareas representing different degrees of exposure to wind. The results
of physical modeling show that the frontal face of an elevated pile is exposed
to wind speeds of the same order as the approach wind speed at the top of the
pile.
For two representative pile shapes (conical and oval with flattop, 37 degree
side slope), the ratios of surface wind speed (us) to approach wind speed (ur)
have been derived from wind tunnel studies.^ The results are shown in
Figure 11.2.7-2 corresponding to an actual pile height of 11 m, a reference
(upwind) anemometer height of 10 m, and a pile surface roughness height (zo)
of 0.5 cm. The measured surface winds correspond to a height of 25 cm above
the surface. The area fraction within each contour pair is specified in
Table 11.2.7-3.
The profiles of us/ur in Figure 11.2.7-2 can be used to estimate the surface
friction velocity distribution around similarly shaped piles, using the
following procedure:
1. Correct the fastest mile value (u+) for the period of interest from the
anemometer height (z) to a reference height of 10 m (u ^Q) using a
variation of Equation 1:
u+1Q = u+ In (10/0.005) (5)
In (z/0.005)
where a typical roughness height of 0.5 cm (0.005 m) has been assumed.
If a site specific roughness height is available, it should be used.
2. Use the appropriate part of Figure 11.2.7-2 based on the pile shape and
orientation to the fastest mile of wind, to obtain the corresponding sur-
face wind speed distribution (u+ ):
S
u+s = Cs) u+10 (6) ,
11.2.7-6 EMISSION FACTORS 9/88
-------
; Flow
! Direction
Pile A
Pile B1
Figure 11.2.7-2. Contours of Normalized Surface Wind Speeds, us/ur
9/88
Miscellaneous Sources
11.2.7-7
-------
3. For any subarea of the pile surface having a narrow range of surface wind
speed, use a variation of Equation 1 to calculate the equivalent friction
velocity (u*):
0.4 u+
u* - = 0.10 UH"
25_
1*0.5
From this point on, the procedure is identical to that used for a flat pile,
as described above.
Implementation of the above procedure is carried out in the following steps;
1. Determine threshold friction velocity for erodible material of interest
(see Table 11.2.7-2 or determine from mode of aggregate size
distribution).
2. Divide the exposed surface area into subareas of constant frequency of
disturbance (N).
TABLE 11.2.7-2. SUBAREA DISTRIBUTION FOR REGIMES OF us/ur
Percent of pile surface area (Figure
Pile subarea
0.2a
0.2b
0.2c
0.6a
0.6b
0.9
1.1
Pile A
5
35
-
48
-
12
»
Pile Bl
5
2
29
26
24
14
"
Pile B2
3
28
-
29
22
.. 15
3
11.2.7-2)
Pile B3
3
25
28
26
14
4
3. Tabulate fastest mile values (u+) for each frequency of disturbance and
correct them to 10 m (U+IQ) using Equation 5.
4. Convert fastest mile values (U+IQ) to equivalent friction velocities (u*),
taking into account (a) the uniform wind exposure of nonelevated surfaces,
using Equation 4, or (b) the nonuniform wind exposure of elevated surfaces
(piles), using Equations 6 and 7.
5. For elevated surfaces (piles), subdivide areas of constant N into sub-
areas of constant u* (i.e., within the isopleth values of us/ur in Figure
11.2.7-2 and Table 11.2.7-3) and determine the size of each subarea.
6. Treating each subarea (of constant N and u*) as a separate source,
calculate the erosion potential (Pj) for each period between disturbances
using Equation 3 and the emission factor using Equation 2.
11.2.7-8
EMISSION FACTORS
9/88
-------
Multiply the resulting emission factor for each subarea by the size of
the subarea, and add the emission contributions of all subareas. Note
that the highest 24-hr emissions would be expected to occur on the
windiest day of the year. Maximum emissions are calculated assuming a
i single event with the highest fastest mile value for the annual period.
The recommended emission factor equation presented above a.ssumes that all of
the erosion potential corresponding to the fastest mile of wind is lost during
the period between disturbances. Because the fastest mile event typically
lasts only about 2 min, which corresponds roughly to the halflife for the
decay of actual erosion potential, it could be argued that the emission factor
overestimates particulate emissions. However, there are other aspects of the
wind erosion process which offset this apparent conservatism:
i ' - .. | .'.".
1. The fastest mile event contains peak winds which substantially exceed the
i mean value for the event. '
2. Whenever the fastest mile event occurs, there are usually a number of
periods of slightly lower mean wind speed which contalin peak gusts of the
same order as the fastest mile wind speed.
i
i '
Of(greater concern is the likelihood of overprediction of wind erosion
emissions in the case of surfaces disturbed infrequently in comparison to the
rate of crust formation.
i
11.2.7.4 Example calculation for wind erosion emissions from conically shaped
coal pile
A coal burning facility maintains a conically shaped surge pile 11 m in height
and 29.2 m in base diameter, containing about 2000 Mg of coal, with a bulk
density of 800 kg/m3 (50 lb/ft3). The total exposed surface area of the pile
is(calculated as follows: !
S = r r2 + h2
=3.14(14.6) (14.6)2 + (ll.O)2
': = 838 m2
Coal is added to the pile by means of a fixed stacker and reclaimed by front-
end loaders operating at the base of the pile on the downwind side. In addi-
tion, every 3 days 250 Mg (12.5% of the stored capacity of coal) is added back
to the pile by a topping off operation, thereby restoring the full capacity of
the pile. It is assumed that (a) the reclaiming operation disturbs only a
limited portion of the surface area where the daily activity is occurring,
such that the remainder of the pile surface remains intact, and (b) the top-
ping off operation creates a fresh surface on the entire pile while restoring
its original shape in the area depleted by daily reclaiming activity.
Because of the high frequency of disturbance of the pile, a large number of
calculations must be made to determine each contribution to the total annual
wind erosion emissions. This illustration will use a single month as an
example. j
.i
i
9/88 Miscellaneous Sources 11.2.7-9
-------
Prevailing
Wind
Di recti on
* A portion of Cg is disturbed daily by reclaiming activities,
area
ID
A
B
Ci + C2
us
Ur
0.9
0.6
0.2
% ..."
12
48
40
Area (m2)
101
402
335
Circled values
refer to us/ur
838
Figure 11.2.7-3. Example 1: Pile surface areas within each wind speed regime.
11.2.7-10
EMISSION FACTORS
9/88
-------
Step 1: In the absence of field data for estimating the threshold friction
velocity, a value of 1.12 m/s is obtained from Table 11.2.7-2.
Step 2: Except for a small area near the base of the pile (see
Figure 11.2.7-3), the entire pile surface is disturbed every 3 days, corre-
sponding to a value of N = 120/yr. It will be shown that the contribution of
the area where daily activity occurs is negligible so that it does not need to
be treated separately in the calculations.
Step 3; The calculation procedure involves determination of the fastest mile
fo|r each period of disturbance. Figure 11.2.7-4 shows a representative set of
values (for a 1 month period) that are assumed to be applicable to the geographic
area of the pile location. The values have been separated into 3 day periods,
and the highest value in each period is indicated. In this example, the
anemometer height is 7 m, so that a height correction to 10 m is needed for the
fastest mile values. From Equation 5,
u+10
In (10/0.005)
u+7 In (7.0.005)
u+io = 1.05 u+7 I
St|ep 4: The next step is to convert the fastest mile value for each 3 day
period into the equivalent friction velocities for each surface wind regime
(i. e., us/ur ratio) of the pile, using Equations 6 and 7. Figure 11.2.7-3
shows the surface wind speed pattern (expressed as a fraction of the approach
wind speed at a height of 10 m). The surface areas lying within each wind
speed regime are tabulated below.the figure.
, '
i i
The calculated friction velocities are presented in Table 11.2.7-4. As
indicated, only three of the periods contain a friction velocity which exceeds
the threshold value of 1.12 m/s for an uncrusted coal pile. These three values
all occur within the Ug/Uj- = 0.9 regime of the pile surface.
Step 5: This step is not necessary because there is only one frequency of
disturbance used in the calculations. It is clear that the small area of
daily disturbance (which lies entirely within the Ug/ur = 0.2 regime) is never
subject to wind speeds exceeding the threshold value.
9/88
Miscellaneous Sources
11.2.7-11
-------
Local Climatological Data
MONTHLY SUMMARY
HIND
es
o
*-
X
<
_<
=1
in
UJ
or
13
30
01
10
13
12
20
29
29
22
1 4
29
17
21
10
10
01
33
27
32
24
22
32
29
07
3*
31
30
30
33
34
29
st
- o.
5*
*-
_l O
r> uj
in uj
uj a.
cr en
H
5.3
10.5
2.4
! 1 .0
1 1 .3
1 1 . 1
19.6
10.9
3.0
14.6
22.3
7.9
7.7
4.5
6.7
13.7
1 1 .2
4.3
9.3
7.5
10.3
17.1
2.4
5.9
11.3
12. 1
8.3
8.2
5.0
3.1
4.9
o
uj
UJ
a.
tn
3 X
ez CL
5 =
15
6.9
10.6
6.0
M.4
1 1 .9
19.0
19.8
1 1 .2
B. 1
15. 1
23.3
13.5
15.5
9.6
8.8
13.8
1 1 .5
5.8
10.2
7.8
10.6
17.3
8.5
8.8
11.7
12.2
8.5
8.3
6.6
5.2
5.5
FASTEST
MILE
o "~
UJQ.
UJ
0. IT
in
16
to
16
17
15
23
18
1 J
1?
16
15
O
16
16
w
9
8
o
»
c_>
UJ
cr
o
17
36
01
02
13
1 I
30
30
30
13
12
29
17
18
13
1 1
35
3-S
31
35
24
20
32
13
02
32
32
25
32
32
31
25
FOR THE MONTH:
30
3.3
M.I
3 1 29
DATE: 1 1
"
UJ
H-
^
0
22
i
2
3
A
5
6 .
7
8
9
10
1 I
12
13
I 4
15
16
17
18
"19
20
21
22
23
24
25
26
27
25
29
30
ji
Figure 11.2.7-4. Daily fastest miles of wind for periods of interest.
11.2.7-12
EMISSION FACTORS
9/88
-------
TABLE 11.2.7-4. EXAMPLE 1: CALCULATION OF FRICTION VELOCITIES
3 Day
period
i ,
[ 1
i 2
j 3
4
: 5
i 6
i 7
i 8
i 9
HO
U+7 u"*"10
(mph)
14
29
30
31
22
21
16
25
17
13
(m/s) (mph)
6.3
13.0
13.4
13.9
9.8
9.4
7.2
11.2
7.6
5.8
15
31
32
33
23
22
17
26
18
14
(m/s) Ug/ur
6.6
13.7
14.1
14.6
10.3
9.9
7.6
11.8
8.0
6.1
1
! u* -
i
0.2
0.13
i 0.27
! 0.28
! 0.29
0.21
i 0.20
0.15
0.24
0.16
0.12
0.1 u+s
0.6
0.40
0.82
0.84
0.88
0.62
0.59
0.46
0.71
0.48
0.37
(m/s)
0.9
0.59
1.23
1.27
1.31
0.93
0.89
0.68
1.06
0.72
0.55
Steps 6 and 7: The final set of calculations (shown in Table 11.2.7-5)
involves the tabulation and summation of emissions for each disturbance period
and for the affected subarea. The erosion potential (P) is calculated from
Equation 3.
TABLE 11.2.7-5. EXAMPLE 1: CALCULATION OF PM10 EMISSIONS3
3 Day
Pile Surface
Area kPA
period u* (m/s) u* - u*fc (m/s) P (g/m2) ID
f
2 1.23 0.11 3.45
j3 1.27 0.15 5.06
4 1.31 0.19 6.84
A
A
A
Total PM]
(m2)
101
101
101
0 emissions
(g)
170
260
350
= 780
For example, the calculation for the second 3 day period is:
j ?2 = 58(1.23 - 1.12)2 + 25(1.23 - 1.12)
: - 0.70 + 2.75 = 3.45 g/m2
i ' i
The PMio emissions generated by each event are found as the product of the
PMio multiplier (k = 0.5), the erosion potential (P), and the affected area
of' the pile (A).
9/08
Miscellaneous Sources
11.2.7-13
-------
As shown in Table 11.2.7-5, the results of these calculations indicate a
monthly PM^o emission total of 780 g.
11.2.7.5 Example calculation for wind erosion from flat area covered with coal
dust
A flat circular area of 29.2 m in diameter is covered with coal dust left over
from the total reclaiming of a conical coal pile described in the example
above. The total exposed surface area is calculated as follows:
S = _ d2 = 0.785 (29. 2)2 = 670 m2
4
This area will remain exposed for a period of 1 month when a new pile will be
formed.
Step 1: In the absence of field data for estimating the threshold friction
velocity, a value of 0.54 m/s is obtained from Table 11.2.7-2.
Step 2: The entire surface area is exposed for a period of 1 month after
removal of a pile and N = 1/yr.
Step 3: From Figure 11.2.7-5, the highest value of fastest mile for the
30 day period (31 mph) occurs on the llth day of the period. In this example,
the reference anemometer height is 7 m, so that a height correction is needed
for the fastest mile value. From Step 3 of the previous example, U+IQ = 1.05
u-fy, so that u+io = 33 mph.
Step 4: Equation 4 is used to convert the fastest mile value of 33 mph
(14.6 m/s) to an equivalent friction velocity of 0.77 m/s. This value exceeds
the threshold friction velocity from Step 1 so that erosion does occur.
Step 5: This step is not necessary because there is only one frequency of
disturbance for the entire source area.
Steps 6 and 7: The PM^o emissions generated by the erosion event are
calculated as the product of the PM^o multiplier (k = 0.5), the erosion
potential (P) and the source area (A). The erosion potential is calculated
from Equation 3 as follows:
P = 58(0.77 - 0.54)2 + 25(0.77 - 0.54)
- 3.07 + 5.75
= 8.82 g/m2
Thus the PM^Q emissions for the 1 month period are found to be:
E = (0.5)(8.82 g/m2)(670 m2)
= 3.0 kg
11.2.7-14 EMISSION FACTORS 9/88
-------
References for Section 11.2.7
1!. C. Cowherd Jr. , "A New Approach to Estimating Wind Generated Emissions
from Coal Storage Piles", Presented at the APCA Specialty Conference on
Fugitive Dust Issues in the Coal Use Cycle, Pittsburgh, PA, April 1983.
2i. K. Axtell and C. Cowherd, Jr. , Improved Emission Factors for Fugitive Dust
I from Surface Coal Mining Sources, EA-600/7-84-048, U,ST.Environmental
Protection Agency, Cincinnati, OH, March 1984.
31. G. E. Muleski, "Coal Yard Wind Erosion Measurement", j Midwest Research
Institute, Kansas City, MO, March 1985.
4|. Update of Fugitive Dust Emissions Factors in AP-42 Section 11.2 - Wind
| Erosion, MRl No. 8985-K, Midwest Research Institute,;Kansas City, MO, 1988.
i I
5;. W. S. Chepil, "Improved Rotary Sieve for Measuring State and Stability
I of Dry Soil Structure", Soil Science Society of America Proceedings,
JL6_:113-117, 1952.
( [-
6. D. A. Gillette, et al., "Threshold Velocities for Input of Soil
Particles Into the Air By Desert Soils", Journal of Geophysical Research,
85(C10):5621-5630. :i
7. Local Climatological Data, National Climatic Center, Asheville, NC.
8'. M. J. Changery, National Wind Data Index Final Report, HCO/T1041-01 UC-60,
National Climatic Center, Asheville, NC, December 197~8.
i i
9. B. J. B. Stunder and S. P. S. Arya, "Windbreak Effectiveness for Storage
j Pile Fugitive Dust Control: A Wind Tunnel Study", Journal of the Air
! Pollution Control Association, 38:135-143, 1988.
9/88
Miscellaneous Sources
11.2.7-15
-------
-------
t
APPENDIX C.3
SILT ANALYSIS PROCEDURES
Select, the appropriate 8 inch diameter 2 inch deep sieve sizes.
Recommended standard series sizes are 3/8 inch No. 4, No. 20, No. 40,
No. 100, No. 140, No. 200, and a pan. .The No. 20 and the No. 200 are
mandatory. Comparable Tyler Series sizes can also be used. "
2. Obtain a mechanical sieving device such as a vibratory shaker or a
: Roto-Tap (without the tapping function).
3. Clean the sieyes with compressed air and/or,a soft brush. Material lodged
! in the sieve openings or adhering to the sides of the sieve should be
removed without handling the screen roughly, if possible.
I
4. Obtain a scale with capacity of at least 1600 grams, and record its make,
capacity, smallest increment, date of last calibration, and accuracy.
5. Record the tare weight of sieves and pan, and check the zero before every
I .weighing.
After nesting the sieves in decreasing order of hole size, and with the
pan at the bottom, dump dried laboratory sample into the top sieve,
preferably immediately after moisture analysis. The sample should weigh
between 800 and 1600 grams (1.8 and 3.5 pounds). Brush fine material
adhering to the sides of the container into the top sieve, and cover the
top sieve with a special lid normally purchased with the pan.
7j. Place nested sieves into the mechanical device, and sieve for 10 minutes.
Remove pan containing minus No. 200 and weigh its contents. Repeat the
sieving in 10 minute intervals until the difference between two successive
I pan sample weights is less than 3.0 percent when the tare of the pan has
been substracted. Do not sieve longer than 40 minutes.
8j. Weigh each sieve and its contents, and record the weight. Remember to
' check the zero before every weighing.
I
9» Collect the laboratory sample, and place it in a separate container if
j further analysis is expected.
i i
10;. Calculate the percent of mass less than the 200 mesh screen (75 micro-
meters). This is the silt content.
U. S. QOVEEHMEHT EKrHOKG OFFICE 1988/526-090/87005
9/88 Appendix C.3 C.3-1
-------
-------
1. REPORT NO.
AF 42, Supplement B
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
4. TITLE AND SUBTITLE
2.
Supplement B to Compilation of Air Pollutant Emissi6n
Factors, AP-42, Fourth Edition
B. REPORT DATE
September 1988
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO.
9. PERFORMING ORGANIZATION NAME AND ADDRESS
U.iS. Environmental Protection Agency
Office of Air And 'Radiation
Office Of Air Quality Planning And Standards
Research Triangle Park, NC 27711
12. SPONSORING AGENCY NAME AND ADDRESS
15. SUPPLEMENTARY NOTES
EPA Editor; Whitmel M. Joyner
16. ABSTRACT ~ ~
3. RECIPIENT'S ACCESSION NO.
10. PROGRAM ELEMENT NO.
Tl. CONTRACT/GRANT NO.
1,3. TYPE OF REPORT AND PERIOD COVERED
14. SPONSORING AGENCY CODE
; In this Supplement to the Fourth Edition of AP-42, new or revised emissions data
are presented for Bituminous And Subbituminous Coal Combustion; Anthracite Coal
Combustion; Residential Wood Stoves; Waste Oil Combustion; Refuse Combustion; Sewage
Sludge Incineration; Surface Coating; Polyester Resin Plastics Product Fabrication;
Soap And Detergents; Grain Elevators And Processing Plants; Lime Manufacturing; Crushed
Stpne Processing; Western Surface Coal Mining; Wildfires And Prescribed Burning;
Unpaved Roads; Aggregate Handling And Storage Piles; Industrial Paved Roads; Industrial
Wind Erosion; and Appendix C.3, "Silt Analysis Procedures".
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
Stationary Sources
Point Sources
Area Sources
Emission Factors
Emissions
18. DISTRIBUTION STATEMENT
EPA F,orm 2220-1 (Rev. 4-77) PREVIOUS EDITION is OBSOLETE
XIDENTIFIERS/OPEN ENDED TERMS
19. SECURITY CLASS {ThisReport)
20. SECURITY CLASS (Thispage)
c. COSATI Field/Group
21. NO. OF PAGES
182
22. PRICE
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