MIDWEST RESEARCH INSTITUTE
EPORT
IRON AND STEEL PLANT OPEN SOURCE FUGITIVE EMISSION CONTROL EVALUATION
DRAFT FINAL REPORT
EPA Contract No. 68-02-3177, Assignment No. 1
MRI Project No. 4862-LC'l)
Date Prepared: June 5, 1980
Prepared for
Industrial Environmental Research Laboratory
U.S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
Attn: R. V. Kendriks
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MRI-NORTH STAR LABORATORIES 10701 Red Circle Drive, Minnetonka, Minnesota 55343 • 612 933-7880
MRI WASHINGTON, D.C. 20006-Suite 250,1750 K Street, N.W. • 202 293-3800
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IRON AND STEEL PLANT OPEN SOURCE FUGITIVE EMISSION,CONTROL EVALUATION
DRAFT FINAL REPORT
EPA Contract No. 68-02-3177, Assignment No. 1
MRI Project No. 4862-L(l)
Date Prepared: June 5, 1980
Prepared for
Industrial Environmental Research Laboratory
U.S. Environmental Protection Agency
Research Triangle Park, North Carolina 27711
Attn: R. V. Hendriks
MIDWEST RESEARCH INSTITUTE 425 VOLKER BOULEVARD, KANSAS CITY, MISSOURI 64110 • 816753-7600
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PREFACE
This report was prepared for the Environmental Protection Agency's
Industrial Environmental Research Laboratory under EPA Contract No. 68-02-
3177, Work Assignment No. 1. Mr. Robert V. Hendriks, Metallurgical Pro-
cesses Branch, was the requestor of this work. The report was prepared in
Midwest Research Institute's Air Quality Assessment Section (Dr. Chatten
Cowherd, Head). Dr. Cowherd was the principal author.
Approved for:
MIDWEST RESEARCH INSTITUTE
kJ^^\
M. P. Schrag, Director
Environmental Systems Department
June 5, 1980
11
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CONTENTS
1.0 Introduction 1
2.0 Open Dust Sources and Potential Emissions 3
Emissions data from previous studies 5
Methodology for more extensive plant surveys 9
Updated emissions inventory 11
Sampling and analysis methods 13
3.0 Control Technology for Open Dust Sources 20
Types of control techniques 20
Efficiency and cost of control 21
Current industry control practices 23
Selection of best controls 27
4.0 Recommendations for Phase II 30
Data needs 30
Sampling and analysis procedures 32
Quality assurance program 40
Statistical basis for sampling plan 49
Distribution of tests 50
Proposed test sites 51
References 55
Appendices
A. Example data compilation from materials handling flow
charts : A-l
B. Bibliography for open dust control B-l
111
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FIGURES
Number Page
1 Effectiveness of road dust suppressants 8
2 Example exposure profiling arrangement 18
3 MRI exposure profiler 34
4 MRI portable and tunnel 38
IV
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TABLES
Number Page
1 Fugitive Dust Emission Factors Experimentally Determined
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
Preliminary Inventory of Open Dust Source Contributions
to Suspended Particulate Emissions
Recent and Current Investigations of Control Technology
Applicable to Open Dust Sources
Cost Effectiveness of Fugitive Emissions Control Methods .
Control Efficiencies of Road Dust Suppressants
Reported Efficiencies for Control of Wind Erosion of
Storage Piles
Summary of Fugitive Emissions Controls (By Plant)
Parameters Affecting Emission Factors for Open Dust
Sources
Sampling Equipment for Open Dust Sources
Criteria for Suspending or Terminating an Exposure
Profiling Test
Moisture Analysis Procedures
Silt Analysis Procedures
Quality Assurance Procedures for Sampling Flow Rates . . .
Quality Assurance Procedures for Sampling Media
Quality Assurance Procedures for Sampling Equipment. . . .
Quality Assurance Procedures for Data Processing and
Calculations
Proposed Distribution of Tests
Sources Proposed for Testing at. Armco's Middletown Works .
w
12
22
24
25
26
28
31
33
36
41
42
44
45
46
47
52
53
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1.0 INTRODUCTION
Iron- and steel-making processes, which are characteristically batch
or semicontinuous operations, generate substantial quantities of fugitive
(nonducted) emissions at numerous points in the process cycle. There are
numerous materials handling steps in the storage and preparation of raw
materials and in the disposal of process wastes. Additionally, fugitive
emissions escape from reactor vessels during chargine, process heating, and
tapping.
Fugitive emissions in the iron and steel industry can be generally di-
vided into two classes—process fugitive emissions and open dust source emis-
sions. Process fugitive emissions include uncaptured particulates and gases
that are generated by steel-making furnaces, sinter machines, and metal form-
ing and finishing equipment, and that are discharged to the atmosphere through
building ventilation systems. Open dust sources of fugitive emissions include
such sources as raw material storage piles, from which emissions are generated
by the forces of wind and machinery acting on exposed aggregate materials.
Recent studies of fugitive emissions from integrated iron and steel
plants1'2 have provided strong evidence that open dust sources (specifical-
ly, vehicular traffic on unpaved and paved roads and storage pile activities)
rank with steel-making furnaces and sinter machines as sources which emit
the largest quantitites of fine and suspended particulate matter, taking
into account typically applied control measures. Moreover, preliminary analy-
sis of promising control options for both process sources of fugitive emis-
sions and open dust sources indicate that control of open dust sources has
a highly favorable cost-effectiveness ratio for particulate. Although lim-
ited in scope, these studies show that open dust sources should occupy a
prime position in control strategy development for fugitive particulate emis-
sions within integrated iron and steel plants.
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Recent guidance for State Implementation Plan revision has generally
included provisions for control of open dust sources. However, lack of in-
formation on emissions and control capabilities for these sources has pre-
vented control officials from taking full advantage of control strategies
that include provision for control of the open dust sources. Furthermore,
although trade-offs between open source's and process sources might result
in significantly improved air quality at a lower cost, this improvement can
only occur if open dust sources can be quantified and controlled successfully.
This report presents an evaluation of existing data on the quantities
of pollutants from open dust sources in steel plants and on the capability
of control procedures for eliminating or reducing these emissions. Based
on this evaluation, a testing program designed to provide needed data on
emissions and controls is outlined.
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2.0 OPEN DUST SOURCES AND POTENTIAL EMISSIONS
The open dust sources which are found within integrated iron and steel
plants may be placed into the following generic categories, based on similar-
ity of physical mechanisms for dust generation:
Vehicular traffic on unpaved surfaces
Unpaved roads
Storage pile maintenance
Unpaved parking lots
Vehicular traffic on paved surfaces
Batch drop operations
Loaders
Railcars
Trucks
Gantry/clamshell buckets
Continuous drop operations
Stackers
Conveyor transfer stations
Bucket wheels
Wind erosion
Storage piles
Exposed areas
3
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The ranking of the emissions potential of open dust sources within the
integrated iron and steel industry is an important tool in deciding where
control studies should be focused. This requires the development of a nation-
wide emissions inventory for the industry.
Calculation of the emission rate for a given source requires data on
source extent, uncontrolled emission factor and control efficiency. The
mathematical expression for this calculation is as follows:
R = Me (1 - c)
where: R = mass emission rate
M = source extent
e = uncontrolled emission factor, i.e., rate of uncontrolled
emissions per unit of source extent
c = fractional efficiency of control
Because of the wide range of particle size associated with emissions
from open dust sources, it is important that the applicable particle size
range be specified for the calculated emission rate. The particle size
range is that for which the uncontrolled emission factor and the fractional
efficiency of control apply.
As noted above, a nationwide inventory of emissions from open dust
sources within the integrated iron and steel industry was developed as part
of an earlier study.2 For that inventory, source extent values were based
in part on: (a) 1976 industry consumption of coal and pelletized iron ore,
and (b) 1977 surveys of four plants. Representative source parameter values
were taken to be the averages of the values obtained from the plant surveys.
Representative control practices for the industry were based on the plant
surveys, and control efficiency values for these measures were estimted.
The emission factors used for the inventory were those judged to be the most
reliable at the time of the inventory.
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The reliability of the emissions inventory was limited by its dependence
on data from the plant surveys and on assumed values where data were lacking.
The four surveyed plants may not have constituted an adequate data base to
represent the industry. Emission factor data were sparse for some generic
source categories, and control efficiency data were almost totally lacking.
The remainder of this section reports on the efforts to develop a more
reliable emissions inventory to be used as the basis for determining the
open dust sources and most promising control measures for which further test-
ing is needed.
2.1 EMISSIONS DATA FROM PREVIOUS STUDIES
The most extensive emission factor data base available to date for open
dust sources is that developed by Midwest Research Institute (MRI).2 As
shown in Table 1, the MRI emission factors take the form of predictive equa-
tions which contain correction parameters to account for source variability.
The correction parameters may be grouped into the following categories:
1. Measures of source activity or energy expended (for example, the
speed and weight of a vehicle traveling on an unpaved road).
2. Properties of the material being disturbed (for example, the content
of silt in the surface material on an unpaved road).
3. Climatic parameters (for example, number of precipitative-free days
per year on which emissions tend to be at a maximum).
The emission factors developed by MRI have been made specific to parti-
cles smaller than 30 |Jm in Stokes diameter, so that emissions may be related
to ambient concentrations of total suspended particulate. The upper size
limit of 30 [Jm for suspended particulate is the approximate effective cutoff
diameter for capture of fugitive dust by a standard high volume particulate
sampler (based on a typical particle density of 2 to 2.5 g/cm).3 It should
be noted, however, that analysis of parameters affecting the atmospheric
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TABLE 1. FUGITIVE DUST EMISSION FACTORS EXPERIMENTALLY DETERMINED BY MRI
Soureo catego
M**ar.urt: of extent
I.
2.
I In paved roads
Paved Roads
Hatch Load-In
(d.g., front-end ionder,
titi tear dump)
Cmiti nuouK Ixiad- in
(e.g., st.ickcf, transfer
station)
Vehicle-Mi les Traveled
Voli i c I n- Ml 1 os Tra v o I et\
Tons of material I .o ad ed In
To i is o C Ma t c rial l
7. Batch loail-diit
Tons of Mitcsrt.ll Ixiailpd (Hit
8. Wind Erosion of Exposed Areas Acre-Years of Exposed l.and
a/
tin Is.'. Jon laclnr-
(lh/iinl.t of sonrco oxtcnt )
0.7
'•' (fc)ft)tf) (f)
o.oi j /A)/s_W_i_W«\
Wlio/u.oooM-)/
0.5
0.7
n.ooin
o.onis
0.10 K
5 mo
O.OOIft
3,400
(!) (i)
jjojjIl/Tp
f.tiS ) '
I 50 /
Correct lh)
M - Material Surface Moisture Content (7«)
Y ~ Dumping Device. (.,'apac i.ty (yd )
IC~ Activity Correction—
/
ct
* E<|tial.s 7.0 for trucks coining from unpaved to paved roads and releasing dust from uiiderhody of vehicle;
* Equals 3.5 when 207. of the vehicles are forced to travel temporarily with one set uf wheels .111 ; ..... npaved road berm while passing on narrow roads;
* Equals 1.0 for traffic entirely on paved surfaces.
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transport of fugitive dust indicates that only the portion smaller than about
5 |Jm in diameter will be transported over distances greater than 5 to 10 km
from the source.4
Other than MRI' s previous work, a few emission factor data for open
dust sources exist. Estimated emission 'factors have been developed for the
handling and transfer of storage materials. An uncontrolled emission factor
of 0.033 Ib/ton coke for coke being dumped into a blast furnace was calculated
from a measured blast furnace cyclone catch.5 This factor might be appli-
cable to a coke conveyor transfer station. AISI6 estimated an emission factor
of 0.13 Ib/ton of coke for a conveyor transfer station. Also AISI6 discovered
an emission factor range from the literature of 0.04 to 0.96 Ib/ton coal
for general coal handling. Speight7 estimated a value of 1.0 Ib/ton for
general coal handling.
In connnection with MRI's emission factor development program,2 limited
testing of the effects of a chemical dust suppressant was also conducted.
Coherex® (a petroleum-based emulsion) was used to treat a dirt/slag surfaced
service road traveled by light- and medium-duty vehicles at an integrated
iron and steel plant. Coherex® was applied at 10% strength in water.
Figure 1 shows a plot of measured dust control efficiency as a function
of the number of vehicle passes following application of the road dust suppres-
sant. Control efficiency was calculated by comparing controlled emissions
with uncontrolled emissions measured prior to road surface treatment. As
indicated, the effectiveness of the road dust suppressant was initially high
but began to decay with road usage. It should also be noted that the apparent
performance of Coherex® was negatively affected by tracking of material from
the untreated road surface connected to the 100-m treated segment.
Figure 1 also shows the results obtained from the similar testing of
another chemical dust suppressant at a taconite mine.8 TREX (ammonium)
lignin sulfonate--a water soluble by-product of papermaking) was applied to
the waste rock aggregate comprising the surface of a haul road. A 20 to
25% solution of TREX in water was sprayed on the road at a rate of 0.08
gal./sq yard of road surface.
7
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EFFECTIVENESS OF ROAD DUST SUPPRESSANTS
00
100
90
U 80
Z
UJ
U
4- 70
O
o;
»—
O
U
60
50
40
VEHICLE TYPE
DUST SUPPRESSANT
O Haul Truck
A Light Duty Vehicles
Lignin Sulfonate
Co he rex
100 120 140 160 180 200 220 240 260
VEHICLE PASSES FOLLOWING TREATMENT
280 300
Figure 1. Effectiveness of road dust suppressants.
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Once again the effectiveness of the dust suppressant was found to be
initially high, but decayed with road usage. According to taconite mine
personnel, the binding effect of TREX can be partially restored by the addi-
tion of water to the road surface.
2.2 METHODOLOGY FOR MORE EXTENSIVE PLANT SURVEYS
In order to gather more extensive and reliable data on source extents,
correction parameters and control practices for open dust sources within
integrated iron and steel plants, a questionnaire was designed in the form
of materials handling flow charts to be completed for specific plants.
The flow charts displayed several alternate handling schemes for the
following materials:
1. Coal
2. Iron ore pellets
3. Unagglomerated iron ore
4. Limestone/dolomite
5. Sinter, nodules, and briquettes
6. Coke
7. Sinter input (flue dust, iron ore, and coke fines)
8. Slag
The completed flow charts for a specific plant provides information
on: (a) the materials handling routes used at the plant, (b) the amount of
material passing through each handling step, (c) physical characteristics
of the handling equipment (e.g., bucket size, drop height, etc.), and (d)
the handling steps that are controlled and the type of control utilized.
Through the assistance of the American Iron and Steel Institute (Mr. John
Barker, Chairman of the AISI Fugitive Emissions Committee, and Mr. William
Benzer), the following companies agreed to complete the materials handling
flow charts for the indicated plants:
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Armco Steel, Incorporated
Middletown Works
Houston Works
Interlake, Incorporated
Chicago Plant (coke ovens and blast furnace)
Works at Riverdale (BOFs)
Bethlehem Steel Corporation
Burns Harbor
Sparrows Point
National Steel Corporation
River Rouge Plant (coke ovens and blast furnaces)
Works at Ecorse (BOFs and EAFs)
Works at Granite City
U.S. Steel Corporation
Geneva Works
Gary Works
Republic Steel Corporation
Cleveland District Plant
Jones and Laughlin Steel Corporation
Aliquippa Works
Indiana Harbor Works
10
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At the time of the writing of this report, most of the completed flow
charts had been received. Appendix A gives an example of materials handling
data compiled from the charts for two plants.
2.3 UPDATED EMISSIONS INVENTORY
The completed materials handling flow charts for the 14 plants will
provide input data for a more representative industry-wide emissions inven-
tory of open dust sources. Pending the compilation of data from the flow
charts, the preliminary inventory developed earlier was updated by using the
revised emission factors for unpaved roads, paved roads, and continuous drop
operations, as developed in Reference 2.
The updated inventory, shown in Table 2, has the same features as the
inventory published earlier. Vehicular traffic on unpaved surfaces accounts
for over 71% of the total open dust source emissions while batch and continu-
ous drop operations combine for less than 5% of the total. This inventory
will be further refined by incorporation of the results of the 14 plant sur-
veys .
Because the data base on the field performance of control measures for
open dust sources is so small as to be insignificant, control measure testing
should be distributed in relation to the magnitude of uncontrolled emissions.
According to Table 1, testing should focus on control measures applicable
to:
Unpaved roads
Paved roads
Storage pile maintenance
Storage pile wind erosion
• Unpaved parking lots
Conveyor transfer stations
Exposed area wind erosion
11
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TABLE 2. PRELIMINARY INVENTORY OF OPEN DUST SOURCE CONTRIBUTIONS TO SUSPENDED PARTICULATE EMISSIONS
Source
1976 Nationwide suspended
particulate emission rate
for the iron and steel industry
Uncontrolled!/
(tons/yr)
Percent of
total emissions
Vehicular traffic on unpaved surfaces
Unpaved roads
Storage pile maintenance
Unpaved parking lots
Vehicular traffic on paved surfaces
Batch drop operations
Loaders
Railcars
Trucks
Gantry/clamshell
Continuous drop operations
Stackers
Conveyor transfer stations
Bucket wheels
Wind erosion
Storage piles
Exposed areas
50,100
9,270
3,350
11,300
13
35
9
26
122
3,840
38
6,500
3,110
87.700
71.5
12.9
0.1
4.5
11.0
£/ Except that natural control due to precipitation is included.
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Based on preliminary analysis of the materials handling flow charts,
uncontrolled emissions from conveyor transfer stations are probably larger
than the value given in Table 1 because the number of transfer stations ex-
ceeds the average value of two per material that was assumed in the calcula-
tions .
2.4 SAMPLING AND ANALYSIS METHODS
Fugitive emissions are especially difficult to characterize for the
following reasons.
1. Emission rates have a high degree of temporal variability.
2. Emissions are discharged from a wide variety of source configura-
tions .
3. Emissions are comprised of a wide range of particle sizes, includ-
ing coarse particles which deposit immediately adjacent to the source.
The scheme for quantification of emission factors must effectively deal with
these complications.
Three basic techniques have been suggested.9
1. The quasi-stack method involves capturing the entire emissions stream
with enclosures or hoods and applying conventional source testing techniques
to the confined flow.
2. The roof monitor method involves measurement of concentrations and
air flows acress well defined building openings such as roof monitors, ceil-
ing vents, and windows.
3. The upwind/downwind method involves measurement of upwind and down-
wind air quality, utilizing ground-based samplers under known meterorlogical
conditions and calculation of source strength with atmospheric dispersion
equations.
13
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Of these techniques, only the upwind/downwind method is suitable for applica-
tion to open dust sources.
As .an alternative to the upwind/downwind method for quantification of
source-specific emission factors for open dust sources, MRI developed the
"exposure profiling" technique, which uses the isokinetic profiling concept
that is the basis for conventional source testing.10 Exposure profiling
consists of the direct measurement of the passage of airborne pollutant im-
mediately downwind of the source by means of simultaneous multipoint sampl-
ing over the effective cross section of the fugitive emissions plume. This
technique uses a mass-balance calculation scheme similar to EPA Method 5
stack testing rather than requiring indirect calculation through the appli-
cation of a generalized atmospheric dispersion model. Exposure profiling
is compared with conventional upwind/downwind sampling in the subsections
below.
2.4.1 Open Dust Source Quantification by Upwind/Downwind Method
The upwind/downwind method has frequently been used to measure fugitive
particulate emissions from open (unconfinable) sources, although only a few
studies have been conducted in the integrated iron and steel industry. Typi-
cally, particulate concentration samplers (most often high-volume filtration
samplers) are positioned at a considerable distance from the source (for
example, at the property line around an industrial operation) in order to
measure the highest particulate levels to which the public might be exposed.
The calculation of the emission rate by dispersion modeling is oftern treated
as having secondary importance, especially because of the difficult problem
of identifying the contributions of elements of the mix of open sources (and
possibly fugitive emissions discharged from process installations).
While the above strategy is useful in characterizing the air quality
impact of an open source mix, it has significant limitations with regard to
control strategy development. The major limitations are as follows:
14
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1. Overlapping of source plumes precludes the determination of source-
specific contributions on the basis of particulate concentration alone.
2. Air samplers with poorly defined intake flow structure (including
the conventional high-volume sampler) exhibit diffuse cutoff size character-
istics for particle capture, which tend "to be affected by wind conditions.11
3. Uncalibrated atmospheric dispersion models introduce the possibil-
ity of substantial error (a factor of three12) in the calculated emission
rate, even if the stringent requirement of unobstructed dispersion from a
simplified source configuration is met.
The first two limitations are not a direct consequence of the upwind/
downwind method but of the way it is used. These limitations could be re-
moved by using samplers designed to capture all or a known size fraction of
the atmospheric particulate, and by designing sampler placement to isolate
the air quality impact of a well defined source operation.
However, there would remain the need to improve method accuracy by cali-
bration of the dispersion model for the specific conditions of wind, surface
roughness, and so on, which influence the near-surface dispersion process.
This need is evident from the significant size of the variation in model-
calculated emission rates for aggregate process operations, based on data
from individual samplers operated simultaneously at different downwind loca-
tions.13 The suggested use of tracers for this purpose is complicated by
the characteristically diffuse and variable nature of an open dust source
and the need for a polydisperse tracer test dust approximating the particle
size distribution of the source emissions.
2.4.2 Open Dust Source Quantification by Exposure Profiling Method
As stated above, the exposure profiling method was developed by MRI3
to measure particulate emissions from specific open sources, utilizing the
isokinetic profiling concept which is the basis for conventional source test-
ing. For measurement on nonbuoyant fugitive emissions, sampling heads are
15
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distributed over a vertical network positioned just downwind (usually about
5 m) from the source. Sampling intakes are pointed into the wind and sampl-
ing velocity is adjusted to match the local mean wind speed, as monitored
by distributed anemometers. A vertical line grid of samplers is sufficient
for measurement of emissions from line or moving point sources while a two-
dimensional array of samplers is required for quantification of area source
emissions.
Grid Size and Sampling Duration--
Sampling heads are distributed over a sufficiently large portion of
the plume so that vertical and lateral plume boundaries may be located by
spatial extrapolation of exposure measurements. The size limit of area
sources for which exposure profiling is practical is determined by the
feasibility of erecting sampling towers of sufficient height and number to
characterize the plume. This problem is minimized by sampling when the wind
direction is parallel to the direction of the minimum dimension of the area
source.
The size of the sampling grid needed for exposure profiling of a particu-
lar source may be estimated by observation of the visible size of the plume
or by calculationof plume dispersion. Grid size adjustments may be required
based on the results of preliminary testing.
Particulate sampling heads should be symmetrically distributed over
the concentrated portion of the plume containing about 90% of the total mass
flux (exposure). For example, if the exposure from a point source is normally
distributed, as shown in Figure 2, the exposure values measured by the sam-
plers at the edge of the grid should be about 25% of the center line exposure.
Sampling time should be long enough to provide sufficient particulate
mass and to average over several units of cyclic fluctuation in the emission
rate (for example, vehicle passes on an unpaved road). The first condition
is easily met because of the proximity of the sampling grid to the source.
16
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Virtual Point Source
X
Exposure
Profiles
Wind Direction
Figure 2. Example exposure profiling arrangement.
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Assuming that sample collection media do not overload, the upper limit
on sampling time is dictated by the need to sample under conditions of rela-
tively constant wind direction and speed. In the absence of passage of weather
fronts through the area, acceptable wind conditions might be anticipated to
persist for a period of 1 to 6 hr.
In order to obtain an accurate measurement of airborne particulate ex-
posure, sampling must be conducted isokinetically, i.e., flow streamlines
enter the sampler rectilinearly. This means that the sampling intake must
be aimed directly into the wind and, to the extent possible, the sampling
velocity must equal the local wind speed. The first condition is by far
the more critical.
Based on replicate exposure profiling of open dust sources under vary-
ing conditions of source activity and properties of the emitting surface,
emission factor formulae have been derived that successfully predict test
results with a maximum error of 20%.3 These formulae account for the frac-
tion of silt (fines) in the emitting surface, the surface moisture content,
and the rate of mechanical energy expended in the process which generates
the emissions. Based on the above results, the accuracy of exposure profil-
ing is considerably better than the ± 50% range given for the upwind/downwind
method with site-specific dispersion model calibration.9
2.4.3 Methods for Particle Sizing
High-volume cascade impactors with glass fiber impaction substrates,
which are commonly used to measure particle size distribution of atmospheric
particulate, may be adapted for sizing of fugitive particulate. A cyclone
preseparator (or other device) is needed to remove coarse particles which
otherwise would be subject to particle bounce within the impactor causing
fine particle bias.14 Once again, the sampling intake should be pointed
into the wind and the sampling velocity adjusted to the mean local wind
speed by fitting the intake with a nozzle of appropriate size.
18
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The recently developed EPA version of the dichotomous sampler,15 which
is virtually free of particle bounce problems is useful for quantification
of fine particle mass concentrations. However, this device operates at a
low flow rate (1 cu m/hr) yielding only 0.024 mg of sample in 24 hr for each
10 (Jg/m3 of TSP concentration. Thus, an analytical balance of high precision
is required to determine mass concentrations below and above the fine particu-
late (2.5 fjm) cutpoint (the minimum in the typical bimodal size distribution
'of atmospheric particulate). In addition, the dichotomous sampler was designed
to have a 15 [Jm cutpoint for capture of airborne particles (the upper size
limit for inhalable particulate based on unit density); however, recent wind
tunnel studies have shown that this cutpoint is wind sensitive.16
The size-selective inlet for a standard high-volume sampler9 is also
designed to capture particles smaller than 15 |Jm in aerodynamic diameter.
This unit is much less wind sensitive than the dichotomous sampler16 but it
does not provide a cutpoint at 2.5 (Jm. However, it can be adapted for use
with a high volume cascade impactor to obtain an IP size distribution.
19
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3.0 CONTROL TECHNOLOGY FOR OPEN DUST SOURCES
A number of publications are available which describe in some level of
detail the various control techniques which have been applied to open dust
sources. A bibliography of such literature resources is presented in Appen-
dix B.
3.1 TYPES OF CONTROL TECHNIQUES
Standard preventive techniques for the control of open dust sources
may be divided into three basic types:
1. Maintenance of high moisture levels in the exposed surface.
2. Chemical stabilization of the exposed surface.
3. Protection of the exposed surface by physical emplacements.
Each of these control method types is discussed briefly below.
Decades of research on the physical principles of soil loss by wind
erosion have quantified the dependence of dust generation on moisture con-
tent.17'18 This may be approximated as an inverse square relationship.
Maintenance of high moisture levels in exposed surfaces associated with open
dust sources is very effective in controlling dust emissions. This may be
accomplished by periodic or continuous watering using fixed or mobile spray
systems. Moisture penetration and.or retention may be enhanced by the use
of: (a) chemical wetting agents or foams, or (b) dessicant materials such
as calcium chloride.
20
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Chemical stabilization of an exposed dusty surface to control dust emis-
sions is accomplished by the direct application of chemical agents to the
surface. These agents bind the loose surface particulate which otherwise
would be subject to entrainment into the atmosphere by the forces of wind
or machinery. If the surface is subject to large mechanical stresses (for
example, as would be the case for an unpaved haul road), it is important
that the base below the surface be strong enough to absorb the stresses.
Otherwise, the surface crust may be broken and become uneffective in con-
trolling dust emissions.
Because the rate of dust generation by wind erosion increases substan-
tially with wind speed (above the "threshold" value), control of wind erosion
can be effected by reducing the wind speed near the exposed surface in rela-
tion to the ambient wind. This may be accomplished by enclosures or other
forms of windbreaks.
Nonpreventive control of emissions from open dust sources entails the
capture of emissions usually by some combination of hooding and enclosures.
Water sprays are not very effective for this purpose, although recent re-
search efforts have shown that charged fogs are substantially more effective.
Table 3 lists current research studies dealing with control technology for
open dust sources.
3.2 EFFICIENCY AND COST OF CONTROL
Ideally, the selection of "best" controls for a particular open dust
source should be based on cost-effectiveness evaluation of each of the po-
tentially applicable control techniques. Unfortunately, the data for these
evaluations are sparce and generally do not reflect the wide variability of
source conditions.
Cost and estimated efficiency data on open dust source controls for
the integrated iron and steel industry have been compiled by Bohn et al.1
These costs included initial and annual operating costs of several control
21
-------
TABLE 3. RECENT AND CURRENT INVESTIGATIONS OF CONTROL TECHNOLOGY
APPLICABLE TO OPEN DUST SOURCES
1. Paved and unpaved road emissions, Midwest Research Institute,
Dr. Chatten Cowherd, EPA Contract No. 68-02-2814.
2. Improved street sweepers for paved roads, Air Pollution Technology,
Dr. Richard Parker, EPA Contract No. 68-02-3148.
3. Road carpet for unpaved roads, Monsanto, Mr. Keith Tackett, EPA
Contract No. 68-02-3107.
4. Windscreening and chemical additives for area sources, The Research
Corporation of New England, Mr. Dennis Martin, EPA Contract No. 68-
02-3115.
5. Charged fog for construction sight activity and front-end loaders,
Aerovironment, Mr. John Kinsey, EPA Contract No. 68-02-3145.
6. Dust control for haul roads, Midwest Research Institute, Mr. Russel
Bohn, BuMines Contract No. J0285015.
7. Emission factors and control technology for fugitive dust from coal
mining sources, PEDCo/MRI, Mr. Ken Axetell/Dr. Chatten Cowherd, EPA
Contract No. 68-02-2585.
8. Fugitive emissions from integrated iron and steel plants, Midwest
Research Institute, Mr. Russel Bohn, EPA Contract No. 68-02-2120
(see EPA-600/2-78-050, March 1978).
22
-------
options applied to each source. As part of the same study, cost-effective-
ness evaluation was performed for a typical process source of fugitive emis-
sions (electric arc furnace) and for several open dust sources (see Table
4).
Recently, Cooper et al.19 have compiled cost-effectiveness data for
the control of emissions from unpaved roads by paving, oiling, watering,
calcium chloride, and speed control. However, details on the application
frequency and intensity of dust suppressants is sketchy.
Another recent compilation of cost-effectiveness data for the control
of emissions from unpaved mining haul roads and access roads has been pre-
pared by Bohn et al.20 As shown in Table 5, the product control efficiencies,
although largely estimates, are properly tied to prescribed levels of appli-
cation density and frequency.
As illustrated in the above examples, the most serious data gap affect-
ing cost-effectiveness evaluation is the nearly total lack of actual field
data on control method performance, especially for the preventive control
techniques. Table 6 illustrates this point by summarizing the reported ef-
ficiencies for control of wind erosion from storage piles; all but one of
the efficiency values are estimates.
Because of the finite durability of all control techniques, ranging
from hours (watering) to years (paving), it is essential to tie an efficiency
value to a frequency of application (or maintenance). For measures of lengthy
durability, such as paving of unpaved roads, the maintenance program required
to sustain control effectiveness should be indicated. One likely pitfall
to be avoided is the use of field data on a freshly applied control measure
to represent the lifetime of the measure.
3.3 CURRENT INDUSTRY CONTROL PRACTICES
Analysis of the materials handling flow charts for the 14 integrated
iron and steel plants indicate that a number of control techniques are being
23
-------
TABLE 4. COST EFFECTIVENESS OF FUGITIVE EMISSIONS. CONTROL METHODS
Source
Process
EAF
Open dust
Storage pile
activities
Load-In/
load -out
Wind erosion
from storage
piles
(lump iron ore )
Control method
Canopy hoods
Utilize mobile
stacker /reclaimer
combination rather
than front-end
loader activity
for pellet piles
Watering
Chemical stabilizers
(Coherex 207. solution)
/fEstlraate/f Annual Iced Annual
\ȣojjt*^l investment Ranking operating
efficiency cost . order cost
70 1.44 [8] NA
80 8.68 [9] NA
80 0.02 [4] NA
97 0.02 [4] 0.008
Ranking
order
CO
Vehicular traffic
Unpaved roadways
Watering
Road oil
Oil and double chip
Chemical stabilizers
(Coherex)
Paving
50
75
80
90
90
0.006
0.006
0.02
0.02
0.08
[2]
C23
03
[5]
0.06
0.4
0.03
0.08
0.08
C7]
CO
[6]
Paved roadways
Wind erosion
from exposed
areas
Broom sweeping
Vacuum sweeping
Road flushing
Watering. .
Chemical stabilizers-
Oiling
Paving with cleaning
70
75
30
50
70
30
95
0.005
0. 01
0.006
0.21
0.16
0.02
0.01
(0
[3]
[2]
[7]
[6]
l~4l
[3] •
0.05
0.05
0.05
0.01
0.05
NA
NA
f4l
[5]
0]
[2]
[4]
.
-
MA - Not available.
£/ Dollar per pound reduction aC fine partlculate per year.
b/ No specific chemical stabilizer given; 707. control efficiency Is assumed to be the average of all
available chemical stabilizers for this control purpose.
24
-------
TABLE 5. CONTROL EFFICIENCIES OF ROAD DUST SUPPRESSANTS
NJ
Ul
Parameter
Control efficiency
Maul road
Access road
Application density
Maul road
Initial
Suhse<|iieut
Access road
Ligniii sul fonate
75%
70%
2 gal ./yd2 of 15%
solution
Same
2. It gal ./yd2 of
12% solution
Coh<; rex®
75%
. 70%
2 gal./yd2 of 1:4
di lution
0.5 gal./yd2 of
1 : 10 diultion
1 gal./yd2 of
1 :7 dilution
Calcium chloride
75%
70%
1 gal./yd2 of 30%
solution
0.3 gal./yd2 of
30% solution
0.6 gal. /yd2 of
of 30% solution
Road watering
75%
70%
0.05 gal ./yd2
Same
0.05 gal ./yd2
Wetting agents
75%
70%
0.05 gal ./yd2
Same
0.05 gal./yd2
Ap|il icatioii Frequency/
Year
Maul road
Access road
Summer: Hourly Summer: Daylight In
Spring anrl Fall: Every 2 lir Spring and Fall: Every 2
daylight hr
Winter: Once per day Winter: Every other day
Summer: Every 2 hr Summer: Every 2 daylight
In
Spring and Fall: Every Spring and Fall: Every 3
daylight hr
Winter: Once every 2 days Winter: Once per week
-------
TABLE 6. REPORTED EFFICIENCIES FOR CONTROL OF WIND EROSION
OF STORAGE PILES
Control method
Reported
efficiency Reference
(%) -(year)*
Method of determination
Watering - periodic 50 22 (1976)
sprinkling 23 (1977)
Watering - wind-activated 80 1 (1978)
sprinkler system
Chemical wetting agents 90
or foam
Continuous chemical spray 90 22 (1976)
onto input material 23 (1977)
Surface crusting agents Up to 99 1 (1978)
Enclosure 95 to 99 23 (1977)
Storage silos 100 1 (1978)
Vegetative windbreak 30 1 (1978)
Low pile height 30 1 (1978)
Ref. 21 (1973) - estimate
Ref. 22 (1976) - estimate
Estimate
23 (1977) Estimate
Vendor brochure -
estimate
Ref. 24 (1974) - wind
tunnel tests
Estimate
Estimate
Estimate
Estimate
* Reference 25 cites References 23 and 1.
26
-------
applied to open dust sources at one or more locations. These are summarized
in Table 7.
In addition, plans are underway at one plant to apply Coherex® to unpaved
roads and to the shoulders and berms of paved roads and to vegetate bare
ground areas. Presumably some form of cost-effectiveness analysis was under-
taken in the selection and implementation of these control measures.
3.4 SELECTION OF BEST CONTROLS
The selection of best controls was based on the extent of use within
the industry and on the results of the preliminary cost-effectiveness evalu-
ations cited above. The "best" controls are reviewed for each source cate-
gory in the paragraphs below.
The best control methods selected for unpaved roads are: application
of Coherex®, watering, and application of calcium chloride. All three of
these techniques have been used in the integrated iron and steel industry.
These techniques have'favorable cost-effectiveness ratios, although recent
increases in the price of calcium__chloride have made it less competitive.
The best control methods selected for paved roads are flushing and vacuum-
ings. These techniques are used in combination within the steel industry.
Preliminary evaluation based on estimated control efficiencies shows that
these two methods have similar cost-effectiveness ratios. At one plant,
Coherex® is being applied to unpaved shoulders and berms of paved roads to
reduce emissions from these areas and to prevent the rapid build-up of sur-
face loadings on the paved road.
Watering (possibly with the addition of wetting agents) has been selected
as the best method to control emissions from storage pile maintenance and
wind erosion. Because of the active nature of the surfaces involved, chemi-
cal stabilization is not effective. Also, the use of physical windbreaks
characteristically prevents the freedom of access to the pile which is nec-
essary to maintain adequate material flows into and out of storage.
27
-------
TABLE 7. SUMMARY OF FUGITIVE EMISSION CONTROLS (BY PLANT)
N3
OO
Source
I . Unpaved roads
II. Paved roads
III. Storage pile (maintenance
Control practice
A.
B.
A.
B.
A.
Watering
Oiling
Flushing
Sweeping
Watering
Plant(s)
Armco-Houston Works
J&L Steel-Aliquippa Works
None reported
Armco-Houston Works (also
1. Armco-Houston Works
•
watering)
and wind erosion)
IV. Unpaved parking lots
V. Conveyor transfer station
B. Chemical sprays
None indicated
A. Enclosures
VI. Exposed Area Wind Erosion
B. Water sprays
C. Chemical sprays
Vegetation
2. Bethlehem Steel-Burns Harbor
3. U.S. Steel-Gary Works
4. U.S. Steel-Geneva Works
1. Bethlehem Steel-Burns Harbor
2. National Steel-Great Lakes Divi-
sion
1. Armco-Middletown Works
2. Bethlehem Steel-Burns Harbor
3. Interlake Steel-Chicago
4. J&L Steel-Aliquippa Works
5. U.S. Steel-Geneva Works
1. Armco-Middletown Works
2. Bethlehem Steel-Burns Harbor
3. U.S. Steel-Geneva Works
1. Bethlehem Steel-Sparrows Point
None reported
-------
The best method to control emissions from unpaved parking lots and other
exposed areas subject to traffic disturbance is through the application of
a chemical stabilizer. Such areas usually have a well compacted subsurface
to allow for mechanical stress absorbance without break up of the stabiliz-
ing agent. Moreover, it is. usually not practical to water large areas that
are poorly accessible.
Conveyor transfer stations are best controlled by enclosure and ducting
of the captured dust to a removal device prior to recycle or disposal. Water
sprays on conveyed material is a preventive method for controlling dust.
Both of these method are widely used in the integrated iron and steel indus-
try.
29
-------
4.0 RECOMMENDATIONS FOR PHASE II
This section presents our recommendations for a field testing program
to supply the data needs for cost-effectiveness evaluation of the best con-
trols for open dust sources within the integrated iron and steel industry.
4.1 DATA NEEDS
The data needs for control cost-effectiveness evaluation fall into the
following categories:
Emission factors for total suspended particulate (TSP), inhalable
particulate (IP), and fine particulate (FP) with and without application of
the control technique.
Emission factor correction parameters (see Table 8) for uncontrolled
and controlled test source segment.
Control application density and time after application for which
controlled testing was performed.
Investment and operating costs of dust control measure.
The procedures for development of size specific emission factors for
open dust sources are outlined in the next section, as are procedures for
on-site correction parameter determination. Control application density
should be expressed in units similar to that found in Table 5.
Cost data for the control technique being tested should be obtained
from the steel plant where testing is performed. These data should include:
(a) annualized costs of equipment purchase and installation, and (b) annual
30
-------
TABLE 8. PARAMETERS AFFECTING EMISSION FACTORS FOR OPEN DUST SOURCES
Generic source category
Material
Equipment
Climate
Vehicular traffic on unpaved
surfaces
Vehicular traffic on paved
surfaces
Wind erosion of storage piles
and exposed areas
Surface silt content
Surface silt content
Surface loading
Surface erodibility
Surface silt content
Surface moisture content
Vehicle speed
Vehicle weight
Number of wheels
Vehicle weight
Wind speed
-------
operating costs. The annualized investment costs should take into account
the initial costs, the life time of the equipment, interest and taxes. To
calculate the total annualized cost, the average annual cost of operation
is added to the product of the initial capital investment and the capital
recovery factor. The capital recovery factor is the percentage of the ini-
tial investment which would be paid yearly on a loan or mortgage.
4.2 SAMPLING AND ANALYSIS PROCEDURES
This section describes the field sampling and laboratory analysis pro-
cedures that will be used to quantify (a) particulate emission rate and par-
ticle size distribution, (b) meteorological conditions, and (c) process con-
ditions. The quality assurance program is also discussed.
4.2.1 Mechanically Generated Particulate Emissions
Table 9 lists the equipment that will be used to sample particulate
emissions from unpaved roads, paved roads, storage pile maintenance, and
unpaved parking lots. Equipment locations and intake heights are specified.
The primary tool for quantification of emission rate will be the exposure
profiler, operated in the moving point source mode.
The exposure profiler (Figure 3) consists of a portable tower (4 to 6
m height) supporting an array of four sampling heads. Each sampling head
is operated as an isokinetic exposure sampler directing passage of the flow
stream through a settling chamber (trapping particles larger than about 50
|jm in diameter) and then upward through a standard 8 by 10 in. glass fiber
filter positioned horizontally. Sampling intakes are pointed into the wind,
and sampling velocity of each intake is adjusted to match the local mean
wind speed, as determined prior to each test. Throughout each test, wind
speed is monitored by recording anemometers at two heights, and the vertical
profile of wind speed is determined by assuming a logarithmic distribution.
Normally, the exposure profiler is positioned at a distance of 5 m from the
downwind edge of the road.
32
-------
TABLE 9. SAMPLING EQUIPMENT FOR OPEN DUST SOURCES
Location
Distance from
source (m)
Equipment
Intake height
(m)
Upwind
5-10
Downwind
1 Standard Hi-Vol
1 Hi-Vol with 15 pm inlet*
1 Hi-Vol with 15 |Jm inlet
1 Continuous wind monitor
1 MRI exposure profiler with
four sampling heads
1 Standard Hi-Vol
2 Hi-Vol cascade impactors
with 15 |Jm inlet or
cyclone precollector
2 Warm wire anemometer
2.0
2.0
4.0
4.0
1.0
2.0
3.0
4.0
2.0
1.0
3.0
1.0
3.0
a A particle sizing unit will be operated in place of this unit for one run
in each 3-run test series.
b This unit will be used only on tests of controlled emissions.
33
-------
Flow Control Circuit Box
Warm-Wire
Anemometer
Electronic Readout/Control Unit-
Figure 3. MRI exposure profiler.
34
-------
Particle size distribution will be measured using a high volume cascade
impactor preceeded either by a size-selective intake (15 Mm cutpoint) or a
cyclone preseparator (10 |Jm cutpoint). The first option provides for direct
measurement of inhalable particulate, but requires total (isokinetic) particu-
late concentrations from the exposure profiler for the calculation of the
particle size distribution of total airbo'rne particulate matter in the emis-
sion plume. The second option provides for direct isokinetic measurement
of the total particle size distribution but requires extrapolation from the
cyclone cutpoint (10 |jm) to determine IP concentrations. In either case,
particle sizing samplers will be operated along side of the exposure profiler
at two heights (usually the first and third profiler levels) in the fugitive
dust plume.
Also, a high-volume sampler with a size-selective inlet (Hi-Vol/SSI)
will be operated at the upwind monitoring station to determine the IP frac-
tion of the background particulate. This will be replaced with a particle
sizing sampler for one run in each 3-run test series. For tests of control-
led emissions, a second Hi-Vol/ SSI will be operated at a higher elevation
to determine the change of background IP concentration with height. Conven-
tional high-volume samplers will be operated at one height both upwind and
downwind of the source.
Table 10 lists the critiera for suspending or terminating an exposure
profiling test. Some of these criteria address the wind conditions in rela-
tion to the requirements for isokinetic sampling. Testing may also cease
if rainfall ensues (reducing emissions to negligible levels) or if light is
insufficient for safe operation. The final criterion deals with an unaccept-
able change in source condition.
Sampling time will be sufficient to provide sufficient particulate mass
and to average over several units of cyclic fluctuation in the emission rate,
e.g., vehicle passes on an unpaved road. Because of the proximity of the
sampling grid to the source, the first condition is easily met for testing
of uncontrolled sources. However, testing of controlled sources may require
a sampling period of up to 4 hours to provide sufficient sample mass.
35
-------
TABLE 10. CRITERIA FOR SUSPENDING OR TERMINATING AN EXPOSURE PROFILING TEST
A test will be suspended or terminated if:—
1. Rainfall ensues during equipment setup or when sampling is in progress.
2. Mean wind speed during sampling moves outside the 4 to 20 mph accept-
able range for more than 20% of the sampling time.
3. The angle between mean wind direction and the perpendicular to the path
of the moving point source during sampling exceeds 45 degrees for more
than 20% of the sampling time.
4. Mean wind direction during sampling shifts by more than 30 degrees from
profiler intake direction.
5. Mean wind speed approaching profiler sampling intake is less than 80% or
greater than 120% of intake speed.
6. Daylight is insufficient for safe equipment operation.
7. Source condition deviates from predetermined criteria,(e.g., occurrence
of truck spill).
a/ "Mean" denotes a 15-min average.
36
-------
Emissions from conveyor transfer stations will be measured by standard
stack sampling methods using the quasi-stack method as described in Reference
9. This will necessitate the testing of a well enclosed station with an
adequate run of ducting. The uncontrolled emission rate will be determined
by sampling the ducted conveyor emissions upstream of the particulate removal
device.
4.2.2 Wind-Generated Particulate Emissions
A portable wind tunnel fabricated by MRI (Figure 4) will be used to
measure emissions from wind erosion of storage piles or other exposed areas.
The wind tunnel consisted of a two-dimensional 5:1 contraction section, an
open-floored test section, and a roughly conical diffuser. The test section
of the tunnel is placed directly on the surface to be tested (30 cm x 2.4
m), and the tunnel centerline air flow is adjusted to predetermined veloci-
ties up to 18 m/sec (40 mph), as measured by a pitot tube at the downstream
end of the test section.
An emissions sampling module2 has been designed and fabricated for use
with the pull-through wind tunnel in measuring particulate emissions and
particle size distributions generated by wind erosion. As shown in Figure
4, the sampling module is located between the tunnel outlet hose and the
fan inlet. The sampling train, which is operated at 34 m3/hr (20 cfra),
consists of a tapered probe, cyclone precollector, parallel-slot cascade
impactor, back-up filter, and high volume motor. Interchangeable probe
tips are sized for isokinetic sampling at predetermined cross-sectional
average velocities within the tunnel test section.
4.2.3 Site/Process Conditions
In addition to the measurements of wind speed obtained at two heights
on the profiling tower, a meteorological instrument will also be located at
the background monitoring station. Continuous measurements of wind speed
and direction at a height of 4 m will be recorded at the upwind site.
37
-------
U)
oo
Schedule 40 Pipe
20cm I.D.
(Aluminum)
— Toil Section
Figure 4. MRI portable and tunnel.
-------
In order to determine the properties of aggregate materials being dis-
trubed by the action of machinery or wind, representative samples of the
materials will be obtained for analysis in the laboratory. Unpaved and paved
roads will be sampled by vacuuming and broom sweeping to remove loose material
from lateral strips of road surface extending across the traveled portion.
Storage piles will be sampled to a depth exceeding the size of the largest
aggregate pieces. If possible, samples of conveyed material will be taken
directly from the conveyer upstream of the transfer station being tested.
Additional detail on the sampling methods is provided elsewhere.2
Throughout a test of traffic-generated emissions, a vehicle count will
be maintained by a pneumatic-tube traffic counter. Periodically (e.g., dur-
ing 15 min of each hour) vehicle mix will be determined by compiling a log
of vehicles passing the test point segregated by vehicle type (usually the
number of axles and wheels). Vehicle speeds will be measured with a radar
gun. Data on vehicle weight will be obtained from plant personnel.
4.2.4 Sample Handling and Analysis
To prevent dust losses, the collected samples of dust emissions will
carefully be transferred at the end of each run to protective containers
within the MRI instrument van. Glass fiber filters from the MRI exposure
profiler and from standard Hi-Vol units and impaction substrates will be
folded and placed in individual envelopes. Dust that collects on the inte-
rior surfaces of each exposure probe will be rinsed with distilled water
into separate glass jars. Dust will be transferred from the cyclone precol-
lector in a similar manner.
Dust samples from the field tests will be returned to MRI and analyzed
gravimetrically in the laboratory. Glass fiber filters and impaction sub-
strates will be conditioned at constant temperature and relative humidity
for 24 hr prior to weighing, the same conditioning procedure used before
taring. Water washes from the exposure profiler intakes and the cyclone
precollectors will be filtered after which the tared filters will be dried,
conditioned at constant humidity, and reweighed.
39
-------
After the gross samples of surface particulate are taken to the labora-
tory, they are prepared for moisture and silt analysis. The first step con-
sists of reducint the sample to a workable size. A riffle sample splitter
should be used for this purpose, following ASTM Method D2013-72, "Standard
Method of Preparing Coal Samples for Analysis." The final split should pro-
duce a sample mass not exceeding 1,000 g.
The reduced samples of surface particulate will be dried to determine
moisture content and screened to determine the weight fraction passing a
200 mesh screen, which gives the silt content. A conventional shaker will
be used for this purpose. That portion of the material passing through the
200 mesh screen will be analyzed to determine the density of potentially
suspendable particules. The procedures for moisture and silt analysis, which
comform to ASTM Method C136-76, are summarized in Tables 11 and 12.
4.3 QUALITY ASSURANCE PROGRAM
4.3.1 Sampling and Analysis of Airborne Particulate
The quality assurance program for particulate sampling and analysis
will include (a) activities designed to demonstrate that measurements are
made within acceptable control conditions, and (b) assessment of sampling
and analysis data for precision and accuracy. The QA program for quantifi-
cation of fugitive particulate emissions meets or exceeds requirements speci-
fied in "Quality Assurance Handbook for Air Pollution Measurement Systems,
Volume II -Ambient Air Specific Methods" (EPA 600/4-77-027a) and "Ambient
Monitoring Guidelines for Prevention of Significant Deterioration" (EPA
450/2-78-019).
A variety of particulate sampling devices will be utilized in the study
to quantify fugitive emissions by exposure profiling. Sampling devices in-
clude: standard Hi-Vol air sampling units (with and without 15 |Jm inlets),
exposure profiling systems, and Hi-Vol cascade impactors. These sampling
devices utilize filter media, impaction substrates, and cyclone catch cham-
bers to collect the sampled particulate. A certain amount of particulate
40
-------
TABLE 11. MOISTURE ANALYSIS PROCEDURES
1. Preheat the oven to approximately 110°C (230°F). Record oven tempera-
ture.
2. Tare the laboratory sample containers which will be placed in the oven.
Tare the containers with the lids on if they have lids. Record the
tare weight(s). Check zero before weighing.
3. Record the make, capacity, smallest division, and accuracy (if dis-
played) of the scale.
4. Weigh the laboratory sample in the container(s). Record the combined
weight(s). Check zero before weighing.
5. Place sample in oven and dry overnight.
6. Remove sample container from oven and (a) weigh immediately if uncovered,
being careful of the hot container; or (b) place tight-fitting lid on
the container and let cool before weighing. Record the combined sample
and container weight(s). Check zero before weighing.
7. Calculate the moisture as the initial weight of the sample and container .
minus the oven-dried weight of the sample and container divided by the
initial weight of the sample alone. Record the value.
8. Calculate the sample weight as the oven-dried weight of the sample and
container minus the weight of the container. Record the value.
41
-------
TABLE 12. SILT ANALYSIS PROCEDURES
1. Select the appropriate 8-in. diameter, 2-in. deep sieve sizes. Rec-
ommended U.S. Standard Series sizes are: 3/8 in., No. 4, No. 20,
No. 40, No. 100, No. 140, No. 200, and a pan. Comparable Tyler
Series sizes can also be utilized. .The No. 20 and the No. 200 are
mandatory. The others can be varied if the recommended sieves are
not available or if buildup on one particular sieve during sieving
indicates that an intermediate sieve should be inserted.
2. Obtain a mechanical sieving device such as a vibratory shaker or a
Roto-Tap.
3. Clean the sieves 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 (if possible) without handling the screen roughly.
4. Attain a scale (capacity of at least 1,600 g) and record make, capac-
ity, smallest division, date of last calibration, and accuracy (if
available).
5. Tare sieves and pan. Check the zero before every weighing. Record
weights.
6. After nesting the sieves in decreasing order with pan at the bottom,
dump dried laboratory sample (probably immediately after moisture
analysis) into the top sieve. 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.
7. Place nested sieves into the mechanical device and sieve for 20 min.
Remove pan containing minus No. 200 and weigh. Replace pan beneath
the sieves and sieve for another 10 min. Remove pan and weigh.
When the difference between two successive pan sample weighings
(where the tare of the pan has been subtracted) is less than 3.0%,
the sieving is complete.
8. Weigh each sieve and its contents and record the weight. Check the zero
before every weighing.
9. Collect the laboratory sample and place the sample in a separate con-
tainer if further analysis is expected.
42
-------
is also collected on interior surfaces of the sampling probe and connect
tubing which must be rinsed and filtered.
There are six main categories which a QA program for fugitive particu-
late sampling must address. They are:
* Calibration of equipment
* Filter and impaction substrate selection and preparation
* Sampling procedures
* Sampling equipment maintenance
* Laboratory analysis procedures
* Calculations and data reporting
A series of tables in EPA 600/4-77-027a presents a matrix of activities which
should be performed to satisfy the QA aspects within each of the above cate-
gories .
Tables 13 through 16 list the adaptations of the EPA requirements which
will be adopted to improve the QA aspects above minimum EPA requirements.
For example, electronic flow controllers will be used in all air sampling
devices to minimize excursions from preset flow rates.
As part of the QA program for the study, routine audits of sampling
activities will be performed. The purpose of the audits will be to demon-
strate that measurements are made within acceptable control conditions for
particulate source sampling and to assess the source testing data for preci-
sion and accuracy. Examples of items to be audited include filter weighing,
flow rate calibration, data processing and calculations. The mandatory use
of specially designed reporting forms for sampling and analysis data obtained
in the field and laboratory aid in the auditing procedure.
43
-------
TABLE 13. QUALITY ASSURANCE PROCEDURES FOR SAMPLING FLOW RATES
Activity
QA Check/Requirement
Calibration
Profilers, hi-vols, and
impactors
Dichotomous samplers
Single-Point Checks
Profilers, hi-vols, and
impactors
Dichotomous samplers
Alternative
Orifice Calibration
Calibrate flows in operating ranges
using calibration orifice every two
weeks at each regional site prior to
testing.
Calibrate flows in operating ranges
with displaced volume test meters
every two weeks at each regional site
prior to testing.
Check 25% of units with rotameter
calibration orifice or electronic
calibrator once at each site prior to
testing (different units each time).
If any flows deviate by more than 7%,
check all other units of same type and
recalibrate non-:complying units. (See
alternative below.)
Check 25% of unit with calibration
orifice once at each site prior to
testing (different units each time).
If any flows deviate by more than 5%,
check all other units and recalibrate
noncomplying units.
If flows cannot be checked at test
site, check all units every two weeks
and recalibrate units which deviate
by more than 7% (5% for dichots).
Calibrate against displaced volume
test meter annually.
44
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TABLE 14. QUALITY ASSURANCE PROCEDURES FOR SAMPLING MEDIA
Activity
QA Check/Requirement
Preparation
Inspect and imprint glass fiber media
with ID numbers.
Inspect and place teflon media (dichot
filters) in petri dishes labeled with
ID numbers.
Conditioning
Weighing
Auditing of weights
(Tare and Final)
Correction for Handling
Effects
Prevention of Handling
Losses
Calibration of
Balance
Equilibrate media for 24 hr in clean
controlled room with relative humidity
of less than 50% (variation of less
than + 5%) and with temperature bet-
ween 20 C + and 25 C (variation of
less than + 3%).
Weigh hi-vol filters and impactor
substrates to nearest 0.1 mg and weigh
dichot filters to nearest 0.01 mg.
Independently verify weights of 7% of
filters and substrates (at least 4
from each batch). Reweigh batch if
weights of any hi-vol filters or sub-
strates deviate by more than +_ 3.0 mg
or if weights of any dichot filters
deviate by more than + 0.05 mg.
Weigh and handle at least one blank
for each 1 to 10 filters or substrates
of each type for each test.
Transport dichot filters upright in
filter cassettes placed in protective
petri dishes.
Balance to be calibrated once per
year by certified manufacturer's
representative check prior to each
use with laboratory Class S weights.
45
-------
TABLE 15. QUALITY ASSURANCE PROCEDURES FOR SAMPLING EQUIPMENT
Activity
QA Check/Requirements
Maintenance
All samplers
Dichotomous samplers
Equipment Siting
Operation
. Timing
Isokinetic sampling
(profilers only)
Prevention of Static
Mode Deposition
Check motors, gaskets, timers, and
flow measuring devices at each re-
gional site prior to testing.
Check and clear inlets and nozzles
between regional sites.
Separate colocated samplers by 3 to
10 equipment widths.
Start and stop all samplers during
time spans not exceeding 1 minute.
Adjust sampling intake orientation
whenever mean (15 min. average) wind
direction changes by more than 30 deg.
Adjust sampling rate whenever mean
(15. min. average) wind speed
approaching sampler changes by more
than 20%.
Cap sampler inlets prior to and imme-
diately after sampling.
46
-------
TABLE 16. QUALITY ASSURANCE PROCEDURES FOR DATA PROCESSING AND CALCULATIONS
Activity ' QA Check/Requirements
Data Recording Use specially designed data forms to
assure all necessary data are
recorded. All data sheets must be
initialed and dated.
Calculations Independently verify 10% of calcu-
lations of each type. Recheck all
calculations if any value audited
deviates by more +_ 3%.
47
-------
4.3.2 Meteorological Monitoring
The primary meteorological parameters to be monitored during source
testing are wind speed and direction. Precipitation (important in open
source fugitive assessments), temperature, and relative humidity will also
be observed. Atmospheric stability will be determined from wind direction
fluctuations. Raw field data will be recorded on a continuous strip chart
and stored on magnetic tape at the site. Parameters will be sampled at in-
tervals no longer than 60 sec. The magnetic tape will be used primarily
for data analysis, with the strip chart as back-up.
QA procedures to be used during meteorological sampling follow federal
EPA guidelines. Each instrument will be sited to produce representative
samples of the meteorological parameters observed. For instance, wind moni-
tors will be sited away from buildings, trees, and other substantial obstacles.
Rainfall measurements will be made to avoid the effects of wind on precipita-
tion catch.
Wind speed and direction sensors will exhibit a starting threshold of
less than 0.5 m/sec. Anemometers will be accurate to ± 0.25 m/sec at speeds
below 5 m/sec. At high velocities, the error will not exceed ± 5% of the
speed, with no errors greater than 2.5 m/sec. The wind vane damping ratio
will be between 0.4 and 0.65. Wind vane errors will not exceed 3 degrees
for 10-min averages.
Temperature will be measured to ± 1.0°C. Relative humidity error will
not exceed an equivalent dew point error of 1.0°C. The rain guage will have
an accuracy of 0.25 mm/hr at a precipitation rate of 7.6 cm/hr.
Each instrument will be calibrated at least every 6 months at MRI facil-
ities and weekly in the field. Field calibration will also be employed when-
ever the instrument is tranported long distances.
Wind speed monitors (cup and warm wire anemometers) will be calibrated
at least every 6 months against known flows in a wind tunnel. In the field,
48
-------
the instruments will be calibrated either by visual observation of wind speed
or by comparison with co-located anemometers. Field calibration will also
include adjustment of the zero and span levels on the cup anemometer signal
processor.
Correct operation of the wind direction sensor will be determined in
the field and at MRI by observing the instrument output while manually adjust-
ing the vane heading. In addition, zero and span settings for the wind vane
signal processor will be set at every field and MRI calibration.
Temperature and relative humidity sensors will be calibrated, in-house
and in the field, by comparison with measurements from a sling psychrometer.
Adjustments to the signal processor will be made by setting zero and span
levels.
Rain gauge calibrations will be made by pouring specified volumes of
water into the intake funnel. The signal processor for this instrument will
be calibrated by setting zero and span levels.
4.4 STATISTICAL BASIS FOR SAMPLING PLAN
This section presents statistical analysis to determine the expected
reliability of the emission factors developed from replicate sampling at
each site. For purposes of this analysis, it is assumed that in the absence
of significant precipitation or other events which might irreversibly alter
the source condition, particulate emission rates vary about a constant mean
for a given test site during the period of replicate testing (usually less
than 1 week).
Based on the detailed error analysis for the exposure profiling method,
it is shown that a typical emission rate can be expected to have a random 1
a error of ± 10%. An additional error due to linear extrapolation of the
particle size distribution will be encountered in calculating emission rates
for particles larger than 15 |Jm diameter. This factor may contribute an
additional ± 10% random 1 a error to a typical emission rate for suspended
49 -
-------
particulate. A combination of these two errors with the natural variability
of the daytime source condition (a = ± 10%) gives an estimate of the standard
deviation, a, of the total population of possible measured values, expressed
as a percentage:
a = (10)2 + (10)2 + (ia)2 = 17.3% (7)
The sample size, n, needed to achieve an expected standard deviation of the
sample mean, S,, that is less than 10% of the mean of the population, is
given by:
Consequently, a sample of three replicate tests will achieve an expected 1
a error of less than 10% for the sample emission rate mean in relationship
to the true emission rate.
4.5 DISTRIBUTION OF TESTS
The proposed distribution of tests over the source categories of interest
is based on the following considerations:
1. The number of control measures tested for a particular source type
should reflect the importance of the source based on uncontrolled emissions,
but may be limited by the number of candidate "best controls" that are avail-
able.
2. All control measures must be referenced to an uncontrolled condition.
3. Triplicate tests are needed to characterize an uncontrolled or con-
trolled condition at any point in time.
4. Long-term control measures must be tested at least twice after appli-
cation to establish control efficiency decay curve.
50
-------
5. Short-term control measures (e.g., watering) will usually show loss
of efficiency during back-to-back testing.
6. Testing of wind erosion must quantify decay of emission rate with
time so that loss potential can be quantified.
The proposed distribution of tests is shown in Table 17.
4.6 PROPOSED TEST SITES
Test sites with established control programs are preferable to those
where control must be applied for the first time. This helps to provide
credibility that the program for application of the control technique is
realistic. For the same reason, chemical dust suppressants and watering
will be tested at typical application densities rather than those which may
be purported to improve performance. All of this will ensure that the his-
torical cost and performance data which have been compiled at a particular
site apply to the control measure as tested.
At the time of this writing, it is envisioned that the first plant to
be tested will be Armco's Middletown Works. The sources proposed for test-
ing at Middletown are given in Table 18. The remainder of the field test
program, which is targeted for completion by the end of October 1980, will
take place at two additional sites, yet to be selected.
The schedule proposed for testing is as follows:
Testing of uncontrolled sources at Armco's Late June/early July
Middletown Works
Pre-test survey of second and third plant Late July
sites
51
-------
TABLE 17. PROPOSED DISTRIBUTION OF TESTS
Source
Unpaved roads (heavy duty)
Paved roads
Storage pile maintenance
Storage pile wind erosion
(active piles)
Moderate winds
High winds
Control measure
Coherex
Lignin sulfonate or
calcium chloride
Watering
Flushing
Vacuuming
Watering
Watering
Test
method"1'
EP
EP
EP
EP
EP
EP
WT
Number of
tests
12
12
12
9
9
9
9
9
Moderate winds
High winds
Unpaved parking lots
Conveyor transfer stations
Exposed area wind erosion
(moderate winds)
Chemical
Enclosure
Chemical
9
9
EP 12
D ' 9
WT 9
EP = Exposure profiling
WT = Wind tunnel testing
D = Duct sampling
52
-------
TABLE 18. SOURCES PROPOSED FOR TESTING AT ARMCO'S MIDDLETOWN WORKS
Source Control measure
Unpaved road Coherex application
Paved road Flushing/vacuuming
Coal stockpile - maintenance Watering
Coal stockpile - wind erosion Watering
53
-------
Testing of controlled sources at Arraco's
Middletown Works
Early August
Testing of uncontrolled and controlled
sources at second plant
Late August/early September
Testing of uncontrolled and controlled
sources at third plant
Late September/early October
In addition, it is also recommended that two or three additional plants
with active control programs be visited during this period to gather addi-
tional data on the cost and performance of control techniques for open dust
sources.
The total effort (technical person-hours) required for the testing pro-
gram and subsequent evaluation of cost-effectiveness of control techniques
may be estimated from the number of field test performed. For this purpose,
the number of test should be multiplied by 80 person-hours. This estimate
should be refined based on final definition of the scope of the program.
54
-------
REFERENCES
1. Bohn, R., T. Cuscino, Jr., and C. Cowherd, Jr. Fugitive Emissions from
Integrated Iron and Steel Plants. Prepared by Midwest Research Institute
for U.S. Environmental Protection Agency, Publication No. EPA-600/2-78-
050, March 1978.
2. Cowherd, C., Jr., R. Bohn, and T. Cuscino, Jr. Iron and Steel Plant
Open Source Fugitive Emission Evaluation. Prepared by Midwest Research
Institute for U.S. Environmental Protection Agency, Publication No. EPA-
600/2-79-103, May 1979.
3. Cowherd, C., Jr., K. Axetell, Jr., C. M. Guenther, and G. Jutze. De-
velopment of Emission Factors for Fugitive Dust Sources. Prepared by
Midwest Research Institute for U.S. Environmental Protection Agency,
Publication No. EPA-450/3-77-027, July 1977.
4. Cowherd, C., Jr., and C. M. Guenther. Development of a Methodology
and Emission Inventory for Fugitive Dust for the Regional Air Pollu-
tion Study. Prepared by Midwest Research Institute for U.S. Environ-
mental Protection Agency, Publication No. EPA-450/3-76-003, January
1976.
5. McCutchen, G., and R. Iversen. Steel Facility Factors. U.S. Environ-
mental Protection Agency, Research Triangle Park, North Carolina. Pre-
pared 1975 and revised December 8, 1976.
6. American Iron and Steel Institute. Source Data for Steel Facility Fac-
tors. Final prepared July 13, 1976.
7. Speight, G. E. Best Practicable Means in the Iron and Steel Industry.
The Chemical Engineer, (3):132-139, 1973.
8. Cuscino, T. , Jr. Taconite Mining Fugitive Emissions Study. Prepared
by Midwest Research Institute for Minnesota Pollution Control Agency,
June 7, 1979.
9. Kalika, P. W., R. E. Kenson, and P. T. Bartlett. Development of Proce-
dures for the Measurement of Fugitive Emissions. Prepared for U.S.
Environmental Protection Agency, Publication No. EPA-600/2-76-284, 1976.
10. Cowherd, C., Jr. Measurement of Fugitive Particulate. Second Symposium
on Fugitive Emissions Measurement and Control, Houston, Texas, May 1977.
11. Lundgren, D. A., and H. J. Paulus. The Mass Distribution of Large At-
mospheric Particles. Paper No. 73-163. Presented at the 66th Annual
Meeting of the Air Pollution Control Association, Chicago, Illinois,
June 1973.
12. Turner, D. B. Workbood of Atmospheric Dispersion Estimates. AP-26,
U.S. Environmental Protection Agency, Research Triangle Park,
North Carolina, 1970.
55
-------
13. Blackwood, T. R. , T. F. Boyle, T. L. Peltier, E. C. Eimutis, .and
D. L. Zanders. Fugitive Dust from Mining Operations. Prepared for
the U.S. Environmental Protection Agency, Contract No. 68-02-1320,
Task 6, May 1975.
14. Cowherd, C., Jr., C. M. Maxwell, and D. W. Nelson. Quantification of
Dust Entrainment from Paved Roadways. Prepared by Midwest Research
Institute for U.S. Environmental Protection Agency, Publication No. EPA-
450/3-77-027, July 1977.
15. SSM. Inhaled Particulates. Environmental Science and Technology, 12:13,
December 1978, p. 1354.
16. Wedding, James B. Ambient Aerosol Sampling: History, Present Thinking
and a Proposed Inlet for Inhalable Particulate Matter. Paper presented
at the Air Pollution Control Association Specialty Meeting. Seattle,
Washington, April 1980.
17. Bagnold, R. A. The Physics of Blown Sand and Desert Dunes, Methuen,
London, 1941.
18. Chepil, W. S., and N. P. Woodruff. The Physics of Wind Erosion and
Its Control. In: Advances in Agronomy, Vol. 15, A. G. Norman (Ed.),
Academic Press, New York, NY, 1963.
19. Cooper, D. W., et al. Setting Priorities for Control of Fugitive Par-
ticulate Emissions from Open Sources. Prepared by Harvard University
for the U.S. Environmental Protection Agency. Publication No. EPA-
600/7-79-188, August 1979.
20. Bonn, R., et al. Dust Control for Haul Roads--A Manual. Draft Report
prepared by Midwest Research Institute for the U.S. Bureau of Mines,
May 1980.
21. Anonymous. Investigation of Fugitive Dust—Sources, Emissions, and
Controls. Prepared by PEDCo Environmental for U.S. Environmental
Protection Agency under Contract No. 68-02-0044, Task 9, May 1973.
22. Anonymous. Evaluation of Fugitive Dust from Mining. Task 2 Report
prepared by PEDCo Environmental for U.S. Environmental Protection
Agency under Contract No. 68-02-1321, Task 36, June 1976.
23. Anonymous. Technical Guidance for Control of Industrial Process Fugi-
tive Particulate Emissions. Prepared by PEDCo Environmental for U.S.
Environmental Protection Agency, Publication No. EPA-450/3-77-010,
March 1977.
24. Boscak, V., and J. S. Tandon. Development of Chemicals from Suppres-
sion of Coal Dust Dispersion from Storage Piles. Paper presented at
Fourth Annual Environmental Engineering and Science Conference,
Louisville, KY, March 1974.
56
-------
25. Currier, E. L. , and B. D. Neal. Fugitive Emissions at Coal-Fired
Power Plants. Paper No. 79-11.4 presented at Annual Meeting of the
Air Pollution Control Association, June 1979.
57
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APPENDIX A
EXAMPLE DATA COMPILATION FROM MATERIALS HANDLING FLOW CHARTS
A-l
-------
TABLE A-l. RAW AND INTERMEDIATE MATERIAL HANDLING AT THE INTERLAKE CHICAGO PLANT IN 1978
Origination
Material Mode
Coal Truck unloaded
(26,000 ST)
Railcar unloaded
by rotary dump
(495,000 ST)
Coke Coke Ovens
(345,000 ST)
Iron Ore Pellets Ship unloaded by
clamshell
(l,20:i,000 ST)
>
1
t-o
Dolomite Truck unloaded
at storage pile
(35,300 ST)
Limestone Ship unloaded by
clamshell
(123,000 ST)
Handling
Transfer Storage
Station Load-in
9 transfer Scraper
stations (495,000 ST)
(521,000 ST)
2 transfer Conveyor
stations stacker
(345.000 ST) (17,000 ST)
None Same clamshell
used to unload
ships
(1,203,000 ST)
None Same truck used
to deliver
material to
plant
(35,300 ST)
None Same clamshell
used to unload
shi ps
(123,000 ST)
Method and Amount of Material Handled
Sto'rage
Open storage
pile
(505,000 ST)
Open storage
pile
(17,000 ST)
Open storage
pile
(1,203,000 ST)
Open storage
pile
(35,300 ST)
Open storage
pile
(123,000 ST)
Storage
Load-out
Scraper
(521,000 ST)
Front-end loader
dump into conveyor
hopper/feeder
(17,000 ST)
Bucket wheel
reclaimer onto
underground
conveyor
(1,203,000 ST)
Crane-Clam-
shell bucket
transfer to
conveyor
(35,000 ST)
Crane-Clam-
shell bucket
transfer to
conveyor
(123,000 ST)
Transfer
Station Screening
21 transfer None
stations
(521,000 ST)
2 transfer Screened - 90%
stations to coke oven; 107.
(345,000 ST) to sinter plant
(345,000 ST)
2 transfer None
stations
(1,203,000 ST) '
2 transfer None
stations
(35.300 ST)
2 transfer No"c
stations
(123,000 ST)
Sinter, Nodules
and Briquette
Sinter Plant
(302,000 ST)
transfer
station
(302,000 ST)
None
None
None
transfer
station
(302,000 ST)
Screened - 82Z to
blast furnace;
18% recycled
(272,000 ST)
Sinter Input
(Flux, Iron ore
.-ind Coke fines)
Truck unloaded
at storage pile
(398,000 ST)
2 transfer Same truck used Open storage
stations to deliver material pile
(199,000 ST) to plant (498,000 ST)
(199,000 ST)
Conveyor stacker
(199,000 ST)
Front-end loader
dump into conveyor
hopper/feeder
(398,000 ST)
3 transfer
stat ions
(398,000 ST)
None
-------
TABLE A-2. RAW AND INTERMEDIATE MATERIAL HANDLING AT THE J&L STEEL ALIQUIPPA PLANT IN 1978
i
u>
Material
Coke
Coa I for bo I lers
and storage
Coal for Coke
Oven
Iron Ore Pellets
Unaggloiuera ted
Iron Ore
Origination
Mode
Railcar unloaded
by bottom dump
(1,465,000 ST)
Ua rge unloaded by
c Inmshel 1
(34,600 ST)
Barge unloaded by
bucket-ladder
conveyor
(1,678,000 ST)
Railcar unloaded
by bottom dump
(17,300 ST)
Ba rge unloaded by
bucket-ladder
conveyor and fed
into bins
(2,358.000 ST)
Railcar unloaded
via rotary dump
(73,000 ST)
Railcar unloaded
to transfer car
via rotary dump
(1,184,000 ST)
Kallcar unloaded
to conveyor via
bottom dump
(1,184,000 ST)
Railcar unloaded
to transfer car
via rotary dump
(62,200 ST)
Handling Method
Transfer Storage
None Conveyors
( 1,465, 000 -ST)
None Conveyor to
temporary storage
pile via clamshell
(623,000 ST)
22 transfer Conveyors to
stations crusher to bins
(2,358,000 ST) (2,431,000 ST)
None Transfer car
to temporary
storage area
to ore yard
pile via
clamshell
(1,184,000 ST)
Conveyors to
cast-house
storage bins
(1,184.000 ST)
None Transfer car to
temporary storage
area to ore yard
via clamshell
(62.200 ST)
and Amount of Material Handled
Storage
Storage bins
(1.465.000 ST)
Open storage
pile
(623.000 ST)
Storage bins
(2.431,000 ST)
Open storage
pile
(1,184.000 ST)
Casthouse
storage bins
(1,184,000 ST)
Open storage
pile
(62,200 ST)
Storage Transfer
Load-out Stations Screening
Conveyors None screened - 95% to
(1,465,000 ST) blast furnaces; 57.
to sinter plants
Clamshell to None None
conveyor
(623,000 ST)
Bins to con- None None
veyor to
crusher to
bins
(2,431,000 ST)
Clamshell to Transfer car Screened
transfer car to cast house (1,018,000 ST)
(1.184.000 ST) storage bin
(1,184,000 ST)
Clamshell Transfer car Screening
bucket to to bin (27,700 ST)
transfer car (62,200 ST)
(62.200 ST)
'(continued)
-------
TABLE A-2. (concluded)
Or Igl ii.it ion
Material node
Lliitestone/Dolonii te Railcar unloaded
to transfer car
via rotary dump
(71.000 ST)
RnLlcar unloaded
to conveyor via
bottom dump
(30.000 ST)
Sinter Sinter Plant
(1,548,000 ST)
Sinter Input (Flux, Railcar unloaded
Iron ore and Coke to conveyor via
Fines) rotary dump
Handling Method
Transfer Storage
Stations Load* in
None Transfer car to
temporary storage
area to main
storage area via
clamshell
(71,000 ST)
Conveyor to bins
(30,000 ST)
5 transfer Conveyor to bins
stations (1,548.000 ST)
(1.548,000 ST)
2 transfer Conveyor to bins
stations (2.182,000 ST)
(2,182,000 ST)
and Amount of Material Handled
Storage
Open storage
pile
(71,000 ST)
Dins
(30.000 ST)
Bins
(1,548.000 ST)
Bins
(2,182,000 ST)
Storage
Loa d - ou t
Clamshel I
bucket to
transfer car
(71,000 ST)
Bins to trans-
fer car
(1,548,000 ST)
Bins to con-
veyor
(2,182.000 ST)
Transfer
Stations Screening
Transfer car to None
bin
(71.000 ST)
Transfer car Screening
to caschonse (666,000 ST)
bins to skip
cars
(882.000 ST)
Transfer car
to casthouse
bins to 3
transfer
stations
(666,000 ST)
15 transfer None
stations
(2,182,000 ST)
(1,527.000 ST)
Railcar unloaded Co
conveyor via
bottom dump
(655,000 ST)
-------
APPENDIX B
BIBLIOGRAPHY FOR OPEN DUST CONTROL
B-l
-------
1. Anonymous. Industrial Ventilation. American Conference of Govern-
mental Industrial Hygienists, Committee of Industrial Ventilation,
Lansing, Michigan, 1970.
2. Manufacturer's Literature, Deter Company, East Hanover, New Jersey.
3. Price, W. L. Open Storage Piles and Methods of Dust Control. Paper
Presented at the October 1972 Meeting of the American Institute of
Mining Engineers, Birmingham, Alabama.
4. PEDCo Environmental Specialists. Investigation of Fugitive Dust;
Volume I: Sources, Emissions, and Control. EPA-450/3-74-036, U.S.
Environmental Protection Agency, Research Triangle Park, North Carolina,
1974.
5. Handy, R. L., J. M. Hoover, K. L. Bergeson, and D. E. Fox. Unpaved
Roads as Sources for Fugitive Dust. Transportation Research News,
(60):6-9, Autumn 1975.
6. Manufacturer's Literature, Roscoe Manufacturing Company, Minneapolis,
Minnesota.
7. Carpenter, B. H. and G. E. Weant III. Particulate Control for Fugitive
Dust. EPA-600/7-78-071, U.S. Environmental Protection Agency, Research
. Triangle Park, North Carolina, April 1978.
8. Cooper, D. W., J. S. Sullivan, Margaret Quinn, R. C. Antonelli, and
Maria Schneider. Setting Priorities for Control of Fugitive Particu-
late Emissions from Open Dust Sources. EPA-600/7-79-186, U.S. Environ-
mental Protection Agency, Research Triangle Park, North Carolina,
August 1979.
9. Hoenig, Stuart A. Use of Electrostatically Charged Fog for Control of
Fugitive Dust Emissions. EPA-600/7-77-131, U.S. Environmental Protec-
tion Agency, Research Triangle Park, North Carolina, November 1977.
10. Daugherty, D. P. and D. W. Coy. Assessment of the Use of Fugitive
Emission Control Devices. EPA-600/7-79-045, U.S. Environmental Pro-
tection Agency, Research Triangle Park, North Carolina, February 1979.
11. Bonn, R., T. Cuscino, Jr., and C. Cowherd, Jr. Fugitive Emissions
from Integrated Iron and Steel Plants. EPA-600/2-78-050, U.S. Environ-
mental Protection Agency, Research Triangle Park, North Carolina,
March 1978.
12. Seibel, Richard J. Dust Control at a Transfer Point Using Foam and
Water Sprays. Technical Progress Report 97, U.S. Bureau of Mines,
Washington, D.C., May 1976.
13. Bonn, Russel. Dust Control from Haul Roads - Draft Report. U.S.
Bureau of Mines, Twin Cities Mining Research Center, Minneapolis,
Minnesota, October 1979.
B-2
-------
14. Cowherd, Chatten, Jr., Russel Bohn, and Thomas Cuscino, Jr. Iron and
Steel Plant Open Source Fugitive Emission Evaluation. EPA-600/2-79-
103, U.S. Environmental Protection Agency, Research Triangle Park,
North Carolina, May 1979.
15. Sultan, Hassan A. Soil Erosion and Dust Control on Arizona Highways-
Part IV-Final Report on Field Testing Program. Report No. ADOT-RS-
13(l4l)IV, Arizona Department of Transportation, Phoenix, Arizona,
November'1975.
B-3
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