SECTION D: POINT SOURCE EMISSION INVENTORY
-------
Point Source Emission Inventory
Point sources are the primary contributors.to the emission of many pol-
lutants. A detailed, high resolution inventory was required for RAPS. Point
sources, as defined for the RAPS study, are sources which emit individually
more than 0.01% of the total emissions for the St. Louis AQCR of any pollutant.
Emission data are available on an hourly basis.
The primary requirement of RAPS in the emission inventory field was for
those pollutants which can be used as tracers in the modelling studies. Thus,
initial emphasis was placed on sources of sulfur dioxide (S02) emissions,
since SOp is closely related to stationary point sources. In time, the inven-
tory was broadened to include all of the "criteria" pollutants.
In addition, a number of specialized inventories were assembled and are
Included in this section.
1. Point Source Methodology and Inventory, Phase I, II and III
Rockwell International - EPA 450/3-74-054.
2. Emission Source Testing Programs
Rockwell International - 6802-2093 T0108B, April 1977.
3. Methodology for Inventorying Hydrocarbons
EPA-600/4-76-013, March 1976.
4. Hydrocarbon Emission Inventory
Rockwell International - 68-02-2093 T0108F, March 1977.
5. Non-Criteria Pollutant Inventory
"RockwelT International - 68-02-1081 T054, January 1976.
6. Heat Emissions Inventory
Rockwell International - 68-02-2093 T0108G, April 1977.
7. Sulfur Compounds and Particulate Size Distribution Inventory
Rockwell International - 68-02-1081 T056, April 1976.
-------
EPA-450/3-74-054
REGIONAL AIR
POLLUTION STUDY
POINT SOURCE
METHODOLOGY
AND INVENTORY
by
Fred E. Littman
Science Center
Rockwell International
1049 Camino Dos Rios
Thousand Oaks, California 91360
Contract No. 68-02-1081
Task Order No. 16
EPA Project Officer: James Southerland
Prepared for
ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Waste Management
Office of Air Quality Planning and Standards
Research Triangle Park, N. C. 27711
October 1974
-------
This report is issued by the Environmental Protection Agency to report technical
data of interest to a limited number of readers. Copies are available free of
charge to Federal employees, current contractors and grantees, and nonprofit
organizations - as supplies permit - from the Air Pollution Technical Information
Center, Environmental Protection Agency, Research Triangle Park, North
Carolina 27711; or, for a fee, from the National Technical Information Service,
5285 Port Royal Road, Springfield, Virginia 22161.
This report was furnished to the Environmental Protection Agency by
Rockwell International, in fulfillment of Contract Nto. 68-02-l<08
-------
This report is issued by the Environmental Protection Agency to report technical
data of interest to a limited number of readers. Copies are available free of
charge to Federal employees, current contractors and grantees, and nonprofit
organizations - as supplies permit - from the Air Pollution Technical Information
Center, Environmental Protection Agency, Research Triangle Park, North
Carolina 27711; or, for a fee, from the National Technical Information Service,
5285 Port Royal Road, Springfield, Virginia 22161.
This report was furnished to the Environmental Protection Agency by
Rockwell International, in fulfillment of Contract No. 68-02-1081. The contents
of this report are reproduced herein as received froro! Rockwell International.
The opinions, findings, and conclusions expressed a«fe those of the author
and not necessarily those of the Environmental Protection Age5n-cy. Mention
of company or product names is not to be considered as aft endorsement by
the Environmental Protection Agency.
Publication No. EPA-450/3-74-054
11
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RAPS POINT SOURCE EMISSION INVENTORY METHODOLOGY
Table of Contents
I. Introduction ......................... 1
II. The Saint Louis Interstate Air Quality Control Region
(SLIAQCR) ......................... 2
III. Sources of At r Pol lut ion ........... . . ...... 4
A. Classification ................ ......%
B. Pollutants of Interest .................. %
B1. Sulfur Dioxide .................... 4
B2. Carbon Monoxide ........... . ....... 6
B3. Part icul ate Matter .......... < ....... 7
BA. Hydrocarbons ............... ..... 8
BS. Oxides of Nitrogen (NOX) ....... . i ....... 8
B6. Heat Emissions ................... 9
C. Sensitivity Analysis ................... HO
D. Size Distribution of Sources ............... 1&
E. Existing Inventory Data .................. 1&
IV. Emission Data Acquisition ................... 2A
A. Survey .......................... 2'£
B. Classification of Sources into Acquisition G^roiaps. . . * .257
C. Acquisition of Data ............... ... .27
C1. Stack Gas Measurements ........... .... .27
C2. Fuel Consumption and Process Data .......... 33
C3. Operating Data ............ ...... . 3'6
V. Handling of Emission Data
VI. RAPS Inventory Acquisition Schedule
VII. Summary and Conclusions
It
-------
TABLES
I. Qualifications of Selected SMSA's 2
II. Classification of Sources for Emission Inventory 5
III. Values of 6 for Selected'Palrs of (a, 1-C) 13
IV. Point Source Emission Inventory, NEDS December 1973 14
V. Maximum Allowable Error 0. for Point Sources of
Various Size Acceptance Material 10%, Confidence
Level 95% 0 - 2.24% 16
VI. Sources of Pollutants In the Saint Louis AQCR 17
VII. List of Companies Emitting More Than 1000 Tons/Year of SO, 19
VIM. Distribution of Large Sources by SCC Codes -
External Combustion Boilers 30
IX. Distribution of Large Sources by SCC Codes -
Process Heaters 6 Processing Emissions 31
X. Minimum Test Schedule 32
XI. Classification of S02 Sources 33
XII. Classification of CO Sources 34
XIII. Classification of Sources of Particulates 34
XIV. Classification of NOX Sources 35
XV. Classification of HC Sources 35
XVI. Wood River Power Station - Daily Log, Unit 5 37
XVII. Wood River Power Station - Boilers 1, 2, 3 Data 38
XVIII. Wood River Power Station - Units 1, 2, 3 Fuel :
Oil Usage Log 39
FIGURES
1. Metropolitan Saint Louis Interstate Air Quality Region 3
\
2. Relationship between o. and -jr— 12
3. RAPS Inventory Schedule 43
iv
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RAPS POINT SOURCE EMISSION INVENTORY METHODOLOGY
1. Introduction
An emission inventory constitutes the starting point for any attempt to ,
control emissions to the atmosphere. As long as such controls deal with average
yearly concentrations, inventories giving total annual emissions of the various
sources of pollutants are sufficient. The Regional Air Pollution Study has,
however, as its first goal the validation of atmospheric dispersion models,
which attempt to predict ambient pollutant concentrations on an hourly basis.
Therefore, emission values derived from total annual emissions are largely in-
adequate, and the RAPS emission inventory was conceived to provide the needed
time resolution and accuracy by measuring and recording hourly emissions (or
parameters directly related to hourly emissions) and/or individualized hourly
estimates derived for the principal sources of pollution. Thus, the emission
inventory for the Regional Air Pollution Study (RAPS) at St. Louis is distinguished
from existing emission inventories by two factors: its time and space resolution
and its accuracy.
Although ultimately such an inventory should Include all pollutants of im-
portance, as a matter of priority, emphasis of the data collection will be
placed on the two major pollutants of prime importance for modeling purposes,
S02 as an indicator of pollution originating from stationary sources, and CO
for mobile sources. Hourly measurement and estimates would provide the needed
time resolution and, at the same time, increase the accuracy of the emission
inventory by updating it. Later, the inventory can be expanded to include hydro-
carbons (or organics), oxides of nitrogen, particulate matter, heat emissions
and others.
Any attempt to obtain measured values for a large number of sources is a
complex and expensive undertaking. Within the usual constraints of air pollution
studies, such an approach is not feasible, and the use of algorithms or models
has been generally resorted to for estimation of emissions. Since such emission
models again describe assumed conditions, their use in the RAPS is less desirable
and they will be used only where it does not impair the overall accuracy of the
inventory, as indicated by a sensitivity analysis.
1
-------
This report proposes an approach to the problem of assembling a "precision"
inventory for the St. Louis Interstate Air Quality Region. It states the nature
of the problem and the rationale for choosing the St. Louis area as a "test chamber";
the pollutants of interest are also discussed briefly. Using an approach sug-
gested by NADB's Weighted Sensitivity Analysis Program, limits were placed on
the scope of the investigation, which were then applied to the actual situation
in St. Louis. The mechanism for the acquisition of data and their preparation
prior to entry into a data bank, as well as a time schedule to accomplish these
aims, are also described.
I I. The Saint Louis Interstate Air Quality Control Region (SLIAQCR)
The St. Louis area was selected on the basis of careful considerations of
the various factors of importance for a regional air pollution study^ . Standard
Metropolitan Statistical Areas (SMSA's) were used as a basis for the analysis,
and all SMSA's with population in excess of 400,000 were examined. The primary
factors considered in the selection were:
0 Geographic isolation from other SMSA's
0 Location within the Continental climate zone
0 Significant level and density of pollutant emissions
0 Presence of a rural fringe with substantial crop lands
0 Existence of control programs and historical data
The final selection of St. Louis was made by the Assistant Administrator
for Research and Monitoring, EPA, from the four considered sites on the basis of
the following rating (Table 1):
TABLE I
QUALIFICATIONS OF SELECTED SMSA'S !
Cri terion
Surrounding area
Heterogeneous emissions
Area size
Control program
Information
Climate
Birmingham Cincinnati
Fai r
Fair
Good
Poor
Poor
Good
Poor
Fai r
Good
Good
Good
Fai r
Pittsburgh
Good
Fai r
Good
Good
Fai r
Fai r
St. Louis
Good
Good
Good
Good
Good
Good
(l) For details, see: Regional Air Pollution Study - A Prospectus, Part III,
Research Facility, Standford Research Institute, 1972, Contract No. EPA 68-02-0207.
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100 km
' 1
n-
----- •— r
CRAWFORD
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III. Sources of Air Pollution
A. Classification
Virtually every human activity results in some form and degree of air
pollution. For practical purposes, it is convenient to classify the sources of
emission; a general classification in shown in Table II. There, sources are
divided into stationary and mobile, since these present significantly different
problems. Stationary sources are further divided into Point and Area sources.
The division between the two is arbitrary: sources tested individually become
"Point Sources". For the RAPS inventory, sources emitting less than ten tons
of pollutants per year will not be considered, at least initially, as individual
points but rather assigned to and distributed over the appropriate a'rea. Of
course, even a very small point source can be a ifKaj-or Contributor to a given
local or nearby receptor (monitoring station), but the investigation of this
problem constitutes a localized, special situation which needs to be dealt with
separately from the overall inventory. Probably the only way the existence of
a local interference can be determined is by examination of the records of each
station.
The division of sources into combustion and nofi-cdTnb'Ustion is again a matter
of convenience; however, combustion sources constitute a specific group of emit-
ters which, in some cases, like S02 for stationary sources or CO for mobile
sources, constitute the overwhelming fraction of these pollutants.
B. Pollutants of Interest
The RAPS inventory is, initially, emphasizing Midf i telM-a" pollutants
(for which Air Quality Standards exist) and, of those, primarily S02 and CO,
since these are the ones which will be used at highest priority in the model
validation studies. An attempt will also be made to inventory hBat emissions.
Ultimately the inventory will also include lesser pollutants such as trace and
hazardous contaminants.
B.I Sulfur Dioxide
Sulfur dioxide (S0£) will be the pollutant initially emphasized
in the inventory since it occupies the position of highest priority within the
Regional Air Pollution Study. In St. Louis, virtually all of it (98.9%) is es-
timated to originate from listed point sources' '. Most of the S0£ is produced
by the combustion of coal and fuel oil, which average 3% and 1.5 - 2.5% of sulfur
respectively, although some of it results from ore roasting, steel production, and
(2) Source:NEDS Inventory (1973)
-------
TABLE II
CLASSIFICATION OF SOURCES FOR EMISSION INVENTORY
Source
Category
Source
Subcategory
Source
Process
Source units
Pollutants
Stationary Sources
Area Sources
Combustion
Commercial
Institutional
Residential
Small Industrial
Fuel Use
Space heaters
Water heaters
Boilers
Waste disposal--
Incinerators
Gases and vapors
S0x
N0x
CO
Hydrocarbons and
derivatives
HC1
HF
Odors
Port leu la tea
Fly ash and its
specific chemical
components
Smoke
Noncombustion
Commercla 1
Small industrial —
Venting of organic
vapors (dry clean-
Ing, painting,
gasoline storage and
handling, food prepa-
ration)
Cases and vapors
Organic vapors
(solvents,
gasoline)
Odors
Particulates
Organic aerosols
Smoke
Point Sources
Combustion
Utilities
Power plants
Municipal — incinerators
Industrial
Boiler and power plants
Indirect-fired air and
process heaters
Stationary Internal
combustion engines
Stationary gas turbine
engln<_.-
Inclncrators
Gases and vapors
S0x
NO,
CO
Hydrocarbons and
derivatives
HC1
HF
Odors
Particulates
Fly ash and Its specific
chemical components
Smoke
Noncombustlon
Industrial
Direct-fired process
units
All other industrial
processes, material
storage and handling
All pollutants
Mobile Sources
Area and Line Sources
Combustion
Surface vehicles
Passenger cars
Trucks and buses
Commercial vehicles
Railroads
Vessels
Off -highway vehicles
and equipment
Aircraft
Piston engines
Jet engines {
Gases and vapors
S°x
NO
X
CO
Hydrocarbons and
derivatives
Odors
Particulates
Smoke
Lead
Oil aerosols
Derivatives of fuel
additives
Noncoir. bust ion
Surface vehicles and
aircraft
Venting of fuel
vapors
Wear of tires and
brakes
Hydrocarbon vapors
Particulates
Organic
Inorganic
Source: A Regional Air Pollution Study -
A Prospectus, Stanford Research
Institute, 1972.
-------
petroleum refining operations. The largest contributors are the power generating
stations of the utility companies. The six generating stations in the St. Louis
area produce over 900,000 tons of S02 per year, or about 75% of all the S02
produced by point sources in the area.
Sulfur dioxide is relatively non-reactive in the atmosphere, at least over
the time interval of a few hours, which is likely to be of interest to modelers.
Removal from the atmosphere occurs by several mechanisms, some of which involve
oxidation to sulfur trioxide with subsequent formation of sulfuric acid mist or
sulfates by reaction with basic materials in the atmosphere (e.g., ammonia).
These processes will have to be considered for long-term (2k hours or longer)
modeling.
Available evidence indicates that the ratio of SO, to SO, in ambient
(3)
air is between 50:1 to 100:1. Recent health data indicate that (at least in the
case of elderly patients with heart and lung diseases, as well as asthmatics) it is
the level of suspended sulfates that correlates with adverse health effects rather
than the S02 level. Best estimates indicate that sulfates are about an order
of magnitude more irritating than S02. At this time, it is not clear whether
sulfuric acid mist or sulfates are implicated, and the importance of atmospheric
transformation products of S02 is not certain.
Ambient concentrations of SO. in the St. Louis atmosphere typically range
3 (3)
from 20 to 40 micrograms/m (annual average)
B.2 Carbo:i Monoxide
Carbon monoxide (CO) is closely linked with automotive traffic.
Stationary combustion sources normally generate only relatively minor amounts of
CO. There are, however, a few important industrial sources of CO: the catalytic
cracker regenerators in petroleum refineries, blast furnaces in steel mills, and
certain chemical processes. And, because of the tremendous volume of stack gases
generated by electric utilities, the relatively low concentrations of CO in these
gases do contribute significantly to the overall CO concentration.
Carbon monoxide is chemically inert. It is removed slowly by contact with
certain soil bacteria, which maintain the natural balance of CO in the air, but
the rates of these processes are not significant on the time scale of interest.
(3) Health Consequences of Sulfur Oxides; CHESS 1970-71 , U. S. Environmental
Protection Agency, Office of Research 6 Development, EPA 65011-74-004.
-------
Carbon monoxide combines with hemoglobin 200 times more readily than oxygen;
it thus prevents the blood hemoglobin from transporting oxygen from the lungs
to the tissues. Exposure to low concentrations (below 100 ppm or 115 mg/m3)
causes headaches and dizziness.. Its actions are most likely to affect persons
living at high altitudes and people with chronic heart and lung diseases.
Cigarette smokers commonly have 5 - 10% carboxy-hemoglobin, an amount that
corresponds to 30 to 60 ppm of CO in ambient air (35 to 70 mg/m^).
Ambient concentrations of CO in the downtown St. Louis area range from 15
,(M
to 35 mi 11 igrams/m-3 .
B.3 Particulate Matter
The fate of particulate matter in the atmosphere is becoming a
major research target. It is a particularly difficult subject because the
characteristics of particles are determined only partially by their chemical
composition and very largely by their size distribution. Thus haziness, by far
the most obvious manifestation of air pollution, is strongly dependent on particle
size. Similarly, the health effect of particulate matter is largely dependent on
particle size, since only particles of a certain size range penetrate into the
lungs and are retained there. The particle size of interest in these areas is
of the order of less than five or six micrometers. Such particles remain afloat
virtually indefinitely and, while their contribution to the total weight of par-
ticulate matter is small, their number is very large.
By contrast, the emission of particulate matter is determined on a weight
basis, whether by sampling or by material balance consideration. Thus the small
number of relatively large particles accounts for most of the mass of particulate
emission. Since particles in excess of 10 ym settle out rather rapidly, these
particles do not contribute much to the ambient concentration of particulates,
nor to their health and visibility effects.
(k) Air Quality Data - 197^ Annual Statistics, U. S. Environmental Protection
Agency Office of Air Quality Planning & Standards, EPA-^50/2-74-001.
-------
Thus, a really useful inventory of particulate emissions would have to specify
not only the mass but also the size distribution of particulate emission as well
as their chemical composition — a difficult and expensive task which cannot be
carried out on a routine monitoring basis.
The problem is further complicated by the processes which form particulates —
mainly droplets — in the atmosphere. The formation of SO, leads directly (via
reaction with water vapor) to the formation of a sulfuric acid mist and to the
stabilization of fog; photochemical reactions result in the polymerization of
initially gaseous hydrocarbons, resulting again in particulate droplets. These
products are only indirectly related to emission inventories.
B.4 Hydrocarbons
In the air pollution literature, the term "hydrocarbons" is used loosely
to designate gaseous organic compounds. There are two major categories of sources
of hydrocarbons in urban atmospheres: incomplete combustion and evaporation.
Incomplete combustion occurs primarily in internal combustion engines (automobiles).
Evaporation results from the storage and handling of solvents, petroleum products,
etc. Additionally, methane is a normal constituent of the atmosphere, the result
of natural decomposition processes.
Hydrocarbons participate in photochemical reactions leading to "smog", but
their reactivity varies widely. It is therefore important to determine not only
the amount of hydrocarbons present, but also their composition. From a practical
point of view, usually only gross classification is possible on a continuous
inventory basis, such as methane and non-methane hydrocarbons. Further separation
into reactive hydrocarbons (olefins, diolefins, aldehydes, alcohols, etc.) and
stable ones (e.g., parafins) is possible but will require an extensive sampling
program. Complete analyses of samples collected in bags by means of a gas
chromotograph are scheduled for samples of ambient air at St. Louis.
B.5 Oxides of Nitrogen (NOX)
Emission inventories of nitrogen oxides constitute a special problem
since these compounds — particularly nitric oxide (NO) — are primarily formed
by nitrogen fixation during combustion operations. Their formation during com-
bustion is a complex function of the time-temperature relationships in the com-
bustion chamber, the amount of excess air present, and even the chamber con-
figurations. Any nitrogen compounds present in the fuel also contribute to the
8
-------
formation of nitrogen oxides. Because of this, the nitrogen oxide concentration
in flue gases cannot be calculated from a theoretical basis but must be determined
experimentally for, at least, each typical situation.
In addition to combustion sources, there are specific point sources emitting
nitrogen oxides, usually N0_, such as nitric acid plants. The NEDS inventory does
not show any such sources in the > 100 tons/year category in the St. Louis area.
As mentioned previously, the importance of oxides of nitrogen and hydro-
carbons as pollutants is primarily as participants in photochemical reactions
where NO- acts as primary light absorber. These compounds will therefore be of
importance to RAPS only if and when a study of photochemical reactions in the
atmosphere is planned.
B.6 Heat Emissions
The large amounts of energy produced and consumed by a city event-
ually are converted into heat, resulting in a "heat island" which has an effect
on atmospheric stability and thus affects modeling efforts. A heat emission
inventory is required for a comprehensive understanding of this effect in much
the same way as a pollutant emission inventory forms the basis for an understanding
of the fate of the pollutants.
Point sources contribute significantly to the heat emission inventory, since
a sizeable portion of the energy consumed is wasted as sensible heat of the stack
gases. Even in highly efficient power plants, about 20 per ceh't of the energy con-
sumed is wasted at the plant. In some industrial operations, such as blast furnaces,
essentially all of the heat of combustion is released to the atmosphere at the plant.
Actually, in a self-contained area such as St. Louis, not only the waste
heat turns up as heat emissions, but virtually all of the converted energy as
well. Except for minor amounts of energy stored as chemical energy (e.g., in
a primary aluminum plant) or radiated into space as visible light, all other
forms of energy, whether electrical or mechanical, are converted into heat and
released into the atmosphere, spread out over the inhabited area. Thus, as a
first approximation, the total Btu content of the fuel used at St. Louis can be
assumed to be released at either point or area sources. The amount of heat re-
leased by point sources can be calculated directly from fuel consumption and
-------
known conversion efficiencies of the power boilers; it can be verified by stack
analysis and measurement of gas volume and temperature, from which the
sensible heat above ambient can be calculated.
Since fuel consumption figures will be obtained in any case, a program to
calculate heat emission from point sources will be initiated. Significant point
sources, defined similar to pollution point sources, will be treated individually,
All other sources will be assigned to grid squares, whose total emission can
be estimated, given the daily total of heating or cooling degree days, average
wind speed, the day of the week and month of the year. Point sources can be
classified into industrial, commercial and residential sources; power generation
will be treated separately.
C. Sensitivity Analysis
An important aspect of every inventory is its accuracy. While no
inventory can be better than the numbers supplied by the data acquisition process,
a statistical estimate of the overall quality and probable error would help place
the uncertainties on a quantitative basis.
As a first approach to this problem, the National Air Data Branch
of EPA commissioned a study which produced a Weighted Sensitivity Analysis Program.
While this program does not supply any estimates of the absolute accuracy, it
does help evaluate the maximum permissible error of any part of the inventory,
given a maximum permissible error for the whole system. In doing so, it keeps
the inventory at an equivalent level of accuracy and points out areas where
accuracy has to be improved to provide a desired overall accuracy. In addition,
it also provides an approach to establish confidence levels for the emission
inventory.
The basic theoretical development proceeds as follows . The linear model:
22^ 22
QV - Z Q? oj
k=l k k
where Q. = total amount of pollutant emitted
100 0 = percentage error associated with Q
Q. = amount of pollutant emitted by subclass k
100 a. = percentage error associated with Q;
is postulated as an appropriate model to analyze the propagation of errors through
the emission inventory.
(5)See F. H. Ditto et al, Weighted Sensitivity Analysis of Emission Data,
Fed. Syst. Div., IBM, EPA Contract #68-01-0398 (1973).
-------
If each subclass contributes to the error an amount proportional to its
relative physical contribution, it can be shown that
The analysis demonstrates that to obtain a predetermined level of precision
for a source class, not all subclasses need to be measured with the same
precision; the greater the ratio of Q:Qi. becomes, the greater becomes the
allowable value of a. . Conversely, Q. approaches the value of 0 as the ratio
approaches unity (Figure 2). .*-'.,
The authors also developed a method for predicting the confidence level
for the inventory; that is, the probability that the actual overall error will
not exceed 0, using Chebyshev's theorem* '. The results for selected pairs
of (a and 1-c) are shown in Table III, where a = 29 and 1-c is the confidence
level .
A two-step procedure thus is suggested. First, establish the overaT1!
allowable error 0, either from user's (modeler's) requirement or as a trade-
off between confidence level and acceptable error interval; secondly, compute
the values of o. for the components of interest.
Applying these considerations to our case suggests thai, in the absence
of any definite information about the modeler's requi relrierits for the accuracy
vf of emission data, a fairly stringent set of conditions would be a confidence
level of 95 per cent and an acceptance interval of 10 p€r cent (these conditions
are probably stricter than the accuracy of the emission data), this would lead
to a permissible maximum error 0 of 2.2k%
Using the emission values in the latest NEDS inventory, as shown in
Table IV, we can now calculate the allowable error for source classes of
various sizes, such as 100 tons/year, 1000 tons/year, etc. For example,
the allowable error for a 100 tons source of SO. would be
(6) Miller, I. and J. E. Freund, Probability and Statistics for Engineers
Prentice-Hall, 1965.
11
-------
5*
10 .
0 0.1 0.2 0.3 O.i» 0.5 0.6 0.7 0.8
Source: Reference (A)
QK/Q
RELATIONSHIP BETWEEN OK AND QK/Q
Figure 2
0.9 1.0
12
-------
Confidence Level
1-C
90%
95%
99%
0)
u
c
ID
4-1
Q.
s
U
5%
1.58%
1.12%
0.5%
10%
3-16%
2.24%
1.0%
20%
6.32%
4.47%
2.0%
TABLE III. VALUES OF 0 FOR SELECTED
PAIRS (a, 1-C)
Source: Reference (4).
13
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TABLE IV
POINT SOURCE EMISSION INVENTORY
NEDS, DECEMBER 1973
SO
X
NO
X
CO
HC
Part.
S0x
N0x
CO
HC
Party
STL Co.
112,206
34,979
1,178
9,255
12,129
Randolph
473,599
128,964
2,993
901
6,399
STL
12
2
39
15
6
City
,798
,647
,433
,965
,527
Mon roe
—
—
2
—
359
St.
1
Madi
202,
51,
,787,
^7,
271,
Charles
15,392
60,086
1,093
328
321
son Cl
630
423
726(7)
694
338
Jefferson
138
in ton
270
114
4
2
277
,384
214
63
3
835
Bond
—
—
—
—
~~
Frankl in
1 1 1 , 1 32
28,492
1,161
303
1 ,244
Grand Total
1,
2,
Wash.
9
5
2
1
900
(Point
187,296
310,993
836,270
78,476
323,952
St.
20
4
2
4
23
Clair
,816
,069
,617
,024
,623
Sources)
NEDS, 'December 1973
14
-------
a100T
100T
V87-296
100
The data are tabulated in Table V.
The very large a. for SO- , CO and evet NO , even for the relatively.
stringent statistical conditions, suggests that there is probably no. need
to obtain measured hourly values for 100 tons/year sources of the'se pollutants,
since in most instances NEDS can be relied upon to provide data of this accuracy.
Thus the collection of hourly data can be limited to source's of TtiOO ton/year
and larger. As indicated in Table III (Section C) , thi"s will redbce the
number of SO- sources to be measured to 62, the stationary Ct) sources to 13,
and the NO sources to 26. The remaining sources can tften be modeled as dis-
cussed in Section IV C3.
D. Size Distribution of Sources
The situation in St. Louis lends itself to a direct attack on the
problem of direct measurement of emissions because of tfne relatively limited
number of major point sources. In terms of SO-, the cuYr^nt National Emission
Data System (NEDS) inventory lists about 300 sources emitting oven ten tons
of SO. per year. Of these, only about 62 emit in excels of 1000 tons/year,
an additional 120 over 100 tons/year. (Since sources emitting less than 100
ton/year are likely to contribute less than 10% of the amount specified by the
National Air Quality Standards to ambient concentrations, they are usually
lumped with area sources.) The 62 largest sources, representing 15 companies,
are concentrated at 20 locations. Thus, the sheer physical magnitude of the
problem of collecting hourly data for the major sources of pollution appears
to be manageable within a reasonable budget.
The situation for other pollutants is somewhat similar. The data are
summarized in Table VI.
: Thus, if direct measurements of emission will be limited to sources emit-
ting in excess of 1000 tons/year, we need to obtain data from 62 sources at 20
15
-------
TABLE V
MAXIMUM ALLOWABLE ERROR a. FOR POINT SOURCES OF VARIOUS SIZE
ACCEPTANCE INTERVAL 10%, CONFIDENCE LEVEL 35%, Q = 2.24%
TOTAL P.S.
EMISSIONS, Q ALLOWABLE ERROR ak FOR PO
POLLUTANT TONS/YR.* 100 T/Yr. 1000 T/Yr.
S°2
CO
NO
X
HC
PART
1,187,296
1,684,79*
310,993
78,47*
323,952
244%
290%
125%
63%
127%
77%
92%
40%
20%
40%
NT SOURCE OF
10,000 T/Yr.
24%
29%
-
-
-
^Source: NEDS December 1973, except for CO, which is given in NEDS at
2,836,270, apparently in error.
16
-------
TABLE VI
SOURCES OF POLLUTANTS IN THE ST. LOUIS AQCR
POLLUTANT
SO,
CO
PARTICULATE
NO
HYDROCARBONS
Tons /Year
No. of Sources
No. of Locations
No. of Companies
3
>10
62
20
15
2
>10
121
15
11
>10
121
17
17
Total
30k
52
kl
3
>10
13
9
7
2
>10
18
8
I*
>10
62
13
13
Total
92
30
2k
3
>10
28
12
9
i
>10
78
25
25
>10
165
29
29
Total
271
66
63
3
>10
26
10
6
f
£.
>10
83
13
10
>10
256
36
34
Total
365
59
50
3
>10
23
10
10
2
>10
80
22
19
>10
165
24
22
Total]
279
56
51
.
Source: National Emission Data System*, C^ildeaswJ Powt SO..UIFG& Listifng^,,. S1IAQC.R, December 1973.
-------
locations for SO-, 13 sources at 9 locations for CO, 28 sources at 12
locations for particulates, and so on. Many of these sources overlap, thus
further reducing the data collection (but not the data recording) problems.
For example, of the 26 major sources of NO , 21 are also major emitters of
s\
S02« The extent of the overlap is shown in Table VII, which lists all major
sources of pollutants in matrix form.
E. Existing Inventory Data
Air pollution studies have been conducted in the St. Louis area for
many years, and several emission inventories have been developed. In 196^,
an "Interstate Air Pollution Study, Saint Louis-East Saint Louis Metropolitan
Areas" was undertaken by the U.S. Public Health Service. Questionnaires were
sent out to determine fuel use and combustible waste disposal practices in
the area as well as manufacturing activities. A revised emission inventory,
still based on 1963 data, was published in December 1966 as Phase II of the
Interstate Study.
After the Metropolitan Saint Louis Interstate Air Quality Control Region
had been established, the first comprehensive inventory was taken in 1968,
to serve as a basis for the Implementation Planning Program (IPP). Since
then, four more inventories have been compiled:
IBM Emission lnventory-1970
DAQED Emission lnventory-1971
. NATO Emission lnventory-1971
. NEDS Emission Inventory-1973
In addition, the following traffic and transportation inventories exist:
Streets and highways
Railways and vessels
The emission inventories in current use by the Missouri and Illinois
regulatory agencies were recently (Summer 1973) acquired and transferred to
the NEDS files.
18
-------
TABLE VI I
SOURCES OF POLLUTANTS IN THE ST. LOUIS AO.CR
EMITTING IN EXCESS OF 1000 TONS/YEAR
Source Name
All led Chemicals
Alpha Cement Co.
Alton Box Co.
Amoco
Anheuser-Busch Co.
Anlin Corp.
Chrysler Corp.
Clark Oil Co.
Columbia Quarry
East St. Louis Stone
Ford Motor Co.
Point
No.
01
01
01
02
03
01
02
03
04
05
06
01
01
01
02
01
02
03
Ok
01
02
01
01
02
Pol lutant
S°2
X
X
X
X
X
X
X
X
X
X
X
CO
X
X
Particu-
lates
X
X
X
X
X
X
N0x
X
X
HC's
X
X
X
X
X
X
X
X
X
X
X
Proposed
Stack
Sampl ing
X
X
X
X
19
-------
TABLE VI I CONTINUED
Source Hatne
• GMAC
Granite City Steel
Highland Electric .Co.
1 J 1 inois Power Co.
Laclede Steel
Point
No.
01
02
03
Ok
01
02
03
Qk
05
01
01
02
03
OH
05
06
07
03
' 09
10
11
01
02
03
Pol lutant
S°2
.
X
X
**
X
X
X
X
X
X
X
CO
X
X
X
X
X
X
X
X
X
Particu-
lates
/ \
X
X
X
X
X
X
X
X
.
"°x
X
X
X
X
X
X
X
X
X
X
X
X
ttC's
X
A
X
X
X
Propo$«d
Stack
Sampl incj
•x
X
20
-------
TABLE VI I C014TINUEU
Source Name
Mississippi Lime Co.
Mississippi Portland
'• Cement
Monsanto Chemical Co
Municipal Incinerator
NL Titanium L)iv.
PPG Glass
St. Joseph Lead Co.
Shell Oil Co.
Point
No.
OK
01
01
02
03
Ok
05
06
07
OG
09
01
02
01
02
03
04
01
01
02
01
02
03
04
S\ I—
Pollutant
S°2
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
V
CO
X
X '
X
X
Particu-
lates
X
X
X
X
X
X
X
NO
X
X
HC's
X
X
Proposed
Stack
Sampl ing
X
X
X
X
X
X
X
X
05
21
-------
TAbLE V! I COUTUIUtD
Source Name
Shell Oil Co.
Socony
Stol le Q.uarry
Texaco.
Union Electric
Point
No. •
06
07
08 -
09
10
11
12
01
01
02
01
01
02
03
OA
05
06
07
08
09
10
11
12
13
}k
Pollutant
S°2
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
CO
Particu-
lates
X
X
X
X
X
x
X
MO
X
X
X
X
X
X
X
X
X
X
X
X
HC's
X
X
X
X
X
Proposed
Stack
Sampl ing
X
X
X
22
-------
TABLE VI I CONTINUED
Source Name
Union Electric
• TOTALS
Point
No. •
15
16
17 .
96
Pol lutant
so2
X
X
X
62
CO
13
Particu-
lates ,
28
N0x
26
HC's
23
Stack
Sampl ing
17
23
-------
These inventories are described in detail in SRI Report "A Regional
Air Pollution Study Preliminary Emission Inventory" (1971*) EPA No. 68-02-1026.
Most of these inventories .are only of historical interest. Current data
are contained in the National Emission Data System (NEDS) inventory, ad-
ministered by the Federal EPA,and similar inventories kept by the Illinois
EPA and the Missouri agencies.
The NEDS inventory contains information on annual emissions of the five
"criteria" pollutants (particulates, SO-, NO , hydrocarbons [HC] and CO) from
stationary point and area sources, as well as a listing of selected industrial
materials emitted by chemical process, food, agriculture, chemical and mineral
products industries, petrochemical operations, wood processing, and incinerators,
From the point of view of the Regional Air Pollution Study, the NEDS
inventory has two major uses: it contains emission data for those sources for
which detailed data are unavailable, and it provides a basis for an analysis
of the problem of obtaining measured data. It therefore can serve as an in-
terim data base for the St. Louis study until the RAPS inventory becomes
operational.
IV. Emission Data Acquisition
A series of sequential steps leads to the eventual acquisition and re-
cording of point source inventory data for the RAPS inventory. The steps are:
Survey
Classification of Sources into Acquisition Groups
Acquisition of Data by:
1) Stack analyses
2) Fuel consumption or process data
3) Derivation from operational data
Transformation of Data and Entry into Computer Bank
(7) APTD-1135, "Guide for Compiling a Comprehensive Emission Inventory",
March 1973.
-------
A. Survey
Classically, data for emission inventories are acquired by the use of
questionnaires which are either mailed out or prepared by the interviewer or
inspector on a one-time basis. -
The requirements of the RAPS inventory for hourly measured data for a
period of a year far exceed the normal reporting routine and require special
arrangements with the management of the various facilities. Thus, personal
contact with the appropriate corporate office by mai1, phone and, ultimately,
in person was considered essential to obtain the necessary cooperation. The
request was made for access to data which would provide a basis for calculating
hourly emissions (using OMB approved NEDS questionnaires as a starting point).
Such data could be
stack concentration measurements
fuel consumption records
process data
steam production records
These data, coupled with the necessary secondary information, such as stack
gas volume, concentration of sulfur in fuel or in process materials, etc.,
will permit the calculation of the weight estimates of pollutant (e.g., S0_)
emitted per hour.
As a sample, appropriate officials of nine of the 15 companies emitting
more than 1000 tons/year (shown in Table 2) were contacted and interviewed.
These included Union Electric, Illinois Power, St. Joseph Lead, Alton Box Board,
Lacle.de Steel, Monsanto Chemicals, Anheuser-Busch, Shell Oil Company, and Amoco
Oil. These nine companies are responsible for over 30% of the total SO-
emitted from point sources in the St. Louis area (based on NEDS data). All
but two agreed to supply the necessary hourly data to RAPS; this includes
the utility companies, who are emitting approximately half of all the S02 in
the area. Thus, even if the percentage of cooperation of the smaller companies
should drop off, it appears that measured data for at least 30% of the total
emission of S02 will be available. The accuracy of these data is of the order
of the finance accounting procedures used by the companies, which is higher
than that of chemical analysis.
25
-------
This type of a survey will be continued to include the remainder of the
major sources. There are two levels at which the initial information has to
be gathered:
1. Management level
2. Operational level
At the management level, an "agreement in principle" is required; usually
operational personnel is present at these meetings since they will later on
be involved. After an agreement is reached, the details of the data acquisition
are worked out with operational personnel.
The following information is then secured from information gathered at the
operating level:
1. Source Description: address, location (by UTM coordinates),
type of operation (SIC and SCC Codes), etc. Most of this
information is available in the NEDS printout but has to be
verified (particularly location, which should be to ± 0.01 Km).
2. Needed Data; pollutant concentration in stack (rarely
available), quantity and type of fuel burned, amount of steam
produced, fuel analysis, process information (weight and analysis),
etc. All of these data should be on an hourly basis; if they are
not, the time interval should be noted, as well as time related
variability. .... ;; |&
•%&*$'
3. Col lection of Data; data collection will biSVar ranged so as to
minimize the effort required by the affected companies. A mes-
senger circuit will be set up to pick up data once a week (or
other agreed-on time interval). If required, the data may have
to be reproduced; in some cases, mail arrangement will be worked
out.
For point sources emitting less than 1000 tons/year, as well as those major
sources where detailed data are not available, hourly emissions have to be
derived by a model, as discussed further on under B3. For these sources, the
following information is necessary.
1. Source description - as above.
2. Work schedule
3. Maximum process and space heating loads
k. Monthly and shift fuel weighting
5. Fuel analysis data
26
-------
B. Classification of Sources into Acquisition Groups
the division of sources of pollutants into major (those emitting more
than 1000 tons per year) and minor (emitting between 100 and 1000 tons/year), which
is based on sensitivity analysis discussed above, produces two broad categories.
Data from sources in Category 1, .the major sources, will be collected on an hourly
basis to the extent that they are available. Data from all other sources, that ,
is the minor ones and those of the larger ones where detailed data are not avail-
able, will be derived by a modeling or algorithmic procedures.
In Group 1 are the utilities and the majority of sources emitting over 1000
tons/year of pollutant, as determined by the initial survey of sources. The
data available from these sources permit a direct calculation of the weight of
pollutants emitted any given hour.
Although sources in Group II contribute only a minor portion of the overall
pollutant load, they may be of considerable significance locally. Under certain
conditions it may become necessary to obtain measured emission data from some of
these sources as a special project.
C. Acquisition of Data
Cl. Stack Gas Measurements '•'<• ••••• <
The RAPS emission inventory should ide-aTly coritain direct statements
of weight of pollutants emitted from each major source as a function of location
for every hour. The most direct way to acquire this information would appear to
be to monitor stack emissions. '
In actuality, emissions (in terms of weight of pollutant) cannot be directly
measured. Stack gas analyzers only provide a measure of the concentration of the
pollutant, thus requiring another measurement — stack gas volume — before the
weight of the emitted pollutant can be determined. Stack gas volume, in turn, is
not measured directly, but rather is determined by measuring the gas velocity by
traversing the cross-section of the stack. From the average velocity and the
known dimension of the stack, the volume of the stack gases can be calculated.
In addition, the molecular weight of the sampled gas has to be determined to ob-
tain theipass flow rate. Thus, the seemingly direct and straight-forward approach
to the determination of pollutant emissions by stack analysis actually consists
of a number of measurements, manipulations and calculations, each of which con-
tributes to the accuracy of the final figure.
27
-------
(Vi the case of SO , there is an alternative approach since all of the sulfur
.*.'' "
is contained in the fuel and is either emitted in the stack gases or remains in
the residue (ash). The distribution of SO_:SO_ in stack gases has been found
to be about 98-9941- Therefore, the amount of SO. emitted can be determined
quite accurately from fuel consumption and analysis figures, and the SO. inventory
for RAPS will be obtained in this manner. With other pollutants, there is no
choice, and stack sampling is the only way to obtain the desired information.
Stack sampling methods for compliance purposes have been standardized. EPA
methods are described in CFR Title AO (Protection of Environment) as an appendix
to paragraph 60.85. The methods are:
Method 1: Sample and Velocity Traverses for Stationary Sources
Method 3: Gas Analyses for C02, Excess Air and Dry Molecular Weight
Method k: Determination of Moisture in Stack Gases
Method 5: Determination of Particulate Emissions from Stationary Sources
Method 6: Determination of S02 Emissions from Stationary Sources
Method 7: Determination of NO Emissions from Stationary Sources
/\
Method 8: Determination of Sulfuric Acid Mist and S0» from
Stationary Sources.
Method 9: Visual Determination of Opacity of Emissions from
Stationary Sources.
For the purposes of the Regional Air Pollution Study, continuous instrumental
monitoring would seem to be preferable to the wet chemical analyses employed by
the EPA methods. A mobile van containing instrumentation for the determination
of S09, CO, HC, NO and possibly particulates is expected to be used in the later
£ ' f\
stages of the emission inventory.
Stack sampling is time consuming and expensive; for this reason, it should
be used only to provide a primary calibration of emission factors which are
used in conjunction with more readily accessible data, such as fuel consumption
or processing rates. The most extensive collection of emission factors is con-
tained in EPA's "Compilation of Air Pollutant Emission Factors" (AP-1»2) which
is in almost universal use. Nevertheless, emission factors contained there
are averages and vary widely in accuracy. They are rated for estimated accuracy
28
-------
on a scale ranging from "A" to "E", depending on the number and quality of field
measurements on which they are based.
To insure the accuracy of the RAPS emission inventory, some stack testing
has to be performed. Such testing should include at least one example in each
SCC category; if budgetary constraints permit, a considerable number of important
(8)
sources should be sampled individually (the SRI report suggests a total of 65
stack tests). Tables VIII and IX show the distribution of the major sources by
SCC categories.
By combining similar sources and matching categories with actual sources in
the St. Louis AQ.CR, the following minimum schedule (Table X) was determined if
at least one installation of each type is to be represented.
The total of 19 stack tests should really be considered as a "Phase 1"
program, to be supplemented by further tests based on inspection and review of
existing facilities.
As discussed above, SO,, is the one pollutant for which adequate data can
be obtained with only minimal stack testing, at least for those facilities which
do not have any stack gas cleaning (scrubbing) equipment. At present, none of
the boilers are equipped with such scrubbers; experimental work is being con-
ducted with a "Catox" unit at the Wood River power plant.
Though fuel consumption and process data are potentially capable of providing
quite accurate S0_ emission figures, there is a hitch: sampling for sulfur analysis
is not usually done adequately. Practices vary widely; some plants have continuous,
automatic samplers, but these are located at the coal-pile end of the conveyor
system. Since there are usually storage bins in the boiler-house itself, there
is an 8 to 12 hour lag between the sample and the material burned. Most plants
sample only intermittently — once a shift, once a day, even once for each barge.
Fortunately, the sulfur analysis of coal does seem to be fairly constant (about
+_ 10%). A statistical evaluation of the sampling procedures will be performed;
when possible, the time lag will be incorporated in the calculations.
There is a way to get good coal samples, and that is to sample at the pul-
verizing mill, immediately ahead of the injection point into the furnace. If the
sampling becomes a problem, it may be necessary to attempt sampling at that point.
Data for NO will have to be based almost wholly on stack testing. The EPA
J\
emission factors span a range of 3 to 55 pounds of NO per ton of coal,
(8) A Regional Air Pollution Study (RAPS), Stanford Research Institute,
Preliminary Emission Inventory
29
-------
TABLE VII I
DISTRIBUTION OF LARGE SOURCES IN THE ST. LOUIS AQCR BY SCC CODES
External Combustion Boilers
SCC Code
Description
Number
1-01-002-01
02
03
08
1-02-002-01
02
Ok
09
OOJ»-01
02
External Combustion Boilers, Elect. Gen., Bitum. Coal, Pulv., wet
> 100 x 106 Btu/hr.
Pulv., dry
Cyclone
Stoked
External Combustion Boilers, Industrial, Bitum. Coal, Pulv., wet 1
> 100 x 106 Btu/hr. Pulv.,dry 3
Stoked 5
Stoked ' 5
Residual Oil 4
Residual Oil 1
30
-------
. TABLE IX
DISTRIBUTION OF LARGE SOURCES IN THE ST. LOUIS AQCR BY SCC CODES
Process Heaters & Processing Emissions
SCC Code
Description
Number
3-01-023-99 Industrial Process
999-99
Chemical Mfg.
H2SO^-Contact
Hi seellaneous
2
2
-03-010-01
Lead Smelter
-04-00^-03
-06-001-03
00]-Qk
002-01
999-98
Secondary Metal
Petroleum Ihd.
Lead Smelter
1
Process Heater,Oil 2
,Gas *
Fluid Crackers k
,; M'f seel laneous
1
31
-------
TABLE X
MINIMUM TEST SCHEDULE
A. -POWER GENERATION
Equipment
Ext. Combust. Boiler
n
n
Fuel
Bitum. Coal
n n
Oil
Minimum No.
Firing Mode of Tests
Stoked
Pulverized
Cyclone
2
2
2
1
Suggested
Location
Monsanto
Wood River-Labadie
Sioux-Baldwin
Shell Oil
B. INDUSTRIAL SOURCES
Industry
Chemical Industry
Prim. & Sec. Metals
Petroleum
Type
Sulfuric Acid
Mi seellaneous
Heaters
Crackers
Others
Minimum No.
of Tests
. i:
2
2
2
1
10
Suggested
Location
N.L.
Monsanto-Anl in
St. Joseph
She 11-Amoco
Shel1-Amoco
Amoco
32
-------
40 to 105 pounds of NO per 10^ gallons of oil.
C2. Fuel Consumption and Process Data
From the point of view of sampling methodology, there is no real
difference between emission data based on fuel consumption and data based on pro-
cessing of, as an example, a sulfide ore. In both cases, the hourly weight of
consumed material determines the amount of gaseous discharge. Process data are
more complex, though, since the amount of residual sulfur.may be more significant,
and variable then in the case of a simple boiler operation. Of course, if a
recovery operation is part of the process (e.g., a sulfuric acid plant), then
stack sampling may become the more reliable source of data. The pattern of
hourly variations may still have to be determined by process data unless con-
tinuous monitors are available.
An analysis of the NEDS inventory shows that the 62 point sources emitting
in excess of 1000 tons of SO- per year fall into the following categories (Table XI)
TABLE XI
CLASSIFICATION OF S02 SOURCES
SCC Code
1-01
; 1-02
3-05
3~xx
Category
Boilers, Electric Generation
Boilers, Industrial
Petroleum Processing
Other Industrial
Number
27
19
11
5
Thus, almost 75% (*»6) of the 62 sources (including all of the large ones) are
boilers; another \7% are concentrated in the petroleum industry.
Carbon monoxide, another combustion-related pollutant, has quite a different
distribution (Table XI l).
33
-------
TABLE XII
CLASSIFICATION OF CO SOURCES
SCC Code
1-01
3-01
-03,-0*»
06
5-01
Category
Boilers, Electric Generation
Chemical Process
Metal. Processing
Petroleum Processing
Incinerators
Number
1
2
6
2
2
Here the largest sources are metal processing (blast furnaces, etc.), petroleum
processing (cat. cracking) and certain chemical processes.
Even participate emissions are largely related to boilers; almost half of
the emission sources are boilers; another 25% comes from the mineral industry
(quarries, cement plants, etc.). The breakdown is shown in Table XIII. The
overlap of pollutants from different sources has been indicated in Table VII.
TABLE XI I I
CLASSIFICATION OF SOURCES OF PARTICULATES
SCC Code
1-01
3-03
3-05
3-06
Category
Bo i 1 e rs , Powe r
Metal Industry
Mineral Industries
Petroleum Processing
Number
13
k
7
k
-------
TABLE XIV
CLASSIFICATION OF NO SOURCES
x
SCC Code
1-01
1-02
3-05
3-06
Category
Boilers, Elect, generation
Boilers, Industrial
Industrial - Cement
Industrial - Petroleum
N umbe r
22
2
1
1
TABLE XV
CLASSIFICATION OF HYDROCARBON SOURCES
SCC Code
1-01
2-01
3-01
3-03
3-06
*»-03
4-02
5-01
Category
Boilers, Elect, generation
Internal Comb., Turbine
Chem. Industry
Primary Metals - Cooking
Petroleum Industry - Processing
- Evaporation
Surface Coating - Evaporation
Municip. Incinerator
Number*
(0)
(0)
(1)
(1)
w
(11)
(6)
(0)
9
2
k
2
bk
19
2
*Bracketed numbers are sources in excess of 1000 tons/year; unbracke;ted
are sources greater than 100 tons/year.
35
-------
The significance of the high percentage of power boilers lies in the fact
that data pertaining to boiler operations are usually well kept and more readily
available than data about process operations. Since S02 emissions can be calcu-
lated readily from fuel consumption and analysis figures, and the emissions of
other pollutants are closely related to fuel consumption and operating conditions,
the acquisition of hourly fuel consumption data will go a long way toward the
creation of an hourly emission inventory. For this reason, considerable emphasis
will be placed on the acquisition of hourly fuel consumption (and related data),
particularly in the early stages of the RAPS inventory effort.
The actual data obtainable cover a wide range of formats, from computer
printouts of hourly fuel consumption to strip and circular charts, and even
entries in log books. As an example, the logs of the Wood River Power Station
of the Illinois Power Company for 29 April 197^ are attached. Table XVI is a
computer printout, giving actual weight of coal used per hour, as well as information
on boiler efficiency, BTU/lb. of coal etc. for Unit 5- On the other extreme,
Tables XVII and XVIII show the oil and gas usage respectively of units 1, 2, and
3- Here data are available only per eight-hour shift and consist of single meter
readings.
C3. Operating Data
This group includes all those point emission sources which are
either minor (emitting less than 1000 tons/year) or for which no detailed hourly
data are available. Here it is necessary to fall back on the annual data recorded
in the NEDS inventory or the corresponding inventory of the local enforcement
(Q)
agency. An approach similar to Roberts v:7/ will be used to approximate the
emission patterns by determining the relative amounts of fuel used for space
heating and for process purposes and allocating each. Space heating require-
ments are distributed in accordance with degree-days (deviation of mean daily
temperature from 65°F in degrees) while process loads are determined from
appropriate month, day and shift factors. From these data, both the sulfur
and heat emissions can be calculated.
Roberts assumes that when the temperature, T, is between -10 and 55°F, there
is a linear relationship for the space-heating thermal load L . This Is expressed as
(9) For detailed description of such a system, see: Roberts, J. J., et al.,
Chicago Air Pollution Systems Analysis Progress, Argonne National Lab.,
ANL/ES-CE007.
36
-------
•ENERATION
GENERATORS
TURUINES
COHDCNSKR
OOILER
FUEL
WIRUT
K
5 a £
1 5 S
U <5 »>
i 3
z ..
3 9
8 8
d i9 i960 1026
25 4751 28 2if4 1961 1C28
30 4£4o 26 21117 l?73 1039
27 4826 28 2131 l'/66 I04l
29 4£46 20 2121 1970 1C29
19 3ilit! 27 1730 i;69 lOi'O
2ri tr.iL 11 1171 2C01 It'll
HEAT INPUT & MISCELLANEOUS
COAL. MILLION DTU
62115
OIL. MILLION OTU
TOTAL. MILLION BTU ,
(>21 15
COAL HEAT VALUE. BTU/LB ))030
FUEL OIL USED. GAL 0
AVO C W IN TEMP. T ,
to
242 £60 1108 114 8992 4.0 60 35 35 ^27 79 931 3'>7
242 £62 1108 114 9073 4.o .60 35 35 9>iC 79 $W 357
243 £00 lioO 114 8962 4.0 62 136 38 : 935 6I| 928 398
2143 679 1108 1)4 9131 4.0 63 -35 34' 153 78 949 398
2143 678 1108 n4 69(2 4.0 £o 35 311 S37 fO 933 3$
2>I2 £Cl 1106 Il4 9109 4.0 60 34 34 550 78 y46 397
385 £'i5 1108 it4 6793 4.o fo 38 37 1109 85 1212 44o
468 706 1108 1)4 8660 4.0 59 4o 39 i£86 91 1707 458
473 708 -lioO n4 8721 4.0 59 39 39 1663 91 t04o 459
4(0 704 noO 114 07(2 4.0 59 39 39 iC02 91 1043 458
'170 702 n ofl nil 00i8 4.o 59 4o 39 iC3i 91 1839 458
'171 yo1! 1108 n4 8808 4.0 59 4o 39 1877 91 1838 459
470 704 1108 114 08i4 4.0 59 4o 39 i08l 91 103!) 459
IK,-; 700 liofl il'i 8792 4.0 59 i)o 3V 1871 90 1828 458
366 700 1106 n4 8922 4,0 59 37 36 11474 04 I422 434
1425 6;a 1108 n4 6882 4.0 59 39 38 1573 88 1527 449
450 701 noQ n4 8783 4.0 £o 4o 30 1768 89 1714 455
46o 697 1108 n4 8706 4.0 59 4o 39 1892 91 1843 46o
1454 6j4 lioO Il4 8785 4.0 59 4o 39 1906 91 1662 45?
454 707 1108 114 8721 4.0 59 .4o 39 1892 91 1872 46l
l»5£ 711 1108 113 8729 4.0 59 4o 39 1858 91 1623 461
45!) 700 1100 n4 8623 4.0 59 4o 39 1900 90 1606 458
3cC 677 1108 tl4 6897 4,o 59 36 35 1537 8t 1510 420
24; (61 1108 ii4 68:>9 4.0 *;
TERMINAL DIFFERENCE *F
HTR A ,
HTR B „ j
H1" ° 20.0
HTR 0 |6 4
HTR Fl ,5 „ HTR F2 0_,
HTR 01 |? ( HTR 02 M (
•*) ^ Vl l«0 77 10£6 Tfl
HEATER DRAIN TERM OIFF 'F
HTR A g
HTR B . ,
HT" ° 35.3
HTR D 9>8
HTR Fl jj , HTR F2 , ,
HTR Ot 2 .. MTR 02 M ,
534 556 270 274 66
533 559 271 276 £6
533 559 272 275 5
534 561 "272 275 65
534 559 271 2?4 £5
536 5£o 271 275 64
557 £25 279 285 £3
579 669 2C4 291 63
577 671 287 23 65
576 668 287 296 66
574 (£.3 283 290; 67
576 664 282 2ta 67
575 «.64 204 291 67
376 664 283 Z'/> £8
561 617 275 280 69
569 645 280 287 69
5?4 658 281 2G8 68
581 672 284 290 67
578 672 284 291 £fl
581 676 284 291 £-7
584 682 286 2J2 t'7
581 674 264 291 67
352 £02 2?2N275 67
m7 •;•;•> 277 2£6 £6
BURNER TILT TIME
% A B
-1.30 TO -MS ,5 ,,.
+15TO° 428 2C5
OT°-1S 667 3?1
-15 TO -30 ,30 63;
MINUTES
(64 143 I'M 5ra 503 0.0 87.091.7 o 75.2 2.3 1.7 1052;
604 142 l4l 505 504 0.0 87.6 91. f 0 7£.0 2,k 1.7 ,10<2:
6C4 (42 139 505 503 0.0 86.5 91.6 0 75.9 2.4 1.£ lot-a-.
£84 142 140 307 507 0.0 88.2 91.6 0 75.9 2.$ 1.9 '0(6f
£84 ili2 l4c 506 507 0.0 8f.4 91.6 0 76.5 2.5 I.o 1^7;
£84 142 l4o 507 508 0.0 86.8 ?1.7 0 77-2 2.6 1.8 io!»
«34 135 133 544 544 o;o 63.7 91.5 o 59.8 i.3 i.£ 1015;
(04 127 123 576 579 o.o 00.2 51.3 0 130.7 2.3 1.5 ?9«
£64 121 119 582 3C4 -o.o 69.1 91.1 0 142.3 2-° I-11 '9r;
£f.4 123 121 582 583 0.0 90.1 91.0 o i4i.8 1.9 1.3 IOC4C
684 131 128 573 573 o.o 0'.).3 91.1 o. i42.J 1.8 1.3 lOic.
£34 129 126 575 57( o.o
yo.O 91.3 o i4i.o 2.0 i.4 trof
£04 128 125 574 576 o.o 90.3 51. 2 o i4i.7 1.9 1.5 tec*.
£04 129 i2t' 574 578 o.o Oj.o 91.2 o ilii.B 1.9 1.4 icr*
604 135 133 543 546 o.c 68.851.11 o 113.9 2.1 1.6 103;'
(84 132 130 561 562 0.0 89.391.5 0 121. 1 2.0 1.5 1017-
£04 125 122 570 572 O.C 69.5 91.1 0 134.0 2.0 1.3 1007-
£64 127 124 579 360 o.o 90.0 91.2 o 142.7 *•<> ••* 77r-
£64 127 124 578 580 o.o 90.5 01. a o 143.3 1.7 1.4 ice*
664 127 124 580 562 0.0 90.2 91.2 0 i4j.4 1.9 1.4 99;
£64 125 122 584 566 0.0 90.2 91.1 0 142.9 1.9 I.* ?976
£fl4 I2£ 123 581 564 c.O C?.3 91.1 0 ik2.i 1.8 1.4 $y
£C4 138 136 537 538 o.c 94.3 91.4 o 111.7 I.O 1.6 l«c*
£91 i-ii 137 sn sof? D."
OPERATING DATA.
HOURS TURB. BLR.
THIS MONTH „- g.
THIS YEAR - .
SINCE START -own V.<&
GROSS MWH THIS MO ^^
AUK. MWH THIS MO lo£fc r
r.8.o 91.7 o 62. B 2.1 1.6 icZ5:
ILLINOIS POWER COMPANY
WOOD RIVER POWER STA.
HOURLY AND DAILY LOG
UNIT 5
BiTF ., «/ 7V
TABLE XVI
VjO
-------
TABLE XVI I.
Oso.
ILLINOIS POWER COMPANY
ftOCD RIVER POWER STATION
BOILERS 1, 2, 3 DATA
DATE.
COAL SCALE
Sltift 12 MN • 0 AM
1. Hde- ct 8 AM
2. R
-------
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the above listing of equipment out of service.
J r/hAAi
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Supoiviv,or ^\r>n^° '2 M
09
VD
-------
HO.
Then the total thermal load is
i .s j. .p
L = L + L ,
P
where L , the process load, is determined from the appropriate month, day,
C 0
and shift factors. The amount of load due to coal, L , and due to oil, L ,
is then determined, and the SO- emission due to each source is calculated as
follows:
r If /h \ - L (therms/hr) x 10^(Btu/therm)
l, uons/nr; - 12000 (Btu/lb) x 2000(lb/ton)
SO^lb/hr) = C(tons/hr) x 38 x %SC;
0(kgal/hr) = L°(tnerms) x 105(Btu/therm)
18000(Btu/lb) x 8000(lb/kgal)
S0°(lb/hr) = 0(kgal/hr) x 157.0 x %S°.
Thus, the total SO- emission is
S02 = SO^ + S0°.
When the ambient temperature is such that a dual-fuel interruptible plant
is probably receiving natural gas, the amount of SO- produced is correspondingly
reduced.
To facilitate data storage according to a uniform and consistent format,
each plant is assumed to have four stacks. For plants having less than four
stacks, zeros are filled in for nonexistent stacks. The following parameters
are associated with each stack:
1. SO- emission in pounds per hour
2. Heat emission in therms per hour.
These parameters are determined by weighting the total SO- and heat emissions
for the plant by the percentage emitted from each stack. The heat emission, H,
is assumed to be \5% of the thermal input.
-------
V. Handling of Emission Data
As indicated in Section IV-C2, emission (or emission related) data will
be provided in many different forms, ranging from computer printouts to strip
or circular charts. The raw data will have to be read off the original records
and tabulated in appropriate form before entry into the RAPS computer bank.
The format for the RAPS emission data storage has not yet been finalized.
A data handling system (System 2000) will be used which is capable of storing
data elements of variable length in repeating groups. The repeating groups define
the structure for storing multiple sets of data values and link the hierarchical
1 eve1s.
Data preparation forms will be designed to aid the data clerk in the struc-
turing of the data and to make it easier to use the correct syntax. It will not
be possible, however, to depend only on well-designed data preparation forms for
data quality because the content as well as the form of the data must be verified.
Data verification can be carried out in part by the data management system,
probably using a preliminary storage file which can be verified, proofread and
corrected before the data manager decides that it is accurate enough to merge
into the main file.
A detailed instruction sheet has to be prepared for each data sheet for
the guidance of the data clerk. This sheet has to stipulate the units (if not
indicated on the original record) and specify the manipulations, if any, which
have to be performed to obtain hourly data which can be fed into the computerized
RAPS inventory. In order to avoid human error as far as possible, only a minimum
of handling will be carried out. For example, data will be recorded in whatever
unit it is supplied and the units made part of the record. Transformation into
standardized units can then be performed by the retrieval program to meet the
specific needs of the user.
For most actual sources, the values stored will be consumption or other
source data, rather than measured values of emission. The format will accom-
modate emission or consumption data. For those sources for which there are no
direct emission data, emissions must be calculated using emission factors or
models applied to the stored data. The emission inventory software system will
-------
be capable of assessing the consumption data element, refer to the appropriate
code, look up the emission factor of model, and compute the emission values for
each specified set of pollutants.
VI. R'A'PS Inventory Acquisition Schedule
Th'e acquisition of the RAPS emission inventory comprises the following
elements: 1) Survey and arrangement for data collection from measured sources;
2) Data acquisition and processing; 3) Acquisition of data from smaller
sources; k) Source testing.
The survey of sources from which hourly data should be obtained should be
accomplished in about three months; this will include detailed arrangements which
will spell out:
which sources will be observed.
what data will be forthcoming.
the necessary factors to transform available data into mass emission
units.
the mechanism of data collection.
During the next three-month period, data will be collected and their
transformation into machine readable data accomplished. Data collection will
continue for at least a year, possibly longer.
Data from lesser sources will be collected concurrently, beginning with
about month 6 or 7. Appropriate algorithms will be designed to provide
hourly emission values. t''' '
* - ' £•:: '
A source testing program will be set up (jjnder another task order) to pro-
vide verification of the emission factors and other assumptions used in the
program. This should be an on-going effort, utilizing a mobile test unit and
providing calibration data on 20 to 60 sources. The more sources are tested,
the more reliable the inventory will become; this effort is limited mostly by
budgetary considerations. A minimum program was outlined in Section C-l (p. 27).
This schedule is shown graphically in Figure 3.
-------
Months
1 . Survey & arrangement
for data collection
from measured sources.
2. Data acquisition and
processing.
3. Acquisition of data
from smaller sources.
k. Source testing.
1, 2, 3
k\ 5I 6
'
) 7, 8, 9
10, 11, 12
1 13I ]k\ 15
July Oct. Jan.'75 April
FIGURE 3. RAPS INVENTORY SCHEDULE
July
Acquisition of data (Step 2) will start about 1 October, li>7*»> using cJata
obtained from Union Electric Company to check out the data entry system. By
1 November data from Illinois Power Co. will be added. Additional data,
including all major sources (but limited to S02 only) will be included
gradually. By 1 January 1975 the inventory of hourly SO^ emissions from all
major sources should be operational. Data from lesser sources will then be
incorporated.
All incoming data will be entered on coding forms and visually checked for
discrepancies. The tabulated data will then be transferred onto machine readable
cards for delivery to NADB. Cards will be sent to NADB once a month.
VII. Summary and Conclusions
The history and purpose of the Regional Air Pollution Study in St. Louis
was reviewed from the point of view of emissions of air pollutants and their
inventories. Based on NEDS data on the size and distribution of the principal
sources of air pollution and on a Weighted Sensitivity Analysis supplied by
NADB, an emission inventory program methodology was designed to provide hourly
data on criteria pollutants, with initial emphasis on sulfur dioxide. The
criteria for choices were the estimated requirements of the most critical users
of the data, the investigators working on dispersion model verification.
-------
The methodology envisages a two-level approach: the measurement of
hourly emissions or emission related data for the principal sources, defined
as those emitting in excess of 1000 tons of pollutants per year, and a simu-
lation of hourly emissions for smaller sources, based on yearly outputs and
appropriate information on the consumption or production cycle.
The successful accomplishment of these goals should provide an emission
inventory of a much higher accuracy than has heretofore been available.
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. REPORT NO.
2.
3. RECIPIENT'S ACCESSION-NO.
4. TITLE ANDSUBTITLE
Regional Air Pollution Study Point Source Methodology
and Inventory
5. REPORT DATE
October 1974
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO.
Fred E. Littman
9. PERFORMING ORGANIZATION NAME AND ADBRESS
10. PROGRAM ELEMENT NO.
Science Center
Rockwell International
1049 Camino Dos Rios
Thousand Oaks, California
11. CONTRACT/GRANT NO.
91360
68-02-1081
12. SPONSORING AGENCY NAME AND ADDRESS
U. S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Research Triangle Park, N.C. 27711
13. TYPE OF REPORT AND PERIOD COVERED
Final-2/74-10/74
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
16. ABSTRACT
An emission inventory constitutes the starting point for any attempt to
control emissions to the atmosphere. As long as such controls deal with average
yearly concentrations, inventories giving total annual emissions of the various
sources of pollutants are sufficient. The Regional Air Pollution Study has,
however, as its first goal the validation of atmospheric dispersion models,
which attempt to predict ambient pollutant concentrations on an hourly basis.
Therefore, emission values derived from total annual emissions are largely in-
adequate, and the RAPS emission inventory was conceived to provide the needed
time resolution and accuracy by measuring and recording hourly emissions (or
parameters directly related to hourly emissions) and/or individualized hourly
estimates derived for the principal sources of pollution. Thus, the emission
inventory for the Regional Air Pollution Study (RAPS) at St. Louis is distinguished
from existing emission inventories by two factors: its time and space resolution
and its accuracy.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b. IDENTIFIERS/OPEN ENDED TERMS C. COS AT I Field/Group
SMSA
Emission Inventory
Point Sources
Pollutants
SCC
AQCR
18. DISTRIBUTION STATEMENT
Release Unlimited
19. SECURITY CLASS (This Report)
Unclassified
21. NO. OF PAGES
45
20. SECURITY CLASS (Thispage)
Unclassified
22. PRICE
EPA Form 2220-1 (9-73)
-------
EPA-600/4-76-013
March 1976
METHODOLOGY FOR INVENTORYING
HYDROCARBONS
By
Philip DiGasbarro and Mark Bornstein
GCA Corporation
GCA/Technology Division
Bedford, Mass 01730
Contract No. 68-02-1006
Task Order No. 7
Project Officer
Charles C. Masser
Monitoring and Data Analysis Division
Office of Air Quality Planning and Standards
Research Triangle Park, N.C,. 27711
U.S. ENVIRONMENTAL PROTECTION AGENCY
OFFICE OF RESEARCH AND DEVELOPMENT
ENVIRONMENTAL SCIENCES RESEARCH LABORATORY
RESEARCH TRIANGLE PARK, N.C. 27711
-------
CONTENTS
Page
List of Figures iv
List of Tables v
Chapters
I INTRODUCTION 1
II REVIEW OF HYDROCARBON PROGRAMS 3
AIR QUALITY STANDARDS 3
STATUS OF NEDS FOR INVENTORYING HYDROCARBONS 4
REGULATIONS FOR THE CONTROL OF HYDROCARBON 11
CONCLUSION 13
III DESCRIPTION OF REGION 14
IV HYDROCARBON STATIONARY SOURCE IDENTIFICATION 18
PROCESS AND EVAPORATIVE SOURCES 18
DEVELOPMENT OF MAILING LIST 23
COMPUTER LABELS AND WORK SHEET 26
MAILING OF QUESTIONNAIRE 27
LOGGING OF RETURNS AND FOLLOW UP 31
RECONTACTING 32
V DATA COMPILATION 33
MANUAL APPROACH 34
COMPUTER DATA HANDLING SYSTEM 63
ii
-------
CONTENTS (Continued)
Chapter Page
VI APPLICATION OF THE HYDROCARBON METHODOLOGY
TO THE REGIONAL AIR POLLUTION STUDY 66
REFERENCES 73
Appendix
A QUESTIONNAIRES 75
B LABEL AND WORK SHEET COMPUTER PROGRAM 88
iii
-------
FIGURES
No. Page
1 Required hydrocarbon emission control as a function of
photochemical oxidant concentration 7
2 Metropolitan Boston Intrastate Air Quality Control Region 17
3 Label contents 26
4 Work sheet contents 28
5 Cover letter 29
6 General instructions for completing questionnaire 30
7 Distribution of total hydrocarbon emissions except from
automobile travel (35,900 tons/year) 36
8 Gasoline flow (106, millions of gallons) and resulting
hydrocarbon (HC) emissions 62
9 Hydrocarbon emissions for the Saint Louis Air Quality
Control Region. 67
iv
-------
TABLES
No. Page
1 COMPOSITE REACTIVITY INDEX VALUES FOR SELECTED
HYDROCARBONS 5
2 NATIONWIDE ESTIMATES OF HYDROCARBON EMISSIONS, 1970 9
3 "BEST ESTIMATE" REACTIVITY RANKING OF MAJOR EMISSION
SOURCES 10
4 MANUFACTURING EMPLOYEES IN REGION BY SIC CATEGORY, 1973 15
5 GUIDELINES TO DETERMINE WHAT COMPANIES WILL BE SURVEYED 25
6 SUMMARY OF HYDROCARBON EMISSIONS 35
7 HYDROCARBON SOURCES GREATER THAN 5 TONS/YEAR, 1973 37
8 SURVEY COVERAGE AND RESULTING EMISSIONS 38
9 POINT SOURCE WORK SHEET 40
10 AREA SOURCE WORK SHEET 41
11 SAMPLE SHEET FOR THE ANALYSES OF TYPE OF HYDROCARBON
EMISSIONS FOR STANDARD INDUSTRIAL CODES (SIC) 43
12 TYPE OF HYDROCARBON EMISSIONS VERSUS SIC FOR DECREASING 44
13 SIZE DISTRIBUTION OF HYDROCARBON EMISSIONS FOR
DECREASING 45
14 PERCENTAGE BREAKDOWN OF TRADE PAINT SALES FOR
U.S. REGIONS 52
15 PERCENTAGE BREAKDOWN OF INDUSTRIAL PAINT SALES FOR
U.S. REGIONS 53
16 PERCENTAGE OF SOLVENT CONTENT FOR TWO DRYING METHODS
VERSUS FIVE PRINTING PROCESSES 54
17 NATIONAL SOLVENT USAGE (TONS/YEAR) 55
18 PROCESSES EMITTING HYDROCARBON FROM MANUFACTURING 57
-------
TABLES (Continued)
No. Page
19 HYDROCARBON EVAPORATIVE LOSSES AT BULK STORAGE SITES 59
20 EMISSIONS: LOSSES-PER 1000 GALLONS TRANSFERRED 61
A-l QUESTIONNAIRE TO MANUFACTURING INDUSTRIES AND
DRY CLEANERS 76
A-2 STUDY AREA BULK STORAGE INFORMATION 86
VI
-------
CHAPTER I
INTRODUCTION
This document describes the methods for obtaining stationary source
hydrocarbon emission inventory information, cataloguing the information
consistent with the National Emission Data System (NEDS), and presenting
the information for the evaluation of control strategies. The acquisi-
tion of statistical data and the procedure for surveying hydrocarbon
stationary sources are described step-by-step. Both the manual approach
and the use of computer data handling system are discussed for the
analysis of data. Methodology development and application to the EPA
Regional Air Pollution Study (RAPS) is also presented.
The definition of hydrocarbon emissions concerned in this report should
be clarified. Hydrocarbons are normally thought of as compounds whose
molecules consist of atoms of hydrogen and carbon only. Organic com-
pounds include all compounds of carbon except the oxides of carbon, the
carbides and the carbonates. Therefore, hydrocarbons are organic com-
pounds. However, all organic compounds, including those which contain
additional elements such as nitrogen, oxygen and chlorine, are also
defined here as hydrocarbons. Throughout the report, the term hydro-
carbon emissions will be synonymous with gaseous and the volatile portion
of particulate organic compounds entering the atmosphere.
This report contains five additional chapters. Chapter II reviews the
programs concerning the reduction of hydrocarbon emissions. Chapter III
describes the methods for collecting information of the study area.
i
Chapter IV delineates the procedure for selecting and surveying the
-------
hydrocarbon stationary sources. Chapter V discusses both the manual
and computer assisted methods for compiling and presenting the data.
And Chapter VI specifically addresses the utilization of this methodology
to the Regional Air Pollution Study Program.
-------
CHAPTER II
REVIEW OF HYDROCARBON PROGRAMS
Sinee the signing of the Clean Air Act and its amendments of 1970, many
programs have been and are being conducted in the area of pollution
related to hydrocarbon emissions. A review of the prog-rams dealing
with air quality standards, existing and evolving regulations, and the
present emissions inventory systems, will lead to an adequate definition
of the type of inventory information needed and the methods for col-
lecting this information.
AIR QUALITY STANDARDS
EPA has promulgated two air quality control standards directly or in-
directly concerned with hydrocarbons. The photochemical oxidant (or
ozone) standard states that the hourly average concentration shall not
exceed 0.08 ppm and the non-methane hydrocarbon standard states that the
6 to 9 a.m. average should not exceed 0.24 ppm (measured as "carbon").
The non-methane hydrocarbon standard was designed solely to meet the
oxidant standard. The document on Air Quality Criteria for Hydrocarbons
2
(AP-64) clearly concludes that "our present state of knowledge does not
demonstrate any direct health effects of the gaseous hydrocarbon in the
ambient air on populations, although many of the effects attributed to
photochemical smog are indirectly related to ambient levels of these
hydrocarbons."
Research programs have developed methods for assessing the reactivity
of various organic compounds present in auto exhaust and recently in
-------
the solvent and surface coating industries. The reactivities of the
compounds vary and classifications have been made according to classes
3
of compounds or for specific compounds as in Table 1. However, "with-
out additional information on the composition of the total hydrocarbon
mixture and variability, it is difficult to appraise the relationships
in the atmosphere between total hydrocarbon or non-methane hydrocarbon
2
concentrations and photochemical effects." Methane, a photochemically
inactive hydrocarbon usually comprises more than half of total atmos-
pheric hydrocarbon. An attempt to correlate photochemical products
with non-methane hydrocarbons/total hydrocarbons has been made for sev-
4
eral cities. This has resulted in the development of the Appendix J
curve, Figure 1, of the Federal Register (August,1971), which is used
in the implementation plans to determine the percent reduction required
in total hydrocarbon emissions in order to achieve the photochemical
oxidant standard. One should note this curve was formed using the upper
limit oxidant-nonmethane hydrocarbon points of various mixtures in cer-
tain cities over a certain period. It does not reflect the actual rela-
tionship of atmospheric hydrocarbons to photochemical air pollution levels
over any study area. The application is supposed to assure that more than
an adequate reduction is achieved.
STATUS OF NEDS FOR INVENTORYING HYDROCARBONS
Total hydrocarbons is one of the five criteria pollutants catalogued
according to point and area source categories. Point and area sources
definitions, along with the procedure for coding the computer input
forms, are found in the "Guide for Compiling a Comprehensive Emissions
Inventory" - APTD 1135. It should be added that a source could be in-
cluded as a point source if it can be controlled individually by a
specific regulation. For example, the hydrocarbon regulation in Los
Angeles, Rule 66, specifies "a person shall not discharge into the at-
mosphere more than 40 pounds of organic materials in any one day
(
-------
Table 1. COMPOSITE REACTIVITY INDEX VALUES
FOR SELECTED HYDROCARBONS3
Compound
2-Butene, 2, 3-dimethyl
2-Pentene, 2, 3-dimethyl
2-Butene, trans -
2-Butene, cis-
1-Butene, 2-tnethyl-
1-Butene, 3-methyl-
2-Butene, 2-methyl-
2-Ftexene, cis-
2-Hexene, trans -
3-Hexene, cis-
3-Hexene, trans -
2-Pentene
2-Pentene, cls-
2-Pentene, trans -
2-Pentene, 4-methyl-
1-Butene
1-Hexene
Formaldehyde
Isobutylene
1-Pentene
1-Pentene, 2 -methyl -
1-Pentene, 4-methyl-
Propylene
Propylene Oxide
Styrene
Vinyl acetate, monomer
Vinyl chloride, monomer
0-Xylene
m-Xylene
p-Xylene
Benzene, 1, 2, 4-trimethyl-
Benzene, 1, 3, 5-trimethyl-
1,3-Butadiene
. Butane, 2 -me thy 1-
Cumene
Cyclopentane
Isobutyl methyl ketone
Propadiene
Toluene
Toluene, diisocyanate
Toluene, m-ethyl-
Composite Reactivity Inc.
(0 to 10 scale)
10
9
8
8
8
8
8
8
8
8
8
8
8
8
8
7
7
7
7
7
7
7
7
7
7
7
7
7
7
7
6
6
6
6
6
6
6
6
6
6
6
-------
Table 1 (continued).
COMPOSITE REACTIVITY INDEX VALUES
FOR SELECTED HYDROCARBONS3
Compound
Composite Reactivity 'Inc.
(0 to 10 scale)
Toluene, p-ethyl-
Tr ichloroethylene
Ethylene
Ethyl benzene
Cyclohexane
Cyc1ohexanone
Cyclopentane
Cyclomethyl
Ethyl methyl ketone
Hexanol, 2-ethyl
Isopropyl alcohol
Methyl alcohol
n-Butyl alcohol
Acetone
Butyl acetates, mixed
Ethyl acetate
Ethyl alcohol
Benzene
Butane, 2, 2-dimethyl
Butane, 2, 3-dimethyl
Hexane
Hexane, 2-methy1-
Hexane, 3-methyl-
Fentane, 2, 3-dimethyl-
Fentane, 2,4-dimethyl-
Pentane, .2,-methyl -
Pentane, 3,-methyl-
Pentane, 2, 2, 4-trimethyl-
Acetylene
Butane
Cellulose acetate
Diethylene glycol
Ethane
Ethylene dichloride
Isobutane
Isopentane
Methane
Methane, trichlorofluoro
Methyl chloride
Methylene chloride
Peptane
Propane
Perchlorpethylene
6
6
5
4
3
3
3
3
3
3
3
3
3
2
2
2
2
1
1
1
I
1
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-------
AFPBMDIX J
HtoUUREO1- tar fHOTOCKWCAL 0«M»T COt^MMWUt^m
MOTE: NO HYDROCARBON OR PHOTOCMEMCAL
OXIDANT BACKGROUND ASSUMED
tat Jsc «o <» JM
MPHOTOCHEKCA onoMtr ewcarMw«.-|»*»
Figure 1. Required hydrocarbon emission control as a function of
photochemical oxidant concentration. (Reference: Air
Quality Criteria for Nitrogen Oxides, AP-84,
Environmental Protection Agency, Washington, D.C.,
January 1971)
-------
may be reasonable to choose 5 tons/year as a cut-off between point and
area sources. The decision is an arbitrary one which also depends on
the ease and cost of control and the extent of the photochemical problem.
Table 2 contains a summary" of the 1970 nationwide hydrocarbon emissions,
by source category. Transportation was the largest hydrocarbon source,
emitting 13.2 million tons (48.4 percent of the total) in 1970. The
other major sources are, evaporative losses of gasoline and solvents, and
industrial process losses. Combined, these sources contributed 9.6 mil-
lion tons (35.5 percent of the total), in 1970.
3
Another estimate of total hydrocarbon emissions is shown in Table 3.
This summary presents emissions from stationary source categories which
are generally higher than comparable estimates in Table 2 due to varia-
tions in methodology and data sources. The table also provides estimates
of "high reactivity" emissions. "High reactivity" emissions are defined
on the basis of photochemical reactivity or smog contribution as deter-
mined by simulative laboratory studies and represents that portion of
emissions from the various source categories with a composite reactivity
index of six or greater (see Table 1). High reactivity does not neces-
sarily correlate with biological response.
Unlike the carbon monoxide and sulfur dioxide, which are specific com-
pounds, the total hydrocarbon emissions consist of rmmfefp'us types of
organic compounds of varying toxicity and photochemical reactivity.
these organic compounds may be emitted as a single compound or in com-
binations with certain others. The types and combinations of these
compounds clearly depend on the process and item/product being manu-
factured or serviced. For some process categories, such as dry clean-
ing and degreasing, where operations are similar and standardized, the
type of pollutant (as a compound) in many cases can be presently spec-
ified in the NEDS system via the Standard Classification Code (SCC).
For some other categories such as chemical manufacturing and surface
coating, the pollutant type information is not specified because the
8
-------
Table 2. NATIONWIDE ESTIMATES OF HYDROCARBON EMISSIONS, 1970
_ P - Point sources
Source category
A - Area sources
Transportation (A)
Motor vehicles
Gasoline
Diesel
Aircraft
Railroads
Vessels
Nonhighway use of motor fuels (A)
Fuel combustion in stationary
sources (P, A)
Coal
Fuel oil
Natural gas
Wood, LPG and kerosene
Industrial process losses (P, A)
Solid waste disposal (P, A)
Agricultural burning (A)
Miscellaneous (P, A)
Forest fires3
Structural fires
Coal refuse burning
Gasoline and solvent
evaporation
Total
Emissions,
10" tons/year
13.2
12.0
11.9
0.1
0.4
0.2
0.6
2.0
0.3
0.2
0.1
0.0
0.0
5.5
1.5
0.3
4.5
0.2
0.1
0.1
4.1
27.3
Percent of
total
48.4
44.0
43.6
0.4
1.5
0.7
2.2
7.3
1.1
0.7
0.4
—
—
20.1
5.5
1.1
16.5
0.7
0.4
0.4
15.0
Includes prescribed burning.
-------
Table 3. "BEST ESTIMATE" REACTIVITY RANKING
OF MAJOR EMISSION SOURCES3
Source category
Total hydrocarbon
emissions
(10° tons/year)
"High reactivity"
emissions
(106 tons/year)
Solvent Evaporation
Solid Waste Combustion
(urban, domestic,
commercial, and
industrial)
Agricultural Waste
Combustion
Petroleum Products
Storage and
Marketing
Petroleum Production
and Refining
Chemical Process
Industry
Other Industrial
Processes
Fuel Combustion
Coal Refuse Burning
Forest Wildfires
Totals
7.1
4.5
4.2
2.3
1.9
1.4
~ 1.0
0.4
0.2
2.4 - 3.0
25.4 - 26.0
1.9
1.4
1.1
1.0
0.2
negligible
negligible
negligible
not estimated
not estimated
5.6
10
-------
SCO process code* have mot. bWfc d-eveiopad, OK tfce pollcpfUMte I*
categorized as solvent, paint solvent, lacquwr solvent, ete. Solvents
in mixtures vary but general classes could b« outlined and SCC's defined.
Still, for other categories such as area sources, where no SCC listing
exists, only the material -being stored, consumed or combusted is known.
Emission factors are applied to these area source categories to calcu-
late the total hydrocarbon emissions. If it is ever needed, the types,
amount and variability from each area source category could be deter-
mined. For example, the marketing of gasoline certainly emits roost of
the compounds found in gasoline and the more volatile in larger quanti-
ties. Also, combustion of certain fuels usually produce various types
of organic compounds within a limited concentration range.
REGULATIONS FOR THE CONTROL OF HYDROCARBON
A critical review of the existing and proposed regulations for the con-
trol of hydrocarbon emissions from stationary sources has recently ap-
Q
peared in the Journal of Air Pollution Control. In summary, the
various state and local agencies having a photochemical oxidant prob-
lem, ,have adopted some variation of the Los Angeles Rule 66.
Recently the National Paint and Coatings Association (NPC) has recorn^
mended modifications of Rule 66 for the control of Organic Solvents.
These are proposed for use as new Federal Guidelines. These regulations
or some slight modifications of them might eventually be adopted by the
states or local agencies considering control of stationary hydrocarbon
sources.
It is evident that some of these regulations at times apply selective
control to the particular categories or pollutant types. For example,
9
below is a part of the regulation on organic solvent use:
11
-------
A person shall not discharge into the atmosphere more than
40 pounds of organic materials in any one day, nor more than
8 pounds in any one hour, from any article, machine, equip-
ment or other contrivance used under conditions other than
described in section (a), (drying) for employing, or applying,
any photochemically reactive solvent, as defined in section (k),
or material containing such photochemically reactive solvent,
unless said discharge'has been reduced by at least 85 percent.
For the purposes of this rule, organic solvents include
diluents and thinners and are defined as organic materials
which are liquids of standard conditions and which are used
as dissolvers, viscosity reducers or cleaning agents, except
that such materials which exhibit a boiling point higher than
220°F at 0.5 millimeter mercury absolute pressure or having
an equivalent vapor pressure shall not be considered to be
solvents unless exposed to temperatures exceeding 200°F.
For the purposes of this rule, a photochemically reactive
solvent is any solvent with an aggregate of more than 20
percent of its total volume composed of the chemical com-
pounds classified below or which exceeds any of the fol-
lowing individual percentage composition limitations,
referred to the total volume of solvent:
1. A combination of hydrocarbons, alcohols, al-
dehydes, esters, ethers or ketones having an
olefinic type of unsaturation: 5 percent;
2. A combination of aromatic compounds with eight
or more carbon atoms to the molecule except
ethylbenzene: 8 percent;
3. A combination of ethylbenzene, ketones having
branched hydrocarbon structures, trichlo-
roethylerte or toluene: 20 percent.
As specific and well defined as these regulations may be, the complex
problem of evaluating the number and type of hydrocarbons emissions
from a plant or class of industries still exists.
Under different circumstances, EPA has used different reactivity criteria
in developing control strategies. The control regulations for automotive
emissions require the control of all hydrocarbons. The regulations for
gasoline marketing and distribution control all emissions, except that in
some areas C. to Co paraffins, acetylene and benzene are exempted. For
12
-------
solvent usage, where control technology is not available, use of. less
reactive compounds has been permitted according to regulations :similar
to those given above.
CONCLUSION
From these earlier discussions, it is apparent that regulations have
been and are being developed with the concept of photochemical reac-
tivity. Up to now EFA has relied on the Appendix J relationship in
the development of the implementation plans because of the unknown
makeup and reactivity of the many organic components involved in the
complicated photochemical reactions and forming oxidants. Since re-
search is actively providing more information on these relationships,
it appears that an accurate catalogue for inventorying hydrocarbons by
type should be developed. Hie cataloguing of emissions should be con-
sistent with the existing and eventual control strategies for meeting
the oxidant standard. Toxicity effects should also be considered with
the expectation that some organic compounds, i.e., vinyl chloride, will
fall into the hazardous pollutant category.
13
-------
CHAPTER III
DESCRIPTION OF REGION
To properly study a hydrocarbon emission problem for an area in question,
it is necessary to have a complete description of the region. After the
study area has been chosen, all necessary maps of the area should be ob-
tained. City and county maps can usually be supplied by the State De-
partment of Commerce and Development. Traffic count maps should be ob-
tained from local and state highway departments and from metropolitan
planning agencies. USGS maps should be used to identify the location
(UTM's) of point sources.
It is very helpful prior to mailing a questionnaire, to have a general
understanding of the types of major industries that exist in the study
area. A list of manufacturing employees and/or number of establish-
ments versus SIC (Standard Industrial Classification) can quickly re-
veal the major type of manufacturing industries in the area. This
information can be obtained from the latest published Bureau of Census
Data or the State Industrial Director. Table 4, constructed for the
Boston AQCR, indicated SIC 38, 36, 31, 30 and 27 to be major industries.
Petroleum bulk storage and distribution and dry cleaning establishments
would also be included in any inventory because they are know emitters
of hydrocarbons.
Statistical information that will be needed for the apportionment of
hydrocarbon emissions to cities, towns, and counties are the following:
population, number of establishments, number of manufacturing employees
per SIC for cities, towns, counties, Standard Metropolitan Statistical
14
-------
table 4. MANUFACTURING EMPLOYEES IN REGION BY SIC CATEGORY, 1973
SIC category
20 Food
22 Textile products
23 Apparel
24 Lumber
25 Furniture
26 Paper
27 Printing
28 Chemicals
29 Petroleum
30 Rubber
31 Leather
32 Stone, clay, etc.
33 Primary metals
34 Fabricated metal
roducts
35 Machinery,
non- electrical
36 Electrical
machinery
37 Transportation
equipment
38 Instruments
39 Miscellaneous
manufacturing
Other
Manufacturing
employees8
21,900
5,400
17,300
2,400
3,000
11,600
25,000
9,000
1,000
12,100
13,200
3,000
3,400
17,500
34,000
52,000
16,600
25,600
6,900
5,600
286,000
~% ofb
U.S. Total
1.6
1.1
0.6
(1.7)
2.1
0.9
(0.5)
(2.3)
(3-9)
(0.5)
0.3
1.2
1.7
2.7
0.8
(6.2)
(1-5)
Primarily from September 1973 Massachusetts "Employment
Newsletter"
From ratio of 1973 Regional to 1970 National Bureau of
Census Data, values in ( ) from 1967 Census Data
15
-------
Areas (SMSA) and state. This information is usually available in
Bureau of Census publications. Information about the labor force, pop-
ulation characteristics and geni&al information for cities and towns
can possibly be obtained from the local Development Council or the State
Department of Labor. Often it is compiled in monographs for the respec-
tive city or town by state agencies.
Data concerning the amount of fuel consumed, transferred, stored, and
produced for each state can be obtained from the "Mineral Industry Sur-
veys" prepared by the U.S. Department of the Interior, Bureau of Mines.
Information about airport operations that are in the study area can be
obtained from the Department of Transportation, Federal Aviation Ad-
ministration.
Other ways of obtaining statistical information, which may not have
been previously mentioned, can be found by referring to the reference
sections in the "Guide for Compiling a Comprehensive Emission Inventory"
(APTD 1135).
Metropolitan Boston Intrastate Air Quality Control Region, Figure 2,
was a typical area chosen for a hydrocarbon emission study. For
this region the city replaced the county concept followed in NEDS.
16
-------
S"
Air Quality
Control Region
Boundary
Figure 2. Metropolitan Boston Intrastate Air
Quality Control Region
17
-------
CHAJPTER IV
HYDROCARBON STATIONARY SOURCE IDENTIFICATION
A primary purpose of a hydrocarbon inventory is to identify stationary
point sources. This is best undertaken by means of a stationary source
questionnaire. One byproduct of the questionnaire mailing is the
gathering of information about small companies that do not emit hydro-
carbons in sufficient quantity to qualify as point sources. Although
these sources are small, they are numerous and may represent a sub-
stantial portion of the total hydrocarbons being emitted. The emissions
from these area sources should be included in the NEDS area source file.
Hydrocarbon stationary sources can be broken down into the following
categories: fuel combustion, solid waste, process and evaporation
sources. Fuel combustion includes the burning of coal, oil, gas, and
wood for residential, commercial, institutional, and industrial use.
Solid waste stationary sources are on-site incineration, and open burn-
ing. Point and area source information for both fuel combustion and
solid waste can be obtained from the existing NEDS file. It is felt
that there is no real need to re-examine these point and area sources
because of past emphases placed on them as emitters of criteria pollu-
tants. r The rest of this chapter discusses process and evaporative sta-
tionary sources.
PROCESS AND EVAPORATIVE SOURCES
Frequently hydrocarbon emissions from process and evaporative sources
have not been carefully cataloged in the past. Therefore, it is
18
-------
necessary to re-examine the industries in the study area. A question-
naire designed specifically for particular classes of industries is
effective in gathering the necessary process, emission and emission
control information.
The questionnaire should be designed for three types of establishments:
the manufacturing industries, the dry cleaners and the bulk petroleum
products distributors.
Manufacturing Industries - (Questionnaire Design)
The operations that frequently emit hydrocarbons from the manufacturing
industries are listed below.
1. Degreasing
2. Surface coating
a. Fabric or rubberized
b. Protective or decorative
c. Printing
d. Miscellaneous surface coating
3. Other manufacturing operations
a. Process losses
b. Bulk storage
The questionnaire for these manufacturing industries is shown in
Appendix A, Table A-l. On the first page, general information is re-
quested. Plant name and mailing address, plant address, person to con-
tact, number of manufacturing employees, etc., are required for identifi-
cation, scale up and completion of NEDS. To assist the respondent a
guide (Page 1, Item G) is provided indicating the pages that should be
completed for the operations performed at the plant. If the plant does
not emit hydrocarbons, the respondent signs the form and returns it so
he will not be recontacted.
19
-------
Degreasing - In many industries, the fabricated product must be de-
greased before the application of surface finishes. The major solvents
used in degreasing operations, Stoddard, 1,1,1-trichloroetharie, perch-
loroethylene, methylene chloride and trichloroethylene are listed on the
questionnaire. Space, of. course, is also provided for other solvents.
The respondent is also asked to identify the amount of each solvent pur-.
chased and returned for reprocessing. In order to assist in the deter-
mination of how much solvent is being sold in the area, the name of the
solvent supplier is requested. The major solvent suppliers, if willing
to disclose what may be considered as proprietary information, could
provide information concerning total solvent usage within the area and
help in the identification of major sources.
Surface Coating - The section concerning surface coating, should be
handled carefully because solvents are added to the purchased coating.
A distinction must be made between quantity of coating purchased and
its solvent content, and the quantity of solvent added to the coating
for dilution. The amount of solvent used for cleaning purposes is
also requested. Since several solvents are often used, the type and
percentage of the major solvents in the coating should be indicated
on the questionnaire.
Manufacturing - The last operation in this major category is manufac-
turing. This part is a catch all, which includes such industries as
asphalt roofing, plywood/particle board products and chemical manu-
facturing. Space is provided to describe the process or operation,
to indicate the material being processed, to indicate the throughput
at the source and to indicate the percentage and types of solvents being
used and lost to the atmosphere.
In order to obtain the information required to fill out a NEDS form
for a point source, one last page of information is needed. This part
of the questionnaire concerns itself with control equipment and stack
20
-------
information. Every piece of equipment that has been mentioned in any
previous page of the questionnaire should be given a unique source
"identification number. This number is used to match a piece of control
equipment or a stack to the proper piece of operating equipment. In-
formation that is needed includes the following:
• Process or operation having a stack and/or
control equipment
• Control equipment specification
• Efficiency of the control equipment and its
date of installation
• Stack information: height, diameter, gas temperature
and velocity
The date of installation can be used to double check the reported ef-
ficiency of that equipment. If a piece of equipment is 50 years old
and it is reported at 99 percent efficiency, a reasonable doubt exists
as to the reported values.
Dry Cleaning - (Questionnaire Design)
Dry cleaning is the second category for which a questionnaire should be
developed. It can be a separate questionnaire or incorporated into the
manufacturing industries questionnaire as shown in Table A-l. Dry
cleaners are requested to complete page 2 instead of pages -3- to -8-
of the manufacturing industries questionnaire. General, stack, control
and bulk storage information remains the same. The dry cleaning opera-
tion uses basically two types of solvents; perchloroethylene and some
form of Stoddard solvent. The users of Stoddard solvent will, in al-
most all cases, use a type of process called a transfer machine. It is
called a transfer process because after the clothes are washed they are
transferred to a separate dryer. The physical process of moving the
wet clothes necessitates that there will be a large evaporative loss.
The second type of process used in dry cleaning is called a dry-to-dry
21
-------
machine and is also used by coin operated cleaning establishments. This
process does not involve a transfer of clothes. The drying cycle is
performed in the same machine as the washing cycle. The question of
what type of process is being used should be included in order to check
the usage figures of solvents. For the same amount, of clothes cleaned
and for the same type of solvent being used, the transfer process should
use more solvent than the dry-to-dry process. As in the manufacturing
questionnaire, the names of the suppliers of solvents are requested to
assist in the determination of solvent usage in the area.
Bulk Storage of Petroleum Products (Questionnaire Design)
The last major category is bulk stx>rage of gasoline and other petroleum
and petrochemicals. In order to obtain information about storage tanks
that a company may have on its premises, an abbreviated form of a bulk
storage section is sent to all manufacturing industries (Section VII
of Questionnaire). This shortened form asks for information concerning
solvent type, capacity of the tank, annual throughput, and fill and
control equipment.
The complete form, Table A-2, is sent to all major oil companies,
petroleum and petrochemical distributors, utilities,, and airports
• !
that have large bulk storage tanks. The questionnaire asks for in-
formation such as tank dimensions, paint on tank, average vapor space
height, type of roof, vapor pressures of liquid, type of fill, etc. All
necessary information is asked so that the emissions from the tank can
be calculated based upon methods described in the Compilation of Air
Pollution Factors, AP-42. Emissions from product transfer are cal-
culated by obtaining the type of fill (splash or submerged) and through-
put at the loading racks.
22
-------
DEVELOPMENT OF MAILING LIST
After a questionnaire has been developed for the specific area in
question, a mailing list of potential hydrocarbon emission sources
should be compiled. This list of companies can be. obtained from many
sources. Some examples are:
• State Industrial Directories
• State Department of Corporations and Taxation
• Dun and Bradstreet, Industrial Directory
• Yellow pages of telephone directories
• Thomas Register
• Trade and professional societies
• Existing NEDS and CDS for the state
• State Air Pollution Control Agency
• Local communities to .obtain appraisal of industrial activity
and listing of solvent storage facilities
• Manufacturers, suppliers and users of solvents and control
equipment.
The selection of companies to be contacted is based on their SIC clas-
sification, with consideration given to their size and nature of their
actual operations through preliminary contact with the firm, local
municipalities or suppliers. Information from two previous studies
shows significant use of hydrocarbons in the manufacturing industries
(SIC 20 to 39), bulk storage and distribution of petroleum products
(SIC 5171) and dry cleaning services (SIC 7216).
After the selection has been made of the industrial categories (SIC codes)
to be surveyed by questionnaire, it is then necessary to determine if
all the companies in the SIC will receive the questionnaires or whether
only the most probable users of solvent based upon employee size will
receive the questionnaire. Experience from past studies shows that it
is helpful to make preliminary telephone calls to representative com-
panies in an SIC. The information obtained can then be used to determine
23
-------
if all companies in this class would receive a questionnaire or whether
for example, only companies with 50 employees or more should receive
the questionnaire.
Table 5 presents guidelines that may be useful in the selection of
companies based upon a previous Rhode Island study. The emission em-
ployee ratio is the ratio of tons of hydrocarbon emitted per employee
as found from respondents. This figure can be used to determine the
size of companies that should be inventoried. For example, if it is
decided that all companies emitting more than 5 tons of hydrocarbon
will be considered as point sources and the SIC emission employee
ratio is 0.5, then all companies with 10 or more employees should be
surveyed. It should be emphasized that this table is based on a small
sample of all the U.S. industries and should be used with discretion
until more hydrocarbon surveys are conducted.
The last two categories should be completely surveyed. A list of
petroleum bulk stations and terminals can be obtained from the follow-
ing sources:
1. State Air Pollution Control Agency
2. Department of Corporations and Taxation
3. New England Yellow Pages
4. Petroleum Industry Publications
A list of dry cleaning establishments can be obtained from either the
Yellow Pages or from the Regional Dry Cleaning Trade Association.
The development of the mailing list involves classification of the com-
panies that have been chosen to be surveyed into a logical order. But,
before this is done it is necessary to minimize duplicate mailings.
To do this all the mailing information about a company is keypunched on
computer cards. This information is then sorted alphabetically by city
or town. Visual spot checking will easily eliminate most of the dupli-
cate names from the computer printout. However, even though extreme
24
-------
Table 5. GUIDELINES TO DETERMINE WHAT COMPANIES
WILL BE SURVEYED
SIC
Selection criteria
Emis./emp. ratio
(tons/employee)
20 Food
21 Tobacco
22 Textiles
23 Apparel
24 Lumber & wood
25 Furniture &
fixtures
26 Paper
27 Printing
28 Chemicals
29 Petroleum
30 Rubber,
plastic
31 Leather
32 Stone, clay,
etc.
33 Primary metal
34 Fab. metal
35 Machinery
36 Elect. Machinery
37 Transpt. equip.
38 Instruments
39 Misc. Mfg.
5171 Bulk terminals
7216 Dry cleaning
Alcoholic beverages (2085)
Not surveyed
Coatings (2295), Non-wovens
(2297), Dyeing (2231)
Not surveyed
Finished product (2435),
(2492)
SIC: (2511), (2514), (2521)
(2522), (2542)
Bags, box (2643), 2651),
(2653), Coated papers
(2641)
Newspaper publishing (2711)
Comm. printing (2751),
(2754)
Organic chemical mfg.
(2821), (2823), 2861),
Chemical coating (2851),
Specialty chemicals (2842),
Carbon black (2895)
All companies
Footwear (3021), Plastics
(3041), (3069)
Mfg. shoes (3149), Bags
(3161), Personal goods
(3172), Leather refinishIng
(3111)
Glass products (3221)
Treating (3398), Tubing
(3357)
Screws (3451-2), Metal
stampings (3469), Plating
(3471), Tool mfg. (3423),
(3429)
Industrial machines
Devices (3643), Semicond.
(3674)
Boats (3732), Truck bodies
(3711), 13, 14, 15)
Optical frames (3832)
Precision Instruments (3825)
Jewelry (3914-15), Toys
(3944), Writing instr.
(3951, 53)
All surveyed
All surveyed
0.89
0.07
0.08
1.0
0.5
0.20
0.32
0.11
0.16
0.03
0.10
0.19
0.03
0.07
0.11
0.04
0.07
25
-------
caution is undertaken in developing the list, duplication of companies
will still exist. This is due to the fact that some companies have
more than one name (e.g., parent company, subsidiary, old name). This
type of duplication generally will not be discovered until it is time
to recontact those companies that did not initially respond.
A logical order in which to list and classify companies is first by
SIC, then by city or county and finally alphabetically within the city
or county. This order will increase the efficiency of all future work
involved in data handling and in recording and analyzing response in-
formation.
COMPUTER LABELS AND WORK SHEET
A computer program can be very helpful in the mailing of the question-
naire, and in the production of a work sheet used for logging the re-
turns. The computer program should produce duplicate mailing labels.
The first label is attached to the general information page. This is
done for identification of returned questionnaires and for name and
mailing address correction. The second label is attached to the out-
side of the envelope. The label is shown below in Figure 3.
xxxx xxxx
TRIAL NAHE,
STREET ZZ,
WOONSOCKET R.I. 02895
Figure 3. Label contents
The SIC classification number is printed on the upper left and an
assigned identification number on the upper right. The ID number is
used to keep records of all correspondence with the company. In the
middle of the label appears the company name, address, and zip code.
26
-------
Figure 4 shows the work sheet listing of the companies In identifica-
tion number order. It is used to record the dates questionnaires were
mailed and returned, the telephone numbers, the telephone contact notes,
and comments. The comment space can contain the type of source, pro-
cess, emissions and number of manufacturing employees required for data
analysis. The computer program listing for doing the above tasks is
found in Appendix B.
MAILING OF QUESTIONNAIRE
There are certain procedures that should be followed to assure a good
questionnaire response. Legal requirements should also be considered;
for example, some state regulations may require that prior to the mail-
ing of a questionnaire ample notice be given in local papers. A cover
letter such as that shown in Figure 5 should accompany all question-
naires, this letter should state the purpose of the study, make refer-
ence to any proposed or applicable regulations, and request cooperation.
General procedures and instructions for the previously designed ques-
tionnaire such as those shown in Figure 6 should also be provide'd.
These instructions should request completion and return of the ques-
tionnaire by a specific date and specify the year for which the data is
requested. The instructions also should explain that the questionnaire
was designed for a wide variety of operations which involve solyet^; ,
and organic chemical usage, and that some questions may not applyVt?-:
:
a particular facility. A telephone number should be supplied in ease
a respondent has questions concerning the form.
The mailing of the questionnaire can be performed in two ways. The
first method is by registered mail. Using this method the agency is
assured that the questionnaire is received by the company. The per-
cent response will probably be higher than if than if the letter was
sent by conventional mail. However, there is still no guarantee that
the company will return the form. It is felt that the slight increase
in response does not justify the added expense of sending every company
a registered letter.
27
-------
TEL NO
DATE 0 IN TEL CONT TEL CONT TEL CONT COMMENTS
XXXX
TRIAL NAKEt
STREET It,
WOONSOCKET
XXXX *
R.I. 02895 *
* 4 4
00
XXXX
TRIAL NA'IE,
STREET ZZ,
WOOMSOCKET
XXXX
R.I. 02P95
+
4
4
4
•f 4
4 4
4 4
4
4
4
4
4 4
4 4
4 4
4 4
-4-
4
*
Figure 4. Work sheet contents
-------
„._, , f 600 Washington Street, Boston 02111
Division of
Environmental Health
Room 320
Dear Sirs:
The enclosed questionnaire is being sent Tinder the auspices of the Massa-
chusetts Department of Public Health, Division of Environmental Health, Bureau
of Air Quality Control, in cooperation with the United States Environmental
Protection Agency. The information being sought concerns the usage of organic
(solvent containing) materials, and will be used to determine the effect of
such materials on the air quality levels in the southern portion of the
Commonwealth.
We would appreciate your assistance and cooperation in' answering those
questions that are applicable to your operations. Even If your facility does not
utilize organic materials it is required that you return the questionnaire so that
you will not be bothered by a follow-up phone call.
Many thanks for your cooperation in this effort.
Very truly yours,
'Gilbert T. Joly
Director
Bureau of Air Quality Control
GTJ/TP/mb
Figure 5. Cover letter
29
-------
HYDROCARBON (SOLVENT) EMISSION STUDY
FOR STUDY AREA
The Division of Air Pollution Control, Department of Public Health
requests your cooperation in providing the information asked for on the
attached questionnaire concerning potential hydrocarbon emissions result-
ing from the operation of your facility. Hydrocarbons are gaseous organic
compound s•
BEFORE FILLING OUT THE QUESTIONNAIRE
PLEASE READ THE FOLLOWING INSTRUCTIONS:
/
• Everyone receiving this form should complete Section I
(General Information) and all other sections pertaining
to his firm and return the questionnaire in the stamped,
addressed envelope.
• Please return the questionnaire on or before May 17, 1974.
Your cooperation and expeditious completion of the inventory
forms will be appreciated.
• Indicate any change in name and/or address in Section I.
• The information submitted should pertain to the calendar
year of 1973.
• The questionnaire was designed for a wide variety of
operations which involve extensive solvent usage.
Accordingly, many questions may not apply to your facilities.
Please complete only those sections that are applicable to
your operations.
• If there is more than one plant location, please request
additional copies or photocopy it for each facility.
• If tne space provided is not adequate, feel free to either
copy the form, use a separate sheet or request an addi-
tional copy.
Your cooperation in filling out this form is greatly appreciated.
If you require additional forms or further information, please contact
Mr. X or Mr. Y, Tel. No.: XXX-XXXX
Division of Air Pollution Control
Street Address
City, State, Zip Code
Figure 6. General instructions for completing questionnaire
30
-------
HYDROCARBON (SOLVENT) EMISSION STUDY
FOR STUDY AREA
The Division of Air Pollution Control, Department of Public Health
requests your cooperation in providing the information.asked for on the
attached questionnaire concerning potential hydrocarbon emissions result-
ing from the operation of your facility. Hydrocarbons are gaseous organic
compound s.
BEFORE FILLING OUT THE QUESTIONNAIRE
PLEASE READ THE FOLLOWING INSTRUCTIONS:
• Everyone receiving this form should complete Section I
(General Information) and all other sections pertaining
to his firm and return the questionnaire in the stamped,
addressed envelope.
• Please return the questionnaire on or before May 17, 1974.
Your cooperation and expeditious completion of the inventory
forms will be appreciated.
• Indicate any change in name and/or address in Section I.
• The information submitted should pertain to the calendar
year of 1973.
• The questionnaire was designed for a wide variety of
operations which involve extensive solvent usage.
Accordingly, many questions may not apply to your facilities.
Please complete only those sections that are applicable to
your operations.
• If there is more than one plant location, please request
additional copies or photocopy it for each facili-ty.
• If tne space provided is not adequate, feel free to either
copy the form, use a separate sheet or request an addi-
tional copy.
Your cooperation in filling out this form is greatly appreciated.
If you require additional forms or further information, please contact
Mr. X or Mir. Y, Tel. No.: XXX-XXXX
Division of Air Pollution Control
Street Address
City, State, Zip Code
Figure 6. General instructions for completing questionnaire
30
-------
The second method is by conventional first class mail. This method
previously used in past studies has proved to be effective if, on the
outside envelope, the following expression is clearly printed,
"ATTENTION: PLANT MANAGER." This expression directs the envelope to
the proper supervisory personnel and reduces the chances of the en-
velope being discarded. Included with the questionnaire should be a
self-addressed stamped envelope. The public is more likely to return
the questionnaire if the postage has already been prepaid.
One factor that should be considered before the mailing is whether
or not to stagger the mailing over a time period. If a large number of
questionnaires (1,000 or greater) are to be mailed, a staggering of
the mailing should be considered. This allows for a more even flow of
returns and eases the task of recording information contained in the
returned questionnaires. If the mailing is spread out over extended
periods of time the return date of the questionnaire should also be
staggered accordingly. Companies should be given a reasonable amount
of time to respond. For most companies, approximately 3 to 4 weeks is
sufficient.
Generally, responses will start coming in within d few days after mail-
ing. Many of the early returns will be from companies that do not use
hydrocarbons in their facility. Also, some of the envelopes will be
returned from the Post Office because either the establishment is out
of business or because the company is no longer at that address. New
addresses for companies that have moved can be obtained by either look-
ing up their addresses in the telephone book or by contacting the
Department of Corporations and Taxations.
LOGGING OF RETURNS AND FOLLOW UP
Emission calculation can be performed on the questionnaires as soon as
they are returned. One of five classifications should be designated on
the return:
31
-------
• P Hydrocarbon point source
i • A Hydrocarbon area source
'•':••. • N - No hydrocarbon emission, non-source
• OOB - Out of business
• R Recontact for reclassification
Emission from many sources within a company should be broken down
into individual point sources. The smallest point source that should
be considered within a company is one having at least 1 ton of emission?-.
As the responses come in, changes should be made to correct any mis-
takes made in the company's name, address or SIC classifications. In-
formation required for data compilation is recorded on the work sheets
described in Chapter V.
RECONTACTING
Approximately 3 to 4 weeks after the questionnaires were initially
mailed, recontacting should begin. This can be accomplished by either
of two methods, telephone or letter. The advantages to recontacting
by telephone are direct verbal communication, and lower costs when
the calls are local. Direct communication quickly identifies any
problem areas. Process information can also be obtained over the tele-
phone. In an average 8-hour work day it is possible for one person to
recontact approximately 30 to 40 companies. A good approach is to
select the larger companies in SIC categories emitting significant
amount of hydrocarbons. Certainly all the bulk storage establishments
should be recontacted.
32
-------
CHAPTER V
DATA COMPILATION
There are two approaches for compiling the data into summary tables that
can be used to analyze hydrocarbon source emissions and study the ef-
fects of regulations. One approach is to process the information man-
ually. The other is to use a computer data handling system. The
selection of one approach over another depends on several factors. The
computer approach is advantageous when the data base is large, a variety
of tabular summaries have to be produced and the tasks are iterative.
The computer approach also forces organization. Since the tasks are
done systematically, this leads to accuracy;-and efficiency.
It has been noted that the methodology for inventorying hydrocarbons
requires information on numerous organic compounds from a variety of
processes. Because of this complexity and the eventual need for many
studies of this type to be done for different regions (states, AQCR)
in the future, it is recommended that a computer data handling system
be developed similar to that described in the paragraphs entitled
"Computer Data Handling System," in this chapter. The manual approach,
which has been used as the basis for the development of the computer
data handling system, is described thoroughly in the section entitled
"Manual Approach." It may be followed for small data bases or when
more flexibility or variation from the computer system approach is
desired.
33
-------
MANUAL APPROACH
The data in the questionnaires and the information gathered on the re-
turn log sheet are used to do a survey coverage analysis and to prepare
a point and area source listing work sheets by major emission categories.
The extent of survey coverage and hydrocarbon emission information by
by category is then used to estimate total stationary source hydrocarbon
emissions. The information on point source work sheets is coded onto
NEDS point source forms. Area sources estimates for each major manu-
facturing and evaporative category are calculated and then summed for
entry by county into the evaporation field of the NEDS area source form.
Other hydrocarbon area source emissions for each county are calculated
either by the NEDS area source computer program or manually as specified
by the "Guide for Compiling a Comprehensive Emissions Inventory,"
APTD-1135 and'"Compilation of Air Pollutant Emission Factors," AP-42.11
Point source hydrocarbon emissions from fuel combustion and solid waste
are also obtained from the NEDS point source printout.
Total hydrocarbon emissions can be summarized by source category for
the region or each county as shown in Table 6. The Pi chart in Fig-
ure 7 is an excellent way to illustrate the percent contribution of
each source category. A table similar to Table 7 is used to list the
point sources. Finally, an analysis of each source category can detail
the types of processes, types of hydrocarbon species emitted, and types
of equipment presently in use or available for control.
Survey Coverage Analysis
;
The extent of survey coverage and the resulting emissions is demon-
strated in Table 8. The latest census data on the number of companies
and manufacturing employees by SIC presents a good accurate picture of
what can fully be surveyed. The number of companies surveyed was based
34
-------
Table 1. SUMMARY OF HYDROCARBON EMISSIONS FOR 1973 IN RHODE ISLAND
Source category
Dry cleaning
Degrees ing
Surface coating
Fabric /rubber
Protective/decorative
Printing
Miscellaneous
Trade Paints
Manuf ac tur ing
Bulk petroleum products
Storage
Fuel combustion
Solid waste incineration
Gasoline marketing
Aircraft
Railroads & vessels
Totals
Point source
Number
-------
DECREASING
13.27.
GASOLINE
MARKETING
11.5%
DRY CLEANING 3.6%
MANUFACTURING
2.21
FUEL COMB.
3.57.
TRADE
PAINTS
5.0%
MISC. 12.3%
PRINTING 5.1%
SURFACE COATINGS
INDUSTRIAL
"PAINTS" 11.47.
BULK PETROLEUM
STORAGE 22.1%
AIRCRAFT, RAILROADS,
VESSELS OF INCINERA-
TION 3.9%
FABRIC/RUBBER
6.2%
Figure 1. Distribution of total hydrocarbon emissions
except from automobile travel (35,900 tons/yr)
in Rhode Island
GCA/TECHNOLOGY DIVISION
-------
Table 7. HYDROCARBON SOURCES GREATER THAN 5 TONS/YEAR, 1973
For
Plant
I.D.
Company
Emissions by source category (tons/year)
Bulk
storage
Dry
cleaning
.-
De-
greasing
Surface coatings
Fabric &
rubber
coatings
!
Paints
Inks
t
Other
Chen.
mfg.
-
Fuel
comb.
& inc.
-------
Table 8. SURVEY COVERAGE AND RESULTING EMISSIONS
SIC
22
24
25
26
27
28
29
30
31
32
33
34
33
2-
3?
33
33
5153
7215
& 7216
Category
Textiles
2231, 2295, 2297
Lumber
Furnl lure
Paper
Printing
Chemicals
Petroleum
Rubber
Leather
Stone, clay, etc.
Primary metals
Fab. aetal prods.
Machinery
Elect, machinery
Tranr.p. equip.
Instruments
Misc. Mfg.
Subtotals
Bulk storage
Dry cleaning •
Totals
Region 1967 census or
(1972 nsnuf. directory) data
No. o£
companies
(2S2)
(38)
(43)
(57)
(185)
(90)
(6)
(84)
(18)
(52)
(114)
(405)
(272)
(61)
(23)
(42)
(S55)
(2,733)
13 "
277 b
3,023
No. of co.
> 20 eiTpl.
187
6
7
32
38
25
--
33
12
14
40
89
57
32
15
15
227
629
..
—
829
So. of
employees
3,700
500
700
2,800
4,400
3,000
300
9,750
1,500
2,500
9,700
8,500
10,900
8,300
1,450
4,100
24,200
96.300
...
^~~".'.'
96,300
No. of
companies
surveyed
57
12
21
41
99
53
2
55
6
3
78
253
155
68
15.
13-
136
1,060
20
277
1,357
Companies responding
Point sources
Ho. of
CO.
19
1
0
5
9
7
2
13
1
1
8
33
12
16
5
2
43
179
20
29
228
No. of
empl.
2,766
45
0
852
1,978
1,445
145
5,541
70
600
1,444
3,115
6,183
10.1S7
616
815
10,142
45,554
—
-.
45,554
HC emis.
3,981
7
0
2,237
252
732
16
1,180
27
19
373
1,160
275
1,116
110
56
1,000
12,541
7,945
370
20,856
Area sources
No. of
CO.
4
2
10
12
63
25
0
16
1
0
9
52
28
22
6
4
41
295
0
40
335
No. of
empl.
400
28
51
517
2,142
750
0
403
150
0
365
1,044
1,801
3,885
389
206
3,381
15,518
.-
—
15,518
HC emis.
10
4
7
16
19
37
0
10
1
0
8
82
25
29
12
3
80
340
0
107
447
Non sources
So. of
CO.
22
5
10
21
13
14
ft
V
20
A
2
54
124
93
14
3
7
27
430
0
54
484
So. of
espl .
1,339
95
34
876
1,192
635
0
1,553
12
100
1,872
2,364
1,196
1,490
140
476
.2,155
16,529
--
--
15,529
Cut of
business
or
duplicate
12
3
1
1
11
5
0
5
3
0
7
25
16
16
1
0
18
124
0
16
140
Percent
coverage
(companies)
surveyed
100
92
100
95
97
96
100
98
67
100
100
' 92
96
100
100
100
96
98
100
47
86
Percent
ccversge
(employees)
surveyed
100
34
12
T;t«!
Cf tir.-;ccJ
KC e=-s.
3.991
-.ia
-3
80 i 2,827
I
100
94
45
77
15
24
62
77
84
100
79
37
65
79
.- ^. .
-.
79' .
299
S43
1.
2.C15
354
39
f?
-------
Table 8. SURVEY COVERAGE AND RESULTING EMISSIONS
SIC
22
lit
15
26
27
28
29
30
31
32
33
36
35
36
37
38
39
5153
7215
& 7216
Category
Textiles
2231, 229S, 2297
Lumber
Furniture
Paper
Printing
Chemicals
Petroleum
Rubber
Leather
Stone, clay, etc.
Primary metals
Fabvrcetal prods.
Machinery
Elect, machinery
Transp. equip.
Misc. Hfg.
Subtotals
Bulk storage
Dry cleaning
Totals
Region 1967 ceuus ox
(1972 unuf. directory) data
No. of
companies
(282)
(38)
(43)
(57)
(185)
(90)
<°>
(84)
(18)
(52)
(114)
(406)
(272)
(61)
(28)
(42)
(955)
(2.733)
13°
277 b
3,023
Mo. of co.
> 20 enjil.
187
6
7
32
38
25
--
33
12
14
40
89
57
32
15
15
227
829
--
829
Ho. of
employees
3,700
500
700
2,800
4,400
3,000
300
9,750
1,500
2,500
9,700
8,500
10,900
8,300
1,450
4,100
24,200
96,300
S&jjpffi
•o. of
companies
surveyed
57
12
21
41
99
53
2
55
6
3
78
253
155
68
15
13
136
1,060
20
277
1,357
Coepanles respond log
Point aourcea
So. of
CO.
19
1
0
5
9
7
2
13
1
1
8
33
12
16
5
2
45
179
20
29
228
•o. of
empl.
2,766
45
0
852
1,978
1,445
145
5,541
70
600
1,444
3,115
6,183
10,197
616
815
10,142
45,554
--
45,554
BC emla.
3,981
7
0
2.237
252
732
16
1,180
27
19
373
1,160
275
1,116
110
56
1,000
12,541
7,945
370
20,856
Area sources
Do. of
CO.
4
2
10
12
63
25
0
16
1
0
9
52
28
22
. . .:<,-.
4
41
295
0
40
335
No. of
empl.
400
28
51
517
2,142
750
0
409
150
0
365
1,044
1,801
3,885
389
206
3,381
15,518
-
15,518
HC emls.
10
4
7
16
19
37
0
10
1
0
8
82
25
29
12
3
80
340
0
107
447
Mon sources
No. of
CO.
22
5
10
21
13
14
0
20
1
2
54
124
93
14
3
7
27
430
0
54
484
Bo. of
empl.
1,339
95
34
876
1,192
635
0
1,553
12
100
1,872
2,364
1,196
1,490
140
476
2,155
15,529.
--
15,529
Out of
business
or
duplicate
12
3
1
1
11
5
0
5
3
0
7
25
16
16
1
0
18
124
0
16
140
Percent
coverage
(companlea)
surveyed
100
92
100
95
97
96
100
98
67
100
100
92
96
100
100
100
96
98
100
47
86
Percent
coverage
(employees)
surveyed
100
34
12
80
100
94
48
77
15
24
62
77
84
100
79
37
65
79
--
79
Total
estimated
HC emla.
3,991
138
303
2,827
299
843
16
2,015
354
39
698
2,016
433
1,145
263
217
2,524
18,121
7,945
1,277
27.343
u>
00
Source - Rhode Island Department of Public Health, Division of APC
b
Source - Telephone Yellow Pages
-------
on the selection procedure in Chapter IV, "Development of Mailing
List." The responding information is obtained from the work sheets
completed as questionnaires were returned. Hydrocarbon emissions are
normally calculated by scaling up to 100 percent manufacturing employee
coverage of the selected Industrial categories (two1-, three-, or four-
digit SIC).
In certain cases no scale-up should be performed, because the number
of responding companies or the number of reported employees'exceeds the
latest census information. Additional estimates and corrections are
made by a careful analysis of each SIC and major category (dry cleaning,
degreasing, printing, etc.). Statistical information or that obtained
from major solvent suppliers should also be considered in any reestima-
tion of survey information.
Point and Area Source Work Sheets
The point and area source work sheets are shown in Tables 9 and 10.
They are completed as an intermediate step prior to summarizing the
type and amount of hydrocarbon emissions by malt* category, city/
county, or SIC. They are also useful for developing the NEDS point
source structure and coding information. Control equipment type and
efficiency, process type, and operating rate information may also be
variables for other summaries.
An entry is made for each point source belonging to a major category
such as dry cleaning, degreasing, etc. Processing equipment or method,
industrial type and pollutant type are described to facilitate SCC
selection and decoding. An attempt is made to select the appropriate
SCC by hydrocarbon type or mixture, otherwise a catch-all SCC ending
in 99 is chosen.
39
-------
Table 9. POINT SOURCE WORK SHEET
Category,
1IEDS ID.
MAKE
COT/CO
SIC
MFG.
EMPL.
S1UDY
PT.
ID.
^--v - - • -
PROCESS TYPE
_.
CONTROL
EOT.
EFT.
sec
MARKIAL &
>
TOLLUTAHT
•
EMISSIONS
(TONS/Y1O
» '
-------
Table 10. AREA SOURCE WORK SHEET
C«t«gory_
Study 10
NAME
CITY/CO.
SIC
MFG.
EMPL.
POLLUTANT
EMISSIONS
(TONS/YR)
41
-------
Summary of Hydrocarbon Emissions by Major Category, SIC and Pollutant
A table similar to Table 11 is constructed to analyze the hydrocarbon
emissions by SIC and major categories. Point and area source emissions
are given by SIC for each type of pollutant. The last few columns give
the reported survey totals and the calculated nonreported survey totals.
The nonreported survey total is estimated using percent survey coverage
information and any additional estimates from national or regional
figures. Any additional amount is apportioned to "SIC's by the extent
of the coverage and the reported hydrocarbon emissions within each SIC.
A discussion on the method for estimating nonreported emissions for
each category follows. Calculation procedures are only detailed in the
paragraph entitled "Degreasing . "
Decreasing - Trichloroethylene, perchloroethylette, and 1,1,1 trichloro-
ethane are the solvents most commonly used for vapor aftd co'l-d degreas-
ing. Other solvents include methylene chloride, Stodflrard s'ol'vetvt and
lesser quantities of others (ke tones, alcohols, aTomS'tic compbufad's ,
etc.) which could be classified under "other." Companies elassified
within SIC codes 34 to 39 also account for most tif the decreasing.
Table 12 summarizes the results of the survey aitd the total non-
reported emissions. The distribution of emissions from reporting
sources, Table 13, is also useful for descriptive and planning purposes.
The non-reported emissions based on a 100 percent coverage in each SIC
of the selected companies is calculated as follows:
Non-Reported Emissions = < ^ ' t**po*t*4 Emissions)
fraction
EN-R
This assumes that emissions are proportional to the total number of
employees within the pertinent SIC codes.
42
-------
Table 11. SAMPLE SHEET FOR THE ANALYSES OF TYPE OF HYDROCARBON EMISSIONS
FOR STANDARD INDUSTRIAL CODES (SIC)
SIC
20
21
22
23
24
23
2*
27
21
29
30
31
32
33
34
35
36
37
38
39
51JJ
7216
Total!
nporcvd
tltlMt*
Totals
Typ* of
Point
(net)
Point
Point
Point
Point
Point
Point
' Point
Point
Point
Point
Point
Point
Point
Point
Point
dr..)
Point
Point
Point
Point
Point
(am)
Point
Point
4 Petet
PeUut*a»
I
-
ssr
irinrata
C
"""£*
•
r?*
Total
,
-------
Table 12. TYPE OF HYDROCARBON EMISSIONS VERSUS SIC FOR DECREASING
SIC
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
5153
7216
Totals
reported
Estimated
Totals
Type of
source
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
(area)
Point
area
Pollutants
Stoddard
1
3
(6)
(I)
208
37
(16)
8
(8)
18
1
281
(31)
281
(199)
Trlchloro-
ethane
.1
8
(1)
30
3
5
40
(1)
425
(14)
77
(*)
106
(6)
47
62
(9)
808
(35)
808
(490)
Perchloro-
ethylene
34
23
7
71
(5)
20
44
4
138
(9)
341
(14)
341
(206)
Methylene
chloride
2
74
2
(1)
6
13
48
145
(1)
145
(80)
Trichloro-
ethylene
6
3
(1)
22
117
(5)
407
(36)
51
(4)
104
(10)
42
(3)
476
(40)
1228
(99)
1228
(816)
Other
(2)
(1)
4
(2)
12
(1)
1
(1)
2
7
(3)
7
(8)
46
(18)
46
(43)
Emissions
reported
Er
40
(2)
(1)
6
9
8
(»)
139
(3)
25
5
373
(7)
944
(72)
162
(16)
292
(19)
42
52
(3)
731
(66)
2828
(198)
2828
(198)
7, employee
coverage
C
1.0
.12
.80
1.0
.81
.77
.15
.24
.62
.77
.84
1.0
.79
.37
.65
ED las ions
non-reported
EN-R
(0)
(7)
(2)
(0)
<«)
(42)
(142)
(16)
(229)
(303)
(34)
(0)
(11)
(94)
1
(428)
_
(1292)
Additional
emlss loo
*A
0
<2)
(0)
(0)
(1)
(10)
(33)
(4)
(88)
(71)
(8)
(0)
(3)
32
(100)
_
(342)
Total
emissions
ET
40
(2)
'
(10)
6
(2)
9
8
(14)
139
(55)
25
(175)
5
(20)
373
(324)
944
(446)
162
(58)
292
(19)
42
(14)
52
117
731
(594)
2828
(1832)
-------
Table 13. SIZE DISTRIBUTION OF HYDROCARBON EMISSIONS FOR DECREASING
Ul
Emission range
< 5 tons /year
5-25 tons /year
25-100 tons /year
> 100 tons/year
No. of
companies
135
53
9
6
Average
size
of company
(employees)
< 150
300
830
2400
Total
emissions
143
538
470
1106
2257
Emissions,
tons per
year per
employee
0.02
0.03
0.06
0.08
-------
For purposes of comparison, emissions should be estimated by other
methods. One method is to obtain trichloroethylene and 1,1,1-trichlo-
12
roethane degreasing solvent usage from "Chemical Profiles" or from
13
the "Chemical Economics Handbook," and apportion them by any of these
three indicators: manufacturing employees within 34.to 39 Codes, total
manufacturing employees, or population. The above indicators are given
in decreasing order of accuracy. Another method is to obtain total
usage estimates from local supplier? who are well informed on marketing.
Reasonable judgment should be exercised to determine any increase or
decrease in the estimate depending upon coverage and any additional in-
formation known about the region. By choosing the higher estimate, the
non-reported emissions figure would be conservative. The control stra-
tegies would be more stringent, requiring a slightly higher reduction.
If additional emissions are estimated for the region, they cafla be appor-
tioned to SIC codes by the extent of the coverage and the quantity of
reported emissions.
_ /Ci i i
E. = ——————-— = ————
where E_ = additional emissions for the ith SIC
Ri
En = reported emissions for the ith SIC
Ri
£„ = non reported emissions for the ith SIC
i based on a 100 percent coverage
C « coverage fraction
n = number of SIC categories
The total non-reported and additional estimated emissions are consid
ered as area sources (non-identified point sources and area sources)
and are reapportioned to pollutant categories by reported emissions.
The total regional area source emissions will become the degreasing
46
-------
portion of the NEDS area source county entries "Solvent Purchased." This
regional total is apportioned to counties by (1) non-responding 34 to 39
SIC manufacturing employees, (2) manufacturing employees in SIC 34 to
39, or (3) all manufacturing employees. The indicator is chosen in
decreasing order depending on availability of census data.
Dry Cleaning - The emissions from this industry are due to two types of
solvents; petroleum or Stoddard solvent and perchloroethylene. Per-
chloroethylene is used in much larger quantities than Stoddard, and
about 80 percent of the perchloroethylene produced annually is used by
dry cleaners. The remaining 20 percent is used for chemical inter-
mediates and degreasing. All solvent purchased by dry cleaners is
assumed to be evaporated.
Total estimated emissions from the survey are calculated based on 100
percent establishment coverage for the one SIC 7216. Three other
methods are available for comparing perchloroethylene usage. The first
method is based on dollar receipts spent on dry cleaning from the
14
Census of Business. The amount is calculated using conversion factors
from the International Fabricare Institute. In 1970, $1.50 was spent
per 3.5 pounds of clothes cleaned and an average of 6.9 gallons of
perchloroethylene is used to clean 1,000 pounds of clothes. The second
method is based on estimates from major manufacturers and suppliers of
dry cleaning solvents. They usually can provide information on re-
gional usage. The third method is based on EPA consumption factors,
2 pounds of solvent evaporated per person per year, or 2.7 pounds per
person per year for colder climates.
Solvent usage by each county is determined by using the results of the
point sources from the questionnaire and by proportioning the remaining
estimated solvent used in this region. Two apportioning methods are
available. The first method of proportionment is based upon the num-
ber of dry cleaners who did not respond to the questionnaire and an
47
-------
estimate of the population served by those establishments. The popula-
tion served by the nonrespendents is determined by multiplying the
fraction of dry cleaners that did not respond by the total population
of that county. The second method assumes that each nonrespondent uses
an equal amount of solvent, and apportions the remaining estimated sol-
vent by the number of nontespendents per county.
Surface Coating - This section will discuss the hydrocarbon emissions
resulting from the application of coatings. This category doesn't
include hydrocarbon emission resulting from chemical manufacturing, food
and agricultural products manufacturing, petroleum refining, basic wood
manufacturing, and textiles refinishing. Surface coating deals ex-
clusively with applying a thin layer of coating on the surface. For
purposes of discussion, it has been divided into four categories:
1. Fabric or rubberized coating
2. Protective or decorative coatings such as paints,
lacquers, varnishes, etc.
3. Printing inks
4. Miscellaneous coatings such as adhesives and
coatings for paper, leather, film and glass
Fabric or rubberized coatings - This section discusses and estimates
the hydrocarbon emissions from establishments engaged in manufacturing
coated and impregnated textiles, rubberized fabrics and other miscel-
laneous coated products such as insulating tapes and pipe wrap. The
products are tailored from numerous decorative and/or protective poly-
meric coatings applied to a variety of fibrous, knitted, or nonwoven
16
textile support webs using the following techniques:
• Impregnation or saturation process
• Surface coating process with
1. 'Vet" or solvent-containing coatings
2. "Dry" or hot melt coatings (casting)
3. Lamination of preformed film
48
-------
Although most polymeric compounds can be applied by any one of these
methods, certain factors such as uniformity, esthetics, softness and
protection enter into the selection of the process.
For example, in polyvinyl.fabrics, the base layer is applied either by
laminating the film or by casting the hot melt containing 5 percent
solvent over a previously laid adhesive. An outer decorative layer,
which contains ink, polymer, and about 80 percent solvent, is then
coated "wet" by knife-over-roll. Only the saturation and 'Vet" surface
coating processes use significant quantities of solvent which will then
24
be emitted upon drying or curing the coated material. Some of the
solvents often used are toluene, naphtha, mineral spirits, and MEK. The
classes of coatings often applied are: rubber, cellulose derivatives,
polyvinyl, olefinic, polyester, acrylic, and polyurethanes. Sometimes
epoxy or silicone adhesives are used to bind the coating to the fabric.
The emissions from them are included in this section.
The industries covered by this section are classified by SIC 22 (2231,
2295, 2297) and 30. Total emissions from each SIC category are scaled
to 100 percent coverage according to manufacturing employees within
each SIC. Since numerous types of coatings and application techniques
exist, and any one coating can be used in large quaratedMji-e's in any one
area or establishment, a national-to-regional breakdown is impractical.
That portion of the total emissions not included in point sources is
apportioned as area sources to counties by SIC 22 and 30 manufacturing
employees. It is represented in the solvent purchased category.
Protective and decorative coatings (paints) - This section includes the
application of paints, lacquers, varnishes, shellacs, primers, and
enamels for protective or decorative purposes. This class of coatings
is referred to by the industry as "paints" and are classified into two
categories, industrial or trade paints. Industrial paints are products
that are formulated and sold to other manufacturers (frequently in
49
-------
large containers) for factory application. Trade paints are shelf
products that are sold through retail stores to the general public,
professional painters, and builders. These products are largely archi-
tectural coatings for the outside and inside of new and existing struc-
tures. Industrial paints that are applied in large quantities at a
fixed locations usually become classified as point sources. Non-point
sources using industrial paints are accounted for in the "Solvents
Purchased" entry of the NEDS area source file. Trade-sale paints are
by definition exclusively area sources and are included in the last
section. But, because the emissions are estimated by the same method
and are also represented in NEDS by the field "Solvent Purchased," they
are discussed here.
Faints are applied by brushing, spraying, rolling, flow ooa*ti
-------
paints. Unfortunately, definitive information regarding the above is
not always available from local industrial manufacturers and suppliers.
If we can consider the survey results as representative, then industrial
paints average about 9 Ib/gal and 67 percent solvent. Using the CEH
figure of 400 x 10 gallons of industrial paint, then ;L,200,000 tons of
solvents were emitted in the United States during 1970 from industrial
paint. Since CEH reports that 1,700,000 tons of solvents were used in
1970, then 500,000 tons must have been used in solvent-based trade paints.
Solvent content of the 937,000 tons of solvent-base trade paints would
average 53 percent which is perhaps somewhat high. Water-based trade
paints contain about 3.5 percent volatile hydrocarbons and for 1970 would
emit 50,000 tons of hydrocarbons. National emissions can be estimated
for a different base year using growth rates also given in the above
reference.
Although regional apportioning factors could be based on manufacturing
employees for industrial paints and population for trade paints, the
18
National Paint and Coating Association (NPC) publishes a percentage
breakdown of industrial and trade paint usage for nine U.S. regions. The
last survey accounted for almost one-half of the national sales. The U.S.
Census of Transportation also publishes similar figures about every five
years. Tables 14 and 15 compare the breakdowns for industrial and trade
paints obtained from NPC, 1967 census, and those calculated from regional
population and manufacturing employees. Although the methods show good
agreement only for some regions, the latest NPC survey or census figures
should be applied. They are the only direct measures of regional paint
sales.
To obtain state, county, or study area figures, regional figures can then
be apportioned by manufacturing employees for industrial paints and by
population for trade paints.
Printing - The printing ink industry is another surface coating category
that uses solvents. There are five basic types of printing operations:
51
-------
Table 15. PERCENTAGE BREAKDOWN OF INDUSTRIAL PAINT
SALES FOR U.S. REGIONS
f>
New England (Me., N.H. , Vt. ,
Mass.., R.I., Conn.)
Middle Atlantic (N.Y. , N.J., Pa.)
East North Central (Ohio, Ind.,
111.)
West North Central (Minn., Iowa,
Mo., Kans., N.D. , S.D., Neb.)
South Atlantic (Del., Md. , D.C., Va.,
W.Va., N.C., S.C., Ga., Fla.)
East SouthCentral (Ky. , Tenn. ,
Ala. , Miss.)
West South Central (Ark., La.,
Okla. , Texas)
Mountain (Mont., Idaho, Wyo.,
Colo., N.M. , Ariz., Utah,
Nevada)
Pacific (Wash., Ore., Calif.,
Alaska, Hawaii
1972
NPC
3.0
10.9
29.4
7.1
19.3
8.9
7.0
1.3
13.1
1967 Census
minus
NPC trade
(adjusted
to 1967)
3.7
11.9
31.9
10.9
12.7
11.0
14.0
1.6
2.2
1967
Manuf.
emp.
8.0
22.8
26.8
6.2
12.8
5.7
5.6
1.6
10.5
53
-------
letter-press, flexographic, gravure, lithographic, aad acreeiu Whether or
not hydrocarbon emissions occur depend on the particular type of ink uaed
for particular methods of application. However, certain types of inks are
often used with certain methods. Table 16 indicates the range of percent
solvent content in inks for two drying methods versus the five printing
processes.1*'1*'20
Table 16. PERCENTAGE OF SOLVENT CONTENT FOR TWO DRYING METHODS
VERSUS FIVE PRINTING PROCESSES
Drying
method
Evaporation
Heat set
Letter-
press
—
~10%
Flexographic
Solvent base (40-75%)
Water base (0-30%)
Litho-
graphic
--
-16%
Gravure
40-75%
—
Screen
0-60%
0-60%
The flexographic and gravure process account for approximately one-third
of all inks used. They mainly use solvent-based inks containing 40 to
75 percent solvent, which is then evaporated on drying. Water-base inks
are also coming into use in the flexographic process. Some of these
water-base inks also contain solvent (0 to 30 percent) for faster drying.
The screen process uses oil and lacquer-type inks which contain 0 to 60
percent solvents. However, this class accounts for less than 6 percent
of the national total solvent used for inks. Letterpress and lithographic
inks, which account for about one-third of the total inks used, are oil-
based and emit some solvents when heat-set letterpress or heat-set web
offset is used. Alcohol type solvents are also used in the water fountain
for the lithographic process.
Oil based inks are mostly used in publications of periodicals and books
and in commercial printing, whose SIC is 27 (272 and 275). Flexographic
and gravure printing, which use mainly solvent-based inks, is mostly used
in making miscellaneous converted paper products and paper-board con-
tainers, whose SIC is 26 (264 and 265).
54
-------
Printing hydrocarbon emissions are scaled to a 100% coverage by manufac-
turing employees. They can be compared to national figures apportioned
to the study area. National total solvent used by the printing industry
is found in the "American Inkmaker." Applying a 7 percent annual growth
rate on the 1967 figures the solvent usage breakdown is given in Table 17.
Table 17. NATIONAL SOLVENT USAGE (TONS/YEAR)
Oil inks
F lexograph ic / gravure
Other
1967
25,000
55,000
5,000
1973
37,000
83,000
8,000
The oil-based ink solvent is apportioned by manufacturing employees in
SIC 27, and the flexographic/gravure and other solvent is apportioned by
manufacturing employees in SIC 26. The results are compared with the
survey figures respectively by SIC. Additional regional information
about printing is also considered. Any "additional" emissions are re-
distributed to SIC18 and the area source total is apportioned to counties
by the indicator used in this section.
Miscellaneous Surface Coatings - This category encompasses the infrequent
operations such as the treatment of paper (SIC 26), refinishing of leather
(SIC 31), manufacture of magnetic tapes and fluorescent tubes (SIC 36),
manufacture of photographic films (SIC 38) and adhesives operations in any
other industries not covered above.
Paper is usually "converted" to end products by such treatments as
embossing, impregnating, saturating, and lamination. The two classes of
coatings used are pigment coatings and barrier coatings. Hydrocarbon
emissions occur from the adhesives that bind the pigment, and from the
solvent acting as a vehicle in the barrier coatings.
55
-------
Finishing of leather involves the application of film-forming materials
to the grain to provide abrasion and stain resistance and the enhancement
of color. Previously leather coatings were restricted to casein, shellac,
albumin, wax, and linseed oil. However, today more sophisticated film-
forming polymeric substances are used and applied by rotary brush, flow
coaters and rotary sprayers. Organic solvents are used as dilutents for
22
the polymeric coatings and are then emitted during the drying stages.
The industries that use leather and allied products for the manufacture
of shoes and furnishings are also a source of hydrocarbon emissions due
to solvents in the adhesives.
If the firms covered by these industries are numerous and not all were
surveyed emissions should be scaled by respective SIC manufacturing em-
ployees. If, however, it is known that only a few companies are
doing these operations hydrocarbon emissions should not be scaled. Some
of these rare operations are the manufacture of magnetic tapes, fluorescent
tubes and photographic films. The first two involve the application of in-
organic particles (iron oxide, fluorescent compound) dispersed in a solvent
on to a base (plastic, glass) and the evaporation of the solvent by drying.
Photographic films are coated with polymeric dispersions and solutions
which contain solvents. These solvents act as a vehicle to uniformly
apply the matrix of layer on to the plastic base film, and are later
evaporated and emitted to the atmosphere.
Hydrocarbon Emissions From Manufacturing Not Including Surface Coating
and Degreasing - Hydrocarbon emissions from this category occur when the
raw or intermediate material, itself, contains hydrocarbons of which
some or all may be driven off, or when hydrocarbon compounds are reacted
or mixed with the raw or intermediate material. This category can nicely
be broken down by SIC industrial classes for discussion purposes.
Table 18 gives the type of processes which emit hydrocarbons.
56
-------
Table 18. PROCESSES EMITTING HYDROCARBON FROM MANUFACTURING
SIC
Description
Processes
20
22
25
28
29
30
31
32
33
34-39
Food & agricultural products
Textile mill products
Lumber & wood products
Chemicals & allied products
Petroleum refining and
related industries
Rubber and miscellaneous
plastic products
Leather and leather products
Mineral products
Primary metal industries
Machinery and other
consumer products
Fermentation & distillation of
alcoholic beverages
Dyeing and finishing
Veneer drying
Organic chemical manufacturing
Surface coatings manufacturing
Specialty chemical manufacturing
Petroleum operations except
asphalt mixing
Plastic and rubber products
operations
Leather refinishing
Asphalt roofing
Asphalt mixing
Coal and coke processing
Fabrication of plastic or resin
products: fiberglass boats,
toys, etc.
-------
For manufacturing categories, total hydrocarbon emissions should be
scaled only when numerous companies are doing the operations described
in the above table. National consumption or production of certain pro-
ducts are of little value for regional breakdown, because the companies
are likely to be relatively few and unevenly distributed in the United
States compared to those doing surface coating, degreasing or dry clean-
ing. Except for petroleum refining and certain chemical processing
operations, the hydrocarbon emissions from these manufacturing opera-
tions are relatively small as compared with surface coating.
Bulk Storage of Petroleum and Petrochemical Products - Hydrocarbon emis-
sions from three operations, the filling, storing and emptying of various
types of tanks, by the manufacturing industry, oil companies, distributors,
utilities and airports are considered here. Most of these three operations
are point sources and are coded into NEDS. For example a fixed roof tank
might regularly be filled by a marine vessel and emptied by truck.
Storage emissions would be both from breathing and working losses.
Evaporative area sources are relatively few and are neglected by the
NEDS area source form. Gasoline, the only petroleum product emitting
significant quantities of hydrocarbons at the retail level, is discussed
in a later section on "Exclusively Area Sources Emitting Hydrocarbons."
The data summary tables are different for this category. Table 19 is a
good way to represent the data. For each type of operation (or operating
variable) the emissions from each type of petroleum product are entered.
Emissions are calculated using EPA emission factors.
Emphasis has been placed on obtaining information from all bulk storage
sites because they are relatively few in number. This is also important
because the emissions can only be recorded as point sources. A check on
the questionnaire information can be made by obtaining petroleum transfer
23
at ports published by 'Vaterborne Statistics." The Army Corps of
58
-------
Table 19. HYDROCARBON EVAPORATIVE LOSSES AT BULK STORAGE SITES
Operation
Marine vessel-
Unload ing
Loading
Tank cars/trucks-
Splash loading
Submerged loading
Unloading
Storage/ fixed roof
Breathing loss
Working loss
Storage/floating roof
Standing loss
Storage/variable vapor
space
Working loss
Total emission by
product
Gasoline
858
115
915
1409
314
1045
807
369
0
5832
Distillate oil
81
8
75
88
—
1140
297
11
0
1700
Jet fuel
9
2
34
1
—
99
52
0
0
197
Kerosene
3
1
1
9
—
71
25
0
0
110
Diesel
2
1
—
10
—
12
4
2
0
31
Total
emissions by
operation
953
127
1025
1517
314
2367
1185
382
.0
7870
Ln
VO
-------
Engineers records (foreign, coast-wise, internal and local) receipts and
shipments of major petroleum products. A flow diagram and material
balances for each product can clearly indicate the storage and transport
patterns of the region. The sum of the transports at each entry or source
place can now be compared. A significant difference would indicate review
of the possible storage sites in number and in the accuracy of the in-
formation provided.
Exclusively Area Sources Emitting Hydrocarbons
These sources are almost always considered area sources because either
they are relatively small emitters and numerous, or they are mobile.
This category consists of evaporation from application of trade paints,
evaporation from gasoline marketing, combustion of fuels in transporta-
tion, non-highway use of motor fuels, and combustion of miscellaneous
sources. Area sources from stationary fuel combustion and solid waste
disposal have already been mentioned in the beginning of this chapter.
The methods for gathering this information is well documented in the
'Guide for Compiling a Comprehensive Emissions Inventory," APTD 1135.
We will therefore only comment on the first three listed above.
Evaporation From the Application of Trade Paints - The methodology for
estimating and apportioning the emissions to counties has already been
discussed in the section on Protective and Decorative Coatings—Paints.
The emissions from trade paints along with all other process and eva-
porative hydrocarbon area source emissions are entered in the "solvent
purchased" entry in NEDS for each county.
Evaporation From Gasoline Marketing - Gasoline is the only one of the
petroleum products, which is emitted in significant ammounts through retail
marketing. A diagram of gasoline flow can be completed using the informa-
tion given in an earlier section on bulk storage and other references
found in the methods for estimating county on-highway motor vehicle and
off-highway gasoline in "A Guide for Compiling a Comprehensive Emissions
60
-------
Inventory," APTD-1135. Figure 8 is the flow pattern found in Rhode
Island. The NEDS entry on county gasoline marketed is the sum of on-
highway and off-highway gasoline use. Calculation methods are also
documented in APTD-1135. Evaporative emissions are calculated using an
overall emission factor which is the summation of emission factors from
five gas station operations. Emission factors are adjusted for an
average gasoline vapor pressure. The operations and emission factors
at 4.6 psia vapor pressure are given in Table 20.
Table 20. EMISSIONS: LOSSES PER 1000 GALLONS
TRANSFERRED
Operation
Tank truck unloading
Storage tank fill (splash)
Storage tank unloading
Vehicle fill
Gasoline spillage
Total
Pounds
1.6
9.2
0.8
8.8
0.6
21.0
Transportation - This is the largest hydrocarbon source and the accuracy
of the methodology for estimating the emissions is important. Methods
for estimating the emissions are also given in APTD-1135 for all trans-
portation classes, motor vehicles, aircraft, railroads and vessels.
Since motor vehicle emissions are by far the largest, the methodology
24
given in "An Interim Report on Motor Vehicle Emission Estimation"
should be followed. Although this requires more information gathering
and processing, it estimates the emissions more accurately.
Miscellaneous Hydrocarbon Area Sources - Hydrocarbon emissions from these
sources are relatively small to the total for most cases. APTD-1135
describes the methodology for estimating the following:
61
-------
o>
to
5832 TC
773
FOREIGN AND
NS/YEAR 4118 T
t i
HC '
392
BULK STORAGE
SITES
(WHOLESALE)
POINT SOURCES
COAST-WISE i
VESSEL T 85
RECEIPTS
ONS/YEAR ,
HC
SERVICE
STATIONS
(RETAIL)
AREA SOURCES
392
HC
ON -HIGHWAY AND
OFF -HIGHWAY
CONSUMPTION
AREA SOURCES
INTERNAL, LOCAL VESSELS
AND TRUCK RECEIPTS
466
OUT OF REGION
TRANSPORT
Figure 4. Gasoline flow (10 , millions of gallons) and resulting
hydrocarbon (HC) emissions for the State of Rhode
Island.
-------
• Non-highway use of motor fuels
• Acres and quantity of wood burned by forest fires
• Acres and quantity of material burned by slash and
agriculture fires
• Structural fires
• Number and size of active coal refuse piles.
EPA emission factors are applied for calculating hydrocarbon emissions.
COMPUTER DATA HANDLING SYSTEM
The development of a computer data handling system involves coding the
information onto standard forms and programming the storage/retrieval,
processing and report generating functions. The present National Emis-
sion Data System (NEDS) has been extensively developed to include and
accommodate these functions. It remains to modify and add any defi-
ciencies in coding hydrocarbon point and area source information, and
to write the program(s) necessary to generate the tabular summaries
found in the "Manual Approach." In this report, only the methodology
for generating the summaries is described. The computer programs are
not provided.
Survey Coverage and Emission Summary Table
The establishment identification card described earlier for labels, and
a response card can be coded for entry into the computer.
The identification card contains the following information:
• plant identification number
• county, AQCR, city codes
• SIC
• name and address
63
-------
The additional information required to complete the summary table would
be on the response card:
• type of source (P, A, N, 0, tf)
P = Point source; A = Area source; N = Not a source;
0 = Out of business; tt = blank, non-respondent
• number of manufacturing employees
• emissions (tons/year) by major category
• Q, T; Questionnaire, Telephone information.
The response card can be completed as the questionnaires or telephone
information is received. In addition, the identification information
should be verified.
Then a single computer program could read, process and summarize the
data in various formats:
• SIC versus coverage by number of establishments, manu-
facturing employees, source type, and emissions
• Emissions by SIC for each major category
• Listing of non-respondents for enforcement
• Listing of telephone respondents for further verification
• Listing of point sources by city, county, AQCR, SIC, size, etc.
The above summaries can then be used to estimate total hydrocarbon emis-
sions and to compare them with estimated study area figures broken down
from national figures by some indicator. Any additional emission esti-
mates would be coded into the area source form. All other area sources
emitting hydrocarbons would also be reviewed.
Coding of NEDS Point Source Form
Point source information is coded on NEDS and made available to the many
federal and private agencies either in computer readable form or in
64
-------
printout listings and summaries. Coding instructions are found in the
"Guide for Compiling a Comprehensive Emission Inventory" - APTD 1135 5
and will not be repeated here.
The information concerning hydrocarbon species is not adequately
being handled by NEDS to generate the summaries described in the "Manual
Approach," or needed for the proper evaluation of the regulations. Four
major categories, dry cleaning (SCC: 401001), degreasing (SCC: 401002),
petroleum product storage (SCC: 403) and petroleum marketing-transportation
(SCC: 406) have an adequate number of SCO's to calculate the type and
quantity of hydrocarbon emitted. Other categories, such as the sub-
categories in surface coating (SCC: 402) (fabric coating, protective or
decorative coatings - paints, printing (SCC: 405), miscellaneous coatings
for glass, paper, leather, etc.), food/agricultural industries, chemical
manufacturing industries (SCC: 301), wood products (SCC: 307), petroleum
industry (SCC: 306), leather products (SCC: 320) and textile manufactur-
ing (SCC: 330) do not have adequate SCC's to describe the process and
type of material used.
Generation of Emission Tabular Summaries
Once the point source information is loaded into the NEDS data files,
the hydrocarbon emission tabular summaries described in the "Manual Ap-
roach" of Section V can be produced with a computer program. This could
be performed by NEDB or outside by the agency performing the study. As
indicated earlier, the SCC codes along with other information in the
files would be retrieved for classification. It is expected that the
classification will assist in the evaluation of control strategies to
meet the oxidant air quality standard.
65
-------
CHAPTER VI
APPLICATION OF THE HYDROCARBON METHODOLOGY
TO THE REGIONAL AIR POLLUTION STUDY
The methodology for inventorying hydrocarbons is a detailed plan to
acquire a very extensive data bank. The data will be in much greater
detail as to the character of emissions than has been achieved before
25
on a regional scale. In the St. Louis Regional Air Pollution Study
(RAPS), the data is needed for the development and validation of mathe-
matical simulation models of air pollution processes. The models are
formulations of all of the atmospheric processes such as convective
transport, diffusion, physical and chemical transformation, and re-
moval of pollutants. Two models that deal with hydrocarbons are pre-
26
sented in "Urban Air Shed Photochemical Simulation Model Study" and
in "User's Guide to Diffusion/Kinetics (DIFKIN) Code."27 The number
of pollutants considered by the models are relatively few, but can be
increased as more information is known. For example, more rate con-
stants and stoichiometric coefficients are being estimated for hydro-
carbon reactions. Time is an important variable allowing consideration
for specific short time intervals.
Several emission inventories have been conducted in the St. Louis area.
The NEDS inventory is the last and most recent inventory. The data
was originally transferred from the other inventories in the summer of
1973, and will be updated quarterly by the state agencies. It is evi-
dent that NEDS is increasing the degree of sophistication and useful-
ness for planning purposes. A recent analysis of the hydrocarbon
28
emissions inventory for the St. Louis AQCR is shown in Figure 9.
66
-------
100
I
o
cc
Ul
o.
> 1 TON/YEAR
TOTAL AQCR
ALL POINT SOURCES
P.S. > 100 TONS/YR
P.S. > 1000 TONS/YR
P.S. > 10.000 TONS/YR
ALL AREA SOURCES
NUMBER
SOURCES
470
99
23
1
TONS/YEAR
294,908
78.295
71,051
45.960
14.100
216,613
PERCENT OF
POINT SOURCES
100.0
9O.7
58.7
18.0
PERCENT
OF TOTAL
100.0
26.5
24.1
15.6
4.8
73.4
20
10
> 10,000 TONS/YEAR
I
100 200 300 400 500
NUMBER OF POINT SOURCES
600
700
Figure 9. Hydrocarbon emissions for the Saint Louis
Air Quality Control Region.
28
67
-------
Point sources account for 78,295 tons/year of the total 294,908 tons/
year for the AQCR. In addition, only approximately 100 point sources
account for 90 percent of the total point source emissions. A total
of 470 point sources were coded. Previous studies of hydrocarbon
emissions in other areas do not indicate an extensive cataloging of
the amount and type of hydrocarbon species. Also, as the effort is
increased to obtain more accurate data and more point sources, there
is an increase in the percent of the emissions that can be attributed
to point sources and monitored for control. Referring to Figure 9,
the curve would shift down and to the right, and the points on the
curve (e.g., > 100 tons/year) would also shift down.
In summary, the application of this methodology to the St. Louis RAPS
program would not only catalog the hydrocarbon emissions by amount and
type, but would increase the accuracy of the inventory, describe the
emissions by source category and give the emission rates over specific
short time periods. To achieve these goals, there are three areas of
the methodology discussed in previous Chapters that need more develop-
ment for the RAPS program than required by most regions. These are:
• Inclusion of smaller point sources
• Delineation of hydrocarbon species
for point and area sources
• Determination of hourly emission
estimates.
The methodology allows for the inclusion of point sources to any degree
of refinement necessary by the RAPS program. The smallest point source
that can be coded in NEDS is 1 ton/year. There are several criteria
for selecting the emission size that distinguish between point and area
sources. Since it takes more time to maintain information on point
sources than area sources, the availability of funds is a factor. An-
other factor would be the percent of emissions required to be monitored
by the program. Once again, the economics and the degree of accuracy
68
-------
are Important. It ordinarily follows that the higher the percent of
emissions monitored the more accurate the inventory becomes. The preci-
sion of the inventory is important for the validation of the simulation
models. Another factor to be considered for classifying a point source
is whether it can be controlled by the existing or proposed regulations.
Previous chapters have already mentioned that the development of new
Standard Classification Codes (SCC) for NEDS will be the partial solu-
tion for defining the process and the type of hydrocarbon species being
emitted. The SCC file has been designed to include new codes as they
are being developed. As they are developed, the general codes which
end in 99 can be shifted to these newly defined ones. The photo-
chemical reactivity of these hydrocarbon species can then be considered
in the simulation models and the models can then estimate the formation
of photochemical oxidants based on the quantity of reactants, reaction
rates and amount of energy from sunlight. It should be noted that the
methodology discussed in Chapter V already provides for point and area
source classification by pollutant, an example of which has been pre-
sented in Table 11. Similar tables can be provided for all major
categories of hydrocarbon sources and utilized in RAPS programs.
The third area is the development of techniques by which the inventory
can be used to estimate emissions over specific short time periods.
These techniques should be used when processing or summarizing the
information in the data bank. Estimating emissions down to the hourly
level, or defining the daily and weekly emission cycle will support
the short time simulation modeling efforts. This is very important
because the formation of photochemical oxidants occurs during sunlight
hours, and is dependent upon the concentration of hydrocarbons during
this time. The basis for the NEDS inventory is one year, however, the
point source quarterly percent thruput and the number of normal
operating hours are recorded for further breakdown of emissions. It
is apparent that some of the hydrocarbon emissions are dependent on
69
-------
the working hours at the establishment. For example, a typical com-
mercial dry cleaner starts work around 7:00 to 8:00 a.m. and operates
for 8 to 10 hours. On the surface, the program which estimates hourly
emission rates should have hydrocarbons emitted only for the operating
hours beginning on the seventh to eighth hour of the day. On the other
hand, hydrocarbon emissions from a fixed roof tank occur throughout the
day and are dependent on several factors such as temperature, absorption
of sunlight, and displacement of the liquid level through transfer
operations.
In any event, it is apparent that the NEDS form and the methodology
discussed previously here (see page 1 of the questionnaire in Table A-l)
do not directly address the question of the daily period of operation
and/or emissions. It can be inferred in most instances that sources
specifying an 8-hour operation do so over a normal 8:00 a.m. to 5:00 p.m.
period. However, to cite the previous examples, a dry cleaning opera-
tion may report an 8 to 10 hour operation yet perform much of its clean-
ing after the closing of its doors to commercial operation. Similarly,
in the case of gasoline storage and distribution operations, much of
the emissions due to transfer activity may take place throughout the
evening.
Most other categories, however, will emit hydrocarbons which will be
proportional to the number of operating hours as reported. Most larger
emitters will operate and emit on a continuous basis. This will be true
for most surface coating operations, power generating plants, large-
scale degreasing, printing plants, etc. However, other manufacturing
operations may be categorized as cyclic or batch type. These could in-
clude many small manufacturing operations and certain process operations,
such as batch type coating formulation, plastic and adhesive manufacture,
Kraft pulp digestion, blowdown operations at refineries, etc. Their
cycles may occur at regular intervals or possibly exhibit hourly, daily,
or long term variations due to product demands.
70
-------
Obviously, when cyclic operations are random or irregular in occur-
rence, the situation is complex. The importance of such variations,
however, may not be serious in that they may be small compared to the
overall contributions of temporally definable sources. Nevertheless,
the question should be addressed. From the standpoint of the method-
ology, some modification of the questionnaire should be considered.
This would involve the supplementation of existing NEDS information
concerning season and normal operating schedules with hourly informa-
tion. The respondent could be requested to estimate the fraction of
sources emitted hourly or at specified intervals of the day: 12 to
6 a.m.; 6 a.m. to 12 p.m.; etc. This estimation could follow a nota-
tion as to whether emissions are continuous, cyclic, or irregular,
as below:
Emission Cycle;
Continuous
Batch
Irregular
Approximate Percentage of Emissions
Occurring During the Day
12 a.m. -6 a.m.
6 a.m. -12 p.m.
12 p.m. -6 p.m.
6 p.m. -12 a.m.
This information should be included preferably throughout the ques-
tionnaire to satisfactorily cover plants engaged in multiple opera-
tions. Although this methodology is cumbersome and may prove to be
an over-refinement of the methodology depicted in Chapter V, it
appears to be the only way of determining hourly emission variations.
The problem of diurnal variations of emissions from storage opera-
tions can be treated mathematically based on temperature vapor
71
-------
pressure considerations in much the same manner as seasonal variations.
To determine distribution losses due to transfer operations, however,
again some assessment of hourly activity must be made. This informa-
tion could be requested on the questionnaire supplied to the principal
gasoline distributors.
72
-------
REFERENCES
1. National Air Quality Standards. Federal Register 36. No. 84.
April 30, 1971.
2. Air Quality Criteria for Hydrocarbons. AP-64. U.S.Dept. of Health,
Education and Welfare. 1970.
3. Hydrocarbon Pollutant System Study. Vol. 1. MSA Research Corp.
October 1972.
4. Requirements for the Preparation, Adoption and Submittal of Im-
plementation Plans. Federal Register. August 1971.
5. Guide for Compiling a Comprehensive Emissions Inventory. APTD-1135.
U.S. EPA. Revised March 1973.
6. Los Angeles Air Pollution Control District. Rule 66.
7. Air Quality and Emissions Trends Annual Report, Volume 1. EPA-450/
1-73-001-a U.S. EPA. August 1973.
8. Feldstein, Milton. Regulations for the Control of Hydrocarbon
Emissions From Stationary Sources. JAPC. Vol. 24 Npv 5. May 1974.
'.. ' '
9. Recommendations for Modification of Rule 66. Air 'Quality Task
Force. NPC Association, Washington, D.C.
10. Hydrocarbon Emission Sources in the Metropolitan Boston Intrastate
AQCR. Vol. 1. GCA/Tech Div. Prepared for EPA Contract No.
68-02-1006.
11. Compilation of Air Pollutant Emission Factors. Second Edition,
AP-42. U.S. EPA. April 1973.
12. Chemical Profiles. Trichloroethylene, November 1972 and 1,1,1-
Trichloroethane. April 1971.
13. Chemical Economics Handbook. SRI.
14. Census of Business 1967. Selected Services Area Statistics.
73
-------
15. International Fabricare Institute, Silver Springs, Maryland.
Technical Bulletin T-468, 1971.
16. Encyclopedia of Polymer Science and Technology, John Wiley & Sons.
Vol. 6. New York. 1965.
17. Conversation with Mr.' Charles Roe of Plymouth Rubber, Canton, Mass.
December 1973.
18. Sales Survey, 1972. NFC Association, Bethesda, Maryland. March
1973.
19. Conversation with Mr. Von Forcken of Sinclair & Valentine Co.,
Boston, Mass. November 1973.
20. Salomon, Gerald, et al. A Compilation of Solvents for Flexo-
graphic and Gravure Inks. American Inkmaker. February 1969.
pp. 28-38.
21. Revson, James E. Chemical Consumption Patterns in the Printing
Ink Industry. American Inkmaker. May 1968. pp. 58-61.
22. Leather Facts. New England Tanners Club. Peabody, Mass. 1972.
23. Waterborne Commerce of the U.S. U.S. Dept. of Army, Corps of
Engineers. 1971.
24. Kircher, D.S. and D.P. Armstrong. An Interim Report on Motor
Vehicle Emission Estimation. EPA. October 1973.
25. Allen, Philip W. Regional Air Pollution Study - An Overview. EPA.
Presentation at the 66th Annual Meeting of the APCA, Chicago,
Illinois. June 1973.
26. Urban Air Shed Photochemical Simulation Model Study. Systems
Applications Inc. Prepared for EPA, Contract No. 68-02-0339.
July 1973.
27. User's Guide to Diffusion/Kinetics (DIFKIN) Code. General Research
Corp. Prepared for EPA, Contract No. 68-02-0336. December 1973.
28. Regional Air Pollution Study (RAPS). Preliminary Emission Inven-
tory. SRI. Prepared for EPA, Contract No. 68-02-1026. January
1974.
74
-------
APPENDIX A
QUESTIONNAIRE
75
GCA/TECHNOIJDGY DIVISION
-------
Table A-l. QUESTIONNAIRE TO MANUFACTURING INDUSTRIES AND DRY CLEANERS
official use
Rec. by Date:
SIC
X,Y ;
1. GENERAL INFORMATION
A. ' Company Naoe_
Plant Address
_Zlp Code_
Nearest Street Intersection,
Mailing Address
City.
_Zlp Code.
B. Person to contact about £orm_
Telephone
Title
C. Approximate number of employees.
D. Nature of Business
E. Normal Operating schedule
Hrs./day
_days/wk..
_vks/yr.
F. Approximate Percent Seasonal Operation:
Dec. -Feb.
Mar -May
Jun-Aug
Sept. -Nov.
G. Are volatile organic or solvent-containing materials such as cleaning fluids,
coatings, adheaives, Inks, etc. used in your operation? _____ Yes No
If NO. sign form and return
If YES, sign form and complete only the sections pertaining to your
operation:
II. Dry Cleaning
III. Degrees ing
IV. Surface Coating Applications
A. Fabric and Rubberized .... •
B. Protective or Decorative other than IV-A-
C. Printing
D. Miscellaneous Surface Coatings
V.
(Adhesives, Paper, Leather, films, Glass etc)
Manufacturing Industries
Signature
Date
Page
2, 9 & 10
3. 9 & 10
9 & 10
'. i 10
9 & 10
9 i 10
9 & 10
76
-------
II. DRY CLEANING
A. Amount of clothes cleaned per year tons.
B. Type of dry cleaning unit Q hot or dry-to-dry
O cold or transfer
C. Type and amount of solvent cleaner purchased in 1973.
Perchloroethylene Gal. /Yr.
Stoddard solvent Gal./Yr.
Other (specify) ; Gal./Yr.
Other (specify) Gal./Yr.
D. Supplier of solvent - Name and address
Perchlorethylene _..
Stoddard Solvent
Other (specify)
Other (specify)
E. Please complete Section VI. page 9.
If you have any questions about this section please contact:
Mr. Roger Schilling
Field Representative for
International Fabricare Institute
5 Shawsheen Ave.
Bedford, Mass.
(617) 275-7583
77
-------
III. DtCKASttC OPERATIONS
A. Type of degreaslngi 0 cold solvent cleaning
Dvapor degree*Ing
B. Typ« and amount of solvent purchased for dagraatlng operation*.
1) Stoddard C«l./yr.
2) 1,1,1-Trichloroethana
(Chlorochene VC) ___Gal./yr.
3) Perchloroethylene Gel./yr.
4) HethyUne chloride G*l./yr.
5) Trlchloroethylene __C«l./yr.
6) Othep (apcclfy) _Gal./yr.
7) Other (specify) Gal./yr.
C. Supplier* of Solvents
D. Waste solvent disposal aethod
E. Asjount of each solvent returned for reprocessing to vendor or collector
1) Stoddard Cal./vr.
2) Trlchloroethane Cal./yr.
3) Perchloroethylene Cal./vr.
4) Methylene chloride Gal./yr.
5) Trlchloroethylene Gal./vr.
6) Other (specify) G«l./yr.
7) Other (specify) Gal./yr.
F. PJ.ease complete Section VI. page 9.
78
-------
IV-A. FABRIC OR RUBBERIZED COATING APPLICATION
(1) Materlal(s) being coated
(2) Type of coating process:
Source
No.*
State Coating Process:
Impregnation,
•Vet" Coating,
Hot Melt Coating,
Lamination
Type of
Coating"
Amount
of Coating
(Gal/Yr)
Type and
7. of Vehicle
Solvent
. ..
Type and
Amount of
Solvent AddoJ
to Coating
(Gal/Yr)
1
\
I
j
(3) Type of cleaning solvent
_, Amount
_, Amount
(4) Is any solvent returned to supplier or collector?
_*
NO
Yes
Type'
Amount
(Cal/Yr)
(Cal/Yr)
(Cal/Yr)
(5) Please complete Section VI. p. 9; use same Source No.
*A source Is an Individual or similar pieces of equipment such as colters, dryers,
etc. It should correspond to the Source No. on page 9. If applicable, It should
also correspond to previously reported sources in "Air Pollution Emissions Report"
(Form 158-R75)
**Poiyvinyl chloride, polyurethanes, etc.
+Tpluene, naphtha, mineral spirits, MEK, xylene, chlorinated hydrocarbon, other
(specify).
79
-------
IV-B. PROTECTIVE OR DECORATIVE COATINGS OTHER THAN FABRIC COATING
1. Indicate material being coated __________________________________
2. Type and amount of coating used:
Source*
Number
State Application Method:
Spraying, Dipping, Roller,
Flow, etc.
Type of
Paint**
Amount
Cala./yr.
X
solids
,
Type and 7. of major
solvents
!
M ,- 1
3. Type* and amount of thinner used for dilution and cleaning not Included
above - - 0.1./yr.
Amount _
Amount
Cal./yr.
4. Please complete Section VI. pane 9.
A source Is an Individual or similar pieces of equipment such as spray booths, tanks,
dryers, etc. It should correspond to the Source Mo. on page 9. If applicable,
It should also correspond to previously reported sources In "Air Pollution Emis-
sions report" (Form 158-R75)
(!) paint, (3) varnish/shellac, (4) lacquer, (5) enamel, (6) primer
If known, - acetone, Isopropyl alcohol, MEK, butyl acetate, cellusolve, coluen,-, >-u .
80
-------
IV-C. PRINTING
(1) Material being coated —_
(2) Type of printing process:
Source
No.*
State Printing Process:
latterpress, Flexo-
graphic, Uthogriphlc,
Gravure . Screen
TXP* 9f
Ink
Amount
(Ib/yr)
Type* and. % of major solvents
in Ink
i
(3) Type and amount of solvent used for dilution and cleaning not
Included above: -mount Cal./yr.
_____________ Amount Gal. /vr.
(4) Pleaaa complete Section VI p.9 ; ; uae same Source Mo.
A source is an Individual or similar printing machines, dryers, etc. It should cor-
respond to the Source No. on page 9. If applicable, it should also correspond to
previously reported sources In "Air Pollution Emissions Report" (Fora 158-R75).
i
**Solvent based, oil based, lacquer-type. etc. .
*Isopropyl alcohol, Ethanol, Propanol, Naphtha/Mineral Spirits, Toluene,
MEK, other (specify) '
81
-------
IV-D. MISCELLANEOUS SURFACE COATING APPLICATION
(Adhealves, Paper, Leather, Films, Glass, etc)
(1) Material(s) being coated_
(2) Type of coating process:
Source
NO.*
State Coating Process;
Spray, Flow, Dip,
Roller, Brush, etc.
Type of
Coating
Amount of
Coating
(Gal/Yr)
Type* and 7.
of Major
Solvents in
Coating
!
i
j
i
i
(3) Type and additional amount of solvent used for dilution and
cleaning not included above .Amount Gal /Yr.
.Amount Gal.'Yr.
(4) Please complete Section VI. page 9 ; use the same Source No,
A source number is an individual or similar pieces of equipment using surface
coatings. It should correspond to the Source No. on page 9. If applicable
it should also correspond to previously reported sources in "Air Pollution i.T.i.-
sions Report" (Form 158-R75).
Adhesive type, pigment coating, barrier coating, polymeric coating, inorg.n:-,.c
.coating, etc. (specify).
Branched alcohol, linear alcohol, ethyl acetate, toluene, xylene, others,
MEK, naphtha, other (specify).
82
-------
V. MANUFACTURING INDUSTRIES
1) Brief Description of Process
00
OJ
Source
No.
Process or
operation using M
organic materials
Type of material
processed +
Annual
thruput at
source
Type •*•*• and X of
solvent In material
Quantity of
volatile
solvent lost
to atmosphere
during process
Ibs/yr.
Method
used to
determine
emissions
(guess or
material
balance)
•
2) Please complete Section VI, page 9 ; use same Source No.
A source is an individual or similar pieces of equipment processing organic materials. It should correspond to Che
Source No. on page 9. If applicable, It should also correspond to previously reported sources in "Air Pollution
Emissions Report" (Fora 158-R75).
Dryer, re-actor, nixing tank, etc.
Paint, varnish, shellac, lacquer, enamel, primer, adhesive, ink, other (specify).
Acetone, MEK, lutyl acetate, cello&olvc, ethanol, naphtha, toluene, mintral spirits, other (s
-------
oo
VI. CONTROL AND STACK INFORMATION
Instructions:
(1) A number should be assigned to each piece of equipment that emits hydrocarbons or to a number
of similar units that are vented to a common stack. The Source No. below should correspond
to the sections previously filled out. If similar equipment have different control equipment
please split the source number to «, b or c.
(2) Identify the process or operation from which hydrocarbons are emitted. For example, dry
cleaner, degreaslng tank, spray booth, reactor, etc. If more than one unit Is emitting to a
common stack, specify the number of units.
(3) Identify the hydrocarbon control method used such as after-burners, scrubbers, carbon adsorption,
condensers, etc.
(4) Indicate approximate efficiency if known.
(5) Indicate installation date of control equipment.
(6) If hydrocarbons are emitted from a stack, provide height, diameter, temperature, velocity and flow
rate information in appropriate columns.
EXAMPLE
(1)
Source
No.
99
._ .
(2)
Process or
Operation
Paint Mix-
ing Tank
(3)
Hydrocarbon
Control
Equipment
Adsorber
L
W
Efficiency
of Control
Equipment
801
(5)
Date of
Instal-
lation
1969
(6)
Stack Data
Height
(ft)
20
Inside
Dla.
(ft)
1.5
Temp.
(°F)
77
Velocity
(feet per
sec)
20
i
|—-
i
I
Lz_.
Flow
rate
ft3/min)
i
2100
(7) PLiCASk. complete the last (.cottons on page 1U.
-------
VII. BULK SOLVENT STORAGE
A. Please complete the following information for each storage tank greater than
250 gallons capacity.
Annual Type of Fill and
Tank No. Solvent Type Capacity Thruput Control Equipment *
VIII. EFFECTS Of ENERGY CRISIS
Please state the changes in type and estimated annual consumption of sol-
vent as a result of the energy crisis. '...
Submerged fill, splash fill, return vent line, adsorber
85
-------
Table A-2. STUDY AREA BULK STORAGE INFORMATION
I. Company name:
2. Tank location: ( name a few nearby cross streets to aid us in locating
your facilities on our maps )
3. Person completing form: Title:
4. Phone number:
5. Type of products stored:
6. Specify number of fixed-roof tanks at this facility:
7. Specify number of floating-roof tanks at this facility:
8. Please use the following space to include any information tha't" would aid us
in obtaining accurate emission estimates: •• ;• ' .'''
86
-------
Table A-2 (continued). STUDY AREA BULK STORAGE INFORMATION
1. Tank location ( if available a diagram of area should be supplied.)
2. Tank Identification (number or name) _
3. Tank capacity, gals.
4. Tank dimensions,ft.
a) Diameter b) Height c) Length d) Width
5. Tank shape. Cycllndrical Spherical Other describe
6. Tank nlaterial of construction. Steel Fiberglass Other describe
7. Paint on tank roof.
a) White b) Aluminum c) Light Grey d) Medium Grey
e) Other describe .
8. Paint on shell
a) White b) Aluminum ______ c) Light Grey _____ d) Medium Grey
e) Other describe ..
9. Tank condition. Good _____ Fair Poor
10. Average vapor space height, ft. _________
11. Type of tank (check all applicable).
a)1 Fixed Roof b) Floating Roof c) Variable Vapor Space (indicate
expansion capacity) ________ d) Pressure _____ e) Underground _____
f) Aboveground
12. If tank is floating roof.
Type of roof: Double Deck __ Pontoon _____ Other describe __________________
Type of seal: Single _____ Double _____ Other describe ,
Type of construction: Riveted _____ Welded _____ Other describe
13. Chemical name of liquid being stored. ________________________
14. True vapor pressure of liquid ______________ psia at _____
15. Density of liquid at storage temperature (Ibs per gal)
16. Average molecular weight of liquid (Ibs per mole) _____
17. Throughput for the year 1973 (gala per year)
18. On a seperate sheet please describe any future anticipated storage tanks.
19. Type of loading: vessel^ , barge , truck (check)
20. Type of filling: submerged , splash
Name: Date:
Title: ' Phone:
87
-------
APPENDIX B
LABEL AND WORK SHEET COMPUTER PROGRAM
88
-------
LEVEL 21 MAIN DATE - 74109 14/47/04
DIMENSION A(45),C(4,26),ZIP(5),SIC(4),PLT(4),NCT<52)
REAL NAME(54,15)
DATA CC,BB/» ,», • •/
C READS CITIES
DO 211 J=l,54
211 READ(5,101) NCT(J), (NAME(J,I),1 = 1, 15)
101 FORMAT(I4,2X,15A1)
WRITE(6,650)
299 JCOUNT=1
300 DO 210 J=i,4
DO 210 K=l,26
210 C(J,K}= BB
C READS SOURCE CARD
READ(5,100,END=33Q)PLT,ICT,SIC,A, ZIP
C SIC + PLT ID TO MATRIX
DO 212 K=l,4
C(1,K) = SIC(K)
212 C(1,22+K) = PLT(K)
J=2
K = l
C NAME + STREET TO MATRIX
DO 200 1=1,45
IF(Ad).EO.CC) GO TO 39
IF(K.LT.2U C(J,K) = A(I)
K=K + 1
GO TO 200
39 C(J,K) = CC
J=J*1
IF(J.E0.4) GO TO 215
K = l
200 CONTINUE
C CITY * ZIP TO MATRIX
C CHECKS LIST FOR CITY
215 DO 216 1=1,54
IFdCT.EQ.NCT(XI) GOTO 220
216 CONTINUE
220 DO 221 K=l,15
IF(K.GT.IO) C(4,K+11) = ZIP(K-IO)
221 C(4,K)=NAME(I,K)
WRITE(6,550) ((C(L,M), M=l,26), L=l,3),)
WRITE(1,250) ((( C(L,M),M=1,26),L=1,3),(C(4,M),M=1,15),(C(4»M),M=
*22,26),MI=1,2)
250 FORMAT ( //3X,26A1/3X,26A1/3X,26A1/3X,15A1,6H R.I. ,5A1)
JCOUNT= JCOUNT + 1
IF (JCOUNT.LE.7) GO TO 300
WRITE(6,650)
650 FORMAT( »1 »,36X, • TEL NO »,3X,» DATE Q IN •t3ClXt.v TEL CONT M,3X,
*'COMMENTS* )
GO TO 299
330 STOP
100 FORMAT(5X,4A1,IX,14,1X,4A1,45A1,5A1)
STOP
END
89
-------
Table A-l. QUESTIONNAIRE TO MANUFACTURING INDUSTRIES AND DRY CLEANERS
official use
Rec. by tote:
SIC
X.Y
I. GENERAL INFORMATION
A. Company N«me_
Plant Address
Zip Cod«_
Nearest Street Intersection..
Mailing Address
Clty_
_Zlp Code,
B. Person to contact about form_
Telephone
Title
C. Approximate number of employees,
D. Nature of Business
E. Normal Operating schedule
_ Hrs. /day
_days/wk._
_wks/yr.
F. Approximate Percent Seasonal Operation:
Dec. -Feb.
Mar-May
Jun-Aug
Sept. -Nov.
C. Are volatile organic or solvent-containing materials such as cleaning fluids,
coatings, adhesive*, Inks, etc. used In your operation? _____ Yes No
If BO. sign form and return
If YES, sign for* and complete only the sections pertaining to your
operation:
II. Dry Cleaning — .-—-—-.
III. Degreaslng ——
IV. Surface Coating Applications
. A. Fabric .and Rubberized -------------------
B. Protective or Decorative other than IV-A•
C. Printing
D. Miscellaneous Surface Coating*
(Adheslves, Paper, Leather, films. Class etc)
Manufacturing Industries
Page
2. 9 & 10
3. 9 & 10
4, 9 & 10
5, 5 6 10
6, 9 & 10
7, 9 & 10
8, 9 & 10
SIgnature
Date
76
-------
II. DRY CLEANING
A. Amount of cloches cleaned per year ton* .
B. Type of dry cleaning unit a hot or dry-to-dry
O cold or transfer
C. Type and amount of solvent cleaner purchased in 1973.
Perch lor oe thy lene Cal./Yr.
Stoddard solvent Gal./Yr.
Other (specify) _ Cal./Yr.
Other (specify) _ Gal./Yr.
D. Supplier of solvent - Name and address
Perchlorethylene _ _
Stoddard Solvent
Other (specify)
Other (specify)
E. Please complete Section VI. page 9.
If you have any questions about this section please contact:
Mr. Roger Schilling
Field Representative for
International Fabricare Institute
5 Shawsheen Ave.
Bedford, Mass.
(617) 275-7583
77
-------
III. DBCUASDIG OPERATIONS
A. Type of degreailngi 0 cold aolvent cleaning
Dvapor degree*Ing
•• Typ* *nd eaounc of solvent purchased for degreaeing operatlona.
1) Stoddard __Gal./yr.
2) 1,1,1-Trlchloroethane
(Chlorothene VG) ; Cal./yr.
3) Perchloroethylene Cel./yr.
4) Hathylene chloride _Gal./yr.
5) Trlchloroethyleae Cal./yr.
6) Other (apeclfy) __Gel./yr.
7) Other (apeclfy) Gal./yr.
C. Supplier* of Solvent*
D. Vaate advent 4i*poael sethod
teount of each aolvent returned for reproceaalng to vendor or collector
1) Stoddard Cal./yr.
2) Trlchloroethane Cal./vr.
3) Ferchloroethylene Cal./vr.
4) Methylene chloride Gel./vr.
5) Trlchloroethylene Gal./vr.
6) Other (apeclfy) Gal./yr.
7) Other (apeclfy) Gal./yr.
Plea«a complete Section VI. pege 9.
78
-------
IV-A. FABRIC OR RUBBERIZED COATING APPLICATION
(1) Materlal(s) being coated
.(2) Type of coating process:
Source
Ko.*
State Coating Process:
Impregnation,
'Vet" Coating,
Hot Melt Coating,
Lamination
Type of
Coating"
Amount
of Coating
(Gal/Yr)
Type* and
X of Vehicle
Solvent
.... —
~ - . .....
- •
Type and
Amount 'of
Solvent Added
to Coating
(Cal/Yr)
• — •• •
•
' !
!
. ^
' '
"
(3) Type of cleaning solvent
_, Amount
., Amount
(4) Is any solvent returned to supplier or collector?
*
No
Yea
Type'
Amount
(Cal/Yr)
(Cal/Yr)
(Cal/Yr)
(5) Please complete Section Vj. p. 9; use saaa Source No.
*A source Is an Individual or similar pieces of equipment such as coalers, dryers.
etc. It should correspond to the Source No. on page 9. If applicable, it should
also correspond to previously reported sources in "Air Pollution Emissions .Report"
(Form 158-R75)
**Polyvinyl chloride, polyurethanes, etc.
+Toluene, naphtha, mineral spirits, MEK, xylene, chlorinated hydrocarbon, other
(specify).
79
-------
IV-B. PROTECTIVE OR DECORATIVE COATINGS OTHER THAN FABRIC COATING
1. Indicate material being coated _______________________———
2. Type and amount of coating used:
Source*
Number
State Application Method:
Spraying, Dipping, Roller,
Flow, etc.
Type of
Paint**
Amount
Gala./yr.
X
solid*
Type and T. of uajor
solvents
i
3. Type* and amount of thinner uaed for dilution and cleaning not Included
*bove ; , Amount Cal./yr.
Amount
Gal./yr.
4. Plea»e complete Section VI. pane 9.
A source is an individual or similar pieces of equipment such as spray booths, tanks,
dryers, etc. It should correspond to the Source No. on page 9. If applicable,
it should also correspond to previously reported sources In "Air Pollution Emis-
sions report" (Form 158-R75)
(!) paint, (3) varnish/shellac, (4) lacquer, (5) enamel, (6) primer
If known, - acetone, isopropyl alcohol, KEK, butyl acetate, cellusolve, toluene, etc.
80
-------
IV-C. PRINTING
(1) Material being coated
(2) Type of printing procees:
Source
No.*
State Printing Process:
Letterpress, Flexo-
graphlc, Lithographic,
Gravure , Screen
Type of
Ink**
Amount
flb/yr)
Type* and 7, of major solvents
In Ink
I
(3) Type and amount of solvent uaed for dilution and cleaning not
included above: Amount tel./yr.
____________ Amount •''••'' Cal./vr.
(*) Please complete Section VI p.9 ; ; use aims Source No.
A source Is an Individual or similar printing machines, dryers, etc. It should cor-
respond to the Source No. on page 9. If applicable, it should also correspond to
previously reported sources in "Air Pollution Emissions Report" (Form 1S8-R7S).
A.A
Solvent based, oil based, lacquer-type. etc.
'laopropyl alcohol, Ethanol, Propanol, Naphtha/Miners! Spirits, Toluene,
MEK, other (specify)
81
-------
V. MANUFACTURING INDUSTRIES
1) Brief Description of Process
Source
Ho.
Process or
operation using M
organic materials
Type of material
processed +
Annual
thruput at
source
Type ** and I of
solvent In material
Quantity of
volatile
solvent lost
to atmosphere
during process
Ibs/yr.
Method
used to
determine
emissions
(guess or
material
balance)
.
2) Please completa Section VI. page9 ; use same Source No.
A source Is an Individual or similar pieces of equipment processing organic materials. Ic should correspond to the
Source No. on page 9. If applicable, It should also correspond to previously reported sources In "Air Pollution
Emissions Report" (Form 158-R75).
Dryer, reactor, mixing tank, etc.
Paint, varnish, shellac, lacquer, enamel, primer, adhesive, Ink, other (specify).
tt
Acetone. MEK. butyl acetate, cellosolve, ethanol, naphtha, toluene, mineral spirits, uthar (s^cifyj.
-------
00
VI. CONTROL AND STACK INFORMATION
Instruction*:
(I) A number should be assigned to each piece of equipment that emits hydrocarbons or to a number
of similar units that are vented to a common stack. The Source No. below should correspond
to the sections previously filled out. If similar equipment have different control equipment
please split the source number to a, b or c.
(2) Identify the process or operation from which hydrocarbons are emitted. For example, dry
cleaner, degreaslng tank, spray booth, reactor, etc. If more than on* unit Is emitting to a
common stack, specify the number of units.
(3) Identify the hydrocarbon control method used such a* after-burners, scrubbers, carbon adsorption,
condensers, etc.
(4) Indicate approximate efficiency If known.
(5) Indicate Installation date of control equipment.
(6) If hydrocarbons are emitted from a stack, provide height, diameter, temperature, velocity and flow.
rate Information In appropriate column*.
EXAMPLE
(1)
Source
No.
99
(2)
Process or
Operation
Paint Mix-
Ing Tank
(3)
Hydrocarbon
Control
Equipment
Adsorber
(4)
Efficiency
of Control
Equipment
BOX
(5)
Date of
Instal-
lation
1969
Height
(ft)
20
S
Inside
Dla.
(ft)
1.5
w
tack I
Temp.
(°F)
77
>ata
Velocity
(feet per
sec)
20
t
I
I
Flow
rate
ft3/mln)
2100
.!
(7) pl£ASfc complete the last motions on page 10.
-------
VIZ. BULK SOLVENT STOHACE
A. Please complete the following information for each storage tank greater than
250 gallons capacity.
Annual Type of Fill and
Tank No. Solvent Type Capacity Thruput Control Equipment *
VIII. EFFECTS OF ENERGY CRISIS
Please state the changes la type and estimated annual consumption of sol-
vent ss a result of the energy crisis.
Submerged fill, splash fill, return vent line, adsorber
85
-------
Table A-2. STUDY AREA BULK STORAGE INFORMATION
1. Company name:
2. Tank location: ( name a few nearby cross streets to aid us in locating
your facilities on our maps ) ^___
3. Person completing form: Title;
4. Phone number:
5. Type of products stored:
6. Specify number of fixed-roof tanks at this facility:
7. Specify number of floating-roof tanks at this facility:
8. Please use the following space to include any information that would aid us
in obtaining accurate emission estimates:
86
-------
Table A-2 (continued). STUDY AREA BULK STORAGE INFORMATION
1. Tank location ( If available a diagram of area should be supplied.)
2. Tank Identification (number or name) _
3. Tank capacity, gals. ______________
4. Tank dimensions,ft.
a) Diameter b) Height c) Length d) Width
5. Tank shape. Cyclindrical . Spherical Other describe ________
6. Tank nlaterial of construction. Steel Fiberglass ___^ Other describe
7. Paint on tank roof.
a) White b) Aluminum c) Light Grey d) Medium Grey
e) Other describe _____________________________________________
8. Paint on shell
a) White _____ b) Aluminum _____ c) Light Grey _____ d) Medium Grey _____
e) Other describe _____________________________________________________
9. Tank condition. Good _____ Fair _____ Poor
10. Average vapor space height, ft. __
11. Type of tank (check all applicable).
a)1 Fixed *oof b) Floating Roof c) Variable Vapor Space (indicate
expansion capacity) _________ d) Pressure _____ e) Underground _____
f) Aboveground _____
12. If tank is floating roof.
Type of roof: Double Deck . Pontoon _ Other describe ___________________
Type of seal: Single _____ Double _____ Other describe _____________________
Type of construction: Riveted _____ Welded . Other describe
13. Chemical name of liquid being stored. _
14. True vapor pressure of liquid ______^______ psia at °F.
IS. Density of liquid at storage temperature (Ibs per gal)
16. Average molecular weight of liquid (Iba per mole) _____
17. Throughput for the year 1973 (gala per year)
18. On a separate sheet please describe any future anticipated storage tanks.
19. Type of loading: vessel , barge , truck (check)
20. Type of filling: submerged , splash
Name; Date:_
Title: Phone:
87
-------
APPENDIX B
LABEL AM) WORK SHEET COMPUTER PROGRAM
88
-------
LEVEL 21 MAIN DATE » 74109 14/47/04
DIMENSION A(45),C(4,26),ZIP(5),SIC(4),PLT(4),NCT(52)
REAL NAME(54,15)
DATA CC,BB/«,«,' •/
C READS CITIES
DO 211 J=l,54
211 READ(5.101) NCT(J), (NAME ( J , I ) 1 1=1, 15)
101 FORMAT(I4,2X,15A1 )
WRITE(6,650)
299 JCOUNT=1
300 DO 210 J = l,4
DO 210 K=l,26
210 C(J,K)= BB
C READS SOURCE CARD
READ(5,100,END=330)PLT,ICT,SIC,Af ZIP
C SIC * PLT ID TO MATRIX
DO 212 K = l,4
C(1,K) = SIC(K)
212 CU.22+K) = PLT(K)
J=2
K=l
C NAME * STREET TO MATRIX
DO 200 1=1,45
IF(Ad).EO.CC) GO TO 39
IF(K.LT.21) C(J,K) = All)
GO TO 200
39 C(J,K) = CC
IFtJ.EO.4) GO TO 215
K=l
200 CONTINUE
C CITY * ZIP TO MATRIX
C CHECKS LIST FOR CITY
215 DO 216 1=1,54
IF(ICT.EQ.NCTdl) GOTO 220
216 CONTINUE
220 DO 221 K=l,15
IF(K.GT.IO) C(4,K+11) = ZIP(K-IO)
221 C(4,K)=NAME( I,K)
WRITE(6,550) ((C(L,M), M=I,26), L=l ,3 ) , (C (4,M) ,M=1 , 15) , (C <4,M ) ,
* M=22,26)
550 FORMAT!/// 1X,36< 1H-) ,5< • + », 10 < 1H-) ),• + • ,25 ( lH-)/3X,26Al , 8X,6 (••»',
*10X) /3X,26A1,8X,6( '*»,10X) /3X,26A1 , 8X ,6 ( •*• , 10X) /3X,15A1,6H R.I
*. ,5A1,8X,6( '*»,10X))
WRITE (1,250) ((( C(L,M),M>l,26),L=l,3),(C(4,H),M«lt15),(C(4,M),Ms
*22,26),MI=1,2»
250 FORMAT I //3X,26A1/3X,26A1/3X,26A1/3X,15A1,6H R.I. ,5A1)
JCOUNT= JCOUNT * 1
IF (JCOUNT. LE. 7) GO TO 300
URITE(6,650>
650 FORMAT! »1 S36X, • TEL NO '.SX,1 DATE 0 IN *,3(1X,* TEL CONT «),3X,
* 'COMMENTS' )
GO TO 299
330 STOP
100 FORMAT (5X,4A1, IX, 14, 1X,4A1,45A1 ,5A1 )
STOP
END
89
-------
APPENDIX B
LABEL AND WORK SHEET COMPUTER PROGRAM
88
-------
LEVEL 21 MAIN DATE * 74109
DIMENSION A(45),C(4,26),ZIP(5),SIC<4),PLT(4),NCT(52)
REAL NAME(54,15)
DATA CC.BB/',',1 •/
C READS CITIES
DO 211 J=l,54
211 READ(5,101) NCT(J), (NAME(J,I),1 = 1,15 )
101 FORMAT(I4,2X,15A1)
WRITE(6,650)
299 JCOUNT=1
300 DO 210 J=l,4
DO 210 K=l,26
210 C(JtK)= BB
C READS SOURCE CARD
READ(5,100,END=330)PLT,ICT,SIC,A, ZIP
C SIC + PLT ID TO MATRIX
DO 212 K=l,4
C(1,K) = SIC(K)
212 C(1,22+K) = PLT(K)
J=2
K=l
C NAME + STREET TO MATRIX
DO 200 1=1,45
IF(Ad).EO.CC) GO TO 39
IF(K.LT.2D C(J,K) = Ad)
K=K + 1
GO TO 200
39 C(J,K) = CC
IF(J.EQ.4) GO TO 215
K = l
200 CONTINUE
C CITY + ZIP TO MATRIX
C CHECKS LIST FOR CITY
215 DO 216 1=1,54
IF(ICT.EQ.NCTd)) GOTO 220
216 CONTINUE
220 DO 221 K=l,15
IF(K.GT.IO) C(4,K+11) = ZIP(K-IO)
221 C(4,K)=NAME( I,K)
WRITE(6,550) ((C(L,M), M = l,26), L=l,3),(C(4,M),M=1,15),(C(4,M),
* M=22,26)
550 FORMAT(/// 1X,36(1H-),5(• + •,1C(1H-)),• + •,25(1H-)/3X,26A1,8X,6<•+•,
*10X) /3X,26A1,8X,6(*+»,10X) /3X,26A1,8X,6(•+•,10X) /3X,15Al,6H R.I
*. ,5A1,8X,6( *+*,10X) )
WRITE(1,250) ((( C(L,M),M=1,26),L=1,3),(C(4,M),M=1,15),(C(4,M),M=
*22,26),MI=1,2)
250 FORMAT ( //3X,26A1/3X,26A1/3X,26A1/3X,15A1,6H R.I. ,5A1)
JCOUNT= JCOUNT + 1
IF (JCOUNT.LE.7) GO TO 300
HRITE(6,650)
650 FORMAT( •! »,36X, • TEL NO *,3X,« DATE Q IN SSdX,* TEL CONT '),3X,
*'COMMENTS' )
GO TO 299
330 STOP
100 FORMAT(5X,4A1,1X,I4,1X,4A1,45A1,5A1)
STOP
END
89
-------
MARCH 1977 AMC7010.T0108F-FCR
REGIONAL AIR POLLUTION STUDY (RAPS)
100% COMPLETION REPORT
FOR
TASK ORDER 108-F
HYDROCARBON EMISSION INVENTORY
Prepared for
Environmental Protection Agency
Office of Air & Water Management
Office Of Air Quality Planning Standards
Research Triangle Park, N.C. 27711
by
F. E. Littman
R. W. Griscom
G. Seeger
Rockwell International
Atomics International Division
Air Monitoring Center
11640 Administration Dr.
Creve Coeur, Mo. 63141
-------
AMC7010.T0108F-FCR
TABLE OF CONTENTS
PAGE
1.0 INTRODUCTION
2.0 HYDROCARBON INVENTORY DATA
3.0 SENSITIVITY ANALYSIS
4.0 METHANE, NON-METHANE SEPARATION METHODOLOGY
5.0 SOURCE TESTING FOR HYDROCARBON CLASSIFICATION
APPENDIX I: SOURCE CLASSIFICATION CODE (SCC) LISTING
VERSUS PERCENTAGE CLASSIFICATION OF
METHANE AND NON-METHANE HYDROCARBONS
APPENDIX II: CHROMATOGRAPHIC METHOD FOR SEPARATION OF
METHANE AND NON-METHANE HYDROCARBONS
APPENDIX III: HYDROCARBON SOURCE TESTS
1
2
4
6
11
13
16
43
-------
AMC7010.T0108F-FCR
TABLES
PAGE
TABLE 1 HYDROCARBON SOURCE LOCATIONS 3
TABLE 2 METHANE EMISSIONS HYDROCARBON SOURCES 7
TABLE 3 NATIONAL EMISSIONS DATA SYSTEM (NEDS) SOURCE
CLASSIFICATION CODE (SCC) REPORT 9
TABLE 4 EMISSION FACTORS 10
-n-
-------
AMC7010.T0108F-FCR
1.0 INTRODUCTION
As part of the RAPS Point Source Inventory a new Hydrocarbon Emission
Inventory has been completed for the St. Louis Air Quality Control Region
(AQCR-70). The existing point source inventory primarily dealt with those
hydrocarbon emissions produced by fuel combustion. This has been expanded
to include all hydrocarbon emission sources which emit more than one ton per
year of total hydrocarbons.
The inventory is chiefly concerned with "point" sources, or those emissions
which are released through a stack or vent as in the case of a petroleum storage
tank. It does not include area sources such as gasoline stations, dry cleaning
and mobile sources. Point sources in the St. Louis AQCR emit approximately
47,000 tons per year total hydrocarbons, or 17.8 percent of the hydrocarbon
emissions in the AQCR.
Data for the hydrocarbon inventory are primarily annual data. The exception
to this is for the hydrocarbon emissions from fuel combustion. The inventory
for fuel combustion sources is the most detailed since, due to the nature of the
operation, hourly records are available in most cases. Data for evaporative
emissions, which account for approximately 40% of the point source hydrocarbon
emissions, are only accurate for accounting periods and are thus presented as
annual
The National Emission Data System (NEDS) Inventory indicates a total of
78,000 tons of hydrocarbon emitted per year in the AQCR. The principal reason
for the large discrepancy between the two inventories is that the NEDS inventory
includes a large number of fixed roof gasoline and crude oil storage tanks
which have since been replaced with floating roof storage tanks.
As part of this Task a methodology has been developed for separating the
total hydrocarbon emissions into methane and non-methane components by Source
Classification Code (SCC). This is described in Section 2.
-1-
-------
AMC7010.T0108F-FCR
2.0 HYDROCARBON INVENTORY DATA
The hydrocarbon point source inventory represents emissions from 64
companies in AQCR-70 with emissions in excess of one ton per year. The
NEDS inventory indicated a total of 78,474 tons per year from point sources.
The NEDS data show quite a large number of fixed roof storage tanks with
gasoline or crude oil. This situation no longer exists; with only a few ex-
ceptions all highly volatile liquids are stored in floating roof storage tanks.
The hydrocarbon emissions in the AQCR are now appoximately 47,000 tons per
year from point sources. Thirty-seven of the locations emit in excess of
100 tons per year, ten in excess of 10 tons per year, and seventeen are in
excess of one ton per year.
The data for the hydrocarbon inventory was obtained by contacting all
of the companies with hydrocarbon emissions in the AQCR. Locations accurate
to 10 meters were obtained from visiting plant sites and pinpointing the
location of sources on Geological Survey maps. The data included petroleum
storage capacities and throughputs, coatings and solvent production and usage,
and calculated emissions. In addition, hydrocarbon emissions are obtained
from combustion information which is continuously being received as part of
the point source inventory. All of the data were recorded on RAPS coding forms,
keypunched, and entered into the RAPS Point Source Data Base. Table 1 is a
list of the companies which furnished data for the hydrocarbon inventory.
Emission patterns for hydrocarbon sources vary widely due to the variety
of types of hydrocarbon sources. Data which are being received continuously
as part of the RAPS Point Source Inventory are generally on an hourly basis
Hydrocarbon data from sources which produce or use coatings and solvents are
accompanied with hourly use patterns based on working hours during a year.
Evaporative emissions from petroleum storage are assumed to be generated on a
continuous basis and are therefore spread equally throughout the year. With
the exception of hydrocarbons from hourly combustion data, the hydrocarbon
emission data are collected as annual data.
-2-
-------
AMC7010.T0108F-FCR
TABLE 1
HYDROCARBON SOURCE LOCATIONS
Amoco Oil
Shell Oil
Clark Oil
Granite City Steel
General Motors
Ford Motors
Chrysler Motors
Mobil Oil Terminal
Lianco Container
American Can
Crown Cork & Seal
Phillips Oil Terminal
Morris Paint
Monsanto
Ke11wood
Continental Can
Union Electric
Illinois Power
A.O. Smith
Great Lakes Carbon
Harvard Interiors
McDonnell Douglas
Williams Pipeline Terminal
Triangle Terminals
Texaco Terminal
Shell Oil Terminal
J. D. Street Terminal
Independent Petrochemical
Missouri Terminal
Amcar
Empire Stove
Mallinckrodt
Municipal Incinerators
Alpha Cement
Missouri Portland Cement
Vitro Products
Ramsey
Martin Oil Terminal
Apex Oil Terminal
Laclede Steel
Moss American
Washington University
Autocrat
Scott Air Force Base
Precoat Metals
Sunoco Terminal
Hartog Terminal
Granite City Army Inst.
Menard Penitentiary
Mascoutah Power Plant
Edwin Cooper
Olin
American Steel
Nestle
Reilly Tar and Chem.
As discussed in Secion 4.0, the hydrocarbon emissions will be available
as a separate printout of methane and non-methane hydrocarbons in addition to
the normal printout in which total hydrocarbons are included in the Point
Source Emission Listing.
-3-
-------
AMC7010.T0108F-FCR
3.0 SENSITIVITY ANALYSIS
To evaluate the accuracy of the hydrocarbon inventory a sensitivity analysis
has been applied to the data. This is similar to the analysis performed for SCL
with the point source inventory under another Task Order^ . To determine the
allowable error of a subclass of pollutant the following equation is used:
„ 0 . a, = allowable error
aix 9 n where: k
k
0 = permissible maximum error
Q = Total emissions
Q. = Emissions subclass
The allowable error is the maximum permissible error of any part of the
inventory, given a maximum permissible error for the whole system. This
approach keeps the inventory at an equivalent level of accuracy and points out
areas where accuracy has to be improved. To evaluate this inventory a fairly
stringent set of conditions were applied: a confidence level of 95 percent and
an acceptance interval of 10 percent. This leads to a maximum permissible
error for the system, 0, of 2.25%.
The analysis indicated that under these constraints, the hydrocarbon
inventory has an allowable error of 49% for the major source subclass of 100
tons per year, 153% for a 10 ton source, and 485% for a 1 ton source.
Since hydrocarbon sources are principally evaporative sources, they are
not monitored hourly. Data are accumulated over longer time periods, generally
for accounting purposes. Thus, long term data are quite accurate; however,
the time pattern of emissions is not well known. A closer examination indicates
that emissions from most evaporative sources, are fairly uniformly distributed.
The major exception to this are loading docks. As a result, the evaporative
hydrocarbon emissions from loading docks may not meet the sensitivity require-
ments on an hourly basis. These sources account for 3700 tons per year, or
approximately 7.9% of the total hydrocarbon emissions in the AQCR.
(1) Littman, F. E., "Regional Air Pollution Study Point Source Methodology
and Inventory", EPA - 450/3-74-054, October 1974.
-4-
-------
AMC7010.T0108F-FCR
The data were entered into the inventory together with an operating
pattern which describes the operation of the source as well as can be done
within the constraints of the data handling system.
-5-
-------
AMC7010.T0108F-FCR
4.0 METHANE, NON-METHANE SEPARATION METHODOLOGY
Hydrocarbons participate in the formation of photochemical oxidants. The
extent of participation is determined by their respective reactivities. Methane
is universally accepted as being non-reactive. More importantly, methane is a
normal constituent of the atmosphere as a result of natural decomposition pro-
cesses. Therefore, a gross classification has been performed and hydro-
carbon inventory has been separated into methane and non-methane hydrocarbons.
(2)
Trijonis and Arledgev have recently reported on a hydrocarbon classifica-
tion scheme for the Los Angeles area based on 2, 5 and 6 reactivity categories.
The only difference between the 5 and 6 category schemes is that methane is
considered separately in the latter. Although their classifications are strictly
valid only for Los Angeles, their breakdown (for methane only) was applied to
sources in St. Louis under this Task and compared with a limited number of source
tests. Table 2 indicates the molar percent methane for the applicable types of
sources in St. Louis. The molar percentages were determined by assuming that the
non-methane hydrocarbons have an average composition of C,-, as reported by
Trijonis and Arledge. Catalytic Crackers were not included in the referenced
report but have been added based upon a source test in St. Louis. In addition,
the number for coke oven emissions is from an as yet unpublished report on a
test of a local coking plant sponsored by the ^
The breakdown in Table 2 for combustion sources was verified by six source
tests of combustion sources in St. Louis.
A few of the results obtained from source testing are quite different from
those reported by Trijonis and Arledge, such as the result for SCC code 1-02-002-09
in Table 2. For all sources in St. Louis which were tested, the test results
will be used to determine new (or "special") emission factors to be applied to
these sources. These special emission factors are only valid for the source
tested. For other sources with the same SCC number, such as 1-02-002-09, the
percentages from the Trijonis and Arledge report will be used.
(2) Trijonis, 0. C., and K. W. Arledge, "Utility of Reactivity Criteria in
Organic Emissions Control Strategies for Los Angeles", EPA Contract
No. 68-02-1735, December 1975.
(3) Conversation with Kirk Foster, USEPA, 30 September 1976.
-6-
-------
AMC7010.T0108F-FCR
TABLE 2
METHANE EMISSIONS HYDROCARBON SOURCES
Methane, % of THC
Source SCC Ref. (1) RAPS Source Test
Petroleum Refining - Storage 4-03-002-01 2 nil
- Catalytic Cracker 3-06-002-01 20
Fuel Combusion - general 1-XX-XXX-XX 78
- utility boiler, oil 1-01-005-01 74
- industrial boiler, oil 1-02-004-01 71
- industrial boiler, coal 1-02-002-09 43
Surface Coating* - Heat Curing 4-02-XXX-XX 2 30
- Air Dry 4-02-XXX-XX 0 10
Degreasing 4-01-002-XX 0
Industrial Manufacturing 3-01-XXX-XX 0
Coking Plants 3-03-003-XX 0
*Note: SCC numbers do not relate a difference between heat curing and air
drying.
The values in Table 2 have been incorporated into a scheme based on the
Source Classification Code (SCC). The SCC is an identification system developed
for NEDS, upon which the point source hierarchy is structured. The SCC system
is being used for the RAPS point source data handling system. All data is stored
and retrieved by use of the SCC. Any plant or process which causes air pollu-
tion can be represented by one or several SCC numbers. Table 3 shows a typical
sample of SCC numbers. The SCC numbers consist of four groupings. For example;
in SCC 4-03-001-02:
Group I - a single digit (4) - designates "Point Source, Evaporative"
Group II - two digits (03) - designates "Petroleum Storage"
Group III - three digits (001) - designates "Fixed Roof"
Group IV - two digits (02) - designates "Breathing - Crude"
In addition the base unit upon which the emission factors are based is given;
in this case, "1000 gallons storage capacity".
-7-
-------
AMC7010.T0108F-FCR
The starting point of the inventory are the emission factors which relate
emissions to the operation of the sources. These factors are based upon the
best available information, generally gathered from source tests. Data are
gathered which are based upon consumption, production, or storage and emission
factors are applied to generate emissions. Table 4 shows a typical example of
emission factors and the associated SCC numbers.
-8-
-------
AMC701Q.T0108F-FCR
TABLE 3
NATIONAL EMISSIONS DATA SYSTEM (NEDS)
SOURCE CLASSIFICATION CODE (SCC) REPORT
I
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
J
3
3
3
3
3
3
3
3
3
4
4
4
4
SCC
11
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
90
99
01
01
01
01
01
02
02
02
02
02
02
03
OJ
10
III
001
002
002
002
00?
002
004
004
004
004
004
004
004
004
OOb
OOb
OOb
OOb
005
OOb
005
OOb
OOb
OOb
OOb
OOb
006
OOb
OOb
OOb
OO/
OOH
009
999
999
999
999
001
001
002
002
999
001
003
004
005
006
999
001
001
SCC CATEGORY NAMES
IV
99
01
Ob
07
OH
99
01
02
03
04
05
Ob
07
99
01
02
03
04
Ob
Ob
07
99
01
02
03
04
05
Ob
07
99
99
99
99
97
98
99
99
01
02
01
99
99
01
01
01
01
01
99
01
02
I 11
INDUSTRIAL PHOCESI INPROCESS FuEL
INDUSTRIAL PROCESI INPROCtSS FUEL
INDUSTRIAL PROCESI INPHOCESS FuEL
INDUSTRIAL PROCESI INPHOCtSS FUEL
INDUSTRIAL PHOCESI INPHOCESS FUEL
INDUSTRIAL KHOCtSI INPHOCtSS FUtL
INDUSTRIAL PRUCESI INPHOCtSS FUEL
INDUSTRIAL PROCESI INPROCEaS Fut.L
INDUSTRIAL PROCtSI INPHOCESS FUEL
INDUSTRIAL PRUCESI INPHOCESS FUEL
INDUSTRIAL PROCtSI INPROCt.SS FUEL
INDUSTRIAL PHOCESI INPROCESS FUEL
INDUSTRIAL PROCESI INPROCESS FUEL
INDUSTRIAL PROCESI INPROCtSS FUEL
INDUSTRIAL PROCESI INPHOCESS FUEL
INDUSTRIAL PROCEil iNPHUCtSS FUEL
INDUSTRIAL PHOCEil INPHOCtSS FuEL
INDUSTRIAL PHOCtS 1 IM'RULtSS FUEL
INDUSTRIAL pHoctsi INPROCESS FUEL
INDUSTRIAL PHOCtSI INPROCESS FUEL
INDUSTRIAL PROCtSI 1NPROCESS FUEL
INDUSTRIAL PHOCESI INPHOCESS FUEL
INDUSTRIAL PRuCEil INPHOCtSS FUtL
INDUSTRIAL PROCESI INPROCESS FuEL
INDUSTRIAL PNOCESI INPHOCtSS FUEL
INDUSTRIAL PROCESI INPROCESS FUEL
INDUSTRIAL PROCESI INPHOCESS FUEL
INDUSTRIAL PROCtSI INPHOCESS FUEL
INDUSTRIAL PROCESI INPROCESS FUEL
INDUSTRIAL PROCESI INPHOCESS FUEL
INDUSTRIAL PROCES 1 INPROCESS FUEL
INDUSTRIAL PROCEbl INPHOCESS FUEL
INDUSTRIAL PROCESI INPHOCESS FUEL
INDUSTRIAL PHOCESI INPROCESS FUEL
INDUSTRIAL PROCESI INPROCESS FUEL
INDUSTRIAL PROCESI INPROCESS FUEL
III
(ANTHRACITE COAL
IHITUMINOUS COAL
IfllTUMINOUS COAL
IBMuMINOUS COAL
IHITUMINO'JS COAL
(BITUMINOUS COAL
(RESIDUAL OIL
(RESIDUAL OIL
(RESIDUAL OIL
RESIDUAL OIL
RESIDUAL OIL
RESIiluAL OIL
RESIDUAL OIL
RESIDUAL OIL
IDISTlLLATE OIL
IDISTlLLATE OIL
IDISTIlLATE OIL
IDISTlLLATE OIL
IOISTILLATE OIL
IOISTILLATE OIL
(DISTILLATE OIL
IOISTILLATE OIL
(NATURAL GAS
INATUHAL GAS
1 NATURAL GAS
INATUHAL GAS
INATUHAL GAS
INATUHAL GAS
(NATURAL GAS
(NATURAL GAS
(PROCESS GAS
ICOKE
1 *OOD
IV UNITS
(OTHER/NOT CLASIFOITONS BORNEO
ICEMENT KILN ITONb BURNED
.IdHICK K1LN/DF)Y ITONS BURNED
IGYPSUM KILN/ETC ITONS BUHNEO
ICOAL DRYERS ITONS BUHNLO
IOIHEH/NOT CLASIfOITONS 6UPNED
IASPHALT DRYER 11000 GALLONS
ICtMENT KILN 11000 GALLONS
ILIME KILN 11000 GALLONS
IKAOLIN KILN 11000 GALLONS
IMETAL MELTING 11000 GALLONS
IBR1CK KILN/OHY 11000 GALLONS
IGYPSUM KILN/ETC 11000 GALLONS
IO!n£H/NOT CLASIFOI1000 GALLONS
(ASPHALT DRYER 11000 GALLONS
(CEMENT KILN 11000 GALLONS
ILIME KILN 11000 GAILCN5
IKAOLIN MLN 11000 GALLONS
iMtTAL MELTING 11000 GALLONS
(BRICK KILN/DRY 11000 GALLONS
IGYPSUM KILN/ETC 11000 GALLONS
IOTHER/NOT CLASIFD'1000 GALLONS
IASPHAUT OHYER IMILLION CUBIC
ICEMENT KILN IMILLION CUBIC
ILIME KRN IMILLION CUBIC
IKAOLIN KILN IMILLION CUBIC
IMETAL MELTING IMILLION CUBIC
IBRICK KILN/OHYS IMILLION CUBIC
IGYPSUM KILN ETC IMILLION CUBIC
IOTHER/NOT CLASIFDIMILHON CUBIC
IOTHER/NOT CLASIFDIMILLION CUBIC
IOTMEH/NOT CLASlFDITOMi
IOTHEH/NOT CLASIFDITONS BURNED
IOTHER/NOT CLASIFDISPECIFY IN REMARK 1 MILL I ON CUBIC
IOTHER/NOT CLASIFDISPECIFY IN HE^AHKIIOOO GALLONS
BURNED
BURNED
BURNED
BURNED
BUPNED
BURNED
BURNED
BURNED
E'UHNED
BURNED
BURNED
BURNED
BURNED
BURNED
BUHNEO
BURNED
FEET BURNED
FEET BURNED
FEET bU
-------
TABLE 4
EMISSION FACTORS
AMC7010.T0108F-FCR
POINl SC CVAP -SURFACE COATING (CONTINUED)
VARNISH/SHELLAC
4-02-003-01 GENERAL
LAQUER
4-02-004-01 GENERAL
ENAHEL
4-02-005-01 GENERAL
PRIMER
4-02-006-01 GENERAL
COATING OVEN
4-02-008*01 GENERAL
SOLVENT
4-02-009-01 GENERAL
OIHEH/N01 CLASIFO
4-02-999-99 SPECIFY IN REHARK
POUNDS EMITTED P t R UNIT
PART SOX NOX HC
1.000.
CO
UNITS
TONS COATING
POINT SC EVAP
FUEO KOUF
4-03-001-01
4-03-001-02
4-03-001-03
4-OJ-OC1-04
4-CJ-OOl-OS
4-03-001-06
4-03-001-0;
4-03-001-OS
4-C3-001-CH
4-C3-001-10
4-03-U01-11
4-03-001-12
4-03-001-13
4-03-001-14
4-03-001-15
4-03-001-16
4-03-001-50
4-G3-001-51
4-03-GCI-52
4-03-001-53
4-03-001-54
4-03-001-55
4-03-001-56
4-03-001-57
4-03-OC1-58
4-03-001-59
4-C3-001-60
4-03-001-61
FLUAlfhG flOO?
4-03-002-01
4-03-O02-U2
4-03-002-03
4-03-OG2-04
4-03-002-05
4-03-002-06
4-0 3-002-0 (
4-03-002-08
4-03-002-09
4-03-00^-10
4-03-002-11
4-03-002-12
4-C3-002-13
4-03-002-14
4-03-002-15
4-03-002-16
VAR-VAPCB SPACE
4-03-00 3-O2
4-03-003-03
4-0 3-00 3-O4
4-03-003-05
4-03-003-06
4-03-003-OT
4-03-003-08
4-03-003-09
4-03-003-10
4-03-003-11
4-03-003-12
4-03-003-13
4-03-003-14
-PETKUL PROO SIG
BREATH-GASOLINE
BREATH-CRUDE
WORKING-GASOLINE
WORKING-CM) OE
OREATH-JGl FULL
UH6ATH-KE8USENE
BP.EATH-OIS1 FUEL
CnEAlH-eF.NZENE
BREATH-CYCLOHEX
BHFATH-CYCLOPtNT
HREATH-HEPTANL
BUJATH-HhXANE
BSEATH-1SOOCTANE
UREATH-ISUPENTANE
BREA1H-PEN1ANE
BREATII-TnLUENE
WORKING- JET FUEL
WORK ING-KEROStNE
WORKING-OIST FUEL
WORKING-BENZENE
WORKING-CYCLOMEX
WOKKING-CYCLOPEHT
WORKI NG-HEPTANE
WORKING-HEX ANE
WOftKIHG-l SOOCTANE
WOHKING-1SUPENT
WORKING-fENTANE
WORKING-TOLUENE
SIANO STG-GASOLN
WORKING-PRODUCT
STAND S1G-CRUOE
WORKING-CRUDE
STANC SfG-JETFUEL
STAND STG-KEROSNE
STAND STG-OIST FL
STAND STG-BENZENE
STAND STG-CYCLHEX
STANC STG-CYCLPEN
STA.NO STG-HEPTANE
STAND STG-HEXANE
STAND STG-ISOGCTN
STAND STG-ISOPENT
STANC STC— PENTANE
STAND STG-TOLUENE
KORKINC-GASOLIhE
WORKINfc-JtT FUEL
W08K-ING-KEROSENE
KORKING-OIST FUEL
WORK ING-BENZENE
HURKING-CrCLOHEX
WORKING-CYCLOPENT
WORKING-HEPTANE
WORKING-HEXANE
WORK ING- I SOOCTANE
WORKING- ISOPENT
WORKING-PENTANE
WORKING-TOLUENE
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0 040<
1.320.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
a.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
a.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
80. 3
54.8
9.00
7.30
25.2
13.1
13.1
18.3
20.8
58.4
11.3
32.1
13.9
142.
94.9
5.84
2.40
1.00
1.00
2.00
2.30
6.40
1.20
3.60
1.50
15.7
10.6
0.64
12.0
0.
10.6
0.
4.38
1.90
1.90
2. TO
3.0)
8.76
1.64
4.75
2.01
20.8
13.9
0.88
10.2
2.30
1.00
1.00
2.30
2.60
7.20
1.40
4.00
1.70
17.8
12.0
0.73
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0 •
0.
0.
0.
0.
0.
0 •
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
0.
e.
0.
0.
0.
0.
TONS
TONS
TONS
TONS
TONS
toss
1000
1000
1000
1000
loac
10'JO
i noo
1000
1000
moo
1000
1000
1000
moo
10!>0
ic oo
1000
1000
1000
1000
1000
1000
1010
1000
1000
1 UC'O
1000
IOOO
1100
lOOC
1030
I COO
lOOJ
l?OD
IOOO
lO'.'O
IOOO
1 1 00
IOOO
loco
loco
1000
1000
1000
1000
1000
moo
1000
1000
IOOO
1000
1000
1000
1000
1000
1000
COATING
COATING
COATING
COATING
COATING
COATING
GALLONS
GUI. cms
GALLONS
GALLONS
CALLOUS
GALLONS
CALL INS
GALLONS
GALLONS
CALt llNS
GALL ONS
GALLONS
GALLONS
GALLONS
''.ALLDNS
r,«i IONS
GALLONS
GAI LONS
CAt.LiiNS
GALLONS
T.ALLUNS
GALLONS
GALLONS
GALLONS
GALLONS
GALLONS
GALLONS
GALLONS
GALLONS
G ALL TNS
GAILONS
GALLONS
GALLONS
GALLONS
GALLONS
GALLONS
GALLONS
GALLONS
GALLONS
GALL'JNS
GALLONS
GALLONS
GALLONS
GALLONS
GALLONS
GAI LONS
GALLONS
GALLONS
GALLONS
GALLONS
GALLONS
GALLONS
GALLONS
GALLONS
GALLONS
STORAGE CAPICI"
.^U';"PI|-
THROUGHPUT
fTC^AGE CAFiCUr
ST^PAG1; C(PAC!TV
ST'Jr'AGr CAPACITY
ST'i'QAGG CJPACITV
STC^AGE CAPACITY
STOP AGF. CAPACI i *
STORAGE CAPACITY
STCHAGF. CAOaclT»
STCJRAGE CAPAC | TY
STORAGE CAPACITY
bT'JPAGF. CAPACITY
THRC*JGHPUT
THOTtlGHOUT
THf-(7JGHPt)T
THKOUOHP'JT
T HP^'Jf,MPt|T
TMPOUGHPUT
THROUGHPUT
THROUGHPUT
THROUGHPUT
THBOUGHPIJT
THROUGHPUT
THCOUGHPUT
THROUGHPUT
OTHER/NOT CLASIFO
4-03-999-99 SPECIFY IN REMARK
1000 GAI STORED
-10-
-------
AMC7010.T0108F-FCR
5.0 SOURCE TESTING FOR HYDROCARBON CLASSIFICATION
To verify the use of published information and to examine sources where
information is not readily available it was necessary to perform source testing.
A method was developed which would easily measure methane and non-methane hydro-
carbons over a wide range of concentrations. The method is discussed in
greater detail in Appendix II.
The procedure is applicable for testing hydrocarbon sources which range
from a few parts per million to several thousand parts per million. Since only
methane and total hydrocarbons are being determined the results are expressed
as parts per million carbon atoms. The developed method is linear with respect
to carbon number, thus providing a good means of comparison for sources of
differing composition.
The method was used for analyzing samples taken at a petroleum refinery,
a can manufacturer, and a paint line and oven at an auto assembly plant. As
expected, the methane from these sources was very low to negligible with the
exception of the can plant. From the can plant half of the hydrocarbons
measured were methane. This result is unexpected; the source of methane is
probably unburned natural gas in the ovens sampled. The results of these tests
are discussed in further detail in Appendix III.
Prior to developing the method for methane and non-methane analysis some
preliminary investigations were made to find a method for further separating
(4)
reactive and non-reactive hydrocarbons. Groth and Zaccardi ' reported on a
subtractive analyzer system which separated hydrocarbons into two categories
- reactive and non-reactive, where the non-reactive hydrocarbons were princi-
pally paraffins. Klosterman and Siqsby^ ' developed a subtractive method for
separating automotive emissions into paraffins, olefins and acetylenes, and
(4) Groth, Richard H. and Vincent A. Zaccardi, "Development of a High-
Temperature Subtractive Analyzer for Hydrocarbons", J.A.P.C.A., Vol. 22,
No. 9, September 1972.
(5) Klosterman, D.L. and J. F. Slgsby, Jr., "Application of Subtractive
Techniques to the Analysis of Automotive Exhaust", Environmental Science
and Technology, Vol. 1, No. 4, April 1967.
-11-
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AMC7010.T0108F-FCR
aromatics. Both of these reports deal with scrubbing systems using sulfuric
acid and mercury and palladium sulfates on some support medium. Should further
analysis of hydrocarbon emissions in St. Louis be desired, an adaptation of
these two methods would probably be used. The analysis method developed under
this Task for methane and non-methane could be easily altered to add a
scrubbing system for more detailed analysis.
-12-
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AMC7010.T0108F-FCR
APPENDIX I
SOURCE CLASSIFICATION CODE (SCC) LISTING VERSUS PERCENTAGE
CLASSIFICATION OF METHANE AND NON-METHANE HYDROCARBONS
-13-
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AMC7010.T0108F-FCR
SOURCE CLASSIFICATION CODE LISTING WITH METHANE,
NON-METHANE BREAKDOWN*
Hydrocarbons
SCC Number
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
*Note:
01 002 01
01 002 02
01 002 03
01 002 08
01 004 01
01 004 07
01 005 01
01 005 02
01 006 01
01 006 02
02 002 02
02 002 04
02 002 05
02 002 06
02 002 08
02 002 09
02 002 12
02 004 01
02 004 02
02 004 03
02 005 02
02 006 01
02 006 02
02 006 02
02 007 01
02 007 08
03 002 09
03 002 13
03 004 01
03 004 02
03 005 02
03 006 01
Only SCC codes
located in the
Methane, %
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
78
are listed for which
St. Louis AQCR.
-14-
Non-Methane, %
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
22
there are hydrocarbon emission
-------
AMC7010.T0108F-FCR
SCC Number
1 03 006 02
2 01 001 01
2 01 002 01
3 03 003 01
3 06 001 02
3 06 001 03
3 06 001 04
3 06 001 07
3 06 001 08
3 06 001 09
3 06 002 01*
3 06 009 99
3 09 002 01
3 90 004 08
3 90 004 30
3 90 004 99
3 90 006 05
3 90 006 08
3 90 006 30
3 90 006 99
4 02 004 01
4 02 005 01
4 03 001 01
4 03 001 03
4 03 001 07
4 03 001 52
4 03 002 01
4 06 001 26
4 06 002 01
5 01 001 01
*Source Test Data used to determine breakdown
Methane,
78
78
78
0
78
78
78
78
78
78
20
78
78
78
78
78
78
78
78
78
2
2
2
2
2
2
2
2
2
78
Hydrocarbons
% Non -Methane, %
22
22
22
100
22
22
22
22
22
22
80
22
22
22
22
22
22
22
22
22
98
98
98
98
98
98
98
98
98
22
-15-
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AMC7010.T0108F-FCR
APPENDIX II
CHROMATOGRAPHIC METHOD FOR SEPARATION OF METHANE
AND NON-METHANE HYDROCARBONS
-16-
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AMC7010.T0108F-FCR
TABLE OF CONTENTS
PAGE
1.0 INTRODUCTION . 20
2.0 SUMMARY 21
3.0 SYSTEM DESIGN 22
4.0 TOTAL HYDROCARBON ANALYSIS 25
4.1 ANALYSIS PROCEDURE 25
4.2 REPRODUCIBILITY OF ANALYSIS 25
4.3 LINEARITY WITH RESPECT TO CARBON NUMBER 27
4.4 LINEARITY WITH RESPECT TO CONCENTRATION AND LIMITS
OF DETECTION 31
4.5 EFFECT OF OXYGEN IN THC ANALYSIS 35
4.6 PREPARATION OF STANDARDS 35
4.7 BAG DIFFUSION 37
5.0 METHANE ANALYSIS 38
5.1 ANALYSIS PROCEDURE 38
5.2 REPRODUCIBILITY OF ANALYSES 38
5.3 LINEARITY OF CONCENTRATION 38
5.4 INTERFERENCE OF METHANE ANALYSES 39
5.5 PREPARATION OF STANDARDS 39
5.6 BAG DIFFUSION 39
-17-
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AMC7010.T0108F-FCR
TABLES
PAGE
TABLE 1 CONCENTRATION AND DETECTION LIMITS 28
-18-
-------
AMC7010.T0108F-FCR
FIGURES
FIGURE 1 SYSTEM DESIGN
FIGURE 2 REPRODUCIBILITY OF RESULTS, CHROMATOGRAM
FIGURE 3 CHROMATOGRAM OF BUTANE VERSUS METHANE, UN-MODIFIED (FID)
FIGURE 4 CHROMATOGRAM OF BUTANE VERSUS METHANE, MODIFIED (FID)
FIGURE 5 CHROMATOGRAM OF TOLUENE VERSUS METHANE, UN-MODIFIED (FID)
CARRIER FLOW
FIGURE 6 CHROMATOGRAM OF TOLUENE VERSUS METHANE, MODIFIED AIR
CARRIER FLOW
FIGURE 7 GRAPH OF CARBON NUMBER LINEARITY
FIGURE 8 OXYGEN EFFECT IN SAMPLE ANALYSIS
FIGURE 9 REPRODUCIBILITY OF METHANE ANALYSIS
FIGURE 10 GRAPH OF METHANE CONCENTRATION VERSUS PEAK HEIGHT
FIGURE 11 CHROMATOGRAM OF METHANE AND ETHANE
PAGE
23
26
29
30
32
33
34
36
40
41
42
-19-
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AMC7010.T0108F-FCR
1.0 INTRODUCTION
In compliance with Task F of Task Order 108, a method was developed to
analyze stack samples for methane and total hydrocarbons at expected stack con-
centrations (10 ppm to Ippm). It was important that the analysis be rapid
(<15 minutes per complete analysis), reproducible, linear with respect to car-
bon number, linear with respect to concentration, and that the instrumentation
remain a stable, maintenance-free system. It was also important that, should
it later become necessary, stack sample analysis could be further divided into
reactive, non-reactive, or individual hydrocarbon constituents. With these
considerations the following analytical system was developed.
-20-
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AMC7010.T0108F-FCR
2.0 SUMMARY
Using a Gow-Mac series 750 gas chromatograph (G.C.), fitted with a flame
ionization detector (FID), an analysis system for methane and non-methane
hydrocarbons in stack samples was designed. This system, upon modification
proved to be linear with respect to carbon number and hydrocarbon concentra-
3
tion up to the level of 3.5 x 10 ppm per carbon number. Normally total
hydrocarbons are not linear with respect to carbon number, as increasingly
heavier hydrocarbons burn less efficiently. Modification to the Gow-Mac
750 G.C. produced a very efficient combustion flame, which resulted in a
linear response.
A mode-select valve is used to change from the methane to the non-methane
mode. Should further breakdown of hydrocarbons be required, selective scrubbers
and/or different analytical columns could be installed.
All results were read on a Linear Instruments chart recorder attached to
the Gow-Mac electrometer. All results are reported in peak height, which is
linear with respect to hydrocarbon concentration.
Teflon bags were found to be both suitable for sampling and preparation of
standards within acceptable levels of error (-3%).
-21T
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AMC7010.T0108F-FCR
3.0 SYSTEM DESIGN
As previously mentioned, modifications to the Gow-Mac 750 G.C. were
necessary to insure accurate and meaningful results for methane and total
hydrocarbon analyses. All modifications may be seen in Figure 1.
The final operating parameters are as follows: The gases needed to maintain
a flame for the FID are oxygen (Linde hydrocarbon free) and hydrogen (Linde
ultra high purity). Both gases were passed from their respective cylinders by
single stage regulators, through particulate filters, and flow restrictive
capillaries [0.025 cm (0.01 in.) ID]. Parameters for oxygen flow were 0.70
2
kg/cm (10 psi) across 0.61 m (2 ft.) of capillary tubing to produce a flow
2
of 40 ml/min. Those for hydrogen are 3.5 kg/cm (50 Ibs.) across 3.0 m
(10 ft.) of capillary to produce a flow of 30 ml/min. Air (Linde hydrocarbon
free) is used to sweep the sample through the analytical system. An outlet
2
pressure of 3.5 kg/cm (50 psi) across a particulate filter and a flow control
valve, produces a total flow across two capillaries of 50 ml/min. A shorter
capillary (0.305 m - 1 ft.) was used to supply a constant air supply to the
FID to aid in flame combustion. The longer (0.61 m) capillary is used to
lessen the flow transients when the inject valve is activated.
The changing of the mode valve (Figure 1) allowed a 50-200 mesh activated
charcoal column .32 x 61 cm (1/8" x 2 ft.) to be placed in series with the
61 m capillary column. This charcoal column was used to separate methane
from other hydrocarbons.
The inject-load valve was used to sweep a sample from a 0.1 ml sample loop.
In the load position a vacuum pump continuously draws a sample through the
sample loop. When placed in the inject position, the sample in the sample
loop is forced either through the charcoal column and the .61 m capillary
(methane analysis), or directly through the .61 m capillary to the detector
(total hydrocarbon analysis).
The entire equipment enclosed in the area marked oven (Figure 1) was kept
at 100°C to insure that no hydrocarbons condensed in any part of the analytical
system. The detector was maintained at 125°C to insure no sample condensation
did occur in the detector.
-22-
-------
n
FID
CO
I
THC
----- CH, MODE
ftlMQQOCP
.61m
3~?
0
£
o
EXPLANATION OF SYMBOLS
B PARTICULATE FILTER
NEEDLE VALVE
CAPILLARY
CHARCOAL
-COLUMN
Q O
RAS CYLINDER
WITH REGULATOR
FIGURE 1
SYSTEM DESIGN
o
>vj
o
o
o
73
-------
AMC7010.T0108F-FCR
All plumbing and Swagelok fittings were stainless steel. The injection
load and mode select valves were both Carle valves fitted with Teflon seats.
All plumbing parts were washed with acetone to remove any contaminates which
could cause interferences.
While this system was not designed to do any analyses other than methane
and non-methane, a further breakdown of total hydrocarbons could be accomplished
by adding selective scrubbers to the sample inlet line, prior to the sample
loop. This method could be used to break hydrocarbon classification down
to reactive and non-reactive hydrocarbons; reactive hydrocarbons being
defined as unsaturates, excluding acetylene, and aromatics, excluding benzene.
Should specific analyses of hydrocarbons be required, replacement of the
activated charcoal column with a different type of column could result in
a specific hydrocarbon analysis.
-24-
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AMC7010.T0108F-FCR
4.0 TOTAL HYDROCARBON ANALYSIS
This section describes the methods, difficulties, interferents, and
their removal, concerning the analysis for total hydrocarbons. To the writers'
knowledge, an accurate measure of total hydrocarbons has never before been
performed. In the past, instruments have been able to measure total hydro-
carbons accurately only when the entire sample was composed only of methane.
These analyses were also highly susceptible to oxygen content in the sample.
With the method developed under this Task Order, total hydrocarbons can
be measured accurately to the concentration of their carbon number, and
with no interference from the oxygen content in the sample.
4.1 ANALYSIS PROCEDURE
To commence an analysis for total hydrocarbons, a sample or standard is
attached to the sample inlet line of the G.C. and the sample vacuum pump
switched on (see Figure 1). With the inject-load valve in the load position
and the mode select valve in the THC position, the sample loop is filled with
sample, as air (Linde hydrocarbon-free) is injected into the FID. This air
is used to aid in combustion at the FID and to sweep the sample loop when the
inject-load valve is turned to the inject position. Approximately 5.5 seconds
after injection, a THC peak occurs as hydrocarbons from the sample loop are
burned. The inject valve should remain in the inject position until the entire
THC peak has returned to base line. This allows the entire sample loop to be
purged into the FID. By returning the inject-load valve to the load position,
a new sample is loaded into the sample loop in preparation for a new analysis.
The results are determined by peak height, read directly on a chart
recorder attached to the G.C. electrometer (Figure 2).
4.2 REPRODUCIBILITY OF ANALYSES
Numerous checks were performed to insure reproducibility of analyses.
Figure 2 indicates that a 1600 ppm methane sample provided peaks with identical
heights for more than one analysis.
-25-
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AMC7010.T0108F-FCR
. . .
' "
' ._
"
"""
•
"9
o
1
1
1
1
. I :
1
" r
„ _ _p.
•"1
FIGURE 2
REPRODUCIBILITY OF RESULTS, CHROMATOGRAM
-26-
-------
AMC7010.T0108F-FCR
Additional samples containing varying amounts of m-xylene, toluene,
butane, and methane, all showed reproducibility over short periods of time.
With the exception of methane (Table 1), reproducibility was not attainable
over extended periods (>1 hr.) due to bag diffusion. It was found if the
inject-load valve held in the inject position for less than 5 seconds, all
of the hydrocarbons were not swept from the sample loop. This produced
varying hydrocarbon peak heights. A guideline, as mentioned previously, is
for valve activation until the THC peak returns to baseline.
4.3 LINEARITY WITH RESPECT TO CARBON NUMBER
A meaningful response of a THC analyzer can be attained only if all of
the hydrocarbons entering the FID are completely burned. When such is the
case, the output response is linear with respect to carbon number. If such
were not the case, different hydrocarbons would give different responses for
the same concentration per carbon number. Ideally, 100 ppm butane would give
the same response as 400 ppm methane, 100 ppm benzene as 600 ppm methane, and
100 ppm acetylene as 200 ppm methane. The amount of response would continue
to be a function of concentration and carbon number for all hydrocarbons.
Initially the Gow-Mac 750 G.C. was set at the manufacturer's recommended
settings of 30 ml/min H^, 450 ml/min burner air, and 30 ml/min air carrier.
The results for a 100 ppm butane sample produced less than the sample response
for 400 ppm methane (Figure 3). As the mechanics for hydrocarbon burning
involved in the carrying of current from the electrically positive flame to
a negative collector are:
CH + 0 -> CHO+ + e"
it was felt that increasing the oxygen supply would aid in combustion. Figure
4 gives an example after oxygen had replaced air as a burner support gas.
This enables the butane to be burned completely, giving a linear response with
respect to carbon number. The burner oxygen rate was initially set at 40 ml/min,
To insure that the complete burning of butane could be applied also to
other hydrocarbons, a second hydrocarbon was chosen to test. Toluene was
-27-
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AMC7010.T0108F-FCR
TABLE 1
CONCENTRATION AND DETECTION LIMITS
CONCENTRATION
1000 ppm Toluene
526 ppm Toluene
200 ppm Toluene
100 ppm Toluene
700 ppm Methane
RANGE AND
ATTENUATION
10-10 x 8
10"10 x 8
10"10 x 8
10'10 x 4
10-"10 x 4
INITIAL
RESULT
(mm)
72.0
46.0
18.5
18.0
18.5
FINAL RESULT
AFTER 18 MRS.
(mm)
67.0
43.0
17.0
16.0
18.5
% DECREASE
7.5%
7.0%
8.8%
12.5%
0.0%
-28-
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AMC7010.T0108F-FCR
ro
L
__(.
__._,... _J
en
«•
oa,
FTP
2t
tx.uir
f
FIGURE 3
CHROMATOGRAM OF BUTANE VERSUS METHANE, UN-MODIFIED (FID)
-29-
-------
AMC7010.T0108F-FCR
FIGURE 4
CHROMATOGRAM OF BUTANE VERSUS METHANE, MODIFIED (FID)
-30-
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AMC7010.T0108F-FCR
selected as it is a hydrocarbon likely to be encountered in future sampling,
and it is a difficult hydrocarbon to burn completely. If this aromatic com-
pound should prove linear with carbon number, it could be assumed that any other
hydrocarbon would be completely burned in a FID. Figure 5 indicates that
100 ppm toluene gave 10% less response than 700 ppm methane. This indicates
that not all of the toluene is being burned completely. The hydrogen and
oxygen gases used for the FID were adjusted both upward and downward from 30
ml/min and 40 ml/min respectively. No adjustment in oxygen or hydrogen helped
in giving the desired equal results for equal carbon number concentration
amounts of methane and toluene.
The one remaining parameter which could be modified in an attempt to attain
100% combustion of toluene was the carrier air. When the carrier air was in-
creased from 30 ml/min to 40 ml/min, 100 ppm toluene gave the same response as
700 ppm methane. Further increases in carrier air eventually resulted in flame
blow out at 70 ml/min. 50 ml/min was finally settled upon as an ideal flow
rate to insure complete combustion and a stable flame. Figure 6 shows equal
responses for 100 ppm toluene and 700 ppm methane. Additional experiments
using various concentrations of toluene versus methane showed a continued
linear response with respect to carbon number. Tests performed with m-x.ylene
and methane also showed the complete combustion of m-xylene under the given
operating parameters.
As a possible explanation of the above results, it is suggested that the
replacement of burner air with oxygen greatly facilitated the formation of
the CHO radical needed to give a hydrocarbon response. Nitrogen molecules
no longer interfered with the contact of oxygen and carbon atoms needed to
form CHO . The added oxygen from the air carrier plus the increase in flame
turbulence at higher flow rates would seem to enhance CHO formation. These
two factors have enabled a totally efficient combustion to be produced.
4.4 LINEARITY WITH RESPECT TO CONCENTRATION AND LIMITS OF DETECTION
Toluene was used to prepare a wide range of standards to determine if the
FID output was linear. Figure 7 shows a graph of concentrations plotted
against peak height. As may be seen, the instrument is linear with respect
-31-
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AMC7010.T0108F-FCR
FIGURE 5
CHROMATOGRAM OF TOLUENE VERSUS METHANE, UN-MODIFIED CARRIER FLOW
-32-
-------
AMC7010.T0108F-FCR
T r~T
FIGURE 6
CHROMATOGRAM OF TOLUENE VERSUS METHANE, MODIFIED AIR CARRIER FLOW
-33-
-------
AMC7010.T0108F-FCR
O
o
o
tr
I
I
w
-------
AMC7010.T0108F-FCR
3
to concentration up to 3.5 x 10' ppm carbon number. It would appear that
at this point detector saturation begins to occur. When a larger sample loop
3
was inserted to replace the 0.1 cm loop, detector saturation occurred at a
much lower concentration. The 0.1 cm' sample loop does have limitations that
larger loops do not. The lower detection limit for a 0.1 cm sample loop is
3
1 ppm per carbon number, while a 1.0 cm loop has a lower detection limit of
0.1 ppm per carbon number.
The 0.1 cm sample loop is the smallest that can be used on the Gow-Mac
750. Should hydrocarbon concentrations exceed 3.5 x 10 ppm per carbon
number, the only accurate method to analyze a sample would be sample dilution.
This would entail using a known volume of pure air and a syringe injected
volume of sample gas By knowing the resulting peak height and the amount of
sample dilution, an accurate result could be obtained for the sample even if
3
it exceeded 3.5 x 10 ppm per carbon number.
4.5 EFFECT OF OXYGEN IN THC ANALYSIS
From work performed in the RAMS network, it is known that THC results are
a function of the percent oxygen in the sample being analyzed. Samples that
are rich in oxygen (relative to the air carrier) give erroneously high readings,
and those deficient in oxygen give results that are erroneously low. These
results were obtained for the Gow-Mac 750 prior to the use of oxygen to support
combustion and the proper adjustment of the air carrier.
The results of an experiment to show whether the Gow-Mac was still
susceptible to sample oxygen content is shown in Figure 8. The gases used
are Scott ultra pure air, which has an oxygen content of 19%, and U.S. Bureau
of Mines helium which has no oxygen content. At a very sensitive instrument
attenuation and range, no difference in result can be seen. Irregularities
in the chromatograph are caused by pressure surges due to sample injections.
4.6 PREPARATION OF STANDARDS
Standards were prepared in leak tested 5 mil Teflon bags. These bags were
purged with high-purity helium (NBM) and evacuated orior to use. A bag was
then filled with a desired volume of pure air (Linde zero grade) using a
-35-
-------
AMC7010.T0108F-FCR
—t H
FIGURE 8
OXYGEN EFFECT IN SAMPLE ANALYSIS
-36-
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AMC7010.T0108F-FCR
mass-flow meter. All precautions were taken to insure that no leaks were
present on filling. While Linde zero air is not totally free of hydrocarbons,
the amount is less than 1 ppm THC and 0.1 x 10 ppm methane. These concen-
trations are below the lower detection limits of the instrument. The filled
Teflon bag was then injected through a silicone septum with a known amount
of hydrocarbon using a precision syringe to attain the desired concentration.
Hydrocarbon concentration should be presented in terms of ppm of carbon.
number. This may be determined by knowing the type and amount of hydrocarbon
injected into the standard bag and multiplying this concentration by its
number of carbon atoms per molecule. 2x16 ppm m-xylene would be expressed
as: 2x8=16 ppm of carbon number. The 10~ ppm per carbon number is
identical to the more common total hydrocarbon term, "ppm expressed as methane".
4.7 BAG DIFFUSION
Tests were performed using various amounts of toluene and methane to
determine if and at what rate these compounds permeate through Teflon bags.
The results are shown in Table 1. These results are in agreement with
the findings of T.O. 103 concerning bag diffusion; that heavier hydrocarbons
permeate faster than lighter ones. As all bag samples will be collected and
analyzed within 6 hrs., the expected error would be less than 3% of the total
concentration. This amount of error is acceptable for this type of analysis
for high hydrocarbon concentrations.
-37-
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AMC7010.T0108F-FCR
5.0 METHANE ANALYSIS
The following concerns the analysis of methane in stack samples.
This type of analysis is very simple and has been performed using many
different types of analytical procedures. The method mentioned in this report
o
is capable of methane analysis from 1 ppm to 5.0 x 10° ppm. This is well
within any level likely to be encountered in stack samples.
5.1 ANALYSIS PROCEDURE
To commence an analysis for methane, a sample or standard is attached
to the sample inlet line of the G.C. and the sample vacuum pump switched
on (See Figure 1). With the inject-load valve in the load position and the
mode select valve in the methane position, the sample loop is filled with
sample as air (Linde hydrocarbon free) is injected into the FID. This air
is used to sweep the sample loop when the inject-load valve is turned to the
inject position. Approximately two minutes after sample injection occurs,
a methane peak occurs as methane from the sample loop is burned. The inject
valve should remain in the inject position for 15 seconds to insure that
all of the sample in the sample loop has been swept into the analytical
column. By returning the inject-load valve to the load position, a new
sample is loaded into the sample loop in preparation for a new analysis.
The results are determined by peak height, read directly on a chart
recorder attached to the G.C. electrometer.
5.2 REPRODUCIBILITY OF ANALYSES
Figure 9 shows a chromatogram of three injections of 200 ppm methane.
All injections had the same peak heights. The results of methane chromato-
grams over an 18 hour period indicate that the methane analyses are totally
reproducible.
5.3 LINEARITY OF CONCENTRATION
Linearity checks were performed using various concentrations of methane.
-38-
-------
AMC7010.T0108F-FCR
Up to the level of 5.0 x 10 ppm, no detector saturation was seen (Figure
10). As methane would never likely be seen at concentrations close to this
figure, no attempt was made to determine at what level detector saturation
for methane would occur.
5.4 INTERFERENCE OF METHANE ANALYSES
Activated charcoal was chosen as a chromatographic column for the
analysis of methane because it has a very poor retention of methane with
an excellent retention of other hydrocarbons. The hydrocarbon with the
poorest retention next to methane is ethane. It was felt that if proper
resolution of ethane from methane could be attained, no other hydrocarbon
would interfere with methane resolution. Figure 11 is a chromatogram of
a spike amount of ethane versus 30 ppm methane. The chromatogram shows that
ethane elutes at 20 min. with a very broad peak, compared with the sharp
methane peak at 2 min. Thus, no interference from ethane or any other hy-
drocarbon will occur.
5.5 PREPARATION OF STANDARDS
Standards were prepared as in Section 3.8, with the exception that
the only hydrocarbon used is methane.
5.6 BAG DIFFUSION
See Section 3.9 and Table 1.
-39-
-------
AMC7010.T0108F-FCR
FIGURE 9
REPRODUCIBILITY OF METHANE ANALYSIS
-40-
-------
AMC7010.T0108F-.FCR
o
o
'"N
i
.^
«
<^
, . . . . • i , ' • •_
?000
FIGURE 10
GRAPH OF METHANE CONCENTRATION VERSUS PEAK HEIGHT
-41-
-------
ro
i
FIGURE 11
CHROMATOGRAM OF METHANE AND ETHANE
o
•yo
-------
AMC7010.T0108F-FCR
APPENDIX III
HYDROCARBON SOURCE TESTS
-43-
-------
AMC7010.T0108F-FCR
TABLES
PAGE
TABLE 1 HYDROCARBON ANALYSES 45
TABLE 2 HYDROCARBON ANALYSES 45
-44-
-------
AMC7010.T0108F-FCR
Source tests for hydrocarbons were conducted at three sites. These sources
were an oil refinery, a can manufacturer, and an automotive assembly plant.
Prior to this, source tests have been conducted at several combustion sources
at which time a hydrocarbon analysis was made. Table 1 gives the results of
these previous tests.
TABLE 1
HYDROCARBON ANALYSES
Source
111. Power - Wood River #1
General Motors #2
Amoco Oil - Boiler #5
- Cat. Cracker
Fuel
qas
oil
oil
coal
oil/qas
Hydrocarbons, ppm
Methane Total HC, as
0.85
0.6
0.6
0.23
0.25
1.07
0.1
^
1.9
1.6
2.1
1.31
2.30
3.28
2.5
The samples from the sources in Table 1 were taken in Teflon bags and returned
to the lab for analysis on a Beckman Model 6800 Gas Chromatograph.
The tests conducted were performed after the development of the classifi-
cation method discussed in Appendix II. These samples were withdrawn with a
metal diaphragm pump into a 5 mil thick Teflon bag. Analysis was performed on
a Gow-Mac Model 750 gas Chromatograph. The results of these tests are given
in Table 2.
TABLE 2
HYDROCARBON ANALYSES
Source
Hydrocarbons, ppm
Methane Total HC, as
Amoco Oil - Premium Gas Storage
- Standard Gas Sample
- Crude Oil Sample
Lianco Can Co. - Coating Oven
- Coating Oven with fume incinerator
General Motors -
Paint Oven
Paint Line, Zone 5
Paint Line, Zone 4
Paint Line, Zone 3
1
nil
nil
1504
39
9
8
6
11
1274
--
--
3336
76
114
128
473
559
-45-
-------
JANUARY, 1976 SC553.T054 FR
REGIONAL AIR POLLUTION STUDY (RAPS)
FINAL REPORT
NON-CRITERIA POLLUTANT INVENTORY
FOR THE ST. LOUIS AQCR
CONTRACT NO. 68-02-1081 - G.O. No. 553
Prepared For
Environmental Protection Agency
Office of Air and Water Management
Office of Air Quality Planning and Standards
Research Triangle Park, N.C. 27711
Prepared by
Fred E. Littman
Harry H. Wang
John Pi ere
Air Monitoring Center
Rockwell International
11640 Administration Dr.
Creve Coeur, Missouri 63141
-------
SC553.T054 FR
TABLE OF CONTENTS
1.0 INTRODUCTION
2.0 SCOPE OF THE NON-CRITERIA INVENTORY
3.0 APPROACH AND METHODOLOGY
4.0 DATA HANDLING
5.0 REPRESENTATIVE EMISSION INVENTORIES
6.0 SUMMARY AND CONCLUSIONS
7.0 REFERENCES
APPENDIX I
APPENDIX II
PAGE
1
2
3
8
10
13
14
-------
TABLES
SC553.T054 FR
PAGE
TABLE 1 NATIONAL EMISSIONS DATA SYSTEM (NEDS)
SOURCE CLASSIFICATION CODE (SCC) REPORT
TABLE 2 EMISSION FACTORS
4
5
TABLE 3 NATIONAL EMISSION DATA SYSTEM POINT SOURCE
LISTING
TABLE 4 EMISSION INVENTORY FOR SELECTED COMPOUNDS
FOR AQCR 70
11
-11-
-------
-m-
SC553.T054 FR
FIGURES .
PAGE
FIGURE 1 EXAMPLE OF CODING SHEET 9
-------
SC553.T054 FR
1.0 INTRODUCTION "
The "Clean Air" Act of 1970, as amended, establishes the achievement of
clean air as a national goal. In pursuance of this goal, Air Quality Criteria
were developed and Air Quality Standards established for five pollutants:
sulfur dioxide, carbon monoxide, particulate materials, hydrocarbons and oxidants.
These pollutants are frequently termed "criteria pollutants". -•
It is well known, however, that a large number of other substances occur
in polluted air, some of which have known toxic or carcenogenic properties, such
as mercury, asbestos or beryllium. The Clean Air Act requires the Administrator
to consider other pollutants and to determine whether they are hazardous. Such
a determination is conditioned on the magnitude of the health and welfare effect;
it, in turn, is a function of the occurrence of the pollutant as well as its'
intrinsic toxicity.
Thus, one input into these considerations is an assessment of the sources
of such pollutants, as well as the pollution burden they create. For this reason,
a series of studies has been performed for the Environmental Protection Agency,
which were issued under the general heading of "National Inventory of Sources
and Emissions". (*) In this series, some 21 compounds were examined, and
emission factors and emission inventories were developed. Though no high degree
of accuracy is claimed for these factors, they can serve as a useful basis for
first approximations of the emissions in a given area. —
In conjunction with the Regional Air Pollution Study (RAPS) being conducted
currently in the St. Louis Air Quality Control Region (AQCR), an inventory of
these "non-criteria" pollutants was assembled.
See page 14 for reference
-1-
-------
SC553.T054 FR
2.0 SCOPE OF THE NON-CRITERIA INVENTORY
The non-criteria inventory is based on the following data:
The National Emissions Data System (NEDS) inventory for the AQCR 70
(St. Louis). This inventory lists some 1300 individual sources. It
is based largely on 1971 and 1972 data.
Emission factors listed in the several reports in the series entitled
"National Inventory of Sources and Emissions", which lists estimated
emission factors for all sources of the 21 compounds discussed. There
is a considerable degree of uncertainty in the values of the emission
factors, and this uncertainty is reflected in the values reported in
this inventory.
The following pollutants are included:
Arsenic Mercury
Asbestos Molybdenum
Barium Nickel
Beryllium Phosphorus
Boron Selenium
Cadmium Silver
Chromium Titanium
Copper Vanadium
Lead Zinc
Magnesium Bap
Manganese
-2-
-------
SC553.T054 FR
3.0 APPROACH AND METHODOLOGY
The starting point for this study was the emission factors listed in
the 21 publications referred to above. These factors are the best available
estimates relating the uses of these materials, from mining to processing
and ultimate consumption or disposal, with their release to the atmosphere.
A discussion of the estimated accuracy of these factors is contained in each
of the reports.
Each emission factor delineated in the reports was assigned one or sev-
eral Source Classification Codes (SCC).?-The SCC is an identification system'
developed for NEDS, upon which the point source hierarchy is structured. Any
plant or process which causes air pollution can be represented by one or sev-
eral SCC numbers. Table 1 shows a typical sample of SCC numbers. The SCC num-
bers consist of four groupings. For example:
Group I - a single digit (3) - designates "industrial processes"
Group II - two digits (03) - designates "primary metals"
Group III - three digits (014) - designates "barium"
Group IV - two digits (03) - designates "driers/calciners";
In addition the base unit upon which the emission factors are.based'is given;
in this case, "tons processed".
Table 2 shows an example of a table of emission factors (for lead) taken
from APTD 1543 "Emission Study of Industrial Sources of Lead Air Pollutants",
with the appropriate SCC codes added. It indicates, for example, that in the
Primary Lead Production, which in NEDS is coded 3-03-010-01 through 3-03-010-
05, an emission of 5 Ibs.of lead per ton of product occurs. Adding the SCC
codes to the information in the "Emission Study" made it possible to determine
which of these sources actually exist in the St. Louis AQCR.
A listing of emission sources for the St. Louis AQCR ordered by SCC codes,
was then obtained from NEDS, and a cross-tabulation prepared, which assigned
to each source category in the region a set of emission factors. These sets
are shown in Appendix I. The emission factors were then transformed to cor-
respond with the production or consumption units which appear in the NEDS
(*) See page 14 for reference j
-3-
-------
SC553.T054 FR
TABLE 1
.NATIONAL EMISSIONS DATA SYSTEM (NEDS)
SOURCE CLASSIFICATION CODE (SCC) REPORT
I
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
i
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
SCC
»••
II
03
03
03
03
03
03
03
03
03
03
0*
04
0*
0*
0*
0*
0*
04
0*
0*
0*
04
04
04
04
04
04
04
04
04
04
04
04
04
04
04
04
04
04
04
04
04
0*
04
04
04
04
04
04
Ok
ID
* ••
III
014
014
030
030
030
030
030
030
030
999
001
001
001
001
001
001
001
001
001
002
003
002
002
002
002
002
003
003
001
003
003
003
003
004
004
004
004
004
00*
005
005
00ft
00<>
007
007
007
007
007
007
OOH
IV
03
99
01
02
03
04
05
06
99
99
01
02
03
04
10
11
20
50
99
01
02
03
04
05
06
99
01
na
03
05
30
40
99
01
02
03
04
01
99
01
99
01
99
01
02
03
04
05
99
01
I
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
INDUSTRIAL
SCC CATEGORY NAMES
II
RROCtSI PRIMARY METALS
PHOCESIPR1MARY METALS
PROCESIPRIMARr METALS
PROCESIPRIMAHY METALS
PHOCESIPRIMARY METALS
PBOCESIPRIMARY MtTALS
PHOCESIPWIMARY MfTALS
FWOCESIPRIMAHr MtTALS
PROCESIPR1HAHY MtTALS
PROCESIPRIMAHY METALS
PROCESISECONOARY METALS
PROCESISECONOARY METALS
PROCESISECONOARY "FTALS
pRoctsiSEcONOAWY METALS
PROCESIStCONUAHY METALS
PROCESI SECONDARY METALS
PROCESISECONOARY M£TALS
PkOCESISECONOaRY METALS
PP.OCES I SECONDARY MtTALS
PROCESISECONDAKY MFTALS
PROCESI SECONDARY wFTAL-S
PROCESISECONOARY MtTALS
PROCESISECONOAR/ METALS
PROCESISFCONOAWY MtTALS
PMOCESI SECONDARY MtTALS
pRoctsisFcoNOAiJY METALS
PWOCESISECONOAHY METALS
PROCESISECONOAHY MfTALS
PROCESISECONOARY METALS
PROCESISECONDARY METALS
PROCESISECONOAHY MMALS
PROCESISfCONO-WY METALS
P"OCFSISECONOi-»Y METALS
PHOCESISECONDARY METALS
PROCEbI SECONDARY METALS
PROCESISECONOARY METALS
PROCESISECONJAOY METALS
POOCESIStCONUAMY MtTALS
"RnCEiI SECONDARY MtTlLS
PRnCtSISECONOAWY METALS
PSOCtSISECONUA-IY MtTALS
ARY MtTALS
SECONDLY MtTALS
PROCESIStCONOArtY MtTALS
PHOCEblSECONDAPY METALS
PHOCESISECONOAHY MtTALS
PROCESIStCONUARY MfcT«LS
1-ROCtSISfCONo.lwY CET/.LS
""OCtSIStCONJuWY MtTALS
FKOCESISECONDOHY
III
IBAHIU"
IRARIUM
IZINC SMELTING
IZINC SMELTING
IZINC SMELTING
IZINC SMELTING
IZINC SMELTING
IZINC SMELTING
IZINC SMELTING
IOTMEK/NOT CLASFD
I ALUMINUM OPtaaTN
ULUMINUM OPt"ATN
(ALUMINUM OPt'ATN
(ALUMINUM OPERATN
I ALUMINUM OPEPATN
(ALUMINUM OPE^ATN
(ALUMINUM OPEBATN
lALUMIhU"
(ALUMINUM
UPASS/BRONZ MELT
IHRASS/HCUNZ »ELT
(HRASS/PPONZ "tLI
IHRASS/BRONZ MTLT
IHRASS/BWONZ MELT
IBOASS/RRONZ UELT
(GRAY IPON
ir.RAY IRON
ir.RAY IRON •
I GRAY IRON
(GRAY IRON
(GRAY IHON
IGRAY IRON
ILEAO SMELT SEC
ILEAD SMELT SEC
ILEAD SMELT SEC
(LEAH SMELT SEC
ILEAD SMFLT SEC
ILEAD SMELT bEC
ILEAO BATTERY
ILEAO BATTE-tY
("AGN^StUM SEC
(MAGNESIUM SEC
I5TEEL FPUNOHY
ISTE6L FOUNUfc*
ISTEEL FOUNUWY
I5TEEL FOUNOwY
ISTEEL FOUNDRY
ISTEEl FOUND-"
IZINC SEC
IV
IORIERS/CALCINEHS (TQNi
IOTHES/-.OT CLASFD I TONS
(GENERAL ITONS
IR1ASTNO/MUL t-MHTMlTONS
(SINTERING ITONS
IMORIZ PETONTS ITONS
(VERT RETORTS ITONS
(ELECTROLYTIC PKOCITONS
(OTriER/NOT CLASFD ITONS
(SPECIFY IN REMAHKITONS
IS«EATI'JGFuBSACE ITONS
ISMELT-CRUCIBLt ITONS
(SMELT-REVERB FNC ITONS
ICHLORINATN STiiTN iTONi
IFQIL ROLLING ITUNS
IFOR CONVERTING ITONS
(CAN MANUFACTURE ITONS
IROLL-D»»/>sOT CLAilFOITONs
(POT FUUNACt ITONS
IREVERB FNC ITONS
I BLAST/CUPOLA FNC ITONS
(ROTARY REVERB FNCITONS
ILEAO 0«IOE "FT, ITONS
IOTMER./NOT CLASIFQITONS
(GENERAL ITONS
lOTHEH/NOT CLASIFDITONS
I POT FUKNACF ITONS
IOTMtR/r.OT CLAilFOlTONS
IELECTMIC ARC FNC ITONS
IO>»EN MtARTH FNC ITONS
(OPEN MEAMTH LANCOITOMS
(MtAT-T->EAT FNC (IONS
(INDUCTION FUONACEITONS
IOT^1B/MOT CLASIFQITONS
IRFTQBT FNC ITONS
UNITS
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROnuCEO
PRODUCED
METAL PRODUCED
METtL PRODUCED
METAL PRODUCED
PRODUCT
PRODUCED
PRODUCED
PRODUCED
PRODUCED
CMAfc&E
CMAUGE
CMA-GE
PROOUCtD
METAL CMA-GE
METAL CMAUGE
METoL CMAT.E
METAL CHARGE
PROCESStD
PROCESSED
METAL CHARGE
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
PROCESSED
pR0r>uceo
-4-
-------
TABLE 2
en
Source
Mining & Milling
Metallurgical Industries
Primary Lead Production
Primary Copper Production
Primary Zinc Production
Secondary Lead Production
Lead Oxide Processing
Consumer Product Manufacturing
Storage Batteries
Storage Batteries
Gasoline Additives
Solder
Cable Covering
Type Metal
Brass & Bronze
EMISSION FACTORS
Factor
0.2 Ib/ton lead mined(controlled)
3-03-010-99
5.0 Ib/ton of product(controlled)
3-03-010-01 3-03-010-03 3-03-010-05
3-03-010-02 3-03-010-04
0.6 Ib/ton of Cu concentrates(controlled)
3-03-005-02 3-03-005-04
3-03-005-03
0.3 Ib/ton of Zn concentrates(controlled)
3-03-030-02 3-03-030-04 3-03-030-06
3-03-030-03 3-03-030-05
0.7 Ib/ton of product(controlled)
3-04-004-01 3-04-004-03 3-04-005-01
3-04-004-02 3-04-004-04
0.7 Ib/ton of lead oxide(controlled)
3-04-004-08
3-04-005-01
8.0 Ib/ton of lead processed(uncontrolled)
1.3 Ib/ton of lead processed(controlled)
3-04-005-01
14.0 Ib/ton of lead processed(controlled)
2-02-003-01 2-03-999-98
3.0 Ib/ton of lead processed(controlled)
3-04-999-99
2.0 Ib/ton of lead processed(controlled)
3-04-999-99
17.0 Ib/ton of lead processed(controlled)
. 3-04-999-99
4.0 Ib/ton of lead processed(controlled)
I 3-04-002-02 3-04-002-06 3-04-002-05
Qualifier
Plant visit
Questionnaires
Estimate
Estimate
Questionnaires
Questionnaires
Questionnaires
Questionnaires
Questionnaires
Estimate
Questionnaires
Questionnaires
Questionnaires
o
en
cn
eo
O
en
-------
SC553.T054 FR
printout, as, for example, the source shown in Table 3 which shows the
"Annual Operating Rate" in the lower right hand corner. The final cor-
relation is listed on the tables shown in Appendix II.
-6-
-------
FlLC CREATED ON THURSDAY
17, i'97£
STATEM«I: ILLINOIS iocp(97ri: METROPOLITAN ST. touis
COVNTY(<; |8p) • MONROE CO PLANT 1 0 '. 0001 POIVT ID! 01'
TABLE 3
M*. I. EMISSION DATA SYSTEM _
POINT S 0 I' R C E LISTING
CITYJOOOOI: missive NAME
PAGE 403
SJ -COLUMBIA f}l»Af?RY C0,- VftLMEYER *???•; SICIH22I: ENGAGED IN MIMtNG-0" QUA RRY ING "CftUSME0 -*f»••«««•«,«•«
! STATUS UNKNOV^
f
UTM GRID coo
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STACK pARANE
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STACK HEIGHT; o
STACK OlAnfTcR: 0.0
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PRI.MA°Y PART
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DCSJfiN CAPACITY;
1
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! SOX! 0 TONS/YR !
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I COMPUTER CALCULATED EMISSIONS :
f " PAPT: — "?3 " TONS/YR r
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COMMENTS; . r
-------
SC553.T054 FR
4.0 DATA HANDLING
In order to include the information thus obtained in the RAPS data
base, it was transferred to RAPS coding sheets and from there to a set of
punched cards. A typical coding sheet is shown in Figure 1. ,
For the system to be compatible with the handling procedures developed
for other facets of RAPS, the following information has to be entered for
each source:,
Card 1
State Code
County Code
Plant ID
Plant Name
Street Address
Zip Code
SIC
Ownership Code
Card 2
Stack ID
UTM Zone
DIM Coordinates
Area ID
Temperature
Stack Height
Boiler Design Capacity
Stack Diameter
Flow Rate
Card 3
Control Equipment and Efficiency
for all Criteria Pollutants
Card 4
Point ID
Fuel Heat Content
Sulfur
Ash
Estimation Method
Pollutant
Units
-8-
-------
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SEQUENCE
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1 1
STACK
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ID
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ACK
ID
ACK
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ID
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ACK
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POINT FUEL HEATCONT
ID tl06Btu/SCC(l)
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POIN
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POIN
ID
POIN
ID
POIN
ID
POIN
ID
POIN
ID
0\l
POIN
ID
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DATA
1 1 II 1
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DATA
1 1 1 1 1
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DATA
Mill
r ANNUAL
DATA
1 1 1 1 1
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DATA
1 1 1 1 1
. SULFUR ASH IN ^ POLLUT
IN FUEL %, FUEL, % i-g ,
i i£id i A If I50i
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DATA I •
1 1 1 |7|VU|
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1 1 1 1 1
1
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II 1 III
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1 1 1 II
1 Mill
1 II 1 II
EMISSION FACTOR
L 1 1 1 Mill
II 1 1 II
** A" Md (1) Tons, I03 gal, I06cu.ft.
81196 (Z) Time Interval (A,M,W,D,S,H)
(3) Year, Julian Date (YYDDD)
ANT UNITS Tl(2) START DATE(
i 161 A MAI 7\5\0&\ l
3)
PATTERN
II 1 II
START STOP DATE (3)
HOUR i
1 1 II
PATTERN
1 II 1 M 1 1 1
PATTERN
II II 1 II
PATTERN
II 1 II
PATTERN
III II II
PATTERN
l |l l I 111
1 M 1
Method: 1
2
It
5
6
7
8
i i
1 1 II
1 III
1 1 1
1 1 1 1 II
III II
Emission measurement
. Material balance
Emission factor (AP-42)
, Guess
Special emission factor
. New construction
Fact 1 1 ty c osed
Calculated mass emissions
STOP THERMAL SCC SEQUENCE
HOUR EFF. *j 1 II III IV i
1 1 1 1 1
II 1 II
II 1 M
1 1 1 1 1 1
1 II 1 M 1
1 1 1 II II
1 1 1 II 1 1 1
SEQUENCE
MM
SEQUENCE
1 II 1
SEQUENCE
1 1 1 1
SEQUENCE
1 II 1
SEQUENCE
1 1 J 1
Z
Z
1—
Z
5
*-
Z
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SEQUENCE £
|<|
1 II 1 rVN?
SEQUENCE
1 1 1 1
1
JL
U
p
it
5
5
5
5
5
5
5
Type: 1. Process data
2, Emission data
3, Annual pattern
A, Non-criteria pollutants
S, Heat emissions
5
-------
SC553.T054 FR
Card 4 (Continued)
Time Increment
Start Date
Start Hour
Stop Date
Stop Hour
SCC Number
Card 5
Annual Operating Rate
An emission factor file, consisting of the 19 sets of factors for the
non-criteria pollutants as shown in Appendix II, is also input into the sys-
tem. This file is keyed to SCC numbers. When requested by the output pro-
gram, the computer will calculate the emissions for any pollutant for a giv-
en source by multiplying its annual operating rate by the appropriate fac-
tor. It can also provide the total amount of any one pollutant by area code,
county, state and AQCR. A set of punched cards representing the emission
sources and the emission factor file is submitted with this report. Retrieval
procedures will be described in the forthcoming RAPS Data Handling Users
Manual (EPA )*
*Document number to be assigned.
-10-
-------
SC553.T054. FR
5.0 REPRESENTATIVE EMISSION INVENTORIES
Emission inventories for five compounds were hand-calculated. The
results are shown in Table 4.
-11-
-------
SC553.T054 FR
TABLE 4
Emission Inventory for Selected Compounds for AQCR 70
(Based on 1972 NEDS Data)
Compound
Arsenic
Cadmium
Lead
Mercury
Benz(a)pyrene
Emissions
(Ibs/year)
166,400
270,400
3,234,800
5,600
12,600
-12-
-------
SC553.T054 FR
6.0 SUMMARY AND CONCLUSIONS
An emission inventory of 21 "non-criteria" pollutants for the St. Louis
AQCR has been assembled and formatted for inclusion in the RAPS data base.
The inventory covers some 1300 sources. Information on the contribution
of each source, the sources of any one pollutant, and the total amount of any
pollutant in a given grid square, county, state and AQCR can be obtained from
the memory bank of the Univac computer at EPA-Research Triangle Park. -
-13-
-------
SC553.T054 FR
7.0. REFERENCES •
(1) National Inventory of Sources and Emissions
(2)
Arsenic
Asbestos
Barium
Beryllium
Boron
Cadmi urn
Chromium
Copper
Emission Study
of Industrial
Sources of
Lead Air
Pollutants
Magnesium
Manganese
Mercury
Molybdenum
Nickel
Phosphorus
Selenium
Silver
Titanium
Vanadium
Zinc
APTD-1507
APTD-70
APTD-1140
APTD-1508
APTD-1159
APTD-68
EPA-450/3-74-012
APTD-1129
APTD-1543 -
EPA-450/3-74-010
APTD-1509
APTD-1510
EPA-450/3-74-009
APTD-69
EPA-450/3-74-013
APTD-1130
EPA-450/3-74-011
EPA-450/3-74-008
APTD-1511
APTD-1139
Preferred Standards Path Report for Polycylic
Organic Matter October 1974
Emission Factors for Trace
Substances EPA-450/2-73-001
NEDS Source Classification Codes and Emission Factor Listings
EPA-Office of Air Quality Planning and Standards
Research Triangle Park, July 1974
Guide for Compiling a Comprehensive Emission Inventory
EPA-APTD-1135 (1973)
Compilation of Air Pollutant Emission Factors
EPA-AP42, Appendix C i
-14-
-------
SC553.T054 FR
APPENDIX I
POINT SOURCES (BY SCC CODES)
AND ASSOCIATED SETS OF POLLUTANTS
-15-
-------
SC553.T054 FR'
SCO CODE
1-01-001-02
1-01-002-01
1-01-002-02
1-01-002-03
1-01-002-08
1-01-004-01
1-01-005-01
1-01-005-02
1-01-005-03
1-02-002-01
1-02-002-02
1-02-002-04
1-02-002-08
1-02-002-09
1-02-002-11
1-02-002-12
1-02-002-13
1-02-004-01
1-02-004-02
1-02-004-03
1-02-005-01
1-02-005-02
1-02-005-03
SET!
01
01
01
01
01
02
03
03
03
01
01
01
01
01
01
01
01
02
02
03
03
03
03
COAL (ANTHRACITE)
BITUMINOUS COAL
BITUMINOUS COAL
BITUMINOUS COAL
BITUMINOUS COAL
RESIDUAL OIL
DISTILLATE OIL
DISTILLATE OIL
DISTILLATE OIL
BITUMINOUS COAL
BITUMINOUS COAL
BITUMINOUS COAL
BITUMINOUS COAL
BITUMINOUS COAL
BITUMINOUS COAL
BITUMINOUS COAL
BITUMINOUS COAL
RESIDUAL OIL
RESIDUAL OIL
RESIDUAL OIL
DISTILLATE OIL
DISTILLATE OIL
DISTILLATE OIL
-16-
-------
SC553.T054 FR;
SCO CODE '
1-02-009-02
1-02-009-03
1-03-002-09
1-03-002-13
1-03-004-01
1-03-004-02
1 -03-004-03
1-03-005-02
1-03-005-03
2-01-001-01
2-01-003-01
3-01-014-01
3-01-014-02
3-01-018-99
3-03-003-01
3-03-003-02
3-03-003-03
3-03-003-04
3-03-003-99
3-03-005-99
3-03-008-01
3-03-008-03
3-03-009-03
3-03-009-05
3-03-010-01
SET;.
04
04
01
01
02
02
02
03
03
03
05
06
06
07
08
08
08
08
08
09
10
11
12
13
14
WOOD/BARK WASTE
WOOD/BARK WASTE
BITUMINOUS COAL
BITUMINOUS COAL
RESIDUAL OIL
RESIDUAL OIL
RESIDUAL OIL
DISTILLATE
DISTILLATE
DISTILLATE OIL
DIESEL
PAINT MFG.
PAINT MFG.
PLASTICS
COKE MET. BYPRODUCT
COKE MET. BYPRODUCT
COKE MET. BYPRODUCT
COKE MET. BYPRODUCT
COKE MET. BYPRODUCT
COPPER SMELTING
IRON PRODUCTION
IRON PROD. SINTER
STEEL PROD. :BOF
STEEL PROD. :ELEC. ARC
LEAD SMELTERS
-17-
-------
SC553.T054 FR
SCO CODE .
3-04-002-02
3-04-003-01
3-04-003-03
3-04-003-30
3-04-004-03
3-05-006-03
3-05-006-99
3-05-007-01
3-05-007-02
3-05-013-01
3-05-014-01
3-06-002-01
3-90-002-01
3-90-004-01
3-90-004-99
3-90-005-01
3-90-005-05
3-90-005-99
4-02-001-01
4-02-999-99;
5-01-001-01
5-01-001-02
5-02-001-02
5-03-001-01
5-03-001-02
5-03-001-05
SET ;
15
16
16
16
17
18
18
18
18
19
20
21
01
02
02
03
03
03
22
23 1
24
24
24
24
24
24
BRASS/BRONZE MELT
GRAY IRON
GRAY IRON
GRAY IRON
LEAD SMELT SEC
CEMENT: KILN: OIL-FIRED
CEMENT: OTHER/NOT CLASSIFIED
CEMENT MFG. WET
CEMENT MFG. WET
FRIT MFG.
GLASS MFG.
GEN. FLUID CRACKER
BITUMINOUS COAL (CEMENT KILN/DRYER)
RESIDUAL OIL (ASPHALT DRYER)
RESIDUAL OIL (OTHER/NOT CLASSIFIED)
DISTILLATE OIL (ASPHALT DRYER)
DISTILLATE OIL (METAL MELTING)
DISTILLATE OIL (OTHER/NOT CLASSIFIED]
PAINT
OTHER/NOT CLASSIFIED!
INCINERATOR (MUNICIPAL)
INCINERATOR (MUNICIPAL)
GENERAL INCINERATOR
INCINERATOR
INCINERATOR
INCINERATOR
-18-
-------
SC553.T054 FR
APPENDIX II
EMISSIONS ( IN LBS. ) PER
DESIGNATED UNIT FOR EACH SOURCE TYPE
-19-
-------
COAL
SC553.T054 FR
SET
01
01
01
01
01
01
01
01
01
01
01
01
01
01
01
01
01
01
01
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.0029 .
.015 .••
. 00058
.018
.0039
.004
.0022
.105
.0077
.001
.0015
.0026
.051
.0025
.001
.018
.0069
.017
.000007
UNITS: PER
TON COAL BURNED
-20-
-------
RESIDUAL OIL
SC553.T054 FR
SET
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
02
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.0007
.010
.0038
.9524
.012
.0004
.008
.4048
.072
.0050
.004
. 0044
1.2143
.0333
.000033
UNITS: PER
1000 GAL OIL BURNED
,
1'
-21-
-------
DISTILLATE OIL
SC553.T054 FR
SET
03
03
03
03
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.0024
.00051
.1190
UNITS: PER
1000 GAL OIL BURNED
J
-22-
-------
WOOD BOILER
SC553.T054 FR
SET
04
04
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.0019
UNITS: PER
TON
-23-
-------
DIESEL
SC553.T054 FR
SET
05
05
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.000136
UNITS: PER
1000 GAL
-24-
-------
PLASTICS
SC553.T054 FR
SET
07
07
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.0006
UNITS: PER
TON
-25-
-------
SC553.T054 FR
COKE
SET
08
08
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.0055
UNITS: PER
TON COKE PRODUCED
-26-
-------
SC553.T054 FR
IRON PROD.
SET
10
10
10
10
10
10
10
10
10
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.015
.022
.019
.0225
.0015
.052
.0001
.0014
.020
UNITS: PER
TON IRON PRODUCED
TON PIG IRON
TON PIG IRON
TON PIG IRON
TON IRON
TON IRON
TON PIG IRON
TON PIG IRON
TON PIG IRON
-27-
-------
SC553.T054 FR
IRON PROD. SINTER
SET
11
11
11
11
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.06
.052
.0002
UNITS: PER
TON SINTER
1
-28-
-------
SC553.T054 FR
STEEL PROD. (BASIC OXYGEN FURNACE)
SET
12
12
12
12
12
12
12
12
12
12
12
12
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.015
.002
.180
.002
.044
.068
.0015
.0087
.0004
.0003
.067
UNITS: PER
TON STEEL PRODUCED
'
'
-29-
-------
SC553.T054 FR
STEEL PRODUCTION ELEC ARC ;
SET
13
13
13
13
13
13
13
13
13
13
13
13
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.015
.007
.036
.10
.078
.0025
.0015
.0087
.0011
.0004
.74
UNITS: PER
TON STEEL PRODUCED
i
-30-
-------
SC553.T054 FR
LEAD SMELTERS
SET
14
14
14
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.8
.3275
5 ,
UNITS: PER
TON LEAD
TON
TON LEAD
-31-
-------
BRASS/BRONZE MELT
SC553.T054 FR
SET
15
15
15
15
15
15
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.30
.20
.40
.02
.50
UNITS: PER
TON
ir
-32-
-------
GRAY IRON
SC553.T054 FR
SET
16
16
16
16
16
16
16
16
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.011
.005
.00022
.005
.003
.33
.000018
.00072
.00017
UNITS: PER
TON METAL CHRG
TON PROC. WT.
TON CAST IRON
TON GRAY IRON PRODUCED
TON IRON
TON CAST IRON
TON CAST IRON
TON
TON-
-33-
-------
SC553.T054 FR
LEAD SMELT (SEC)
SET
17
17
17
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS.
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.8
.7
.0015
UNITS: PER
TON LEAD
-
TON PROD.
TON PROD.
-34-
-------
SC553.T054 FR
CEMENT, DRY
SET
18
18
18
18
18
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
0.13
.120
.012
.003
UNITS: PER
TON
v
(1 BBL = 376 LBS.)
-35-
-------
SC553.T054 FR
GLASS MFG
SET
20
20
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.154
.010
UNITS: PER
TON
TON
-
•
-36-
-------
SC553.T054 FR
FLUID CRACKER
SET
21
21
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.006
UNITS: PER
>»
1000 BBL
(1 BBL = 42 GAL.)
-37-
-------
SC553.T054 FR
INCINERATOR
SET
24
24
24
24
24
24
24
24
24
24
POLLUTANT
ARSENIC
ASBESTOS
BARIUM
BERYLLIUM
BORON
CADMIUM
CHROMIUM
COPPER
LEAD
MAGNESIUM
MANGANESE
MERCURY
MOLYBDENUM
NICKEL
PHOSPHORUS
SELENIUM
SILVER
TITANIUM
VANADIUM
ZINC
BAP
(Pounds)
QUANT.
.055
.003
.2
.0014
.046
.00002
.004
.252
.013
UNITS: PER
TON} SEWAGE BURNED |
; - . SOLID WASTE |
CHRG. I - - .
-38-
-------
EPA-600/4-77-017
April 1977
REGIONAL AIR POLLUTION STUDY
Sulfur Compounds and Particulate Size Distribution Inventory
by
Fred E. Littman
Robert W. Griscorn
Harry Wang
Air Monitoring Center
Rockwell International
Creve Coeur, MO 63141
Contract 68-02-1081
Task Order 56
Project Officer
Francis A. Schiermeier
Regional Air Pollution Study
Environmental Sciences Research Laboratory
11640 Administration Drive
Creve Coeur, MO 63141
ENVIRONMENTAL SCIENCES RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
RESEARCH TRIANGLE PARK, NORTH CAROLINA 27711
-------
DISCLAIMER
This report has been reviewed by the Environmental Sciences Research
Laboratory, U.S. Environmental Protection Agency, and approved for publication.
Approval does not signify that the contents necessarily reflect the views and
policies of the U.S. Environmental Protection Agency, nor does mention of trade
names or commercial products constitute endorsement or recommendation for use.
11
-------
ABSTRACT
In conjunction with the Regional Air Pollution Study being conducted
in the St. Louis Air Quality Control Region (AQCR), a methodology for
estimating the amount of sulfur trioxide (SO ) emitted by combustion sources
was developed. It is based on SO /SO ratios determined both experimentally
and from literature surveys. The most likely value appears to be 1.85% of
the SO emissions. On this basis, about 22,000 tons of SO are emitted
yearly from combustion sources.
A fine particle size inventory for the area was also developed. The
inventory gives a breakdown of particulate emissions in the range of 7 to
.01 microns, based on production rates and collection efficiencies for
point sources in the St. Louis AQCR. The information on the SO /SO
ratios and the particle size breakdown is stored in the RAPS Data Handling
System.
iii
-------
CONTENTS
Abstract iii
Figures vi
Tables. . . . ^ vii
1.0 Summary 1
2.0 Introduction 2
3.0 Sulfur Compounds 3
3.1 Scope and Definitions 3
3.2 Development of Base Data and Algorithms . 3
3.2.1 Base Data 3
3.2.2 Sulfur Dioxide-Sulfur Trioxide Ratios 4
4.0 Particulate Size Inventory 12
4.1 Definitions and Scope of Inventory 12
4.2 Development of Inventory for AQCR-70 13
4.2.1 Method 13
4.2.2 Particulate Size Inventory Data Files 15
4.3 Experimental Particle Size Distribution Data 15
4.3.1 Method and Equipment '16
4.3.2 Measurements of Particle Size 16
References 26
Appendices
I. Laboratory Evaluation of the "Shell" Method of
Determination of SOg 29
II. Particulate Inventory: Size - File -42
-------
FIGURES
Number Page
1 SCL Concentration Plotted Aganist CL in Flue
Gas for Four Star Coal 5
2 Variation of SCL Conversion to SCL with Oxygen 6
3 Percentage Conversion of SCL to SO- 9
4 Sulphur Trioxide Collector - 10
5 Anderson Stack Sampler 17
6 Deposits on Stage 2 - General Motors 20
7 Deposits on Stage 4 - General Motors 20
8 Deposits on Stage 6 - General Motors 20
9 Deposits on Stage 2 - Stag Brewery 21
10 Deposits on Stage 4 - Stag Brewery 21
11 Deposits on Stage 6 - Stag Brewery 21
12 Deposits on Back-up Filter - Stag Brewery 21
13 Ammonium Sulfate Crystals on Back-Up Filter -
General Motors 23
14 Particle Size Distribution Wood River Boiler #4 25
-------
TABLES
Number Page
1 Relationship Between Boiler Size and SO- Formation 6
2 Sulfur Oxide Analysis and Ratios 8
3 Particle Size Distribution Results 18
-------
1.0 SUMMARY
A methodology for estimating the amount of sulfur trioxide (SCL) emitted
by combustion sources in the St. Louis AQCR was developed. It is based on SO,,/
S03 ratios determined both experimentally and from literature surveys. The most
likely value appears to be 1,85% of the S0? emissions. On this basis, about
22,000 tons of SO, are emitted yearly from combustion sources.
An alternative method for SOo determination was evaluated and field tested.
The "Shell" method, developed originally by Goks^yr and Ross, appears to give
reliable results both in the laboratory and in the field.
A fine particle size inventory for the area was developed, based on earlier
work by MRI. The inventory gives a breakdown of particulate emissions in the range
of 7 to .01 microns, based on production rates and collection efficiencies for
point sources in the St. Louis AQCR. The information can be stored in the RAPS
Data Handling System.
Experimental data were obtained on particle size distribution of represen-
tative sources using an Andersen cascade impactor. Tfie results indicated a
bimodal distribution peaking at around 5 microns and at less than 7 microns.
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2.0 INTRODUCTION
Within the framework of the Regional Air Pollution Study (RAPS) at St. Louis,
MO., a high-resolution emission inventory has been assembled. Initially, this
inventory was focused on one pollutant - sulfur dioxide - for which hourly,
measured emission data were collected. This inventory was broadened to include
all "criteria" pollutants. In addition, special inventories were also developed
for trace pollutants, heat emissions and hydrocarbons.
This study is concerned with two classes of pollutants: sulfur compounds -
primarily SO (sulfur trioxide) since a detailed S02 (sulfur dioxide) inventory
exists, and a particle size inventory, a refinement of the particle inventory
available as part of the "criteria" pollutant inventory, which does not take
particle size into consideration.
-2-
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3.0 SULFUR COMPOUNDS
Hourly, measured emission data for all major point sources of S02 in the St.
Louis AQCR have been gathered and are available in the RAPS emission inventory
(1-4)
data base. This work is described in a series of reports v ' .
In the St. Louis area, virtually all sulfur dioxide emissions (98+%) occur
from point sources (stacks, vents, etc.). -This is not to say that the remaining
emissions are unimportant, since they originate essentially at street level (auto-
motive emissions, residential and commercial heating etc.) and thus may contribute
a disproportionate share to ambient concentrations.
3.1 SCOPE AND DEFINITIONS
This report deals with S03 emissions from stationary point sources. The term
"sulfur trioxide" (SO-,) is used, though it is realized that in its particulate
form, in which it is customarily collected, the compound is hydrated to sulfuric
acid (H2S04).
At stationary-point sources, both S02 and SO., originate from the oxidation
of sulfur or sulfur containing compounds. The bulk of the sulfur oxides orig-
inates from the combustion of fossil fuels, while the remainder comes from pro-
cess operations such as the roasting of ores, the manufacture of sulfuric acid,
etc.
The two oxides exist side by side in an equilibrium which is largely de-
termined by operational conditions at the source. The amount of SO, present is
usually expressed as a fraction of the S02 concentration.
3.2 DEVELOPMENT OF BASE DATA AND ALGORITHMS
3.2.1 Base Data
' (c \
In conformity with the National Emission Data System (NEDS) v ', the RAPS
Emission Inventory records basic fuel consumption and process data, rather than
mass emissions of pollutants. The basic data are converted to mass flow of pol-
lutants using emission factors, stored in a separate file. The advantage of this
-3-
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arrangement is that it permits periodic updating of the relatively small emis-
sion factor file, without disturbing the large mass of base data.
NEDS is an annual system, based on yearly reports gathered by local or re-
gional Air Pollution Control Agencies. By contrast, the RAPS emission inventory,
which covers the St. Louis Interstate Air Quality Control Region, is a collec-
tion of hourly values obtained directly for this purpose. Hourly data, based on
a measured parameter such as fuel consumption, steam or power production are
being obtained from all the major sources of pollutants in the AQCR. A major
source for the purposes of this inventory, is one which individually emits more
than 0.1% of the total of a given "criteria" pollutant in the area. "Criteria"
pollutants for which national standards exist include SCLj NOX, CO, hydrocarbons
and particulates.
The RAPS Emission Inventory also contains data on smaller sources, emitting
as little as 10 tons of SOp per year. Data on these sources are based on annual
consumption or process figures, modified by an operating pattern peculiar to the
source. The pattern, which is also stored in the RAPS Data Handling System,
recoH0 the hc'irs per day and days per week for normal operation, as well as any
holiday or vacation,periods. Using this information, average hourly S02 emis-
sion values can be obtained as an output. Since these sources make up less than
2% of all point source emissions, no significant errors are introduced by this
method.
As a result of this effort, a detailed and relatively accurate record of
SOp production exists, which can serve as a base for an SOo inventory.
3.2.2 Sulfur Dioxide - Sulfur Trioxide Ratios
In the presence of excess air in a combustion operation, a fraction of the
sulfur dioxide is converted to sulfur trioxide (SO,) according to
2 S02 + 02 + 2 S03 + 45.2 Kcal
The reaction is exothermic; however, the reaction rates are negligible be-
low 200°C (392°F), reach a maximum around 400°C (752°F) and taper off to zero at
1000°C (1832°F). Rapid conversion takes place only in the presence of a catalyst
-4-
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As would be expected from the reaction constant
K = (S02)2 x (02)
the yield increases with excess oxygen.
The information of SO, in boiler stack gases has been investigated fairly
/ c\ -J
extensively. Corbett ^ ' investigated the" SO, formation in an oil-fired boiler.
He found that 1 to 3% of the SCL was oxidized to
o.
The amount of SCU found
did not correlate with the percentage of sulfur in the oil or boiler conditions.
Lee ^ ' used a wet-bottom, pulverized coal-fired research boiler, several types
of coal , and varied the excess oxygen from 0.5 to 5%. He found a distinct re-
lationship on excess oxygen (Fig. 1).
(u
a
o
>
2
&
-
/^
—
0
tf*
~
4
— ;
0
»w
•
3
__
~'
"*<9
0
'
fr
O
^>
T
»*.
0
a<
02.% BY VOLUME
FIGURE 1: S02 CONCENTRATION PLOTTED AGAINST 02 IN FLUE GAS FOR FOUR STAR COAL
(Ref. 7)
-5-
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Gills
/0\
In a later study v ; Lee obtained similar results in an oil-fired furnace.
(9)
found a similar dependence on excess oxygen, but did not get a flat-
tening of the curve up to 12% oxygen (Fig. 2>. He also found a strong de-
pendence on boiler size, with an 850 tons steam/hour boiler producing a 1% con-
version to S03 at an oxygen level of 0.5%, while smaller boilers (up to 25 tons
steam/hour) produce only a 0.25% conversion under similar conditions.
o
o
00
oi
1-5
Q 10
tr
w
O
O
o-5
BOILER CAPACITIES
UP TO 25 tons steam/h
0 2 4 6 8 10 12
OXYGEN CONTENT (% VOL)
Figure 2: VARIATION OF S09 CONVERSION TO SO. WITH OXYGEN (Ref. 9)
£ O
The latter relationship was confirmed by Reese
following results at 4% excess oxygen.
(10)
, who obtained the
TABLE 1
RELATIONSHIP BETWEEN BOILER SIZE AND S03 FORMATION
Installation size
MW
55
no
185
% Conversion \
•i
to SO, 1
2.1 i
3.5 j
4.4 j
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In general, the percentage conversion falls in the range of 0.5 to 5%, with
absolute values below 50ppm of SO *
Our results are shown in Table 2 and Figure 3.
The concentration of S0~ varied from 120 ppm for a boiler operated on
distillate oil to 2660 ppm S0? for a coal burning boiler. Average for coal burn-
ing boilers was about 1600 ppm. The SO^ concentration ranged from 2.7 to 44.3
ppm, well within the range indicated by other investigators. As indicated in
Figure 3, there appears to be a marked dependence on excess oxygen. The percent-
age of S03 increased with increasing oxygen up to about 9%, then dropped rapidly.
This may be due to the cooling effect of large amounts of excess air. There did
not seem to be any correlation with the sulfur content of the fuel nor did there
appear to be any marked effect of boiler capacity on the amount or concentration
of SOo produced.
The RMS average S03 emission appears to be about 1.85% of the SOp emission.
This factor will be incorporated in the data handling system output program,
which will report SO^ emissions based on the corresponding S02 emissions. Using
the current figures for S02, this amounts to an annual emission of 22,585 tons
of S03 per year.
Analytical Methods for S03
The current standard method for SO, in stack gases is EPA Method 8 (CFR
40, 60.85, Appendix-Test Methods). In this method, the sample of stack gases
is drawn through a series of impingers. The first impinger contains 100ml of
80% iso-propanol; the second and third 100ml of 3% hydrogen peroxide. There is
a filter between the first and second impinger to retain entrained particulates.
The contents of the impingers are analyzed for sulfate using the barium
perchlorate-thorin method.
(9)
* An interesting exception was found by Gills v in brick kilns, where up to
28% of the sulfur oxides were in the form of SO.,.
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TABLE 2
SULFUR OXIDE ANALYSIS AND RATIOS
Wood River #1
#4
Highland
Stag
GM
Amoco
Average
RMS Average
so2
Ibs/SCF x 105
2.15
38.95
47.50
11.90
34.90
12.60
24.60
ppm
120.5
2183.5
2662.8
667.1
1956.5
706.3
1382.8
so3
Ibs/SCF x 103
6.07
34.50
32.85
16.76
98.90
14.25
33.8
ppm
2.7
15.4
14.7
7.5
44.3
6.4
15.2 '
S0,/S0p
O £-
Wt. Vol.
2.82%
1.13
.69
1.41
2.83
1.13
1.69
1.86
1.49%
.70
.55
1.12
2.26
.91
1.17
Excess 02
8.9%
6.0
4.8
11.2
8.9
10.5
8.4
Boiler Cap.
Ibs steam/hr
450,000
710,700
60,000
50,000
80,000
200,000
% Sulfur
in Fuel
.29
3.21
3.25
3.25
3.46
*3.00
I
00
I
*Weighted
average
-------
so
3 —
2 H
0
I
4
T
6
10
I
12
02
FIGURE 3
PERCENTAGE CONVERSION OF S02 TO S03
-9-
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8
Recent work cast doubts on both accuracy and reproducibility of Method
^ '. The method assumes that only S03 (sulfuric acid mist) will be retained
in the first impinger and the filter (both of which are analyzed together)."
(12)
However, Hillenbrand^ ' found that substantial amounts of SCL are retained in
the first impinger, some of which is subsequently oxidized to SCU, thus con-
tributing to high results. For this reason a different technique was used,
(13)
which was first described by Goks^yr and Rossx ' and subsequently verified by
(14)
Lisle and Sensenbaugh v . The method is generally referred to as the "Shell"
method, as it was developed in their laboratories. The method is based on the
condensation of sulfuric acid mist at temperatures below its dew point (but
above the dew point of water) in a condenser backed up by a fritted glass fil-
ter (Fig. 4). The condensate is washed out and titrated.
STOPPER
SPIRAL TUBE
GRADE 4
SINTERED
GLASS
DISC
GAS SAMPLE
OUT
FIGURE 4: SULPHUR TRIOXIDE COLLECTOR (Ref. 12)
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Data presented in references 12 and 13 indicate that adsorption of S03
is essentially complete, repeatability is excellent, S0? in concentrations
+ ^
up to ZOOOppm does not interfere and a precision of - O.Sppm of SO, can be
readily attained.
The method was then evaluated in our laboratories. The results of the
evaluation are shown in Appendix I; they indicate an average 100.1 - 6.5%
recovery with no significant interference from any of the variables tested.
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4.0 PARTICULATE SIZE INVENTORY
Emissions .of participate materials constitute a more complex problem
than gaseous emissions, since the properties of particles are determined
not only by their composition, but also by their size and shape. In fact,
the most important properties of particles, their effect on visibility,
their life-time as suspended materials, and to a large extent, their effect
on health, are all determined by'particle size. On all of these counts small
particles, 5 microns or less in diameter, are responsible for most of the ob-
served effects.
The common methods of collection and reporting of particulate emissions
do not distinguish particle size. Total particulate matter is reported on a
weight basis, which biases the results in favor of large particles. Since large
particles are only of local importance - they settle out rapidly - and are gen-
erally not involved in health effects because they are readily retained by the
body's screening-mechanisms, there are good reasons why particulate emission
data should be reported in such a way as to provide maximum information on small
particles.
4.1 DEFINITIONS AND SCOPE OF INVENTORY
There is no universally accepted definition of "fine particles", but most
authors agree on a range of 3 to 5 microns as the upper limit. Particles small-
er than approximately 5 microns have settling velocities in still air of the
order of 0.01 cm/sec and tend to stay aloft almost indefinitely. Particles can
be either solid or liquid.
The most up-to-date study of fine particulate emissions is contained in EPA
Technical Report entitled "Fine Particulate Emission Inventory and Control
(15)
Survey" v . The methodology contained in that report was applied to the St.
Louis AQCR. In addition, samples were taken at representative emission sources
using'an Andersen cascade impactor. Data developed from this study are also
included.
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4.2 DEVELOPMENT OF INVENTORY FOR AQCR-70
In order to prepare a particle size inventory within the scope of RAPS,
compatible with the NEDS and RAPS Data Handling Systems, the procedure outlined
below was used. No effort was devoted to the inventory of area sources, mobile
sources, chemical .and physical characterization of these particulates.
4.2.1 Method
The method put forth in the "Fine Particulate Emission Inventory and Control
Survey" uses the following equation for the calculation of particulate emissions:
Vd2
where
A A — n
Pe C
KefLt
2000
m-i f r- n f\ r>
= emission rate for particles with diameter between d, and dp
P = production rate
ef = emission factor (uncontrolled)
C. = percentage of production capacity on which control equipment is in-
stalled (for that device)
f-j(d) = emitted particle size distribution
f~(d) = penetration = (1 -fractional efficiency of control system)
The size ranges are (in microns):
.01 - .05, .05 -.!,.!- .5, .5 - 1, 1 - 3, 3 - 7.
The data sources are:
(1) RAPS coding forms (or NEDS computer listing)
(2) "NEDS Source Classification Codes and Emission Factor Listing" (SCC
listing), July 1974.
(3) "Fine Particulate Emission Inventory and Control Survey" (EPA-450/3-
74-040), January 1974.
The equations used for calculating the total particulate emissions are:
E, , (total) E, , (controlled) , E, , (uncontrolled) (2)
Q-, ~up ~~ u-i ~Qp "r I ~ 9
-13-
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where E^ _^ (controlled) is expressed in equation 1, and
pe 0-CJ
E , , (uncontrolled) _ f * f / ,»
dTd2 ' ~2000 fl (d)
The assumption used here is that f,, (d) applies to that fraction of the
emission which is specified by C. and (1-C.) has no control and therefore
f2(d) = 1.
The algorithm for a computer program may be something like the following:
I For every point source
la Look up from RAPS coding form, the SCO code Card 4
Ib Look up P (annual data) Card 5
Ic Look up C. (control efficiency) Card 3
Id Look up CID (control device ID code) Card 3
II From EFACTR file. Look up ef (uncontrolled emission factor) for the
corresponding SCC number.
Ill From SIZE file, look up size distribution in fractional values for each
size range for the corresponding SCC number.
IV From the EFCNCY file. Look up the fractional efficiency of each size
for the corresponding control device as identified by the code number
CID.
V Calculate the emissions using equations 1, 2 and 3.
The following are examples of the three computer input data files:
File Name: SIZE
SCC Code .01-.05 .05-.1 .1-.5 .5-7 1-3 3-7
Fractional Values
File Name: EFACTR
SCC Code Emission Factor
I Pounds per Ton
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File Name: EFCNCY
CID .01-.05 .05-.1 .1-.5 .5-.1 1-3 3-7
Efficiency
4.2.2 Participate Size Inventory Data Files
Of the three files required for calculations of the particulate size inven-
tory, one, the emission factor file EFACTR, is already contained in the RAPS in-
ventory. The other two were developed on this Task and are given in Appendix II.
The SIZE-file, in a matrix form, gives the particle-size distribution of
emitted particulates for any one of the forty-four SCC-codes listed in column 2.
Each column between columns 3 through 8 lists the fractional value of the total
particulate effluent that falls within the corresponding particle-size range.
All values to the right of the double line (columns 2-8) are keypunched for
computer input with the READ format: (18, 6F4.0), blanks = 0. The fractional
values in the F-format are left justified with no decimal points.
The EFCNCY-file lists the fractional efficiency of the effluent control de-
vice for each particle-size range. The control device is identified by the CID
number under column 2 and the particle-size ranges have the same diameter group-
ings as that in the SIZE-file.
All values to the right of the double line (columns 2-8) are keypunched for
computer input with the READ format:
(13, 6F4.0), blanks = 0
The fractional values in the F-format are left justified with no decimal points.
Both files were keypunched. The cards are available for input into the RAPS
Data Handling System. •
4.3 EXPERIMENTAL PARTICLE SIZE DISTRIBUTION DATA
In connection with the emission factor verification program carried out as
part of the RAPS study, data were gathered on particles size distribution of a
number of representative sources.
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4.3.1 Method and Equipment
Particle size testing was performed with an Andersen Stack Sampling head
coupled with the apparatus used for standard EPA method for particulates. The
Andersen is a fractionating inertial impactor which separates particles accord-'
ing to aerodynamic characteristics.
The Mark II sampling head consists of a stainless case, plate holder and
nine jet plates. The plates have a pattern of precision-drilled orifices. The
nine plates, separated by 2.5 millimeter stainless steel spacers, divide the
sample into eight fractions or particle size ranges. The jets on each plate are
arranged in concentric circles which are offset on each succeeding plate. The
size of the orifices is the same on a given plate, but is smaller for each
succeeding downstream plate. Therefore, as the sample is drawn through the
sampler at a constant flow rate, the jets of air flowing through any particular
plate direct the particulates toward the collection area on the downstream plate
directly below the circles of jets on the plate above. Since the jet diameters
decrease from plate to plate, the velocities increase such that whenever the
velocity imparted to a particle is sufficiently great, its inertia will overcome
the aerodynamic drag of the turning airstream and the particle will be impacted
on the collection surface.
The Mark III is identical to the Mark II except the location of the orifices
in the plates have been modified to permit the use of a special collection sub-
strate (glass fiber in our tests). This permits lighter tare of weights for
gravimetric analyses and a collection of material for chemical analysis. Figure
5 illustrates the Andersen sampling head and an exploded view of the plate holder
and plates.
4.3.2 Measurements of Particle Size
Particle Size Distribution measurements have been conducted at five of the
seven test sites sampled in 1975. Initially only the Andersen Mark II plates
were available. Because of this the only results available at the first test
site' are the weight distribution. On subsequent tests, runs were made with both
the Mark II plates and Mark III plates with glass fiber filters for comparison.
Sites that have been tested for particle size are shown in Table 3. Some of the
filter samples were inspected microscopically and a few of these were also
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FIGURE 5
ANDERSEN STACK SAMPLER
-17-
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analyzed by x-ray fluorescence. A summary of the results of the testing is given
in Table 3. Particle size is given as aerodynamic size for spherical particles
with unit density.
TABLE 3
PARTICLE SIZE DISTRIBUTION RESULTS
Source
111 . Power - Wood River
Highland Electric
Stag Brewery
General Motors
Amoco
Sec Code
1-01-002-02
1-01-002-08
1-02-002-05
1-02-002-09
3-06-001-02
3-06-001-03
% vs Particle Size
>7y 3-7y l-3u 0.5-lu < 0.5y
22.5 22.8 18.-5 8.3 27.9
26.6 18.9 10.0 12.7 31.8
37.4 16.0 7.6 18.3 20.7
14.3 24.4 18.5 9.2 33.6
13.9 8.9 22.0 18.8 36.4
At General Motors, fourteen tests were performed to evaluate variations of
testing methods consisting of placing the Andersen in-stack, out of stack (in oven):
using Mark II plates and Mark III plates with filters. Each of these methods has
its advantages which may make it desirable for any one individual test. The main
objective of these tests was to arrive at a testing arrangement to be used on all
subsequent tests. As it turned out there was no clearcut single method which
proved better than the others.
Sampling in the stack avoids any problems with extracting a sample and hav-
ing some of it deposited in the probe. Also the sample head is at the same temper-
ature as the stack gases which avoids any problems of condensation. In-stack samp-
ling, however, means the impaction surface is vertical and is subject to having
the sample dislodged in handling. WheTi sampling must be done vertically in a duct,
from the top down, this method cannot be used.
Sampling with the Andersen sampler in the sample oven at the end of a heated
probe affords much better handling. The sample head can be kept vertically with
the plates horizontal at all times. The sample head is also clamped in place and
doesn't have to be threaded on to the probe, which avoids more handling.
rr-,. -,cr-..-> -?0"4 ? r-^R O f
Isokinetic sampling rates can be determined more readily when the Andersen
is in the oven since the probe has a pi tot attached and the probe remains in the
stack (for in-stack sampling a pi tot measurement is made, the pi tot is removed
-18-
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and the sampler is inserted to approximately the same position). There are two
problems with sampling this way: the oven can be heated only to 350 F, which
may not be as high as the temperature in the stack, and larger particles tend
to be deposited in the probe, which lowers the weight of the deposit on the first
two plates.
Parallel sampling with both the Mark II plates above and the Mark III plates
with filters indicates that there~ isn't any significant difference in the weight
of catch and the size distribution between these two methods. If the Mark II
model is used, the number of tests is limited by how many sets of plates are avail-
able. With the Mark III plates and filters more runs can be performed by chang-
ing the filters between runs with the available time being the only constraint
on the number of runs. More care must be taken in assembling the Mark III, since
the filters are pre-cut to match the plates and must be properly aligned to avoid
blocking any holes.
As a result of these comparison tests, it was decided that testing would be
performed with the Mark III plates and filters and that the Andersen sample head
would be placed in the oven for ease in handling and subsequent analysis.
Photomicrographs have been made by Illinois Institute Qf Technology Research
Institute (IITRI) of samples collected on each stage from three Andersen runs.
These pictures confirm that the Andersen does in fact separate by particle size
as the instructions would indicate. Evidence of this is shown in Figures 6, 7
and 8 from General Motors and Figures 9, 10, 11 and 12 from the Stag Brewery.
Figure 6 is from stage 2 taken at 163x. This shows a high percentage of
fly ash and partially fused clays and minerals, average particle size is approxi-
mately 6 microns. Figure 7 is from stage 4 taken at 163x. This shows much small-
er particles, a high percentage of fly ash and more FepO.,, and an average
particle size of approximately 2 microns. Figure 8 is from stage 6 taken at 163x.
This shows mostly submicron partially burned coal, fly ash and F^p^s*
For spherical particles with unit density stage 2 should have separated
from 10.9 to 17 microns, stage 4 from 5.0 to 7.3 microns, and stage 6 from 1.7 to
3.2 microns. Since fly ash has a density between 2 and 3, these stages will
actually separate smaller particles.
-19-
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FIGURE 6
a-i»»t->A..'S....ali_ LI
DEPOSITS ON STAGES
2,4 AND 6
GENERAL MOTORS
FIGURE 7
FIGURE 8
-20-
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ro
i
FIGURE 9
FIGURE 11
FIGURE 10
FIGURE 12
DEPOSITS ON STAGES 2,4,6
AND BACK-UP FILTER
STAG BREWERY
-------
Figure 9 from Stag Brewery is from stage 2 taken at 406x. This shows lots
of incompletely combusted coal, partially fused glassy material and Fe^O-
partially fused and coating other particles. Average particle size is approxi-
mately 5 microns. Figure 10 is from stage 4 taken at 406x. This shows fine fly
ash spheres most of which are dark due to iron in solid solution and some miner-
als and fine carbonaceous particles. Average particle size is approximately 2
microns. Figure 11 is from stage 6 taken at 406x. This shows what appears to be
black carbonaceous material which hit as a liquid or is particles suspended in a
liquid. There is very little fly ash or else it is below 0.5 micron. Figure 12
is from the backup filter taken at 406x. This shows extremely fine liquid drop-
lets with trapped fine carbonaceous particles and extremely fine sulfate par-
ticles.
Microscopic analysis of the filters has indicated that sulfate crystals form
on the filters in increasing amounts on descending stages to the point where the
backup filter sample is mostly sulfate. Personnel from IITRI have indicated that
these crystals are ammonium sulfate and that they have grown on the filters.
Figure 13 is from a backup filter from a test at General Motors, taken at 163x.
Clearly, these crystals could not have passed through the Andersen impactor.
The mechanism for the formation of these crystals is still not understood.
Apparently, there is a reaction between ammonia in the flue gases with sulfuric
acid on the filters. To check that this reaction didn't take place from ex-
posure sometime later, one backup filter was sealed in an air-tight enclosure at
the test site and then examined immediately after opening the sample container.
This sample also showed a large amount of crystals.
A few of these backup filters have been analyzed for acidity. Approximately
17% of the amount of sulfuric acid measured in the stack at General Motors.was
found to be entrained by the backup filter and by the total particulate filter
on an EPA particulate run. Whether this is due to condensation and entrainment,
or a gas-solid phase reaction, is not known. At these temperatures, 440 F in-
stack and 350 F in the oven, sulfuric acid vapor should not condense.
One test run indicated that temperature has some relationship to the amount
of material in the backup filter. Two identical Andersen runs were made at
General Motors with the sample head in the oven. The first test was with an oven
-22-
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FIGURE 13
AMMONIUM SULFATE CRYSTALS
ON BACK-UP FILTER
GENERAL MOTORS
-23-
-------
temperature of 300°F and the second with a temperature of 370°F. While the first
8 stages were very similar in weight, there was twice as much material collected
on the backup filter in the first test than in the second.
The particle size distribution from all of the tests performed to date shows
a bimodal distribution, generally with a peak around stages 4 or 5 and a large
peak on the last backup stage. A typical curve is shown in Figure 14. The large
amount of sulfate crystals on the backup indicates that perhaps 30% of that amount
is sulfuric acid and should not be included. But even after this is subtracted
there are two peaks, one around 5 microns and the other less than 0.7 micron.
-24-
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45-
40-
35-
30-
FIGURE 14
PARTICLE SIZE DISTRIBUTION
WOOD RIVER
BOILER #4
25-
20-
15-
10-
5-
11 10 9 87 654 32 TO
ECD, microns
-25-
-------
5.0 REFERENCES
1. Littman, F. E., "Regional Air Pollution Study Point Source Methodology and
Inventory" Rockwell International, EPA 450/3-74-054, October 1974
2. Littman, F. E. and R. W. Griscom "RAPS Point Source Emission Inventory - Phase
II" Air Monitoring Center, Rockwell International, EPA Contract No. 68-02-
1081, July 1975.
3. Littman, F. E., R. W. Griscom and Otto Klein "RAPS Point Source Emission Inven-
tory" Air Monitoring Center, Rockwell International, EPA Contract No. 68-02-
1081, February 1976.
4. Pierre, John, and W. Tillman "RAPS Point Source Emission Inventory Data Hand-
ling System" Air Monitoring Center, Rockwell International, EPA Contract No.
68-02-1081, February 1976.
5. "Guide for Compiling a Comprehensive Emission Inventory", U. S. Environmental
Protection Agency APTD-1135, March 1973.
6. Corbett, P. F., "The SO, Content of the Combustion Gases from an Oil-fired
Water-tube Boiler", J. Inst. Fuel, Aug. 1953, p. 92.
7. Lee, G. K. et al, "Effect of Fuel Characteristics and Excess Combustion Oil on
Sulfuric Acid Formation in a Pulverized-coal-fired Boiler", J. Inst. Fuel,
Sept. 1967, p. 397.
8. Lee, G. K., et al, "Control of SO, in Low-pressure Boiler", J. Inst. Fuel,
Feb. 1969, p. 67.
9. Gills, B. G., "Production and Emission of Solids, SQ« and NO,, from Liquid Fuel
Flames, J. Inst. Fuel, Feb. 1973, p. 71.
10. Reese, J. T., et al, "Prevention of Residual Oil Combustion Problems By Use
of Low Excess Air", Trans. ASME, J. Engrg. Power, 1965, V87A, p. 229.
11. Hamil, H. F., et al, "Collaborative Study of EPA Method 8 (Determination of
Sulfuric Acid Mist and Sulfur Dioxide Emissions from Stationary Sources)",
EPA 650/4-75-003.
-26-
-------
12. Hillenbrand, et al, "Chemical Composition of Participate Air Pollutants from
Fossil-Fuel Combustion Sources", Battelle Columbus Labs, March 1973, EPA-
R2-73-216, PB219.009.
13. Gokstfyr, H., and K. Ross, "Determination of Sulphur Trioxide in Flue Gases",
0. Inst. Fuel V35, p. 177 (1962).
14. Lisle, E. S. and J. D. Sensenbaugh, "Determination of Sulfur Trioxide and Acid
Dew Point in Flue Gases", Combustion 36_, 12, (1965).
15. Weast, T. E., et al, "Fine Particulate Emission Inventory and Control Survey",
Midwest Research Institute, EPA 458/3-74-040, Jan. 1974.
-27-
-------
APPENDIX I
-28-
-------
LABORATORY EVALUATION
OF THE "SHELL" METHOD
OF
DETERMINATION OF S03
The "Shell" method for determinationof sulfur trioxide (sulfuric acid)
in flue gas is based on its selective condensation from the flue gas. This
is achieved by utilizing the relatively high (60-90°C) dew point of SO,. At
this temperature only the sulfuric acid condenses from the flue gas and there-
fore it can be determined rather easily.
Flue gas is drawn through the condenser at a rate of 2 liters per minute
for 10-20 minutes depending upon the SO., level in the flue gas. Particulates
are removed from the flue gas sample by using a plug of glass wool as a filter.
At the end of the sampling period, the H^SO* is washed out of the condenser
with 5% solution of isopropyl alcohol in water. The combined washings were
titrated with 0.02 N NaOH using bromophenol blue as indicator.
The laboratory evaluation of this method had a dual purpose. The first
was to check the accuracy of the method under the experimental conditions and
secondly, to determine which of the experimental parameters may affect the per-
formance of this method. For the latter, stack conditions had to be simulated
in a way which would allow adjustment of each parameter to predetermined levels.
The accuracy of the method was tested by duplicating the experimental work of
tioi
(2)
E.S. Lisle and J.D. Sensenbauglr . The effect of the experimental conditions
on the accuracy of the method was evaluated by using the Plackett-Burman
statistical design of screening process variables. This method is based on
balanced incomplete blocks. A good example of applying this method to a chem-
ical process has been published by R.A. Stowe and R.P. Mayer^. With this
method it is possible to effectively screen all the experimental parameters and
to find out which of them most likely will affect the overall process, by per-
forming only a small fraction of experimental work usually required for other
methods of screening variables. For example, a complete factorial design for
fifteen variables at two levels requires 32,768 experiments; with the Plackett-
-29-
-------
Burman method the same number of variables can be screened effectively with
(3)
only 16 experimentsv '. It should be emphasized, however, that this method
does not optimize the process; it only indicates which of the parameters do
not affect the process.
EXPERIMENTAL
The experimental set-up used in this study is given in Figure 1. A
special condenser thermostated at 60-90°C was used for the collection of the
condensed H^SO*. The simulated flue.gas is introduced at the end of the con-
denser which consists of a spiral glass tube followed by a coarse glass frit-
ted disc. Both the spiral and the glass fritted disc are kept at constant tem-
perature (60-90°C) by circulating water from a heating bath. The hLSO, gener-
ator consists of a quartz tubing heated electrically by a spiral of nichrome
wire insulated by several layers of asbestos tape. With this arrangement the
temperature of the HLSCL generated can be adjusted at the desired level and kept
constant within 10°F. Dilute sulfuric acid solution is added at a constant rate
by a peristaltic pump through a hypodermic needle and serum cap in the top open-
ing of the FLSCL generator. The rate of hLSO* addition can be altered by using
pump tubes of different diameter. The flow rate of the gases (Op. N^. SC^) was
adjusted and maintained at the proper levels with a combination of valves and
rotometers. The total flow was checked by a rotometer at the outlet of the
condenser.
PROCEDURE
The FUSO* generator was calibrated by titrating the amount of acid delivered
by the peristaltic pump at the upper end of the generator for a certain period
of time (about 10 minutes) for the two pump tubes and the two hLSO* solutions used
throughout the experimental work. The nominal flow rates of the pump tubes used
were 0.42 and 0.70 cc/min and the normality of the HUSO, solutions was 0.01 and
0.03 N. Tables 1, 2, 3 and 4 give the calibration of the H^SO. generator for the
above flow -rates and the sulfuric acid solutions. The results are expressed in
y. equiv/min. The actual experiments were conducted in a similar manner. Sul-
furic acid solution was delivered to the HLSO* generator by the pump for about
ten minutes and collected in.the condenser. The condensed hLSO* was washed out
of the condenser with 5% isopropyl alcohol in water and the combined washings
-30-
-------
CO
—J
I
FIGURE 1
CALIBRATION EQUIPMENT
Peristaltic Pump
I
S03 Generator (550-650'
Rotometer
Thermometer
H20 (60-90°C)
H2S04
SO,
-------
Table 1
CALIBRATION OF THE SOg
Nominal Pump Rate - 0.
GENERATOR
42 cc/min
Normality of H2$04 Solution = 0.01 N
Run #
1
2
3
4
5
Time
Sec.
601.
599.
599.
600.
600.
cc of 0.02 N NaOH
7 2.58
7 2.42
5 2.45
3 2.30
4 2.32
Average
Table 2
CALIBRATION OF THE S03
Nominal Pump Rate = 0
y equil/min
5.14
4.84
4.90
4.60
4.63
4.82 +0.22 y. equiv/min
GENERATOR
.42 cc/min
Normality of H2$04 Solution = 0.03 N
Run #
1
2
3
4
Time
Sec.
601.
601.
600.
600.
ml of 0.2 N NaOH
0 7.46
5 7.82
4 7.52
5 7.66
u equil/min
14.89
15.60
15.03
15.30
Average 15.20 +_ 0.31 y. equiv/min
-32-
-------
TABLE 3
CALIBRATION OF THE SOg GENERATOR
Nominal Pump Rate = 0.7U cc/min
Normality of H2$04 Solution = 0.01 N
Run #
1
2
3
4
5
Time
Sec.
630.6
600.0
689.8
600.7
600.4
Titrant
ml of 0.02 N NaOH
4.60
4.46
4.98
4.44
4.42
u equil/min
8.15
8.92
8.66
8.87
8.83
Average
8.81 t 0.10 y.equiv/min
TABLE 4
CALIBRATION OF THE S03 GENERATOR
Nominal Pump Rate = 0.70 cc/min
Normality of H2S04 Solution = 0.03 N
in #
1
2
3
4
5
Time
Sec.
599.9
600.2
599.2
600.7
602.2
Titrant
cc of 0.02 N NaOH
12.80
12.23
12.26
12.42
13.24
y equil/min
25.60
24.45
24.55
24.81
26.38
Average
25.16 t 0.82 y.equiv/min
-33-
-------
were titrated with 0.02 N_ NaOH. Throughout this work all the experimental
parameters were varied at two levels: one high level and one low level des-
ignated here as (+) or (-) respectively. Table 5 gives all the experimental
parameters examined in this study and their respective high and low values.
The resulting efficiency of collection of the generated hLSO, vapors was
determined by dividing the recovered amount of H^SO* by the amount of S03 de-
livered into the system (Tables 1 and 4).
RESULTS AND DISCUSSION
As it was mentioned previously, the purpose of this study was to first de-
termine the efficiency of the system under the recommended conditions and sec-
ondly to screen all the experimental parameters and determine which of them af-
fect the efficiency of the system.
Table 6 summarizes the results obtained by using the system under the rec-
ommended conditions. No S02 was used in these experiments because the main pur-
pose was to determine the efficiency of collection of HUSO/, from flue gas. These
(1)
experiments were performed in the manner recommended by Lisle and Sensenbaughv .
The samples were introduced in the evaporator by a syringe through the serum cap
without the use of the proportioning pump. The average recovery was found to be
equal to 100.1 - 6.5%. It should be noted, however, that no extra effort was
made to optimize any of the experimental conditions and therefore these results
represent data obtained by a casual application of this method. A close inspec-
tion of the results tabulated in Table 6 shows that sources of positive (recov-
eries > 100%) and negative (recoveries < 100%) errors do exist and therefore an
examination of the parameters affecting the accuracy of the method appeared to
be necessary. The parameters listed in Table 5 were tested by the method of
Plackett and Burman by using a matrix for sixteen runs and fifteen variables.
Figure 2 gives the Plackett-Burman matrix used in this study. Five out of the
fifteen variables were blank "dummy" tests from which the standard error of the
method was calculated.
, The statistical analysis of the results is given in Table 7. In this table,
confidence levels are shown only to the 70% level; the remaining variables are
considered to have an insignificant effect on the method within the studied ranges.
Therefore from the ten variables studied only four may have an effect on the ac-
-34-
-------
TABLE 5
VARIABLES CHOSEN FOR STUDY
Code letter of Levels
the variable Variable Low(-) High(+)
A Temperature of Condenser (°C) 60 - 3 90-3
B Temperature of Evaporator (°F) 550 650
C 02/S02 Ratio 149 223
(D) Dummy —. —
E Total Flow (liter/min) 2 4
F Flow Rate of H2S04 Solution (cc/min) 0.42 0.70
(G) Dummy — —
H Elapsed Time Prior to Rinsing the 1 10
Condenser (min)
I Volume of Solvent for Each Washing (ml) 10 25
J Total Volume of Solvent Used for Each 135 185
Experiment (ml)
K Size of Hypodermic Needle (gauge) 26 20
(L) Dummy — —
M Normality of H2S04 Solution 0.01 0.03
(N) Dummy — —
(0) Dummy — —
-35-
-------
TABLE 6
COLLECTION EFFICIENCY OF THE METHOD
OF S03 DETERMINATION IN FLUE GASES
Volume of acid =
20:1 ; condenser1
4.0 mil ; total
s temperature 85
flow = 3.96 liter/min; nitrogen to oxygen ratio
°C; temperature of H^SO, generator 600°F.
m. equiv. HpSO,
Run #
1
2
3
4
5
6
7
8
9
10
11
12
Taken
0.040
0.040
0.040
0.040
0.080
0.080
0.080
0.080
0.120
0.120
0.120
0.120
Found %
0.039
0.042
0.041
0.047
0.077
0.077
0.074
0.077
0.123
0.119
0.120
0.115
Recovery
97.50
105.00
102.50
117.50
96.25
96.25
92.50
96.25
102.50
99.17
100.00
95.83
Average % Recovery 100.0 +_ 6.5
-36-
-------
PLACKETT-BURMAN MATRIX FOR DETERMINING
THE EFFECTS OF FIFTEEN VARIABLES
AT TWO LEVELS USING SIXTEEN RUNS
- = LOW
Random Run VaHable + = """
Number Order A B C (D) E F (G) H I J K (L) M (N) (0) % Recovery
1 1 + -}.+ + -+ -.+4---4-- _ g2>4
2 2 + 4-+-+- + 4--+--~ + 93>9
3 3 + + _ + _+ + _- + ___+ + 92.5
4 8 +_+_++_- + -__ + + + 94j
5 4 - + - + 4---+--- + + + + 87.4
6 6 +-.+ + ,_ + -__+ + + + _ 86.6
7 9 _ + +--+---4-4 + + - + 83.1
8 12 + + --+- -- + 4+ + - + - 109.3
9 10 4--- + ---44- + 4- + - + 87.3
10 13 __+___ + + + + _ + „+ + -J02.1
11 14 _ + ___+-i-+4-4- + 4 - 83.7
12 164---4-44-4-4- + 4-- - 96.4
13 5 ___ + 44-4- + -4-4---+ 98.5
14 7 __4 + 4+-4-44--+ - 107.5
15 11 _ + + + +- + - + +-- + - - 81.8
16 15 __„___-____-__ _ 84i3
FIGURE 2
-37-
-------
TABLE 7 - LIST OF PARAMETERS
I
CO
\
Code
A
B
C
/n\
(D)
E
F
I r \
(G;
H
I
J
K
/i \
ILJ
M
/HI \
(N)
lr\\
'ariable
Name
Temp, of Condenser
Temp, of Evaporator
02/S02 Ratio
Dummy
Total Flow
Flow Rate of H2S04 Soln.
Dummy
Elapsed Time Prior to Rinsing
Volume of Solvent for Each Washing
Total Volume of Solvent for Each Exp't.
Size of Hypodermic Needle
Dummy
Normality of H2SO* Solution
Dummy
Hi trnrm/
Effect*
(+) to (-)
0.0289
-0.0421
0.0014
n m A Q
~(J . U 1 Hy
0.0699
-0.0110
Om Tfi
. U 1 JD
0.0244
0.0231
0.0501
0.0224
Om AT
. U 1 *t/
-0.0989
OncoT
. Ubol
_n nnKi
t-Test
1.018
1.482
0.049
2.464
0.387
0.860
0.814
1.7G6
0.789
3.486
Relative Significance
** % Confidence Level
80
95
85
99
*The effect of each parameter is the difference of the average high (+) minus the average low (-)
yD f ^. \
response. For example, the effect of A is Eft - X -
M o
**t-Test value of a variable is given by t =
standard error effect given by
dummy variables.
>« t .
•^
i n
where Ev is the effect of variable v and S.E. ff is the
cl '
\2 where Ed is the dummy effect and n the number of the
-------
curacy of the method and should be studied further for the optimization of the
total system. These four variables are the temperature of the evaporator (B),
the total flow (E), the total volume of washing solution (J) and the normality
of the H2S04 solution used (M). It should be noted at this point that from these
four variables, the two (B and M) are very closely related with the experimental
conditions used for generating simulated flue gas in the laboratory and therefore
may not be associated with the application of the method in the determination of
SO, in real flue gas. The other two (E and J) are associated with the method and
appear to be the most significant parameters which may affect the accuracy of the
S03 determination in flue gas. The total flow (parameter E) most likely affects
the condensation of SO, from the flue gas and the total volume of washing solu-
tion (parameter J) is related with the efficient washing of the condensed HLSO,.
These two parameters are most likely the ones on which proper attention should be
given in the application of this method for determination of SOg in flue gas.
-39-
-------
REFERENCES
1. E.S. Lisle and J.D. Sensenbaugh, Combustion 36_, 12 (1965).
2. R.L. Plackett and J.P. Burman, Biometrica 33_, 305 (1946).
3. R.A. Stowe and R.P. Mayer, Ind. and Eng. Chem. 58, 36 (1966),
-40-
-------
APPENDIX II
-41-
-------
ro
i
RAPS - TASK 56 PARTICULATE INVENTORY:
SOURCE OPERATION
Asphalt Dryers
Asphalt Vent Lines
Cement Kilns
Fertilizer Granulators
and Dryers
Iron and Steel: BOF
Elec. arc
sintering
Iron Foundry Cupolas
Kraft Pulp Mill: B.F.
Boiler
Lime Plant: Sec. sources
Municipal Incinerators
VENTORY: SIZE
SCC - CODE
3-05-002-01
3-05-002-02
3-05-006-03
3-05-007-01
3-01-027-06
3-03-009-03
3-03-009-05
3-03-008-03
3-04-003-01
1-02-009-02
3-05-016-01
3-05-016-02
5-01-001-01
5-01-001-02
- FILE
3-7 y
.190
.232
.165
.165
.040
0
.13
.050
.065
.120
.320
.320
.050
.050
l-3y
.131
.0735
.103
.103
.0182
.060
.200
.027
.060
.083
.350
.350
.075
.075
PARTI CULATE
.5-ly
.022
.0041
.0165
.0165
.0043
.360
.120
.0056
.020
.018
.045
.045
.035
.035
SIZE
l-.5y
0009
0004
0054
0054
0023
578
210
0024
0230
0080
005
005
045
045
RANGE
.05-.ly
.0001
0
.0001
.0001
.0002
.002
.060
0
.0035
.0003
0
0
.010
.010
1/3
.01-.05y
0
0
0
0
0
0
.070
0
.0035
.0001
0
0
.015
.015
-------
RAPS - TASK 56 PARTICULATE INVENTORY:|SIZE - FILE
SOURCE OPERATION
Elec. Util: Pulv. coal
Stoker coal
Cyclone coal
Gas
Oil
Industrial: Pulv. coal
Stoker coal
IC.IN 1 UM . IO1Z.C -
SCC CODE
1-01-002-01
1-01-002-02
1-01-001-02
1-01-002-08
1-01-002-03
1-01-006-01
1-01-006-02
1-01-004-01
1-01-005-01
1-01-005-02
1-01-005-03
1-02-002-01
1-02-002-02
1-02-002-08
1-02-002-12
1-02-002-04
1-02-002-09
1-02-002-11
1-02-002-13
riLt
2/3
PARTICULATE SIZE RANGE'
3-7y
.160
.160
.180
.180
.250
0
0
.90
.90
.90
.90
.100
.100
.100
.100
.050
.050
.050
.050
l-3y
.100
.100
.048
.048
.220
.90
.90
0
0
0
0
.0195
.0195
.0195
.0195
.0176
.0176
.0176
.0176
.5-ly
.021
.021
.009
.009
.055
0
0
0
0
0
0
.0005
.0005
.0005
.0005
.0019
.0019
.0019
.0019
.l-.5y
.0087
.0087
.0029
.0029
.0244
0
0
0
'0
0
0
0
0
0
0
.0005
.0005
.0005
.0005
.05-.ly
.0002
.0002
0
0
.0005
0
0
0
0
0
0
0
0
0
0
0
0
0
0
.01-.05y
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-------
SOURCE OPERATION
Gas
Oil
ULATE INVENTORY:
SCC CODE
1-02-006-01
1-02-006-02
1-02-006-03
1-02-067-01
1-02-010-03
1-02-004-01
1-02-004-02
1-02-004-03
1-02-005-01
1-02-005-02
1-02-005-03
SIZE -
FIlT]
3/3
PARTICULATE SIZE RANGE
3-7 y
0
0
0
0
0
.90
.90
.90
.90
.90
.90
l-3y
.90
.90
.90
.90
.90
0
0
0
0
0
0
.5-ly
0
0
0
0
0
0
0
0
0
0
0
.l-.5y
0
0
0
0
0
0
0
0
0
0
0
.05-.ly
0
0
0
0
0
0
0
0
0
0
0
.01-.05y
0
0
0
0
0
0
0
0
0
0
0
-------
-Fa
tn
i
RAPS - TASK 56 PARTICULATE INVENTORY:
CONTROL DEVICE/METHOD
No Equipment
Net Scrubber: high efficiency
med. efficiency
low efficiency
Centrifugal Collector: high eff.
med. eff.
Elec. Precipitator: high eff.
med. eff.
low eff.
Fabric Filter: high temp.
: EFCNtt
r-FILE
DEVICE ID PARTICLE
000
001
002
003
007
008
010
on
012
016
3-7y 1-3y
0 0
.9997 .91
.98 .79
.90 .69
.68 .43
.44 .17
.991 .984
.93 .89
.90 .75
.9999 .995
SIZE RANGE
.5-1y
0
.74
.57
.39
.18
.03
.977
.83
.60
.982
.1-.5y
0
.38
.26
.14
.06
.01
.962
.71
.45
.967
1/1
.05-.ly
0
.08
.05
.01
0
0
.945
.59
.22
.958
.01-05y
0
.02
0
0
0
0
.918
.45
.12
.956
-------
TEC: 'NICAL REPORT DATA
(Please read IiiitniL lions on the reverse before completing)
1. REPORT NO.
EPA-600/4-77-017
2.
3. RECIPIENT'S \CCESSION-NO.
4. TITLE AND SUBTITLE
REGIONAL AIR POLLUTION STUDY
Sulfur Compounds and Particulate Size Distribution
Inventory
5. REPORT DATE
April 1977
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO.
Fred Littman, Robert W. Griscom, and Harry Wang
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Air Monitoring Center
Rockwell International
11640 Administration Drive
Creve Coeur, MO 63141
10. PROGRAM ELEMENT NO.
1AA603
11. CONTRACT/GRANT NO.
68-02-1081
Task Order 56
12. SPONSORING AGENCY NAME AND ADDRESS
Environmental Sciences Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, N.C. 27711
- RTP, NC
13. TYPE OF REPORT AND PERIOD COVERED
Final
14. SPONSORING AGENCY CODE
EPA/600/09
15. SUPPLEMENTARY NOTES
16. ABSTRACT
In conjunction with the Regional Air Pollution Study being conducted in
the St. Louis Air Quality Control Region (AQCR), a methodology for estimating the
amount of sulfur trioxide (SO ) emitted by combustion sources was developed. It
is based on SO /SO ratios determined both experimentally and from literature
surveys. Th~ most likely value appears to be 1.85% of the SO,, emissions. On
?h~ most l:,kely value appears to be 1.85% of the SO emissions.
this basis, about 22,000 tons of SO are emitted yearly from combustion sources
A fine particle size inventory for the area was also developed. The inventory
gives a breakdown of particulate emissions in the range of 7 to .01 microns,
based on production rates and collection efficiencies for point sources in the
St. Louis AQCR. The information on the SO /SO ratios and the particle size
breakdown is stored in the RAPS Data Handling System.
17.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b. IDENTIFIERS/OPEN ENDED TERMS C. COSATI Field/Group
*Air pollution
*Sulfur tiroxide
*Particle size distribution
*Estimates
*Environmental surveys
St. Louis, MO
13B
07B
05J
13. DISTRIBUTION STATEMENT
RELEASE TO PUBLIC
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54
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EPA Form 2220-1 (9-73)
46
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